Table of Contents:



INTRODUCTION

This document describes the progress of our research under NASA Grant NAGW-2686, "Global Water Cycle: Extension Across the Earth Sciences" during the period November, 1993 - October, 1994. The "Near Term Objectives" of the original Work Plan (p. 67-87) and the key tasks listed in the "Near Term Research Priorities, Supplement to the Work Plan for Confirmation" (February, 1991) describe FY91, FY92, FY93, and FY94 research plans. We have keyed the sections in this document to the detailed research objectives listed below. The Susquehanna River Basin Experiment (SRBEX) focuses five of our original objectives in a regional experiment. Progress on this element of our research program is reported in a combined section.




OBJECTIVES

  1. Evaluation of GCM capability to simulate hydrologic cycle components

  2. Development of standardized model products

  3. Evaluate GCM sensitivity to lower boundary forcing

  4. Generation of global data sets for documentation of global change, specifically for hydrologic variables, and for global model validation and verification

  5. Development and testing of components of an atmospheric model of the regional hydrologic cycle

  6. Testing the adaptability of hydrologic models for sensitivity to spatial and topographic scales

  7. Test methodologies for indirect measurement of soil water content and integrate results into mesoscale model simulations

  8. Development of a comprehensive database and GIS for the Susquehanna River Basin to facilitate the development and evaluation of the nested model approach to regional prediction

  9. Development of a comprehensive database and GIS for the Cape Region in E. Central Florida in order to better understand process coupling between the land and atmosphere in a subtropical summer environment.

  10. Determination of ice sheet mass balance

  11. Development of a landscape evolution model

  12. Climate - Agriculture Modeling




EOS CONTRIBUTIONS

1993-1994

Albrecht, B.A., 1993: Effects of precipitation on the thermodynamic structure of the trade wind boundary layer. J. Geophy. Res., 98, 7327-7337.

Albrecht, B.A., M.P. Jensen and W.J. Syrett, 1994: Marine boundary structure and fractional cloudiness. J. Geophy. Res. (Submitted)

Allen, M.R., C.T. Mutlow, G.M.C. Blumberg, J.R. Christy, R.T. McNider and D.T. Llewellyn-Jones, 1994: Global change detection. Nature, 370:24-25.

Baker, W.E., G.D. Emmitt, F.R. Robertson, R. Atlas, J. Molinari, D. Bowdle, J. Paegle, R.M. Hardesty, R. Menzies, T.N. Krishnamurti, R. Brown, M.J. Post, J. Anderson, A. Lorenc, D. Fitzjarrald, T. Miller, and J. McElroy, 1994: Lidar measured winds from space: An essential component for weather and climate prediction. Bull. Amer. Met. Soc. (Accepted).

Barron, E.J. and G.S. Jenkins, 1994a: General circulation model prediction of regional precipitation: The Susquehanna River Basin. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Barron, E.J. and G.S. Jenkins, 1994b: General circulation and regional climate model simulations over the eastern United States: Large scale to synoptic scale simulations for the Susquehanna River Basin Experiment. Glob. Planet. Chg. (To be Submitted)

Bluth, G.J.S. and L.R. Kump, 1994: Lithologic and climatologic controls of river chemistry. Geochimica et Cosmochimica Acta. 58:2341-2359.

Capehart, W.J. and T.N. Carlson, 1994a: A soil-water-budget model enhanced with remotely sensed observations to provide initial soil-water content for atmospheric prediction and terrestrial hydrology models. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Capehart, W.J. and T.N. Carlson, 1994b: Estimating near-surface soil moisture availability using a meteorologicially driven soil water profile model. J. Hydro. 160:1-20.

Capehart, W.J. and T.N. Carlson, 1994c: Estimation of surface moisture availability using a hydrological budget model aided by surface satellite observations and a soil vegetation atmosphere transfer scheme (SVAT). Proc. 21st AMS Con. on Ag. and Forest Met. and 11th Con. on Biomet. and Aerobiol.. March 7-11, 1994: San Diego, CA.

Carlson, T.N., O. Taconet, A. Vidal, R.R. Gillies, A. Olioso, and K. Humes, 1995: An overview of the Workshop on Thermal Remote Sensing held at La Londe les Maures, France. September 20-24, 1993: Remote Sens. Rev. (In Press).

Carlson, T.N., R.R. Gillies, and T.J. Schmugge, 1995: An interpretation of methodologies for indirect measurements of soil water content. Ag. Forest. Met. (Accepted).

Carlson, T.N., W.J. Capehart, and R.R. Gillies, 1995: A new look at the simplified method for remote sensing of daily evapotranspiration. (To be submitted to Remote Sens. Env.)

Carlson, T.N., R.R. Gillies, and E.M. Perry, 1994: A method to make use of thermal infrared temperature and NDVI measurements to infer soil water content and fractional vegetation cover. Remote Sens. Rev. 52:45-59.

Chen, J.P. and D. Lamb, 1994a: Simulation of cloud microphysical and chemical processes using a multicomponent framework. Part I: Description of the microphysical model. J. Atmos. Sci. 51:2613-2630.

Chen, J.P. and D. Lamb, 1994b: The theoretical basis for the parameterization of ice crystal habits: Growth by vapor deposition. J. Atmos. Sci. 51:1206-1221.

Christy, J.R. and J. Goodridge, 1995: Precision global temperatures from satellites and urban warming effects of non-satellite data. Atmos. Env. (Submitted)

Christy, J.R. and S.J. Drouilhet, Jr., 1994: Variability in daily, zonal mean lower-stratospheric temperatures. J. Climate, 1:106-120.

Christy, J.R. and R.T. McNider, 1994: Satellite greenhouse signal. Nature, 367:325.

Christy, J.R., R.W. Spencer and R.T. McNider, 1995: Reducing noise in the daily lower tropospheric global temperature data set. J. Climate, 8 (In Press).

Cohen, C. and F.R. Robertson, 1994: A numerical investigation of the relationship between cloud mass flux and precipitating ice in mesoscale convective systems. J. App. Met. (Submitted).

Crosson, W.L., C.E. Duchon, R. Raghavan and S.J. Goodman, 1994: Rainfall estimation for Central Florida using standard and probability matching method Z-R relationships applied to composite radar data. J. App. Met. (Submitted).

Duchon, C.E., T.M. Renkevens and W.L. Crosson, 1995: Estimation of daily area-average rainfall during the CaPE experiment in Central Florida. (Submitted).

Fitzjarrald, D., F. Robertson, E. Barron, J. Christy, D. Pollard, S. Thomson, 1995: The scale and persistence of soil mositure anomalies as simulated in a global model. Preprints of the Conference on Hydrology, AMS. Dallas, TX, January 15-20, 1995.

Frakes, B. and B. Yarnal, 1995a: The variable response of watersheds to synoptic forcing: The SRBEX results. Preprints of the Sixth Symposium on Global Change Studies. Dallas, TX, January 1995, American Meteorological Society, Boston, MA (in press).

Frakes, B. and B. Yarnal, 1995b: The variable response of differing-scale watersheds to synoptic forcing. Abstracts of the Annual Meeting of the Association of American Geographers. March 15-19, 1995, Association of American Geographers,Washington, DC (In Press).

Frakes, B. and B. Yarnal, 1994: Using synoptic climatology to define representative hydrologic events in the Susquehanna River basin. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Gillies, R.R. and T.N. Carlson, 1995a: Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into mesoscale prediction models. J. Appl. Met. (In Press).

Gillies, R. and T.N. Carlson, 1995b: A physically based land use scheme for use in the study of deforestation and urbanization. (To be submitted to Water Res. Bull.).

Gillies, R.R. and T.N. Carlson, 1994: An efficient method for incorporating remote multispectral measurements in land-surface models. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Gillies, R.R. and T.N. Carlson, 1994: A physically based modeling approach for including remotely sensed measurements in the study of land use change. Proc. Am. Water Resour. Assoc., Ann. Summer Symp. on Effects of Human-Induced Changes on Hydrologic Systems, Jackson Hole, WY. June 26-29, 1994: (Reviewed Paper).

Gillies, R.R., J. Cui, T.N. Carlson, W.P. Kustas, K.S. Kustas, 1995: Implications oof the NDVI and the surface radiant temperature relationship. AMS Con. on Hydrology, Dallas, TX. January, 1995 (Abstract Submitted).

Gillies, R.R., A. Olioso, and K.S. Humes (Eds.), 1995: Proc. of the Workshop on Thermal Remote Sensing over Vegetation. La Londe les Maures, France. September 20-24, 1993: (Remote Sensing Rev. and Ag. Forest Met.).

Gillies, R.R., J. Cui, T.N. Carlson, W.P. Kustas, and K.S. Humes, 1995: Verification of the triangle method for remotely derived surface energy fluxes. (To be submitted to J. Appl. Met.).

Hewitson, B.C. and R.G. Crane, 1994: Precipitation controls in Southern Mesico. In: "Neural Nets: Applications in Greography," Hewitson and Crane (editors). Kluwer Academic Publishers.

Jenkins, G.S. and E.J. Barron, 1994: Coupled general circulation and mesoscale simulations over the Susquehanna River Basin. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Johnson, D.L. and A.C. Miller, 1994: A hydrologic model for use with rasterized data. Proc. Am. Water Resour. Assoc., Ann. Summer Symp. on Effects of Human-Induced Changes on Hydrologic Systems, Jackson Hole, WY. June 26-29, 1994: (Reviewed Paper).

Johnson, D.L. and A.C. Miller, 1994: A hydrologic model for use with rasterized data. Proc. HYDROVISIONS 1994 Summer Con., Phoenix, AZ.

Johnson, D.L. and A.C. Miller, 1994: A terrestrial hydrologic model for use with rasterized data sets. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Johnson, D.L. and A.C. Miller, 1994: Application of GIS to a raster based hydrologic model. 2nd Ann. Penn. GIS Con. March, 1994: Harrisburg, PA.

Johnson, D.L. and A.C. Miller, 1994: Hydrologic improvements for practicing engineer - Where is hydrology headed? Invited presentation and published proceedings of the the 1994 Aldon Res. Lab. Innovations in Elec. Power Ind. Con., August 1994:

Kapsner, W.R, 1994: Response of snow accumulation to temperature variations in central Greenland. M.S. Thesis. The Pennsylvania State University, University Park, PA.

Kapsner, W.R, 1993: Response of snow accumulation to temperature variations in Central Greenland. Trans. Am. Geophys. Union., San Francisco, CA.

Kapsner, W.R., R.B. Alley, C.A. Shuman, S. Anandakrishnan, P.M. Grootes, D.A. Meese and A.J. Gow, 1994: Dominant influence of atmospheric circulation on snow accumulation in Greenland over the past 18,000 years. Nature. (In Review).

Karl, T.R., R.W. Knight and J.R. Christy, 1994: Global and hemispheric temperature trends: Uncertainties related to inadequate spatial sampling. J. Climate, 7:1144-1163.

Lakhtakia, M.N, 1994: The application of a mesoscale model to downscaling. Invited Presentation at the Biospheric Aspects of the Hydrologic Cycle (BAHC) Focus 4 Workshop on Downscaling Methods. June 26-28, 1994: Karlsruhe, Germany.

