This study presents a comprehensive analysis of extreme events, especially drought and wet events... more This study presents a comprehensive analysis of extreme events, especially drought and wet events, spanning over the past years, evaluating their trends over time. An investigation of future projections under various scenarios such as SSP-126, SS-245, and SSP-585 for the near (2023–2048), mid (2049–2074), and far future (2075–2100) using the bias-corrected Coupled Model Intercomparisons Project 6 (CMIP6) multi-model ensemble method was also performed. The Standard Precipitation Index (SPI), a simple yet incredibly sensitive tool for measuring changes in drought, is utilized in this study, providing a valuable assessment of drought conditions across multiple timescales. The historical analysis shows that there is a significant increase in drought frequency in subdivisions such as East MP, Chhattisgarh, East UP, East Rajasthan, Tamil Nadu, and Rayalaseema over the past decades. Our findings from a meticulous examination of historical rainfall trends spanning from 1951 to 2022 show a n...
Harmful Algal Blooms lead to multi-billion-dollar losses in the United States due to shellfish cl... more Harmful Algal Blooms lead to multi-billion-dollar losses in the United States due to shellfish closures, fish mortalities, and reluctance to consume seafood. Therefore, an improved early seasonal prediction of harmful algal blooms severity is important. Conventional methods for harmful algal blooms prediction using nutrient loading as the primary driver have been found to be less accurate during extreme bloom years. Here we show that a machine learning approach using observed nutrient loading, and large-scale climate indices can improve the harmful algal blooms prediction in Lake Erie. Moreover, the seasonal prediction of harmful algal blooms can be completed by early June, before the expected peak in harmful algal bloom activity from July to October. This improved early seasonal prediction can provide timely information to policymakers for adopting proper planning and mitigation strategies such as restrictions in harvesting and help in monitoring toxins in shellfish to keep contami...
Journal of Advances in Modeling Earth Systems, 2020
Urban land surface processes need to be represented to inform future urban climate and building e... more Urban land surface processes need to be represented to inform future urban climate and building energy projections. Here, the single layer urban canopy model Town Energy Balance (TEB) is coupled to the Weather Research and Forecasting (WRF) model to create WRF‐TEB. The coupling method is described generically, implemented into software, and the code and data are released with a Singularity image to address issues of scientific reproducibility. The coupling is implemented modularly and verified by an integration test. Results show no detectable errors in the coupling. Separately, a meteorological evaluation is undertaken using observations from Toulouse, France. The latter evaluation, during an urban canopy layer heat island episode, shows reasonable ability to estimate turbulent heat flux densities and other meteorological quantities. We conclude that new model couplings should make use of integration tests as meteorological evaluations by themselves are insufficient, given that err...
Ice records at Lake George, an oligotrophic and dimictic freshwater lake in upstate New York, Uni... more Ice records at Lake George, an oligotrophic and dimictic freshwater lake in upstate New York, United States reveal that it has failed to freeze over completely 13 times since 1990. This transition from annual to intermittent ice cover is analogous to many other dimictic freshwater lakes globally. Over 60 years of meteorological observations from a nearby airport are analysed and a complicated picture emerges when considering the specific characteristics of each year. For example, Lake George froze over in 1983 and 2007 despite the air temperature having a net warming effect on the lake in the month prior to ice‐in. Simple machine learning classifiers are trained using local weather data to predict the presence of complete ice coverage on Lake George and are found to perform adequately compared to observations, with one configuration having an accuracy of 91%. Using downscaled data from a coupled‐climate model through to 2,100, projections with the trained classifiers suggest complet...
Large impacts of global warming and urbanization on near‐surface air temperature increase and coo... more Large impacts of global warming and urbanization on near‐surface air temperature increase and cooling energy demand are expected for the American Southwest region. The relative importance of these two features and their interactions are studied by means of a mesoscale model with a multilayer building energy model that allows accounting for the feedback between cooling energy consumption and air temperature for a typical summer period in Arizona. This approach allows to separate the impact of global warming from the one due to urbanization, on energy demand and air temperature. Under the highest greenhouse gas emissions scenario (RCP8.5), adverse effects on mean air temperature of global warming overwhelm those from the urbanization of new areas. In particular, the mean temperature increase for a summer period due to global warming and urban expansion in the Phoenix metropolitan area is 3.6 °C and in the Tucson metropolitan area, it is 3.1 °C. These result in an increase in the spati...
