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A detailed review was done on the past studies conducted by the researchers on climate change and variability, particularly for the Indian conditions having a typical monsoon climate. The short-term droughts (flash droughts) occurring due to the prolonged dry spells, heat waves, soil moisture deficits, which are caused due to the climate variability were also investigated. Accurate prediction techniques used for flash drought (FD), assessment of its impact on agriculture and farmers’ income as well as appropriate coping strategies recommended by different researchers to minimize the losses in crop yield and farmers’ income were analyzed. The total loss in crop yield was found to increase with increase in land size; however, per acre loss was higher for smaller holdings. It was observed that the resource crunch small and marginal farmers particularly belonging to SC/ST were worst sufferers due to their inability to adopt appropriate coping strategies such as: crop insurance, short duration climate resilient cultivars, low-interest loans from financial institutions etc. It was inferred that the FD needs special attention particularly for the state of Odisha, where a majority of the population are engaged in agriculture and its allied activities. Agriculture accounts for around 30 per cent of the net state domestic product (NSDP). Investigations of the past studies revealed that the western Odisha regions are most vulnerable to climate change and variability and to the FD caused by the climate variability. The small and marginal tribal farmers of western Odisha whose sole source of income is from agriculture, with low affordability, are worst affected. To cope with these natural calamities, they need to adopt coping strategies namely, going for a variety of sources of income, cultivation of short-duration climate resilient varieties, in-situ rainwater conservation and use for life-saving irrigation, crop insurance, and low interest loans as well as low-cost post-harvest techniques for the perishable crop produce etc.

Highlights • Realistic representation of Land Use and Land Cover (LULC) changes improves the prediction of convection over urban regimes. • The 2019 urban amalgamation in LULC spread in the weather model discloses that the rainfall intensity has increased compared to the 1980 LULC simulation • The maximum rainfall limited to a shorter spell (~1 hour), due to the urban heating effect.

Abstract Amplified rates of urban convective systems pose a severe peril to the life and property of the inhabitants over urban regions, requiring a reliable urban weather forecasting system. However, the city scale's accurate rainfall forecast has constantly been a challenge, as they are significantly affected by land use/ land cover changes (LULCC). Therefore, an attempt has been made to improve the forecast of the severe convective event by employing the comprehensive urban LULC map using Local Climate Zone (LCZ) classification from the World Urban Database and Access Portal Tools (WUDAPT) over the tropical city of Bhubaneswar in the eastern coast of India. These LCZs denote specific land cover classes based on urban morphology characteristics. It can be used in the Advanced Research version of the Weather Research and Forecasting (ARW) model, which also encapsulates the Building Effect Parameterization (BEP) scheme. The BEP scheme considers the buildings' 3D structure and allows complex land–atmosphere interaction for an urban area. The temple city Bhubaneswar, the capital of eastern state Odisha, possesses significant rapid urbanization during the recent decade. The LCZs are generated at 500 m grids using supervised classification and are ingested into the ARW model. Two different LULC dataset, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and WUDAPT derived LCZs and initial, and boundary conditions from NCEP GFS 6-h interval are used for two pre-monsoon severe convective events of the year 2016. The results from WUDAPT based LCZ have shown an improvement in spatial variability and reduction in overall BIAS over MODIS LULC experiments. The WUDAPT based LCZ map enhances high-resolution forecast from ARW by incorporating the details of building height, terrain roughness, and urban fraction.

Abstract Climate change and sustainability are among the most widely used terms among policymakers and the scientific community in recent times. However, climate action or steps to sustainable growth in cities in the global south are mostly borrowed from general studies at a few large urban agglomerations in the developed world. There are very few modeling studies over south Asia to understand and quantify the impact of climate change and urbanization on even the most primary meteorological variable, such as temperature. Such quantifications are difficult to estimate due to the non-availability of relevant long-term observational datasets. In this modeling study, an attempt is made to understand the urban heat island (UHI), its transition, and the segregation of regional climate change effects and urbanization over the rapidly growing tier 2 tropical smart city Bhubaneswar in India. The model is able to simulate the UHI for both land surface temperature, called the SUHI, and 2-m air temperature, called UHI, reasonably well. Their magnitudes were ~ 5 and 2.5°C, respectively. It is estimated that nearly 60–70% of the overall air and 70–80% of the land surface temperature increase during nighttime over the city between the period 2004 and 2015 is due to urbanization, with the remaining due to the regional/non-local effects.