Lakhtakia, M.N. and D.A. Miller, 1995: The role of the USGS-EDC land-cover characteristics database in the NASA-EOS interdisciplinary study at Penn State. Ecol. Appl. (Submitted).

Lakhtakia, M.N. and D.A. Miller, 1994: On the initialization of surface variables in mesoscale atmospheric models used in hydrologic balance studies. International GCIP/MAGS Workshop on Scaling in Hydrometeorological/Hydrologic Processes and Models, Victoria, British Columbia, Canada, September 19-23 (abstract to be published).

Lakhtakia, M.N. and T.T. Warner, 1994: A comparison of simple and complex treatments of surface hydrology and thermodynamics suitable for mesoscale atmospheric models. Mon. Wea. Rev. 122:880-896.

Lakhtakia, M.N., D.A. Miller, R.A. White and C.B. Smith, 1995: GIS as an integrative tool in climate and hydrology modeling. Proceedings of the 2nd Conference/Workshop on Integrating Geographic Information Systems and Environmental Modeling, Breckenridge, Colorado, September 26-30, 1993, (reviewed paper).

Lakhtakia, M.N., A.M. Lario, and T.N. Carlson, 1994: Initialization of soil-water content for real-time simulations with the Penn State/NCAR Mesoscale Model. Preprints 10th Con. on Num. Weath. Pred. July 18-22, 1994, Portland, OR. pp. 428-429.

Lakhtakia, M.N., C.B. Smith, T.N. Carlson, W.J. Capehart, and A.M. Lario, 1994: Initialization of soil-water content for regional-scale atmospheric prediction models. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Lamb, D. and J.P. Chen, 1995: An expanded parameterization of the growth of ice crystals by vapor deposition. In: Preprints, AMS Con. on Cloud Physics. Dallas, TX. January 15-20, 1995:

Lukhele, D.M., 1994: Physical infiltration models and the use of STATSGO soils data base for estimating model parameters. M.S. Thesis, The Pennsylvania State University, Univ. Park, PA.

Lukhele, D., A.C. Miller and D.L. Johnson, 1994: Estimating parameters for infiltration models utilizing STATSGO data. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Mace, G.G., D.O'C. Starr, T.P. Ackerman and P. Minnis, 1994: Examination of coupling between an upper tropospheric cloud system and synoptic scale dynamics diagnosed from wind profiler and radiosonde data. J. Atmos. Sci. (Accepted for publication)

McGinnis, D.L., 1994: Predicting snowfall from synoptic circulation: A comparison of linear regression and neural network methodologies. In: "Neural Nets: Applications in Geography," Hewitson and Crane (editors). Kluwer Academic Publishers.

Miller, A.C. and D.L. Johnson, 1994: Using spatial data structures in a raster based hydrologic model. Series of 3 invited presentations to EPRI, FERC, and ASDO in Marlboro, MA. Feb.- May, 1994:

Miller, D.A. and M.N. Lakhtakia, 1994a: Quantification of soil hydraulic properties for a regional-scale atmospheric prediction model. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Miller, D.A. and M.N. Lakhtakia, 1994b: Quantification of soil physical and hydraulic properties for regional atmospheric modeling. Preprints 10th Con. on Num. Weath. Pred. July 18-22, 1994, Portland, OR. pp. J12-J13.

Miller, D.A., G.W. Petersen, and M.N. Lakhtakia, 1994: Using the State Soil Geographic Database (STATSGO) for regional atmospheric modeling. Poster. Ann. Meet. Soil Science Soc. Amer., November 13-17, 1994: Seattle, WA.

Nizeyimana, E., D.A. Miller, and T.W. Gardner, 1994: Techniques to derive input soil parameters for terrestrial hydrology models from the STATSGO database. Invited Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Peuquet, D.J, 1994: An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographic data. Annual National Meeting of the Association of American Geographers, San Francisco, CA.

Peuquet, D.J, 1994: It's About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems. An. Assoc. Amer. Geog. 84:441-461.

Peuquet, D.J, 1993: A framework for the representation of spatiotemporal processes in geographic information systems. In: Proc. International Workshop on an Infrastructure for Temporal Databases, Arlington, TX. Section CC. 21pp.

Peuquet, D.J, 1993: What, Where and When - A conceptual basis for design of spatiotemporal databases. In: Proc. Workshop on Advances in Geographic Information Systems, in conjunction with Conference on Information and Knowledge Management, Association for Computing Machinery, Washington, DC.

Peuquet, D.J. and N. Duan, 1994: An Event-Based Spatio-Temporal Data Model (ESTDM) for Temporal Analysis of Geographic Data. Intl. J. Geog. Infor. Sys. (In Press).

Peuquet, D. J. and E. Wentz, 1994: An approach for time-based analysis of spatiotemporal data. Proc. Sixth International Symposium on Spatial Data Handling, Edinburgh, Scotland.

Richards, P.A. and L.R. Kump, 1994a: Scale dependence of chemical erosion rates in the field: Results from the Susquehanna River Basin, Northeastern United States. Abstract. Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Richards, P.A. and L.R. Kump, 1994b: The effects of watershed scale, lithology, and land use on weathering fluxes in the Susquehanna River Basin. Hydro. Proc. (Submitted).

Robertson, F.R. and E.W. McCaul, 1994: Large scale structure of water vapor and condensate over the TOGA COARE Region. 6th AMS Conference on Climate Variations, Nashville, TN, January 23-28, 1994:

Shuman, C.A., R.B. Alley, S. Anandakrishnan, and C.R. Stearns, 1994a: An empirical technique for estimating near-surface air temperatures in central Greenland from SSM/I brightnesss temperatures. Remote Sens. Env. (In Press).

Shuman, C.A., R.B. Alley, S. Anandakrishnan, J.W.C. White, P.M.Grootes and C.R. Stearns, 1994b: Temperature and accumulation at the Greenland Summit: Comparison of high-resolution isotope profiles and satellite passive microwave brightness temperature trends. J. Geophys. Res. (In Review).

Slingerland, R., J. W. Harbaugh, and K.P. Furlong, 1994: Simulating clastic sedimentary basins. Prentice-Hall, Inc., Englewood Cliffs, NJ. 220 p. (Chapter 3, Denudation of Source Terrains).

Smith, C.B., M.N. Lakhtakia, W.J. Capehart, and T.N. Carlson, 1994: Initialization of soil-water content in regional-scale atmospheric prediction models. Bull. Amer. Met. Soc. 75:585-593.

Spencer, R.W., W.M. Lapenta, and F.R. Robertson, 1994: Vorticity and vertical motions diagnosed from satellite deep layer temperatures. Mon. Wea. Rev. (Accepted).

Spencer, R.W. and J.R. Christy, 1993: Precision lower stratospheric temperature monitoring with the MSU: Technique, validation and results 1979-1991. J. Climate, 6:1191-1204.

Syrett, W.J., B.A. Albrecht and E.E. Clothiaux, 1994: Vertical cloud structure in a midlatitude cyclone from a 94 GHz radar. Mon. Wea. Rev. (Submitted)

Tucker, G.E. and R. Slingerland, 1994: Erosional dynamics, flexural isostasy, and long-lived escarpments: A numerical modeling study. J. Geophys. Res. 99,B6:12229-12243.

Wang, S., 1994: An application of Tiedtke's prognostic cloud scheme in a simple mass-flux boundary layer model. Mon. Wea. Rev. (To Be Submitted).

Wang, S. and Q. Wang, 1994: Roles of drizzle in a one-dimensional third-order turbulence closure model of the nocturnal stratus-topped marine boundary layer. J. Atmos. Sci., 51:1559-1576.

Wang, S., B.A. Albrecht and P. Minnis, 1993: A regional simulation of marine boundary-layer clouds. J. Atmos. Sci., 50:4022-4043.

Yarnal, B, 1994a: Policy relevance of the Susquehanna River Basin Experiment. Abstract, Spring Meeting of the American Geophysical Union, Baltimore, Maryland, May 23-27.

Yarnal, B., 1994b: The policy relevance of Global Environmental Change Research. The case of the Susquehanna River Basin Experiment. Glob. Planet. Chg. (Submitted).

Yarnal, B, 1993: Synoptic Climatology in Environmental Analysis, Belhaven Press, London.

Yarnal, B, 1992: Human dimensions of global environmental changes in the Susquehanna River Basin: A call for research. Penn. Geog. XXX, 2:19-34.

Yarnal, B. and J.D. Draves, 1993: A synoptic climatology of stream flow and acidity. Cli. Res. 2:193-202.

Yarnal, B. and J. Frick, 1995: Atlas of the Northeast United States' Synoptic Climatology and Climatic Variation. Northeast Regional Climate Center, Ithica, NY (in preparation).




RESEARCH ELEMENTS



Global Circulation Modeling (Objectives 1, 2, 3, 4)
(E. Barron, R. Crane, F. Robertson, J. Christy, and D. Fitzjarrald)



GENESIS

During the past year we have participated with D. Pollard, NCAR, in the development of the new version of the GENESIS climate GCM, which will operate at higher resolution (T31 or T42 in the atmosphere), coupled with an improved LSX land surface exchange model (2deg by 2deg with 6 vertical layers), and will eventually be coupled with a dynamic ocean model. As the tuning of this improved model is taking longer than anticipated, we have obtained an interim version, also run at T31 resolution. We are using this interim version to become familiar with aspects of the new model that will effect simulations of hydrological variables, particularly the improved resolution. We have made a simulation to investigate the diurnal variability of upper tropospheric temperature and moisture, and have initiated a run to investigate the effect of stratus cloud formulation on soil moisture in North America.


GENESIS Sensitivity to SST Anomalies

We have continued the analysis of the hydrologic response in Genesis GCM simulations that were forced by observed SST's. The 10 year control run forced by climatological SST has been compared with the 10 year run forced by the observed SST's (AMIP data set). Of particular interest in this study are the scale and persistence of soil moisture anomalies, and their feedback to the climate, particularly to the rainfall. The results show strong correlations between the SST forcing and soil moisture in sensitive areas of the globe, for example, the Sahel. One month lagged autocorrelations of soil moisture indicate an interesting minimum across the Americas and Eurasia. This area will be a prime target of study, since it represents an area of high variation due to the storm tracks, indicating the region to study for soil moisture-climate feedbacks.

We have also compared a full suite of GCM experiments (prescribed AMIP SST, Climatologic SST, T42 vs. R15, mixed layer) to analyze precipitation for the continental U.S. (Barron and Jenkins, 1994b; see SRBEX discussion).


Large-Scale Modeling of Boundary Layer Clouds

Use of Prognostic Method to Define Boundary-Layer Cloud Variables (S. Wang)

Shouping Wang (IGCRE, NASA/MSFC) has modified Tiedke's prognostic cloud scheme and implemented it in a two-layer boundary-layer model. In this cloud scheme, the cloud fraction and mean liquid water are predicted by a balance among convective mixing, evaporation, cloud-top entrainment and large-scale condensation. The convective mixing term is the detrainment of liquid water from updrafts. This model was used to simulate downstream evolution of marine boundary layer clouds from cold ocean surfaces to warm ocean surfaces. Over the cold ocean surfaces, the cloud and subcloud layers are closely coupled, and the mass flux is strong, which gives a strong liquid water detrainment from updrafts. Therefore cloud fraction is close to 100% over cold oceans. Toward warm oceans, the boundary layer tends to be decoupled, and thus the cloud-base mass flux decreases, which leads to a weak mass flux detrainment in the cloud layer. In addition, the environment becomes unsaturated due to a strong cloud-top entrainment. Therefore the cloud fraction is only 30% over the warm ocean. These results show that the prognostic cloud scheme coupled with a mass-flux convective mixing scheme provides a good framework for the parameterization of marine boundary-layer clouds in a large-scale model.

