The importance seasonal rainfall associated with the Indian summer monsoon is very significant fo... more The importance seasonal rainfall associated with the Indian summer monsoon is very significant for an agricultural-dependent economy like India. An imbalance in the seasonal rainfall can create havocs in the form of droughts or flood. Other than agricultural sector, various other sectors are also widely associated with the monsoon rainfall and can have a direct impact on the economy of India. With large sectors at stake due to monsoon rainfall, the demand for a skillful prediction of Indian summer monsoon rainfall has been ever increasing. This review article focuses on the recent developments and success of the statistical and dynamical methods for the prediction of Indian summer monsoon rainfall. Statistical methods were widely used in the late 20 th century, when the availability of computational power was limited. But, with advancements in computational technologies dynamical methods were developed and used with reasonable success. This review has provided a glimpse of the long history of India Meteorological Department (IMD) operational forecast system, including the recent efforts and the success by the Indian scientific community using advanced global climate models and multi-statistical approaches. Recent scientific studies have also been discussed for the creation of a hybrid-dynamical-statistical model where the results of dynamically downscaled products are statistically corrected using various statistical methods, thereby creating a robust method for a skillful prediction system.
This study presents the reversal nature in rainfall over heavy rainfall zone (HRZ; more than 80% ... more This study presents the reversal nature in rainfall over heavy rainfall zone (HRZ; more than 80% of the long-period average (LPA) of the Indian summer monsoon rainfall (ISMR)) and low rainfall zone (LRZ; less than 40% of ISMR-LPA) in India. The India Meteorological Department (IMD) high-resolution (0.25˚×0.25˚) dataset is used from 1901 to 2016. The single and multiple change point detection techniques are used to nd the change in rainfall pattern over both the regions. Further, the study period is divided into two halves P1 (1901-1958) and P2 (1959-2016) in order to study change in rainfall pattern in the recent and past periods. In P2, rainfall pattern gets reversed and interestingly ISMR has shown an increasing trend over LRZ and a decreasing trend is noticed over HRZ and the results are statistically signi cant. The increasing/decreasing number of moderate and high intensity rainfall events are the main cause for this reversal pattern. Additionally, the number of dry days is increased over the HRZ and deceased over the LRZ. This study further con rms that 'dry becomes drier and wet becomes wetter' paradigm is not solely acceptable for India. The present study provides information about changes in dry days and ISMR variability in the context of climate change, which will be useful to agricultural risk management, water resources, drought monitoring, model developers, and policy planer on the adaptation strategies for climate change.
Establishment of Indian Summer Monsoon (ISM) Rainfall passes through the different phases and is ... more Establishment of Indian Summer Monsoon (ISM) Rainfall passes through the different phases and is not uniformly distributed over the Indian subcontinent. This enhancement and reduction in daily rainfall anomaly over the Indian core monsoon region during peak monsoon season (i.e., July and August) is commonly termed as 'active' and 'break' phases of monsoon. The purpose of this study is to analyze Regional Climate Model (RegCM) results obtained by using the most suitable Convective Parameterization Scheme (CPS) to determine active/break phases of ISM. The model simulated daily Outgoing Longwave Radiation (OLR), Mean Sea Level Pressure (MSLP), and the wind at 850hPa of spatial resolution of 0.5ox0.5o are compared with NOAA, NCEP, and EIN15 data, respectively over the South-Asia Coordinated Regional Climate Downscaling EXperiment (CORDEX) region. Twenty five years (1986-2010) composites of OLR, MSLP, and the wind at 850hPa are considered from start to the dates of active/break phase and upto the end dates of active/break spell of monsoon. A negative/positive anomaly of OLR with active/break phase is found in simulations with CPSs Emanuel and Mix99 (Grell over land; Emanuel over ocean) over the core monsoon region as well as over Monsoon Convergence Zone (MCZ) of India. The appearance of monsoon trough during active phase over the core monsoon zone and its shifting towards the Himalayan foothills during break phase are also depicted well. Because of multi cloud function over oceanic region and single cloud function over the land mass, the Mix99 CPSs are performing well in simulating the synoptic features during the phases of monsoon.
