Evaluating a mesoscale atmosphere model and a satellite-based algorithm in estimating extreme rainfall events in northwestern Turkey

Quantitative precipitation estimates are obtained with more uncertainty under the influence of changing climate variability and complex topography from numerical weather prediction (NWP) models. On the other hand, hydrologic model simulations depend heavily on the availability of reliable precipitation estimates. Difficulties in estimating precipitation impose an important limitation on the possibility and reliability of hydrologic forecasting and early warning systems. This study examines the performance of the Weather Research and Forecasting (WRF) model and the Multi Precipitation Estimates (MPE) algorithm in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in the western Black Sea region of Turkey. Precipitation derived from WRF model with and without the three-dimensional variational (3DVAR) data assimilation scheme and MPE algorithm at high spatial resolution (5 km) are compared with gauge precipitation. WRF-derived precipitation showed capabilities in capturing the timing of precipitation extremes and to some extent the spatial distribution and magnitude of the heavy rainfall events, whereas MPE showed relatively weak skills in these aspects. WRF skills in estimating such precipitation characteristics are enhanced with the application of the 3DVAR scheme. Direct impact of data assimilation on WRF precipitation reached up to 12% and at some points there is a quantitative match for heavy rainfall events, which are critical for hydrological forecasts.


Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions
Derin, Yagmur; Anagnostou, Emmanouil; Berne, Alexis; Borga, Marco; Boudevillain, Brice; Buytaert, Wouter; Chang, Che-Hao; Chen, Haonan; Delrieu, Guy; Hsu, Yung Chia; Lavado-Casimiro, Waldo; Manz, Bastian; Moges, Semu; Nikolopoulos, Efthymios I.; Sahlu, Dejene; Salerno, Franco; Rodriguez-Sanchez, Juan-Pablo; Vergara, Humberto J.; Yılmaz, Koray Kamil (MDPI AG, 2019-12-02)
The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014-2015) of reference daily precipitation data from rain gauge networks in te...
Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey
Bulut, Burak; Yılmaz, Mustafa Tuğrul; Afshar, Mahdı Hesamı ; Sorman, A. Unal; Yücel, İsmail; Cosh, Michael H.; Simsek, Osman (MDPI AG, 2019-08-01)
This study evaluates the performance of widely-used remotely sensed- and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), the Antecedent Precipitation Index (API), and the Global Land Data Assimilation System (GLDAS-NOAH). Evaluations are performed between 2008 and 2011 against the calibrated station-based soil moisture observations coll...
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Sancak, S; Besiktepe, ST; Yılmaz, Ayşen; Lee, M; Frouin, R (Informa UK Limited, 2005-05-20)
The performance of NASA's OC2 and OC4 algorithms to estimate chlorophyll-a concentrations from SeaWiFS radiometric measurements on the global scale was tested in two contrasted bio-optical environments, the Black Sea and the Mediterranean Sea. The in situ bio-optical measurements were made during October 1999 at 25 stations. Comparisons of the in situ measurements with the concurrent SeaWiFS retrievals indicate that the OC2 and OC4 algorithms are not working satisfactorily in both seas. Case 2 waters domina...
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Sensoy, A; Tekeli, AE; Forman, AA; Sorman, AU (Informa UK Limited, 2003-12-01)
In mountainous regions, runoff from snowmelt is an important hydrologic and economic factor, and therefore early runoff forecasting brings significant advantages to the planning and operation of water resources systems. Similarly, predicting runoff from snowmelt during spring months in the eastern part of Turkey, where most of the water originates from high mountains and contributes to the large dams on the Euphrates River, is of crucial importance. In this study, an event-type, physically based hydrologic ...
Integration of environmental variables with satellite images in regional scale vegetation classification
Domaç, Ayşegül; Süzen, Mehmet Lütfi; Bilgin, Cemal Can (Informa UK Limited, 2006-04-01)
The difficulty of collecting information at conventional field studies and relatively coarse spatial and spectral resolution of Landsat images forced the use of environmental variables as ancillary data in vegetation mapping. The aim of this study is to increase the accuracy of species level vegetation classification incorporating environmental variables in the Amanos Mountains region of southern central Turkey. In the first part of the study, ordinary vegetation classification is attained by using a maximu...
Citation Formats
İ. Yücel, “Evaluating a mesoscale atmosphere model and a satellite-based algorithm in estimating extreme rainfall events in northwestern Turkey,” NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, pp. 611–624, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35778.