In the context of the GCIP, a coupled atmospheric-hydrologic model is defined to be a model or combination of models which simultaneously represents both atmospheric and hydrological processes, which can operate in predictive mode without the need to specify variables or exchanges at the interface between the two model components, and which can benefit from the assimilation of data to specify that interface. This context provides the framework for the GCIP Objective: Develop and evaluate coupled hydrologic/atmospheric models at resolutions appropriate to large scale continental basins.

5.1 General Approach

The implementation of model development in GCIP has followed two paths as described in the GCIP Implementation Plan (IGPO, 1993) and shown in Figure 5-1. On the "research" path are the longer term modeling and analysis activities needed to achieve the GCIP coupled modeling research goal - To identify and understand the coupled processes that influence predictability at temporal time scales ranging from diurnal to seasonal and spatial scales relevant to water resource applications , and to develop a coupled model which can be validated (at these scales ) using data for the Mississippi River basin. Research is focusing on determining , understanding and modeling those processes which are demonstrably important in coupling atmospheric and hydrological systems, rather than those processes which are separately important within these two systems.

An "operational" path was started in 1993 during 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.


Figure 5-1.  Strategy framework for implementing GCIP.


5. 2 Coupled Modeling Research

The GCIP coupled modeling research is predicated on the hypothesis that the creation of regional-scale coupled models which simultaneously represent both relevant atmospheric and the land-surface processes, and the validation of these models against observations from GCIP, will improve our ability to:
(a) predict variations in weather and climate at time scales up to interannual; and

(b) interpret predictions of weather and climate in terms of water resources at all time scales.

GCIP is focusing on those research activities which create, calibrate, and apply coupled models of the atmospheric and hydrologic systems with priority given to research to improve climate prediction and to improve hydrological interpretation of meteorological predictions at the above time scales. The GCIP coupled modeling research is focusing on the program elements that address the four scientific questions and priority needs given in Table 5-1. These issues and planned research activities are described further in the Major Activities Plan (IGPO, 1997).

5.3 Coupled Modeling Operations

Progress in the representation of land-atmosphere interactions over the last two decades has been sufficient to motivate several operational modeling centers (for example, the National Center for Environmental Prediction, the European Centre for Medium Range Forecasting, and the Japanese Meteorological Center) to implement and benefit from modern-era, multi-layer soil-vegetation- atmosphere transfer schemes. Planetary, continental, and regional atmospheric circulation patterns in such assimilation systems are constrained near truth by the assimilation of atmospheric observations. Nonetheless, the implementation of improved representation of hydrologic-atmospheric interactions has undoubtedly improved the quality of the precipitation and low-level temperature analysis products provided by data assimilation systems.

For the past five years there has been an extensive effort to acquire the model output from several operational/experimental centers from a range of operational models of varying resolution, physics and data assimilation systems. GCIP is concentrating on three regional mesoscale models (IGPO, 1995):

