scholarly journals Neonates in Ahmedabad, India, during the 2010 Heat Wave: A Climate Change Adaptation Study

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Khyati Kakkad ◽  
Michelle L. Barzaga ◽  
Sylvan Wallenstein ◽  
Gulrez Shah Azhar ◽  
Perry E. Sheffield
Keyword(s):  
Climate Change ◽  
Heat Wave ◽  
Climate Change Adaptation ◽  
Vulnerable Populations ◽  
Urban Areas ◽  
Neonatal Morbidity ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Maternity Ward

Health effects from climate change are an international concern with urban areas at particular risk due to urban heat island effects. The burden of disease on vulnerable populations in non-climate-controlled settings has not been well studied. This study compared neonatal morbidity in a non-air-conditioned hospital during the 2010 heat wave in Ahmedabad to morbidity in the prior and subsequent years. The outcome of interest was neonatal intensive care unit (NICU) admissions for heat. During the months of April, May, and June of 2010, 24 NICU admissions were for heat versus 8 and 4 in 2009 and 2011, respectively. Both the effect of moving the maternity ward and the effect of high temperatures were statistically significant, controlling for each other. Above 42 degrees Celsius, each daily maximum temperature increase of a degree was associated with 43% increase in heat-related admissions (95% CI 9.2–88%). Lower floor location of the maternity ward within hospital which occurred after the 2010 heat wave showed a protective effect. These findings demonstrate the importance of simple surveillance measures in motivating a hospital policy change for climate change adaptation—here relocating one ward—and the potential increasing health burden of heat in non-climate-controlled institutions on vulnerable populations.

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>

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.

Analysis of the extreme heat events in Iran

2017 ◽  
Vol 9 (4) ◽  
pp. 418-432 ◽  
Author(s):  
Hojjatollah Yazdanpanah ◽  
Josef Eitzinger ◽  
Marina Baldi
Keyword(s):  
Trend Analysis ◽  
Heat Wave ◽  
Heat Waves ◽  
Temporal Variations ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Positive Trend ◽  
Content Type ◽  
Hot Days

Purpose The purpose of this paper is to assess the spatial and temporal variations of extreme hot days (H*) and heat wave frequencies across Iran. Design/methodology/approach The authors used daily maximum temperature (Tmax) data of 27 synoptic stations in Iran. These data were standardized using the mean and the standard deviation of each day of the year. An extreme hot day was defined when the Z score of daily maximum temperature of that day was equal or more than a given threshold fixed at 1.7, while a heat wave event was considered to occur when the Z score exceeds the threshold for at least three continuous days. According to these criteria, the annual frequency of extreme hot days and the number of heat waves were determined for all stations. Findings The trend analysis of H* shows a positive trend during the past two decades in Iran, with the maximum number of H* (110 cases) observed in 2010. A significant trend of the number of heat waves per year was also detected during 1991-2013 in all the stations. Overall, results indicate that Iran has experienced heat waves in recent years more often than its long-term average. There will be more frequent and intense hot days and heat waves across Iran until 2050, due to estimated increase of mean air temperature between 0.5-1.1 and 0.8-1.6 degree centigrade for Rcp2.6 and Rcp8.8 scenarios, respectively. Originality/value The trend analysis of hot days and heat wave frequencies is a particularly original aspect of this paper. It is very important for policy- and decision-makers especially in agriculture and health sectors of Iran to make some adaptation strategies for future frequent and intense hot days over Iran.

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.

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 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.

Model evaluation for Heatwaves over South Korea in CMIP6 models

2020 ◽  
Author(s):  
Ji-Seon Oh ◽  
Maeng-Ki Kim ◽  
Dae-Geun Yu ◽  
Jeong Sang
Keyword(s):  
Heat Wave ◽  
Development Program ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Northwestern Pacific ◽  
Circulation Index ◽  
Convective Activity ◽  
Simulation Performance ◽  
Diagnostic Indices

<p>In this study, we defined diagnostic indices to evaluate the CMIP6 models based on the heatwaves mechanisms of Korea presented in previous studies. Based on this, the simulation performance of the model was quantitatively evaluated using Relative Error (RE), Inter-annual Variability Skill-score (IVS), and Correlation Coefficient (CC). The REs in diagnostic indices are still large, especially in heat wave circulation index (HWCI) and Indian summer monsoon rainfall index (IMRI), which is mainly due to weak convective activity bias over the northwestern Pacific Ocean and the northwestern India. However, the IVSs in diagnostic indices have been improved overall in the CMIP6 compared to the CMIP5, especially in the IMRI. The CC between the daily maximum temperature (TMAX) and the diagnostic factors in the model is very higher in HWCI than other indices, indicating that the convective activity over the northwestern Pacific is very important in heat wave in Korea. As a result, the total ranking of the model performance for heatwaves in Korea suggested that EC-Earth3-Veg, EC-Earth3, and UKESM-1-0-LL ranked high in CMIP6.</p><p> </p><p>This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI(KMI2018-03410)</p>

scholarly journals Trends in Extreme Climate Indices in Cherrapunji for the period 1979 to 2020

