H23D-1144 1340h
Towards an Integrated Global Water Cycle Observations (IGWCO) Strategy
The Integrated Global Observing Strategy Partnership (IGOS-P), which consists of space agencies (represented by the Committee on Earth Observing Satellites) and international programs, adopted water as a priority in 2001. Subsequently, in November 2003, it adopted a Global Water Cycle Observations theme report and now is planning follow-on activities. The Integrated Global Water Cycle Observing (IGWCO) strategy provides an international framework for guiding decisions on priorities and strategies regarding water cycle observations for: a) monitoring climate variability and change; b) effective water management and sustainable development of the world's water resources; c) societal applications for resource development and environmental management; d) specification of initial conditions for weather and climate forecasts, and e) research directed at priority water cycle questions. It also promotes strategies that facilitate the processing, archiving and distribution of water cycle data and products. The IGWCO report contains a number of recommendations aimed at improving water cycle observations and products and supporting the further development of the theme. Since November 2003, a number of steps have been taken to develop a plan for implementing the theme. This implementation plan has identified activities and studies related to the Coordinated Enhanced Observing Period (CEOP), the Global Water System Project (GWSP), and the development of integrated precipitation and soil moisture products. Other activities under consideration involve building the capacity of developing countries to make measurements and analyze global water cycle variables thereby strengthening their ability to manage national water resources. The purpose of this presentation is to inform the scientific community of these activities and to solicit advice and assistance in the implementation of the strategy.
H23D-1145 1340h
Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Data Products and Browse Images at the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC)
The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) was launched aboard NASA's Aqua Satellite on 4 May 2002. With six instruments aboard, the Aqua Satellite travels in a polar, sun-synchronous orbit. AMSR-E is a multichannel passive microwave radiometer that is capable of measuring geophysical variables in the global water cycle, such as snow, sea ice, sea surface temperature, precipitation and soil moisture, providing finer spatial resolution than previously possible with spaceborne microwave radiometers. The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) archives and distributes all AMSR-E standard products, including Levels 1A, 2, and 3 data. This poster provides an overview of each of the AMSR-E data products, including browse images. For more information about AMSR-E data products available from NSIDC, please see http://nsidc.org/data/amsr.
http://nsidc.org/data/amsr
H23D-1146 1340h
Glacier Fluctuations in the Western Himalaya: Multi-temporal Assessment Using Multi-sensor Satellite Imagery
Alpine glaciers are retreating and downwasting in many mountain environments. Systematic and quantitative assessments are sorely needed, as regional mass-balance trends are not known, and many glaciers may disappear before we can study them and assess glacier sensitivity to climate forcing. This urgency dictates remote sensing and GIS-based studies to provide baseline information and estimates of mass balance. In the Western Himalaya there is a paucity of quantitative information on glacier fluctuations and meltwater contributions to rising sea level. As part of the Global Land Ice Measurements from Space (GLIMS) project, we conducted several glacier change-detection studies to assess ice fluctuations on selected glaciers. We compared SPOT imagery from the 1990's to ASTER satellite imagery from the 2000-2004 time period. Ground photography and satellite image analysis using artificial neural networks were used to compare glacier characteristics. Results indicate that some glaciers have retreated, while others exhibit very similar terminus positions to past positions, but have downwasted. Glacier retreat and downwasting have resulted in the disconnection of tributary glaciers to valley glaciers in the Hindu Kush and Nanga Parbat Himalaya. In addition, there are increases in meltwater production on some glaciers, as revealed by surging and variation in the frequency and size of supraglacial lakes. These results identify increased hazard potential in many areas, and suggest negative mass balance for some glaciers. Quantitative results from remote sensing studies, however, should be carefully interpreted, as climate, glacier, lithosphere interactions that dictate glacier fluctuations are not adequately accounted for in image-based analyses of supraglacial conditions. The integration of quantitative remote sensing/GIS information into numerical ice flow/mass balance models is required to obtain better estimates of mass balance and glacier sensitivity to climate forcing.
