MAJOR ACTIVITIES PLAN FOR 1997, 1998 AND OUTLOOK FOR 1999

for the

GEWEX CONTINENTAL-SCALE INTERNATIONAL PROJECT (GCIP)

SUMMARY

December 1996

IGPO Publication Series No. 25

For information on ordering a complete hard copy version of this document see below.

Summary

S1. Background

The World Climate Research Program in its Global Energy and Water Cycle Experiment (GEWEX) has established Continental Scale Experiments to improve scientific understanding and to model on a continental scale the coupling between the atmosphere and the land surface hydrologic processes for climate prediction purposes. The GEWEX Continental-scale International Project (GCIP) was established in the Mississippi River basin in 1992 to take advantage of the extensive meteorological and hydrological networks including the new Doppler radars, wind profilers, and automatic weather stations. GCIP is contributing to the long-term goal of demonstrating skill in predicting changes in water resources on time scales up to seasonal, annual, and interannual as an integral part of the climate prediction system. The overall strategy framework for implementing GCIP is shown in Figure S-1.

Figure S-1 Strategy Framework for Implementing GCIP.

The understanding and modeling of a continental scale requires, from the outset, consideration of nonlinear-scale interactions in the aggregation of smaller processes to the larger scale and vice versa. GCIP research involves a systematic multiscale approach to accommodate physical process studies, model development, data assimilation, diagnostics, and validation topics. GCIP research activities occur in a phased timetable and emphasize a particular region with special characteristics for a period of about two years. Four Large Scale Areas (LSAs) have been identified which encompass major river sub-basins of the Mississippi River basin and which in aggregate cover most of the GCIP domain, as shown in Figure S-2. The time phasing of activities within each of these areas is also shown in the figure. The GCIP Enhanced Observing Period started on 1 October 1995 and will continue for five years. A fundamental thrust of the GCIP implementation strategy is that although the developmental activities are being initiated in limited regions, they lead toward an integrated continental-scale capability.

Figure S-2 The Mississippi River basin with boundaries defining the Large Scale Areas (LSAs) for GCIP Focused Studies (top). Temporal emphasis for each LSA from 1994 through 2000 (bottom).

Model development in GCIP has two paths as was shown in Figure S-1. A key strategy adopted early in GCIP was to fully exploit the high resolution limited area models that were being applied to regional weather prediction tasks through various nesting procedures in the global models. This strategy was implemented as part of the operational" path to provide the model assimilated and forecast data products for GCIP research as well as serving as a proof of concept" for components of a coupled hydro- climate model. The research" path focuses on the longer term activities needed for a coupled climate model.

GCIP Objective: Develop and evaluate coupled hydrologic/atmospheric models at resolutions appropriate to large-scale continental basins.

S2.1 Near-Term Priorities for Coupled Modeling

In accordance with the overall goals of GCIP, the coupled modeling activities will focus on regional mesoscale modeling as an element in developing a capability to produce experimental seasonal-to-interannual climate predictions for the North American continent and evaluate these relative to GCIP data. While recognizing that initially such experimental forecasts are likely only to have limited skill, GCIP will initiate exploratory investigation of the potential value of such predictions in the context of water resource issues which can also serve as a mechanism through which to understand and develop the required interface between climate and weather predictions and their hydrological interpretation.

The improved parameterization of land surface processes and warm season convective precipitation in coupled models will be a major focus of interest within GCIP in the next two years, and the intention to begin providing a soil moisture product for at least portions of the Arkansas-Red River basin in Oklahoma during 1997 will provide a critical new resource for such studies. Equally, the planned joint NOAA-NASA call for proposals is an important new opportunity to implement the most essential aspects of an ISLSCP initiative within GCIP. In this context, the basin-wide introduction of advanced representations of the biosphere that are able to exploit remotely sensed data is particularly important, because this will provide a basis for understanding the significance of the seasonal behavior of vegetation in coupled models, and of assessing the biosphere response to extreme conditions of water shortage. The Enhanced Seasonal Observing Period during the winter of 1997 provides the data needs for beginning the studies and modeling of cold season processes with emphasis on the problems of snow cover.

