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  • 1
    Publication Date: 2021-10-14
    Description: This study provides a comprehensive evaluation of a great variety of state-of-the-art precipitation datasets against gauge observations over the Karun basin in southwestern Iran. In particular, we consider (a) gauge-interpolated datasets (GPCCv8, CRU TS4.01, PREC/L, and CPC-Unified), (b) multi-source products (PERSIANN-CDR, CHIRPS2.0, MSWEP V2, HydroGFD2.0, and SM2RAIN-CCI), and (c) reanalyses (ERA-Interim, ERA5, CFSR, and JRA-55). The spatiotemporal performance of each product is evaluated against monthly precipitation observations from 155 gauges distributed across the basin during the period 2000–2015. This way, we find that overall the GPCCv8 dataset agrees best with the measurements. Most datasets show significant underestimations, which are largest for the interpolated datasets. These underestimations are usually smallest at low altitudes and increase towards more mountainous areas, although there is large spread across the products. Interestingly, no overall performance difference can be found between precipitation datasets for which gauge observations from Karun basin were used, versus products that were derived without these measurements, except in the case of GPCCv8. In general, our findings highlight remarkable differences between state-of-the-art precipitation products over regions with comparatively sparse gauge density, such as Iran. Revealing the best-performing datasets and their remaining weaknesses, we provide guidance for monitoring and modelling applications which rely on high-quality precipitation input.
    Keywords: 551.6 ; evaluation ; interpolated dataset ; Karun basin ; precipitation datasets ; reanalysis dataset ; satellite rainfall estimate
    Language: English
    Type: map
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  • 2
    Publication Date: 2020-07-03
    Electronic ISSN: 2045-2322
    Topics: Natural Sciences in General
    Published by Springer Nature
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  • 3
    Publication Date: 2017-12-07
    Description: This paper investigates the accuracy of Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG), which provides merged microwave and infrared satellite precipitation estimates, over the contiguous US. The study focuses on diurnal variations in precipitation during a two-year summer period (June-July-August, 2014-2015). The normalized amplitude and phase of the diurnal cycle of IMERG are evaluated against those of ground reference from the Multi-Radar/Multi-Sensor system in terms of precipitation amount, frequency, and intensity on a 1 ∘ /1-h scale. IMERG well captures large-scale regional features of the diurnal cycle of precipitation and overall agrees well with the reference for both diurnal and semidiurnal variations. The comparison results indicate that the IMERG precipitation estimates can be a reliable alternative to ground-based measurements even at the subdaily scale; however, region-specific data discrepancies are still observed. For instance, we reveal that IMERG substantially overestimates normalized amplitude of diurnal precipitation in the central US, while IMERG tends to underestimate diurnal variations over the mountain regions in the western and eastern US. In terms of phase, we find a significant difference in the timing of peak precipitation between convective and stratiform regions of mesoscale convective systems (MCSs) over the Great Plains. This time shift is more apparent during the mature and dissipation stages of MCSs, which lead to relatively early peaks in the diurnal cycle of precipitation from IMERG. This phase bias implies a higher sensitivity of IMERG towards the convective regions of MCSs, supposedly because of the brightness temperature depression coming from ice particles aloft sampled by spaceborne passive microwave sensors. Such discrepancy between the actual and satellite-estimated precipitation timing can be challenging, e.g., when the satellite data are used to study subdaily precipitation processes or to validate numerical simulations. Consequently, our assessment of the IMERG performances highlights the need for improvements of the IMERG system.
    Print ISSN: 0035-9009
    Electronic ISSN: 1477-870X
    Topics: Geography , Physics
    Published by Wiley
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  • 4
    Publication Date: 2018-08-21
    Description: Extreme convective precipitation on subhourly scales is notoriously misrepresented in rain gauge-based observations, but uncertainties are weakly quantified at the 1 to 30 km scale. We employ a unique observing network, the high-density WegenerNet and surrounding operational rain gauge network in southeastern Austria, to sample convective precipitation extremes at these scales. By systematically constructing lower-density networks, we explore how estimated maximum area precipitation depends on observing station density. Using subhourly to hourly temporal resolution, we find a d−0.5(±0.1) power law decay of the event maximum area precipitation over distances d from 1 to 30 km, showing that operational gauge networks underrate extreme convective precipitation falling over small areas. Furthermore, extremes at point scale are found underestimated by operational networks by about 20%. We consider the dependencies representative for short-duration convective events over similar regions at midlatitudes and the results valuable for high-resolution climate model evaluation. ©2018. The Authors.