H23D-1147 1340h
Glacier Change Detection in the Hindu Kush of Afghanistan
A half century of intermittently collected cryospheric and hydrologic data in Afghanistan has involved diverse field surveys, aerial photography, and satellite imagery that enable change detection in the war-torn, drought-stricken region. Afghanistan relies heavily upon snow-and ice-melt for vital irrigation and ground-water recharge, yet the past two decades of war have only exacerbated the originally already deficient information collection and analysis of such data. Glacier field studies and base-line inventory work initiated in the pre-war 1960-1970 period are now providing limited change detection information for the vital physical analysis necessary in the reconstruction of the country. Five case study areas were selected for renewed assessment over the intervening half century, from the western-most ice masses of the Koh-i-Foladi region in central Afghanistan, through the Mir Samir and Sakhi regions of the central Hindu Kush, to the Keshnikhan and Pamir areas of the Wakhan Corridor. Certain incompatibilities or ambiguities exist between Soviet-era and Western-derived data sets. In general, however, glaciers of Afghanistan are continuing to downwaste and retreat, with smaller ice masses disappearing altogether, presumably as the climatic snowline continues to rise above the peaks, a trend first noticed in the 1960s. Glacier survival in the lower central areas is now in part determined by topographic shielding from solar radiation high in shadowed cirques, or being preserved beneath increasing debris covers, whereas in the higher regions to the northeast, fewer changes to the larger, higher altitude glaciers are apparent. Renewed assessment of all Afghanistan glaciers is now underway as a part of the USGS- and NASA-supported GLIMS (Global Land-Ice Measurements from Space) project, and is viewed as an important element in the primary geodata collection and hazard assessment necessary for aiding in rebuilding the infrastructure of the beleaguered nation.
H23D-1148 1340h
Shuttle Topography Radar Mission DEM, ASTER Images and Aerial Photography in Evaluation of Mountain Glacier Area and Volume Changes
The glacier monitoring on a regional scale have been done traditionally by means of optical space images resulting mainly in observing of changes of area, length and other 2-D information. A lack of texture on the snow fields, steep walls with deep shadows and often cloudiness in high mountains significantly reduce quality and availability of photogrammetrically derived Digital Elevation Models (DEM). Laser altimetry and repeat-pass InSAR DEMs show large potential for glacier volume changes measurements but still have very limited spatial coverage. Recently released 3-arcsecond DEM by NASA-JPL resulted from STRM flown in February 2000 provide unique opportunity for regional-scale glacier change assessment. The method of glacial area and glacier volume changes has been developed over the Akshiirak ice-fields in the Tien Shan Mountains, Central Asia using aerial photography of 1977, topographic maps and RS data of 2000/2003. The datum transformation from WGS-84 used in STRM data to Pulkovo 1942 (Russian) coordinate system was accomplished by 7-parameter Helmert transformation with accuracy at least one order higher than STRM horizontal accuracy (20 m). For vertical validation we compared STRM DEM with DEM constructed from 10 and 5 m additional contour lines digitized from 1:25000 topographic maps on non-glacial relatively flat areas. Though well consistent with 16 m (90%) absolute vertical accuracy, relative accuracy requirement of 6 m (90%) can be easily met only after removing systematic wavy bias in along-track direction. The Akshiirak ice-fields have more than 83% area inclination below $30\deg$. These factors reduce influence of slope-related STRM vertical error to final glacier volume change calculations. Glacier boundaries were manually digitized from an ASTER L1A image acquired on August 18, 2003 that was orthorectified in Orthobase digital photogrammetric package with 9.5 m RMSE of 28 GCPs. For delineating of glaciers in problem areas (debris-covered termini, shadows) we used thermal bands and true hardware-enabled stereo viewing with nadir 3N and backward-looking 3B bands. Accuracy of digitized 2003 glacier boundaries were checked against GPS measurements of 7 glacier termini made in 2002. For surface elevation comparison a second DEM was generated from 10 m contour lines for all glaciers (424 km$^{2}$) using 16 topographic maps of 1:25000 scale created from 1977 aerial photography. The map vertical accuracy is 1/3 of contour interval. Glacier boundaries of 1977 were directly delineated from stereo models. It is revealed that from 1977 till 2003 Akshiirak glaciers have lost 10 km$^{3}$ of ice volume and 35 km$^{2}$ of area.