The participation by the operational centers in providing regional model output for GCIP leads to a mutually beneficial relationship. The principal benefit to GCIP is to provide a measure of the inter-model variability of the outputs from the different regional models which can also be related to the global model output from the operational centers. GCIP can provide benefit to the operational centers by enabling them to make use of the enhanced data sets to calibrate and validate the model data assimilation and forecast systems.
The regional mesoscale models are supporting GCIP research in the following manner:
  • Provide model assimilated and forecast data products for GCIP diagnostic studies including energy and water budget studies.
  • Table 5-1: Scientific Agenda for the GCIP Coupled Modeling Research
    1.   " To what extent is meteorological prediction at daily to seasonal time scales sensitive to hydrologic-atmospheric coupling processes?" - the priority research issues to be addressed by GCIP are:
  • The Evidence for, and the Mechanisms Involved in, Seasonal Predictability
  • The Relative Importance of Hydrologic-Atmospheric Coupling over an annual cycle
  • The Need to Represent Diurnal Variations in Surface Energy Fluxes
  • 2.   "To what extent can meteorological predictions be given hydrological interpretation?" - the priority needs in GCIP are for:
  • Evaluation of Seasonal-to-Interannual Predictions
  • Definition of the Predictive Products Required by Hydrologists 
  • 3.   "How can models of relevant hydrologic-atmospheric coupling processes be improved to enhance meteorological and hydrological prediction?"- the priority needs for GCIP are:
    For Precipitation Processes
    • Improved Parameterization of Convective Precipitation in Atmospheric Models
    • Statistical Analyses of Subgrid Scale Precipitation
    • Research into Cold Season Precipitation Issues
    • Improved Understanding of Topographic Influences on Precipitation
    For Soil Moisture Processes
    • Improved and Extended Soil Moisture Measurement
    • Coupled Modeling of the Effect of Soil Moisture Heterogeneity on the Atmosphere
    • Improved Parameterization of Hydrologic Submodels
    For Snowcover and Other Cold Season Processes
    • Snow Cover
    • Subgrid Interactions
    • Hydrologic Interactions
    For Biospheric Processes
    • Vegetation Influences on Hydrologic Cycle
    4. "To what extent is model parameter estimation for the hydrologic part of coupled models basin dependent? - the priority needs for GCIP are:
    • Evaluate the Transferability of Existing Parameter Estimation Techniques
    • Improved and Extended Parameter Estimation Techniques
    The regional models now running operationally (NCEP/Eta and CMC/GEM) will be upgraded with numerous improvements during the next several years. The GCIP investigators need to be aware of these plans for improvements and the schedule being followed to incorporate these improvements into the operational models. The experimental MAPS model will also be upgraded during the next several years. Projected improvements to each of the regional models is described in the Major Activities Plan (IGPO,1997).

    5.4 Coupled Hydrologic/Atmospheric Modeling in the LSA-NW

    The GCIP LSA-NW is defined by the Missouri River basin, an area encompassing 1.36 million km2. It is physiographically, ecologically, and climatically diverse. Regional hydroclimatic processes and regimes within the basin are affected by many local variables, including topographic gradient and aspect, drainage pattern and density, soil texture, permeability, irrigation, groundwater and water storage capacity, soil moisture, and land-cover. From the perspective of coupled atmospheric/hydrologic modeling, the Missouri River Basin, compared to the other three GCIP LSA areas, features the
    following unique hydroclimatic settings: The general goal for the GCIP coupled modeling activities is to identify and understand the coupled processes that influence predictability at temporal scales relevant to water resource applications, and to develop coupled models, which can be validated at these scales using data from the Mississippi River Basin.  In this context, the overall research theme proposed for coupled modeling in the LSA-NW region is:
    "To diagnose and skillfully represent the significant regional effects of land atmosphere interactions on the hydrometeorology and hydroclimate of the Missouri River Basin on spatial and temporal scales relevant for hydrologic applications and water resources".
    The regional effects include terrain characteristics, soil moisture, snow, land-use, vegetation cover, and other factors relating to the energy balances at the surface, and particularly, the Bowen ratio.  The latter represents the partition of sensible and latent heat fluxes at the surface, and is a fundamental aspect needed to correctly represent land surface-atmosphere processes.

    The LSA-NW presents some complex scientific issues, and a number of opportunities and challenges for coupled modeling research.  For example, great strides have been made in developing and validating land-surface and hydrology models for the previous LSA regions, and implementing some land-surface models, both in off-line and coupled mode, for the LSA-NW area in order to address the issue of transferability of models among different hydroclimate regions, and to provide insights regarding needed improvements of land-surface and coupled models.  This is also true for other coupled model sub-components such as cloud, precipitation and the parameterization of radiative processes,  In order to achieve the overall scientific goal, four research priorities are identified for the LSA-NW area study:

    1)  Evaluate and improve the representations of the effects of seasonally varying land-use, soil moisture, vegetation cover, and other soil characteristics forcing and their spatial heterogeneity in regional coupled models.
    2)  Determine and model the multiscale responses of complex terrain on the regional hydroclimate at seasonal and diurnal time scales.
    3)  Examine the models' surface energy budgets to evaluate the performance of the parameterizations in physical terms.
    4)  Characterize and model the temporal and spatial distribution of snow cover including its accumulation/melt and the impact of frozen ground on atmosphere/hydrology interactions.

