Attributes for NHDPlus catchments (version 1.1) for the conterminous United States: 30-year average annual maximum temperature, 1971-2000

Data Series ◽  
2010 ◽  
Author(s):  
Michael Wieczorek ◽  
Andrew E. LaMotte
Keyword(s):  
United States ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Annual Maximum Temperature

Modelling annual maximum temperature of India: a distributional approach

2021 ◽  
Author(s):  
Bishal Gurung ◽  
Krishna Pada Sarkar ◽  
K. N. Singh ◽  
Achal Lama
Keyword(s):  
Maximum Temperature ◽  
Annual Maximum ◽  
Annual Maximum Temperature

scholarly journals A bayesian analysis of the annual maximum temperature using generalized extreme value distribution

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 607-618
Author(s):  
CHERAITIA HASSEN
Keyword(s):  
Goodness Of Fit ◽  
Estimation Method ◽  
Gumbel Distribution ◽  
Extreme Value ◽  
Generalized Extreme Value Distribution ◽  
Maximum Temperature ◽  
Ratio Test ◽  
Annual Maximum ◽  
Generalized Extreme Value ◽  
Annual Maximum Temperature

The annual maximum temperature was modeled using the Generalized Extreme Value (GEV) distribution to Jijel weather station. The Mann-Kendall (MK) and Kwiatkowski Phillips, Schmidt and Shin (KPSS) tests suggest a stationary model without linear trend in the location parameter. The Kurtosis and the Skewness statistics indicated that the normality assumption was rejected. The Likelihood Ratio test was used to determine the best model and the goodness-of-fit tests showed that our data is suitable with a stationary Gumbel distribution. The Maximum Likelihood estimation method and the Bayesian approach using the Monte Carlo method by Markov Chains (MCMC) were used to find the parameters of the Gumbel distribution and the return levels were obtained for different periods. JEL Classification: C1, C13, C46, C490.

scholarly journals Projection of key meteorological hazard factors in Xiongan new area of Hebei Province, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dapeng Huang ◽  
Yaoming Liao ◽  
Zhenyu Han
Keyword(s):  
High Temperature ◽  
Daily Precipitation ◽  
Flood Hazard ◽  
Linear Trend ◽  
Maximum Temperature ◽  
Projection Data ◽  
Annual Maximum ◽  
High Hazard ◽  
Under Construction ◽  
Annual Maximum Temperature

AbstractIt is of great importance to explore the future spatiotemporal dynamics of key meteorological hazard factors in Xiongan New Area, an area of great strategic significance under construction in China. Based on 6.25 km high-resolution downscaling projection data under RCP4.5 and RCP8.5 scenarios, Mann–Kendall trend and linear trend were analyzed, and then stationary generalized extreme value (GEV) and time-varying GEV methods were determined to calculate the extremes of four key meteorological hazard factors with return periods of 10, 20, 30, 50 and 100 years during the projection period 1991–2050. Results show that extremes of annual maximum daily precipitation and annual maximum amount of consecutive precipitation under two climate scenarios will not increase too much. Extremes of annual maximum temperature will increase by above 1.5 °C under RCP4.5 scenario in most grids and above 1.9 °C under RCP8.5 scenario. Extremes of annual longest consecutive high-temperature days will increase by above 0.9d under RCP4.5 scenario and above 1.6d under RCP8.5 scenario. On the whole, the hazard of flood disaster will hardly show any change up to 2050, but there will be relatively higher flood hazard in Xiongxian county and its adjacent region. All regions in Xiongan New Area will face high hazard of high-temperature disaster.

scholarly journals Exceedance and Return Period of High Temperature in the African Region

Climate ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 53
Author(s):  
Alemtsehai A. Turasie
Keyword(s):  
High Temperature ◽  
Return Period ◽  
Extreme Events ◽  
Extreme Event ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
African Region ◽  
Probability Of Exceedance ◽  
Mean Temperature ◽  
Annual Maximum Temperature

