Variability of Temperature Extremes in Northwest Himalayas during Early 21st Century.

2021 ◽  
Author(s):  
Farhan Aziz ◽  
Nadeem Tariq ◽  
Akif Rahim ◽  
Ambreen Mahmood
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Extreme Temperature ◽  
Northern Region ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Early 21St Century ◽  
Northwest Himalayas

<p>In recent years, extreme events and their severe damage have become more common around the world. It is widely known that atmospheric greenhouse gases have contributed to global warming. <br>A set of appropriate indicators describing the extremes of climate change can be used to study the extent of climate change. This study reveals the trends of temperature extreme indices on the spatial scale in the western part of Northwest Himalayas. The study is conducted at 13 climate stations lies at a different altitude of the study area.The Daily maximum and minimum temperature data during 2000--2018 of stations obtained from the Pakistan Meteorological Department (PMD) and Water and Power Development Authority (WAPDA). The 12 extreme temperature indices (FD, SU, TXx , TXn., TNx, TNn, TN10p , TN90p, TX10p , TX90p, CSDI, WSDI) recommended by ETCCDI (Expert Team on Climate Change Detection and Indices) are used to study the variabilities in temperature extremes. These indices are characterized based on amplitude, persistence, and frequency. The analysis is performed by using R package of extremes “RClimDEX”. The analysis shows the frequency of summer days (Su) and warm spells (WSDI) have increasing trends in the Southwest region, whereas the frequency of cold spells and frost days have decreasing trends observed in the Northern region of the study areas. The maximum and minimum values of daily maximum temperature (TXX, TXN) increase in the foothill area of the region and decreasing trends in the high elevation region. The day and night get cool in the Northwest region, whereas the days and nights are showing warmer trends in low elevation regions of the study area. Overall, the study concludes that the Northwestern parts have cool trends while South West and South eastern parts have warm trends during the early 21st century.</p><p><strong>Key words:</strong>  Temperature Extremes, Northwest Himalayas, Trends, R-Climdex, Climate Change</p>

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

Indices for daily temperature and precipitation based on quality controlled and homogenized data in Madagascar

2020 ◽  
Author(s):  
Luc Yannick Andréas Randriamarolaza ◽  
Enric Aguilar ◽  
Oleg Skrynyk
Keyword(s):  
Climate Change ◽  
Missing Data ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Indices ◽  
Low Density ◽  
Climate Data ◽  
Temperature And Precipitation

<p>Madagascar is an Island in Western Indian Ocean Region. It is mainly exposed to the easterly trade winds and has a rugged topography, which promote different local climates and biodiversity. Climate change inflicts a challenge on Madagascar socio-economic activities. However, Madagascar has low density station and sparse networks on observational weather stations to detect changes in climate. On average, one station covers more than 20 000 km<sup>2</sup> and closer neighbor stations are less correlated. Previous studies have demonstrated the changes on Madagascar climate, but this paper contributes and enhances the approach to assess the quality control and homogeneity of Madagascar daily climate data before developing climate indices over 1950 – 2018 on 28 synoptic stations. Daily climate data of minimum and maximum temperature and precipitation are exploited.</p><p>Firstly, the quality of daily climate data is controlled by INQC developed and maintained by Center for Climate Change (C3) of Rovira i Virgili University, Spain. It ascertains and improves error detections by using six flag categories. Most errors detected are due to digitalization and measurement.</p><p>Secondly, daily quality controlled data are homogenized by using CLIMATOL. It uses relative homogenization methods, chooses candidate reference series automatically and infills the missing data in the original data. It has ability to manage low density stations and low inter-station correlations and is tolerable for missing data. Monthly break points are detected by CLIMATOL and used to split daily climate data to be homogenized.</p><p>Finally, climate indices are calculated by using CLIMIND package which is developed by INDECIS<sup>*</sup> project. Compared to previous works done, data period is updated to 10 years before and after and 15 new climate indices mostly related to extremes are computed. On temperature, significant increasing and decreasing decade trends of day-to-day and extreme temperature ranges are important in western and eastern areas respectively. On average decade trends of temperature extremes, significant increasing of daily minimum temperature is greater than daily maximum temperature. Many stations indicate significant decreasing in very cold nights than significant increasing in very warm days. Their trends are almost 1 day per decade over 1950 – 2018. Warming is mainly felt during nighttime and daytime in Oriental and Occidental parts respectively. In contrast, central uplands are warming all the time but tropical nights do not appear yet. On rainfall, no major significant findings are found but intense precipitation might be possible at central uplands due to shortening of longest wet period and occurrence of heavy precipitation. However, no influence detected on total precipitation which is still decreasing over 1950 - 2018. Future works focus on merging of relative homogenization methodologies to ameliorate the results.</p><p>-------------------</p><p>*INDECIS is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).</p>