H23D-1149 1340h
Ku-band Radar Response to Terrestrial Snow Properties
Microwave data from the SeaWinds Ku-band (13.4 GHz) scatterometer aboard the QuikSCAT platform were compared to coincident National Snow Analyses (NSA) data sets describing terrestrial snow pack properties. The scatterometer collects data from two beams with different polarizations and incidence angles. The inner beam (H-pol) 3db footprints are 24 x 31 km with a nominal incidence angle of 46\deg. The outer beam (V-pol) 3db footprints are 26 x 36 km with a nominal incidence angle of 54\deg. The microwave measurements for individual footprints throughout the coterminous U.S. (CONUS) during the 2003-2004 snow season were gridded to a series of daily 25-km grids for each beam and for ascending and descending orbits. The NSA are produced by the NOAA National Weather Service by daily assimilation of all available in situ observations of snow water equivalent and snow depth, and satellite observations of snow cover, into a high-resolution (1-km$^{2}$) land surface model for the CONUS. The NSA products used in this study included snow water equivalent, snow depth, snow pack temperature, and snow melt rate. Snow and non-snow precipitation data sets used to force the NSA snow model were also examined. The 1-km NSA data sets were aggregated to the same 25-km grid used for the microwave data. The mean, variance, minimum, and maximum of the snow pack properties for the 625 1-km NSA grid cells within each 25-km were computed and used in the comparative analysis. The two data sets were compared to help understand Ku-band radar response to terrestrial snow properties. The empirical data show that the Ku-band backscatter is strongly correlated to the snow pack water storage, and importantly is also sensitive to perturbations of the snow pack resulting from new snowfall and snow melt. The results support the instrument concept for the Cold Land Processes Pathfinder mission (CLPP), an experimental mission proposed to measure snow water storage.
H23D-1150 1340h
Monitoring Freeze-Thaw States in the Pan-Arctic: Application of Microwave Remote Sensing to Monitoring Hydrologic and Ecological Processes
The transition of the landscape between predominantly frozen and non-frozen conditions in seasonally frozen environments impacts climate, hydrological, ecological and biogeochemical processes profoundly. Satellite microwave remote sensing is uniquely capable of detecting and monitoring a range of related biophysical processes associated with the measurement of landscape freeze/thaw status. We present the development, physical basis, current techniques and selected hydrological applications of satellite-borne microwave remote sensing of landscape freeze/thaw states for the terrestrial cryosphere. Major landscape hydrological processes embracing the remotely-sensed freeze/thaw signal include timing and spatial dynamics of seasonal snowmelt and associated soil thaw, runoff generation and flooding, ice breakup in large rivers and lakes, and timing and length of vegetation growing seasons and associated productivity and trace gas exchange. Employing both active and passive microwave sensors, we apply a selection of temporal change classification algorithms to examine a variety of hydrologic processes. We investigate contemporaneous and retrospective applications of the QuikSCAT scatterometer, and the SSM/I and SMMR radiometers to this end. Results illustrate the strong correspondence between regional thawing, seasonal ice break up for rivers, and the springtime pulse in river flow. We present the physical principles of microwave sensitivity to landscape freeze/thaw state, recent progress in applying these principles toward satellite remote sensing of freeze/thaw processes over broad regions, and potential for future global monitoring of this significant phenomenon of the global cryosphere. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and at the University of Montana, Missoula, under contract to the National Aeronautics and Space Administration.
H23D-1151 1340h
Comparative Image Analysis to Ensure Data Quality in the Global Land Ice Measurements from Space (GLIMS) Glacier Database
GLIMS (Global Land Ice Measurements from Space) is an international collaborative project to map the world's glaciers and to build a GIS database that is usable via the World Wide Web. The GLIMS programme includes approximately 60 institutions, divided into twenty Regional Centers (RCs), who analyze satellite imagery, primarily ASTER and Landsat, to map glaciers in their regions. The results are collected at the National Snow and Ice Data Center (NSIDC) and inserted into the GLIMS Glacier Database. A major concern for future users of the database is data quality. The process of analyzing imagery to extract vector outlines of glaciers has been automated to some degree, but human expertise remains essential to the process. To quantify the consistency of data provided by different Regional Centers, we carried out a method of comparative image analysis whereby several RCs analyzed the same group of glaciers in one image. The image was chosen to contain a variety of glaciers, as well as several glacier boundary types: ice-water, ice-rock, snow-rock, snow-snow. The results, in the form of glacier outlines, were compiled, compared, and quantified for consistency. We will describe the results of this experiment, which uncovered a variety of errors that may occur during the analysis. As a result, GLIMS is instituting a series of protocols that Regional Centers must follow in order to produce glacier data for GLIMS.
