The future of evapotranspiration : global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources

The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with changes in drought frequency and intensity on the distribution and timing of water availability. The development of effective adaptation strategies for these emerging threats to food and water security are compromised by limitations in our understanding of how natural and managed ecosystems are responding to changing hydrological and climatological regimes. This information gap is exacerbated by insufficient monitoring capabilities from local to global scales. Here, we describe how evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, and highlight both the outstanding science and applications questions and the actions, especially from a space-based perspective, necessary to advance them

Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation

Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance System (SEBS) was evaluated for its ability to estimate hourly ET rates of summer tall and short crops grown in the Texas High Plains by using 15 Landsat 5 Thematic Mapper scenes acquired during 2006 to 2009. Performance of SEBS was evaluated by comparing estimated hourly ET values with measured ET data from four large weighing lysimeters, each located at the center of a 4.3 ha field in the USDA-ARS Conservation and Production Research Laboratory in Bushland, TX. The performance of SEBS in estimating hourly ET was good for crops under both irrigated and dryland conditions. A locally derived, surface albedo-based soil heat flux (G) model further improved the G estimates. Root mean square error and mean bias error were 0.11 and −0.005 mm h−1, respectively, and the Nash–Sutcliff model efficiency was 0.85 between the measured and calculated hourly ET. Considering the equal or better performance with a minimal amount of ancillary data as compared to with other EB algorithms, SEBS is a promising tool for use in an operational ET remote sensing program in the semiarid Texas High Plains. However, thorough sensitivity and error propagation analyses of input variables to quantify their impact on ET estimations for the major crops in the Texas High Plains under different agroclimatological conditions are needed before adopting the SEBS into operational ET remote sensing programs for irrigation scheduling or other purposes

Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters

The overarching objective of this study was to produce a disaggregated SMOS Soil Moisture (SM) product using land surface parameters from a geostationary satellite in a region covering a diverse range of ecosystem types. SEVIRI data at 15 minute temporal resolution were used to derive the Temperature and Vegetation Dryness Index (TVDI) that served as SM proxy within the disaggregation process. West Africa (3 N, 26 W; 28 N, 26 E) was selected as a case study as it presents both an important North-South climate gradient and a diverse range of ecosystem types. The main challenge was to set up a methodology applicable over a large area that overcomes the constraints of SMOS (low spatial resolution) and TVDI (requires similar atmospheric forcing and triangular shape formed when plotting morning rise temperature versus fraction of vegetation cover) in order to produce a 0.05 degree resolution disaggregated SMOS SM product at sub-continental scale. Consistent cloud cover appeared as one of the main constraints for deriving TVDI, especially during the rainy season and in the southern parts of the region and a large adjustment window (105x105 SEVIRI pixels) was therefore deemed necessary. Both the original and the disaggregated SMOS SM products described well the seasonal dynamics observed at six locations of in situ observations. However, there was an overestimation in both products for sites in the humid southern regions; most likely caused by the presence of forest. Both TVDI and the associated disaggregated SM product was found to be highly sensitive to algorithm input parameters; especially of conditions of high fraction of vegetation cover. Additionally, seasonal dynamics in TVDI did not follow the seasonal patters of SM. Still, its spatial heterogeneity was found to be a good proxy for disaggregating SMOS SM data; main river networks and spatial patterns of SM extremes (i.e. droughts and floods) not seen in the original SMOS SM product were revealed in the disaggregated SM product for a test case of July-September 2012. The disaggregation methodology thereby successfully increased the spatial resolution of SMOS SM, with potential application for local drought/flood monitoring of importance for the livelihood of the population of West Africa

Oceanic and terrestrial sources of continental precipitation

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Reviews of Geophysics 50 (2012): RG4003, doi:10.1029/2012RG000389.The most important sources of atmospheric moisture at the global scale are herein identified, both oceanic and terrestrial, and a characterization is made of how continental regions are influenced by water from different moisture source regions. The methods used to establish source-sink relationships of atmospheric water vapor are reviewed, and the advantages and caveats associated with each technique are discussed. The methods described include analytical and box models, numerical water vapor tracers, and physical water vapor tracers (isotopes). In particular, consideration is given to the wide range of recently developed Lagrangian techniques suitable both for evaluating the origin of water that falls during extreme precipitation events and for establishing climatologies of moisture source-sink relationships. As far as oceanic sources are concerned, the important role of the subtropical northern Atlantic Ocean provides moisture for precipitation to the largest continental area, extending from Mexico to parts of Eurasia, and even to the South American continent during the Northern Hemisphere winter. In contrast, the influence of the southern Indian Ocean and North Pacific Ocean sources extends only over smaller continental areas. The South Pacific and the Indian Ocean represent the principal source of moisture for both Australia and Indonesia. Some landmasses only receive moisture from the evaporation that occurs in the same hemisphere (e.g., northern Europe and eastern North America), while others receive moisture from both hemispheres with large seasonal variations (e.g., northern South America). The monsoonal regimes in India, tropical Africa, and North America are provided with moisture from a large number of regions, highlighting the complexities of the global patterns of precipitation. Some very important contributions are also seen from relatively small areas of ocean, such as the Mediterranean Basin (important for Europe and North Africa) and the Red Sea, which provides water for a large area between the Gulf of Guinea and Indochina (summer) and between the African Great Lakes and Asia (winter). The geographical regions of Eurasia, North and South America, and Africa, and also the internationally important basins of the Mississippi, Amazon, Congo, and Yangtze Rivers, are also considered, as is the importance of terrestrial sources in monsoonal regimes. The role of atmospheric rivers, and particularly their relationship with extreme events, is discussed. Droughts can be caused by the reduced supply of water vapor from oceanic moisture source regions. Some of the implications of climate change for the hydrological cycle are also reviewed, including changes in water vapor concentrations, precipitation, soil moisture, and aridity. It is important to achieve a combined diagnosis of moisture sources using all available information, including stable water isotope measurements. A summary is given of the major research questions that remain unanswered, including (1) the lack of a full understanding of how moisture sources influence precipitation isotopes; (2) the stationarity of moisture sources over long periods; (3) the way in which possible changes in intensity (where evaporation exceeds precipitation to a greater of lesser degree), and the locations of the sources, (could) affect the distribution of continental precipitation in a changing climate; and (4) the role played by the main modes of climate variability, such as the North Atlantic Oscillation or the El Niño–Southern Oscillation, in the variability of the moisture source regions, as well as a full evaluation of the moisture transported by low-level jets and atmospheric rivers.Luis Gimeno would like to thank the Spanish Ministry of Science and FEDER for their partial funding of this research through the project MSM. A. Stohl was supported by the Norwegian Research Council within the framework of the WATER‐SIP project. The work of Ricardo Trigo was partially supported by the FCT (Portugal) through the ENAC project (PTDC/AAC-CLI/103567/2008).2013-05-0

Laboratory Calibration of the Float Method for Open-Channel Flow Mesurement

Measurements were taken in a rectangular flume in a hydraulics laboratory to determine surface velocity coefficients for the float method, used in open-channel flow measurement, and to obtain detailed cross-sectional velocity profiles under steady-state, uniform flow conditions. Various longitudinal bed slopes were used, each with a series of different flow rates. Measured values were compared to published surface velocity coefficients, and the cross-sectional velocity profiles were used to help calibrate a three-dimensional mathematical model of open channel flow, currently being used in the study of surface velocity coefficients for the calibration of the float method

Multi-model, multi-sensor estimates of global evapotranspiration: climatology, uncertainties and trends

International audienceEstimating evapotranspiration (ET) at continental to global scales is central to understanding the partitioning of energy and water at the earth's surface and the feedbacks with the atmosphere and biosphere, especially in the context of climate change. Recent evaluations of global estimates from remote sensing, upscaled observations, land surface models and atmospheric reanalyses indicate large uncertainty across the datasets of the order of 50% of the global annual mean value. In this paper, we explore the uncertainties in global land ET estimates using three process-based ET models and a set of remote sensing and observational based radiation and meteorological forcing datasets. Input forcings were obtained from International Satellite Cloud Climatology Project (ISCCP) and Surface Radiation Budget (SRB). The three process-based ET models are: a surface energy balance method (SEBS), a revised Penman-Monteith (PM) model, and a modified Priestley-Taylor model. Evaluations of the radiation products from ISCCP and SRB show large differences in the components of surface radiation, and temporal inconsistencies that relate to changes in satellite sensors and retrieval algorithms. In particular, step changes in the ISCCP surface temperature and humidity data lead to spurious increases in downward and upward longwave radiation that contributes to a step change in net radiation, and the ISCCP data are not used further. An ensemble of global estimates of land surface ET are generated at daily time scale and 0.5 degree spatial resolution for 1984-2007 using two SRB radiation products (SRB and SRBqc) and the three models. Uncertainty in ET from the models is much larger than the uncertainty from the radiation data. The largest uncertainties relative to the mean annual ET are in transition zones between dry and humid regions and monsoon regions. Comparisons with previous studies and an inferred estimate of ET from long-term inferred ET indicate that the ensemble mean value is reasonable, but generally biased high globally. Long-term changes over 1984-2007 indicate a slight increase over 1984-1998 and decline thereafter, although uncertainties in the forcing radiation data and lack of direct linkage with soil moisture limitations in the models prevents attribution of these changes

Long-term global evapotranspiration from remote sensing

Deriving overland evapotranspiration (ET) estimates is an important part of the larger effort to develop long-term Earth System Data Records (ESDRs) for the major components (storages and fluxes) of the terrestrial water cycle. In the current study, global estimates of sensible heat and evaporative fluxes are developed for 1984-2006 using three process-based models forced by two remote sensing based data sets. The models are surface energy balance system (SEBS), a modified Penman-Monteith approach, and a Priestley-Taylor approach. The models are driven by radiation inputs from the ISCCP and SRB data sets, with the meteorological forcing data from ISCCP, and vegetation characteristics from AVHRR. Estimates are made using the three models. Comparisons among the data sets show large differences in magnitude and long-term variability, due mainly to uncertainties in the forcing radiation. Comparisons with independent data sets from inferred evaporation estimates [(P-Q)climatology], off-line land surface model (VIC) data, previously developed remote sensing products and estimates derived from tower data, reveals consistency at large scales, but large differences in some regions, most notably in the northern hemisphere

Multimodel analysis of energy and water fluxes: Intercomparisons between operational analyses, a land surface model, and remote sensing

Using data from seven global model operational analyses (OA), one land surface model, and various remote sensing retrievals, the energy and water fluxes over global land areas are intercompared for 2003/04. Remote sensing estimates of evapotranspiration (ET) are obtained from three process-based models that use input forcings from multisensor satellites. An ensemble mean (linear average) of the seven operational (mean-OA) models is used primarily to intercompare the fluxes with comparisons performed at both global and basin scales. At the global scale, it is found that all components of the energy budget represented by the ensemble mean of the OA models have a significant bias. Net radiation estimates had a positive bias (global mean) of 234 MJ m -2 yr -1 (7.4 W m -2) as compared to the remote sensing estimates, with the latent and sensible heat fluxes biased by 470 MJ m -2 yr -1 (13.3 W m -2) and 2367 MJ m -2 yr -1 (11.7 W m -2), respectively. The bias in the latent heat flux is affected by the bias in the net radiation, which is primarily due to the biases in the incoming shortwave and outgoing longwave radiation and to the nudging process of the operational models. The OA models also suffer from improper partitioning of the surface heat fluxes. Comparison of precipitation (P) analyses from the various OA models, gauge analysis, and remote sensing retrievals showed better agreement than the energy fluxes. Basin-scale comparisons were consistent with the global-scale results, with the results for the Amazon in particular showing disparities betweenOAand remote sensing estimates of energy fluxes. The biases in the fluxes are attributable to a combination of errors in the forcing from the OA atmospheric models and the flux calculation methods in their land surface schemes. The atmospheric forcing errors aremainly attributable to high shortwave radiation likely due to the underestimation of clouds, but also precipitation errors, especially in water-limited regions.</p