Identifying key driving mechanisms of heat waves in central Chile

Author(s):  
Martín Jacques-Coper ◽  
Alan Demortier ◽  
Deniz Bozkurt

<p>This study explores the main drivers of heat wave (HW) events in central Chile using state-of-the-art reanalysis data (ERA5) and observations during the extended austral summer season (November to March) for the period 1979-2018. Frequency and intensity aspects of the HW events are considered using the total number of HW events per season and the amplitude, respectively. We first contrast ERA5 with several surface meteorological stations in central Chile to evaluate its ability to capture daily maximum temperature variability and the HW events. We then use synoptic- and large-scale fields and teleconnection patterns to address the most favorable conditions of the HW events from a climatological perspective, as well as for the extreme January 2017 HW event that swept central Chile with temperature records and wildfires. ERA5 tends to capture temperature extremes and the HW events at the inland stations; on the contrary, it has difficulties in capturing the maximum temperature variability at the coastal stations, which is plausible given the complex terrain features and confined coastal climate zone (only ~7% of all grid boxes within central Chile). The HW composite based on ERA5 reveals a mid-level trough-ridge dipole pattern exhibiting a blocking anticyclone on the surface over a large part of southwest South America. Relatively dry and warm easterly flow appears to accompany the anomalous warming in a large part of central Chile. The temporal evolution of the HW events yields a wave-like propagation pattern and enhancement of trough-ridge pattern along the South Pacific. This meridional dipole pattern is found to be largely associated with the Pacific South American pattern. In addition, the Madden-Julian Oscillation (MJO) appears to be a key component of the HW events in central Chile. In particular, while active MJO phases 2 and 7 promote sub-seasonal patterns that favor the South Pacific dipole mode, synoptic anomalies can superimpose on them and favor the formation of a migrating anticyclone over central-southern Chile and coastal lows over central Chile. Agreeing with the climatological findings, the extreme January 2017 HW analysis suggests that an eastward migratory mid-latitude trough-ridge pattern associated with the MJO phase 2 was at work. We highlight that, in addition to large- and synoptic-scale features, sub-synoptic processes such as coastal lows can have an important role in shaping the HW events and can lead to amplification of temperature extremes during the HW events.</p>

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  

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.


2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner

<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>


2002 ◽  
Vol 11 (4) ◽  
pp. 281 ◽  
Author(s):  
Michael J. Janis ◽  
Michael B. Johnson ◽  
Gloria Forthun

High spatial resolution maps of daily Keetch-Byram Drought Index (KBDI) are constructed for the south-eastern United States. KBDI is a cumulative algorithm for estimating fire potential from meteorological information, including daily maximum temperature, daily total precipitation, and mean annual precipitation. With few input parameters, the KBDI is attractive for providing estimates of fire potential at a large number of locations. The Southeast Regional Climate Center (SERCC) applies the original algorithms over daily time steps to maximize the response time in the event of rapidly increasing fire potential. Algorithms are applied to a network of 261 weather stations across the south-eastern United States to provide regional contour maps of KBDI as well as maps of week-to-week KBDI difference. Though uniformity and spatial density of weather stations and the consistency of input parameters are potential hurdles, it is shown that careful compilation of meteorological databases makes KBDI a tractable and valuable monitoring tool for automated fire-potential monitoring.


2007 ◽  
Vol 46 (11) ◽  
pp. 1993-2013 ◽  
Author(s):  
Reed P. Timmer ◽  
Peter J. Lamb

