Understanding Atmospheric Convection Using Large Eddy Simulation

Cloud formation is based on the fundamental principle of atmospheric convection, which involves the vertical transport of heat and moisture into an unstable environment. Convective transfer of moisture and heat in the form of turbulent fluxes over the Bay of Bengal (BoB) has not been explored much and is not resolved in global and regional climate models (GCMs and RCMs) due to the coarser grid resolutions used. Therefore, the present study is an attempt to understand the convection phenomenon over the BoB using a high-resolution cloud-resolving large eddy simulation. Due to the lack of observational data over the BoB, initial and boundary conditions were generated using reanalysis data. We found that the LES successfully captured the cloud formation and convection phenomenon. The turbulence in the convection was analyzed by using Reynolds averaging to obtain variances and covariances. The presence of turbulence over the region was observed. The cloud characteristics were verified by conditionally averaging the output fields. The present study paves a pathway to perform various simulations at different atmospheric conditions over the region in order to create a library of high-resolution simulations

Understanding Atmospheric Convection Using Large Eddy Simulation

Cloud formation is based on the fundamental principle of atmospheric convection, which involves the vertical transport of heat and moisture into an unstable environment. Convective transfer of moisture and heat in the form of turbulent fluxes over the Bay of Bengal (BoB) has not been explored much and is not resolved in global and regional climate models (GCMs and RCMs) due to the coarser grid resolutions used. Therefore, the present study is an attempt to understand the convection phenomenon over the BoB using a high-resolution cloud-resolving large eddy simulation. Due to the lack of observational data over the BoB, initial and boundary conditions were generated using reanalysis data. We found that the LES successfully captured the cloud formation and convection phenomenon. The turbulence in the convection was analyzed by using Reynolds averaging to obtain variances and covariances. The presence of turbulence over the region was observed. The cloud characteristics were verified by conditionally averaging the output fields. The present study paves a pathway to perform various simulations at different atmospheric conditions over the region in order to create a library of high-resolution simulations

Long-term cloud fraction biases in CMIP5 GCMs over India during monsoon season

Using 24years of cloud fraction (CF) data from the International Satellite Cloud Climatology Project (ISCCP) observations and their corresponding simulators in general circulation models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5), we have analyzed cloud biases and their role on radiation over the Indian region (65-100 degrees E and 5-40 degrees N) for the monsoon season of June to September. The present study reports the spatial patterns of CFs and their biases in GCMs compared to observations. It is found that the simulated CFs are highly underestimated up to 40%. Mean of total CF from ISCCP observations is 75% with at least 10% difference with simulated CFs. For high-topped clouds, this difference is about 3-4%. Except for high-topped clouds, other cloud types are not simulated realistically by CMIP5 models used in this study. Further, we investigated the individual cloud types classified based on cloud optical depth and cloud top pressure. We found that, in general, individual cloud types are poorly simulated by models, although some (Max Planck Institute Earth System Model, Low Resolution and Hadley Centre Global Environmental Model, version 2, Earth System) models convincingly simulate high-topped thin clouds. To assess the impact of cloud biases on the simulated radiative forcings, we studied shortwave and longwave cloud radiative forcings from CERES (Clouds and the Earth's Radiant Energy System) observations and CMIP5 GCMs. It is noticed that the spatial patterns of biases in radiative forcings are similar to the patterns of biases in CFs for high-topped clouds, specifically over the oceanic regions. We find that the biases in cloud radiative forcings could potentially be caused due to the inefficacy of CMIP5 models in simulating high-topped anvil clouds (high-topped cirrus/stratocirrus clouds). The present study confirms that the uncertainty in simulating cloud fractions over the Indian region is still a prominent issue to be addressed in general circulation models

Projected precipitation changes over the south Asian region for every 0.5 °C increase in global warming

Using all ensemble members of NCAR CCSM4 for historical natural, RCP4.5 and RCP8.5 scenarios from CMIP5, we analyse changes in mean and extreme precipitation over the south Asian region for every 0.5 ^o C increase in global warming. An increase in mean annual precipitation is projected over majority of the south Asian region with increased levels of warming. Over Indian land, the spatially-averaged annual mean precipitation shows an increase in the range of ~2-14 % based on the RCP scenario and level of warming. However, a decrease in mean annual precipitation is projected over northwest parts of the Indian sub-continent and the equatorial Indian Ocean with increased levels of warming. In general, we find multifold increase in the frequency of occurrence of daily precipitation extremes over the Indian subcontinent and surrounding oceans. Over Indian land, frequency of occurrence of daily precipitation extremes show up to three-fold increase under both RCP scenarios for global warming levels in the range of 1.5 ^o C–2.5 ^o C. With further increase in warming we find that the frequency of occurrence of daily precipitation extremes could show a massive four- to six-fold increase over majority of Indian land. Notably, unlike the projected increase in the frequency of occurrence of daily precipitation extremes, the projected change in annual mean precipitation is found to be insignificant in a 1.5 ^o C warmer world, over majority of the south Asian region, under both RCP scenarios. Given the projected large increase in frequency of daily precipitation extremes with increased levels of warming, our study provides scientific support to the recommendations of the Paris Agreement of 2015

The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects

The performance of the Advanced Regional Prediction System (ARPS) in simulating an extreme rainfall event is evaluated, and subsequently the physical mechanisms leading to its initiation and sustenance are explored. As a case study, the heavy precipitation event that led to 65 cm of rainfall accumulation in a span of around 6 h (1430 LT–2030 LT) over Santacruz (Mumbai, India), on 26 July, 2005, is selected. Three sets of numerical experiments have been conducted. The first set of experiments (EXP1) consisted of a four-member ensemble, and was carried out in an idealized mode with a model grid spacing of 1 km. In spite of the idealized framework, signatures of heavy rainfall were seen in two of the ensemble members. The second set (EXP2) consisted of a five-member ensemble, with a four-level one-way nested integration and grid spacing of 54, 18, 6 and 1 km. The model was able to simulate a realistic spatial structure with the 54, 18, and 6 km grids; however, with the 1 km grid, the simulations were dominated by the prescribed boundary conditions. The third and final set of experiments (EXP3) consisted of a five-member ensemble, with a four-level one-way nesting and grid spacing of 54, 18, 6, and 2 km. The Scaled Lagged Average Forecasting (SLAF) methodology was employed to construct the ensemble members. The model simulations in this case were closer to observations, as compared to EXP2. Specifically, among all experiments, the timing of maximum rainfall, the abrupt increase in rainfall intensities, which was a major feature of this event, and the rainfall intensities simulated in EXP3 (at 6 km resolution) were closest to observations. Analysis of the physical mechanisms causing the initiation and sustenance of the event reveals some interesting aspects. Deep convection was found to be initiated by mid-tropospheric convergence that extended to lower levels during the later stage. In addition, there was a high negative vertical gradient of equivalent potential temperature suggesting strong atmospheric instability prior to and during the occurrence of the event. Finally, the presence of a conducive vertical wind shear in the lower and mid-troposphere is thought to be one of the major factors influencing the longevity of the event