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MAUSAM ◽  
2021 ◽  
Vol 62 (3) ◽  
pp. 305-320
Author(s):  
D.R. PATTANAIK ◽  
ANUPAM KUMAR ◽  
Y.V.RAMA RAO ◽  
B. MUKHOPADHYAY

The monsoon depression of September 2008, which crossed Orissa coast near Chandbali on 16th had contributed heavy rainfall over Orissa, Chhattisgarh and northern India along the track of the system. The sensitivity of three cumulus parameterization schemes viz., Kain-Fritch (KF) scheme, Grell-Devenyi (GD) scheme and Betts-Miller-Janjic (BMJ) Scheme are tested using high resolution advanced version (3.0) Weather Research Forecasting (WRF) model in forecasting the monsoon depression. The results of the present study shows that the genesis of the system was almost well captured in the model as indicated in 48hr forecast with all three convective parameterization schemes. It is seen that the track of monsoon depression is quite sensitive to the cumulus parameterization schemes used in the model and is found that the track forecast using three different cumulus schemes are improved when the model was started from the initial condition of a depression stage compared to that when it started from the initial condition of low pressure area. It is also seen that when the system was over land all the schemes performed reasonably well with KF and GD schemes closely followed the observed track compared to that of BMJ track. The performance of KF and GD schemes are almost similar till 72 hrs with lowest landfall error in KF scheme compared to other two schemes, whereas the BMJ scheme gives lowest mean forecast error upto 48 hr and largest mean forecast error at 72 hr. The overall rainfall forecast associated with the monsoon depression is also well captured in WRF model with KF scheme compared to that of GD scheme and BMJ scheme with observed heavy rainfall over Orissa, Chhattisgarh and western Himalayas is well captured in the model with KF scheme compared to that with GD scheme and BMJ scheme.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1666
Author(s):  
Qiang Long ◽  
Bingui Wu ◽  
Xinyue Mi ◽  
Shuang Liu ◽  
Xiaochen Fei ◽  
...  

Low visibility, associated with fog, severely affects land, marine, and air transportation. Visibility is an important indicator to identify different intensities of fog; therefore, improving the ability to forecast visibility in fog is an urgent need for social and economic development. Establishing a proper visibility parameterization scheme is crucial to improving the accuracy of fog forecast operation. Considering various visibility impact factors, including RH, Nd, D, LWC, the parameterization formula of visibility in fog, as well as their performance in meteorology operation, are reviewed. Moreover, the estimated ability of the visibility parameterization formulas combined with the numerical model is briefly described, and their advantages and shortcomings are pointed out.


Author(s):  
Roméo S. Tanessong ◽  
A. J. Komkoua Mbienda ◽  
G. M. Guenang ◽  
S. Kaissassou ◽  
Lucie A. Tchotchou Djiotang ◽  
...  

With the recurrence of extreme weather events in Central Africa, it becomes imperative to provide high-resolution forecasts for better decision-making by the Early warning systems. This study assesses the performance of the Weather Research and Forecasting (WRF) model to simulate heavy rainfall that affected the city of Douala in Cameroon during 19–21 August 2020. The WRF model is configured with two domains with horizontal resolutions of 15 and 5[Formula: see text]km, 33 vertical levels using eight cumulus parameterization schemes (CPSs). The WRF model performance is assessed by investigating the agreement between simulations and observations. Categorical and deterministic statistics are used, which include the probability of detection (POD), the success ratio (SR), the equitable threat score (ETS), the pattern correlation coefficient (PCC), the root mean square error (RMSE), the mean absolute error (MAE), and the BIAS. K-index is finally used to assess the capacity of the WRF model to predict the instability of the atmosphere in Douala during the above-mentioned period. It is found that (1) The POD, SR and ETS decrease when the threshold increases, showing the difficulty of the WRF model to predict and locate heavy rainfall events; (2) There are important differences in the rainfall area simulated by the eight CPSs; (3) The BIAS is negative for the eight CPSs, implying that all of the CPSs tested underestimate the rainfall over the study area; (4) Some of the CPSs have good agreement with observations, especially the new modifed Tiedtke and the Betts–Miller–Janjic schemes; (5) The K-index, an atmospheric instability index, is well predicted by the eight CPSs tested in this work. Overall, the WRF model exhibits a strong ability for rainfall simulation in the study area. The results point out that heavy rainfall events in tropical areas are very sensitive to CPSs and study domain. Therefore, sensitivity tests studies should be multiplied in order to identify most suitable CPSs for a given area.


