Extreme rainfall event in Crimea: Cloud-resolving modeling and radar observations

2020 ◽  
Author(s):  
Anatolii Anisimov ◽  
Vladimir Efimov ◽  
Margarita Lvova ◽  
Viktor Popov ◽  
Suleiman Mostamandi
Keyword(s):  
Spatial Resolution ◽  
Extreme Event ◽  
Flash Flood ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Squall Line ◽  
The Black Sea ◽  
Model Parameters ◽  
Extreme Rainfall Event ◽  
Radar Observations

<p>We present a case study on extreme rainfall event in Crimea in September 2018. The event was caused by extratropical cyclone forming above the Black Sea. The cyclone approached the Crimean Mountains from the south, producing over 100 mm of rainfall in Yalta on September 6 and causing a flash flood. In the mountains, about 140 mm of rainfall was reported. </p><p>To study this extreme event, we use the WRF model v.4.0.1 forced by the boundary conditions from ECMWF operational analysis with the spatial resolution of approximately 10 × 10 km. The model was run for 8 days of September 1 – 8, and 5 microphysical schemes were tested (WDM6, Morrison, Milbrandt, NSSL, and Thompson). Other model parameters were set identical to CONUS configuration suite. The simulations were done for two one-way nested convective-resolving domains with spatial resolution of 2.7× 2.7 km and 0.9 × 0.9 km. The simulations were verified using the meteorological radar observations in Simferopol airport and GPM measurements.</p><p>All of the microphysical schemes substantially underestimate the amount of rainfall reaching the ground compared to observations. However, several schemes (Milbrandt, Morrison, and WDM6) do add value to the forecasts, producing significantly larger amount of rainfall compared to the driving model that almost completely missed it on the local scale. WDM6 performs best to capture the proper location of the squall line and to reproduce the rainfall orographic enhancement in the mountains. The amount of rainfall in the child domain was also slightly larger compared to the parent one. Despite the rainfall underestimation, we also show that the simulated reflectivity patterns are in good agreement with observations, although the convective cores are wider and less intense compared to the observed by the radar.</p>

scholarly journals Evaluation of the WRF-ARW model during an extreme rainfall event: subtropical storm Guará

2021 ◽  
Author(s):  
Yasmin Kaore Lago Kitagawa ◽  
Erick Giovani Sperandio Nascimento ◽  
Noéle Bissoli Perini Souza ◽  
Pedro Junior Zucatelli ◽  
Prashant Kumar ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Temporal Evolution ◽  
Extreme Event ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Extreme Rainfall Event ◽  
Arw Model

This study simulates an unusual extreme rainfall event that occurred in Salvador City, Bahia, Brazil, on December 9, 2017, which was the subtropical storm Guará and had precipitation of approximately 24 mm within less than 1 h. Numerical simulations were conducted using the weather research and forecasting (WRF) model over three domains with horizontal resolutions of 9, 3, and 1 km. Different combinations of seven microphysics, three cumulus, and three planetary boundary layer schemes were evaluated based on their ability to simulate the hourly precipitation during this rainfall event. The results were compared with the data measured at the Brazilian National Institute of Meteorology (INMET) meteorological stations. The best configuration for the planetary boundary layer, cumulus, and microphysics schemes were Mellor-Yamada-Janjić, Grell-Devenyi, and Lin, respectively. The WRF model could depict the daily variations on the hourly parameters well, along with the spatial and temporal evolution of the extreme event.

scholarly journals Extreme rainfall impacts on soil CO2 efflux in an urban forest ecosystem in Beijing, China

2016 ◽  
Vol 96 (4) ◽  
pp. 504-514 ◽  
Author(s):  
Wenjing Chen ◽  
Xin Jia ◽  
Chunyi Li ◽  
Haiqun Yu ◽  
Jing Xie ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Forest Ecosystem ◽  
Urban Forest ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event ◽  
Co2 Efflux ◽  
Abrupt Decrease ◽  
Environmental Controls ◽  
Beijing China

Extreme rainfall events are infrequent disturbances that affect urban environments and soil respiration (Rs). Using data measured in an urban forest ecosystem in Beijing, China, we examined the link between gross primary production (GPP) and soil respiration on a diurnal scale during an extreme rainfall event (i.e., the “21 July 2012 event”), and we examined diel and seasonal environmental controls on Rs. Over the seasonal cycle, Rs increased exponentially with soil temperature (Ts). In addition, Rs was hyperbolically related to soil volumetric water content (VWC), increasing with VWC below a threshold of 0.17 m3 m−3, and then decreasing with further increases in VWC. Following the extreme rainfall event (177 mm), Rs showed an abrupt decrease and then maintained a low value of ∼0.3 μmol m−2 s−1 for about 8 h as soil VWC reached the field capacity (0.34 m3 m−3). Rs became decoupled from Ts and increased very slowly, while GPP showed a greater increase. A bivariate Q10-hyperbolical model, which incorporates both Ts and VWC effects, better fits Rs than the Q10 model in summer but not for whole year.

scholarly journals Impacts of Polarimetric Radar Observations on Hydrologic Simulation

2010 ◽  
Vol 11 (3) ◽  
pp. 781-796 ◽  
Author(s):  
Jonathan J. Gourley ◽  
Scott E. Giangrande ◽  
Yang Hong ◽  
Zachary L. Flamig ◽  
Terry Schuur ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Laboratory Research ◽  
Model Parameters ◽  
Polarimetric Radar ◽  
Storm Events ◽  
Hydrologic Simulation ◽  
Radar Observations

Abstract Rainfall estimated from the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler [WSR-88D (KOUN)] was evaluated using a dense Micronet rain gauge network for nine events on the Ft. Cobb research watershed in Oklahoma. The operation of KOUN and its upgrade to dual polarization was completed by the National Severe Storms Laboratory. Storm events included an extreme rainfall case from Tropical Storm Erin that had a 100-yr return interval. Comparisons with collocated Micronet rain gauge measurements indicated all six rainfall algorithms that used polarimetric observations had lower root-mean-squared errors and higher Pearson correlation coefficients than the conventional algorithm that used reflectivity factor alone when considering all events combined. The reflectivity based relation R(Z) was the least biased with an event-combined normalized bias of −9%. The bias for R(Z), however, was found to vary significantly from case to case and as a function of rainfall intensity. This variability was attributed to different drop size distributions (DSDs) and the presence of hail. The synthetic polarimetric algorithm R(syn) had a large normalized bias of −31%, but this bias was found to be stationary. To evaluate whether polarimetric radar observations improve discharge simulation, recent advances in Markov Chain Monte Carlo simulation using the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) were used. This Bayesian approach infers the posterior probability density function of model parameters and output predictions, which allows us to quantify HL-RDHM uncertainty. Hydrologic simulations were compared to observed streamflow and also to simulations forced by rain gauge inputs. The hydrologic evaluation indicated that all polarimetric rainfall estimators outperformed the conventional R(Z) algorithm, but only after their long-term biases were identified and corrected.

Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study

2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event
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