The prognostic cloud scheme is very sensitive to the details of the convective mixing scheme used, since mass flux and updraft liquid water content critically define the budgets of both cloud fraction and liquid water content. This work is being summarized in the paper by Wang (1994).


Simulation of Low-Level Clouds with the GENESIS Climate Model (S. Wang)

The goal of this study is to determine (1) how realistic the model represents boundary-layer clouds and (2) what physical processes produce the simulated clouds and their variabilities. As the first step of this study, the model results were compared with both satellite and surface observations. The simulated global distribution of annual mean of the cloud cover is comparable with the observations. Seasonal variations of the cloud over some locations are poorly represented by the model. Presently, we are trying to determine what the causes of these discrepancies are.


Global Data Sets for Earth System Change Documentation

Integrated Water Vapor and Condensate Analysis (F. Robertson)

One of the key challenges for EOS is to synthesize an integrated understanding of how the atmospheric water and energy balances couple to determine thermodynamic, dynamic, and biogeochemical character of climate, its variability, and potential for change. An essential step in this direction is to improve the observational estimates of the mass transport of atmospheric water vapor, its transformation to and from condensate, and its boundary fluxes as precipitation and evaporation. We have been developing an analysis technique that combines dynamics from large-scale analyses, parameterized moist physics, and satellite-derived moisture constrains to generate consistent diagnostics of the atmospheric hydrologic cycle. This analysis is proving useful to: (1) recover large-scale 3-D/time structure of vapor, condensate and precipitation, (2) obtain vertical profiles of LHR, evaporation, melting, (3) serve as a testbed for convective and cloud parameterization, and (4) provide a basis to explore how best to use remotely-sensed data as an analysis constraint.

A unique aspect of this study is a semi-prognostic approach whereby remotely-sensed moisture data are assimilated into an evolving analysis. Wind and temperature fields from global gridded analyses, (e.g. GSFC, NMC or ECMWF reanalyses) are used to drive predictive equations for water vapor, condensate, and precipitation. In addition to transport processes, parameterized bulk microphysics and moist convection affect the distribution of water substance. The incorporation of remotely-sensed water vapor is accomplished by a nudging procedure which updates the evolving water vapor field and constrains it to observations. This semi-prognostic approach differs from 4-DDA in several ways: (1) only these moisture fields are prognosed, (2) it is much less computationally expensive so many experiments with differing moist physics can be done. In fact it can serve as a testbed for future 4-DDA model convective and cloud parameterizations, (3) current reanalysis efforts do not include explicit simulation of cloud water or ice.

This year we have implemented diagnostics which allow us to estimate vertical motion, moisture, and condensate transports associated with convection and with other subgrid-scale clouds. This allows us to now study the ice budget of tropical regions and to determine the extent to which detrained convective condensate is controlling the upper-tropospheric water vapor balance. We have been diagnosing the TOGA-COARE period of Nov. 1992 - Jan. 1993 (Robertson and McCaul, 1994) and have been able to reproduce the observed upper-level cloudiness field (Fig. 1) which has such a strong effect on cloud radiative forcing in the western Pacific.


SSM/I Precipitating Ice as Signatures of Convective/Mesoscale Vertical Mass Flux (F. Robertson)

Vertical mass flux within organized deep convection has long been recognized as crucial agent in the global hydrologic and energy cycles by virtue of its vertical transport of heat, moisture, and momentum. Nevertheless, quantitative measures of this variable remain quite elusive as does any reliable measure of variability.

Intuitively, the connection between cloud updraft strength and the extent of precipitation and cloudiness produced is quite strong, condensate being produced when moist air parcels are lifted beyond their saturation level. In our work this year we have sought to clarify the physical basis for the relationship between kinematics and condensate and inquired to what extent this relationship might be quantified: To what degree can observations of precipitating ice be interpreted as bulk cloudscale and mesoscale vertical mass flux? A series of experiments with the RAMS cloud ensemble model have revealed the following:

  1. Within convection and mesoscale cloud systems, the ratio of precipitating ice to vertically-integrated updraft and net mass fluxes between the freezing level and cloud top is sensitive to the in-cloud water vapor mixing ratio at the freezing level. Colder atmospheres thus show less ice production for a given amount of integrated updraft only and net mass flux. This effect has by far the most impact on relationships between ice and vertical mass fluxes. Notably, one might expect the in-cloud water vapor mixing ratio estimated by simple parcel theory to be quite accurate in most situations.

  2. In this 2-D model, cloudy downdrafts at upper levels are a pervasive and largely stable fraction of the updraft mass flux.

  3. Large changes in the ratio of graupel to total ice do not produce large changes in the ice mass to vertical mass flux relationship.

  4. Sensitivity to vertical wind shear is present but small in these 2-D simulations with net cloud mass flux/ice ratios varying by approximately 10% in the three different shears examined for maritime and continental clouds.

These consistent, repeatable patterns in the ratios of ice to integrated vertical mass fluxes, and the fact that differences between experiments are related to gross thermodynamics of the environmental sounding are encouraging. Our results to date using a 2-D numerical cloud model suggest that this relationship is strong enough to warrant development of algorithms to relate ice as detected by the SSM/I and Microwave Sounding Unit (MSU) sensors to upper-tropospheric cloud mass flux. We are currently pursuing this.


Lower Stratospheric Temperature (J.R. Christy)

Considerable research has been carried out in understanding the precision of the MSU instrument, especially in the lower tropospheric measurements. The orbital drift of NOAA-11 caused a spurious warming trend in those data which have now been identified, documented and corrected. The global and regional temperatures provided from the MSU are used in a wide variety of research, much of which looks at the detection of global climate change.

Christy has participated as a key contributor on IPCC 1994 and 1995 deliberations as well as other less prominent conferences in assessing the state of the climate. MSU data are/will be featured in these reports concerning climate observations for monitoring global change. Temperature is inextricably linked to the hydrologic cycle and is thus critical for hydrologic studies.


Validation of Synoptic-Scale GCM Circulation (Robert Crane and Bruce Hewitson)

The dominant theme of the ESSC EOS project is to develop techniques that will allow us to make valid assessments of the regional hydrologic response to global environmental change. One approach that we have adopted is to nest higher resolution regional models within a global climate model, and the first step in this progression is to nest the Penn State/NCAR mesoscale model within GENESIS. Earlier case studies with the mesoscale model have shown that the sensitivity of the model to local environmental factors (e.g., soils and vegetation) depends on the synoptic conditions. As one might expect, local factors play a greater role with slow moving systems, and they are less important when the systems move rapidly through the region. As we can expect the mesoscale model to behave differently under various synoptic conditions, and as we ultimately wish to run this model in a climate mode, driven with GCM output, then it is important that the GCM (GENESIS) produces an accurate simulation of the synoptic-scale circulation. The objective of this part of the project, therefore, is to assess the synoptic-scale performance of GENESIS.


Synoptic-Scale Validation

Validation in this context takes two forms: one is a simple comparison of the spatial and temporal characteristics of the synoptic-scale circulation of the model, while the other one examines observed relationships between the synoptic-scale circulation and local climate (temperature and precipitation) and determines whether those same relationships are present in the simulated climate of the GCM. This work began with earlier NASA funding that examined the synoptic-scale circulation of the 8x10 GISS model and the relationships between circulation and temperature over the United States. Under EOS funding we have also examined the relationships between the large-scale circulation and rainfall in tropical Mexico. The results from both studies were outlined in previous EOS reports, and recent publications are attached. The focus since the last report has been on relationships between circulation and snowfall in the Colorado Basin, and, more recently, on the synoptic-scale circulation over the eastern U.S. in the GENESIS model. Tropical Mexico and the Colorado Basin are regions that represent two very different precipitation regimes; the objective was to establish that the techniques we have developed are valid for a wide range of environments before applying them to the Susquehanna River Basin as part of SRBEX.

Colorado Basin Snowfall: The rotated Principal Components of the wintertime daily 700mb height fields are used as an index of the synoptic-scale circulation, and transfer functions between the circulation and snowfall are derived using neural networks. Three components are obtained that explain 93% of the variance in the 700mb flow. The snowfall data were obtained from the Soil Conservation Service Snow Telemetry (SNOTEL) automated recording stations. SNOTEL sites in the upper Colorado Basin are grouped according to their temporal similarities, resulting in five groups of stations, and neural nets are used to predict the mean daily snowfall for the group as a function of the synoptic circulation. The neural net is a simple feed-forward back-propagation of error network that uses a four-day lagged sequence of synoptic data (component scores) to predict the snowfall on the last day. The correlations between the observed and the neural-net predicted snowfall range from 0.80 to 0.88; for the region as a whole we find that 70% of the variance in the daily snowfall data can be accounted for by the synoptic circulation (McGinnis, 1994).

Synoptic Circulation in GENESIS: The output from the present-day simulation runs at Penn State are archived as monthly averages; our analysis requires daily data and our first task was to reprocess the history tapes to derive daily grids. As part of this project and an ongoing DOE CHAAMP project, we have produced ten years of daily data for the present-day control run (R15 resolution, mixed-layer ocean with parameterized latitudinal ocean heat fluxes), and three years from a doubled CO2 experiment. We are in the process of extracting the daily data for the AMIP run (present-day simulation driven with 10 years of observed sea-surface temperatures).

The mean January sea-level pressure distributions from the NMC data and the ten year simulation of the GENESIS GCM are shown for the eastern U.S. in Figure 2a. The observed and modelled fields show similar patterns, but the model has pressures that are 4mb to 14mb too low; the differences being greater in the north-east than south-west, resulting in pressure gradients that are much steeper in the model. A slightly larger window shows that the Icelandic Low appears to be displaced south and west in the model (being located south of Greenland). The NMC data also show a closed high pressure cell over the eastern U.S. with pressure increasing to the south-west, while the model shows a more zonal distribution with the high pressure cell being elongated east-west and again being displaced to the south. The implication is that the winter circulation is more intense in the model, and that the circulation features are displaced equatorward.

Principal components analysis results in five components for both data sets; there is very close agreement between the components (Table 1, Figure 3). The lowest overall correlations between matching NMC and GENESIS components are between NMC Component One and GENESIS Component Two, and NMC Component Five and GENESIS Component Four. These two pairs of components represent variance in the north-east and south-east parts of the region respectively, and reflect the areas of greatest difference in the mean sea-level pressure maps. Note also that all of the matching pairs of components show lower correlations in their north-south gradients. The results show that the patterns of spatial variance are very similar in the two data sets, although the GENESIS patterns do appear to be displaced southward.



Table 1:  Correlation Coefficients between the NMC and GENESIS
Components.  The correlations are carried out on a grid-point by grid-point
basis, and by correlating the north-south and east-west gradients at each
grid-point.  The  average” column is the average of the three different
calculations.

