On correcting precipitation as simulated by the regional climate model COSMO-CLM with daily rain gauge observations

Lindau, Ralf; Simmer, Clemens

doi:10.1007/s00703-012-0215-7

Cited by 9 publications

(10 citation statements)

References 25 publications

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“…Even though each gridded climate data set incorporates information derived from station‐based climate observations, the reliability of the data vary with the quality and density of observing stations and the topography of the region. Therefore, additional comparisons of each gridded data set with reliable observational data were necessary to identify the most consistent gridded data set corresponding to the different seasons and regions within the ARB (Petrik et al ., ; Lindau and Simmer, ). Observational station data employed in these data sets were obtained from (1) the study of Mekis and Vincent (), who adjusted daily rainfall and snowfall data for 450 stations over Canada that account for not only wind undercatch and evaporation and wetting losses for each type of rain gauges but also a density correction from a set of coincident ruler measurements and Nipher gauge observations for snowfall stations and (ii) the study of Vincent et al .…”

Section: Methodsmentioning

confidence: 99%

Inter‐comparison of high‐resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed, Canada

Eum

Dibike

Prowse

et al. 2014

Hydrological Processes

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Abstract:Several different gridded climate data sets have recently been made available with the purpose of providing a consistent set of climatic data for many hydro-climatic studies. Recent advances in land-surface schemes and their implementation in fully distributed processes-based hydrologic models have demanded even higher-resolution gridded data. It remains, however, a challenge to identify the most reliable gridded climate data for hydrologic modelling, especially in mountainous headwater regions where there is significant spatial variability but few observing stations. Moreover, the accuracy of such climate forcing data applied to alpine headwaters directly affects the modelled hydrologic responses of the lower, downstream portions of river basins. This study evaluates the spatial and temporal differences in precipitation and temperature fields among three highresolution climate data sets available in Canada, namely, the North American Regional Reanalysis, the Canadian Precipitation Analysis and the thin-plate smoothing splines (ANUSPLIN). Inter-comparison of the quality of these data sets was undertaken for the Athabasca River basin in western Canada. The hydrologic responses of this watershed with respect to each of the three gridded climate data sets were also evaluated using the Variable Infiltration Capacity model. Results indicate that the data sets have systematic differences, which vary with regional characteristics -the largest differences being for mountainous regions. The hydrologic model simulations corresponding to those three forcing data sets also show significant differences and more with North American Regional Reanalysis than those between Canadian Precipitation Analysis and ANUSPLIN.

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Section: Methodsmentioning

confidence: 99%

Inter‐comparison of high‐resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed, Canada

Eum

Dibike

Prowse

et al. 2014

Hydrological Processes

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“…Long-term, large-scale precipitation records guide decisions related to water resource management; short-term, finescale measurements are mandatory for accurate predictions of flash floods. Accurate QPE may also lead to improved precipitation forecasts by means of data assimilation in numerical weather prediction (NWP) models (e.g., Milan et al 2008Milan et al , 2014, for the verification of weather forecast and climate models (e.g., Bachner et al 2008;Lindau and Simmer 2013), and development of statistical forecasting tools, such as model output statistics (MOS). Precipitation radars have the potential to provide the fields of precipitation rate with high temporal and spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Using Microwave Backhaul Links to Optimize the Performance of Algorithms for Rainfall Estimation and Attenuation Correction

Trömel

Ziegert

Ryzhkov

et al. 2014

Journal of Atmospheric and Oceanic Technology

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The variability in raindrop size distributions and attenuation effects are the two major sources of uncertainty in radar-based quantitative precipitation estimation (QPE) even when dual-polarization radars are used. New methods are introduced to exploit the measurements by commercial microwave radio links to reduce the uncertainties in both attenuation correction and rainfall estimation. The ratio a of specific attenuation A and specific differential phase K DP is the key parameter used in attenuation correction schemes and the recently introduced R(A) algorithm. It is demonstrated that the factor a can be optimized using microwave links at Ku band oriented along radar radials with an accuracy of about 20%-30%. The microwave links with arbitrary orientation can be utilized to optimize the intercepts in the R(K DP ) and R(A) relations with an accuracy of about 25%. The performance of the suggested methods is tested using the polarimetric C-band radar operated by the German Weather Service on Mount Hohenpeissenberg in southern Germany and two radially oriented Ku-band microwave links from Ericsson GmbH.

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“…Also the simulated seasonal patterns compare well with REGNIE, but the virtual reality overestimates precipitation over the mountains and the south-eastern part of the Neckar catchment. Such differences have also been found for COSMO coupled to its own TERRA land surface model with the same spatial resolution (e.g., Dierer et al, 2009;Lindau and Simmer, 2013). During summer (June to August) cloud bases are usually higher and reduce luff-lee effects.…”

Section: Precipitationmentioning

confidence: 58%

High-Resolution Virtual Catchment Simulations of the Subsurface-Land Surface-Atmosphere System

Schalge

Rihani

Baroni

et al. 2016

Preprint

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Abstract. Combining numerical models, which simulate water and energy fluxes in the subsurface-land surface-atmosphere system in a physically consistent way, becomes increasingly important to understand and study fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models, when run at highest possible resolutions while incorporating as many processes as attainable, may be regarded as a proxy of the real world – a virtual reality – which can be used to test hypotheses on functioning of the coupled terrestrial system and may serve as source for virtual measurements to develop data-assimilation methods. Such simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in the compartments of the terrestrial system. The present study is motivated by the development of cross-compartmental data-assimilation methods, which face the difficulty of data scarcity in the subsurface when applied to real data. With appropriate and realistic measurement operators, the virtual reality not only allows taking virtual observations in any part of the terrestrial system at any density, thus overcoming data-scarcity problems of real-world applications, but also provides full information about true states and parameters aimed to be reconstructed from the measurements by data assimilation. In the present study, we have used the Terrestrial Systems Modeling Platform TerrSysMP, which couples the meteorological model COSMO, the land-surface model CLM, and the subsurface model ParFlow, to set up the virtual reality for a regional terrestrial system roughly oriented at the Neckar catchment in southwest Germany. We find that the virtual reality is in many aspects quite close to real observations of the catchment concerning, e.g., atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent both in the ability of such models to correctly simulate some processes – which still need improvement – and the realism of the results of some observation operators like the SMOS and SMAP sensors, when faced with model states. In a succeeding step, we will use the virtual reality to generate observations in all compartments of the system for coupled data assimilation. The data assimilation will rely on a coarsened and simplified version of the model system.

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On correcting precipitation as simulated by the regional climate model COSMO-CLM with daily rain gauge observations

Cited by 9 publications

References 25 publications

Inter‐comparison of high‐resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed, Canada

Inter‐comparison of high‐resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed, Canada

Using Microwave Backhaul Links to Optimize the Performance of Algorithms for Rainfall Estimation and Attenuation Correction

High-Resolution Virtual Catchment Simulations of the Subsurface-Land Surface-Atmosphere System

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