Raju Pathak

Raju Pathak
King Abdullah University of Science and Technology | KAUST · Division of Physical Sciences and Engineering (PSE)

PhD

About

17
Publications
3,254
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171
Citations
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

Publications

Publications (17)
Article
Full-text available
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 intermodel uncertainty underestimation. We assessed the influences of similarities in CMIP6 through CMIP3 C...
Article
Full-text available
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. In our implementations, we considered the effect of Stokes drift, Langmuir t...
Article
Full-text available
Four generations of the NCAR Community Atmosphere Model (CAM3, 4, 5, and 6) are used to assess model upgrades to the Indian summer monsoon rainfall (ISMR) simulations. The total precipitation simulation in CAM3 is significantly overestimated over the western equatorial Indian Ocean, Arabian Sea, and southwest Bay of Bengal (BoB), and underestimated...
Preprint
Full-text available
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...
Preprint
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Conference Paper
Full-text available
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...
Article
Full-text available
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...
Preprint
Full-text available
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...
Preprint
Full-text available
Four generations of the NCAR Community Atmosphere Model (CAM-3, 4, 5, and 6) are evaluated for the Indian summer monsoon (ISM) simulations. Total precipitation simulated by successive versions of CAM is overestimated over the western equatorial Indian Ocean (EIO), Arabian Sea, and Western Ghats (WGs), and underestimated over the eastern EIO, Bay of...
Thesis
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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...
Article
Full-text available
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,...
Poster
Full-text available
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...
Article
Full-text available
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...

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