There was an error in footnote no. 1 in the initial online publication. The original article has been corrected.

The cloud processes play an important role in all forms of precipitation. Its proper representation is one of the challenging tasks in mesoscale numerical simulation. Studies have revealed that mesoscale feature require proper initialization which may likely to improve the convective system rainfall forecasts. Understanding the precipitation process, model initial condition accuracy and resolved/sub grid-scale precipitation processes representation, are the important areas which needed to improve in order to represent the mesoscale features properly. Various attempts have been done in order to improve the model performance through grid resolution, physical parameterizations, etc. But it is the physical parameterizations which provide a convective atmosphere for the development and intensification of convective events. Further, physical parameterizations consist of cumulus convection, surface fluxes of heat, moisture, momentum, and vertical mixing in the planetary boundary layer (PBL). How PBL and Cumulus schemes capture the evolution of thunderstorm have been analysed by taking thunderstorm cases occurred over Kolkata, India in the year 2011. PBL and cumulus schemes were customized for WSM-6 microphysics because WSM series has been widely used in operational forecast. Results have shown that KF (PBL scheme) and WSM-6 (Cumulus Scheme) have reproduced the evolution of surface variable such as CAPE, temperature and rainfall very much like observation. Further, KF and WSM-6 scheme also provided the increased moisture availability in the lower atmosphere which was taken to higher level by strong vertical velocities providing a platform to initiate a thunderstorm much better. Overestimation of rain in WSM-6 occurs primarily because of occurrence of melting and freezing process within a deeper layer in WSM-6 scheme. These Schemes have reproduced the spatial pattern and peak rainfall coverage closer to TRMM observation. It is the the combination of WSM-6, and KF schemes which have preformed reasonably well to reproduce the right atmospheric condition for a thunderstorm leading to improved spatial and temporal rainfall over the study domain. Thus the parameterization schemes of WMS-6 and KF have shown significant improvement by capturing the location, intensity and surface meteorological parameters closer to observed details.

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

The thunderstorms are typical mesoscale systems dominated by intense convection. Mesoscale models are essential for the accurate prediction of such high-impact weather events. In the present study, an attempt has been made to compare the simulated results of three thunderstorm events using NMM and ARW model core of WRF system and validated the model results with observations. Both models performed well in capturing stability indices which are indicators of severe convective activity. Comparison of model-simulated radar reflectivity imageries with observations revealed that NMM model has simulated well the propagation of the squall line, while the squall line movement was slow in ARW. From the model-simulated spatial plots of cloud top temperature, we can see that NMM model has better captured the genesis, intensification, and propagation of thunder squall than ARW model. The statistical analysis of rainfall indicates the better performance of NMM than ARW. Comparison of model-simulated thunderstorm affected parameters with that of the observed showed that NMM has performed better than ARW in capturing the sharp rise in humidity and drop in temperature. This suggests that NMM model has the potential to provide unique and valuable information for severe thunderstorm forecasters over east Indian region.

