Evaluation of gauge adjustment methods in improving radar precipitation estimation quality over Antalya radar in Turkey.

Yousufi, Kaveh Patakchi
Yılmaz, Mustafa Tuğrul
Ozturk, Kurtulus
Yücel, İsmail
Yılmaz, Koray Kamil
Radar-based precipitation estimates rely on algorithms that utilize observations of backscattered waves sent from the radar. By utilizing these backscattered observations and different reflectivity-rainfall (Z-R) equations, radar-based precipitation estimates are obtained. However, this process contains uncertainties due to used Z-R equations or other error sources such as beam blockage, attenuation, etc. on the radar beams. The majority of the studies in the literature focused on reducing errors caused by Z-R relation and radar beam correction. This study investigates relative performances of different statistical algorithms to improve radar-based quantitative precipitation estimation (QPE) using ground observation data, rather than focusing on the evaluation of different Z-R relationships and reflectivity corrections commonly implemented in the literature. Initial investigations are implemented using datasets obtained over Antalya radar, while this study will be extended using all 18 radar-based observations acquired over different regions of Turkey. Implemented statistical methodologies include Mean Field Bias (MFB), Local Multiplicative Bias (LMB), Local Additive Bias (LAB), Local Mixed Bias (LMIB), and Multiple Linear Regression (MLR) adjustment techniques. To test the performance of these algorithms, cross-validation methods have been used. In cross-validation, 50%, 25%, 12.5% of the station-based observations are excluded for validation while the remaining are used for the calibration in different experiments. Both the calibration and validation results obtained from all rainfall events of 2015 for Antalya radar suggests LMB, LMIB, and LAB adjustment methods perform better in terms of agreement with the rain-gauge observations. However, LMB doesn’t contribute significantly to the improvement of the correlation coefficient. The advantage of the proposed time-independent MLR method is that does not require any gauge observation for real-time radar estimation correction, and it is quite successful in addressing the radar underestimation problem on a monthly scale. However, the spatial distribution of the RMSE and Correlation Coefficient plots suggest multiplicative bias correction methods (MFB, LMB, and MLR) fail to contribute to improving the accuracy of the radar QPE in the areas with a partial or complete radar beam blockage.
IV. Meteorolojik Uzaktan Algılama Sempozyumu (11 - 15 Kasım 2019)


Production of a high-resolution improved radar precipitation estimation map using gauge adjustment bias correction methods
Yousefi, Kaveh Patakchi; Yılmaz, Mustafa Tuğrul; Ozturk, Kurtulus; Yücel, İsmail; Yılmaz, Koray Kamil (null; 2020-05-08)
This study evaluates relative performances of different statistical algorithms to enhance radar-based quantitative precipitation estimation (QPE) accuracy using rain gauge network data. Initial investigations are implemented using observations obtained via 17 C-band radars located over different regions of Turkey. It was observed that there is an underestimation problem in radar estimations compared with the ground observations. According to the initial results, daily mean bias for radar estimations over di...
Evaluating the hydro-estimator satellite rainfall algorithm over a mountainous region
Yücel, İsmail; Gochis, David J. (2011-01-01)
This study investigates the performance of the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) operational rainfall estimation algorithm, called the hydro-estimator (HE), with and without its orographic correction method, in its depiction of the timing, intensity and duration of convective rainfall in general, and of the topography-rainfall relationship in particular. An event-based rainfall observation network in north-west Mexic...
Evaluating the use of different precipitation datsets in flood modelling
Akyürek, Sevda Zuhal (2016-04-17)
Satellite based precipitation products, numerical weather prediction model precipitation forecasts and weather radar precipitation estimates can be a remedy for gauge sparse regions especially in flood forecasting studies. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study compares the Hydro-Estimator precipitation product, Weather Research and Forecasting (WRF) model precipitation and weather radar values with gauge data in Samsun-T...
Evaluation of the sensitivity of open source DEM vs. local high resolution DEM data in tsunami hazard assessment
Tüfekçi Enginar, Duygu; Süzen, Mehmet Lütfi; Yalçıner, Ahmet Cevdet (2020-05-06)
Tsunami simulations using high resolution datasets would always resemble the results that are closer to the reality. However, high resolution airborne or spaceborne local datasets have not yet been available for many regions and acquisition of this data is costly or might not even be possible for some locations. This hard-to-reach situation of high resolution datasets obliged researchers to work with open source datasets in their studies, which forces them to cope with the uncertainties of low spatial resol...
Cetin, Ramazan; Erturk, Ozan; Akın, Tayfun (2018-09-14)
This study presents design, analysis, optimization, and fabrication of umbrella structures as an efficient quarter wave absorber within the Long Wave Infrared (LWIR) range for uncooled IR detectors. Both the effect of the ni-chrome (NiCr) layer and effect of varying pixel pitch sizes on the IR absorption performance of the umbrella structures are examined. An average of 96% absorption is measured for the optimized case within the LWIR range.
Citation Formats
K. P. Yousufi, M. T. Yılmaz, K. Ozturk, İ. Yücel, and K. K. Yılmaz, “Evaluation of gauge adjustment methods in improving radar precipitation estimation quality over Antalya radar in Turkey.,” presented at the IV. Meteorolojik Uzaktan Algılama Sempozyumu (11 - 15 Kasım 2019), Antalya, TURKEY, 2019, Accessed: 00, 2021. [Online]. Available: http://uzalmet.mgm.gov.tr/Default.aspx.