http://www.glims.org/
H23D-1152 1340h
Effect of Snow Cover on the Characterization of Seasonal Freeze-Thaw Processes From Spaceborne Radar
In boreal forests, the seasonal transition between frozen and thawed conditions affects a number of terrestrial processes that cycle between winter dormancy and summer active states. Accurate characterization of these processes can improve regional assessment of seasonal carbon dynamics. Satellite microwave remote sensing is sensitive to landscape freeze/thaw state and has been used for regional assessment and monitoring of this important process at high latitudes and upper elevations. The presence and status of snow cover strongly influences accurate detection and monitoring of freeze/thaw status using microwave sensors. We investigate the effect of snow cover on characterization of landscape freeze-thaw dynamics with spaceborne radars. We examine time series spaceborne Synthetic Aperture Radar (SAR) imagery from ERS (C-band) and JERS (L-band), and scatterometer backscatter from QuikSCAT (Ku-Band) and utilize a radiative transfer backscatter model for interpretation of snow cover effects on the radar signatures. We focus on the interpretation of seasonal thawing relative to snowpack dynamics in a boreal environment. The study sites represent a selection of snow regimes over a range of climatic conditions, from relatively shallow boreal continental snowpacks to deep, wet maritime snowpacks. We employ SNTHERM, a one-dimensional mass and energy balance model, at a stand scale to calculate critical snow properties. SNTHERM is used to infer the snowpack conditions at selected sites and to drive the snow backscatter model. We compare the measured radar backscatter response at each study site to the snow backscatter model and SNTHERM results. We show the radar temporal response to the landscape thaw transition and assess the radar sensitivity to snowpack properties. Finally, we demonstrate how varying snow conditions, characteristic of a boreal landscape, affect freeze-thaw characterization at different wavelengths. This work was performed at the Jet Propulsion Laboratory, California Institute of Technology, at the University of Montana, Missoula, and at the U.S. Army Corps of Engineers Cold Regions Research and Engineering Lab under contract with the National Aeronautics and Space Administration.
H23D-1153 1340h
Evaluation of MODIS Vegetation Products in Regions of Complex Terrain and Monsoon Climates
An evaluation of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation products through comparison against independent surface observations is essential to establish quantitative measures of uncertainty and the confidence level of these satellite-based products for use in land-data assimilation models, for land-use change detection and attribution studies, and for process oriented research. Here, we focus specifically on Photosynthesis and Primary Productivity, Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR), Land Surface Temperature and Emissivity, and Evapotranspiration data sets. Our objective is to perform extensive quantitative assessment of the accuracy and statistical properties of these products against independent estimates in tropical mountainous regions at two climatologically distinct sites. The first site, the Sonora river basin in northern Mexico, is a semi-arid region characterized by complex topography and highly heterogeneous vegetation cover, which exhibits dramatic and fast response to rainfall forcing at the onset of the North-American Monsoon. The second site, the Marsyandi river basin in central Nepal, is a humid region characterized by strong ecohydrological gradients on steep orography, which remain generally stable subsequent to the onset of the Indian Monsoon. Atmospheric soundings, flux tower measurements, and raingauge observations are available for both sites. We evaluate the MODIS products in two ways: 1) comparison with tower-based observations, and 2) evaluation of hydrological response and diurnal cycles of surface water and energy budgets prior, during and post monsoon onset as simulated by a 3D hydroecological model with assimilation of MODIS data. Statistical analysis of the scaling behavior of the variables, both in space and time, is also performed to address the scale discrepancy between flux tower observations and the resolution of MODIS data.
H23D-1154 1340h
Monitoring Playa Hydrology using LANDSAT Imagery
Playa lakes are wetland basins found across the Great Plains. These ephemeral lakes serve as habitat for migrating waterfowl and act as concentrated recharge points for groundwater aquifers. Playas are generally small but number in the tens of thousands, making them a significant component of the ecology and hydrology of the Great Plains. The shear number of playas makes this system difficult to study. Satellite remote sensing, however, can be used to monitor playa hydrology over broad space and time scales. This study demonstrates the use of a four-image LANDSAT sequence to study a cluster of playas in Beaver County, Oklahoma. A simple water budget model is developed to predict aggregate playa water surface area for the study area.
