Changes In Extreme Temperature Indices Research Articles

Projection on Antarctic Temperature Extremes from the CMIP6 Multimodel Ensemble under Different Scenarios

Abstract Global warming has been accelerating the frequency and intensity of climate extremes, and has had an immense influence on the economy and society, but attention is seldom paid to future Antarctic temperature extremes. This study investigates five surface extreme temperature indices derived from the multimodel ensemble mean (MMEM) based on 14 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) under the shared socioeconomic pathways (SSPs) of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. In Antarctica, the variations in extreme temperature indices exhibit regional and seasonal differences. The diurnal temperature range (DTR) usually illustrates a downward trend, particularly for the Antarctic Peninsula and Antarctic coast, and the strongest change occurs in austral summer. In all cases, the annual highest minimum/maximum temperature (TNx/TXx) increases faster in inland Antarctica. Antarctic amplification of extreme temperature indices is detected and is strongest at the lowest maximum temperature (TXn). At the Antarctic Peninsula, TXx amplification only appears in winter. Great DTR amplification appears along the Antarctic coast and is strongest in summer and weakest in winter. The changes in extreme temperature indices indicate the accelerated Antarctic warming in future scenarios.

Changes in extreme temperature indices at the Ukrainian Antarctic Akademik Vernadsky station, 1951-2020

Changes in extreme temperature indices at the Ukrainian Antarctic Akademik Vernadsky station, 1951-2020

Extreme temperature indices in Eurasia in a CMIP6 multi‐model ensemble: Evaluation and projection

AbstractIt is important to project the changes in extreme temperature in Eurasia, where more than two‐thirds of the world's population reside. Employing Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations and extreme temperature indices defined by the expert team on climate change detection and Indices, we firstly evaluate the performance of the CMIP6 models, and then project the spatial patterns of changes in extreme temperature in different periods under shared social‐economic Pathway scenarios and at different global warming levels. The results show that the performance of the CMIP6 models in simulating the indices of the coldest day (TXn), the coldest night (TNn), summer days (SU), tropical nights (TR) and frost days (FD) are good. Therefore, these five indices were selected for projection. Overall, TXn, TNn, SU and TR show an increasing trend and FD a decreasing trend, consistent with global warming in the future. The responses to global warming tend to be strongest in high latitudes for TXn and TNn, in high latitudes and high‐altitude areas for FD, and in some low‐latitude areas for SU and TR. At the local scale over Eurasia, where the change is larger than the regional median level, the changes in extreme temperature indices at 1.5°C of global warming above pre‐industrial levels are projected to be reduced by 30–55% and 55–85%, respectively, compared with the situation at 2.0°C and 3.0 warming. If global warming could be controlled to within 2.0°C, the changes in extreme temperature indices over Eurasia would be reduced by up to 60% compared with the situation at 3.0°C warming. Therefore, if global warming can be controlled to within a low warming target, the risk of extreme temperature change will be greatly reduced in these regions.

Future changes in temperature extremes in climate variability over Iran

AbstractThe objective of the current study was to project changes in extreme temperature indices over Iran by the end of the 21st Century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. We used six extreme temperature indices recommended and defined by the Expert Team on Climate Change Detection and Indices from a set of 18 CMIP5 model simulations from different modelling centres. The extreme temperature indices simulation results of the models were compared with the gridded extreme temperature indices observations of the Asfazari National Database with a spatial resolution of 15 × 15 km during the period 1962–2005. For comparison purposes, the CMIP5 model data and the Asfazari data were regridded to a uniform horizontal resolution 0.5° × 0.5° grid using a bilinear interpolation scheme before further processing. After first validating the model performance by computing bias, future changes in the period 2006–2100 were projected. The modified Mann Kendall trend test and the Sen slope estimator test were used for evaluating the trend of indices and estimating the change rate, respectively, at a 95% confidence level. The results show that the minimum of the daily minimum temperature (TNn) and the minimum of the daily maximum temperature (TXn) will increase in the future. Warming of night time temperature indices (TNn and TN90p) are projected to be stronger than those of daytime temperature indices (TXn and TX90p). Warming is not uniform across the country, with considerably more warming in the western and southern parts. In terms of the frequency of frost days, a decrease is generally projected in the 21st Century. The largest decrease is projected for the Zagros mountain ranges in the west and the mountainous region in the northeastern part of the country with a magnitude of around 8–10 days⋅decade−1. The number of heat wave days is expected to increase sharply from about 13 days in the reference period (1963–2005) to 100 days by mid‐century to more than 235 days by the end of the century under Representative Concentration Pathway 8.5.

Observed trends in daily temperature extreme indices in Aguascalientes, Mexico

Climate change is a pernicious and irrefutable reality. The objective of this work was to analyze trends in extreme temperature indices in Aguascalientes. With RClimdex 1.0 and data on daily maximum (Tmax) and minimum temperature (Tmin), 16 temperature indices were calculated. The trend in indices was determined with the non-parametric Mann-Kendall test (p ≤ 0.05), while the rate of change was obtained with Theil-Sen’s trend estimator. Significant positive trends were observed in 72 time series of indices associated with Tmax and in 39 time series of indices associated with Tmin. Significant negative trends were observed in 22 time series of indices associated with Tmax, and in 45 time series of indices associated with Tmin. In some regions of Aguascalientes, diurnal warming is occurring; in others, warmer or less cold nights prevail. The changes in extreme temperature indices might have severe implications in the use of irrigation water, cause physiological stress in crops, promote respiratory and cardiac diseases, and improve the reproduction cycles and populations of insects. Also, the fruit production, such as guava, could be affected under the reduction of minimum temperature, and the increase in warm days where other fruit trees are cultivated can intensify the use of chemical compensators of cold. These results are of significance for long-term economic planning and design of strategies of adaptation/mitigation to climate change. In Aguascalientes, the changes observed in extreme temperature indices could be due to climate change of a bigger scale, either regional or at the watershed level.

