Evaluation of Radiation Components in a Global Freshwater Model with Station-Based Observations

Schmied, Hannes Müller; Müller, Richard; Sánchez-Lorenzo, Arturo; Ahrens, Bodo; Wild, Martin

doi:10.3390/w8100450

Cited by 21 publications

(26 citation statements)

References 52 publications

(67 reference statements)

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“…Similarly to climate models, reanalyses were shown to have difficulties in representing the multidecadal variations in surface shortwave radiation seen in the GEBA data (Wild and Schmucki, 2011). The quality of reanalysis-calculated surface radiative fluxes has also been assessed with GEBA data to check their suitability as input data in a global hydrological modeling framework (Müller Schmied et al, 2016).…”

Section: Validation Of Surface Energy Fluxes From Climate Models Reamentioning

confidence: 99%

The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

Wild

Ohmura

Schär

et al. 2017

Earth Syst. Sci. Data

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110

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Abstract. The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as "global dimming" and "brightening". GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.

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Section: Validation Of Surface Energy Fluxes From Climate Models Reamentioning

confidence: 99%

The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

Wild

Ohmura

Schär

et al. 2017

Earth Syst. Sci. Data

Self Cite

110

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“…It is expected to find high correlations from TWSA-SWEA rela- In a number of studies, the performance of the WGHM in the simulation of discharge, reservoir, radiation, and evapotranspiration was evaluated, and it was found that the model estimate in the gridded and basin scales generally outperforms other global models (Masaki et al, 2017;Müller Schmied et al, 2016b;Veldkamp et al, 2018;Wartenburger et al, 2018;Zaherpour et al, 2018Zaherpour et al, , 2019Zhao et al, 2017). The comparison of seasonal amplitudes of the model to GRACE data showed that WGHM underestimates TWSA in the Southern Hemisphere and the tropics but compares favourably with GRACE in the Northern…”

Section: Discussionmentioning

confidence: 99%

“…The Water-Global Assessment and Prognosis Global Hydrology Model (WGHM) is part of the Water-Global Assessment and Prognosis (WaterGAP) model Müller Schmied et al, 2016aMüller Schmied, 2017;Müller Schmied et al, 2016b). It calculates water fluxes and storages on global land area.…”

Section: Wghm Terrestrial Water Storagementioning

confidence: 99%

Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Bahrami

Goı̈ta

Magagi

2019

Hydrological Processes

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In this study, the spatial and temporal variabilities of terrestrial water storage anomaly (TWSA) and snow water equivalent anomaly (SWEA) information obtained from the Gravity Recovery and Climate Experiment (GRACE) twin satellites data were analysed in conjunction with multisource snow products over several basins in the Canadian landmass. Snow water equivalent (SWE) data were extracted from three different sources: Global Snow Monitoring for Climate Research version 2 (GlobSnow2), Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E), and Canadian Meteorological Centre (CMC). The objective of the study was to understand whether SWE variations have a significant contribution to terrestrial water storage anomalies in the Canadian landmass. The period was considered from December 2002 to March 2011. Significant relationships were observed between TWSA and SWEA for most of the 15 basins considered (53% to 80% of the basins, depending on the SWE products considered). The best results were obtained with the CMC SWE products compared with satellite‐based SWE data. Stronger relationships were found in snow‐dominated basins (Rs > = 0.7), such as the Liard [root mean square error (RMSE) = 21.4 mm] and Peace Basins (RMSE = 26.76 mm). However, despite high snow accumulation in the north of Quebec, GRACE showed weak or insignificant correlations with SWEA, regardless of the data sources. The same behaviour was observed in the Western Hudson Bay basin. In both regions, it was found that the contribution of non‐SWE compartments including wetland, surface water, as well as soil water storages has a significant impact on the variations of total storage. These components were estimated using the Water‐Global Assessment and Prognosis Global Hydrology Model (WGHM) simulations and then subtracted from GRACE observations. The GRACE‐derived SWEA correlation results showed improved relationships with three SWEA products. The improvement is particularly important in the sub‐basins of the Hudson Bay, where very weak and insignificant results were previously found with GRACE TWSA data. GRACE‐derived SWEA showed a significant relationship with CMC data in 93% of the basins (13% more than GRACE TWSA). Overall, the results indicated the important role of SWE on terrestrial water storage variations.

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“…As part of so-called climate or meteorological forcing datasets such as those generated within the Global Soil Wetness Project (GSWP; Zhao and Dirmeyer, 2003), at Princeton University (Sheffield et al, 2006), and within the Integrated Project Water and Global Change (WATCH; Weedon et al, 2011), the longwave and shortwave components of surface downwelling radiation (abbreviated as rlds and rsds or just longwave and shortwave radiation in the following) are used to correct model biases in climate model output (Hempel et al, 2013;Iizumi et al, 2017;Cannon, 2017) and drive simulations of climate impacts, for example (Müller Schmied et al, 2016;Veldkamp et al, 2017;Chang et al, 2017;Krysanova and Hattermann, 2017;Ito et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

Lange

2018

Earth Syst. Dynam.

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Abstract. Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds). Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016) rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011) data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016). This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.

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Evaluation of Radiation Components in a Global Freshwater Model with Station-Based Observations

Cited by 21 publications

References 52 publications

The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada

Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset

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