scholarly journals Recent trends in daily temperature extremes over northeastern Spain (1960–2006)

2011 ◽  
Vol 11 (9) ◽  
pp. 2583-2603 ◽  
Author(s):  
A. El Kenawy ◽  
J. I. López-Moreno ◽  
S. M. Vicente-Serrano
Keyword(s):  
Land Use Planning ◽  
Crop Yields ◽  
Extreme Temperature ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Growing Season Length ◽  
Cold Extremes

Abstract. Spatial and temporal characteristics of extreme temperature events in northeastern Spain have been investigated. The analysis is based on long-term, high-quality, and homogenous daily maximum and minimum temperature of 128 observatories spanning the period from 1960 to 2006. A total of 21 indices were used to assess changes in both the cold and hot tails of the daily temperature distributions. The presence of trends in temperature extremes was assessed by means of the Mann-Kendall test. However, the autocorrelation function (ACF) and a bootstrap methodology were used to account for the influence of serial correlation and cross-correlation on the trend assessment. In general, the observed changes are more prevalent in hot extremes than in cold extremes. This finding can largely be linked to the increase found in the mean maximum temperature during the last few decades. The results indicate a significant increase in the frequency and intensity of most of the hot temperature extremes. An increase in warm nights (TN90p: 3.3 days decade−1), warm days (TX90p: 2.7 days decade−1), tropical nights (TR20: 0.6 days decade−1) and the annual high maximum temperature (TXx: 0.27 °C decade−1) was detected in the 47-yr period. In contrast, most of the indices related to cold temperature extremes (e.g. cold days (TX10p), cold nights (TN10p), very cold days (TN1p), and frost days (FD0)) demonstrated a decreasing but statistically insignificant trend. Although there is no evidence of a long-term trend in cold extremes, significant interdecadal variations were noted. Almost no significant trends in temperature variability indices (e.g. diurnal temperature range (DTR) and growing season length (GSL)) are detected. Spatially, the coastal areas along the Mediterranean Sea and the Cantabrian Sea experienced stronger warming compared with mainland areas. Given that only few earlier studies analyzed observed changes in temperature extremes at fine spatial resolution across the Iberian Peninsula, the results of this work can improve our understanding of climatology of temperature extremes. Also, these findings can have different hydrological, ecological and agricultural implications (e.g. crop yields, energy consumption, land use planning and water resources management).

scholarly journals A Statistical Adjustment of Regional Climate Model Outputs to Local Scales: Application to Platja de Palma, Spain

2012 ◽  
Vol 25 (3) ◽  
pp. 939-957 ◽  
Author(s):  
A. Amengual ◽  
V. Homar ◽  
R. Romero ◽  
S. Alonso ◽  
C. Ramis
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Climate Projections ◽  
Recent Past

Abstract Projections of climate change effects for the System of Platja de Palma (SPdP) are derived using a novel statistical technique. Socioeconomic activities developed in this settlement are very closely linked to its climate. Any planning for socioeconomic opportunities in the mid- and long term must take into account the possible effects of climate change. To this aim, daily observed series of minimum and maximum temperatures, precipitation, relative humidity, cloud cover, and wind speed have been analyzed. For the climate projections, daily data generated by an ensemble of regional climate models (RCMs) have been used. To properly use RCM data at local scale, a quantile–quantile adjustment has been applied to the simulated regional projections. The method is based on detecting changes in the cumulative distribution functions between the recent past and successive time slices of the simulated climate and applying these, after calibration, to the recent past (observed) series. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs, although the correction does not result in such clear improvement when dealing with very extreme rainfalls. Next, the corrected series are analyzed to quantify the climate change signal. An increase of the annual means for temperatures together with a decrease for the remaining variables is projected throughout the twenty-first century. Increases in weak and intense daily rainfalls and in high extremes for daily maximum temperature can also be expected. With this information at hand, the experts planning the future of SPdP can respond more effectively to the problem of local adaptation to climate change.

