Testing the Hydrological Coherence of High‐Resolution Gridded Precipitation and Temperature Data Sets
| Autor: | Sebastiano Piccolroaz, Grigory Nikulin, Lavinia Laiti, Stefano Mallucci, Aldo Fiori, Dino Zardi, Alberto Bellin, Bruno Majone |
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| Přispěvatelé: | Laiti, L., Mallucci, S., Piccolroaz, S., Bellin, A., Zardi, D., Fiori, A., Nikulin, G., Majone, B. |
| Rok vydání: | 2018 |
| Předmět: |
Alpine region
010504 meteorology & atmospheric sciences 0208 environmental biotechnology gridded climate data High resolution 02 engineering and technology Coherence (statistics) observational uncertainty 01 natural sciences hydrological modeling Physics::Geophysics 020801 environmental engineering 13. Climate action Adige river basin hydrological coherence Water Science and Technology Precipitation Computer Science::Distributed Parallel and Cluster Computing Physics::Atmospheric and Oceanic Physics Geology 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Water Resources Research. 54:1999-2016 |
| ISSN: | 1944-7973 0043-1397 |
| DOI: | 10.1002/2017wr021633 |
| Popis: | Assessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989–2008 and includes five gridded daily meteorological data sets: E-OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E-OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large-scale hydroclimatic studies. |
| Databáze: | OpenAIRE |
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