S2.2 Coupled Modeling Long-term Items to be Initiated in the Next Two Years

Now that complementary studies of ocean-atmosphere interactions within the Pan American climate Studies (PACS) and of land-atmosphere interactions under GCIP are both beginning to make noteworthy progress, it is timely to begin defining and implementing a coordinated US seasonal-to-interannual research program. Consistent with the priorities of the Global Ocean-Atmosphere Land System (GOALS), such a program will have focus on documenting, understanding and modeling the Mexican Monsoon and the indirect impact of this hydroclimatic feature on the summer season climate elsewhere on the North American continent. In this context, the need to correct the weakness of a missing observational interface between PACS and GCIP is a particularly important issue in this planning process.

S2.3 Improvements to Coupled Mesoscale Models

An operational" path (Figure S-1) was started very early in the GCIP Buildup Phase to develop and implement the improvements needed in the operational analysis and prediction schemes to produce the model assimilated and forecast output products for GCIP research, especially for energy and water budget studies. The regional mesoscale models also serve to test components of a regional climate model and can provide output for the evaluation of a coupled hydrologic/atmospheric model during the assimilation and early prediction time periods as a precursor to developing and testing a coupled hydrologic/atmospheric climate model. The output from three different regional mesoscale models is routinely compiled as part of the GCIP data set.

S2.3.1 Near-Term Priorities for Coupled Mesoscale Models

(1) - Utilize the GCIP special data sets to validate and evaluate the regional model output. Concentrate on validation of surface energy fluxes, surface skin temperature, soil moisture, cloud cover, precipitation, and diurnal planetary boundary layer profiles of temperature and humidty.

(2)- Produce plots and graphs of the monthly Mississippi River Basin water budget components from the ETA, MAPS, and RFE systems. Compare with similar but independently computed budget components from observations.

S2.3.2 Coupled Mesoscale Models Long-term Items to start in the Next Two Years

(1) - Validate and evaluate the 4DDA and forecast runoff of the Eta, Mesoscale Analysis and Prediction System (MAPS), and Regional Finite Element (RFE) models (and later their companion land data assimilation systems), by applying streamflow/river routing algorithms to the gridded runoff archives from these systems.

(2) - Investigate and develop algorithms for parameterizing sub-grid scale fractional precipitation distribution for use in the surface infiltration algorithms of coupled mesoscale models. Study the spatial and temporal distribution characteristics of the precipitation fields from the Eta, MAPS, and RFE assimilation and forecast systems. Also study the convective stability index products from these systems.

(3) - Investigate and develop strategies for a priori continental-scale estimation of key hydrological parameters, such as saturation hydraulic conductivity, soil moisture capacity ("bucket depth"), rooting depth, soil porosity, active soil column depth, and slope.

(4) - Imbed coupled mesoscale models into global ocean/atmosphere models and investigate the advantages of imbedding (if any) on the skill and utility of seasonal and annual forecasts.

S3. Hydrological Modeling And Water Resources

One of the eventual aims of the GCIP modeling effort is to generate inputs for operational hydrological and water resources management models over a range of time scales.

GCIP Objective: Improve the utility of hydrologic predictions for water resources management up to seasonal and interannual time scales.

GCIP plans to increase the level of effort in this area. It has been working with the Office of Hydrology in the area of hydrologic modeling with the hope that some links will be forged with water resource agencies through this initiative. The priority for the Des Moines River Basin in the Upper Mississippi River basin, the first basin in the nation where the Office of Hydrology is installing its Advanced Hydrologic Prediction System, is recognition that links to water resource managers could be strengthened within this area -

In the past, a Water Resources Principal Research Area has considered the issue of climate change and water resources. Since the priorities for GCIP in this area have now broadened with the clarification of the GCIP mission statement by the National Academy of Sciences, a focus on hydrologic modeling and its application to water resources is now taking place in GCIP. Further, it was recognized at the GCIP Workshop for studies and modeling in the Ohio and Tennessee River basins that improvements in short and long-range weather forecasting represent the strongest tie between the GCIP research community and water resources operations, both generally and for the Ohio and Tennessee River basins in particular. This has led to some early planning for an experimental streamflow forecast capability for the two river systems.

S4. Data Assimilation

The NAS/NRC GEWEX Panel in its review of the GCIP Objectives recommended that more emphasis should be placed on data assimilation as one of the GCIP objectives.

GCIP Objective: Develop and evaluate atmospheric, land, and coupled data assimilation schemes that incorporate both remote and in-situ observations.