2021 ◽  
Author(s):  
Raju Kalita ◽  
Dipangkar Kalita ◽  
Atul Saxena
Keyword(s):  
Climate Change ◽  
Negative Trend ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Trend Test ◽  
Climate Indices ◽  
Daily Maximum ◽  
Positive Trend ◽  
Extreme Climate

Abstract We have used Mann-Kendall trend test and Sen’s slope estimator method to find out significant changes in extreme climate indices for daily temperature as well as precipitation over the period 1979 to 2020 in Cherrapunji. In the present study, a total of 24 precipitation and temperature based extreme climate indices were calculated using RClimDex v 1.9-3. Among 24 indices, 7 were derived from number of days above nn mm rainfall (Rnn) according to Indian Meteorological Department (IMD) convention and the rest were in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). It was observed that, among all the indices, consecutive dry days (CDD), summer days (SU25) and very light rainfall (VLR) days increased significantly with 0.54, 1.58 and 0.14 days/year respectively, while only consecutive wet days (CWD) decreased significantly with 0.36 days/year. A slight negative trend was also observed in case of tropical nights (TR20) and among the other precipitation indices as well. Again, the indices associated with daily maximum temperature increased significantly with annual change of 0.06 to 0.07 ⁰C/year. And for indices associated with daily minimum temperature, almost no change or a slight negative change was observed, except a significant positive trend in February and significant negative trend in November for TNN only. The analysis reveals that some of the extreme climate indices which explains the climatic conditions of Cherrapunji has changed a lot over the period of 42 years and if this trend continues then Cherrapunji will be under threat when it comes to climate change.

scholarly journals Evaluation the WRF Model with Different Land Surface Schemes: Heat Wave Event Simulations and Its Relation to Pacific Variability over Coastal Region, Karachi, Pakistan

2021 ◽  
Vol 13 (22) ◽  
pp. 12608
Author(s):  
Adil Dilawar ◽  
Baozhang Chen ◽  
Lifeng Guo ◽  
Shuan Liu ◽  
Muhammad Shafeeque ◽  
...  
Keyword(s):  
Heat Wave ◽  
Land Surface ◽  
Southern Oscillation ◽  
Wrf Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Relative Role ◽  
Heat Wave Event ◽  
Wave Event

This study investigates the relative role of land surface schemes (LSS) in the Weather Research and Forecasting (WRF) model, Version 4, to simulate the heat wave events in Karachi, Pakistan during 16–23 May 2018. The efficiency of the WRF model was evaluated in forecasting heat wave events over Karachi using the three different LSS, namely NOAH, NOAH-MP, and RUC. In addition to this we have used the longwave (RRTM) and shortwave (Dudhia) in all schemes. Three simulating setups were designed with a combination of shortwave, longwave, and LSS: E1 (Dudhia, RRTM, and Noah), E2 (Dudhia, RRTM, and Noah-MP), and E3 (Dudhia, RRTM, and RUC). All setups were carried out with a finer resolution of 1 km × 1 km. Findings of current study depicted that E2 produces a more realistic simulation of daily maximum temperature T(max) at 2m, sensible heat (SH), and latent heat (LH) because it has higher R2 and lower errors (BIAS, RMSE, MAE) compared to other schemes. Consequently, Noah-MP (LSS) accurately estimates T(max) and land surface heat fluxes (SH&LH) because uses multiple physics options for land atmosphere interaction processes. According to statistical analyses, E2 setup outperforms other setups in term of T(max) and (LH&SH) forecasting with the higher Nash-Sutcliffe efficiency (NSE) agreement is 0.84 (0.89). This research emphasizes that the selection of LSS is of vital importance in the best simulation of T(max) and SH (LH) over Karachi. Further, it is resulted that the SH flux is taking a higher part to trigger the heat wave event intensity during May 2018 due to dense urban canopy and less vegetated area. El Niño-Southern Oscillation (ENSO) event played role to prolong and strengthen the heat wave period by effecting the Indian Ocean Dipole (IOD) through walker circulation extension.

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