Dr. Thomas Holmes is a Research Scientist in the Hydrological Sciences Lab at NASA Goddard Space Flight Center, Greenbelt, MD. His research interests center on the utilization of satellite data for the study of the global hydrological cycle, in particular in terms of evaporation and soil moisture. He has been involved in the development of several research models and global satellite products, including the land parameter retrieval model (LPRM) for soil moisture retrieval, the community microwave emission model (CMEM) for the modeling of L-band brightness temperature, and the observation-based global land evaporation methodology (GLEAM). Dr. Holmes received his M.Sc. in Eco-Hydrology and Ph.D. in Earth science from VU University Amsterdam, the Netherlands.
Thomas Holmes
(RSCH AST, EARTH SCIENCES REMOTE SENS)
| Email: | thomas.r.holmes@nasa.gov |
| Phone: | 301.614.5444 |
| Org Code: | 617 |
| Address: |
NASA/GSFC Mail Code 617 Greenbelt, MD 20771 |
| Employer: |
Missions & Projects
Brief Bio
Research Interests
The application of all-weather microwave-based land surface temperature products for energy balance studies.
Earth Science: Remote SensingBiomass as a dynamic reservoir of water within the hydrological cycle.
Earth Science: Remote SensingDrought monitoring and Food Security
Earth Science: ApplicationsCurrent Projects
Landsat Next NASA Deputy Project Scientist
Remote Sensing
Microwave Land Surface Temperature for all-weather Evapotranspiration estimates.
Hydrology / Water Cycle
Thermal Science and Sensors Strategy Group lead
Remote Sensing
Consumptive water use for Upper Colorado
Applications
Positions/Employment
Research Physical Scientist
NASA Goddard Space Flight Center - Greenbelt, MD
May 2016 - Present
Senior Research Scientist
SSAI (at USDA HRSL) - Beltsville, MD
May 2014 - May 2016
Research Physical Scientist
USDA ARS Hydrology and Remote Sensing Lab - Beltsville, MD
April 2009 - April 2014
Post-doctoral researcher
VU University Amsterdam - Amsterdam
June 2008 - December 2008
Education
Ph.D, VU University Amsterdam, Amsterdam, the Netherlands, 2008.
MSc. VU University Amsterdam, Amsterdam, the Netherlands, 2004.
Awards
1. 2018 Hydrosphere, Biosphere and Geophysics Peer Award for Best Science Monthly Highlight
2. 2018 Hydrosphere, Biosphere and Geophysics Peer Award for Scientific Achievement
Selected Publications
Refereed
2024. "Nonstationarity in the global terrestrial water cycle and its interlinkages in the Anthropocene." Proceedings of the National Academy of Sciences 121 (45): [10.1073/pnas.2403707121] [Journal Article/Letter]
2024. "Soil Moisture Profiles of Ecosystem Water Use Revealed With ECOSTRESS." Geophysical Research Letters 51 (8): [10.1029/2024gl108326] [Journal Article/Letter]
2024. "Estimating Hydrological Regimes from Observational Soil Moisture, Evapotranspiration, and Air Temperature Data." Journal of Hydrometeorology 25 (3): 495–513 [10.1175/jhm-d-23-0140.1] [Journal Article/Letter]
2024. "On‐Orbit Spatial Performance Characterization for Thermal Infrared Imagers of Landsat 7, 8, and 9, ECOSTRESS and CTI." Journal of Geophysical Research: Biogeosciences 129 (2): [10.1029/2023jg007506] [Journal Article/Letter]
2024. "Droughts impede water balance recovery from fires in the Western United States." Nature Ecology & Evolution [10.1038/s41559-023-02266-8] [Journal Article/Letter]
2022. "Flash Drought Onset and Development Mechanisms Captured with Soil Moisture and Vegetation Data Assimilation." Water Resources Research 58 (12): e2022WR032894 [10.1029/2022wr032894] [Journal Article/Letter]
2022. "Compact thermal imager: a flight demonstration of infrared technology for Earth observations." Applied Optics 61 (14): 4215 [10.1364/ao.450442] [Journal Article/Letter]
2021. "Compact Thermal Imager (CTI) for Atmospheric Remote Sensing." Remote Sensing 13 (22): 4578 [10.3390/rs13224578] [Journal Article/Letter]
2021. "NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms." Remote Sensing of Environment 257 112349 [10.1016/j.rse.2021.112349] [Journal Article/Letter]
2020. "The 2019‐2020 Australian drought and bushfires altered the partitioning of hydrological fluxes." Geophysical Research Letters 48 (1): [10.1029/2020gl091411] [Journal Article/Letter]
2020. "Soil Evaporation Stress Determines Soil Moisture‐Evapotranspiration Coupling Strength in Land Surface Modeling." Geophysical Research Letters 47 (21): [10.1029/2020gl090391] [Journal Article/Letter]
2020. "Assimilation of vegetation optical depth retrievals from passive microwave radiometry." Hydrology and Earth System Sciences 24 (7): 3431-3450 [10.5194/hess-24-3431-2020] [Journal Article/Letter]
2019. "Uncertainties in Evapotranspiration Estimates over West Africa." Remote Sensing 11 (8): 892 [10.3390/rs11080892] [Journal Article/Letter]
2019. "Earth Observations and Integrative Models in Support of Food and Water Security." Remote Sensing in Earth Systems Sciences [10.1007/s41976-019-0008-6] [Journal Article/Letter]
2018. "Global relationships among traditional reflectance vegetation indices (NDVI and NDII), evapotranspiration (ET), and soil moisture variability on weekly timescales." Remote Sensing of Environment 219 339-352 [10.1016/j.rse.2018.10.020] [Journal Article/Letter]