2021 ◽  
Vol 11 (23) ◽  
pp. 11221
Author(s):  
Ji Won Yoon ◽  
Sujeong Lim ◽  
Seon Ki Park

This study aims to improve the performance of the Weather Research and Forecasting (WRF) model in the sea breeze circulation using the micro-Genetic Algorithm (micro-GA). We found the optimal combination of four physical parameterization schemes related to the sea breeze system, including planetary boundary layer (PBL), land surface, shortwave radiation, and longwave radiation, in the WRF model coupled with the micro-GA (WRF-μGA system). The optimization was performed with respect to surface meteorological variables (2 m temperature, 2 m relative humidity, 10 m wind speed and direction) and a vertical wind profile (wind speed and direction), simultaneously for three sea breeze cases over the northeastern coast of South Korea. The optimized set of parameterization schemes out of the WRF-μGA system includes the Mellor–Yamada–Nakanishi–Niino level-2.5 (MYNN2) for PBL, the Noah land surface model with multiple parameterization options (Noah-MP) for land surface, and the Rapid Radiative Transfer Model for GCMs (RRTMG) for both shortwave and longwave radiation. The optimized set compared with the various other sets of parameterization schemes for the sea breeze circulations showed up to 29 % for the improvement ratio in terms of the normalized RMSE considering all meteorological variables.


MAUSAM ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 579-590
Author(s):  
A. P. DIMRI ◽  
U. C. MOHANTY ◽  
M. AZADI ◽  
L. S. RATHORE