H23D-1155 1340h
Global Cryospheric Impact on Satellite Gravity Measurements: 1980-2003
It is widely appreciated that cryospheric mass exchange with the ocean is an important component of the low order gravity field changes. Traditionally, attention has been focused on the secular trend in the non-tidal gravity variability. Glacioisostatic adjustment (GIA) causes an ongoing oblateness decrease; $\dot{J}^{GIA}_2 \, \simeq \, -2 \, \mathrm{to} \, -9 \, \times \, 10^{-11} \mathrm{yr}^{-1}$, and a pear-shape change; $\dot{J}^{GIA}_3 \, \simeq \, 0 \, \mathrm{to} \, 3 \, \times \, 10^{-11} \mathrm{yr}^{-1}$, with an $n \, = \, 4$ and $5$ zonal rates at; $\dot{J}^{GIA}_4 \, \simeq \, -1 \, \mathrm{to} \, -6 \, \times \, 10^{-11} \mathrm{yr}^{-1}$ and $\dot{J}^{GIA}_5 \, \simeq \, 1 \, \mathrm{to} \, 4 \, \times \, 10^{-11} \mathrm{yr}^{-1}$. The GIA field changes generally deviate from the satellite laser ranging (SLR) observations, $\dot{J}^{Obs}_2 \, \simeq \, -2.9 \pm 0.3 \, \times \, 10^{-11} \mathrm{yr}^{-1}$, $\dot{J}^{Obs}_3 \, \simeq \, -0.9 \pm 0.4 \, \times \, 10^{-11} \mathrm{yr}^{-1}$, $\dot{J}^{Obs}_4 \, \simeq \, 1.2 \pm 0.9 \, \times \, 10^{-11} \mathrm{yr}^{-1}$ and $\dot{J}^{Obs}_5 \, \simeq \, 1.3 \pm 0.4 \, \times \, 10^{-11} \mathrm{yr}^{-1}$, with the notable exception of the oblateness rate. Secular changes in the cryosophere, and, possibly, the global oceans, are thought to provide the geophyiscal source for the residual differences, $\dot{J}^{Obs}_n \, - \, \dot{J}^{GIA}_n$. Here we compute the interdecadal and interannual cryospheric mass change contributions to global gravity fields with Stokes coefficients $n \, \leq \, 256$ from known constraints, and from estimates based upon quantitative climatological and glaciological extrapolation. We examine pre- and post-Mt. Pinatubo climate epochs, and the era after the mid-1990's, when well-documented accelerations of subpolar glacial mass loss are underway in Alaska and Patagonia. Northern hemispheric retreat, including that of Greenland (\textit{Rignot and Thomas}, 2002), may drive $\dot{J}^{Cryo.}_n$ trends during the last 9 years at rates of $1.7, 0.5$ and $1.1 \, \times \, 10^{-11} \mathrm{yr}^{-1}$ for zonals $n = 2,3$ and $4$, respectively. The southern hemisphere contribution is roughly $1.2, -1.0, 0.8$ and $-0.5 \, \times \, 10^{-11} \mathrm{yr}^{-1}$ for $n = 2,3,4$ and $5$, respectively. The two hemispheres contribute to eustatic sealevel rise at the rates $\dot{\xi}_{\mathrm{N}} \, \simeq \, 0.63$ and $\dot{\xi}_{\mathrm{S}} \, \simeq \, 0.42$ mm/yr (N = north, S = south). Hemispheric cancellation of $\dot{J}^{Cryo.}_3$, and the absence of a northern $\dot{J}^{Cryo.}_5$, might provide control on scenarios that hypothesize larger, but unconstrained, mass transfer from continents to oceans. Year-to-year measurements taken by the GRACE satellite should detect Alaskan glacier change, as well as change in areas of Greenland that are known to be thinning at rates of 0.25 m/yr, or more. We show that the sustained changes in geoid height, $\aleph$, are roughly $\dot{\aleph} \, \simeq \, -1.2$ to $-1.75$ mm/yr over wavelengths of 600 to 1200 km, and, as such, are feasible for detection by GRACE (\textit{Wahr et al.}, 2004) in Greenland, Alaska and Antarctica.
