Estimation of Large-Scale Evaporation Using Remote Sensing III
Presiding: M Jasinski, NASA Goddard Space Flight Center; B Kustas, USDA Hydrology and Remote Sensing Laboratory
H32B-01 10:30h
Global Evapotranspiration Estimates using the Land Information System
The Global Land Data Assimilation System (GLDAS) is being used extensively by the research community for studies ranging from climate and weather forecast initialization to the improvement of hydrologic decision support systems. The goal of the GLDAS is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes (Rodell et al., 2004). The GLDAS software, which has been streamlined and parallelized by the Land Information System (LIS) software infrastructure, drives multiple, offline (not coupled to the atmosphere) land surface models, integrates a huge quantity of observation based data, executes on a global domain at high spatial resolutions (2.5° to 1 km), and is capable of producing results in near-real time. A vegetation-based "tiling" approach is used to simulate sub-grid scale variability, with a 1 km global vegetation dataset as its basis. Soil and elevation parameters are based on high-resolution global datasets. Observation-based precipitation and downward radiation products, as well as output fields from the best available global coupled atmospheric data assimilation systems, are employed to force the models. The international research community is using GLDAS to help assess global land surface conditions as part of the Global Energy and Water Cycle Experiment (GEWEX) Coordinated Enhanced Observing Period (CEOP), and GLDAS has been identified as NASA's land surface contribution to the Joint Center for Satellite Data Assimilation (JCSDA) enabling better use of remote sensing data in operational weather and climate forecasting. The global 1km resolution capability of LIS allows it to take advantage of the latest satellite observations, such as MODIS leaf area index and surface temperature, at their full resolution. In this presentation we will critically evaluate global LIS-based evapotranspiration estimates at various time and space scales, and demonstrate its usefulness in various applications.
http://lis.gsfc.nasa.gov
H32B-02 10:45h
Global Evaluation of a MODIS-based Evapotranspiration Product
Both observations and theoretical simulation show that the surface hydrologic condition and vegetation cover have a major control on surface energy flux patterns. Remote sensing techniques provide a basis for assessing these controls, and the subsequent patterns of surface fluxes at scales ranging from kilometres to regional and, potentially, to global scales. These remotely sensed data, and their derived hydrologic variables can be compared to and combined with hydrological models to estimate the surface water and energy balances at continental to global scales. In this presentation, regional estimates of the evapotranspiration, based on a combination of remote sensing measurements and operational surface observations, will be presented using the Surface Energy Balance System. Results will be obtained for a diverse set sites identified as part of the GEWEX Global Energy and Water Experiments (GEWEX) Coordinated Enhanced Observation Period (CEOP), and represent a range of hydroclimatologies and surface condition making them ideally suited to the assessment of routine retrieval of remote sensing based evapotranspiration. Surface temperature and vegetation information is based on MODIS satellite retrievals and are used in conjunction with the Global Land Data Assimilation (GLDAS) project data to estimate daily values of evapotranspiration. These estimates are compared with both tower flux data and GLDAS derived estimates forcing.
H32B-03 11:00h
Potential of Satellite-Based Models for Land Surface Evapotranspiration Estimation
Use of satellite remote sensing data for the estimation of surface evapotranspiration (ET) is emerging as a promising approach with a range of application potentials. Unlike traditional point-based approaches, some of these satellite-based approaches have been shown to have bounded error. This is a significant advantage of such ET estimation approaches compared to ground-based or hybrid (i.e. combining ground and remote sensing data) approaches, particularly over large heterogeneous domain where representation of key distributed parameters from ground-based observations are questionable. For clear days, main components relevant to surface ET estimation such as evaporative fraction (EF) and net radiation (Rn) can be derived using data from AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Use of temporal stability of EF and a mathematically convenient and physically realistic, at least for clear sky days, diurnal model for Rn may allow us to get a reasonably accurate estimates of daily ET over large heterogeneous areas. Extension of these results for cloudy days and related challenges will be discussed with particular examples from South Florida and Southern Great Plains using data from MODIS and AVHRR.
H32B-04 11:15h
Interannual Variability of Tropical Ocean Evaporation: A Comparison of Microwave Satellite and Assimilation Results
Remote sensing methodologies for turbulent heat fluxes over oceans depend on driving bulk formulations of fluxes with measured surface winds and estimated near surface thermodynamics from microwave sensors of the Special Sensor Microwave Imager (SSM/I) heritage. We will review recent work with a number of SSM/I-based algorithms and investigate the ability of current data sets to document global, tropical ocean-averaged evaporation changes in association with El Nino and La Nina SST changes. We show that in addition to interannual signals, latent heat flux increases over the period since late 1987 range from about .1 to .6 mm / day are present; these represent trends 2 to 3 times larger than the NCEP Reanalysis. Since atmospheric storage cannot account for the difference, and since compensating evapotranspiration changes over land are highly unlikely to be this large, these evaporation estimates cannot be reconciled with ocean precipitation records such as those produced by the Global Precipitation Climatology Project, GPCP. The reasons for the disagreement include less than adequate intercalibration between SSM/I sensors providing winds and water vapor for driving the algorithms, biases due to the assumption that column integrated water vapor mirrors near surface water vapor variations, and other factors as well. The reanalyses have their own problems with spin-up during assimilation, lack of constraining input data at the ocean surface, and amplitude of synoptic transients. A number of recent model integrations with specified SSTs are available, including "Climate of the 20th Century" integrations as well as integrations from more recent versions of the NASA GEOS climate model. These do not suffer from the "spinup" problem and evaporation from these integrations is compared to the microwave estimates and to the NCEP reanalysis. We will also discuss the potential for improving retrievals of the near-surface specific humidity (qa) and air temperature (Ta) needed for flux calculations through the addition of moisture and temperature profile data from the SSM/T-2 and AMSU-A and -B sounders. Incorporation of information on the vertical moisture structure has enabled improved retrievals of qa in cases where the presence of moist layers aloft alters the relationship between the surface humidity and total column water vapor content. Development of an improved satellite-based qa algorithm combining SSM/I and SSM/T-2 data has enabled a reduction in the rms error in qa to 1.06 g/kg from a value of 1.12 g/kg for an algorithm incorporating only SSM/I data. Further inclusion of data from the AMSU-A sounder leads to an additional reduction in the error to 0.83 g/kg. We will assess the current ability to quantify regional and global ocean evaporation changes, examine promising improvements afforded by additional microwave channels, and put these in the context of similar challenges to precipitation measurement and the global water cycle in general.