NMC GENESIS grid-point to north-south east-west Components Components average grid-point gradient gradient 1 2 0.84 0.97 0.67 0.88 2 1 0.93 0.98 0.87 0.95 3 5 0.94 0.97 0.88 0.97 4 3 0.92 0.97 0.82 0.98 5 4 0.91 0.97 0.83 0.93

Two-dimensional frequency histograms are constructed for each component. One dimension of the histogram represents the frequency distribution of the component scores, the second dimension is the frequency distribution of change from one day to the next. In other words, for every frequency class the histograms show how the scores change the next day. The histograms for each matching pair of components are almost identical, showing that the temporal behavior of the components is also very similar for the modelled and the observed data. As a further check, the standard deviations of the daily pressure at each grid-point are plotted in Figure 2b. The modelled and the observed data are very similar. Both data sets show the same variability, again indicating that the day-to-day variability in the model is very realistic.

The analysis shows that, in some respects, the January synoptic-scale circulation of the GENESIS model is very realistic over the eastern U.S. Although the GCM features are displaced south by about five degrees, and actual pressures in the model are much lower than observed, the model does show synoptic-scale features that are similar to the observed patterns, and have day-to-day changes that match the observed variability at each grid-point. From the perspective of driving the mesoscale model with GENESIS output, if the daily pressure maps were presented as daily departures from the January mean, there would be almost no difference between the observed and modelled circulations.

In the next stage of the project we will use the neural-net techniques that were developed for Mexico and the Colorado Basin, to examine the relationships between circulation and local temperature and precipitation over the Susquehanna River Basin, and compare these analyses with the fields produced by both GENESIS and the mesoscale model.



Mesoscale Modeling (Objective 5)
(T. Ackerman, B. Albrecht, D. Lamb)


Improved Treatment of Cloud and Precipitation Processes

Generalized technique for using observations to test parameterizations
(T. Ackerman and G. Mace (unfunded investigator)).

The representation of clouds in models of the global climate is widely recognized as a significant shortcoming in our ability to predict future climate change. One of the foremost difficulties in the cloud parameterization problem is rigorously verifying the results of present parameterizations so that they can be improved. Current methods concentrate on comparing satellite observations with model output and suffer from an inability to examine such fundamental parameters as cloud base, cloud top for thin clouds and internal cloud structure. We have developed a hierarchy of techniques that essentially divorces the parameterization from the parent model and drives the parameterization with data. The output from the cloud parameterization is then compared with observables including cloud radar and lidar data and surface- based and satellite-based observations of radiative flux. This technique, outlined in Mace et al. (1994), is being used to verify a suite of GCM cloud and radiation parameterizations against observations collected during the NASA FIRE Cirrus II field campaign, at the Department of Energy's Cloud and Radiation Testbed site, and at our field site in central Pennsylvania. This technique has distinct advantages beyond the simple intercomparison of parameterization output, however, since it provides a direct link between the multiple scales important to the parameterization problem. At the smallest scales, those on which individual cloud elements are maintained, cloud radar and lidar observations and instantaneous radiative flux data provide a direct link between cloud process models and nonhydrostatic mesoscale models where explicit representation of cloud processes can be included. The coupling between the meso and GCM scales is then clearly defined since the GCM parameterization results can be examined against the smaller scale model output. In this way our understanding of scale interaction is improved and the coupling between cloud processes and climate can be more faithfully represented in global models.


Marine Boundary Layer Structure and Fractional Cloudiness (B. Albrecht)

We have characterized the structure of the marine boundary layer using extensive sets of soundings that were collected during the past several years over the tropics and the subtropics during FIRE, ASTEX and TIWE. A total of approximately 300 soundings from four different locations were used to produce composite structures of the temperature and moisture of the marine boundary layer. Average sea-surface temperatures for these four data sets vary from 16-27 oC. A unique aspect of these data sets is that fractional cloudiness from each site can be quantitatively estimated using laser ceilometers operated from the four sites. The average cloudiness for these four data sets ranges from nearly solid stratocumulus (fractional cloudiness of 0.83) to classic broken trade-cumulus conditions (fractional cloudiness of 0.26). The composite soundings were used to evaluate model parameterizations that represent fractional cloudiness as a function of boundary layer structure. Parameterizations based on the relative humidity in the cloud layer show better agreement with the observations than those that attempt to account for the effects of cloud-top entrainment instability on fractional cloudiness. These results are discussed in Albrecht et al. (1994). We plan to use the composite boundary layer and fractional cloudiness data sets to test the generalized boundary layer model that was developed under previous EOS support (Wang et al., 1993).


Continental Stratus Clouds (B. Albrecht)

Continental stratus clouds substantially impact local climate by altering the surface radiation budget. Furthermore, if climate models are to realistically simulate continental temperatures and annual and diurnal temperature cycles, they must include the effects of boundary layer clouds. Representing boundary layer clouds in numerical models is at least as challenging as it is for marine stratocumulus. There is, however, a lack of observations of continental stratus. To overcome this deficiency, we are currently (under NSF support) using surface-based remote sensing systems (primarily a cloud radar, ceilometer, and microwave radiometer) to develop extensive characterizations of continental stratus. Although the focus of the NSF project is on the mechanisms responsible for the maintenance of these clouds, under EOS support we will use these data to develop and evaluate cloud parameterizations and evaluate the potential for using satellite data (EOS data eventually) to characterize these clouds. Based on our first month of observations, we have established that continental stratus clouds (unlike marine boundary layer clouds) are associated with a wide variety of meteorological conditions and have characteristics that vary substantially between cases. Furthermore, their vertical extent is generally quite limited. Thus even sophisticated mesoscale models may have difficulty in resolving these cloud features.



Cloud Microphysics Process Studies

The primary goal of our cloud microphysical studies has been to improve the representation of clouds in atmospheric models over various scales. Whereas the conditions for cloud formation are established on the meso- and synoptic scales in the atmosphere, all "excess" water vapor is transformed into cloud particles via microscale processes. These diverse scales interact in complicated ways, thus necessitating the use of detailed numerical modeling.

The general approach taken has therefore involved the development of process-oriented microphysical modeling. A detailed description of the microphysical model has been presented by Chen and Lamb (1994a). Unique features of this model include the use of a multicomponent categorization scheme, by which not only the masses of the cloud particles, but also their solute contents, can be grouped ("binned"). Various chemical attributes can thus be ascribed to the particles so that a proper treatment of cloud initiation on soluble particles (cloud condensation nuclei) and of cloud scavenging can be performed. Because the numerical scheme is general and the number of components is limited primarily by computer memory, the axial ratios of the particles can also be categorized. This feature allows us to "track" the shapes of nonspherical particles, such as occurs during the growth of the ice phase.

The ice phase is an important component of many clouds. Ice particles serve to initiate precipitation formation in many cases, and they are the dominant particle type in cirriform clouds. We have extended an empirical parameterization of the growth of individual ice crystals by the process of vapor deposition (Chen and Lamb, 1994b) in a way that allows the shapes of the ice crystals to change with time and with the environmental conditions. This "adaptive" parameterization thus allows the past histories of the particles to affect the future growth of the particles in a fairly realistic manner. Although the calculated growths of representative ice particles compare favorably with experimental results when the environment is saturated with respect to the liquid phase, as in supercooled clouds, a modification of the ice growth parameterization has been undertaken to allow for growth under a wide range of supersaturations (Lamb and Chen, 1995). This level of detail will be particularly important when trying to simulate cirriform clouds or the anvils of precipitating systems.



Susquehanna River Basin Experiment (SRBEX) (Objectives 5, 6, 7, 8, 11)
(E. Barron, T. Carlson, T. Gardner, L. Kump, A. Miller, G. Petersen, D. Peuquet, R. Slingerland, T. Warner, B.Yarnal)



Introduction

SRBEX is the first of several planned regional experiments which are to be undertaken in our EOS research program. The Susquehanna River Basin (SRB) is a 62,419 km2 watershed covering portions of New York, Pennsylvania, and Maryland (Figure 4). The overarching goals of SRBEX are to understand the hydrologic cycle of the basin through modeling and the analysis of observed data, and - as a result of this understanding - to develop capabilities for monitoring and projecting changes in basin hydrology (Yarnal, 1994a and 1994b). The reason for SRBEX is clear: Accurate projections mean that managers will be able (1) to lessen the impacts of variations in water quality and supply and (2) to optimize water resources. Thus, significant social and economic costs can be avoided, and benefits can be realized by the research efforts of SRBEX.

More specifically, SRBEX includes the following policy-relevant objectives:

  1. Identification of hydrologic parameters sensitive to climatic variation and change.

  2. Model experimentation to provide quantitative comparison of the hydrologic-system sensitivities to various natural and human forcing functions.

  3. Observational studies to provide the context for comparisons of natural versus human-induced variations.

Figures 5 and 6 summarized the SRBEX suite of databases, data sets and linked models. These models include: the GENESIS GCM, the Penn State/National Center for Atmospheric Research (NCAR) mesoscale model (MM), the Soil Hydrology Model (SHM), the Penn State University Biosphere-Atmosphere Model Scheme (PSUBAMS), the Terrestrial Hydrologic Model (THM), and the Water Quality Model (WQM). The linkages between the different models are under development and/or validation.

We have defined three tests of the linked-model strategy: a storm simulation, a multiple-event simulation, and a 2xCO2 simulation. For the first proposed test, we have chosen the storm event from 9-11 April 1980. This particular storm was chosen because it is a climatologically representative event for the northeastern U.S. We expect to have preliminary results from this storm simulation by the end of 1994. The multiple-event simulation will involve a seasonal simulation including several storm events and dry periods, and will take place in early 1995. We expect that the 2xCO2 simulation will take place in the second half of 1995. The outcome of each of these tests will result in the improvement of our models and their linkages.

In 1994 the SRBEX research group, which consists of approximately 15 faculty, staff and graduate students, continued the practice of regular meetings (approximately every 2 weeks) focused on building the model linkages and support infrastructure required to carry our research effort through the EOS launch date. This evolutionary process has opened new areas of interaction and synergism within our team. The following discussion of the SRBEX research elements elaborates on the relationships shown in Figures 3 and 4.



Gobal Circulation Model

A primary goal of SRBEX has been to link global-scale climate change to regional climate with a particular emphasis on the hydrologic components. The emphasis of this work is to compare statistics from a GCM (with horizontal grid spacing of ~ 500 km) and a regional-scale climate model (with horizontal grid spacing of ~ 100 km). This will provide the necessary framework to go to higher resolution (grid spacing < 50 km).

During the past year, two coupled GCM/regional scale simulations have been undertaken with the GENESIS GCM (Thompson and Pollard, 1994; Pollard and Thompson, 1994) and a mesoscale model (MM Version 4) which has been altered for climate studies. The altered version of the MM is known as the RegCM2 (Giorgi et al., 1993a; 1993b) and has been used in a number of climate studies. RegCM2 is driven at the lateral boundaries (outer 4 grid points) with meteorological fields (temperature, wind components, surface pressure and humidity) from the GENESIS GCM every 12 hours.