Based on some initial considerations, the principal areas in data assimilation for GCIP are summarized as follows:

- application of improved data assimilation techniques (e.g., 3-d variational and 4-d variational) to coupled atmospheric/surface models;

- improved algorithms that translate from observation variables to model variables and vice versa (e.g., radiative transfer models, hydrological models);

- incorporation of new data sources (which must pass the test of providing additional information over that already known from other sources and the model forecast). These may include not only new sources of atmospheric moisture information, but also process rates such as rainfall rate, streamflow, and Top-of-Atmosphere radiative fluxes, and various soil- moisture measurements; and,

- understanding of uncertainty in GCIP analyzed data sets.

S5. Diagnostic Studies

The diagnostics studies activities are directed toward deriving quantitative descriptions of the annual, interannual and spatial variability of the water and energy cycles over the Mississippi River basin.

GCIP Objective: Determine the time-space variability of the hydrological and energy budgets over the Mississippi basin.

Diagnostics studies provide a basis for evaluation of the atmospheric, land, and coupled model data assimilation schemes as well as the forecasts produced from the prediction models. The ultimate aim of the diagnostic studies research is to contribute to further improvements of seasonal to interannual climate predictions in support of water resource management.

The near term priority and strategy is to describe the water budgets over the GCIP domain through utilization of observations in conjunction with model analyses to arrive at a better understanding of the hydrologic cycle. Specific activities over the period covered in this Major Activities Plan include further investigations of the full four-dimensional continental scale water budgets based on radiosonde, wind profiler, precipitation and river discharge observations in comparison to model-based analyses with particular emphasis on the output from the regional mesoscale models producing the output for GCIP. Water budget components will also be examined over the major sub-basins of the Missippi River basin and on some of the Intermediate and Small Scale Areas used as focus study areas for GCIP. The effects of spatial and temporal sampling on evaluation of the water budgets will be examined as well as the multi-year behavior of water balance components including storage.

Energy budgets pose a more complex problem since there are no direct measurements that can be used for comparison, in particular regarding radiation terms. The near term approach will be to estimate residual diabatic heating from regional model analyses to check for consistency with other analyses and regions.

S6. Observation Enhancements and Derived Products

S6.1 Precipitation

Overall Objective: Achieve better understanding and estimation of the space-time structure of precipitation over the Mississippi River basin, including improvements in atmospheric model representation of precipitation to support improved coupled modeling.

S6.1.1 Precipitation Research Activities

Near-Term Priorities for Precipitation Research

Investigate over diverse areas of the Mississippi River basin the structure of the subgrid scale variability of rainfall as a function of storm type (e.g., cold vs. warm season rainfall, stratiform vs. convective) and propose schemes for parameterizing this variability in atmospheric models.

Assess the limits of predictability of atmospheric model precipitation as a function of scale and understand the effects of relative patterns of convective/stratiform rainfall and of subgrid scale spatial rainfall variability on rainfall prediction and on the surface water and energy partitioning via coupled modeling.

Inputs are needed on the degree of sensitivity of coupled models to rainfall spatial variability to enable precipitation investigators to assess the utility and degree to which this variability is worth resolving. Also, based on the premise that two-way coupling (atmosphere to land to the atmosphere feedbacks) will not only improve hydrologic predictions but also rainfall predictions themselves, we need collaboration on the best hydrologic modules that should be used to examine the sensitivity of rainfall predictions to this two-way coupling and determine how rainfall predictability can be improved through this coupling.

A timely provision of a range of data sets is needed (especially routine WSR-88D, GOES satellite, rain- gauge-network data, soundings and frequent observations of standard surface meteorological variables) to test the performance of atmospheric model rainfall predictions and investigate how these predictions can be further improved.

Precipitation Research Long Term Items To Be Initiated In Next Two Years

As some issues are resolved in specific settings, e.g. effect of subgrid scale rainfall variability on surface fluxes, we should move also towards the direction of extremes and especially, heavy precipitation producing systems in the Mississippi River Basin.

Also, include orography and understanding of how the resolution of orography affects rainfall predictions that determine forecasts of hydrologic balances and flooding over the whole basin, and develop methods for better use of WSR-88D scans over complex terrain (especially use of information obtained in higher elevation angle scans, and possibly modifying the scans over complex topography to take advantage of this information.)

S6.1.2 Precipitation Measurement and Analysis

Objective: Produce the best possible estimates of spatial and temporal distribution of precipitation at time increments of one hour to one month and spatial increments of four to 50 km.

