Large-scale modes of climate variability (or teleconnection patterns), such as the El Ni\uffc3\uffb1o Southern Oscillation and the North Atlantic Oscillation, affect local weather worldwide. However, the response of terrestrial water and energy fluxes to these modes of variability is still poorly understood. Here, we analyse the response of evaporation to 16 teleconnection patterns, using a simple supervised learning framework and global observation-based datasets of evaporation and its key climatic drivers. Our results show that the month-to-month variability in terrestrial evaporation is strongly affected by (coupled) oscillations in sea-surface temperature and air pressure: in specific hotspot regions, up to 40% of the evaporation dynamics can be explained by climate indices describing the fundamental modes of climate variability. While the El Ni\uffc3\uffb1o Southern Oscillation affects the dynamics in land evaporation worldwide, other phenomena such as the East Pacific\uffe2\uff80\uff93North Pacific teleconnection pattern are more dominant at regional scales. Most modes of climate variability affect terrestrial evaporation by inducing changes in the atmospheric demand for water. However, anomalies in precipitation associated to particular teleconnections are crucial for the evaporation in water-limited regimes, as well as in forested regions where interception loss forms a substantial fraction of total evaporation. Our results highlight the need to consider the concurrent impact of these teleconnections to accurately predict the fate of the terrestrial branch of the hydrological cycle, and provide observational evidence to help improve the representation of surface fluxes in Earth system models.
", "keywords": ["EVAPOTRANSPIRATION", "0207 environmental engineering", "TELECONNECTION", "02 engineering and technology", "15. Life on land", "01 natural sciences", "6. Clean water", "NORTH-ATLANTIC", "PACIFIC OSCILLATION", "13. Climate action", "Earth and Environmental Sciences", "LAND EVAPORATION", "PRECIPITATION", "PATTERNS", "HYDROCLIMATOLOGY", "TEMPERATURE", "SATELLITE", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.nature.com/articles/s41612-018-0053-5.pdf"}, {"href": "https://doi.org/10.1038/s41612-018-0053-5"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/npj%20Climate%20and%20Atmospheric%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41612-018-0053-5", "name": "item", "description": "10.1038/s41612-018-0053-5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41612-018-0053-5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-11-15T00:00:00Z"}}, {"id": "10.1109/lgrs.2021.3073484", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:15Z", "type": "Journal Article", "created": "2021-06-10", "title": "Sentinel-1 Backscatter Assimilation Using Support Vector Regression or the Water Cloud Model at European Soil Moisture Sites", "description": "Sentinel-1 backscatter observations were assimilated into the Global Land Evaporation Amsterdam Model (GLEAM) using an ensemble Kalman filter. As a forward operator, which is required to simulate backscatter from soil moisture and leaf area index (LAI), we evaluated both the traditional water cloud model (WCM) and the support vector regression (SVR). With SVR, a closer fit between backscatter observations and simulations was achieved. The impact on the correlation between modeled and in situ soil moisture measurements was similar when assimilating the Sentinel data using WCM (\u0394 R = +0.037) or SVR (\u0394 R = +0.025).", "keywords": ["Vegetation mapping", "support vector regression (SVR)", "Technology and Engineering", "Data models", "0211 other engineering and technologies", "Computational modeling", "02 engineering and technology", "15. Life on land", "Geotechnical Engineering and Engineering Geology", "01 natural sciences", "Backscatter", "radar backscatter", "Soil", "Earth and Environmental Sciences", "LAND EVAPORATION", "Data assimilation", "Soil moisture", "Electrical and Electronic Engineering", "soil moisture", "Moisture", "SMOS", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://xplorestaging.ieee.org/ielx7/8859/9651998/09451176.pdf?arnumber=9451176"}, {"href": "https://doi.org/10.1109/lgrs.2021.3073484"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/IEEE%20Geoscience%20and%20Remote%20Sensing%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1109/lgrs.2021.3073484", "name": "item", "description": "10.1109/lgrs.2021.3073484", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1109/lgrs.2021.3073484"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.3390/rs10101601", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:21:58Z", "type": "Journal Article", "created": "2018-10-09", "title": "Sensitivity of Evapotranspiration Components in Remote Sensing-Based Models", "description": "Accurately estimating evapotranspiration (ET) at large spatial scales is essential to our understanding of land-atmosphere coupling and the surface balance of water and energy. Comparisons between remote sensing-based ET models are difficult due to diversity in model formulation, parametrization and data requirements. The constituent components of ET have been shown to deviate substantially among models as well as between models and field estimates. This study analyses the sensitivity of three global ET remote sensing models in an attempt to isolate the error associated with forcing uncertainty and reveal the underlying variables driving the model components. We examine the transpiration, soil evaporation, interception and total ET estimates of the Penman-Monteith model from the Moderate Resolution Imaging Spectroradiometer (PM-MOD), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL) and the Global Land Evaporation Amsterdam Model (GLEAM) at 42 sites where ET components have been measured using field techniques. We analyse the sensitivity of the models based on the uncertainty of the input variables and as a function of the raw value of the variables themselves. We find that, at 10% added uncertainty levels, the total ET estimates from PT-JPL, PM-MOD and GLEAM are most sensitive to Normalized Difference Vegetation Index (NDVI) (%RMSD = 100.0), relative humidity (%RMSD = 122.3) and net radiation (%RMSD = 7.49), respectively. Consistently, systemic bias introduced by forcing uncertainty in the component estimates is mitigated when components are aggregated to a total ET estimate. These results suggest that slight changes to forcing may result in outsized variation in ET partitioning and relatively smaller changes to the total ET estimates. Our results help to explain why model estimates of total ET perform relatively well despite large inter-model divergence in the individual ET component estimates.
", "keywords": ["550", "Science", "TROPICAL RAIN-FOREST", "0208 environmental biotechnology", "evapotranspiration", "0207 environmental engineering", "02 engineering and technology", "interception", "SOIL-MOISTURE", "transpiration", "modelling", "partitioning", "soil evaporation", "uncertainty", "DROUGHT", "evapotranspiration; modelling; sensitivity; uncertainty; transpiration; soil evaporation; interception; partitioning", "CLIMATE-CHANGE", "Q", "Biology and Life Sciences", "PLANT TRANSPIRATION", "sensitivity", "6. Clean water", "CHIHUAHUAN DESERT", "GLOBAL TERRESTRIAL EVAPOTRANSPIRATION", "13. Climate action", "Earth and Environmental Sciences", "LAND EVAPORATION", "WATER-BALANCE", "FEEDBACKS", "[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]", "[PHYS.ASTR] Physics [physics]/Astrophysics [astro-ph]"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/10/10/1601/pdf"}, {"href": "https://doi.org/10.3390/rs10101601"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs10101601", "name": "item", "description": "10.3390/rs10101601", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs10101601"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-09T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=LAND+EVAPORATION&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=LAND+EVAPORATION&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=LAND+EVAPORATION&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=LAND+EVAPORATION&offset=3", "hreflang": "en-US"}], "numberMatched": 3, "numberReturned": 3, "distributedFeatures": [], "timeStamp": "2026-07-28T09:09:06.937543Z"}