North India is comprised, in parts, of complex Himalayan mountain ranges having different altitudes and orientations all along this region. Due to the highly variable altitude and orientation of orographic barriers the prevailing weather conditions over the region are complex. The winter season over this region is frequented by eastwardmoving low pressure synoptic weather systems called Western Disturbances WDs. Advance information of these WDs are important for organizations where men and machines are employed to operate in the open, for example, for defence purpose, agriculture, tourism and transport. Future projection of meteorological variables is important during the winter in assessment of cold wave conditions, avalanche release and a critical human comfort index. Therefore, a nonhydrostatic version of the Penn State UniversityNational Center for Atmospheric Research, US, PSUNCAR mesoscale model is used to simulate the characteristic features of the Western Disturbances WDs occurring over the Indian region during a winter season. For this study, four cases of active WDs are selected. The model is integrated with 60 km horizontal resolution to simulate the WD features. The model simulations with 60 km horizontal resolution are compared with the National Center for Environmental PredictionNational Center for Atmospheric Research, US, NCEPNCAR reanalyses. It is seen that in all the cases the rate of movement of the system is, in general, a little slower in the simulations. Examining the differences between the predicted and analysed zonal component of the wind reveal that the model simulated zonal winds are generally weakerunderestimated in the location of the upper trough at 500 hPa or aloft and even in the position of the WDs at lower levels. These results suggest that the model has a systematic easterly bias, though the magnitude is small. In other words the advection simulated in the model is not strong enough to advect the system with the observed speed. Copyright © 2009 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The precipitation over Orissa State, a meteorological subdivision on the east coast of India, shows large‐scale spatio‐temporal variation caused by the interaction of the basic monsoon flow with the monsoon disturbances over the Bay of Bengal and the orography owing to the Eastern Ghats and other hill peaks in Orissa and its neighbourhood. Hence, it is difficult to predict daily precipitation over Orissa. The objective of this study is to predict the occurrence and quantity of precipitation 24 h ahead, over specific locations of Orissa during the summer monsoon season (June‐September). For this purpose, a probability of precipitation (PoP) model has been developed by applying stepwise regression with the available surface and upper air parameters from synoptic and radiosonde and radio wind stations in and around Orissa as potential predictors. The parameters selected through stepwise regression for the PoP model have been used to develop a probabilistic model for a Quantitative Precipitation Forecast (QPF) in different ranges, such as 0.1–10, 11–25, 26–50, 51–100 and > 100 mm, using Multiple Discriminant Analysis (MDA). Both the PoP and QPF models have been developed based on data from 1980 to 1994 and verified with the data from 1995 to 1998.Considering six representative stations for six homogeneous regions in Orissa, the PoP model performs very well with percentages of correct forecast for occurrence/non‐occurrence of precipitation being about 73 and 65% respectively for developmental and independent data. However, the skill score of the MDA model for categorical forecast is poor, especially for higher values of precipitation. Copyright © 2007 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

