Global Land Data Assimilation System (GLDAS)
H. K. Beaudoing
October 26, 2012 15:25:41
Description of Problem
Land surface states and fluxes influence the weather and climate through exchanges of energy, water, and momentum between land and atmosphere. The energy and water stored in land present persistence on diurnal, seasonal, and inter-annual time scales. Because these conditions (e.g. soil moisture, temperature, and snow) are integrated states, biases in forcing data (i.e. meteorological and land characteristics) and parameterizations (i.e. models) lead to incorrect estimates. We are working on deriving accurate surface conditions at global, high spatio-temporal resolutions, and near-real time to help improve weather forecast and prediction skills, water and energy budget studies, and water resource management applications.
Scientific Objectives and Approach
We work with offline land surface model (LSM) simulations (uncoupled to atmosphere) using the observation based input that are ground-based, remote sensing, and/or reanalysis/analysis fields data. By using such data, we constrain the model states in two ways; one is through realistic forcing fields and the other is through data assimilation. One of the primary objectives was to develop a modeling framework that allows users to run multiple LSMs using various combination of forcing and land characteristic datasets. We do not develop the LSMs ourselves, but rather, we focus on optimizing the configuration (e.g. merge and refine input data) and developing supplemental capabilities (e.g. irrigation, data assimilation).
We continue to serve GLDAS products from NASA/GSFC’s Data and Information Services Center (DISC). The products are updated every month to extend to delayed present. The GLDAS users have nearly doubled and number of files accessed has increased about eight times more than last year. On average about 54 users access GLDAS data, downloading more than 56 K files per month.
We are making progress on the production of GLDAS version 2 dataset. The GLDAS2 is forced by a climatologically consistent meteorological dataset of Princeton University, with the updated versions of LSMs, and extends from 1948 to present. Because the Princeton forcing has lag of more than 2 years, we will have a branch run that covers from 2001 onwards to delayed present. As a part of Community Land Model (CLM) upgrade, new model parameters have been created based on MODIS datasets for globe at 1 km resolution. In addition to the plant functional types data created last year, leaf area index (LAI) and stem area index (SAI) monthly climatology, land units (lake, wetland, and urban), and soil color data were completed. Evaluation of Catchment model and debugging of Variable Infiltration Capacity (VIC) model are ongoing. For the branch run forcing, we disaggregated the GPCP Daily precipitation data to 3 hourly using the NASA/MERRA and NCEP/GDAS model outputs for 1996/10-2009/08. A 1 degree NOAH model simulation has completed from 1948 to 2006 and is published at the DISC.
We have developed irrigation schemes for multiple cropping and rice paddy. Based on MIRCA2000 data, the frequency and timing of growing season, type of crops, and whether irrigated or rain fed were identified. The schemes are based on the crop demand and compute the amount of water to irrigate. A simulation was carried out over the Southeastern Asian domain and evaluated against the FAO’s water use per country reports. The irrigation amount predicted agrees fairly well with the reports, however, we need more validation with in-situ measurements of fluxes and soil moisture to further optimize the schemes.
We are leading a study on water and energy cycle climatology with the numerous members of the NASA Energy and Water cycle Study (NEWS) climatology group. In this study, we are working on establishing the current “state of the global water/energy cycle”, by using modern, observation–integrating products and associated error-analyses. We are developing a monthly climatology of water and energy cycle components for each continental and oceanic to global scale region. Gathering and integration of data provided by the team members, and an initial analysis on annual, global scale is completed.
Other Publications and Conferences
Beaudoing, H. K., M. Rodell, and M. Ozdogan, 2010: Towards global simulation of irrigation in a Land Surface Model: multiple cropping and rice paddy in Southeast Asia. Western Pacific Geophysics Meeting, Taipei, Taiwan, June 22-25, 2010.
Fang, H., H. K. Beaudoing, D. M. Mocko, M. Rodell, W. L. Teng, and B. Vollmer, 2010: Terrestrial Hydrological Data from NASA’s Hydrology Data and Information Services Center (HDISC): Product, Services, and Applications. ASPRS Annual Conference, San Diego, CA, April 26-30, 2010.
Rodell, M., T. L’Ecuyer, H. K. Beaudoing, and the NEWS Water and Energy Cycle Climatology Team, 2010: The NEWS Water and Energy Cycle Climatology Project. AGU 2010 Fall Meeting, San Francisco, CA, December 13-17, 2010.
Rui, H., H. K. Beaudoing, D. M. Mocko, M. Rodell, W. L. Teng, and B. Vollmer, 2010: New and Improved GLDAS and NLDAS data sets and data services at HDISC/NASA. AGU 2010 Fall Meeting, San Francisco, CA, December 13-17, 2010.