The GENESIS simulation was integrated for 10 years using observed sea-surface temperatures (the AMIP data set) for the 1979-1988 time period. The GENESIS GCM used a horizontal resolution of 4.5o of latitude by 7.5o of longitude and 12 vertical levels. It also uses a land-surface package (LSX) in which heat, momentum and moisture fluxes from the biosphere are computed on a horizontal grid with a resolution of 2o x 2o. A time period of six months (1 December 1979 through 1 June 1980) was used for the coupled GCM/RegCM2 simulations.

The primary focus of the RegCM2 simulations were on the Eastern U.S., since the SRB is the area of interest. A horizontal resolution of 108 km was used in both simulations along with 16 vertical levels. In the first simulation, the grid was centered at 41oN, 77oW (Central Pennsylvania). A total of 30 grid points are specified in the north-south, east-west directions. This places the western boundary of the RegCM2 grid in Kansas, the eastern boundary over the Western Atlantic, the Northern boundary over the Hudson Bay and the Southern boundary over Southern U.S..

Results from the model simulations were very fruitful and were presented at the American Geophysical Union Spring meeting in May, 1994. Some of the results include:

  1. The coupled RegCM2/GENESIS simulation produced more realistic synoptic-scale systems when compared to the GENESIS storms.

  2. When compared to observations over this six-month period however, both GENESIS and RegCM2 produced excessive precipitation.

  3. The largest biases were during the Spring months over much of the domain, and during the Winter months, both GENESIS and RegCM2 produced too excessive rainfall along the eastern seaboard compared to observations.

  4. Interior regions of the domain compared favorably to observations, but near the western boundary of the domain the model produced very little rainfall.

Observations show that December 1979 through February 1980 was a deficient rainfall period throughout much of the Eastern U.S., with the driest area over the Northeastern U.S. (Taubensee, 1980; Wagner, 1980; Dickson, 1980). Furthermore, during the month of January and February, most of the cyclones moved north of the U.S. border with no more than 10 crossing the Central U.S. or moving up the eastern seaboard. This was due in part to a strong ridge over the Western U.S. and nearly zonal flow over the Eastern U.S. during the winter months of 1980.

During the Winter season of the RegCM2/GENESIS simulation, the majority of synoptic features also tracked north of the U.S. border, but a greater number of cyclones tracked through the central U.S. and up the eastern seaboard as compared to the observations. Differences in the cyclone tracks can be explained by the different GENESIS storm track over North America when compared to observations. Because GENESIS drives the RegCM2, errors in the GENESIS simulations also occur within the RegCM2/GENESIS simulations (Giorgi et al., 1994). Favorable results occurred for an important Winter-season feature in the Eastern U.S.: the East-coast cyclogenesis. In several instances, we found that the coupled RegCM2/GENESIS simulation produced a more realistic cyclone compared to the stand-alone GENESIS simulation. Indeed in some cases, these East-coast cyclone produced snow conditions in the RegCM2/GENESIS simulation as compared to rain in the stand-alone GENESIS simulation.

During the Spring months of 1980, observations show that a high-pressure ridge developed over the Central U.S., causing below normal rainfall and drought in this region, and above normal precipitation elsewhere. During the same time period, both the GENESIS and GENESIS/RegCM2 simulations overestimate rainfall. This appears to be in agreement with biases in the 200 mb zonal wind field for GENESIS and the GENESIS/RegCM2 models when compared to ECMWF analyses over the U.S.. In particular, the magnitude of the 200 mb jet was often too strong by 5-20 m/s, and its position was often diffuse and extended over much of the continental U.S., when compared to a well defined jet in the ECMWF analyses.

The second GENESIS/RegCM2 simulation was performed using an expanded RegCM2 domain, that includes the entire continental U.S., parts of Southern Canada, the Eastern Pacific and the Gulf of Mexico. The purpose of this simulation was to study the effect of the lateral boundary conditions on the RegCM2 results. Once again, a horizontal grid spacing of 108 km was used in RegCM2, with the center of the grid being 40oN, 95oW (Kansas-Missouri border). A total of 42 grid points are specified in the north-south, and 60 in the west-east directions. This puts the western and eastern boundaries of the RegCM2 grid over the eastern Pacific and the Western Atlantic, and the northern and southern boundaries over central Canada and the Gulf of Mexico, respectively. This simulation was integrated over the same time period as the previously described RegCM2 simulation (1 Dec. 1979- 1 June 1980).

A comparison of GENESIS precipitation rates and the RegCM2 eastern U.S. domain simulation indicates that rainfall biases in GENESIS also occur in the coupled RegCM2 simulation (noted above). For example, in Figures 7b and 7c many of the overestimated rainfall amounts in GENESIS also appear in the Eastern U.S. RegCM2 domain, especially in the western part of the domain.

However, a comparison of Figures 7c and 7d shows that increasing the domain size reduces the rainfall biases when compared to the observations (Barron and Jenkins, 1994a). Furthermore, it was found that for all of the Spring months, a larger domain size reduced precipitation biases when compared to observations. The results suggest that in order to produce reasonable results over the SRB, a larger domain (preferable the size of the continental U.S.) should be used, with smaller domains nested within.

Finally, as a way of estimating the errors which are likely to occur in future simulations as a result of the GENESIS biases, we have completed an inter-comparison of all GENESIS simulations (T42 vs. R15, fixed AMIP SST, climatologic SST, mixed layer) to observed data (Barron and Jenkins, 1994b).

This seasonal inter-comparison for the eastern U.S. indicated:

  1. in all cases winter precipitation predictions compared more favorably to observations,

  2. knowledge of SSTs improved precipitation predictions,

  3. climatological SSTs predictions were largely similar to the AMIP predictions, and

  4. enhanced resolution of GENESIS did not produce a dramatic improvement in comparison with observations

Currently, summertime simulations with the GENESIS GCM driving the RegCM2 are underway, in order to test several cumulus parameterizations.



Synoptic Climatology of the SRB

SRBEX research in synoptic climatology had three foci in 1994:

  1. Determining representative circulation patterns and their hydrologic response;

  2. Establishing empirical relationships between the response of watersheds with differing scales and synoptic forcing;

  3. Developing techniques to monitor large-scale climatic variation.

First, the nested-modeling efforts assume that there is a strong causal relationship between the atmospheric circulation and the hydrologic response of the basin. Many of the simulations linking the atmosphere and basin hydrology rely on observed events believed to be typical. Yet no methodology has been developed to determine either the representativeness of the circulation patterns producing a significant hydrologic response, or the representativeness of the hydrologic response to a given storm system. In preliminary research, Yarnal and Draves (1993) used composite pressure patterns and storm tracks to show that the largest runoff events in the SRB may result from characteristic sequences of synoptic patterns. Consequently, Frakes and Yarnal (1994) developed a technique for determining unique circulation events and those storm patterns that typically produce a strong hydrologic response in the basin. These data can also be used to understand which hydrologic responses to a given circulation event are representative or not. The results suggest that synoptic climatology is a useful tool for defining model scenarios and model verification in global-change experiments.

Second, SRBEX seeks to identify how watersheds of differing scales respond to forcing by weather systems. For the observational component of this objective, Frakes and Yarnal (1995a and 1995b) related lagged sequences of daily synoptic weather types to discharge from several watersheds in the SRB. The results show that small basins respond to a large range of moisture-producing weather patterns over many time scales, while larger basins usually require a long string of wet days to generate a strong response. For some synoptic sequences, stronger responses were observed when the data were lagged; in other cases, lagging the data produced inferior results. These temporal differences can often be explained by physical characteristics of the weather patterns involved.

The third focus of the synoptic climatological research was to develop ways to monitor large-scale climatic variation over the SRB. Yarnal and Frick (1995) are creating a catalog of daily eigenvector-based synoptic map patterns, plus indices based on these patterns (Yarnal, 1993) for the period 1946-1994. Quarterly updates of the catalog will be available in hard copy and over the Internet starting in the last quarter of 1995. These data will be integral to developing long-range forecasts of basin climate and hydrology.



Penn State/NCAR Mesoscale Model

During the last year a number of model-development efforts have been underway that will enable the Penn State/NCAR Mesoscale Model (MM) to be used as a more effective tool for studies of regional climate change. Part of this effort involved the continued evaluation and improvement of the 5th generation of the MM (MM5) for a variety of meteorological situations. This model is nonhydrostatic, it allows for multiple movable nested domains, and it has a more sophisticated atmospheric hydrologic cycle, an improved atmospheric radiation scheme, and more efficient numerics to make longer-range simulations more tractable. It can be initialized with observed or synthetic atmospheric data and can be applied to any region on earth. Version 1 of MM5 was officially released for public use in February 1994. At that time, Mercedes Lakhtakia transfered the entire MM5 system (including pre- and post-processing programs) to ESSC, and made the necessary changes to run those programs on the ESSC CRAY YMP.

During this year Dr. Lakhtakia also introduced a modified version of the Biosphere-Atmosphere Transfer Scheme, or BATS, (Lakhtakia and Warner, 1994) into MM5, so that the latter can then be used as part of the SRBEX suite of models. Much emphasis has been put on the improvement of some of the variables/parameters within BATS that require initialization/specification. BATS requires the initialization of the soil-water content (SWC) and the specification of some surface characteristics. Routine SWC measurements over large areas (like the ones typically covered by regional NWP model domains) are unfeasible. Hence, climatological estimates of soil moisture are usually used to provide initial conditions for the models. This approach may result in large errors during periods of excessive rainfall or drought. In the absence of observations, an indirect method is needed to determine SWC fields from routine meteorological observations. This need for SWC initial conditions is being fulfilled by the Soil Hydrology Model (SHM) system (Smith et al., 1994).


Soil Hydrology Model (SHM) link with Mesoscale Model (MM)

The SHM, developed by Bill Capehart and Toby Carlson (Capehart and Carlson, 1994b), determines the temporal evolution of the SWC as a function of depth using a one-dimensional soil-water diffusion and gravitation scheme. The model also includes modules for infiltration, runoff, ponding and evaporation at the soil surface, transpiration and interception of rainwater by plant leaves, and underground runoff and removal by the root system of liquid water for transpiration. The SHM is driven by routine meteorological observations at the surface (i.e., the atmospheric forcing: air temperature, moisture and wind speed, as well as rainfall and cloud cover), and conventional topographic information, surface-cover parameters (vegetation type, vegetation fraction), and soils information (soil texture). The soil column depth, vertical grid spacing and the nature of the lower boundary (impermeable, permeable or saturated barrier) in the model are specified by the user.

The SHM is initialized with an arbitrary SWC profile, usually chosen to be 50% of saturation. The model, driven by the atmospheric forcing, converges toward a common solution regardless of the chosen initial SWC value. This convergence takes place over a balancing period that may range from several weeks to a few months, depending mostly upon the precipitation amounts.

A publication in the Bulletin of the American Meteorological Society (Smith et al., 1994) describes a system that uses the SHM to produce the SWC initial conditions for the MM. This system has two components: a method to analyze the meteorological information to the MM domain, resulting in the SHM atmospheric-forcing dataset, and the SHM itself. Once the atmospheric-forcing dataset is available, the SHM is applied to every pixel within the MM domain. The SHM has been modified for this work so that it has similar surface-characteristics requirements as BATS within the MM. These surface characteristics include surface-cover and soils information. The recent development of high-spatial-resolution databases of surface-cover and soils characteristics provides an excellent opportunity to improve the representation of land surface/atmosphere interaction processes in these models. This particularly applies to the development of the 1-km resolution Land Cover Characteristics Database developed at the United States Geological Survey EROS Data Center (hereafter referred to as the EDC database) (Loveland et al., 1991), and the State Soil Geographic Database (STATSGO), developed at the United States Department of Agriculture (USDA) Soil Conservation Service (SCS).

