Name
Title | ||
|---|---|---|
Using enhanced GRACE water storage data to improve drought detection by the U.S. and North American Drought Monitors |
Abstract | ||
|---|---|---|
NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IGARSS.2010.5654237 | Geoscience and Remote Sensing Symposium |
Keywords | Field | DocType |
atmospheric precipitation,climatology,gravity,groundwater,hydrology,soil,spatiotemporal phenomena,Earth gravity field,GRACE TWS data,Gravity Recovery and Climate Experiment satellites,NASA,North American Drought Monitors,U.S,catchment land surface model,climatology,deep soil moisture,drought detection,drought indicator percentiles,drought indicators,ensemble Kalman smoother,groundwater components,groundwater storage conditions,precipitation indices,spatial downscaling,spatiotemporal variations,temporal downscaling,time variations,total terrestrial water storage,vertical decomposition,GRACE,data assimilation,drought indicators,drought monitor,terrestrial water storage | Downscaling,Moisture,Climate change,Computer science,Groundwater,Remote sensing,Water storage,Data assimilation,Water content,Climatology,Precipitation | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4244-9564-1 | 978-1-4244-9564-1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 12 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rasmus Houborg | 1 | 25 | 7.02 |
| Matthew Rodell | 2 | 1 | 2.05 |
| Jay Lawrimore | 3 | 0 | 0.34 |
| Bailing Li | 4 | 0 | 0.34 |
| Rolf Reichle | 5 | 369 | 33.86 |
| Richard Heim | 6 | 0 | 0.34 |
| Matthew Rosencrans | 7 | 0 | 0.34 |
| Rich Tinker | 8 | 0 | 0.34 |
| James S. Famiglietti | 9 | 2 | 1.11 |
| Mark Svoboda | 10 | 0 | 0.34 |
| Brian Wardlow | 11 | 19 | 5.34 |
| Benjamin F. Zaitchik | 12 | 6 | 3.44 |