"Understanding our global environment and our role in it is the first step toward living in better harmony with nature."

Reports to the Nation: Our Changing Planet

GAPP Overview

Mission:  To demonstrate skill in predicting changes in water resources on time scales up to seasonal and annual, as an integral part of the climate system.

Methodology:  The GAPP objectives will be met by an integrated approach of modeling and observations.  Modeling efforts include land surface models (LSMs), general circulation models (GCMS), regional climate models (RCMs), hydrological models, and water resources management reservoir models.  Models are also used to provide land data assimilation and reanalysis products.  Both in situ and remote sensing are used in GAPP research.  In situ measurements include standard meteorological station data and special flux tower and soil moisture observations, while remote sensing includes measurements from a wide range of sensors on a number of satellites.  Satellites measure temperature and moisture profiles, precipitation, cloud properties, and land surface characteristics like vegetation.

Predictability in Land Surface Processes:  GAPP is studying land memory processes including:

• effects of topography on convective precipitation and horizontal flow within catchments

• role of snow/ice and frozen soil in coupled and uncoupled models

• the seasonal cycle of snow and soil moisture

• soil moisture initialization

• heterogeneous vegetation cover and the seasonal cycle of vegetation in soil-vegetation-atmosphere-transfer schemes (SVATS).

Hydrometeorology of Orographic Systems:  Studies of thermal and dynamical effects of the mountains in the western Cordillera on the cold-season hydrological cycle, require nonhydrostatic and prognostic cloud microphysics.  This component involves both:

• large-scale flow and mesoscale processes

• effects of topography on ENSO episodes

• lake effects on mesoscale circulation, such as those related to the Great Salt Lake

• effect of maritime mountains along the West Coast

• microphysical processes in mountainous regions.

Predictability in Monsoonal Systems:  In examining temporal and spatial variability of the warm-season North American monsoon system (NAMS),  special attention will be paid to:

• role of the Great Plains Low Level Jet (GPLLJ) and the Gulf of California Low Level Jet (GCLLJ)

• relative roles of the land surface and the ocean on seasonal variability

• understanding the mean climate as well as the spatial and temporal climate variability of the monsoon region.

Integration of Predictability Into Prediction Systems:  The GAPP approach involves both ensemble downscaling from global atmosphere-ocean-land models to atmosphere-land models and hydrological models, as well as land, atmosphere, and ocean data assimilation throughout the process.  The approaches will include coupled atmosphere-land-ocean modeling, spatial downscaling using regional climate models (RCMs) and hydrological models, analysis of ensemble runs, and global and regional land data assimilation systems including soil moisture, soil temperature, and snowpack.

Testing of Models in Special Climate Regimes:  Model transferability will apply models from data rich to data sparse regions and across different climate zones and times scales.  The purpose of these studies is to increase understanding of the land surface and relevant feedbacks and timescales with respect to the regional and larger-scale climate system.  Components include:

• relatively simple geographic region without major topography such as the Mississippi River basin

• complex geographic regions, such as the area around the Baltic  Sea

• neutral geographic regions, such as the region of the Niger River basin in West Africa

• SAGE (Saskatchewan and surrounding Area GEWEX Experiment), in the Canadian Prairies

• La Plata River Basin in South America.

CEOP: Data and Studies for Model Development:  The Coordinated Enhanced Observing Period aims to acquire datasets and initiate modeling  studies towards the goal of improving model transferability.  CEOP will run from 2001-2005, with the data acquisition period from 2001-2003.  Specific CEOP research objectives include the role of anomalous heat sources and sinks over land and how they are connected from one area to another.

Use of Predictions for Water Resource Management:  This component will assess: 

• predictability of the hydrological cycle

• how to apply hydrology models at different spatial scales

• coupled land-atmosphere modeling for hydrological prediction

• biases in the models

• improvements in model strategies for prediction

• transfer of information from coupled land-atmosphere modeling, land data assimilation, and ensemble forecasts to the user community.