Variations in global temperature and precipitation for the period of 1948 to 2010.

Climate change has impacts on both natural and human systems. Accurate information regarding variations in precipitation and temperature is essential for identifying and understanding these potential impacts. This research applied Mann-Kendall, rescaled range analysis and wave transform methods to analyze the trends and periodic properties of global and regional surface air temperature (SAT) and precipitation (PR) over the period of 1948 to 2010. The results show that 65.34% of the area studied exhibits significant warming trends (p < 0.05) while only 3.18% of the area exhibits significant cooling trends. The greatest warming trends are observed in Antarctica (0.32 °C per decade) and Middle Africa (0.21 °C per decade). Notably, 62.26% of the area became wetter, while 22.01% of the area shows drying trends. Northern Europe shows the largest precipitation increase, 12.49 mm per decade. Western Africa shows the fastest drying, -21.05 mm per decade. The rescaled range analysis reveals large areas that show persistent warming trends; this behavior in SAT is more obvious than that in PR. Wave transform results show that a 1-year period of SAT variation dominates in all regions, while inconsistent 0.5-year bands are observed in East Asia, Middle Africa, and Southeast Asia. In PR, significant power in the wavelet power spectrum at a 1-year period was observed in 17 regions, i.e., in all regions studied except Western Europe, where precipitation is instead characterized by 0.5-year and 0.25-year periods. Overall, the variations in SAT and PR can be consistent with the combined impacts of natural and anthropogenic factors, such as atmospheric concentrations of greenhouse gases, the internal variability of climate system, and volcanic eruptions.

Anthropogenic influence on the changing risk of heat waves over India.

The overarching goal of this paper is to shed light on the human influence on the changing patterns of heat waves in India using the Heat Wave Magnitude Index daily (HWMId). The HWMId obtained from the observational data sets shows a large increase in the heat waves during the past decades. Investigating the effects of natural (e.g., solar variations and volcanic forcings) and anthropogenic (e.g., greenhouse gas emissions, anthropogenic, land use, and land cover) forcings revealed that the anthropogenic factors have cause a two-fold increase in the occurrence probability of severe heat waves in central and mid-southern India during twentieth century. The spatial distribution of maximum HWMId values under natural and all forcings (including anthropogenic) indicates that in most places human activities have increases the frequency, duration and intensity of extreme heat waves. Under the Representative Concentration Pathway (RCP) 4.5, the risk of heat waves is projected to increase tenfold during the twenty-first century. More than ~ 70% of the land areas in India is projected to be influenced by heat waves with magnitudes greater than 9. Furthermore, we find a significant relationship between heat waves and deficits in precipitation. Results show that concurrent heat waves and droughts are projected to increase in most places in India during the twenty-first century.

Global heat stress on health, wildfires, and agricultural crops under different levels of climate warming.

The effects of heat stress are spatially heterogeneous owing to local variations in climate response, population density, and social conditions. Using global climate and impact models from the Inter-Sectoral Impact Model Intercomparison Project, our analysis shows that the frequency and intensity of heat events increase, especially in tropical regions (geographic perspective) and developing countries (national perspective), even with global warming held to the 1.5 °C target. An additional 0.5 °C increase to the 2 °C warming target leads to >15% of global land area becoming exposed to levels of heat stress that affect human health; almost all countries in Europe will be subject to increased fire danger, with the duration of the fire season lasting 3.3 days longer; 106 countries are projected to experience an increase in the wheat production-damage index. Globally, about 38%, 50%, 46%, 36%, and 48% of the increases in exposure to health threats, wildfire, crop heat stress for soybeans, wheat, and maize could be avoided by constraining global warming to 1.5 °C rather than 2 °C. With high emissions, these impacts will continue to intensify over time, extending to almost all countries by the end of the 21st century: >95% of countries will face exposure to health-related heat stress, with India and Brazil ranked highest for integrated heat-stress exposure. The magnitude of the changes in fire season length and wildfire frequency are projected to increase substantially over 74% global land, with particularly strong effects in the United States, Canada, Brazil, China, Australia, and Russia. Our study should help facilitate climate policies that account for international variations in the heat-related threats posed by climate change.

Linkage Between Hourly Precipitation Events and Atmospheric Temperature Changes over China during the Warm Season.

We investigated changes in the temporospatial features of hourly precipitation during the warm season over mainland China. The frequency and amount of hourly precipitation displayed latitudinal zonation, especially for light and moderate precipitation, which showed successive downward change over time in northeastern and southern China. Changes in the precipitation amount resulted mainly from changes in frequency rather than changes in intensity. We also evaluated the linkage between hourly precipitation and temperature variations and found that hourly precipitation extreme was more sensitive to temperature than other categories of precipitation. A strong dependency of hourly precipitation on temperature occurred at temperatures colder than the median daily temperature; in such cases, regression slopes were greater than the Clausius-Clapeyron (C-C) relation of 7% per degree Celsius. Regression slopes for 31.6%, 59.8%, 96.9%, and 99.1% of all stations were greater than 7% per degree Celsius for the 75th, 90th, 99th, and 99.9th percentiles for precipitation, respectively. The mean regression slopes within the 99.9th percentile of precipitation were three times the C-C rate. Hourly precipitation showed a strong negative relationship with daily maximum temperature and the diurnal temperature range at most stations, whereas the equivalent correlation for daily minimum temperature was weak.