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Studies have explored concurrent hot extremes and dry events across the world, however, the modulation of average temperature regimes during droughts is lacking. This study explores the differential intensification rates in average temperatures in the historical past and projected future for different climatologies (dry, wet, and average) over the Indian subcontinent, and the intensification rates are linked with established atmospheric feedback mechanisms. Thereafter, future differential shifts in temperatures associated with different climatologies were studied under climate change for the 2 °C and 3 °C warming worlds using CMIP6 simulations. Results show that temperature intensification rates are much more pronounced under dry/wet climatology than average climatology. Dry climatology temperatures (Td) exhibit extensive cooling trends in northern India while warming trends are reported in southern India. Wet climatology temperatures (Tw) show extensive warming trends in northern India. Further, analysis of atmospheric moisture and aridity metrics such as vapor pressure deficit (VPD) and relative humidity (RH) show a stronger linkage with temperatures during the dry/wet climatology compared to the long-term average. Multi-model shifts under climate change project cooling and warming Td shifts under 2 °C and 3 °C levels, respectively with greater pronounced temperature shifts in northern regions. The results of this study have implications for water resource management, drought risk reductions, and mitigation of agricultural crop losses. [ABSTRACT FROM AUTHOR]

Accurate and reliable air temperature forecasts are necessary for predicting and responding to thermal disasters such as heat strokes. Forecasts from Numerical Weather Prediction (NWP) models contain biases which require post-processing. Studies assessing the skill of probabilistic post-processing techniques (PPTs) on temperature forecasts in India are lacking. This study aims to evaluate probabilistic post-processing approaches such as Nonhomogeneous Gaussian Regression (NGR) and Bayesian Model Averaging (BMA) for improving daily temperature forecasts from two NWP models, namely, the European Centre for Medium Range Weather Forecasts (ECMWF) and the Global Ensemble Forecast System (GEFS), across the Indian subcontinent. Apart from that, the effect of probabilistic PPT on heatwave prediction skills across India is also evaluated. Results show that probabilistic PPT comprehensively outperform traditional approaches in forecasting temperatures across India at all lead times. In the Himalayan regions where the forecast skill of raw forecasts is low, the probabilistic techniques are not able to produce skillful forecasts even though they perform much better than traditional techniques. The NGR method is found to be the best performing PPT across the Indian region. Post-processing Tmax forecasts using the NGR approach was found to considerably improve the heatwave prediction skill across highly heatwave prone regions in India. The outcomes of this study will be helpful in setting up improved heatwave prediction and early warning systems in India. [ABSTRACT FROM AUTHOR]

The study makes a probabilistic assessment of drought risks due to climate change over the southeast USA based on 15 Global Circulation Model (GCM) simulations and two emission scenarios. The effects of climate change on drought characteristics such as drought intensity, frequency, areal extent, and duration are investigated using the seasonal and continuous standard precipitation index (SPI) and the standard evapotranspiration index (SPEI). The GCM data are divided into four time periods namely Historical (1961-1990), Near (2010-2039), Mid (2040-2069), and Late (2070-2099), and significant differences between historical and future time periods are quantified using the mapping model agreement technique. Further, the kernel density estimation approach is used to derive a novel probability-based severity-area-frequency (PBS) curve for the study domain. Analysis suggests that future increases in temperature and evapotranspiration will outstrip increases in precipitation and significantly affect future droughts over the study domain. Seasonal drought analysis suggest that the summer season will be impacted the most based on SPI and SPEI. Projections based on SPI follow precipitation patterns and fewer GCMs agree on SPI and the direction of change compared to the SPEI. Long-term and extreme drought events are projected to be affected more than short-term and moderate ones. Based on an analysis of PBS curves, especially based on SPEI, droughts are projected to become more severe in the future. The development of PBS curves is a novel feature in this study and will provide policymakers with important tools for analyzing future drought risks, vulnerabilities and help build drought resilience. The PBS curves can be replicated for studies around the world for drought assessment under climate change. [ABSTRACT FROM AUTHOR]

Droughts in the southeast USA have been linked to economic losses and intractable water conflicts. The region has witnessed several severe droughts events during the period from 1901 to 2005. In this study, spatiotemporal variability in meteorological drought characteristics in the southeast were analyzed using two different datasets by the means of standard precipitation index and standard precipitation evapotranspiration index for the period 1901-2005 for agricultural and non-agricultural seasons. The study periods were divided into three epochs 1901-1935, 1936-1970, and 1971-2005 and drought characteristics, in terms of severity, frequency, number, and trends were analyzed. Additionally, areal extent, drought severities and return periods associated with three severe drought years 1904, 1954, and 2000 were analyzed. Except for the state of Florida, results indicate decrease in drought severity during the recent epoch of 1970-2005 in the study domain. Trend analysis confirms that the study domain has become wetter over the last 105 years. Wetting trends were more prominent in the agricultural season. Additionally, droughts seem to have migrated from the western part of the study area encompassing the states of Alabama, Tennessee, Louisiana, and Mississippi to the Florida panhandle region during the recent epoch. Droughts exhibited higher spatiotemporal variability during the agricultural season compared to the non-agricultural seasons. Results also showed that early to mid-1950s experienced some of the most severe droughts in the study domain. Some of the drought events, such as the drought of 1954 and 2000, have been equivalent to a 100-year drought event in the southeast. The results from this study form the benchmark for studying the impacts of future climate change projections on meteorological droughts in the southeast. [ABSTRACT FROM AUTHOR]

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Reaction of an excess of 2-aminobenzenethiol or thiosalicylic acid (H2T) with cis-[MoO2L] (H2L=tridentate 2,2′-dihydroxyarylazo compound) causes elimination of one oxo ligand to give a monomeric monooxomolybdenum(VI) product [MoOL(T)]. These deep red complexes have been characterized by elemental analyses and spectroscopic techniques. [ABSTRACT FROM AUTHOR]