We have also prepared -- with the aid of William Jester (an engineering student) and staff members of the Center for Academic Computing at Penn State -- a 5-minute video showing the time evolution of the SWC fields over the 36-km SRBEX domain as generated by the SHM for the particular application presented in Smith et al. (1994). This film is available for demonstration (copy available for loan).

Ongoing work involving the SHM includes the development of a real-time SHM system, which will soon provide initial conditions to the real-time MM at Penn State (Lakhtakia et al., 1994). This will allow for real-time testing of the SHM-system capabilities when linked to the MM. Testing will include MM simulations, using the SHM-simulated SWC fields as initial conditions, and comparison of the predicted afternoon temperature and specific humidity close to surface with observations.


Surface-Cover and Soils Information within SRBEX

As discussed previously, surface characteristics are an important component of the modeling effort within SRBEX. The SHM and the MM both require the specification of several surface-cover parameters for each pixel within the domain. This is achieved by specifying one of 18 surface-cover types (Table 2), which, with the help of a look-up table, provides the surface-cover characteristics required by both models (e.g., roughness length, depth of rooting-zone soil layer, vegetation albedo, minimum stomatal resistance, etc.).

Until recently, the only high-resolution surface-cover dataset routinely used in the MM was the one archived at NCAR. This dataset covers the entire globe at 10 minute resolution (approximately 19 km). In order to initialize the SHM and the BATS module within the MM, this dataset (hereafter referred to as the NCAR dataset) has to be converted to the appropriate BATS surface-cover type shown in Table 2. Figure 8a shows the surface-cover type distribution over the 4-km SRBEX domain using the NCAR dataset.



  Table 2:  BATS surface-cover types used in the SHM and BATS
            module within the MM

1.    Crop/mixed farming (C)		10.   Irrigated crop (IC)
2.    Short grass (SG)			11.   Semi-desert (SD)
3.    Evergreen needleleaf tree (EN)	12.   Ice cap/glacier(I/G)
4.    Deciduous needleleaf tree (DN)	13.   Bog or marsh (B/M)
5.    Deciduous broadleaf tree (DB)	14.   Inland water (IW)
6.    Evergreen broadleaf tree (EB)	15.   Ocean (S)
7.    Tall grass (TG)			16.   Evergreen shrub (ES)
8.    Desert (D)			17.   Deciduous shrub (DS)
9.    Tundra (T)			18.   Mixed woodland (MW)


The EDC database has also been used in preliminary SRBEX studies. This database provides surface-cover types for the entire 48 conterminous United States at 1-km resolution. Dick White and Doug Miller reduced the original 167 surface-cover classes in the EDC database to the 18 BATS surface-cover types shown in Table 2, and then analyzed the information to the MM horizontal nested domains using a modal aggregation technique. Surface-cover information for the areas of Canada that are part of the 36-km and the 12-km domains was merged from the NCAR dataset. This resulted in seamless surface-cover type maps for each of the domains. Figure 8b shows the surface-cover type distribution over the 4-km domain using the EDC database. Mercedes Lakhtakia and Doug Miller were invited to present modeling results using the EDC database at the USGS-organized workshop: "Test and Evaluation of the USGS 1-km AVHRR Land Cover Characteristics Data for the Conterminous United States: Results and Recommendations", that took place in April 1994 at the EROS Data Center, in Sioux Falls, South Dakota. As an outcome from the workshop, they have also been invited to contribute to a special issue of Ecological Applications that will contain key papers presented at the workshop (Lakhtakia and Miller, 1995).

Apart from information on the surface-cover type, the SHM and the MM also require the specification of the soil-texture class (one of the 12 USDA soil-texture classes, as shown in Table 3) for each pixel in the MM domain. The soil-texture class, with the help of a look-up table, provides the soil parameters required by both models (e.g., SWC at saturation, minimum soil suction, saturated hydraulic conductivity, SWC at the wilting point, etc.). Traditionally, the lack of reliable information on soil characteristics at the regional scale has been an impediment to Soil-Vegetation-Atmosphere Transfer Scheme (SVATS) improvement. In fact, until now the SHM and the BATS module within the MM have relied on surface-cover derived soil-texture classes. Figures 9a and 9b show the soil-texture class distribution over the 4-km domain derived from the NCAR surface cover and the EDC surface cover, respectively.

The recent development of STATSGO shows potential for the delivery of much needed realistic soil information to the modeling community (Miller and Lakhtakia, 1994a and 1994b). STATSGO has been developed for river basin, multi-state, state, and multi-county resource planning. The compiled soil maps are created with the USGS 1:250,000-scale topographic quadrangles as base maps. STATSGO contains information on a wide range of soil properties (e.g., texture, particle size distribution, available water capacity, and bulk density). Doug Miller has performed initial work with STATSGO and has produced a soil-texture dataset that is compatible with the look-up table approach of the models. Figure 9c shows the STATSGO-derived soil-texture class distribution over the 4-km domain. Ongoing work focuses on the development of a STATSGO-derived multi-dimensional soil-characteristics dataset, that will provide measured or derived values of the soil parameters that are presently obtained from the look-up table.



   Table 3:  BATS soil-texture classes used in the
             SHM and MM

1. Sand 7. Sandy clay loam 2. Loamy sand 8. Silty clay loam 3. Sandy loam 9. Clay loam 4. Silt loam 10. Sandy clay 5. Silt 11. Silty clay 6. Loam 12. Clay

Mesoscale Model (MM) link with Terrestrial Hydrology Model (THM)

The linkage of the MM with the THM and the SHM is a central element within SRBEX. This linkage consists of the SHM providing initial values of SWC to the MM and the THM. In turn, the MM provides the simulated precipitation data to the THM. The precipitation fields simulated by the MM are piped into the GIS environment, where they are regridded for use by the THM as a forcing term in the surface hydrology balance (Lakhtakia et al., 1995). Dick White is developing the GIS link between the two models. This link is nearing completion and will be tested in the very near future.


Soil-Vegetation-Atmosphere Transfer (SVAT) Model/Remote Sensing

The SVAT/Remote Sensing research being conducted as a part of SRBEX has made significant progress in a number of areas in the past year. A workshop, under the auspices of our EOS investigation and the French agencies CETP and CEMAGREF, focusing on the problems and approaches in using multispectral measurements to infer the surface energy fluxes and soil water content, was held September 20-23, 1993 in La Londe les Maures, France. Dedicated volumes of formal papers from this workshop, entitled "Thermal IR Workshop of the Energy and Water Balance over Vegetation in Conjunction with Other Sensors," will be published in 1995 in Remote Sensing Reviews and Agricultural and Forest Meteorology. A version of the executive summary for the workshop will appear as the leading paper in each journal.

A new collaborative effort has been initiated with members of the USDA-ARS - Beltsville (William Kustas, Karen Humes, and Thomas Schmugge) to use field measurements where available (Walnut Gulch, AZ - Monsoon-90) and eventually the Little Washita field program in Oklahoma to continue to develop and further verify the triangle method implicit within the remote sensing program.

A related project has just gotten started to apply these newly developed methods to the study of deforestation and urbanization. Work has already begun in the first target area (i.e., State College, PA). Tim Owen, an MS candidate in Meteorology is conducting this research.

The interaction with other SRBEX members working in the area of watershed modeling has continued, with various data sets and model results being exchanged.

During 1995 the SHM will be increased in resolution to a vertical grid spacing under 1 cm in order to study the rapid drying of the soil surface. Results of the remote sensing project (Carlson et al, 1995) indicate that rapid drying occurs in the top soil layer, such that the surface soil water content becomes decoupled from the deeper layer soil water content. This has important implications for using thermal infrared temperature measurements to derive soil water content and for nudging the values obtained with the SHM with the remotely derived values.

The research in this area reinforces the development of advanced teaching methods in graduate training at Penn State. A graduate course in biosphere-atmosphere feedback processes will be taught, for the second time, in the Spring Semester 1995. The course used the PSUBAMS (see Figure 6) to teach the fundamentals of land-surface processes. A streamlined version of the model is currently being developed with a sophisticated front end to create a "user-friendly" environment.


Watershed Modeling Studies

Hydrologic Abstractions

Hydrologic modeling within SRBEX is concerned with the interaction and behavior of the hydrologic cycle as it pertains to the land surface. The main thrust of investigations has been the soil infiltration characteristics and modeling of the overland flow and channel routing mechanisms. During 1994 development and calibration of the terrestrial model, testing, and data analysis were conducted.

Several soils and land-use classification data bases have been investigated to estimate hydrologic abstractions. The STATSGO database has been examined for its general applicability. Soil-texture class, hydrologic soil group, available water content, and permeabilities are some of the main parameters extracted from this database.

In examining the permeabilities extracted from STATSGO, it was found that the values reported may not be applicable to most hydrologic modeling applications. Specifically, the values were very high compared to other recommended values of permeabilities. It is thought that the values reported in STATSGO are laboratory values of saturated permeability rates, and are thus not applicable to soils exposed to varying climatic conditions. The immediate solution to this problem has been to cross-reference soil types with published values of permeabilities for the various procedures.

The use of the more detailed Soil Survey Geographic Data Base (SSURGO) was examined for the WE-38 intensive study area within the Mahantango Creek Watershed and will continue to be investigated as more coverage becomes available.

The EPA EMAP Land Use/Land Cover Classification Data Base was used in conjunction with the hydrologic soil groupings to estimate curve numbers for the Mahantango basin, as well as the WE-38 intensive study area.

A 1994 thesis by Penn State student D. M. Lukhele, entitled "Physical Infiltration Models and the Use of STATSGO Soils Data Base for Estimating Model Parameters," compared runoff hydrographs generated by runoff predicted by the Green-Ampt Equation and by the Philip's Equation with actual stream gage data. It was found that the Green-Ampt method performed better than the Philip's equation. Specifically, it was found that the Green-Ampt method was better able to account for precipitation and infiltration under variable rainfall intensities. This study is considered very important in the development of the terrestrial hydrologic model (THM) for use with rasterized data.


Model Development

The THM has been under developement for approximately 2 years. The past year has been devoted to continued developement and testing of the various components. The basic structure of the present model includes estimation of the infiltration and ultimately the runoff by one of 3 methods. A phi-index or constant infiltration routine, the SCS Curve Number method, and the Green-Ampt Equation. Overland flow is approximated via the forward finite difference solution to the kinematic wave equation. Finally, a modified Muskingum channel routing routine is used.

While most of the modules in the THM have been operational for several months, difficulties in maintaining stable solutions, maintaining continuity, estimating boundary conditions, and estimating parameters in remotely sensed situations have been encountered Considerable progress has been made this past year to address and overcome these difficulties.

Because of the nature of SRBEX and EOS, which concentrate on remotely sensed data acquisition, the model has been written to accept various levels of data. The various levels of data and analysis can create stability problems for mathematical solutions when estimated parameters are used.