High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand f... more High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand for fine-scale products over the Indian monsoon region (IMR) which has diverse land-surface characteristics. This demand is fueled by findings that improved representation of land-state help improve rainfall/flood prediction. Here we report on the development of a high-resolution (4 km and 3 hourly) SM/ST product for 2001–2014 during Indian monsoon seasons (June–September). First, the quality of atmospheric fields from five reanalysis sources was examined to identify realistic forcing to a land data assimilation system (LDAS). The evaluation of developed SM/ST against observations highlighted the importance of quality forcing fields. There is a significant relation between the forcing error and the errors in the SM/ST. A combination of forcing fields was used to develop 14-years of SM/ST data. This dataset captured inter-annual, intra-seasonal, and diurnal variations under different monso...
In the present study, simulations have been carried out to study the relationship between wintert... more In the present study, simulations have been carried out to study the relationship between wintertime precipitations and the large scale global forcing (ENSO) using the tropical band version of Regional Climate Model (RegT-Band) for 5 El Niño and 4 La Niña years. The RegT-Band model is integrated with the observed sea-surface temperature and lateral boundary conditions from National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis 2 (NCEP-DOE2) reanalysis. The model domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of 45 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. The performance evaluation of the model in capturing the large scale fields followed by ENSO response with wintertime precipitation has been carried out by using model simulations against NCEP-DOE2 and Global Precipitation Climatology Project (GPCP) precipitation data. The analysis suggests that the model is able to reproduce the upper airfields and large-scale precipitation during wintertime, although the model has some systematic biases compared to the observations. A comparison of model-simulated precipitation with observed precipitation at 17 station locations has been carried out. It is noticed that the RegT-Band model simulations are able to bring out the observed features reasonably well. Therefore, this preliminary study indicates that the tropical band version of the regional climate model can be effectively used for the better understanding of the large-scale global forcings.
Climate prediction over the Western Himalaya is a challenging task due to the highly variable alt... more Climate prediction over the Western Himalaya is a challenging task due to the highly variable altitude and orientation of orographic barriers. Surface characteristics also play a vital role in climate simulations and need appropriate representation in the models. In this study, two land surface parameterization schemes (LSPS), the Biosphere-Atmosphere Transfer Scheme (BATS) and the Common Land Model (CLM, version 3.5) in the regional climate model (RegCM, version 4) have been tested over the Himalayan region for nine distinct winter seasons in respect of seasonal precipitation (three years each for excess, normal and deficit). Reanalysis II data of the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) have been used as initial and lateral boundary conditions for the RegCM model. In order to provide land surface boundary conditions in the RegCM model, geophysical parameters (10 min resolution) obtained from the United States Geophysical Survey were used. The performance of two LSPS (CLM and BATS) coupled with the RegCM is evaluated against gridded precipitation and surface temperature data sets from the India Meteorological Department (IMD). It is found that the simulated surface temperature and precipitation are better represented in the CLM scheme than in the BATS when compared with observations. Further, several statistical analysis such as bias, root mean square error (RMSE), spatial correlation coefficient (CC) and skill scores like the equitable threat score (ETS) and the probability of detection (POD) are estimated for evaluating RegCM simulations using both LSPS. Results indicate that the RMSE decreases and the CC increases with the use of the CLM compared to BATS. ETS and POD also indicate that the performance of the model is better with the CLM than with the BATS in simulating seasonal scale precipitation. Overall, results suggest that the performance of the RegCM coupled with the CLM scheme improves the model skill in predicting winter precipitation (by 15-25%) and temperature (by 10-20%) over the Western Himalaya.
The climatology, amplitude error, phase error and mean square skill score (MSSS) of temperature p... more The climatology, amplitude error, phase error and mean square skill score (MSSS) of temperature predictions from five different state-of-the-art General Circulation Models (GCMs) have been examined for the winter (December-January-February) seasons over the North India. In this region, temperature variability affects the phenological development processes of wheat crops and the grain yield. The GCM forecasts of temperature for a whole season issued in November from various organizations are compared with observed gridded temperature data obtained from the India Meteorological Department (IMD) for the period 1982-2009. The MSSS indicates that the models have skills of varying degrees. Predictions of maximum and minimum temperature obtained from the NCEP climate forecast system model (NCEP_CFSv2) is compared with station level observations from the Snow and Avalanche Study Establishment (SASE). It has been found that when the model temperatures are corrected to account the bias in the model and actual orography, the predictions are able to delineate the observed trend compared to that which doesn't have orography correction.
