scholarly journals Summer maximum temperature over the gulf cooperation council states in the twenty-first century: multimodel simulations overview

2020 ◽  
Vol 13 (12) ◽  
Author(s):  
Mansour Almazroui
Keyword(s):  
Gulf Cooperation Council ◽  
Global Climate Models ◽  
First Century ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Gcc Countries ◽  
The Future ◽  
Summer Maximum ◽  
Twenty First Century

Abstract The present study analyzes the Survivability for a Fit Human Threshold (SFHT) maximum temperature during the summer (June–August) over the six Middle Eastern countries known as the Gulf Cooperation Council (GCC) in the twenty-first century. An ensemble of three dynamically downscaled global climate models available from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5 emission scenarios is used to analyze the future climate (2006–2099) over the region. The ground-truth air temperature for ten major cities across the GCC countries is utilized for model evaluation and to estimate the model-simulated temperature biases. Both positive and negative biases found during the present climate (1976–2005) are used to adjust the future temperature changes. These adjustments show that the summer maximum temperature is likely to increase continuously for most cities in the GCC countries at the rate of about 0.2 °C (0.6 °C) per decade under RCP4.5 (RCP8.5) for the future period (2020–2099), which is significant at the 99% confidence level. For RCP8.5, the adjusted summer maximum temperature may exceed the SFHT limit of 42 °C in five capital cities of the GCC states and four major cities of Saudi Arabia. The projections based on adjusted values indicate that the average summer maximum temperature should not exceed 52 °C in any city investigated by the end of the twenty-first century. The daily maximum temperature is projected to exceed 55 °C in some cities in the GCC region by the end of the twenty-first century under a business-as-usual scenario that seems to be unrealistic if the biases are not taken into account. It is highly recommended that the GCC states should coordinate their efforts to respond appropriately to these projections using large ensembles of multimodel simulations while allowing for the associated uncertainty.

scholarly journals Projections of Twenty-First-Century Climate Extremes for Alaska via Dynamical Downscaling and Quantile Mapping

2017 ◽  
Vol 56 (9) ◽  
pp. 2393-2409 ◽  
Author(s):  
Rick Lader ◽  
John E. Walsh ◽  
Uma S. Bhatt ◽  
Peter A. Bieniek
Keyword(s):  
Climate Change ◽  
Dynamical Downscaling ◽  
Climate Extremes ◽  
First Century ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Quantile Mapping ◽  
Temperature And Precipitation ◽  
Twenty First Century

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.

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 Response of shortwave cloud radiative effect to greenhouse gases and aerosols and its impact on daily maximum temperature

2020 ◽  
Author(s):  
Tao Tang ◽  
Drew Shindell ◽  
Yuqiang Zhang ◽  
Apostolos Voulgarakis ◽  
Jean-Francois Lamarque ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Boreal Summer ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Sulfate Aerosols ◽  
Multilinear Regression

Abstract. Shortwave cloud radiative effects (SWCRE), defined as the difference of shortwave radiative flux between all-sky and clear-sky conditions, have been reported to play an important role in influencing the Earth’s energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe and East China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from the changes in relative humidity (RH) and, to a lesser extent, changes in circulation and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 K and 0.13 K per W m−2 increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the SWCRE change contribution to summer mean Tmax changes was 10–30 % under CO2 forcing and 30–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socio-economic activities.

scholarly journals Response of surface shortwave cloud radiative effect to greenhouse gases and aerosols and its impact on summer maximum temperature

2020 ◽  
Vol 20 (13) ◽  
pp. 8251-8266 ◽  
Author(s):  
Tao Tang ◽  
Drew Shindell ◽  
Yuqiang Zhang ◽  
Apostolos Voulgarakis ◽  
Jean-Francois Lamarque ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Eastern China ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Boreal Summer ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Sulfate Aerosols ◽  
Clear Sky ◽  
Sky Conditions

Abstract. Shortwave cloud radiative effects (SWCREs), defined as the difference of the shortwave radiative flux between all-sky and clear-sky conditions at the surface, have been reported to play an important role in influencing the Earth's energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols, and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe, and eastern China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from changes in relative humidity (RH) and, to a lesser extent, changes in cloud liquid water, circulation, dynamics, and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC because part of the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 and 0.13 K per watt per square meter (W m−2) increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the contribution of SWCRE change to summer mean Tmax changes was 10 %–30 % under CO2 forcing and 30 %–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socioeconomic activities.

scholarly journals Downscaling probability of long heatwaves based on seasonal mean daily maximum temperatures

2018 ◽  
Vol 4 (1/2) ◽  
pp. 37-52
Author(s):  
Rasmus E. Benestad ◽  
Bob van Oort ◽  
Flavio Justino ◽  
Frode Stordal ◽  
Kajsa M. Parding ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Principal Component ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Conditions ◽  
Probability Of Occurrence

