Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables
Land surface energetic partitioning between latent, sensible, and ground heat fluxes determines climate and influences the terrestrial segment of land-atmosphere coupling. Soil moisture, among other variables, has a direct influence on this partitioning. Dry surfaces characterize a water-limited reg...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2020
|
| Online Access: | https://hdl.handle.net/1721.1/125701 |
| _version_ | 1826192160393789440 |
|---|---|
| author | Feldman, Andrew F Gianotti, Daniel J Trigo, Isabel F. Salvucci, Guido D. Entekhabi, Dara |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Feldman, Andrew F Gianotti, Daniel J Trigo, Isabel F. Salvucci, Guido D. Entekhabi, Dara |
| author_sort | Feldman, Andrew F |
| collection | MIT |
| description | Land surface energetic partitioning between latent, sensible, and ground heat fluxes determines climate and influences the terrestrial segment of land-atmosphere coupling. Soil moisture, among other variables, has a direct influence on this partitioning. Dry surfaces characterize a water-limited regime where evapotranspiration and soil moisture are coupled. This coupling is subdued for wet surfaces, or an energy-limited regime. This framework is commonly evaluated using the evaporative fraction–-soil moisture relationship. However, this relationship is explicitly or implicitly prescribed in land surface models. These impositions, in turn, confound model-based evaluations of energetic partitioning-–soil moisture relationships. In this study, we use satellite-based observations of surface temperature diurnal amplitude (directly related to available energy partitioning) and soil moisture, free of model impositions, to estimate characteristics of surface energetic partitioning–-soil moisture relationships during 10–-20-day surface drying periods across Africa. We specifically estimate the spatial patterns of water-limited energy flux sensitivity to soil moisture (m) and the soil moisture threshold separating water and energy-limited regimes (θ*). We also assess how time evolution of other factors (e.g., solar radiation, vapor pressure deficit, surface albedo, and wind speed) can confound the energetic partitioning–-soil moisture relationship. We find higher m in drier regions and interestingly similar spatial θ* distributions across biomes. Vapor pressure deficit and insolation increases during drying tend to increase m. Only vapor pressure deficit increases in the Sahelian grasslands systematically decrease θ*. Ultimately, soil and atmospheric moisture availability together play the largest role in land surface energy partitioning with minimal consistent influences of time evolution of other forcings. ©2019. The Authors. |
| first_indexed | 2024-09-23T09:07:09Z |
| format | Article |
| id | mit-1721.1/125701 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:07:09Z |
| publishDate | 2020 |
| publisher | American Geophysical Union (AGU) |
| record_format | dspace |
| spelling | mit-1721.1/1257012022-09-26T10:36:09Z Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables Feldman, Andrew F Gianotti, Daniel J Trigo, Isabel F. Salvucci, Guido D. Entekhabi, Dara Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Land surface energetic partitioning between latent, sensible, and ground heat fluxes determines climate and influences the terrestrial segment of land-atmosphere coupling. Soil moisture, among other variables, has a direct influence on this partitioning. Dry surfaces characterize a water-limited regime where evapotranspiration and soil moisture are coupled. This coupling is subdued for wet surfaces, or an energy-limited regime. This framework is commonly evaluated using the evaporative fraction–-soil moisture relationship. However, this relationship is explicitly or implicitly prescribed in land surface models. These impositions, in turn, confound model-based evaluations of energetic partitioning-–soil moisture relationships. In this study, we use satellite-based observations of surface temperature diurnal amplitude (directly related to available energy partitioning) and soil moisture, free of model impositions, to estimate characteristics of surface energetic partitioning–-soil moisture relationships during 10–-20-day surface drying periods across Africa. We specifically estimate the spatial patterns of water-limited energy flux sensitivity to soil moisture (m) and the soil moisture threshold separating water and energy-limited regimes (θ*). We also assess how time evolution of other factors (e.g., solar radiation, vapor pressure deficit, surface albedo, and wind speed) can confound the energetic partitioning–-soil moisture relationship. We find higher m in drier regions and interestingly similar spatial θ* distributions across biomes. Vapor pressure deficit and insolation increases during drying tend to increase m. Only vapor pressure deficit increases in the Sahelian grasslands systematically decrease θ*. Ultimately, soil and atmospheric moisture availability together play the largest role in land surface energy partitioning with minimal consistent influences of time evolution of other forcings. ©2019. The Authors. NASA sponsored research grant (Subcontract No.1510842). 2020-06-05T20:47:48Z 2020-06-05T20:47:48Z 2019-12 2019-06 2020-05-26T19:08:13Z Article http://purl.org/eprint/type/JournalArticle 1944-7973 https://hdl.handle.net/1721.1/125701 Feldman, Andrew F. et al., "Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables." Water Resources Research 55, 12 (December 2019): 10657-77 doi. 10.1029/2019WR025874 ©2019 Authors en https://dx.doi.org/10.1029/2019WR025874 Water Resources Research Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf American Geophysical Union (AGU) American Geophysical Union (AGU) |
| spellingShingle | Feldman, Andrew F Gianotti, Daniel J Trigo, Isabel F. Salvucci, Guido D. Entekhabi, Dara Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title | Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title_full | Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title_fullStr | Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title_full_unstemmed | Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title_short | Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables |
| title_sort | satellite based assessment of land surface energy partitioning soil moisture relationships and effects of confounding variables |
| url | https://hdl.handle.net/1721.1/125701 |
| work_keys_str_mv | AT feldmanandrewf satellitebasedassessmentoflandsurfaceenergypartitioningsoilmoisturerelationshipsandeffectsofconfoundingvariables AT gianottidanielj satellitebasedassessmentoflandsurfaceenergypartitioningsoilmoisturerelationshipsandeffectsofconfoundingvariables AT trigoisabelf satellitebasedassessmentoflandsurfaceenergypartitioningsoilmoisturerelationshipsandeffectsofconfoundingvariables AT salvucciguidod satellitebasedassessmentoflandsurfaceenergypartitioningsoilmoisturerelationshipsandeffectsofconfoundingvariables AT entekhabidara satellitebasedassessmentoflandsurfaceenergypartitioningsoilmoisturerelationshipsandeffectsofconfoundingvariables |