The present study examines the performance of convective parameterization schemes at two differen... more The present study examines the performance of convective parameterization schemes at two different horizontal resolutions (90 and 30 km) in simulating winter (December-February; DJF) circulation and associated precipitation over the Western Himalayas using the regional climate model RegCM4. The model integrations are carried out in a one-way nested mode for three distinct precipitation years (excess, normal and deficit) using four combinations of cumulus schemes. The National Center for Environment Prediction-Department of Energy Reanalysis-2 project utilized gridded data, observed precipitation data from the India Meteorological Department and station data from the Snow and Avalanche Study Establishment were used to evaluate model performance. The seasonal mean circulation patterns and precipitation distribution are well demonstrated by all of the cumulus convection schemes. However, model performance varies using different schemes. Statistical analysis confirms that the root mean square error is reduced by about 2-3 times and the correlation coefficient (CC) increases in the fine resolution (30 km) simulations compared to coarse resolution (90 km) simulations. A statistically significant CC (at a 10 % significance level) is found only in the fine resolution simulations. The Grell cumulus model with a Fritsch-Chappell closure (Grell-FC) is better at simulating seasonal mean patterns and inter-annual variability of two contrasting winter seasons than the other scheme combinations.
The performance of RegCM4 for seasonal-scale simulation of winter circulation and associated prec... more The performance of RegCM4 for seasonal-scale simulation of winter circulation and associated precipitation over the Western Himalayas (WH) is examined. The model simulates the circulation features and precipitation in three distinct precipitation years reasonably well. It is found that the RMSE decreases and correlation coefficient increases in the precipitation simulations with the increase of model horizontal resolutions. The ETS and POD for the simulated precipitation also indicate that the performance of model is better at 30 km resolution than at 60 and 90 km resolutions. This improvement comes due to better representation of orography in the high-resolution model in which sharp orography gradient in the domain plays an important role in wintertime precipitation processes. A comparison of model-simulated precipitation with observed precipitation at 17 station locations has been carried out. Overall, the results suggest that 30 km model produced better skill in simulating the pr...
ABSTRACTThis study aims to analyse the skill of state‐of‐the‐art of five general circulation mode... more ABSTRACTThis study aims to analyse the skill of state‐of‐the‐art of five general circulation models (GCMs) in predicting winter precipitation over northern India. The precipitation in winter season (December, January and February) is very important for Rabi crops in north India, particularly for wheat, as it supplements moisture and maintains low temperature for the development of the crops. The GCM outputs (seasonal mean forecasts issued in November) from various organizations are compared with the observed high‐resolution gridded rainfall data obtained from India Meteorological Department (IMD). Prediction skill of such GCMs is examined for the period 1982–2009. The climatology, interannual standard deviation (ISD) and correlation coefficients have been computed for the five GCMs and compared with observation. It is found that the models are able to reproduce the climatology and ISD to varying degrees; however, skill of predictions is too low. Multi‐model ensemble (MME) approaches...
The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in... more The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in NCMRWF global spectral model is examined in simulating the winter circulation and associated precipitation over the Northwest India (NWI; 23 0-37.5 0 N and 69 0-85 0 E) region. For this purpose, nine different set of orography representations for nine distinct precipitation years (three years each for wet, normal and dry) have been considered by increasing (decreasing) 5%, 10%, 15% and 20% from the mean height (CNTRL) of the Himalaya in RegCM4 model. Validation with various observations revealed a good improvement in reproducing the precipitation intensity and distribution with increased model height compared to the results obtained from CNTRL and reduced orography experiments. Further it has been found that, increase in height by 10% (P10) increases seasonal precipitation about 20%, while decrease in height by 10% (M10) results around 28% reduction in seasonal precipitation as compared to CNTRL experiment over NWI region. This improvement in precipitation simulation comes due to better representation of vertical pressure velocity and moisture transport as these factors play an important role in wintertime precipitation processes over NWI region. Furthermore, a comparison of model-simulated precipitation with observed precipitation at 17 station locations has been also carried out. Overall, the results suggest that when the orographic increment of 10% (P10) is applied on RegCM4 model, it has better skill in simulating the precipitation over the NWI region and this model is a useful tool for further regional downscaling studies.
