Simulation of monsoon depression over India using high resolution WRF Model – Sensitivity to convective parameterization schemes

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.

Sensitivity of Rainfall to Cumulus Parameterization Schemes from a WRF Model over the City of Douala in Cameroon

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.

Evaluation of different convective schemes on simulation of thunderstorm event over Delhi by ARPS Model

Three difference cumulus parameterization schemes namely, Kain-Fritsch, New Kain-Fritsch and the Betts-Miller-Janjic are used to simulated convective rainfall associated with two thunderstorm events over Delhi by Advanced Regional Prediction Model (ARPS). An inter comparison of model simulated precipitation in respect of each convection scheme is made with reference to observed precipitation. The study shows that for the Delhi thunderstorm events, the Kain-Fritsch scheme provides more realistic results. This scheme is able to capture the temporal distribution of rainfall and the timely development of thunderstorm in both the cases. While the other two schemes fail to capture these features. However, the Kain-Fritsch scheme is found to overestimate the rainfall amount.

Impact of physical parameterization schemes on the numerical simulation of Orissa Super Cyclone (1999)

& 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.

Climatological sensitivities of shallow-cumulus bulk entrainment in continental and oceanic locations

Cumulus entrainment is a complex process that has long challenged conceptual understanding and atmospheric prediction. To investigate this process observationally, two retrievals are used to generate multi-year climatologies of shallow-cumulus bulk entrainment (ϵ) at two Atmospheric Radiation Measurement cloud observatories, one in the US southern Great Plains (SGP) and the other in the Azores archipelago in the eastern North Atlantic (ENA). The statistical distributions of ϵ thus obtained, as well as certain environmental and cloud-related sensitivities of ϵ, are consistent with previous findings from large-eddy simulations. The retrieved ϵ robustly increases with cloudlayer relative humidity and decreases in wider clouds and cloud ensembles with larger cloud-base mass fluxes. While ϵ also correlates negatively with measures of cloud-layer vigor (e.g., maximum in-cloud vertical velocity and cloud depth), the extent to which these metrics actually regulate ϵ (or vice-versa) is unclear. Novel sensitivities of ϵ include a robust decrease of ϵ with increasing subcloud wind speed in oceanic flows, as well as a decrease of ϵ with increasing cloud-base mass flux in individual cumuli. A strong land–ocean contrast in ϵ is also found, with median values of 0.5-0.6 km−1 at the continental SGP site and and 1.0-1.1 km−1 at the oceanic ENA site. This trend is associated with drier and deeper cloud layers, along with larger cloud-base mass fluxes, at SGP, all of which favor reduced ϵ. The flow-dependence of retrieved ϵ implies that its various sensitivities should be accounted for in cumulus parameterization schemes.