Sensitivity of convective rainfall to the adjustment parameters in the Betts-Miller scheme

ABSTACT. Three numerical experiments are carried out to study the sensitivity of the convective rain fall to the adjustment parameters used in the Betts-Miller scheme of cumulus convection. The results of the numerical experiments indicate that the convective rainfall has considerable sensitivity to saturation pressure departure value (S) whereas the impact of stability weight (W) on the convective rainfall is marginal. The limiting S values are found to produce drying of the column.

Optimization of physical schemes in WRF model on cyclone simulations over Bay of Bengal using one-way ANOVA and Tukey’s test

Evaluation of appropriate physics parameterization schemes for the Weather Research and Forecasting (WRF) model is vital for accurately forecasting tropical cyclones. Three cyclones Nargis, Titli and Fani have been chosen to investigate the combination of five cloud microphysics (MP), three cumulus convection (CC), and two planetary boundary layer (PBL) schemes of the WRF model (ver. 4.0) with ARW core with respect to track and intensity to determine an optimal combination of these physical schemes. The initial and boundary conditions for sensitivity experiments are drawn from the National Centers for Environmental Prediction (NCEP) global forecasting system (GFS) data. Simulated track and intensity of three cyclonic cases are compared with the India Meteorological Department (IMD) observations. One-way analysis of variance (ANOVA) is applied to check the significance of the data obtained from the model. Further, Tukey’s test is applied for post-hoc analysis in order to identify the cluster of treatments close to IMD observations for all three cyclones. Results are obtained through the statistical analysis; average root means square error (RMSE) of intensity throughout the cyclone period and time error at landfall with the step-by-step elimination method. Through the elimination method, the optimal scheme combination is obtained. The YSU planetary boundary layer with Kain–Fritsch cumulus convection and Ferrier microphysics scheme combination is identified as an optimal combination in this study for the forecasting of tropical cyclones over the Bay of Bengal.

Numerical experiments for improvement in mesoscale simulation of Orissa super cyclone

& 29 vDrwcj] 1999 dks mM+hlk ds rV ij vk;k egkpØokr mM+hlk ds vc rd ds bfrgkl dk lcls izpaM rwQku Fkk ftldh 250 fd-eh- izfr ?kaVk dh rhoz xfr okyh iouksa us jkT; ds 12 rVh; ftyksa dks rgl&ugl dj MkykA rwQku ds LFky ls Vdjkus ds i'pkr~ 36 ?kaVs ls Hkh vf/kd le; rd iouksa dh izpaMrk cuh jghA bl rwQku ls tku eky dk dkQh uqdlku gqvkA yxHkx 10]000 yksxksa dh tkusa xbZA bl v/;;u esa rwQku ds eslksLdsy izfr:Ik dks csgrj cukus ds fy, dqN egRoiw.kZ igyqvksa dh tk¡p gsrq O;kid la[;kRed iz;ksx fd, x, gSaA bu igyqvksa esa xSj nzoLFkSfrd xfrd] fun’kZ {kSfrt foHksnu vkSj egRoiw.kZ izR;{k izfØ;kvksa ds izkpyhdj.k 'kkfey gSaA rwQku dk 5 fnolh; izfr:Ik ¼123 ?kaVksa ds yxkrkj lekdyu½ rS;kj djus ds fy, eslksLdsy fun’kZ ,e- ,e- 5 dk mi;ksx fd;k x;k gSA blesa le:ih foHksnu ¼30 fd-eh-½ vkSj le:ih le; J`a[kyk ds lkFk nzoLFkSfrd ¼,p-,l-½ rFkk xSj nzoLFkSfrd ¼,u- ,l-½ xfrdksa ds lg;ksx ls rwQku ds izfr:i esa xSj nzoLFkSfrdrk ds izHkko dh tk¡p dh xbZ gSA bl fof/k ls rwQku vkSj fo’ks"k :Ik ls bldh rhozrk dk xSj nzoLFkSfrd xfrdksa ds lkFk lgh izfr:i.k gksrk gSA xSj nzoLFkSfrd xfrdksa ds lkFk 90 fd-eh-] 60 fd-eh- vkSj 30 fd-eh- ds foHksnuksa ij rwQku dk izfr:i.k djrs gq, fun’kZ dh laof/kZr {kSfrt foHksnu dh egRrk dh tk¡p dh xbZ gS vkSj rwQku ds izfr:i.k esa bldk izR;{k izHkko ns[kk x;k gSA egRoiw.kZ izR;{k izfØ;k okys diklh laogu xzgh; ifjlhek Lrj ¼ih- ch- ,y-½ vkSj fofdj.k gsrq fun’kZ esa miyC/k izkpyhÑr ;kstukvksa ds csgrj lEHkkO; leUo; dk irk yxkus ds fy, la[;kRed iz;ksx Hkh fd, x,A lh- lh- ,e- 2 fofdj.k izkpyhÑr ;kstuk lesr xzsy diklh laogu vkSj gk¡x&isu ih- ch- ,y- ;kstuk ds lkFk leUo;u okyh ;kstuk ds vU; ijhf{kr ;kstukvksa dh rqyuk esa lcls csgrj ifj.kkeksa dk irk pyk gSA The super cyclone that crossed Orissa coast on 29 October 1999 was the most intense storm in the history of Orissa with 12 coastal districts of the state were battered by winds reaching 250 kmph. The fury of winds continued for more than 36 hours after landfall of the storm. The storm caused huge damage to properties and nearly 10,000 people lost their lives. In the present study, extensive numerical experiments are conducted to investigate some important aspects that may lead to the improvement in mesoscale simulation of the storm. The aspects that are addressed here include non-hydrostatic dynamics, model horizontal resolution and parameterization of important physical processes. The mesoscale model MM5 is used to produce 5-day simulation of the storm. The influence of non-hydrostaticity is investigated by simulating the storm with hydrostatic (HS) and non-hydrostatic (NS) dynamics at same resolution (30 km) and with same time step. The storm, in particular its intensity is better simulated with non-hydrostatic dynamics. The importance of increasing model horizontal resolution is investigated by simulating the storm at 90 km, 60 km and 30 km resolutions with non-hydrostatic dynamics and found to have perceptible impact in simulation of the storm. Numerical experiments also are conducted to find the best possible combination of the parameterization schemes available in the model for the important physical processes cumulus convection, planetary boundary layer (PBL) and radiation. The combination of Grell cumulus convection and Hong-Pan PBL scheme along with CCM2 radiation parameterization scheme is found to provide the best result compared to the other schemes tested.

Updraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol-deep convection interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether or under what conditions a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using two different reference frames: static cloudy-updraft grid cells versus tracked cumulus thermals. In both frameworks we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that analysis of thermals can provide a better pathway to sample the most relevant convective processes. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy-updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy-updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations. These results suggest that cumulus thermals are more realistic dynamical building blocks of cumulus convection, acting as natural cloud chambers for microphysical processes.

Evaluating the Performance of Cumulus Convection Parameterization Schemes in Regional Climate Modeling System

In this study, we explored the performance of the cumulus convection parameterization schemes of Regional Climate Modeling System (RegCM) towards the Indian summer monsoon (ISM) of a catastrophic year through various numerical experiments conducted with different convection schemes (Kuo, Grell amd MIT) in RegCM. The model is integrated at 60KM horizontal resolution over Indian region and forced with NCEP/NCAR reanalysis. The simulated temperature at 2m and the wind at 10m are validated against the forced data and the total precipitation is compared with the Global Precipitation Climatology Centre (GPCC) observations. We find that the simulation with MIT convection scheme is close to the GPCC data and NCEP/NCAR reanalysis. Our results with three convection schemes suggest that the RegCM with MIT convection scheme successfully simulated some characteristics of ISM of a catastrophic year and may be further examined with more number of convection schemes to customize which convection scheme is much better.

Modelling a tropical-like cyclone in the Mediterranean Sea under present and warmer climate

This study focuses on a single Mediterranean hurricane (hereafter medicane), to investigate its response to global warming during the middle of the 21st century and assesses the effects of a warmer ocean and a warmer atmosphere on its development. Our investigation uses the state-of-the-art regional climate model WRF to produce the six-member, multi-physics ensembles. Results show that our model setup simulates a realistic cyclone track and the transition from an initial disturbance to a tropical-like cyclone with a deep warm core. However, the simulated transition occurs earlier than for the observed medicane. The response of the medicane to future climate change is investigated with a pseudo global warming (PGW) approach. This is the first application of the PGW framework to medicanes. The PGW approach adds a climate change delta (defined as difference between future and present climate) to WRF's boundary conditions which is obtained for all prognostic variables using the mean change in an ensemble of CMIP5 simulations. A PGW simulation where the climate change delta is added to all prognostic variables (PGWALL) shows that most of the medicane characteristics moderately intensify, e.g. surface wind speed, uptake of water vapour, and precipitation. However, the minimum sea level pressure (SLP) is almost identical to that under present climate conditions. Two additional PGW simulations were undertaken; One simulation adds the projected change in sea surface and skin temperature only (PGWSST) while the second simulation adds the PGW changes to only atmospheric variables (PGWATMS); i.e. we use present-day sea surface temperatures. These simulations show opposing responses of the medicane. In PGWSST, the medicane is more intense than PGWALL as indicated by lower SLP values, the stronger surface wind, and the more intense evaporation and precipitation. In contrast, the medicane in PGWATMS still transitions into a tropical-like cyclone with a deep warm core, but the PGWATMS medicane weakens considerably (SLP, surface wind, and rainfall decrease). This difference can be explained by an increase in water vapour driven by the warmer ocean surface (favourable for cumulus convection). The warmer and drier atmosphere in PGWATMS tends to inhibit condensation (unfavourable for cumulus convection). The warmer ocean and warmer atmosphere have counteracting effects which leads to only a modest enhancement of the medicane by global warming. The novel approach in this study provides new insights into the different roles of warming of the ocean and atmosphere in medicane development.

Applying deep learning to NASA MODIS data to create a community record of marine low-cloud mesoscale morphology

Marine low clouds display rich mesoscale morphological types and distinct spatial patterns of cloud fields. Being able to differentiate low-cloud morphology offers a tool for the research community to go one step beyond bulk cloud statistics such as cloud fraction and advance the understanding of low clouds. Here we report the progress of our project that aims to create an observational record of low-cloud mesoscale morphology at a near-global (60∘ S–60∘ N) scale. First, a training set is created by our team members manually labeling thousands of mesoscale (128×128) MODIS scenes into six different categories: stratus, closed cellular convection, disorganized convection, open cellular convection, clustered cumulus convection, and suppressed cumulus convection. Then we train a deep convolutional neural network model using this training set to classify individual MODIS scenes at 128×128 resolution and test it on a test set. The trained model achieves a cross-type average precision of about 93 %. We apply the trained model to 16 years of data over the southeastern Pacific. The resulting climatological distribution of low-cloud morphology types shows both expected and unexpected features and suggests promising potential for low-cloud studies as a data product.