H23D-1156 1340h
Comparison of Global Continental Hydrology Models Using Low Degree Time Variable Gravity Measurements
Changes in the distribution of mass within the Earth system produce variations in the Earth's gravity field. This redistribution of mass is largely due to movement of water between and within the atmosphere, hydrosphere, cryosphere, and ocean. While we have good models of the mass distribution of the atmosphere and ocean, the hydrology models are less well determined. Observations of the Earth's time variable gravity field can help to validate the hydrology models. The models we have been investigating are the hydrology fields from the National Centers for Environmental Prediction (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses, the Land Dynamics (LaD) model, the Variable Infiltration Capacity model (VIC), the NOAA Climate Prediction Center (CPC) soil moisture model, the International Satellite Land-Surface Climatology Project (ISLSCP) snow climatology, and the Global Land Data Assimilation System (GLDAS) model. Comparisons of geodetic observations of gravity to the climate forcing estimates have been made on a variety of timescales. We will present the results of these comparisons and discuss the implications for evaluating which hydrology models are best suited for geodetic studies.
H23D-1157 1340h
GRACE captured the drought associated with the 2003 European heat wave
One of the most poorly observed components of the climate system is continental-scale water storage and its variations on annual to interannual scales. Indeed, available ground observations are generally of very small spatial or temporal scope and models driven with observed forcing seldom agree on simulated terrestrial water storage The recently launched twin satellite mission GRACE has the capability of detecting mean seasonal variations of terrestrial water storage for large river basins. We demonstrate here the skill of GRACE data in detecting interannual variability in terrestrial water storage, in particular two drought events associated with record heat waves in Central Europe (2003) and western Russia (2002). GRACE water storage changes are corroborated with indirect estimates of soil water changes based on atmospheric analysis and with in-situ observations of gravity changes using super-conducting gravimeters in Europe, both confirming the validity of these results.
H23D-1158 1340h
Continental Water Storage Changes From GRACE And GLDAS
The Gravity Recovery and Climate Experiment(GRACE) mission is now providing monthly measures of global scale temporal gravity variations, from which terrestrial water storage changes can be inferred. In this presentation we explore continental-scale changes in land water storage, with implications for mass movements in the global water cycle. First we compare GRACE derived spatial patterns of water storage changes to output from the Global Land Data Assimilation System(GLDAS), and assess GRACE capabilities for characterizing spatio-temporal variations over the period of available data. Next we present global scale time series for terrestrial water storage variations, and compare them to those for ocean and atmospheric water mass changes, with a view towards mass redistribution from land to other Earth system components. The results have implications for using GRACE to monitor terrestrial hydroclimatology and for using GRACE as an integrated observing system for characterizing mass movements in the global water cycle.
H23D-1159 1340h
Water Balance Estimates From GRACE Measurements of Time-Variable Gravity
The GRACE satellite mission is now providing regular, monthly solutions for the Earth's gravity field. Two years of solutions are available as of this writing, and more months continue to be generated as the data become available. We have used the time-variable component of these solutions to compute month-to-month changes in the large-scale distribution of water storage. We have combined our results with river discharge data to estimate precipitation minus evapotranspiration over large river basins. We have developed methods of quantifying the uncertainties in all these results. In this talk we will discuss these estimates and their uncertainties, and compare with appropriate hydrological models.
H23D-1160 1340h
River Basin Water Balance Estimates of Evapotranspiration Using GRACE and Other Observations
Evapotranspiration links the global cycles of water, energy, and carbon, thus it is integral to Earth system science. However, it is difficult to estimate on regional, climatic scales. One approach is to use a water budget equation, i.e., total precipitation minus the sum of evapotranspiration and net runoff equals the change in terrestrial water storage. Gravity Recovery and Climate Experiment (GRACE) satellite observations of Earth's gravity field are enabling closure of this equation by providing the terrestrial water storage change term, which has been even more elusive than evapotranspiration until now. Here we describe the method for estimating evapotranspiration using data from GRACE along with observation based precipitation and runoff, which takes into account the unique nature of the GRACE observations. GRACE water storage changes are first substantiated by comparison with results from a land surface model and a combined atmospheric-terrestrial water budget approach. Evapotranspiration is then estimated over the Mississippi River basin and compared with output from the land surface model and two operational atmospheric modeling systems. Results suggest that the new technique provides skill in evaluating modeled evapotranspiration, particularly in terms of bias.