The model has been run for several rainfall events in the WE-38 intensive study area with very good results. Hydrograph peaks, which are obviously the result of the immediate response of overland flow, are matched quite well. Hydrograph volumes are matched reasonably well, particularly when there is an attempt to account for baseflow contributions. There is need to enhance this aspect of the model, as the current THM does not contain a groundwater or through-flow component.

Present research is concentrating on the stabilization of the channel routing scheme and the sensitivity of the rainfall network requirements. Also, the applicability of the 3 infiltration routines is being investigated.


Future Hydrologic Modeling Work

Work on the model will continue, particularly in the testing and calibration modes. Complete coverage of curve numbers derived from STATSGO and EMAP data, permeability estimates, digital elevation models (DEM's), and precipitation data have been acquired for both the WE-38 intensive study area and the Mahantango watershed. The simulation of several storms is planned for the next few months.

Also, the linkage of the THM with the MM is currently under way. Precipitation values and derived hydrograph outputs will be compared with actual measurements.

Additional modules must be added to the THM for a "complete" model. These modules include a groundwater component, a reservoir component, and a snowmelt component. Finally, several publications are underway, as well as continued exposure of the model with several planned presentations in the near future.


Synthetic Aperture Radar Studies at the Mahantango Creek Watershed

A primary goal of the SRBEX research involves the application of selected instruments for the acquisition of input data for hydrologic models. The active instrument Synthetic Aperture Radar (SAR) is of particular interest due to its day-night and all weather imaging capabilities and its sensitivity to soil moisture, an important variable for modeling exercises. Last year Eric Warner, under the supervision of Gary Petersen, began work to test the sensitivity of the NASA/JPL AIRSAR backscatter data, collected during the 1990 NASA-sponsored MAC-HYDRO mission, to a range of agricultural covers and soil-moisture conditions. The related question concerning the influence of terrain on SAR sensitivity to vegetation and soil moisture was also of interest. Progress in addressing these questions has been made in the following areas:

  1. Adaptation of NASA-provided programs and images to in-house platforms and software.

  2. Exploratory data analysis which has revealed significant differences between cover types for all frequencies and like-polarizations as well as differences in backscatter between wet and dry conditions for soils under like cover types.

  3. Generation of two fine resolution DEMs to assist in the examination of terrain influences.

This ongoing research has raised aditional questions. These questions will be addressed, in part, under the current EOS investigation. In addition, they are the focus of a proposal submitted to the NASA-sponsored Topographic Change Program involving both instrument and applications research. The goals of the proposed investigation include:

  1. Extend the examination of AIRSAR sensitivity to soil moisture and agricultural cover to include a comparison with imagery from the Space Shuttle-borne SAR instrument. The Mahantango Creek Watershed was overflown conjunctively with AIRSAR and the Shuttle SAR instrument during two time periods in 1994. This will allow a comparison of the data from the two instruments, clarifying the potential for space-borne multi-frequency sensors to conduct soil-moisture investigations.

  2. Utilize Canada's soon-to-be launched RADARSAT for soil roughness and agricultural cover studies. A proposal will be submitted to the Canadian Space Agency for variable incidence angle imagery to conduct numerical modeling of soil-surface and plant-canopy characteristics.

  3. Employ terrain corrections procedures examined for AIRSAR imaging with the Shuttle-borne SAR imagery. This investigation defines the need for terrain corrections for imagery from space based sensors and the appropriate scale of elevation data for correction procedures.

  4. Compare elevation data acquired from conventional sources with that obtained from candidate instruments for a space-based platform dedicated to the collection of elevation data on a global basis. The importance of elevation data in hydrologic and geologic investigations, as well as for correcting terrain influences on imagery from various sensors, has underscored the need for an orbiting platform to collect elevation data. The comparison of data from candidate instruments with conventional sources permits an assessment of prototypes for an orbiting system.

The proposed and existing research addresses issues important to the application of SAR imagery for a range of earth, ecological and agronomic investigations. The scope of this work should involve the affiliated staff for at least three years.


Water Quality Modeling

Our role in this research group is to use stream chemistry data to validate the models developed by the other parts of SRBEX and to obtain insight in how hydrological processes should be modelled at increasing scales. This year we have completed compiling a water-quality database for 52 sampling stations in the SRB. Catchments associated with the stations form a nested hierarchy of watersheds representing a suite of scales, lithologies and land uses. The database consists of all the available stream chemistry for each station, its watershed divide, lithology, stream network, and land use. The data products are in Arc/Info export format and are available to other EOS and scientific investigators. This year two scientific goals were achieved, partially fulfilling objectives 6 and 9 of the research prospectus:

  1. Completion of a series of mass balance calculations of weathering fluxes to investigate the roles that watershed scale, lithology, climate and land use play in controlling weathering rates (Bluth and Kump, 1994; Richards and Kump, 1994b).

  2. The development of a function relating water quality to discharge that we have linked to the terrestrial hydrology model (Richards and Kump,1994a).

What follows is a partial summary of the important findings from these studies:

  1. Weathering fluxes in the SRB are a strong function of the lithology and the extent of mining in a watershed.

  2. Mg fluxes are controlled by the amount of carbonate in the watershed.

  3. Mg fluxes from watersheds with abundant mining operations were found to be 6 to 10 times higher than fluxes from comparable pristine watersheds.

  4. Mining practices are believed to enhance chemical weathering by increasing the surface area of unweathered rock water has access to.

  5. Weathering fluxes were found to increase with watershed scale. This scale dependance is believed to be caused by the inclusion of small amounts of carbonate at larger scales, that are not accounted in our lithology estimates.

  6. Flux-concentration-discharge relationships for the stations suggest that elemental fluxes in the SRB vary primarily with discharge and that export rates can be accurately modelled with a simple power function.The empirical constants for this function were found to vary with scale and dissolved species but not land use or lithology. The results indicate that small catchments, typical of the watersheds for which most hydrological models are developed, differ fundamentally from large watersheds. Fluxes from small watersheds are controlled by the chemistry and water residence time of flow paths in soils and fractured bedrock.


Landscape Evolution Modeling

The specific objective of this research component is to understand how catchment morphometrics and sediment yields in drainage basins will evolve in response to changing boundary conditions, especially changing climate.

To answer this question R. Slingerland and G. Tucker first derived a Geophysical Landscape Evolution Model (GOLEM). The past year has been spent calibrating GOLEM for use in the Mahantango Creek Watershed within the SRB, and exploring its behavior under various initial and boundary conditions. We have discovered, through sensitivity experiments, that the evolution of the landscape is critically dependent upon the functional relationship between fluvial erosion rate and slope x discharge. To determine the appropriate functional relationship for the Mahantango study area we:

  1. Obtained a copy of the USGS 30m DEM data and used GIS to delineate the Mahantango Creek Watershed.

  2. Obtained a copy of the PA Survey's geologic contacts map, subset the portion that covers the Mahantango, and converted it to a 30m raster coverage.

  3. Wrote new GIS software to extract and analyze channel slope and drainage areas for the Mahantango catchment, and separate out those data according to the separate mapped lithologies.

  4. Analyzed slope-area trends for the watershed as a whole, as well as for individual lithologies.

If one assumes an equilibrium landscape, then our conclusion is that erosion of the Mahantango Creek Watershed is proportional to QmSn where m and n are 0.25 and 0.7, respectively. The exponents do not seem to be particularly sensitive to lithology.

We are now in the process of using these exponents, the lithologies, and the present drainage net of the watershed to fine-tune the model. Hillslope processes are assumed to follow a diffusion law and the streams erode like bedrock channels. Each lithology has a unique set of parameters for hillslope and channel processes which we fit by minimizing sum-of-the-squares error in mean and point elevations. We also insure that the area aggregation index (a statistic representing how rapidly drainage coalesces) is within observed bounds. The result will be a calibrated small-scale process model of the Mahantango drainage basin.

Over the next year we will explore the response of the calibrated model to changes in climate and uplift. For example, we will increase the rainfall without changing hillslope diffusivity. Under these conditions we expect that channel heads will extend and incise. If we increase hillslope diffusivity without changing rainfall as might happen upon loss of vegetation, we expect the channel network to retreat. The final product will be predictions of erosion hot spots within the basin as well as an improved understanding of how sensitive this basin is to order of magnitude changes in the forcing factors.


Human Dimensions of Environmental Change in the SRB

Research on the human dimensions of environmental change spotlighted the policy relevance of SRBEX and similar global-change projects (Yarnal, 1994a and 1994b). This work concluded that, to be pertinent to policy makers and water resource managers, SRBEX must add a significant human component. Specifically, new objectives must:

  1. Identify socioeconomic vulnerabilities to hydrologic-system variations and change;

  2. Project the socioeconomic impacts of water-resource changes.

These objectives require the integrated assessment of hydrologic, human and decision-making systems. This assessment is clearly beyond the scope of the present program and calls for increased research on the human and policy dimensions of SRBEX (Yarnal, 1992 and 1993). A major effort to procure funding for this important work will be mounted in 1995.

Education is another area critical to projects like SRBEX. The College of Earth and Mineral Sciences at Penn State is well known for its training of earth and atmospheric scientists, and the ESSC is a leader in developing courses and programs on the physical dimensions of global change. Recognizing the importance of the human component, undergraduate and graduate courses on the human dimensions of global environmental change are now being offered regularly. Most exciting, a full-year course (EARTH 497 CAUSE) on integrated assessment and involving the College's top undergraduates in policy-relevant field research in the SRB is currently being developed for January 1995.


SRBEX GIS and Data Management System

GIS and data management activities have continued to focus on creating a hierarchical structure for archiving and retrieving datasets needed to support SRBEX investigations, enhancing tools for storage, retrieval, and analysis of image and GIS data, and obtaining additional geographic and remotely sensed data to support modeling activities.

A hierarchical database supporting searches at five levels of geographic extent is now in place. The five levels contain, respectively, datasets whose approximate extent is the entire world, continent-sized areas, states or countries, one-degree squares in latitude and longitude, and 7.5 minute squares in latitude and longitude. At each level, the directory covering a given region contains three types of entries: subdirectories containing datasets whose extent approximates that of the region, links to directories for subregions at the next lower level, and links to directories for adjacent regions at the same level which may contain datasets which overlap several regions.

Maintenance of this data structure is facilitated by a growing set of utility programs. These utilities currently include modules for creating directory subtrees at any of the four lower levels of geographic extent, automatically entering standard products such as DEM files into the database and generating preliminary documentation for them, and creating cross references for datasets spanning more than a single geographic region. Various user help materials have also been developed, including information on database structure and usage, map projections, and data format conversions.

We are in the process of linking this database to the Mosaic World Wide Web server, developed by the National Center for Supercomputing Applications. This hypertext-oriented interface allows database users to display boundaries of regions (extracted from the Defense Mapping Agency's Digital Chart of the World), select one region by placing the cursor within its boundaries, and then display either a catalog of available datasets at the scale of the selected region, or boundaries of the subregions at the next lower geographic level.