Near-Term Priorities for Precipitation Measurement and Analysis

Evaluate if current precipitation products (e.g., hourly 4x4 km composites) meet GCIP requirements for atmospheric model verification studies and for analysis of space-time precipitation structures. Also work towards improving the availability and quality of WSR-88D and concurrent atmospheric observations (e.g., GOES satellite data, soundings, etc.) for GCIP precipitation research.

GCIP is making use of the national stage IV precipitation analysis being produced by NOAA/NCEP. Near-term priority improvements for this product include:

(1) - Adapt and apply Stage III-type automated quality assurance algorithms for filtering and/or "flagging" such analysis problems as anomalous propagation, bright bands, and grossly erroneous gauge reports. Utilize the rich NCEP and NESDIS centralized hourly databases of atmospheric analyses (e.g. temperature, freezing level) and satellite retrievals (e.g. cloud cover and hourly precipitation estimates) to apply filtering algorithms beyond those feasible at the local RFC.

(2) - Develop a terrain-height database for the national 4-km "HRAP" grid. Use this terrain database and known elevations of WSR-88D radar sites to identify and flag beam blockage prone regions in the Stage IV analysis.

(3) - Investigate the feasibility of a GCIP archive of operational hourly RFC Stage III precipitation analyses to build a national mosaic of Stage III for GCIP research studies.

Longer term improvements to Stage IV precipitation analysis for GCIP research which should be initiated in the next two years include:

(1) - Perform a retrospective 24-hour gauge-only precipitation analysis using the GCIP composite gauge data set. Consider applying gauge correction algorithms for wind exposure effects, etc.

(2) - At NCEP, develop a realtime "final" 24-hour gage/radar precipitation analysis by using the vastly more spatially dense set of realtime 24-hour gage reports. Merge this latter set with a derived set of 24-hour summations of the realtime hourly, 3-hourly, and 6-hourly gauge reports.

(3) - Evaluate the hourly, 3-hourly, 6-hourly, and 24-hourly precipitation gauge reports routinely available to the RFC Stage III and NCEP Stage IV analyses and develop practical and reproducible automated quality control and filtering algorithms for the gauge data.

S6.1.3 Snow Measurements

A GCIP study is underway to design techniques for correcting the in-situ snow measurements for systematic biases due to exposure and wind losses. These techniques will be used to prepare a corrected set of snowfall measurements on a daily and monthly timescale for the Enhanced Seasonal Observing Period in the Upper Mississippi River basin during Water Year 1997. Such corrections will also be applied to the same region during Water Year 1998.

The results from the snowfall measurement corrections applied to the Upper Mississippi River basin will be used in other regions of the Mississippi River basin to compile corrected snowfall measurements, and thus compile reasonably accurate in-situ precipitation measurements over the full annual hydrologic cycle.

S6.2 Soil Moisture

A validated soil moisture product will be developed for at least a portion of the Arkansas-Red River basin at a spatial scale of about 40 km and a daily temporal scale for four depths corresponding to the regional mesoscale model output archived for GCIP studies. This should start in 1997 to take advantage of the planned aircraft campaign over a portion of the ARM/CART site in June and July 1997. This assimilated product must be produced from a variety of data sources, including output from hydrologic models driven by measured meteorological data, in situ soil moisture observations, and remote sensing.

A large scale ( ~ 10,000 sq km) aircraft remote sensing data collection campaign to provide a relatively long term data set approaching the type of data one would get with satellite remote sensing. Selecting and carrying out a series of imbedded experiments that address issues of model derived soil moisture, scaling and uncertainties.

Comparisons of actual model estimates of soil moisture (spatially and temporally) with measured values. The measured values may come from the index stations, existing data collection programs (Little Washita, Illinois State Water Survey, FIFE, etc.), or from airborne remote sensing campaigns. The objective of these comparisons is to evaluate which models may be able to use measured data and what data might be used. A subsidiary task is to modify existing models to use measured data.

Longer term items that should be started in 1997 include:

- Analysis of existing remote sensing data (RADARSAT, ERS-1&2, SAR , SCAT,and SSM/I) to estimate the information content that can be used to achieve the goals for the soil moisture contributions to GCIP.

- Develop procedures to extrapolate or assimilate point data to basin and regional scales.

S6.3 Land Surface Characteristics

The goal of land surface characterization research within GCIP is to improve the quantitative understanding of the relationships between model parameterizations of land surface processes and land surface characteristics, while also facilitating the development, availability, evaluation, and validation of multiresolution land surface data sets required for land surface process research in GCIP.