Observed Changes in Temperature and Precipitation Extremes Over the Yarlung Tsangpo River Basin during 1970–2017

Twenty-five climate indices based on daily maximum and minimum temperature and precipitation at 15 meteorological stations were examined to investigate changes in temperature and precipitation extremes over the Yarlung Tsangpo River Basin (1970–2017). The trend-free prewhitening (TFPW) Mann–Kendall test and Pettitt’s test were used to identify trends and abrupt changes in the time series, respectively. The results showed widespread significant changes in extreme temperature indices associated with warming, most of which experienced abrupt changes in the 1990s. Increases in daily minimum and maximum temperature were detected, and the magnitude of daily minimum temperature change was greater than that of the daily maximum temperature, revealing an obvious decrease in the diurnal temperature range. Warm days and nights became more frequent, whereas fewer cold days and nights occurred. The frequency of frost and icing days decreased, while summer days and growing season length increased. Moreover, cold spell length shortened, whereas warm spell length increased. Additionally, changes in the precipitation extreme indices exhibited much less spatial coherence than the temperature indices. Spatially, mixed patterns of stations with positive and negative trends were found, and few trends in the precipitation extreme indices at individual stations were statistically significant. Generally, precipitation extreme indices showed a tendency toward wetter conditions, and the contribution of extreme precipitation to total precipitation has increased. However, no significant regional trends and abrupt changes were detected in total precipitation or in the frequency and duration of precipitation extremes.

Changes in extreme temperature indices over the Peripannonian region of Bosnia and Herzegovina

The paper analyzes changes in extreme temperature indices over the Peripannonian region of Bosnia and Herzegovina. Data on daily minimum and maximum temperatures during the period 1961–2016 from four meteorological stations were used for the calculation in the RClimDex (1.0) sopware trends in 16 indices recommended by the Expert team on climate change detection and indices. The estimated significant upward tendency in indices of warm extremes and downward in cold-related indices confirm that warming is present. The highest trend values were obtained for indices TXx, TNn, TN90p, TX90p, SU25, SU30 and WSDI. The results indicate significant distributional changes in the period 1987−2016 compared to the period 1961−1990. A significant positive (negative) correlation between the East-Atlantic pattern and indices of warm (cold) extremes was determined throughout the year. In winter and spring, significant links to the North Atlantic Oscillation and the Arctic Oscillation, respectively, were also found.

Observed changes in temperature extremes for the Beijing–Tianjin–Hebei region of China

ABSTRACTAs one of the most significant threats facing the world, climate change has already been manifested everywhere in the form of frequent extreme climate events (e.g. heat waves, floods, droughts and wildfires) and has caused serious impacts on all aspects of the living environment. Due to the regional variability of global climate change, understanding the ongoing climatic changes at a local scale is very important for decision makers and resource managers to develop appropriate mitigation and adaptation strategies against the changing climate. In this study, recent changes in extreme temperature indices (including frost days, summer days, icy days, tropical nights, growing season length, cool nights and warm nights, cool days and warm days, and daily temperature range) over the Beijing–Tianjin–Hebei (BTH) region of China were investigated in the context of global warming. The results indicate that the historical trends of these extreme temperature indices are statistically significant in Huailai, Beijing, Leting and Shijiazhuang while no significant trends are reported in Chengde, Tianjin and Cangzhou−Potou. By comparing results between coastal and inland stations, it is found that the changes in temperature extremes in inland stations are less significant than the changes in coastal stations. The results also suggest that the indices based on minimum temperature show decreasing trends while those for maximum temperature present increasing trends. Furthermore, mutation tests were performed for all indices in order to understand when the changes were initiated. An apparent mutation point (mostly in the 1980s) is detected for most of the analysed temperature indices. This may be caused by the wide implementation of the reform and opening policy in the early 1980s to boost economic development in the BTH region.

Robustness of climate change signals in near term predictions up to the year 2030: Changes in the frequency of temperature extremes

[1] This is the first study to examine whether human contributions to changes in extreme temperature indices have larger amplitudes than natural variability in near future (up to 2030) climate prediction. We performed 10 runs of the initial condition perturbed ensemble of a coupled atmosphere-ocean general circulation model. In the near future, over most land areas, all 10 runs predict more frequent occurrences of warm nights and warm days, and less frequent cold nights and cold days, suggesting that human influences have become larger than natural variability. The fraction of areas where all runs agree on the direction of changes over land is less sensitive to ensemble sizes (for warm nights, 96% and 93% for 4 runs and 10 runs, respectively). The changes in the frequency of warm and cold extremes are mainly due to shifts in seasonal mean temperatures. Additionally snow cover affects the frequency of cold extremes in some areas.