Comparison of INSAT-3D retrieved total column ozone with ground-based and AIRS observations over India.

Ozone plays an important role in the thermal structure and chemical composition of the atmosphere. The present study compares the temporal and spatial distributions of Total Column Ozone (TCO) over the Indian sub-continent retrieved from a geostationary Indian National Satellite (INSAT-3D) and Atmospheric Infrared Sounder (AIRS). The INSAT-3D TCO values are also evaluated against the Dobson spectrophotometer observations at two locations. The inter-comparison results reveal a good correlation of 0.8, the bias of -5 DU, and Root Mean Square Error (RMSE) of 15 DU approximately between the TCO retrieved from INSAT-3D and AIRS. The lowest RMSE and highest correlation coefficient were found in the pre-monsoon season. The INSAT-3D and AIRS show reasonable agreement with the RMSE varying between 10 and 30 DU. On the other hand, evaluation of the INSAT-3D TCO with the ground-based observations from Dobson spectrophotometers located at New Delhi and Varanasi showed fair agreement with a maximum monthly mean correlation coefficient of 0.68 and 0.76, respectively, and RMSE varying from 11 to 16 DU for both the stations. The seasonal distribution of TCO and its variation over the Indian region has also been studied using INSAT-3D and AIRS data. The analysis exhibits strong seasonal variations, with higher values in pre-monsoon season and minimum values in winter season. The noticeable seasonal variability of TCO can be attributed to complex combination of photochemical and dynamical processes in the troposphere and stratosphere. The main objectives of the study are to compare the INSAT-3D TCO with two independent ground-based Dobson spectrophotometer observations and Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite.

Analysis of Outdoor Thermal Discomfort Over the Kingdom of Saudi Arabia.

In this study, the variability and trends of the outdoor thermal discomfort index (DI) in the Kingdom of Saudi Arabia (KSA) were analyzed over the 39-year period of 1980-2018. The hourly DI was estimated based on air temperature and relative humidity data obtained from the next-generation global reanalysis from the European Center for Medium-Range Weather Forecasts and in-house high-resolution regional reanalysis generated using an assimilative Weather Research Forecast (WRF) model. The DI exceeds 28°C, that is, the threshold for human discomfort, in all summer months (June to September) over most parts of the KSA due to a combination of consistently high temperatures and relative humidity. The DI is greater than 28°C for 8-16 h over the western parts of KSA and north of the central Red Sea. A DI of >28°C persistes for 7-9 h over the Red Sea and western KSA for 90% of summer days. The spatial extent and number of days with DI > 30°C, that is, the threshold for severe human discomfort, are significantly lower than those with DI > 28°C. Long-term trends in the number of days with DI > 28°C indicate a reduced rate of increase or even a decrease over some parts of the southwestern KSA in recent decades (1999-2018). Areas with DI > 30°C, in particular the northwestern regions of the Arabian Gulf and its adjoining regions, also showed improved comfort levels during recent decades. Significant increases in population and urbanization have been reported throughout the KSA during the study period. Analysis of five-years clinical data suggests a positive correlation between higher temperatures and humidity with heat-related deaths during the Hajj pilgrimage. The information provided herein is expected to aid national authorities and policymakers in developing necessary strategies to mitigate the exposure of humans to high levels of thermal discomfort in the KSA.

Projections of heat stress and associated work performance over India in response to global warming.

Summertime heat stress future projections from multi-model mean of 18 CMIP5 models show unprecedented increasing levels in the RCP 4.5 and RCP 8.5 emission scenarios over India. The estimated heat stress is found to have more impact on the coastal areas of India having exposure to more frequent days of extreme caution to danger category along with the increased probability of occurrence. The explicit amount of change in temperature, increase in the duration and intensity of warm days along with the modulation in large scale circulation in future are seemingly connected to the increasing levels of heat stress over India. A decline of 30 to 40% in the work performance is projected over India by the end of the century due to the elevated heat stress levels which pose great challenges to the country policy makers to design the safety mechanisms and to protect people working under continuous extreme hot weather conditions.

A comparison of HWRF, ARW and NMM models in Hurricane Katrina (2005) simulation.

The life cycle of Hurricane Katrina (2005) was simulated using three different modeling systems of Weather Research and Forecasting (WRF) mesoscale model. These are, HWRF (Hurricane WRF) designed specifically for hurricane studies and WRF model with two different dynamic cores as the Advanced Research WRF (ARW) model and the Non-hydrostatic Mesoscale Model (NMM). The WRF model was developed and sourced from National Center for Atmospheric Research (NCAR), incorporating the advances in atmospheric simulation system suitable for a broad range of applications. The HWRF modeling system was developed at the National Centers for Environmental Prediction (NCEP) based on the NMM dynamic core and the physical parameterization schemes specially designed for tropics. A case study of Hurricane Katrina was chosen as it is one of the intense hurricanes that caused severe destruction along the Gulf Coast from central Florida to Texas. ARW, NMM and HWRF models were designed to have two-way interactive nested domains with 27 and 9 km resolutions. The three different models used in this study were integrated for three days starting from 0000 UTC of 27 August 2005 to capture the landfall of hurricane Katrina on 29 August. The initial and time varying lateral boundary conditions were taken from NCEP global FNL (final analysis) data available at 1 degree resolution for ARW and NMM models and from NCEP GFS data at 0.5 degree resolution for HWRF model. The results show that the models simulated the intensification of Hurricane Katrina and the landfall on 29 August 2005 agreeing with the observations. Results from these experiments highlight the superior performance of HWRF model over ARW and NMM models in predicting the track and intensification of Hurricane Katrina.

Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators.