Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis
Land evapotranspiration (ET) estimates are available from several global datasets. Here, monthly global land ET synthesis products, merged from these individual datasets over the time periods 1989–1995 (7 yr) and 1989–2005 (17 yr), are presented. The 5 merged synthesis products over the shorter period are based on a total of 40 distinct datasets while those over the longer period are based on a total of 14 datasets. In the individual datasets, ET is derived from satellite and/or in-situ observations (diagnostic datasets) or calculated via land-surface models (LSMs) driven with observationsbased forcing and atmospheric reanalyses. Statistics for four merged synthesis prod10 ucts are provided, one including all datasets and three including only datasets from one category each (diagnostic, LSMs, and reanalyses). The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (1.15mmyr-2 in our merged product) followed by a decrease in this trend (-1.40mmyr-2), although 15 these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all datasets) is 1.35mm per day for both the 1989–1995 and 1989–2005 products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 34 406 km3 per year for a total land area of 130 922 km2. Precipitation, 20 being an important driving factor and input to most simulated ET datasets, presents uncertainties between single datasets as large as those in the ET estimates. In order to reduce uncertainties in current ET products, improving the accuracy of the input variables, especially precipitation, as well as the parameterizations of ET are crucial.
| Main Authors: | , , , , , , , , , |
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| Format: | Article/Letter to editor biblioteca |
| Language: | English |
| Subjects: | 20th-century, climate, evaporation, global-scale, model, reanalysis data, soil-moisture, surface, trends, variability, |
| Online Access: | https://research.wur.nl/en/publications/benchmark-products-for-land-evapotranspiration-landflux-eval-mult |
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| Summary: | Land evapotranspiration (ET) estimates are available from several global datasets. Here, monthly global land ET synthesis products, merged from these individual datasets over the time periods 1989–1995 (7 yr) and 1989–2005 (17 yr), are presented. The 5 merged synthesis products over the shorter period are based on a total of 40 distinct datasets while those over the longer period are based on a total of 14 datasets. In the individual datasets, ET is derived from satellite and/or in-situ observations (diagnostic datasets) or calculated via land-surface models (LSMs) driven with observationsbased forcing and atmospheric reanalyses. Statistics for four merged synthesis prod10 ucts are provided, one including all datasets and three including only datasets from one category each (diagnostic, LSMs, and reanalyses). The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (1.15mmyr-2 in our merged product) followed by a decrease in this trend (-1.40mmyr-2), although 15 these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all datasets) is 1.35mm per day for both the 1989–1995 and 1989–2005 products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 34 406 km3 per year for a total land area of 130 922 km2. Precipitation, 20 being an important driving factor and input to most simulated ET datasets, presents uncertainties between single datasets as large as those in the ET estimates. In order to reduce uncertainties in current ET products, improving the accuracy of the input variables, especially precipitation, as well as the parameterizations of ET are crucial. |
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