Abstract The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations between winter (November–February; December–February) temperature and residential gas consumption for the United States east of the Rocky Mountains for 1989–2000, by region and on monthly and seasonal time scales. State-level monthly gas consumption data are aggregated for nine multistate subregions of three Petroleum Administration for Defense Districts of the U.S. Department of Energy. Two temperature indices [days below percentile (DBP) and heating degree-days (HDD)] are developed using the Richman–Lamb fine-resolution (∼1° latitude–longitude) set of daily maximum and minimum temperatures for 1949–2000. Temperature parameters/values that maximize DBP/HDD correlations with gas consumption are identified. Maximum DBP and HDD correlations with gas consumption consistently are largest in the Great Lakes–Ohio Valley region on both monthly (from +0.89 to +0.91) and seasonal (from +0.93 to +0.97) time scales, for which they are based on daily maximum temperature. Such correlations are markedly lower on both time scales (from +0.62 to +0.80) in New England, where gas is less important than heating oil, and on the monthly scale (from +0.55 to +0.75) across the South because of low January correlations. For the South, maximum correlations are for daily DBP and HDD indices based on mean or minimum temperature. The percentiles having the highest DBP index correlations with gas consumption are slightly higher for northern regions than across the South. This is because lower (higher) relative (absolute) temperature thresholds are reached in warmer regions before home heating occurs. However, these optimum percentiles for all regions are bordered broadly by surrounding percentiles for which the correlations are almost as high as the maximum. This consistency establishes the robustness of the temperature–gas consumption relations obtained. The reference temperatures giving the highest HDD correlations with gas consumption are lower for the colder northern regions than farther south where the temperature range is truncated. However, all HDD reference temperatures greater than +10°C (+15°C) yield similar such correlations for northern (southern) regions, further confirming the robustness of the findings. This robustness, coupled with the very high correlation magnitudes obtained, suggests that potentially strong gas consumption predictability would follow from accurate seasonal temperature forecasts.


Author(s):  
Hojjatollah Yazdanpanah ◽  
Josef Eitzinger ◽  
Marina Baldi

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.


2021 ◽  
pp. jeb.236505
Author(s):  
Joel G. Kingsolver ◽  
M. Elizabeth Moore ◽  
Kate E. Augustine ◽  
Christina A. Hill

Climate change is increasing the frequency of heat waves and other extreme weather events experienced by organisms. How does the number and developmental timing of heat waves affect survival, growth and development of insects? Do heat waves early in development alter performance later in development? We addressed these questions using experimental heat waves with larvae of the Tobacco Hornworm, Manduca sexta. The experiments used diurnally fluctuating temperature treatments differing in the number (0-3) and developmental timing (early, middle and/or late in larval development) of heat waves, in which a single heat wave involved three consecutive days with a daily maximum temperature of 42 °C. Survival to pupation declines with increasing number of heat waves. Multiple (but not single) heat waves significantly reduced development time and pupal mass; the best models for the data indicated that both the number and developmental timing of heat waves affected performance. In addition, heat waves earlier in development significantly reduced growth and development rates later in larval development. Our results illustrate how the frequency and developmental timing of sublethal heat waves can have important consequences for life history traits in insects.


2020 ◽  
Author(s):  
Gerd Schädler ◽  
Marcus Breil

Abstract. Regional Climate Networks (RCNs) are used to identify heat waves and droughts in Germany and two subregions for the summer half years resp. summer seasons of the period 1951 to 2019. RCNs provide information for whole areas (in contrast to the point-wise information from standard indices), the underlying nodes can be distributed arbitrarily, they are easy to 5 construct and provide details otherwise difficult to avail of like extent, intensity and collective behaviour of extreme events. The RCNs were constructed on the regular 0.25 degree grid of the E-Obs data set. The season-wise correlation of time series of daily maximum temperature Tmax and precipitation were used to construct the adjacency matrix of the networks. Metrics to identify extremes were the edge density, the 90th percentile of the correlations and the average clustering coefficient, which turned out to be highly correlated; they increased considerably during extreme events. The standard indices for comparison 10 were the effective drought and heat index (EDI and EHI) respectively, based on the same time series, and complemented by other published data. Our results show that the RCNs are able to identify severe extremes in all cases and moderate extremes in most cases. An interesting finding is that during average years, the distribution of the node degrees is close to the Poisson distribution, characteristic of random networks, while for extreme years the distribution is more uniform and heavy tailed.


2021 ◽  
Vol 9 ◽  
Author(s):  
Jiayan Ren ◽  
Guohe Huang ◽  
Yongping Li ◽  
Xiong Zhou ◽  
Jinliang Xu ◽  
...  

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.


2021 ◽  
Author(s):  
Farhan Aziz ◽  
Nadeem Tariq ◽  
Akif Rahim ◽  
Ambreen Mahmood

<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>


2020 ◽  
Author(s):  
Ivana Tosic ◽  
Suzana Putniković ◽  
Milica Tošić

<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>


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