The importance seasonal rainfall associated with the Indian summer monsoon is very significant fo... more The importance seasonal rainfall associated with the Indian summer monsoon is very significant for an agricultural-dependent economy like India. An imbalance in the seasonal rainfall can create havocs in the form of droughts or flood. Other than agricultural sector, various other sectors are also widely associated with the monsoon rainfall and can have a direct impact on the economy of India. With large sectors at stake due to monsoon rainfall, the demand for a skillful prediction of Indian summer monsoon rainfall has been ever increasing. This review article focuses on the recent developments and success of the statistical and dynamical methods for the prediction of Indian summer monsoon rainfall. Statistical methods were widely used in the late 20 th century, when the availability of computational power was limited. But, with advancements in computational technologies dynamical methods were developed and used with reasonable success. This review has provided a glimpse of the long history of India Meteorological Department (IMD) operational forecast system, including the recent efforts and the success by the Indian scientific community using advanced global climate models and multi-statistical approaches. Recent scientific studies have also been discussed for the creation of a hybrid-dynamical-statistical model where the results of dynamically downscaled products are statistically corrected using various statistical methods, thereby creating a robust method for a skillful prediction system.
This study presents the reversal nature in rainfall over heavy rainfall zone (HRZ; more than 80% ... more This study presents the reversal nature in rainfall over heavy rainfall zone (HRZ; more than 80% of the long-period average (LPA) of the Indian summer monsoon rainfall (ISMR)) and low rainfall zone (LRZ; less than 40% of ISMR-LPA) in India. The India Meteorological Department (IMD) high-resolution (0.25˚×0.25˚) dataset is used from 1901 to 2016. The single and multiple change point detection techniques are used to nd the change in rainfall pattern over both the regions. Further, the study period is divided into two halves P1 (1901-1958) and P2 (1959-2016) in order to study change in rainfall pattern in the recent and past periods. In P2, rainfall pattern gets reversed and interestingly ISMR has shown an increasing trend over LRZ and a decreasing trend is noticed over HRZ and the results are statistically signi cant. The increasing/decreasing number of moderate and high intensity rainfall events are the main cause for this reversal pattern. Additionally, the number of dry days is increased over the HRZ and deceased over the LRZ. This study further con rms that 'dry becomes drier and wet becomes wetter' paradigm is not solely acceptable for India. The present study provides information about changes in dry days and ISMR variability in the context of climate change, which will be useful to agricultural risk management, water resources, drought monitoring, model developers, and policy planer on the adaptation strategies for climate change.
Establishment of Indian Summer Monsoon (ISM) Rainfall passes through the different phases and is ... more Establishment of Indian Summer Monsoon (ISM) Rainfall passes through the different phases and is not uniformly distributed over the Indian subcontinent. This enhancement and reduction in daily rainfall anomaly over the Indian core monsoon region during peak monsoon season (i.e., July and August) is commonly termed as 'active' and 'break' phases of monsoon. The purpose of this study is to analyze Regional Climate Model (RegCM) results obtained by using the most suitable Convective Parameterization Scheme (CPS) to determine active/break phases of ISM. The model simulated daily Outgoing Longwave Radiation (OLR), Mean Sea Level Pressure (MSLP), and the wind at 850hPa of spatial resolution of 0.5ox0.5o are compared with NOAA, NCEP, and EIN15 data, respectively over the South-Asia Coordinated Regional Climate Downscaling EXperiment (CORDEX) region. Twenty five years (1986-2010) composites of OLR, MSLP, and the wind at 850hPa are considered from start to the dates of active/break phase and upto the end dates of active/break spell of monsoon. A negative/positive anomaly of OLR with active/break phase is found in simulations with CPSs Emanuel and Mix99 (Grell over land; Emanuel over ocean) over the core monsoon region as well as over Monsoon Convergence Zone (MCZ) of India. The appearance of monsoon trough during active phase over the core monsoon zone and its shifting towards the Himalayan foothills during break phase are also depicted well. Because of multi cloud function over oceanic region and single cloud function over the land mass, the Mix99 CPSs are performing well in simulating the synoptic features during the phases of monsoon.