S6.3.1 Near- Term Priorities for Land Surface Characteristics

Facilitate the use and evaluation of existing land surface characteristics data sets at the continental scale. Although several key land surface characteristics data sets are now available for GCIP researchers, considerable efforts are still needed to apply and test these new data sets. Specific efforts are needed to expand the use of these land surface characteristics data bases. For example, atmospheric modelers need to incorporate the new soils data base into their analysis, especially within the land surface parameterizations for mesoscale models.

Evaluation and/or validation of these land surface data sets by the data-providers and GCIP researchers is needed. In most cases, these data sets are aggregated to a coarser resolution for use in the land surface parameterizations, for example, 20-50 km grid cells for continental scale analysis. The method of aggregation is typically based on the use of the "predominant" class within the model grid cell.

Deliver enhanced land surface characteristics data sets and place them on-line for easy access. The NASA- led ISLSCP/GEWEX Initiative Number 2 could provide enhanced biophysical land cover land cover parameters at a 0.5 degree grid size by late 1997.

Use GCIP findings to assess the new levels of understanding concerning the role of land surface characteristics in land surface parameterization research.

S6.3.2 Land Surface Characteristics Long-Term Items to be Started in the Next Two Years

Conduct land surface characterization research on rules for aggregation of land surface data in grid cells, scaling of point processes to the landscape level, and investigation of multiresolution interrelationships among land cover, soils, and topographic characteristics data sets.

Conduct advanced land surface characterization research using physically-based models and remote sensing algorithms. For example, atmospherically corrected satellite reflectance data are needed to overcome the adverse and variable affects of atmospheric water vapor and aerosols on surface reflectance retrievals. Lack of such atmospheric corrections, as well as bidirectional reflectance distribution function (BRDF) corrections, significantly degrade the use of existing satellite reflectance data to calculate vegetation greenness indexes that can be reliably used to study intra- and inter-annual variability of vegetation greenness.

Develop plans to review and incorporate remote sensing data sets that will become available following the launches of the NASA-led Earth Observing System (EOS) AM1 Platform and Landsat 7 during the mid-1998 time-frames. The advanced scientific algorithms under development by the MODIS Land Science Team are of particular relevance to GCIP. In addition, current plans call for near-synchronous orbits of the EOS AM1 and Landsat 7 satellite systems, thereby creating a substantial potential for the complementary operation of coarse- and high-resolution satellite data of interest to some GCIP researchers.

S6.4 Streamflow/Runoff

Over Objective: To improve the description of the space-time distribution of runoff over the GCIP study area and to develop mechanisms for incorporation of streamflow measurements in the validation and updating of coupled land/atmosphere models.

Streamflow is determined from measurements of stream stage at a stream-gauging station. Runoff is the spatially distributed supply of water to the stream network which cannot be measured directly. Both surface and sub-surface components are part of runoff. A delay is also inherent between runoff initiation and the time when the runoff reaches a stream-gauging station. This delay varies spatially depending on the distance to the gauge and on how much runoff is occurring.

Near-Term Priorities for Streamflow/Runoff

Extend the available historical data base for unregulated basins at the intermediate and small scales (10 to 1000 km2) in the Arkansas-Red River basin by updating from 1988 the active streamflow to develop and demonstrate regionalization methods for the estimation of hydrologic model parameters. In addition to allowing the estimation of the land-surface model parameters these data are needed for the development of runoff routing parameters and gridding runoff.

Develop naturalized streamflow records at key locations in the Arkansas-Red River basin up to the current time to enable the validation of the atmospheric model predictions. Key locations would include the Red River at Shreveport and the Arkansas River at Little Rock, being the largest basins which can be feasibly considered.

Test a method for estimating gridded runoff data for the Arkansas-Red River basin to enable the direct validation of atmospheric model runoff predictions.

S6.5 Clouds and Radiation

As new and improved satellite products for GCIP are developed and brought into production, it is necessary to validate and tune the algorithms to provide the most consistently accurate quantities. This requires operating a parallel system that produces the satellite products offline using the same data and the same algorithms, so that the algorithms can be modified and tuned, and the results compared with ground truth. There are current problems with the retrieval of cloud cover and insolation over a snowcovered surface that must be addressed through tuning with a parallel system.