scholarly journals A Stepwise-Clustered Simulation Approach for Projecting Future Heat Wave Over Guangdong Province

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiayan Ren ◽  
Guohe Huang ◽  
Yongping Li ◽  
Xiong Zhou ◽  
Jinliang Xu ◽  
...  
Keyword(s):  
Heat Wave ◽  
Climate Models ◽  
Extreme Event ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Simulation Approach

A heat wave is an important meteorological extreme event related to global warming, but little is known about the characteristics of future heat waves in Guangdong. Therefore, a stepwise-clustered simulation approach driven by multiple global climate models (i.e., GCMs) is developed for projecting future heat waves over Guangdong under two representative concentration pathways (RCPs). The temporal-spatial variations of four indicators (i.e., intensity, total intensity, frequency, and the longest duration) of projected heat waves, as well as the potential changes in daily maximum temperature (i.e., Tmax) for future (i.e., 2006–2095) and historical (i.e., 1976–2005) periods, were analyzed over Guangdong. The results indicated that Guangdong would endure a notable increasing annual trend in the projected Tmax (i.e., 0.016–0.03°C per year under RCP4.5 and 0.027–0.057°C per year under RCP8.5). Evaluations of the multiple GCMs and their ensemble suggested that the developed approach performed well, and the model ensemble was superior to any single GCM in capturing the features of heat waves. The spatial patterns and interannual trends displayed that Guangdong would undergo serious heat waves in the future. The variations of intensity, total intensity, frequency, and the longest duration of heat wave are likely to exceed 5.4°C per event, 24°C, 25 days, and 4 days in the 2080s under RCP8.5, respectively. Higher variation of those would concentrate in eastern and southwestern Guangdong. It also presented that severe heat waves with stronger intensity, higher frequency, and longer duration would have significant increasing tendencies over all Guangdong, which are expected to increase at a rate of 0.14, 0.83, and 0.21% per year under RCP8.5, respectively. Over 60% of Guangdong would suffer the moderate variation of heat waves to the end of this century under RCP8.5. The findings can provide decision makers with useful information to help mitigate the potential impacts of heat waves on pivotal regions as well as ecosystems that are sensitive to extreme temperature.

scholarly journals Changes of Extreme Temperature and Its Influencing Factors in Shiyang River Basin, Northwest China

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1171
Author(s):  
Junju Zhou ◽  
Jumei Huang ◽  
Xi Zhao ◽  
Li Lei ◽  
Wei Shi ◽  
...  
Keyword(s):  
Global Warming ◽  
River Basin ◽  
Minimum Temperature ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Extreme Temperatures ◽  
Shiyang River Basin

The increase in the frequency and intensity of extreme weather events around the world has led to the frequent occurrence of global disasters, which have had serious impacts on the society, economic and ecological environment, especially fragile arid areas. Based on the daily maximum temperature and daily minimum temperature data of four meteorological stations in Shiyang River Basin (SRB) from 1960 to 2015, the spatio-temporal variation characteristics of extreme temperature indices were analyzed by means of univariate linear regression analysis, Mann–Kendall test and correlation analysis. The results showed that the extreme temperatures warming indices and the minimum of daily maximum temperature (TXn) and the minimum of daily minimum temperature (TNn) of cold indices showed an increasing trend from 1960 to 2016, especially since the 1990s, where the growth rate was fast and the response to global warming was sensitive. Except TXn and TNn, other cold indices showed a decreasing trend, especially Diurnal temperature (DTR) range, which decreased rapidly, indicating that the increasing speed of daily min-temperature were greater than of daily max-temperature in SRB. In space, the change tendency rate of the warm index basically showed an obvious altitude gradient effect that decreased with the altitude, which was consistent with Frost day (FD0) and Cool nights (TN10p) in the cold index, while Ice days (ID0) and Cool days (TX10p) are opposite. The mutation of the cold indices occurred earlier than the warm indices, illustrating that the cold indices in SRB were more sensitive to global warming. The change in extreme temperatures that would have a significant impact on the vegetation and glacier permafrost in the basin was the result of the combined function of different atmospheric circulation systems, which included the Arctic polar vortex, Western Pacific subtropical high and Qinghai-tibet Plateau circulation.