Hkkjrh; {ks= esa ’khr _rq ds nkSjku if’peh fo{kksHkksa ¼MCY;w-Mh-½ dh egRoiw.kZ fo’ks"krkvksa dks izfr:fir djus ds fy, isu LVsV ;wfuoflZVh&us’kuy lsUVj Qksj ,V~eksLQsfjd fjlpZ ¼ih-,l-;w-&,u-lh-,-vkj-½ la;qDr jkT; vejhdk ds xSj ty LFkSfrd :ikUrj ds rkSj ij eslksLdsy ekWMy ¼,e- ,e- 5½ dk mi;ksx fd;k x;k gSA   bl v/;;u esa  nks xzgh; ifjlhek Lrj i)fr;ksa uker%&CySdknj ,oa gkSax&iSu rFkk pkj laogu izkpyhdj.k i)fr;ksa uker% dqvks] xzsy] dSufÝz’k ,oa csV~l&feYyj ds 60 fd- eh- ds {kSfrt foHksnu ekWMy dk mi;ksx djds vkB lqxzkfgrk iz;ksx fd, x, gaSA blesa {kSfrt foHksnu ekWMy rFkk LFkykÑfr ds egRo ds nks dkjdksa&30 fd-eh-] 60 fd-eh- ,oa 90 fd- eh- ds {kSfrt foHksnu ekWMy ftlesa ,d fLFkfr esa LFkykÑfr ij fopkj ugha fd;k x;k gS rFkk nwljh esa lkekU; LFkykÑfr ij fopkj fd;k x;k gS] ds vk/kkj ij N% iz;ksx djds v/;;u fd;k x;k gSA bl v/;;u ds fy, nks lfØ; if’peh fo{kksHkksa dk p;u fd;k x;k gS ftlds dkj.k if’peh fgeky; {ks= esa Hkkjh o`f"V gqbZA izFke v/;;u ds fy, 18 tuojh ls 21 tuojh] 1997 rd dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gS rFkk nwljs iz;ksx ds fy, 20 tuojh ls 25 tuojh] 1999 dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gSA blesa vkjafHkd rFkk lhekar fLFkfr;ksa ds fy, us’kuy lsUVj QkWj bu~okbjWuesUV fizMhD’ku&us’kuy lsUVj QkWj ,V~eksLQsfjd fjlpZ ¼,u- lh-  b- ih-&,u- lh- , - vkj-½ la;qDr jkT; vejhdk }kjk iqufoZ’ysf"kr vkaadM+ksa dk mi;ksx fd;k x;k gSA   bl v/;;u ls ;g irk pyk gS fd gkSax&iSu vkSj csV~l feYyj dh Øe’k% xzgh; ifjlhek Lrj rFkk es?k laogu izkpyhdj.k i)fr ds la;kstu dk izn’kZu  mi;ksx dh xbZ vU; la;kstu i)fr;ksa ds rqyuk esa lcls vPNk jgk gSA vkn’kZ HkkSfrdh ¼ekWMy fQftDl½ vU; la;kstu i)fr;ksa dh rqyuk esa bl la;kstu ds }kjk leqnz ry dk nkc T;knk lgh izfr:fir djus esa l{ke jgh  gSA blds vykok LFkykÑfr jfgr {ks= esa if’peh fo{kksHk dk izfr:i.k lkekU; LFkykÑfr esa izfr:fIkr if’peh fo{kksHk dh rqyuk esa de o"kkZ dh ek=k dks n’kkZrk gSA tc blesa lkekU; LFkykÑfr dks ’kkfey fd;k x;k rks fgeky; {ks= ds vkl&ikl Hkkjh o"kkZ gqbZA o"kkZ ds {ks=ksa ds ,dhÑr ekWMy lR;kfir fo’ys"k.k ds vuq:Ik ik, x, gaSA o"kkZ {ks=ksa ds  lqxzkfgrk v/;;u ls irk pyk gS fd NksVs izHkko& {ks= ¼30 fd-eh-½ ds izfr:fir ekWMy vPNs ifj.kke nsrs gSaA       ”                                                              A non-hydrostatic version of the Penn State University - National Center for Atmospheric Research (PSU-NCAR), US, Mesoscale Model (MM5) is used to simulate the characteristic features of the Western Disturbances (WDs) occurred over the Indian region during winter. In the present study sensitivity eight experiments are carried out by using two planetary boundary layer schemes, viz., Blackadar and Hong-Pan, and four convection parameterization schemes, viz., Kuo, Grell, Kain-Fristch and Betts-Miller, with 60 km horizontal model resolution. And also the role of horizontal model resolution and topography is studied by carrying out six experiments based on two factors: horizontal model resolution of 30 km, 60 km and 90 km with assumed no topography and normal topography. For this study two active WDs are chosen which yielded extensive precipitation over western Himalayas. WD from 18 to 21 January 1997 is chosen for study one and WD from 20 to 25 January 1999 is chosen for experiment two. National Center for Environmental Prediction – National Center for Atmospheric Research (NCEP-NCAR), US, reanalyzed data is used for initial and boundary conditions.                It is found that the performance of combination of the Hong-Pan and Betts-Miller as planetary boundary layer and cloud convection parameterization schemes respectively is best compared to the other combinations of schemes used in this study. The model physics could able to simulate sea level pressure better with this combination as compared to the combinations with other schemes. Further, WD simulations with assumed no topography shows lesser amount of precipitation compared to WD simulations with normal topography. When normal topography is included, intense localized of precipitation was observed along the Himalayan range. Model integrations of precipitation fields are found close to the corresponding verification analysis. Sensitivity studies of precipitation field shows that finer domain (30 km) of the model simulation gives better results.


MAUSAM ◽  
2021 ◽  
Vol 57 (1) ◽  
pp. 97-110
Author(s):  
D. K. TRIVEDI ◽  
P. MUKHOPADHYAY ◽  
S. S. VAIDYA