High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand f... more High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand for fine-scale products over the Indian monsoon region (IMR) which has diverse land-surface characteristics. This demand is fueled by findings that improved representation of land-state help improve rainfall/flood prediction. Here we report on the development of a high-resolution (4 km and 3 hourly) SM/ST product for 2001–2014 during Indian monsoon seasons (June–September). First, the quality of atmospheric fields from five reanalysis sources was examined to identify realistic forcing to a land data assimilation system (LDAS). The evaluation of developed SM/ST against observations highlighted the importance of quality forcing fields. There is a significant relation between the forcing error and the errors in the SM/ST. A combination of forcing fields was used to develop 14-years of SM/ST data. This dataset captured inter-annual, intra-seasonal, and diurnal variations under different monso...
In the present study, simulations have been carried out to study the relationship between wintert... more In the present study, simulations have been carried out to study the relationship between wintertime precipitations and the large scale global forcing (ENSO) using the tropical band version of Regional Climate Model (RegT-Band) for 5 El Niño and 4 La Niña years. The RegT-Band model is integrated with the observed sea-surface temperature and lateral boundary conditions from National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis 2 (NCEP-DOE2) reanalysis. The model domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of 45 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. The performance evaluation of the model in capturing the large scale fields followed by ENSO response with wintertime precipitation has been carried out by using model simulations against NCEP-DOE2 and Global Precipitation Climatology Project (GPCP) precipitation data. The analysis suggests that the model is able to reproduce the upper airfields and large-scale precipitation during wintertime, although the model has some systematic biases compared to the observations. A comparison of model-simulated precipitation with observed precipitation at 17 station locations has been carried out. It is noticed that the RegT-Band model simulations are able to bring out the observed features reasonably well. Therefore, this preliminary study indicates that the tropical band version of the regional climate model can be effectively used for the better understanding of the large-scale global forcings.
Climate prediction over the Western Himalaya is a challenging task due to the highly variable alt... more Climate prediction over the Western Himalaya is a challenging task due to the highly variable altitude and orientation of orographic barriers. Surface characteristics also play a vital role in climate simulations and need appropriate representation in the models. In this study, two land surface parameterization schemes (LSPS), the Biosphere-Atmosphere Transfer Scheme (BATS) and the Common Land Model (CLM, version 3.5) in the regional climate model (RegCM, version 4) have been tested over the Himalayan region for nine distinct winter seasons in respect of seasonal precipitation (three years each for excess, normal and deficit). Reanalysis II data of the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) have been used as initial and lateral boundary conditions for the RegCM model. In order to provide land surface boundary conditions in the RegCM model, geophysical parameters (10 min resolution) obtained from the United States Geophysical Survey were used. The performance of two LSPS (CLM and BATS) coupled with the RegCM is evaluated against gridded precipitation and surface temperature data sets from the India Meteorological Department (IMD). It is found that the simulated surface temperature and precipitation are better represented in the CLM scheme than in the BATS when compared with observations. Further, several statistical analysis such as bias, root mean square error (RMSE), spatial correlation coefficient (CC) and skill scores like the equitable threat score (ETS) and the probability of detection (POD) are estimated for evaluating RegCM simulations using both LSPS. Results indicate that the RMSE decreases and the CC increases with the use of the CLM compared to BATS. ETS and POD also indicate that the performance of the model is better with the CLM than with the BATS in simulating seasonal scale precipitation. Overall, results suggest that the performance of the RegCM coupled with the CLM scheme improves the model skill in predicting winter precipitation (by 15-25%) and temperature (by 10-20%) over the Western Himalaya.
The climatology, amplitude error, phase error and mean square skill score (MSSS) of temperature p... more The climatology, amplitude error, phase error and mean square skill score (MSSS) of temperature predictions from five different state-of-the-art General Circulation Models (GCMs) have been examined for the winter (December-January-February) seasons over the North India. In this region, temperature variability affects the phenological development processes of wheat crops and the grain yield. The GCM forecasts of temperature for a whole season issued in November from various organizations are compared with observed gridded temperature data obtained from the India Meteorological Department (IMD) for the period 1982-2009. The MSSS indicates that the models have skills of varying degrees. Predictions of maximum and minimum temperature obtained from the NCEP climate forecast system model (NCEP_CFSv2) is compared with station level observations from the Snow and Avalanche Study Establishment (SASE). It has been found that when the model temperatures are corrected to account the bias in the model and actual orography, the predictions are able to delineate the observed trend compared to that which doesn't have orography correction.
