Changes in Daily Climate Extremes of Observed Temperature and Precipitation in China

2013 ◽  
Vol 6 (5) ◽  
pp. 312-319 ◽  
Author(s):  
Wang Ai-Hui ◽  
Fu Jian-Jian
2017 ◽  
Vol 56 (9) ◽  
pp. 2393-2409 ◽  
Author(s):  
Rick Lader ◽  
John E. Walsh ◽  
Uma S. Bhatt ◽  
Peter A. Bieniek

AbstractClimate change is expected to alter the frequencies and intensities of at least some types of extreme events. Although Alaska is already experiencing an amplified response to climate change, studies of extreme event occurrences have lagged those for other regions. Forced migration due to coastal erosion, failing infrastructure on thawing permafrost, more severe wildfire seasons, altered ocean chemistry, and an ever-shrinking season for snow and ice are among the most devastating effects, many of which are related to extreme climate events. This study uses regional dynamical downscaling with the Weather Research and Forecasting (WRF) Model to investigate projected twenty-first-century changes of daily maximum temperature, minimum temperature, and precipitation over Alaska. The forcing data used for the downscaling simulations include the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; 1981–2010), Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), historical (1976–2005), and GFDL CM3 representative concentration pathway 8.5 (RCP8.5; 2006–2100). Observed trends of temperature and sea ice coverage in the Arctic are large, and the present trajectory of global emissions makes a continuation of these trends plausible. The future scenario is bias adjusted using a quantile-mapping procedure. Results indicate an asymmetric warming of climate extremes; namely, cold extremes rise fastest, and the greatest changes occur in winter. Maximum 1- and 5-day precipitation amounts are projected to increase by 53% and 50%, which is larger than the corresponding increases for the contiguous United States. When compared with the historical period, the shifts in temperature and precipitation indicate unprecedented heat and rainfall across Alaska during this century.


2021 ◽  
Author(s):  
Firdos Khan ◽  
Shaukat Ali ◽  
Christoph Mayer ◽  
Hamd Ullah ◽  
Sher Muhammad

Abstract This study investigates contemporary climate change and spatio-temporal analysis of climate extremes in Pakistan (divided into five homogenous climate zones) using observed data, categorized between 1962–1990 and 1991–2019. The results show that on the average, the changes in temperature and precipitation are significant at 5 % significance level throughout Pakistan in most of the seasons. The spatio-temporal trend analysis of consecutive dry days (CDD) shows an increasing trend during 1991–2019 except in zone 4 indicating throughout decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days) and R25mm (extremely heavy precipitation days) are significantly decreasing (increasing) during 1962–1990 (1991–2019) in North Pakistan. Summer days (SU25) increased across the country, except in zone 4 with a decrease. TX10p (Cool days) decreased across the country except an increase in zone 1 and zone 2 during 1962–1990. TX90p (Warm days) has an increasing trend during 1991–2019 except zone 5 and decreasing trend during 1962–1990 except zone 2 and 5. The Mann-Kendal test indicates increasing precipitation (DJF) and decreasing maximum and minimum temperature (JJA) in the Karakoram region during 1962–1990. The decadal analysis suggests decreasing precipitation during 1991–2019 and increasing temperature (maximum and minimum) during 2010–2019 which is in line with the recently confirmed slight mass loss of glaciers against Karakoram Anomaly.


2021 ◽  
pp. 5-16
Author(s):  
V. N. Kryjov ◽  

The 2019/2020 wintertime (December–March) anomalies of sea level pressure, temperature, and precipitation are analyzed. The contribution of the 40-year linear trend in these parameters associated with global climate change and of the interannual variability associated with the Arctic Oscillation (AO) is assessed. In the 2019/2020 winter, extreme zonal circulation was observed. The mean wintertime AO index was 2.20, which ranked two for the whole observation period (started in the early 20th century) and was outperformed only by the wintertime index of 1988/1989. It is shown that the main contribution to the 2019/2020 wintertime anomalies was provided by the AO. A noticeable contribution of the trend was observed only in the Arctic. Extreme anomalies over Northern Eurasia were mainly associated with the AO rather than the trend. However, the AO-related anomalies, particularly air temperature anomalies, were developing against the background of the trend-induced increased mean level.


Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 675 ◽  
Author(s):  
Almazroui

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.


2016 ◽  
Vol 55 (5) ◽  
pp. 1169-1182 ◽  
Author(s):  
Lei Wang ◽  
Zhi-Jun Yao ◽  
Li-Guang Jiang ◽  
Rui Wang ◽  
Shan-Shan Wu ◽  
...  

AbstractThe spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. A decreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7–11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2535
Author(s):  
Jintao Zhang ◽  
Fang Wang

Limiting the global temperature increase to a level that would prevent “dangerous anthropogenic interference with the climate system” is the focus of intergovernmental climate negotiations, and the cost-benefit analysis to determine this level requires an understanding of how the risk associated with climate extremes varies with different warming levels. We examine daily extreme temperature and precipitation variances with continuous global warming using a non-stationary extreme value statistical model based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results show the probability of extreme warm and heavy precipitation events over East Asia (EA) will increase, while that of cold extremes over EA will decrease as global warming increases. A present-day 1-in-20-year heavy precipitation extreme in EA is projected to increase to 1.3, 1.6, 2.5, and 3.4 times more frequently of the current climatology, at the global mean warming levels of 1.5 °C, 2 °C, 3 °C, and 4 °C above the preindustrial era, respectively. Moreover, the relative changes in probability are larger for rarer events. These results contribute to an improved understanding of the future risk associated with climate extremes, which helps scientists create mitigation measures for global warming and facilitates policy-making.


2011 ◽  
Vol 15 (24) ◽  
pp. 1-36 ◽  
Author(s):  
Sarah E. Perkins

Abstract Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081–2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in-20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.


Climate ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 40
Author(s):  
Gabriela V. Müller ◽  
Miguel A. Lovino ◽  
Leandro C. Sgroi

The core crop region of the Humid Pampa is one of the most productive agricultural lands around the world and depends highly on climate conditions. This study assesses climate variability, climate extremes, and observed and projected climate changes there, using 1911–2019 observations and CMIP5 model simulations. Since 1970, the annual mean temperature has risen by 1 °C and the mean annual minimum and maximum temperatures by 2 and 0.5 °C, respectively. The frequency of warm days and nights increased, and cold days and nights decreased. Heatwaves became longer and more intense, and cold waves decreased with less frost events. Annual precipitation increased by 10% from 1911, mainly in summer, and years with excess precipitation outnumbered those with a deficit. Both intense precipitation events and consecutive dry days grew, suggesting more annual precipitation falling on fewer days. Projections show a warming of 1 °C by 2035, regardless of the scenario. From then on until 2100, mean temperature will increase by 2 and 3–3.5 °C in the RCP4.5 and RCP8.5 scenarios, respectively. Annual precipitation will grow 8 and 16% from current values by 2100 in the RCP4.5 and RCP8.5 scenarios, respectively. No major precipitation changes are projected in the RCP2.6 scenario.


2015 ◽  
Vol 12 (22) ◽  
pp. 18389-18423 ◽  
Author(s):  
J. F. Siegmund ◽  
M. Wiedermann ◽  
J. F. Donges ◽  
R. V. Donner

Abstract. Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions are known to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. In this study, we systematically quantify simultaneities between meteorological extremes and the timing of flowering of four shrub species across Germany by means of event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences. Our systematic investigation supports previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of wildlife plants. In addition, we find statistically significant indications for some long-term relations reaching back to the previous year.


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