& 29 vDrwcj] 1999 dks mM+hlk esa vk, egkpØokr dks izfr:fir djus ds fy, isuflyosfu;k LVsV ;wfuoflZVh ds jk"Vªh; ok;qeaMyh; vuqla/kku dsUnz ds eslksLdsy ekWMy ¼,e- ,e- 5½ ds xSj&nzoLFkSfrd :ikarj dk mi;ksx fd;k x;k gSA pØokr ds ekxZ vkSj mlds fodkl ij dSu&fÝ’k] csV~l&feyj] xzsy vkSj ,aFksl&dqvks uked pkj diklh izkpyhdj.k Ldheksa rFkk gk¡x&iSu vkSj cdZ FkkWEilu uked nks xzgh; ifjlhek Lrj izkpyhdj.k ¼ih- ch- ,y-½ Ldheks ds izHkko dk v/;;u djus ds fy, iz;ksx fd, x, gSA pØokr dh xfr] U;wure nkc dk fodkl] o"kkZ dk iSVuZ vkSj rkieku ds m/okZ/kj ØkWl lsD’ku ds laca/k esa laosnu’khyrk dh tk¡p dh xbZ gSA ,aFksl&dqvks Ldhe dks NksM+dj vU; lHkh izfr:i.k vfr {kh.k ifjlapj.k ls vfr izpaM pØokrh; rwQku fodflr djus esa l{ke gSaA U;wure dsUnzh; nkc dk cuuk fofHkUu diklh Ldheksa esa vf/kd laosnu’khyrk n’kkZrk gS ftlesa lekdyu vof/k ds 4 fnuksa ds nkSjku dSu&fÝ’k Ldhe ls 966 gS- ik- vkSj ,aFksl&dqvks Ldhe ls 1004 gS- ik- jghA izfr:fir pØokr dh xfr ij fofHkUu diklh izkpyhdj.k Ldheksa dk egRoiw.kZ izHkko jgk gSA blls izkIr gq, ifj.kkeksa ls irk pyk gS fd dSu&fÝ’k vkSj gk¡x&iSu dh feyh tqyh Ldheksa ls pØokr ds U;wure dsUnzh; nkc dk fodkl vkSj iouksa dh {kSfrt ,oa m/okZ/kj lajpukvksa] rkieku folaxfr;ksa vkSj jsucSaM y{k.kksa dks vPNh rjg iznf’kZr fd;k tk ldrk gSA Non-hydrostatic version of Pennsylvania State University- National Center for Atmospheric Research mesoscale model (MM5) is used to simulate the super cyclonic storm that crossed Orissa coast on 29 October, 1999. Experiments are carried out with four cumulus parameterization schemes namely; Kain-Fritsch, Betts-Miller, Grell and Anthes-Kuo and two planetary boundary layer parameterization (PBL) schemes namely; Hong-Pan and Burk-Thompson to study their impact on the movement and development of the cyclone. The sensitivity is examined in terms of movement, evolution of minimum pressure, rainfall pattern and vertical cross section of temperature. All the simulations are able to develop the very severe cyclonic storm from very weak circulation except with Anthes-Kuo scheme. The evolution of the minimum central pressure shows much sensitivity among the different cumulus schemes with Kain-Fritsch producing 966 hPa while Anthes-Kuo 1004 hPa during the 4 days of the integration period. Different cumulus parameterization schemes show significant impact on the simulated movement of the cyclone. The results reveal that the evolution of minimum central pressure and horizontal as well as vertical structures of winds, temperature anomalies and rainband characteristic to a cyclone are well brought out by the combination of Kain-Fritsch and Hong-Pan schemes.


2021 ◽  
Vol 13 (22) ◽  
pp. 4556
Author(s):  
Dongmei Xu ◽  
Xuewei Zhang ◽  
Hong Li ◽  
Haiying Wu ◽  
Feifei Shen ◽  
...  

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity.


2021 ◽  
Vol 893 (1) ◽  
pp. 012029
Author(s):  
Fazrul Rafsanjani Sadarang ◽  
Fitria Puspita Sari

Abstract The WRF model was used to forecast the most intensive stage of Cempaka Tropical Cyclone (TC) on 27 - 29 November 2017. This study evaluates the combination of cumulus and microphysics parameterization and the efficiency of assimilation method to predict pressure values at the center of the cyclone, maximum wind speed, and cyclone track. This study tested 18 combinations of cumulus and microphysics parameterization schemes to obtain the best combination of both parameterization schemes which later on called as control model (CTL). Afterward, assimilation schemes using 3DVAR cycles of 1, 3, 6 hours, and 4DVAR, namely RUC01, RUC03, RUC06, and 4DV, were evaluated for two domains with grid size of each 30 and 10 km. GFS data of 0.25-degree and the Yogyakarta Doppler Radar data were used as the initial data and assimilation data input, respectively. The result of the parameterization test shows that there is no combination of parameterization schemes that constantly outperform all variables. However, the combination of Kain-Fritsch and Thompson can produce the best prediction of tropical cyclone track compared to other combinations. While, the RUC03 assimilation scheme was noted as the most efficient method based on the accuracy of track prediction and duration of model time integration.


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