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).
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.
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).
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).
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.
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:
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.
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.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.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
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.
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.
More specifically, SRBEX includes the following policy-relevant objectives:
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.
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:
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:
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.
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).
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.
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
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.
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.
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.
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.
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:
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.
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.
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.
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).
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
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.
Barron, E.J. and G.S. Jenkins, 1994b: 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.
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, 1994b: Estimating near-surface soil moisture availability using a meteorologicially driven soil water profile model. J. Hydro. 160:1-20.
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).
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.
Dickson, R., 1980: Weather and circulation of February 1980, California floods. Mon. Wea. Rev.108: 679-684.
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Send comments to: R. A. White / raw@essc.psu.edu