The peak structure and future changes of the relationships between extreme precipitation and temperature

2017 ◽  
Vol 7 (4) ◽  
pp. 268-274 ◽  
Author(s):  
Guiling Wang ◽  
Dagang Wang ◽  
Kevin E. Trenberth ◽  
Amir Erfanian ◽  
Miao Yu ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Peak Structure ◽  
Precipitation And Temperature

Evaluation of the relationship between daily extreme precipitation and temperature over Eastern China

2020 ◽  
Author(s):  
Rui Wang
Keyword(s):  
Surface Temperature ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Precipitable Water ◽  
Precipitation Intensity ◽  
Dew Point ◽  
Near Surface ◽  
Dew Point Temperature ◽  
The Relationship ◽  
Precipitation And Temperature

<p>    In this work, the relationship between daily extreme precipitation and temperature is investigated by using rain gauge precipitation data and corresponding the Integrated Global Radiosonde Archive over eastern China during 1998-2012. Eventually, 14 stations are selected to explore the relationship in eastern China (MEC) and southeastern China (SEC). The result shows that daily extreme precipitation intensity increases approximately 7% when near surface temperature increases 1 °C in MEC and SEC, which generally follows Clausius–Clapeyron (CC) rate (CC rate describes the increasing rate of water vapor with temperature). Moreover, the regression slopes for the logarithmic daily extreme precipitation intensity and near surface temperature range from 3% °C<sup>-1</sup> to 9% °C<sup>-1</sup> at the selected stations in MEC and SEC. However, extreme precipitation intensity decreases with near surface temperature when the temperature is higher than 25 °C. That is, the increase of extreme precipitation with near surface temperature performances single peak structure in MEC and SEC. The variation of extreme precipitation and near surface dew point temperature shows the similar pattern in MEC and SEC (The transition dew point temperature is also about 25 °C). Therefore, <strong>it could be deduced that extreme precipitation intensity does not always increase with climate warming in MEC and SEC.</strong> In addition, precipitable water, which corresponds to extreme precipitation event, increases with near surface temperature at CC rate. <strong>It is found that the increase rate of precipitable water with temperature is closer to CC rate than that of extreme precipitation.</strong></p>

Extreme Precipitation and Temperature over the U.S. Pacific Northwest: A Comparison between Observations, Reanalysis Data, and Regional Models*

2011 ◽  
Vol 24 (7) ◽  
pp. 1950-1964 ◽  
Author(s):  
Valérie Dulière ◽  
Yongxin Zhang ◽  
Eric P. Salathé
Keyword(s):  
Pacific Northwest ◽  
Extreme Precipitation ◽  
Global Climate Model ◽  
Extreme Temperature ◽  
Reanalysis Data ◽  
Grid Spacing ◽  
Regional Models ◽  
Temperature Indices ◽  
The U.S ◽  
Precipitation And Temperature

Abstract Extreme precipitation and temperature indices in reanalysis data and regional climate models are compared to station observations. The regional models represent most indices of extreme temperature well. For extreme precipitation, finer grid spacing considerably improves the match to observations. Three regional models, the Weather Research and Forecasting (WRF) at 12- and 36-km grid spacing and the Hadley Centre Regional Model (HadRM) at 25-km grid spacing, are forced with global reanalysis fields over the U.S. Pacific Northwest during 2003–07. The reanalysis data represent the timing of rain-bearing storms over the Pacific Northwest well; however, the reanalysis has the worst performance at simulating both extreme precipitation indices and extreme temperature indices when compared to the WRF and HadRM simulations. These results suggest that the reanalysis data and, by extension, global climate model simulations are not sufficient for examining local extreme precipitations and temperatures owing to their coarse resolutions. Nevertheless, the large-scale forcing is adequately represented by the reanalysis so that regional models may simulate the terrain interactions and mesoscale processes that generate the observed local extremes and frequencies of extreme temperature and precipitation.