Abstract. A methodology for estimating and downscaling the probability associated with the duration of heatwaves is presented and applied as a case study for Indian wheat crops. These probability estimates make use of empirical-statistical downscaling and statistical modelling of probability of occurrence and streak length statistics, and we present projections based on large multi-model ensembles of global climate models from the Coupled Model Intercomparison Project Phase 5 and three different emissions scenarios: Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. Our objective was to estimate the probabilities for heatwaves with more than 5 consecutive days with daily maximum temperature above 35 ∘C, which represent a condition that limits wheat yields. Such heatwaves are already quite frequent under current climate conditions, and downscaled estimates of the probability of occurrence in 2010 is in the range of 20 %–84 % depending on the location. For the year 2100, the high-emission scenario RCP8.5 suggests more frequent occurrences, with a probability in the range of 36 %–88 %. Our results also point to increased probabilities for a hot day to turn into a heatwave lasting more than 5 days, from roughly 8 %–20 % at present to 9 %–23 % in 2100 assuming future emissions according to the RCP8.5 scenario; however, these estimates were to a greater extent subject to systematic biases. We also demonstrate a downscaling methodology based on principal component analysis that can produce reasonable results even when the data are sparse with variable quality.

scholarly journals Effects of Climate Change on Burn Probability of Forests in Daxing’anling

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 611 ◽  
Author(s):  
Xiaorui Tian ◽  
Wenbin Cui ◽  
Lifu Shu ◽  
Xuezheng Zong
Keyword(s):  
Global Climate Models ◽  
Fire Season ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Fire Weather ◽  
Climate Scenarios ◽  
Fire Weather Index ◽  
Burned Areas ◽  
Burn Probability

Projecting the burn probability (BP) under future climate scenarios would provide a scientific basis for the implementation of forest fire adaptation technology. This study compared the changes in the climate, fire weather, and burn probability during the fire season in Daxing’anling, China. A burn probability model was established and used to simulate the daily fire occurrence and spread at baseline (1971–2000) and into the 2030s (2021–2050) based on the outputs from five global climate models (GCMs) (GFDL-ESM2M, Had GEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and Nor ESM1-M) under four climate scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). The results showed that the average daily maximum temperature in the fire season will be increased by 2.1 °C (+16.6%) in the 2030s compared with the baseline and precipitation in the fire season will be increased by 7.1%. The average fire weather index (FWI) of the fire season in the 2030s will be increased by 4.2%, but this change is not significant. There will be 39 fires per year in the 2030s, representing an increase of 11.4%. The accuracy of simulated burned areas was 71.2% for the 1991–2010 period. The simulated and observed burned areas showed similar interannual fluctuations during period 1971–2010. The potential burned areas in the 2030s will increase by 18.8% over those in the baseline period and the BP will increase by 19.4%. The implementation of proactive fire management in areas with high predicted BP values will be key for an effective mitigation of future wildfire impacts.

scholarly journals Geoengineering: Impact of Marine Cloud Brightening Control on the Extreme Temperature Change over East Asia

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1345
Author(s):  
Do-Hyun Kim ◽  
Ho-Jeong Shin ◽  
Il-Ung Chung
Keyword(s):  
East Asia ◽  
Radiative Forcing ◽  
Climate Models ◽  
Extreme Temperature ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Extreme Temperatures

We investigated the effect of artificial marine cloud brightening on extreme temperatures over East Asia. We used simulation data from five global climate models which have conducted the GeoMIP G4cdnc experiment. G4cdnc was designed to simulate an increase in the cloud droplet number concentration of the global marine lower clouds by 50% under the greenhouse gas forcing of the RCP4.5 scenario. G4cdnc decreased the net radiative forcing in the top of the atmosphere more over the ocean, alleviating the rise in mean temperature under RCP4.5 forcing. For extreme temperatures, G4cdnc reduced both the monthly minimum of daily minimum temperature (TNn) and monthly maximum of daily maximum temperature (TXx). The response of TNn was higher than that of TXx, especially in the winter, over the Sea of Okhotsk and the interior of the continent. This spatial heterogeneity and seasonality of the response were associated with sea ice–albedo and snow–albedo feedbacks. We also calculated the efficacy of warming mitigation as a measure of the relative effect of geoengineering. The efficacy for TXx was higher than that for TNn, opposite to the absolute effect. After the termination of geoengineering, both TNn and TXx tended to rapidly revert to their trend under the RCP4.5 forcing.

scholarly journals On forecasting daily summer maximum temperature at Madras

MAUSAM ◽  
2021 ◽  
Vol 49 (1) ◽  
pp. 95-102
Author(s):  
Y. E. A. RAJ
Keyword(s):  
Zonal Wind ◽  
Lead Time ◽  
Optimal Number ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Statistical Techniques ◽  
Daily Maximum ◽  
Skill Scores ◽  
Summer Maximum ◽  
Maximum Temperatures

Forecasting schemes based on statistical techniques have been developed to forecast daily summer (March-May) maximum temperatures of Madras. A set of optimal number of predictors were chosen from a large number of parameters by employing stepwise forward screening. Separate forecasting schemes for Madras city and airport, with lead time of 24 and 9 hr were developed from the data of 12 years and tested in an independent sample of 4 years. Maximum temperature of the previous day, normal daily maximum temperature, temperature advection index and morning zonal wind at Madras at 900 hPa level were among the predictors selected. The schemes yielded good results providing 77-87% correct, forecasts with skill scores of 0.29-0.57.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

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