Event attribution in the context of climate change seeks to understand the role of anthropogenic greenhouse gas emissions on extreme weather events, either specific events or classes of events. A common approach to event attribution uses climate model output under factual (real-world) and counterfactual (world that might have been without anthropogenic greenhouse gas emissions) scenarios to estimate the probabilities of the event of interest under the two scenarios.

India has witnessed some of the most devastating extreme precipitation events, which have affected urban transportation, agriculture, and infrastructure. Despite the profound implications and damage due to extreme precipitation events, the influence of anthropogenic warming on the intensity and frequency of extreme precipitation events over India remains poorly constrained.

Examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rainfed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. To that end, trend analysis has been employed to inspect the change of rainfall and temperature in northcentral Ethiopia using gridded monthly precipitation data obtained from Global Precipitation and Climate Centre (GPCC V7) and temperature data from Climate Research Unit (CRU TS 3.23) with 0.5° by 0.5° resolution from 1901 to 2014.

Drought characteristics for the Indian monsoon region are analyzed using two different datasets and standard precipitation index (SPI), standardized precipitation-evapotranspiration index (SPEI), Gaussian mixture model-based drought index (GMM-DI), and hidden Markov model-based drought index (HMM-DI) for the period 1901–2004. Drought trends and variability were analyzed for three epochs: 1901–1935, 1936–1971 and 1972–2004.

Original Source

With the need to increase crop production to meet the needs of a growing population, protecting the productivity of our soil resource is essential. However, conservationists are concerned that conservation practices that were effective in the past may no longer be effective in the future under projected climate change. In winter wheat cropland in the Southern Great Plains of the U.S., increased precipitation intensity and increased aridity associated with warmer temperatures may pose increased risks of soil erosion from vulnerable soils and landscapes.

Gridded rainfall data of 0.5×0.5° resolution (CRU TS 3.21) was analysed to study long term spatial and temporal trends on annual and seasonal scales in Wainganga river basin located in Central India during 1901–2012. After testing the presence of autocorrelation, Mann–Kendall (Modified Mann–Kendall) test was applied to non-auto correlated (auto correlated) series to detect the trends in rainfall data. Theil and Sen׳s slope estimator test was used for finding the magnitude of change over a time period.

In the present study, the observed variability of monsoon droughts over India has been examined using a drought monitoring index, namely the Standardized Precipitation Evapo-transpiration Index (SPEI). For calculating the SPEI over different time periods, long term (1901–2010), high resolution, monthly gridded temperature and rainfall data sets have been used. The drought time series shows significant interannual, decadal and long term trends. The analysis suggests a general increase in the intensity and percent area affected by moderate droughts during the recent decades.