A relation between extreme precipitation and surface air temperature over Russia in the last four decades

2021 ◽  
Author(s):  
Maria Aleshina ◽  
Vladimir Semenov ◽  
Alexander Chernokulsky
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Extreme Precipitation ◽  
Surface Air Temperature ◽  
Precipitation Extremes ◽  
Convective Precipitation ◽  
Temperature Range ◽  
Precipitation Temperature ◽  
Moisture Availability ◽  
Precipitation And Temperature

<p>Precipitation extremes are widely thought to intensify with the global warming due to exponential growth, following the Clausius-Clapeyron (C-C) equation of atmosphere water holding capacity with rising temperatures. However, a number of recent studies based on station and reanalysis data for the contemporary period showed that scaling rates between extreme precipitation and temperature are strongly dependent on temperature range, region and moisture availability. Here, we examine the scaling between daily precipitation extremes and surface air temperature over Russian territory for the last four decades using meteorological stations data and ERA-Interim reanalysis. The precipitation-temperature relation is examined for total precipitation amount and, separately, for convective and large-scale precipitation types. In winter, a general increase of extreme precipitation of all types according to C-C relation is revealed. For the Russian Far East region, the stratiform precipitation extremes scale with surface air temperature following even super C-C rates, about two times as fast as C-C. However, in summer we find a peak-like structure of the precipitation-temperature scaling, especially for the convective precipitation in the southern regions of the country. Being consistent with the C-C relationship, extreme precipitation peaks at the temperature range between 15 °C and 20 °C. For the higher temperatures, the negative scaling prevails. Furthermore, it was shown that relative humidity in general decreases with growing temperature in summer. Notably, there appears to be a temperature threshold in the 15-20 °C range, beyond that relative humidity begins to decline more rapidly. This indicates that moisture availability can be the major factor for the peak-shaped relationship between extreme precipitation and temperature revealed by our analysis.</p>

Spatio-temporal variation of extreme indices derived from observed and reanalysis products for detection of climate change across India

2020 ◽  
Author(s):  
Sachidanand Kumar ◽  
Kironmala Chanda ◽  
Srinivas Pasupuleti
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Spatio Temporal ◽  
Precipitation And Temperature

<p><strong>Abstract</strong></p><p>This article reports the research findings in a recent study (Kumar et al., 2020) that utilizes eight indices of climate change recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) for analyzing spatio-temporal trends in extreme precipitation and temperature at the daily scale across India. Observed gridded precipitation (1971-2017) and temperature (1971-2013) datasets from India Meteorological Department (IMD) are used along with reanalysis products from Climate Prediction Centre (CPC). The trends are estimated using non-parametric Mann-Kendall (MK) test and regression analysis. The trends in ‘wet days’ (daily precipitation greater than 95<sup>th</sup> percentile) and ‘dry days’ (daily precipitation lower than 5<sup>th</sup> percentile) are examined considering the entire year (annual) as well as monsoon months only (seasonal). At the annual scale, about 13% of the grid locations indicated significant trend (either increasing or decreasing at 5% significance level) in the index R95p (rainfall contribution from extreme ‘wet days’) while 20% of the locations indicated significant trend in R5p (rainfall contribution from extreme ‘dry days’). For the seasonal analysis (June to September), the corresponding figures are nil and 21% respectively. The spatio-temporal trends in ‘warm days’ (daily maximum temperature greater than 95<sup>th</sup> percentile), ‘warm nights’ (daily minimum temperature greater than 95<sup>th</sup> percentile), ‘cold days’ (daily maximum temperature lower than 5<sup>th</sup> percentile) and ‘cold nights’ (daily minimum temperature lower than 5<sup>th</sup> percentile) are also investigated for the aforementioned period. The number of ‘warm days’ per year increased significantly at 14% of the locations, while the number of ‘cold days’, ‘warm nights’ and ‘cold nights’ per year decreased significantly at several (42%, 34% and 39%) of the locations. The extreme temperature indices are also investigated for the future using CanESM2 projected data for RCP8.5 after suitable bias correction. Most of the locations (49% to 84%) indicate significant increasing (decreasing) trend in ‘warm days’ (‘cold days’) in the three epochs, 2006-2040, 2041-2070 and 2071-2100. Moreover, most locations (60% to 81%) show an increasing trend in ‘warm nights’ and a decreasing trend in ‘cold nights’ in all the epochs. A similar investigation for the historical and future periods using CPC data as the reference indicates that the trends, on comparison with IMD observations, seem to be in agreement for temperature extremes but spatially more extensive in case of CPC precipitation extremes.</p><p><strong>Keywords: extreme precipitation and temperature, climate change indices, spatio-temporal variation, India</strong></p><p><strong>References:</strong></p><p>Kumar S., Chanda, K., Srinivas P., (2020), Spatiotemporal analysis of extreme indices derived from daily precipitation and temperature for climate change detection over India, Theoretical and Applied Climatology, Springer, In press, DOI: 10.1007/s00704-020-03088-5.</p>

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