2018. "Global Investigation of Soil Moisture and Latent Heat Flux Coupling Strength." Water Resources Research 54 (10): 8196-8215 [10.1029/2018wr023469] [Journal Article/Letter]
2018. "Attribution of flux partitioning variations between land surface models over the continental U.S." Remote Sensing 10 (5): 751 [10.3390/rs10050751] [Journal Article/Letter]
2018. "Microwave implementation of two-source energy balance approach for estimating evapotranspiration." Hydrology and Earth System Sciences 22 (2): 1351-1369 [10.5194/hess-22-1351-2018] [Journal Article/Letter]
2018. "Assessment of the impact of spatial heterogeneity on microwave satellite soil moisture periodic error." Remote Sensing of Environment 205 85-99 [10.1016/j.rse.2017.11.002] [Journal Article/Letter]
2016. "Cloud tolerance of remote-sensing technologies to measure land surface temperature." Hydrology and Earth System Sciences 20 (8): 3263-3275 [10.5194/hess-20-3263-2016] [Journal Article/Letter]
2015. "A Methodology to Determine Radio-Frequency Interference in AMSR2 Observations." IEEE Transactions on Geoscience and Remote Sensing 53 (9): 5148-5159 [10.1109/tgrs.2015.2417653] [Journal Article/Letter]
2015. "A Preliminary Study toward Consistent Soil Moisture from AMSR2." Journal of Hydrometeorology 16 (2): 932-947 [10.1175/jhm-d-13-0200.1] [Journal Article/Letter]
2015. "Diurnal temperature cycle as observed by thermal infrared and microwave radiometers." Remote Sensing of Environment 158 110-125 [10.1016/j.rse.2014.10.031] [Journal Article/Letter]
2014. "Leveraging microwave polarization information for the calibration of a land data assimilation system." Geophysical Research Letters 41 (24): 8879-8886 [10.1002/2014gl061991] [Journal Article/Letter]
2014. "A spatially coherent global soil moisture product with improved temporal resolution." Journal of Hydrology 516 284–296 [10.1016/j.jhydrol.2014.02.015] [Journal Article/Letter]
2014. "Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring." J. Hydrometeor. 15 (3): 1117–1134 [10.1175/JHM-D-13-0125.1] [Journal Article/Letter]
2014. "Remote monitoring of soil moisture using passive microwave-based techniques — Theoretical basis and overview of selected algorithms for AMSR-E." Remote Sensing of Environment 144 197-213 [10.1016/j.rse.2014.01.013] [Journal Article/Letter]
2013. "El Niño–La Niña cycle and recent trends in continental evaporation." Nature Climate Change 4 (2): 122-126 [10.1038/nclimate2068] [Journal Article/Letter]
2013. "Spatial patterns in timing of the diurnal temperature cycle." Hydrology and Earth System Sciences 17 (10): 3695 [Journal Article/Letter]
2012. "An assessment of surface soil temperature products from numerical weather prediction models using ground-based measurements." Water Resour. Res. 48 (2): W02531 [10.1029/2011WR010538] [Journal Article/Letter]
2008. "Multisensor historical climatology of satellite-derived global land surface moisture." J. Geophys. Res. 113 (F1): F01002 [10.1029/2007JF000769] [Journal Article/Letter]
Non-Refereed
2019. "Advances in the Remote Sensing of Terrestrial Evaporation." Remote Sensing 11 (9): 1138 [10.3390/rs11091138] [Journal Article/Letter]
Talks, Presentations and Posters
Invited
Global mapping of Evaporation in the presence of clouds
May 26, 2018
Spring seminar series, Department of Earth and Ocean Sciences, University of South Carolina
Other
A growing role for Microwave observations in estimating Evaporation from space. AMS 2020
February 16, 2020
Evaluation the application of thermal infrared and microwave surface temperature observations in the retrieval of evapotranspiration under clear sky conditions.
June 2018
Poster presentation during GEWEX 2018 in Canberra, CA.
Microwave based implementation of a two-source energy balance model to estimate evapotranspiration
May 28, 2017
There is a need for observation-based methodologies to estimate evapotranspiration (ET) at diverse spatial domains. The ALEXI methodology (Atmosphere Land Exchange Inverse) is a time difference implementation of the two-source energy balance method and provides diagnostic estimates of actual ET. ALEXI has been implemented with thermal infrared (TIR) observations at diverse spatial scales to estimate crop water use, as an indicator of agricultural drought, and for the study hydrological impacts of climate variations and land-use change.
While TIR is the most direct measurement of physical land surface temperature (LST), sole reliance on TIR limits the sampling to clear skies. It also impacts the accuracy if the cloud masking fails. Passive microwave (MW) methods to estimate LST could help to overcome this limitation and provide a more cloud tolerant alternative to TIR. As a first test of the functioning of a MW-based LST within the ALEXI framework we ran two parallel implementations of ALEXI, one with TIR-LST (MODIS), and one with MW-LST (without any calibrations to accommodate MW-LST). This paper presents an analysis of the clear sky ET estimates for the years 2003-2013 and explores the level of agreement between the MW- and TIR-based ET and derived stress indices.