scholarly journals Improved Bias Correction Techniques for Hydrological Simulations of Climate Change*

2015 ◽  
Vol 16 (6) ◽  
pp. 2421-2442 ◽  
Author(s):  
David W. Pierce ◽  
Daniel R. Cayan ◽  
Edwin P. Maurer ◽  
John T. Abatzoglou ◽  
Katherine C. Hegewisch
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Temperature And Precipitation

Abstract Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models’ simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season’s values at once.

Seasonal analysis of warm extreme events in Serbia from 1949 to 2017

2020 ◽  
Author(s):  
Ivana Tosic ◽  
Suzana Putniković ◽  
Milica Tošić
Keyword(s):  
Extreme Events ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Extreme Temperature Events ◽  
Air Temperatures ◽  
Seasonal Analysis ◽  
Novi Sad

<p>Worldwide studies revealed a general increase in frequency and severity of warm extreme temperature events. In this study, extreme temperature events including Heat waves (HWs) are examined. Extreme indices are calculated based on daily maximum temperature (Tx). The following definitions are employed: SU - number of days with Tx > 25 °C, umber of days with Tx > 90<sup>th</sup> percentile, and WSDI - number of days in intervals of at least six consecutive days for which Tx is higher than the calendar day 90<sup>th</sup> percentile. Daily values of air temperatures from 11 meteorological stations distributed across Serbia were used for the period 1949–2017.</p><p>Trends of extreme temperature events and their frequencies are examined. The period 1949–2017 are characterised by a warming of extreme temperature indices (SU, Tx90, HWs). It is found that maximum air temperatures increased at all stations, but statistically significant at 6 stations in winter, 4 stations in summer and two stations in spring. The average number of SU per station was between 63.1 in Novi Sad to 73.5 in Negotin during the summer season. Significant increase of SU is recorded in summer for 10 out of 11 stations. Positive trends of SU and Tx90 are observed for all stations and seasons, except in Novi Sad. The average number of Tx90 is about 9 for all stations in all seasons. The longest heat waves prevailed in 2012, but the most severe are recorded in 2007. Increasing of warm extreme events in Serbia are in agreement with studies for different regions of the world.</p>

Detection of Anthropogenic Influence on Fixed Threshold Indices of Extreme Temperature

2018 ◽  
Vol 31 (16) ◽  
pp. 6341-6352 ◽  
Author(s):  
Hong Yin ◽  
Ying Sun
Keyword(s):  
Dominant Role ◽  
Extreme Temperature ◽  
Poor Performance ◽  
Internal Variability ◽  
Global Scale ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Anthropogenic Forcing ◽  
Fixed Threshold

Threshold indices of extreme temperature are defined based on temperature values that fall above or below fixed thresholds and thus have important implications for agriculture, engineering, and human health. Here, we focus on four extreme temperature fixed threshold indices and their detection and attribution at the global and continental scales, as well as within China. These indices include the number of days with daily minimum temperatures below 0°C [frost days (FD)] and above 20°C [tropical nights (TR)] and the number of days with daily maximum temperatures below 0°C [ice days (ID)] and above 25°C [summer days (SU)]. We employ an optimal fingerprinting method to compare the spatial and temporal changes in these fixed threshold indices assessed from observations and simulations performed with multiple models. We find that an anthropogenic signal can be robustly detected in these fixed threshold indices at scales of over the globe, most of the continents, and China. A natural signal cannot be identified in the changes in most of the indices, thus indicating the dominant role of anthropogenic forcing in producing these changes. In North and South America, the models show poor performance in reproducing the fixed threshold indices related to daily maximum temperature. The changes in summer days are not clearly related to their responses to external forcing over these two continents. This study provides a useful complement to other detection studies and sheds light on the importance of anthropogenic forcing in determining most of the fixed threshold indices at the global scale and over most of the continents, compared with internal variability.

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