The present study examines the performance of convective parameterization schemes at two differen... more The present study examines the performance of convective parameterization schemes at two different horizontal resolutions (90 and 30 km) in simulating winter (December-February; DJF) circulation and associated precipitation over the Western Himalayas using the regional climate model RegCM4. The model integrations are carried out in a one-way nested mode for three distinct precipitation years (excess, normal and deficit) using four combinations of cumulus schemes. The National Center for Environment Prediction-Department of Energy Reanalysis-2 project utilized gridded data, observed precipitation data from the India Meteorological Department and station data from the Snow and Avalanche Study Establishment were used to evaluate model performance. The seasonal mean circulation patterns and precipitation distribution are well demonstrated by all of the cumulus convection schemes. However, model performance varies using different schemes. Statistical analysis confirms that the root mean square error is reduced by about 2-3 times and the correlation coefficient (CC) increases in the fine resolution (30 km) simulations compared to coarse resolution (90 km) simulations. A statistically significant CC (at a 10 % significance level) is found only in the fine resolution simulations. The Grell cumulus model with a Fritsch-Chappell closure (Grell-FC) is better at simulating seasonal mean patterns and inter-annual variability of two contrasting winter seasons than the other scheme combinations.
The performance of RegCM4 for seasonal-scale simulation of winter circulation and associated prec... more The performance of RegCM4 for seasonal-scale simulation of winter circulation and associated precipitation over the Western Himalayas (WH) is examined. The model simulates the circulation features and precipitation in three distinct precipitation years reasonably well. It is found that the RMSE decreases and correlation coefficient increases in the precipitation simulations with the increase of model horizontal resolutions. The ETS and POD for the simulated precipitation also indicate that the performance of model is better at 30 km resolution than at 60 and 90 km resolutions. This improvement comes due to better representation of orography in the high-resolution model in which sharp orography gradient in the domain plays an important role in wintertime precipitation processes. A comparison of model-simulated precipitation with observed precipitation at 17 station locations has been carried out. Overall, the results suggest that 30 km model produced better skill in simulating the pr...
ABSTRACTThis study aims to analyse the skill of state‐of‐the‐art of five general circulation mode... more ABSTRACTThis study aims to analyse the skill of state‐of‐the‐art of five general circulation models (GCMs) in predicting winter precipitation over northern India. The precipitation in winter season (December, January and February) is very important for Rabi crops in north India, particularly for wheat, as it supplements moisture and maintains low temperature for the development of the crops. The GCM outputs (seasonal mean forecasts issued in November) from various organizations are compared with the observed high‐resolution gridded rainfall data obtained from India Meteorological Department (IMD). Prediction skill of such GCMs is examined for the period 1982–2009. The climatology, interannual standard deviation (ISD) and correlation coefficients have been computed for the five GCMs and compared with observation. It is found that the models are able to reproduce the climatology and ISD to varying degrees; however, skill of predictions is too low. Multi‐model ensemble (MME) approaches...
The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in... more The role of the Himalayan orography representation in a Regional Climate Model (RegCM4) nested in NCMRWF global spectral model is examined in simulating the winter circulation and associated precipitation over the Northwest India (NWI; 23 0-37.5 0 N and 69 0-85 0 E) region. For this purpose, nine different set of orography representations for nine distinct precipitation years (three years each for wet, normal and dry) have been considered by increasing (decreasing) 5%, 10%, 15% and 20% from the mean height (CNTRL) of the Himalaya in RegCM4 model. Validation with various observations revealed a good improvement in reproducing the precipitation intensity and distribution with increased model height compared to the results obtained from CNTRL and reduced orography experiments. Further it has been found that, increase in height by 10% (P10) increases seasonal precipitation about 20%, while decrease in height by 10% (M10) results around 28% reduction in seasonal precipitation as compared to CNTRL experiment over NWI region. This improvement in precipitation simulation comes due to better representation of vertical pressure velocity and moisture transport as these factors play an important role in wintertime precipitation processes over NWI region. Furthermore, a comparison of model-simulated precipitation with observed precipitation at 17 station locations has been also carried out. Overall, the results suggest that when the orographic increment of 10% (P10) is applied on RegCM4 model, it has better skill in simulating the precipitation over the NWI region and this model is a useful tool for further regional downscaling studies.
Uploads
Papers by Palash Sinha