H23D-1161 1340h
GRACE Measurements of the Mackenzie River Basin Water Balance
Direct measurement of an integrated watershed storage amount may be considered a panacea for the ills of watershed modeling. Watershed models typically transfer moisture and energy between model "stores" using physically based transfer laws and conservation equations to produce streamflow hydrographs. Because of the problem of non-uniqueness in the generation of model hydrographs, it has become increasingly important to ensure the representativeness of model results. This is being accomplished by: a) performing model integrations over long, multi-year periods, b) applying models to watersheds with diverse hydroclimatic conditions, c) comparing model "stores" with measured components of watershed storage such as snow depth, soil moisture, groundwater levels, and lake storage. Many of these components, however, either are not regularly measured or have large uncertainties associated with their values. Lack of a true integrated storage measurement represents an unwanted degree of freedom in watershed modeling. In 2002, the GRACE (Gravity Recovery And Climate Experiment Mission) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its five year life a pair of orbiting satellites will produce a time series of "mass" changes of the earth-atmosphere system. When integrated over a number of years, this will yield a highly refined picture of the earth's gravity. However, month to month changes in mass is an indicator of the integrated value of watershed moisture storage. It has been reported by Wahr et al. (2004) that when smoothed over 1000 km that centimeter accuracy can be achieved in monthly storage change. The goal of this research to compare changes in moisture storage over the Mackenzie River basin using GRACE data with those developed by atmospheric and hydrologic water balances developed under the Mackenzie GEWEX Project (MAGS). Monthly estimates of watershed storage have been developed for the basin through the analysis of streamflow hydrographs using the WATFLOOD and WATCLASS hydrologic models and these have been validated independently through atmospheric water balance computations (Strong et al., 2002 Atmosphere-Ocean).
H23D-1162 1340h
Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)
For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of "wet" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful to the City of Tucson and Tucson Water for their support and cooperation.
http://uanews.org/cgi-bin/WebObjects/UANews.woa/3/wa/EngrStoryDetails?ArticleID=9367
H23D-1163 1340h
Surface Water Frequency Distribution over the Continental Scale
The NASA SeaWinds Scatterometer on the QuikSCAT satellite (QSCAT) is used to detect and monitor surface water changes on the continental United States (CONUS). We developed and implemented an algorithm to detect and map surface soil-moisture frequency for CONUS. QSCAT has a nearly daily coverage over the continental scale allowing an estimate of the spatial distribution of surface water (due to precipitation) frequency. Over CONUS, in-situ soil moisture and other meteorological data are available from field experiments and station networks to verify remote sensing results. Wet surface maps derived from QSCAT data compare well in timing and in spatial pattern with surface measurements of precipitation. Results for summer seasons (mid-May to mid-September) in the last half-decade over CONUS reveal a highly recurrent precipitation pattern over the Midwest with the wettest condition in year 2000 and a severe drought in 2003. In several New England states, summer 2001 experienced the most frequent precipitation-induced surface wetness. Moreover, QSCAT results for surface moisture pattern have been verified by an inter-comparison with Princeton University's LDAS (Land Data Assimilation System) precipitation maps (data courtesy of E. Wood) over the SMEX (Soil Moisture Experiment) region including Iowa and the surrounding states. Thus, QSCAT results can serve as an independent dataset for the inter-comparison of NLDAS (North American Land Data Assimilation System) and GLDAS (Global Land Data Assimilation System) results. Furthermore, with the large-scale coverage on the daily basis, QSCAT results are useful for flood and drought monitoring and water resource applications.
H23D-1164 1340h
Latitudinal Distribution of the Deuterium to Hydrogen Ratio in the Atmospheric Water Vapor Retrieved From Space FTS Data
Latitudinal distribution of the columnar deuterium/hydrogen ratio of atmospheric water vapor, dD, was firstly retrieved from high-resolution infrared spectra observed from space (Zakharov et al., 2004: doi:10.1029/2004GL019433). A Fourier Transform Spectrometer (FTS) sensor, Interferometric Monitor for Greenhouse gases (IMG), aboard the ADvanced Earth Observing Satellite (ADEOS) observed the thermal infrared spectra over the ocean during the sensor operational period from December 1996 through June 1997. We analyzed these spectrum data to obtain the dD values based on a type of spectral fitting method using a forward/retrieval calculation code developed by Gribanov et al. [2001]. The results show that the latitudinal mean was relatively large with values around -V100 permillage in the tropical region decreasing down to minimal values of -V800 permillage at high latitudes. These data were plotted against the sea surface temperature at which the spectra were observed, and we discussed the deuterium fractionation processes occurred during the evaporation, condensation, and transport of the water vapor comparing with the dD values from a simple two-phase distillation model. Also investigated were the synoptic scale situations at which some typical dD data were observed. Water vapor transport around the synoptic scale systems were discussed based on the trajectory analyses of the air mass in which the dD values were observed. The data analysis method adopted in this study is expected to be applicable for data analyses of satellite sensors such as IASI and TES which have almost the same performance as IMG.