This study presents a comprehensive analysis of extreme events, especially drought and wet events... more This study presents a comprehensive analysis of extreme events, especially drought and wet events, spanning over the past years, evaluating their trends over time. An investigation of future projections under various scenarios such as SSP-126, SS-245, and SSP-585 for the near (2023–2048), mid (2049–2074), and far future (2075–2100) using the bias-corrected Coupled Model Intercomparisons Project 6 (CMIP6) multi-model ensemble method was also performed. The Standard Precipitation Index (SPI), a simple yet incredibly sensitive tool for measuring changes in drought, is utilized in this study, providing a valuable assessment of drought conditions across multiple timescales. The historical analysis shows that there is a significant increase in drought frequency in subdivisions such as East MP, Chhattisgarh, East UP, East Rajasthan, Tamil Nadu, and Rayalaseema over the past decades. Our findings from a meticulous examination of historical rainfall trends spanning from 1951 to 2022 show a n...
Harmful Algal Blooms lead to multi-billion-dollar losses in the United States due to shellfish cl... more Harmful Algal Blooms lead to multi-billion-dollar losses in the United States due to shellfish closures, fish mortalities, and reluctance to consume seafood. Therefore, an improved early seasonal prediction of harmful algal blooms severity is important. Conventional methods for harmful algal blooms prediction using nutrient loading as the primary driver have been found to be less accurate during extreme bloom years. Here we show that a machine learning approach using observed nutrient loading, and large-scale climate indices can improve the harmful algal blooms prediction in Lake Erie. Moreover, the seasonal prediction of harmful algal blooms can be completed by early June, before the expected peak in harmful algal bloom activity from July to October. This improved early seasonal prediction can provide timely information to policymakers for adopting proper planning and mitigation strategies such as restrictions in harvesting and help in monitoring toxins in shellfish to keep contami...
Journal of Advances in Modeling Earth Systems, 2020
Urban land surface processes need to be represented to inform future urban climate and building e... more Urban land surface processes need to be represented to inform future urban climate and building energy projections. Here, the single layer urban canopy model Town Energy Balance (TEB) is coupled to the Weather Research and Forecasting (WRF) model to create WRF‐TEB. The coupling method is described generically, implemented into software, and the code and data are released with a Singularity image to address issues of scientific reproducibility. The coupling is implemented modularly and verified by an integration test. Results show no detectable errors in the coupling. Separately, a meteorological evaluation is undertaken using observations from Toulouse, France. The latter evaluation, during an urban canopy layer heat island episode, shows reasonable ability to estimate turbulent heat flux densities and other meteorological quantities. We conclude that new model couplings should make use of integration tests as meteorological evaluations by themselves are insufficient, given that err...
Ice records at Lake George, an oligotrophic and dimictic freshwater lake in upstate New York, Uni... more Ice records at Lake George, an oligotrophic and dimictic freshwater lake in upstate New York, United States reveal that it has failed to freeze over completely 13 times since 1990. This transition from annual to intermittent ice cover is analogous to many other dimictic freshwater lakes globally. Over 60 years of meteorological observations from a nearby airport are analysed and a complicated picture emerges when considering the specific characteristics of each year. For example, Lake George froze over in 1983 and 2007 despite the air temperature having a net warming effect on the lake in the month prior to ice‐in. Simple machine learning classifiers are trained using local weather data to predict the presence of complete ice coverage on Lake George and are found to perform adequately compared to observations, with one configuration having an accuracy of 91%. Using downscaled data from a coupled‐climate model through to 2,100, projections with the trained classifiers suggest complet...
Large impacts of global warming and urbanization on near‐surface air temperature increase and coo... more Large impacts of global warming and urbanization on near‐surface air temperature increase and cooling energy demand are expected for the American Southwest region. The relative importance of these two features and their interactions are studied by means of a mesoscale model with a multilayer building energy model that allows accounting for the feedback between cooling energy consumption and air temperature for a typical summer period in Arizona. This approach allows to separate the impact of global warming from the one due to urbanization, on energy demand and air temperature. Under the highest greenhouse gas emissions scenario (RCP8.5), adverse effects on mean air temperature of global warming overwhelm those from the urbanization of new areas. In particular, the mean temperature increase for a summer period due to global warming and urban expansion in the Phoenix metropolitan area is 3.6 °C and in the Tucson metropolitan area, it is 3.1 °C. These result in an increase in the spati...
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Papers by Mukul Tewari