About
13
Publications
2,494
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
99
Citations
Citations since 2017
Introduction
The main focus of my research is to improve cloud and convection representation in climate and weather models, and hence reducing biases and uncertainties in tropical precipitation with a focus on Asian summer monsoon (ASM). I use process-based stochastic and deterministic approaches to better represent the interaction between large-scale and small-scale organized convections and improve the simulation of ASM, MJO, and planetary-scale equatorial waves, leading to improved prediction/projection
Skills and Expertise
Publications
Publications (13)
Climate change projections (CCPs) are based on the multimodel means of individual climate model simulations that are assumed to be independent. However, model similarity leads to projections biased toward the largest set of similar models and the underestimation of uncertainties. We assessed the influence of similarities in CMIP6 through CMIP3 CCPs...
In this work, we integrated the WaveWatch III model into the regional coupled model SKRIPS (Scripps–KAUST Regional Integrated Prediction System). The WaveWatch III model is implemented with flexibility, meaning the coupled system can run with or without the wave component. To demonstrate the impact of coupling we performed a case study using a seri...
The synoptic precipitation variability over Central Africa (CA) in the March-to-May (MAM) and September-to-November (SON) seasons is investigated in this study. The composite analysis is used to highlight the evolution of synoptic precipitation, related convection, and dynamic fields. Composite analysis findings show that synoptic precipitation ano...
Model simulations are highly sensitive to the formulation of the atmospheric mixing process or entrainment in the deep convective parameterizations used in their atmospheric component. In this paper, we have implemented stochastic entrainment in the deep convection scheme of NCAR CAM5 and analyzed the improvements in model simulation, focusing on t...
An inverse algorithm was developed to profile the vertical structure of temperature and humidity using a feed-forward neural network. Numerous simulations using the inverse algorithm (inverse model) have been conducted and compared with various existing independent techniques. The inverse model is highly efficient at profiling the temperature and h...
Uncertainty quantification (UQ) in weather and climate models is required to assess the sensitivity of their outputs to various parameterization schemes and thereby improve their consistency with observations. Herein, we present an efficient UQ and Bayesian inference for the cloud parameters of the NCAR Single Column Atmosphere Model (SCAM6) using...
Model simulations are highly sensitive to the formulation of the atmospheric mixing process or entrainment in the deep convective parameterizations used in their atmospheric component. In this paper, we have implemented stochastic entrainment in the deep convection scheme of NCAR CAM5 and analyzed the improvements in model simulation, focusing on t...
Although significant efforts have been made in recent decades for improvements in global climate models (GCMs), many important biases still remain, the South Asian Summer Monsoon (SASM) being one of the important areas with a large scope for improvement. In this thesis we have used one of the better performing community models, namely, the NCAR Com...
Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulati...
Using data from 33 models from the CMIP5 historical and AMIP5 simulations, we have carried out a systematic analysis of biases in total precipitation and its convective and large-scale components over the south Asian region. We have used 23 years (1983–2005) of data, and have computed model biases with respect to the PERSIANN-CDR precipitation (wit...
The effects of global warming and geoengineering on annual precipitation and its seasonality over different parts of the world are examined using the piControl, 4xCO2 and G1 simulations from eight global climate models participating in the Geoengineering Model Intercomparison Project. Specifically, we have used relative entropy, seasonality index,...
We have carried out a systematic analysis of the structure of precipitation biases over South Asia in 33 CMIP5 and AMIP5 models to assess the common and unique biases with special emphasis on the NCAR CESM. The models have been clustered into various groups based on the correlation of their biases in total, convective and large-scale precipitation...
We analyzed 113 years (1901-2013) of daily rainfall over India to investigate spatiotemporal variability of rainfall seasonality. Rainfall seasonality and mean annual rainfall were found to be high over the Western Ghats, central, and northeastern parts of India and over the Indo-Gangetic plains, and low over northwest, southern, and northernmost p...