North India is composed, in parts, of the Himalayan mountain ranges having different altitudes and orientations. Wintertime eastward‐moving low‐pressure synoptic weather systems (western disturbances) are modified by these orographic barriers. Therefore, advance and proper information of maximum and minimum temperature becomes important for assessing natural hazard threats. The objective of the present study is to use the Perfect Prognostic Method (PPM) to develop statistical‐dynamical models for location‐specific forecast of maximum and minimum temperatures during the winter season of December to March (DJFM). Reanalysis data from the United States National Center for Environmental Prediction‐National Center for Atmospheric Research (NCEP–NCAR), upper and surface observations at three stations of the India Meteorological Department, and surface observations at three selected study sites, were used. The models were developed with data of DJFM for 12 years (1984–1996) and tested with data of DJFM for 1 year (1996–1997). For evaluation of the performance of the models with independent data sets, four comparisons were carried out using different sets of predictors: (1) NCEP–NCAR reanalysis data, (2) operational analysis of the National Center for Medium Range Weather Forecasting (NCMRWF), India, (3) day 1 forecast fields with the T80 spectral model, which is the operational general circulation model at the NCMRWF, and (4) a mesoscale model MM5 day 1 forecast. Evaluation of the performance of these statistical‐dynamical models, developed on the basis of PPM, with independent data sets for maximum and minimum temperature, demonstrates the advantages of using MM5 day 1 forecast fields as predictors. Copyright © 2007 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Dynamic and thermodynamic characteristics of the Asian summer monsoon during the onset phase over the Indian Peninsula (Kerala coast) and its variability are examined with reanalysis data sets. For this study, daily averaged (0000 and 1200 UTC) reanalysis data sets of National Centre for Environmental Prediction–National Centre for Atmospheric Research for the period 1948–99 are used.Based on 52 years of onset dates of the Indian summer monsoon, we categorized pre‐onset, onset and post‐onset periods (each averaged 5 days) to investigate the mean circulation characteristics and the large‐scale energetics of the Asian summer monsoon. It is found that the strength of the low‐level Somali jet and upper tropospheric tropical easterly jet increase rapidly during the time of evolution of the summer monsoon over India. Over the Bay of Bengal and the Arabian Sea, predominant changes are noticed in the large‐scale balances of kinetic energy, heat and moisture from the pre‐onset to the post‐onset periods. Prior to the onset of the summer monsoon over India, a zone of flux convergence of heat and moisture is noticed over the eastern sector of the Bay of Bengal and this intensifies in the onset and post‐onset periods. During onset of the monsoon over India, the horizontal flux convergence of heat and moisture, as well as diabatic heating, are enhanced over the Arabian Sea. These subsequently increase with the evolution and advancement of the monsoon over India.Further, the dynamics of the evolution processes (15 days before and 30 days after the onset date of the monsoon over Kerala for each annual cycle) are studied over various sectors, such as the Arabian Sea, Bay of Bengal and Indian Peninsula region. The study reveals that the low‐level kinetic energy, vertically integrated generation of kinetic energy and net tropospheric moisture over Arabian Sea can be used as potential predictors for the prediction of the possible onset date of the summer monsoon over the Indian Peninsula. Copyright © 2005 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The rainfall associated with the Indian summer monsoon shows large intraseasonal and interannual variability. Break-monsoon conditions are one of the important epochs of the monsoon, and they contribute significantly to the intraseasonal variability of the monsoon. The National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis data sets are used to investigate the significant energy budget terms during the pre-break (5 days prior to the commencement of the break), break and post-break (5 days after the cessation of the break) periods. In the present study, certain dynamic and thermodynamic characteristics of the monsoon circulation during break-monsoon conditions are investigated. The important terms in the various energy budget equations are analysed between the surface and 100 hPa for the break and its departures from pre- and post-break for the period 1968–96. The statistical significance of these departures is also examined by Student''s t-test at the 95% confidence level. The volume integral of the budget terms is also examined in four sectors, i.e. the Arabian Sea, Bay of Bengal, northern India and central India. Significant changes in the wind field and vorticity at 850 hPa take place in the monsoon trough zone, coastal regions of the western coast of India and the southwestern Bay of Bengal off the southern Indian coast. The vertically upward rising arm of the Hadley cell weakens during the break phase. The strong flux convergence of kinetic energy in the central Arabian Sea and flux divergence in the northeastern Bay of Bengal weakens during pre- and post-break periods. Significant changes in the diabatic heating horizontal flux of heat and moisture are observed in the monsoon trough zone, central and northwestern Bay of Bengal. The Bay of Bengal and central India sectors show higher magnitudes and changes in respect of dynamic and thermodynamic parameters compared with the Arabian Sea and northern India. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Southwest summer monsoon rainfall over Orissa, a state of eastern India, shows characteristic spatial and temporal variability, due to the interaction of basic westerly flow with orography and the synoptic-scale monsoon disturbances developing over the northern Bay of Bengal and moving west-northwestwards along the monsoon trough. The aim of this study is to find out the main features of the spatial variability of daily monsoon rainfall over Orissa and associated synoptic systems. Empirical orthogonal function (EOF) analysis is a good tool to filter out the main components from any noise, and this was applied to daily monsoon rainfall (June–September) data of 31 uniformly distributed stations over a period of 20 years (1980–1999). The association of synoptic systems with significant EOFs has been confirmed by analysing daily synoptic systems over Orissa and its neighbourhood during the same period. The first three EOFs in S-mode may be attributed to good monsoon rainfall in association with low-pressure systems/cyclonic circulation (LPSC), like lows, depressions, cyclonic storms and cyclonic circulation extending up to the mid-tropospheric level over the northwest (NW) Bay/NW and the adjoining northeast (NE) Bay, over Gangetic West Bengal (GWB) and over Orissa/NW and the adjoining west central (WC) Bay. The fourth and fifth EOFs may be attributed to a weak monsoon condition being associated only with a monsoon trough without any embedded system and LPSC over the NE and the adjoining NW Bay respectively. Based on rotation of significant EOFs in T-mode, which gives better regionalization, Orissa consists of five homogeneous regions of daily monsoon rainfall: (i) eastern Orissa, (ii) western Orissa, (iii) northwest Orissa, (iv) north Orissa and (v) northeast Orissa. Eastern Orissa gets higher rainfall than the other regions, due to LPSC over NW Bay/NW and the adjoining NE Bay, western Orissa rainfall is due to LPSC over Orissa/NW and the adjoining WC Bay; likewise, northwest Orissa rainfall is due to LPSC over GWB, north Orissa rainfall is due to LPSC over the NE and the adjoining NW Bay, and northeast Orissa rainfall is due only to a monsoon trough without any significant embedded system over Orissa and adjoining land/sea areas. Copyright © 2003 Royal Meteorological Society [ABSTRACT FROM AUTHOR]