    In this context, the following research activities are encouraged for the GCIP LSA-NW region:

    (i)  Develop and validate coupled model subcomponents and macro-scale hydrologic models in both stand-alone and coupled modes.  The emphasis needs to be on improving the precipitation and runoff processes related to spring snow accumulation and snowmelt.  This includes the land-surface/hydrology model components that simulate snow accumulation and melt in the LSA-NW.  Evaluations of the performance of these model components would constitute a relatively stringent test of the transferability and the applicability to an overall semi-arid environment with a large annual cycle, complex terrain, and large spatial and year-to-year variability.

    (ii)  Conduct coupled model numerical experiments at large-scales to understand the effects of terrain and seasonal evolution of various land-surface forcing components (e.g., snow cover, ground water, irrigation, soil moisture, land-use, vegetation cover, etc.)  on mean seasonal and diurnal land-surface/atmosphere interactions.  One important aspect concerns the interactions between the land-surface process (e.g., soil moisture, land-use, and their heterogeneous spatial distribution) and the formation and evolution of mesoscale convective complexes.  In addition, it appears necessary to evaluate the effects of coupled model resolution on seasonal and diurnal land-surface/atmosphere interactions in complex terrain regions.

    (iii)  Assess and compare the regional performance of operational mesoscale models in terms of energy interactions at the surface.  Despite the important advances achieved in coupled modeling, deficiencies can be detected in diagnostic studies and through careful comparisons with observations.  Timely evaluations can contribute to the improvement of the quality of GCIP's archives by reducing the chances of erroneous information being introduced in the data sets.

    (iv)  Conduct model and diagnostic case studies at ISA/SSA scales for several anomalous occurrences.  This should include studies of the physical processes and extreme events using extensive data collected in these ISA/SSA areas.

    (v)  Develop and evaluate techniques for assimilating new remote sensing products and other data.  The LSA-NW will be the first GCIP LSA study-area to have access to new satellite products including the Landsat-7 detailed land-cover and vegetation mapping, and the suite of surface and atmospheric observations provided by the Earth Observing System (EOS) AM-1 platform.  Also, it is important to explore an appropriate approach for the utilization of the newly available high-resolution satellite snow product for the initializing the snow cover and depth in coupled regional models.

    (vi)  Investigate orographic-precipitation processes during the warm season, including orographic uplift of an airmass over the U.S. Great Plains during large-scale easterly flow conditions.  Accurate forecasting of water resources requires better definition of the location of precipitation than is possible with the current numerical weather prediction models.  While research related to improving the current precipitation process in operational models must continue, exploratory research is also required to evaluate the value of successively nested coupled models (with resolution around 2-3 km) as a possible mechanism for applying seasonal-to-interannual forecasts to water resource issues.

    (vii)  Develop a better understanding of cold season precipitation and hydrology processes including snow and frozen-ground physics under the influence of complex terrain.  Much of the critical spring runoff in the LSA-NW occurs as a result of snowmelt.  The central issue is to improve the coupled model precipitation forecast skill so that it gives an accurate measure of the temporal and spatial distribution of snowfall.  It is important to determine the representativeness of rain-gage measurement of snowfall and develop and test methods for combining surface observations of snow cover and information from remote-sensing observations.

    (viii)  Assess and improve runoff models in coupled atmospheric/hydrologic models for sub-basins under the influence of complex terrain.  This includes validation of runoff-streamflow estimates fro use by water resource managers to assess the amount and timing of water resources and the soil moisture available for subsequent evaporation, it is also necessary to document, understand, and model the partition of precipitation including snowfall into runoff and soil water storage when snow and ice melts.

    (ix)  Consider and if feasible initiate groundwater modeling studies for the High Plains and/or Madison aquifers.  Interactions between surface soil storage and groundwater may be important fractions of the water budget in wetlands and in aquifer recharge zones.  This type of study, however, requires consistent groundwater observations.