Radiation budget components, cloud amounts and heights, and surface temperatures from the regional scale Numerical Weather Prediction models must be compared with satellite observations of the same quantities. Radiation and cloud output from the Eta model will be collected from selected forecast times and remapped into the resolution and map projection of the GOES satellite products and provided for comparison studies. The degree of agreement, conditions under which the model output and the observations are quite different (season, snowcover, bare soil, etc.), and the degree to which the diurnal cycle in observed variables are replicated by model output are both needing evaluation.

The cloud and radiation models in the Eta and other regional and global models need improvement and research to upgrade them needs to be started in the next two years if GCIP is to benefit from the research results. Such topics as the interaction of cloud and radiation fields and surface variability within a grid box, use of better cloud parameterization, and cloud resolving models are all appropriate for research. The specific area of research may be dictated by the results of the comparison of model output with observations.

S7. Data Collection and Management

GCIP Objective: Provide access to comprehensive in-situ, remote sensing and model output data sets for use in GCIP research and as a benchmark for future studies.

As noted in Figure S-2, the GCIP Enhanced Observing Period started on 1 October 1995 and will continue for five years. The data collected during each year will be compiled into a number of standard and custom data sets. The data collection periods for the GCIP standard data sets are shown in Figure S-3. These data sets will be published on CD-ROMs for distribution, especially to international scientists interested in GCIP. Increasingly, the national GCIP investigators are making use of the on-line GCIP data services available through the World Wide Web at the URL address:

http://www.ncdc.noaa.gov/gcip/gcip_home.html

Figure S-3 Compiled and Planned Standard Data Sets for GCIP Research.

The initial focus of GCIP on the warm season processes in the annual hydrological cycle has produced data sets for three different periods in the LSA-SW(see Figure S-4). The data collected during the Enhanced Seasonal Observing Period in 1996 (ESOP-96) is scheduled to be compiled into a standard data set by June 1997. The types of data which comprise the ESOP-96 are described in the Tactical Data Collection and Management Plan for the 1996 Enhanced Seasonal Observing Period (ESOP-96).

Figure S-4 The LSA-SW Encompasses the Arkansas-Red river basin. GCIP Focus Study Areas in the LSA-SW Include the CART/ARM Site Operated by the Department of Energy and the Little Washita Watershed Operated by the USDA/Agriculture Research Service.

The data collection activities for Water Years(WY) 1997 and 1998 will include the cold season in the Upper Missippi River basin identified as the LSA-NC in Figure S-5. The details of the data to be collected during the first period are given in the Tactical Data Collection and Management Plan for the 1997 Enhanced Seasonal Observing Period (ESOP-97).

Figure S-5 The LSA-NC encompasses the Upper Mississippi River basin. GCIP Focus Study Areas in the LSA-NC include the Des Moines River and Minnesota River basins outlined in the western part of the basin and the State of Illinois.

The data sets for the whole of the Mississippi river basin will remain largely distributed among different data centers through WY 1998. It was shown in Figure S-3 that composite data sets for the Mississippi River basin are planned to be compiled beginning in 1999.

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TABLE S-1. Types of Observations in each Layer of Near Surface Observation Data Set
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1. Boundary Layer Z < 3000 meters

1.1 Temperature profiles
1.2 Water vapor profiles
1.3 Wind profiles
1.4 Clouds

2.1 Temperature, Specific Humidity, Wind Component, and Surface Pressure
U & V component wind speed at 10 m
Temperature at 2 m
Specific humidity at 2 m
Surface pressure
2.2 Surface momentum flux
Surface U wind stress
Surface V wind stress
2.3 Surface sensible and latent heat fluxes
Surface latent heat flux
Surface sensible heat flux
Soil heat flux to Surface
2.4 Surface skin temperature
2.5 Precipitation (including snow)
2.6 Surface Radiation
Downward shortwave
Upward shortwave (albedo)
Downward longwave
Upward longwave
Net radiation (measured)
Photosynthetically Active Radiation (PAR)
2.7 Surface and ground water
2.8 Vegetation type and characteristics
2.9 Site Description

3.1 Soil moisture (profiles)
3.2 Soil temperature (profiles)
3.3 Soil physical and hydraulic properties
3.4 Wilting point
3.5 Rooting zone
3.6 Field capacity

Note: A hard copy of the complete Plan is available in two parts:

PART I - RESEARCH
PART II - Data Collection and Management

e-mail- gcip@ogp.noaa.gov
telephone: (301) 427-2089 ext 511
mail:

GCIP Project Office
NOAA/OGP; Suite 1225
1100 Wayne Avenue
Silver Spring, MD 20910