The GCIP activities in land surface and hydrological characteristics are striving to improve the quantitative understanding of the relationships between model parameterizations of land processes and land surface characteristics; and facilitating the development, test, evaluation, and validation of multiresolution land surface characteristics data and information required by GCIP researchers for developing, parameterizing, initializing, and validating atmospheric and hydrological models.

4.1 Land Surface Characteristics Research

The strategy for land surface characterization research is twofold. In the near term, the primary emphasis is on facilitating the adaptation, tailoring, test and evaluation, and validation of existing land surface characteristics data sets that will meet the immediate requirements of GCIP's Principal Research Areas. This near-term strategy also includes adapting and testing promising biophysical remote sensing algorithms that are available in the literature, for example published results from ISLSCP's remote sensing science activities involving FIFE, Boreal Ecosystem Atmosphere Study (BOREAS), or the GEWEX/ISLSCP global one-degree latitude-longitude global land data sets published on compact disk, read-only memory (CD-ROM). Many GCIP modelers will conduct land characterization research as an integral part of their efforts to develop land surface process models and parameterizations, therefore, facilitating the cross-disciplinary flow and sharing of land characterization results and information within the GCIP research community is needed. GCIP's longer-term strategy for land surface characterization research will focus on developing and testing enhanced high-resolution land data sets. This includes collecting field data that are necessary to develop, adapt, test, and validate promising remote sensing algorithms for land cover characterization and model parameterizations; conducting advanced remote sensing research, for example, canopy reflectance modeling; and investigating landscape heterogeneity, grid cell aggregation rules, and land data interrelationships as related to land process parameterizations. This longer-term strategy also includes provisions by GCIP to test and evaluate remote sensing data sets that will become potentially available following the planned launches of the NASA-led Earth Observing System (EOS) (Terra; formerly AM1) Platform and Landsat 7 during the mid-1999 time-frame.

Land surface characterization research is highly interdisciplinary in scope. Therefore, an equally important high-priority task is to develop Federal agency participation and resource support for cooperative work on the accomplishment of GCIP's land surface characteristics research objectives and activities. Some of the potential Federal agency participants for conducting and supporting this land surface characterization research include NOAA (NWS and NESDIS), the USGS (National Mapping Division and Water Resources Division), NASA [Marshall Space Flight Center (MSFC) and GSFC] and the USDA [ARS, Natural Resources Conservation Service, and National Agricultural Statistics Service (NASS)]. In many cases, the results of this interdisciplinary land surface characterization research will directly benefit agency missions, such as those concerning land data set development, remote sensing science, operational programs involving atmospheric and hydrological modeling, natural resource assessment, and agricultural monitoring and forecasting. Furthermore, activities such as SAST, involving flood disaster management, can contribute to GCIP both in terms of a supplier of land data and as a key user of GCIP atmospheric, hydrologic, and water resource products for policy decision making. The efforts of such Federal agencies would complement contributions made by GCIP's research community including expertise at universities. The coordination of this research with potential contributions by GEWEX/ISLSCP presents an outstanding opportunity, especially for biophysical remote sensing algorithm development, operational data set development, and scaling research.

4.2 LSA-NW Research

The land surface and hydrological characteristics within the Missouri River Basin of the LSA-NW are quite variable in both space and time. The land cover and land use conditions are diverse throughout the LSA-NW, for example, including dryland and irrigated crops, rangelands, pastures, natural grasslands, and some forested areas. Agricultural land use can change from year-to-year due to economic, farm management, agricultural policy, weather variability, or other factors. Regional land cover and land use patterns are also determined by the east-west precipitation gradient, north-south temperature gradient, and orographic/surface hydrologic effects ranging from mountainous terrain to prairie potholes. Especially in the semi-arid west, there is a strong annual cycle of heterogeneous snow cover during the cold season and seasonally variable vegetation in the warm season. Spatial and temporal variability of snow cover conditions (snow vs no snow) and land cover (percent bare ground vs vegetative cover) is a major determinant of land surface processes throughout the LSA-NW. Year-to-year variations in seasonal and monthly climatic conditions significantly determine this variability of land surface and hydrologic characteristics (e.g., albedos, surface roughness, LAI/FPAR, NPP, etc.) associated with the beginning, peak, and duration of the growing season.

The LSA-NW provides GCIP with an opportunity to move from static, coarse-resolution representations of the land surface to a more detailed, dynamic landscape characterized by a strong annual cycle with significant spatial and temporal variability. In this context, the following research activities are planned for the GCIP LSA-NW region:

(i) Conduct research projects that contribute to the incorporation of spatially heterogeneous (<= 1-km) and temporally variable (1-10 days) vegetation and snow cover conditions into the land surface hydrology component of GCIP models. Research includes:
(a) Monitoring, analysis, parameterization, and aggregation of subgrid variability of surface characteristics and processes within 20-30 km model grid cells. Such studies would benefit from calibrated, atmospherically-corrected satellite-derived land surface reflectance and temperature data.
(b) Use of in situ and high-resolution satellite data (e.g., 30 m Landsat 7) for selected land processes research (e.g., snow sublimation, snow cover heterogeneity, snow patchiness-albedo effects, snow drifting, subgrid fluxes given seasonally variable fractional bare soil-vegetation conditions, etc.). The LSA-NW snow cover and snow melt hydrologic processes are significantly influenced by snow cover patchiness including drifting effects, sublimation, and downslope winds which may differ from snow/cold season hydrologic processes under study in the LSA-NC (Upper Mississippi River basin).
(c) Use of 1-km AVHRR (e.g., NDVI) for spatial and interannual vegetation seasonality analysis during CY 1999 (e.g., irrigated areas), as a step towards the use of potential MODIS land products if available for CY2000.
(d) Development of checks and GIS studies to ensure the internal consistency of aggregated land cover, soils, surficial geologic, and topographic characteristics within model grid cells on the order of 10-30 km. Conduct analogous studies at various hydrologic watershed scales with a focus on topographic data derivatives (e.g., watershed boundaries, stream traces- gauge location, wetness indexes, drainage slope profiles, and spatial context), especially as related to macroscale hydrologic models.

(e) Communication of requirements for land cover and hydrologic characteristics data sets on seasonally variable biophysical parameters throughout the entire year (albedo, surface roughness, LAI/FPAR, fraction bare soil/vegetation, etc.) suitable for aggregation within model grid cells on the order of 10-30 km.

(f) Begin the study of how land cover and land use changes at decadal time-scales affect surface fluxes and hydrologic processes. Such changes may include irrigated areas (center-pivot irrigation) and land cover conversion due to agricultural policy or conservation.
(ii) Ensure GCIP coupled-modeling research includes unique LSA-NW conditions such as orographic and surface hydrologic processes (potholes, Sand Hills, and regional exposed aquifer recharge areas).
(iii) Initiate research to develop a surface net radiation algorithm based on a combination of satellite and in situ data for potential validation of mesoscale model output, and as a step towards surface flux estimates.