    Print ISSN: 0094-8276
    Electronic ISSN: 1944-8007
    Topics: Geosciences , Physics
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  • 5
    Publication Date: 2017-09-27
    Print ISSN: 1976-7633
    Electronic ISSN: 1976-7951
    Topics: Geosciences , Physics
    Published by Springer
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  • 6
    Publication Date: 2020-07-23
    Description: Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over poorly gauged regions. This study examines the usefulness of current state-of-the-art precipitation data sets in hydrological modeling. For this purpose, we force a conceptual hydrological model with multiple precipitation data sets in 〉200 European catchments to obtain runoff and evapotranspiration. We consider a wide range of precipitation products, which are generated via (1) the interpolation of gauge measurements (E-OBS and Global Precipitation Climatology Centre (GPCC) V.2018), (2)  data assimilation into reanalysis models (ERA-Interim, ERA5, and Climate Forecast System Reanalysis – CFSR), and (3) a combination of multiple sources (Multi-Source Weighted-Ensemble Precipitation; MSWEP V2). Evaluation is done at the daily and monthly timescales during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs; in contrast, simulated evapotranspiration is generally much less influenced in our comparatively wet study region. We also find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation data sets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the particularly strong agreement, while ERA5, GPCC V.2018, and MSWEP V2 show good performances. We further reveal climate-dependent performance variations of the considered data sets, which can be used to guide their future development. The overall best agreement is achieved when using an ensemble mean generated from all the individual products. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions, such as central Europe, there are increasing implications for evapotranspiration in drier regions.
    Print ISSN: 1027-5606
    Electronic ISSN: 1607-7938
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
    Publication Date: 2020-08-25
    Description: Future climate projections require Earth system models to simulate conditions outside their calibration range. It is therefore crucial to understand the applicability of such models and their modules under transient conditions. This study assesses the robustness of different types of models in terms of rainfall–runoff modeling under changing conditions. In particular, two process-based models and one data-driven model are considered: 1) the physically based land surface model of the European Centre for Medium-Range Weather Forecasts, 2) the conceptual Simple Water Balance Model, and 3) the Long Short-Term Memory-Based Runoff model. Using streamflow data from 161 catchments across Europe, a differential split-sample test is performed, i.e., models are calibrated within a reference period (e.g., wet years) and then evaluated during a climatically contrasting period (e.g., drier years). Models show overall performance loss, which generally increases the more conditions deviate from the reference climate. Further analysis reveals that the models have difficulties in capturing temporal shifts in the hydroclimate of the catchments, e.g., between energy- and water-limited conditions. Overall, relatively high robustness is demonstrated by the physically based model. This suggests that improvements of physics-based parameterizations can be a promising avenue toward reliable climate change simulations. Further, our study illustrates that comparison across process-based and data-driven models is challenging due to their different nature. While we find rather low robustness of the data-driven model in our particular split-sample setup, this must not apply generally; by contrast, such model schemes have great potential as they can learn diverse conditions from observed spatial and temporal variability both at the same time to yield robust performance.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2020-10-01
    Electronic ISSN: 2589-0042
    Topics: Biology , Chemistry and Pharmacology , Geosciences , Natural Sciences in General , Physics
    Published by Cell Press
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  • 9
    Publication Date: 2018-07-19
    Description: This study investigates the potential changes in surface energy budget components under certain future climate conditions over the Alps and Northern Italy. The regional climate scenarios are obtained though the Regional Climate Model version 3 (RegCM3) runs, based on a reference climate (1961–1990) and the future climate (2071–2100) via the A2 and B2 scenarios. The energy budget components are calculated by employing the University of Torino model of land Processes Interaction with Atmosphere (UTOPIA), and using the RegCM3 outputs as input data. Our results depict a significant change in the energy budget components during springtime over high-mountain areas, whereas the most relevant difference over the plain areas is the increase in latent heat flux and hence, evapotranspiration during summertime. The precedence of snow-melting season over the Alps is evidenced by the earlier increase in sensible heat flux. The annual mean number of warm and cold days is evaluated by analyzing the top-layer soil temperature and shows a large increment (slight reduction) of warm (cold) days. These changes at the end of this century could influence the regional radiative properties and energy cycles and thus, exert significant impacts on human life and general infrastructures.
    Electronic ISSN: 2073-4441
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 10
    Publication Date: 2020-01-05
    Print ISSN: 0899-8418
    Electronic ISSN: 1097-0088
    Topics: Geosciences , Physics
    Published by Wiley
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