Several studies have indicated that the social, economic and other impacts of global warming can be linked with changes in the frequency and intensity of extreme weather/climate events. Developing countries, particularly in the African region, are highly affected by extreme events such as high temperature, usually followed/accompanied by drought. Therefore, studying the probability of occurrence and return period of extreme temperatures, and possible change in these parameters, is of high importance for climate-related policy making and preparedness works in the region. This study aims to address these issues by assessing probability of exceedance and return period of extremes in annual maximum and annual mean temperatures. The analyses of historical data in this study showed that extremes in both annual maximum and mean temperature are highly likely to be exceeded more often in the future compared to the past. For the extreme event marker (threshold) defined in this study, probability of 3 exceedances in the following 19 years (for instance), at any gridpoint, is estimated to be at least 10% for extremes in annual maxima and at least 15% for those in annual means. Most places in the region, however, have much higher (up to 20%) probability of exceedance. The estimated probability of exceedance has shown increasing tendency with time. Return period, based on the most recent data, of extremes in annual maximum temperature is found to be less than 6.5 years at about 48% of the gridpoints in the region. Similarly, return period of extremes in annual mean temperature is estimated to be less than 5.5 years at about 82% of places in the region. These estimates have also shown a strong tendency of getting shorter as time goes on. On average, extremes in annual mean temperature were found to have shorter return periods (4–7 years) compared to those in annual maximum temperature (6–10 years), at 95% confidence. The empirical results presented in this study are generally in agreement with IPCC’s projections of increased warming trend. This data-driven, robust method is used in the present study and the results can also be considered as an alternative approach for detecting changes in climate via estimating and assessing possible changes in frequency of extreme events with time.

scholarly journals Selecting the probability distribution of annual maximum temperature in Malaysia

2021 ◽  
Vol 36 ◽  
pp. 01010
Author(s):  
Nurfatini Mohd Supian ◽  
Husna Hasan
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Agricultural Sector ◽  
Estimation Method ◽  
Information Criterion ◽  
Maximum Temperature ◽  
Logistic Distribution ◽  
Annual Maximum ◽  
Goodness Of Fit Test ◽  
Annual Maximum Temperature

The issues on global warming have become very popular and been discussed both locally and internationally. This phenomenon due to the temperature rises will increase the variability of climate and more natural disasters were expected to occur. Increasing of global temperature will affect the agricultural sector, increase some of the infectious diseases that may lead to high mortality rates in humans, high demand for electricity, water and food which eventually affecting the economy of Malaysia. Hence, this work aims to study the best fitted probability distribution that describes the annual maximum temperature recorded at seventeen meteorological stations in Malaysia. The Normal, Lognormal, Gamma, Weibull and Generalized Skew Logistic distributions are considered using the maximum likelihood estimation method to estimate the parameters. The goodness of fit test and model selection criteria such as Kolmogorov-Smirnov and AndersonDarling tests, Corrected Akaike Information Criterion and Bayesian Information Criterion are used to measure the accuracy of the predicted data using theoretical probability distributions. The results show that most of the stations favour the Generalized Skew Logistic distribution as the best fitted probability distribution. Also, some stations favour the Normal, Lognormal as well as Weibull distribution as the best fitted distribution to describe the annual maximum temperature.

scholarly journals Impact of Climate Change on Milk Production and Perceptions of Farmers in the West Bengal

2021 ◽  
pp. 533-540
Author(s):  
Subhankar Biswas ◽  
Ajay Verma ◽  
R. Sendhil ◽  
AK Dixit ◽  
Ajmer Singh ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Milk Production ◽  
West Bengal ◽  
Late Onset ◽  
Adaptation Strategy ◽  
Cow Milk ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Annual Minimum Temperature ◽  
Annual Maximum Temperature

The cause and effect relationship of climatic variables on milk production of indigenous cattle and buffalo had been carried in West Bengal state during 2019-2020. Regression analysis indicated the indigenous cow milk production was directly responsive to annual minimum temperature, while crossbred cow milk production was indirectly responsive to annual maximum temperature and relative humidity. The buffalo milk production was inversely related to annual maximum temperature and relative humidity. More than half of surveyed farmers had a medium level of experience in farming. Majority of farmers were perceived climate variability in general like increase in temperature during the summer season, late onset of monsoon and early withdrawal of monsoon season. For crop farming, crop diversification was the most preferred adaptation strategy among the farmers followed by changing crop variety. For dairy farming, provide proper shed and shelter was most preferred adaptation strategy followed by provide additional fresh drinking water in summer.

scholarly journals Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Extreme Events ◽  
First Century ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Temperature And Precipitation ◽  
Projected Change ◽  
Twenty First Century ◽  
Projected Changes ◽  
The Tropics

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

Sign in / Sign up

Export Citation Format

Share Document