We have continued to enhance the software available for image analysis, GIS, and data transfer/reformatting between models. Recent upgrades include Version 7.0 of the Arc/Info GIS software, Version 8.2 of ERDAS Imagine, and Version 6.0 of the Land Analysis System (LAS) image processing software, which was developed by NASA/GSFC and the EROS Data Center. We are currently collaborating with the EDC and the Alaska SAR Facility in porting LAS to the Sun Solaris 2.X operating system. Our collaboration with EDC also addresses development of LAS modules for interchanging data with Arc/Info. A suite of locally developed LAS programs, which is nearing completion, will automate the conversion of LAS imagery and Arc/Info GIS data into a format and map projection suitable for ingest by the MM, and the subsequent conversion of model output back into LAS and Arc/Info formats for further analysis and input to other models.

In addition to loading previously acquired data sets into the database and creating documentation files for them, we have acquired a number of additional data sets required for model inputs. At the continental scale, these include the 1-km DEM and land-cover database, watershed boundaries at the 8-digit classification level from the USGS, and 40 years of daily precipitation data for the 48 conterminous U.S. states. More localized coverages include digitized geologic maps for the part of the SRB within Pennsylvania, and recent Landsat TM imagery and high-resolution (15 meter horizontal, 0.5 meter vertical) DEM data for parts of the WE-38 intensive study area. As a high priority, we plan to complete our holdings of available 30-meter (horizontal resolution) DEM data for the entire SRB; 30-meter DEMs are not yet available for roughly 10 percent of the Basin, mainly in the northern part in New York State.

We have also acquired a number of data sets on CD-ROM, including the Digital Chart of the World, biweekly AVHRR composites for the U.S. compiled by EDC, ISCCP monthly cloud cover, atmospheric data compiled as part of the Greenhouse Effect Detection Experiment (GEDEX), and 114 years of streamflow data from the U.S. Hydro-Climatic Data Network. To facilitate access to these data sets and the large amounts of other remote sensing, climate, and earth surface-characteristics data which are becoming available on CD-ROM, we are keeping the header files for each CD-ROM on-line in the main database, and, subject to copyright restrictions and space limitations, plan to copy the entire contents of selected CD-ROMs to the archival tape system on the ESSC Cray YMP.


Advanced Techniques for the Representation of Geographic Information

The Triad database design, developed within a GIS context during years one and two of this project, was further refined and studied within a much broader, more fundamental, philosophical context. This broader study of spatiotemporal representations was undertaken with the realization that addressing complex human and environmental issues such as global warming and human impact on the environment requires not only sophisticated, multidimensional tools for handling and analyzing empirical data, but also an integrated, interdisciplinary representational framework from the conceptual (human) viewpoint. Initial results of this broader effort are described in the paper, "It's About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems" (Peuquet, 1994).

The location-based component, the second element of the triad database design, has been successfully implemented. This is currently being integrated with the temporally based component in a second-generation demonstration prototype system called TEMPEST. The design and implementation of TEMPEST is presented in "An Approach for Time-based Analysis of Spatiotemporal Data," (Peuquet and Wentz, 1994).



Cape Experiment (Objective 9)
(S. Goodman)

The Convection and Precipitation/Electrification (CaPE) Experiment was a multi-agency field program conducted in central Florida between July 8 and August 18, 1991. The focus of the experiment was to study the development of mesoscale meteorological conditions and consequent storm characteristics, and to develop improved techniques for performing short-period forecasts of convection initiation, downbursts, and tornadoes. This experiment resulted in a diverse data set from gound stations, radiosondes, surface radar, and aircraft and satellite remote sensors. The availability of such data spawned additional research projects, including CAPE Hydrometeorology Project (CHymP) involving scientists from NASA's Marshall Space Flight Center and the University of Oklahoma. The objective of CHymP was to develop and apply a method to diagnose large-scale (~25,000 km2) land and atmosphere water budget components with an underlying philosophy that these techniques can be tested and aplied over regional-scale areas in conjunction withe GCIP (GEWEX Continental Scale International Project).

Data used in CHymP include station data, map data, and image data. These data were obtained from many sources including supervised field measurements, unsupervised temporary and permanent gaging stations, surface radars, radiosondes, aircraft-based instruments, and aircraft and satellite remote sensing instruments (Table 4). Data sets were supplied in many disparate formats by universities and various state and federal agencies. Data were quality-controlled and preprocessed using spreadsheet software and a GIS with image processing capability. Utilities were developed through this project to provide additional required functionality to manipulate data not already accommodated by existing software.

Through CHymP an understanding of data quality issues involved in assimilating data of disparate types and a strategy for data assimilation necessary in land-surface hydrologic modeling within a GIS framework was developed. Because of the importance of rainfall in forcing most hydrologic models, considerable effort was dedicated to deriving a climatologically tuned Z-R relationship for radar-derived precipitation fields using a probability matching method. A new SVATS was developed and used in studies of the sensitivity of surface fluxes and runoff to soil and landcover characterization. Results of these experiments have raised many questions about how to treat the scale-dependence of land-surface/atmosphere interactions on spatial and temporal variability.

The SVATS being developed through CHymP is the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS), a new contribution to the study of large-scale hydrologic processes and parameterizations. The physics of SHEELS are based on those of BATS. SHEELS has inherited that model's physical treatment of vegetation properties. The model uses a single canopy layer but allows for fractional coverage of the ground by vegetation. The soil is divided into three layers, the upper two of which contain roots. The nested soil layer approach of BATS has been converted to a discrete layer configuration in SHEELS. Other modifications from BATS include a simplification of the radiation scheme to utilize measured radiative fluxes, a more refined treatment of soil thermal and hydraulic properties, inclusion of a water table and a combined soil/vegetation albedo. Unlike BATS, SHEELS accounts for topography as well as surface and vadose zone water and energy fluxes thereby offering the potential to study and develop parameterization schemes for a range of scales (from large catchement to mesoscale). SHEELS represents an integral approach to land-surface modeling, bringing together the key biophysical components of the soil, vegetation canopy and atmospheric surface layer. Its uniqueness lies in its treatment of surface variability of soil properties obtained from the STATSGO database. Landcover information is obtained from remotely sensed landcover classification images.



   Table 4:  SHEELS data requirements and the sources of data used in CHymP.


 SHEELS DATA REQUIREMENTS         CHymP DATA SOURCES            ANCILLARY SOURCES       

Atmospheric Inputs:             Flux stations, PAMs          NWS stations, remote
T, RH, pressure, wind,                                          sensing, model
analyses radiation fluxes

Precipitation                   Raingage network, radars     Model Analyses

Land Surface Inputs: LAI,       Landcover classification     VIS and thermal remote
canopy height, % vegetation                                  sensing

cover, surface emissivity       (Landsat-TM)

soil density, porosity,         SCS STATSGO data,  flux
hydraulic conductivity,         stations
suction, wilting point,
organic matter content

Slope, aspect                   Digital elevation data

Verification/Constraint         Flux stations                Model output
Variables: Latent, sensible
and ground heat fluxes, soil
temperature, soil moisture

Surface temperature,            Flux stations, PAMS, MAMS    AVHRR, SPOT, Landsat-TM
albedo, TRN, NDVI

Steam discharge                 USGS gages

Groundwater                     USGS groundwater wells


Interaction with the EOSDIS.

The MSFC Science Team produced 2 data sets at the MSFC DAAC, available to EOS researchers, which will be helpful in studying extreme hydrologic events and the space-time variability on a continental scale. These data sets are:

  1. U.S. national composite precipitation - 8 km spatial resolution every 15 minutes

  2. U.S. national lightning flash rates - 8 km spatial resolution every 15 minutes

These data sets are available in HDF format and browse products are going through integration and test during October-November 1994. These browse products will be .gif files available through EOSDIS.



Ice-Sheet Mass Balance (Objective 10)
(R. Alley)

Our work on ice-sheet mass balance continues apace. A summary was presented to the EOS IWG meeting this month, as ``Predicting Sea Level: The Solid and the Speculative'', and a summary was presented to U.S. Vice President A. Gore, at his request, at a breakfast meeting in Washington.

Sea-level predictions assume a strong thermodynamic control on snowfall, such that cold regions of ice sheets remove water from the oceans during global warming owing to enhanced snowfall. Questions about that are raised by our studies relating snow accumulation to temperature over long times (Kapsner, 1993; Kapsner,1994; Kapsner et al., 1994 ).

Sea-level predictions also assume that ice sheets cannot change rapidly. Our West Antarctic and North Atlantic studies are contributing to a revised view that ice sheets can and have changed rapidly on time scales of human interest. A manuscript, by R. Alley, for an AGU Monograph is about to be submitted.

Passive-microwave remote-sensing work in support of ice-sheet studies also is proving productive. Shuman et al. (1994a; 1994b) have demonstrated the capability to conduct thermometry of snow surfaces from space, and to combine the temperature measurements with snow-pit measurements to identify time lines in snow stratigraphy and learn the seasonality of snowfall.

Near-surface air temperatures in central Greenland can be estimated from satellite passive microwave brightness temperatures supported by limited air-temperature data from automatic weather stations. In this region, brightness temperature depends on snow emissivity, which varies slowly over time, and on snow temperature, which varies more rapidly and is controlled by air temperature. The air temperature and brightness temperature data define an emissivity trend which can be modeled as an annual sinusoid. Estimated air temperatures represent an integrated near-surface value that defines the overall temperature trend at the Greenland Summit. The modeled emissivity trend allows daily-average air temperatures to be estimated across significant gaps in weather station records, as well as quality control of their temperature data. The technique also generates annual trends of emissivity which can be used to calibrate or test radiative transfer models of microwave emissivity from dry firn.

Long-term satellite passive microwave brightness temperature trends, supported by short-term automatic weather station (AWS) temperature data, show that the Greenland Summit area experiences secondary warm periods in the late fall and/or winter as well as primary midsummer warmth. High-resolution isotope profiles from snow pits dug in 1989, 1990, and 1991 near the Greenland Ice Sheet Project II (GISP2) site reveal that stable isotope ratios (del18O and delD) preserve this distinctive temperature cycle. This indicates that snow accumulation occurs frequently through the year at Summit and that the isotope record initially contains temperature information from many times of the year. Through an empirically derived emissivity model using AWS air temperature data and brightness temperatures, our approach allows isotope values preserved in the snow to be related to estimated near-surface air temperatures. Density-corrected, water-equivalent profiles allow the amounts and timing of accumulation to be determined as well. Our results indicate that stable isotope ratios from the near-surface snow at the Greenland Summit are reliable, high-resolution temperature proxy. This gives confidence to the paleoclimatic interpretation of isotope signal variations in the GISP2 core.

Projections of sea-level rise during anthropogenic climate warming often assume that increased vapor pressure will cause enhanced snow accumulation on cold regions of ice sheets, partially offsetting the increased melting of low-latitude and low-altitude ice. To test whether this has been true in the past, we compare accumulation rates and temperature derived from the oxygen-isotopic composition of the GISP2 deep ice core. We find that atmospheric circulation and not temperature is the primary control on snow accumulation in central Greenland over the last 18,000 years. Within both warm (Holocene) and cold (Younger Dryas, glacial maximum) climate states, the sensitivity of accumulation to temperature is less than expected if accumulation is controlled primarily by the ability of warmer air to deliver more moisture. During transitions between warm and cold climate states, accumulation varies more than can be explained thermodynamically, probably because of storm-track shifts. In a greenhouse-warmed world, any circulation changes may be more important than the direct effects of temperature change in controlling accumulation in Greenland and its contribution to sea-level change.


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