H23D-1165 1340h
Atmospheric water vapor over the subtropical oceans
Atmospheric water vapor is an important part of the Earth's hydrological cycle and plays a crucial role in many aspects of the climate system. The main source of the atmospheric moisture are the oceans, but the information we have about the distribution of atmospheric water vapor over the oceans is based on a relatively sparse distribution of radiosonde profiles, or on satellite-based measurements from microwave radiometers. The Marine-Atmosphere Emitted Radiance Interferometer (M-AERI) is a sea-going instrument that measures spectra of atmospheric infrared emission with ~10 minute temporal resolution. These spectra can be used to retrieve profiles of temperature and humidity in the atmosphere, and can thus be employed for continuous monitoring of the distribution of temperature and humidity in the marine atmosphere. M-AERI measurements can also be used to validate both modeling results and satellite measurements. This study compares ship-based measurements of atmospheric water vapor path from the M-AERI, radiosondes, and an upward-looking microwave radiometer. The data come from a two-month deployment in the Caribbean Sea on the RCCL Explorer of the Seas and during a month long cruise on the USCGC Healy. The measurements are compared with results from global circulation models NCEP and ECMWF. A comparison of satellite retrieved profiles of atmospheric water vapor from the Atmospheric Infrared Sounder (AIRS) with M-AERI measurements is discussed in a presentation in session A.19.
H23D-1166 1340h
Spatial Scales of Tropical Precipitation Inferred From TRMM Microwave Imager Data
The local spatial scales of tropical precipitating systems were studied using TRMM Microwave Imager (TMI) rain rate imagery from the Tropical Rainfall Measuring Mission (TRMM) satellite. Rain rates were determined from TMI data using the Goddard Profiling (GPROF) Version 5 algorithm. Following the analysis of Ricciardulli and Sardeshmukh (RS, [1]) who studied local spatial scales of tropical deep convection using Global Cloud Imagery (GCI) data, active precipitating months were defined as those having greater than 1mm/hr of rain for more than 5% of the time. Spatial autocorrelation values of rain rate were subsequently computed on these grid cells for convectively active months from 1998 to 2002. The results were fitted to an exponential correlation model using a nonlinear least squares routine to estimate a spatial correlation length at each grid cell. The mean spatial scale over land was 94.3 km and over oceans was 121.8 km. An error analysis was performed which showed that the error in these determinations was of order 1-5%. The results of this study should be useful in the design of convective schemes for general circulation models and for precipitation error covariance models for use in numerical weather prediction and associated data assimilation schemes. The results of the TMI study also largely concur with those of RS, although the more direct relationship between the TMI data and rain rate relative to the GCI imagery provide more accurate correlation length estimates. The results also confirm the strong impact of land in producing short spatial scale convective rain. [1] Ricciardulli, L., and Sardeshmukh, P. D., "Local Time and Space Scales of Organized Tropical Deep Convection," J. Climate, v. 15, pp. 2775-2790, 2002.
H23D-1167 1340h
Oceanic Influence on Continental Rainfall Observed From Space
A method has been developed and validated to estimate moisture transport integrated over the depth of the atmosphere (Q) over the ocean, using both spaceborne scatterometers and microwave radiometers. The divergence of Q compares well with the fresh water flux into the ocean as estimated from separate estimates of evaporation and precipitation, and it is related to the long term variation of in situ salinity measurements. For major land masses over the world under the influence of monsoons, Q normal to the coastlines have been computed and compared with continental rainfall measured by the Tropical Rain Measureing Mission for four years, starting 1999. During the summer. moisture is observed to be transported from the Arabian Sea across the west coast of the Indian Subcontinent, and out to the Bay of Bengal across the east coast. The temporal variation of the net Q agrees, and is in phase with, the changes of rainfall integrated over the subcontinent. However, the onset of moisture moving out the subcontinent into the Bay of Bengal is earlier than the onset of moisture transport into the subcontinent from the Arabian Sea. The variation of rainfall over China and Indochina agrees very well, and is in phase with, the total transport from the Bay of Bengal and Indian Ocean but out-of-phase with moisture advection from the Pacific coastline. The variation of rainfall in the Amazon is dominated by, and is in phase with Q from the Atlantic, particularly in the intra-seasonal time scales