Assessing several downscaling methods for daily minimum and maximum temperature in a mountainous area. Are we able to statistically simulate a warmer climate in the Pyrenees?

2020 ◽  
Author(s):  
Marc Lemus-Canovas ◽  
Swen Brands
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Regression Models ◽  
Temporal Correlation ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Mountainous Area ◽  
Present Contribution ◽  
Mountain Areas ◽  
Maximum Daily Temperature

<p>Mountain areas are one of the most vulnerable areas to climate change, due to the large amount of natural resources they contribute to society. Moreover, the announced increase in temperature for the next few decades may have uncertain consequences for the ecosystems and landscapes of such territories. To face this challenge, it is necessary to test the capacity to simulate the climate of warm periods using observed data. In the present contribution, different perfect prog (PP) downscaling methods were evaluated to simulate the minimum and maximum daily temperature in a 1x1 km grid in the Pyrenees (Spain, France & Andorra) for the period 1985-2015. To obtain the results, several combinations of predictors, different geographical domains of such predictors, as well as different reanalysis databases were used, to check how much they can influence the prediction skill. In addition, different metrics were calculated to evaluate the bias, the similarity in the observed and predicted distributions, the temporal correlation, etc.</p><p>The results obtained reflect that the regression models better represent the warm periods using the observed data, as well as a lower bias. The present study will facilitate the decision making on which method of downscaling PP is more useful to reproduce the future temperature in the Pyrenees.</p><p> </p><p><strong>Keywords: </strong>Statistical downscaling, perfect prog, Pyrenees, daily temperature.</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.

scholarly journals Climate change impact on hydrological characteristics and water availability of the Mountain Pamir Rivers

2020 ◽  
Vol 383 ◽  
pp. 31-41
Author(s):  
Inom Normatov ◽  
Parviz Normatov
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Climate Change Impact ◽  
River Flow ◽  
Mass Movement ◽  
Atmospheric Precipitation ◽  
Mountainous Area ◽  
Mountain Areas ◽  
Change Impact ◽  
Using Data

Abstract. Results of monitoring accumulated snow cover in upstream areas of the Transboundary Pyanj River (Central Asia) are presented. It is found that the formation of the snow cover and the spatial distribution of atmospheric precipitation in the Mountain Pamir is determined by the orography of the terrain. Orography influences air mass movement in mountain areas, which contributes in different climatic zones to a shift in periods when the maximum amount of snow is falling. Completely different scenarios for the development of meteorological variables in the western and eastern parts of the Gunt River Basin were found, due, firstly, to the influence of the mountainous area orography and, secondly, to the penetration of various air masses. It is observed that in the western part of the basin the average annual precipitation remained almost unchanged over the period 1944–2014, whereas there is a decreasing trend in the eastern part. Assessment of the climate change impact on the formation of the Gunt River water flow was made by comparing the trend in the change of discharge using data from two observation periods 1940–1970 and 1986–2016. Calculations show a decrease of the Gunt River discharge by 5 % over a period of more than 70 years. The influence of climate warming on the river flow is indicated by comparison of river hydrograph in two periods 1940–1970 and 1986–2016. The hydrograph of the Vanch River in the earlier-mentioned periods shows a shift in the maximum of the monthly discharge towards the left, indicating an earlier melting of snow and glaciers in the upstream regions of the river and a significant increase in discharge in the period 1986–2016.

Effect of heat and precipitation on pea yield and reproductive performance in the field

2015 ◽  
Vol 95 (4) ◽  
pp. 629-639 ◽  
Author(s):  
Rosalind A. Bueckert ◽  
Stacey Wagenhoffer ◽  
Garry Hnatowich ◽  
Thomas D. Warkentin
Keyword(s):  
Reproductive Performance ◽  
Crop Growth ◽  
Daily Temperature ◽  
Growth And Yield ◽  
Maximum Temperature ◽  
Future Research ◽  
Yield Reduction ◽  
Weather Factors ◽  
Reproductive Growth ◽  
Maximum Daily Temperature

Bueckert, R. A., Wagenhoffer, S., Hnatowich, G. and Warkentin, T. D. 2015. Effect of heat and precipitation on pea yield and reproductive performance in the field. Can. J. Plant Sci. 95: 629–639. Pea (Pisum sativum L.) is important globally as a cool season crop. Pea cultivars are heat-sensitive so our goal was to investigate how weather impacted growth and yield in recent cultivars in the Co-operative pea yield trials (2000 to 2009) for a dryland (Saskatoon) and an irrigated (Outlook) location. We explored relationships between days to maturity, days spent in reproductive growth (flowering to maturity), yield and various weather factors. Yield and the length of reproductive growth increased with seasonal precipitation. Pea was sensitive to heat but heat units did not satisfactorily describe growth and yield in all environments. Strong relationships were observed between crop growth and mean maximum daily temperature experienced during reproductive growth, and between crop growth and mean minimum temperature. The greater the mean maximum temperature (>25.5°C), the fewer the number of days (<35) spent in reproductive growth at the dryland location. At Outlook, 35 to 40 d in reproductive growth occurred in a much wider temperature range from 24.5 to 27°C, and irrigation mitigated some reduction in yield. For dryland pea, more than 20 d in the season above 28°C were associated with less time in reproductive growth and less yield. The threshold maximum temperature for yield reduction in the field was closer to 28°C than 32°C from published studies, and above 17.5°C mean seasonal daily temperature. Western Canadian cultivars currently have short lifecycles, which make them heat sensitive. Heat tolerance could be improved by earlier flowering and a longer duration of flowering via an indeterminate habit. Future research will investigate pea nodal development, flowering and abortion patterns in a range of pea cultivars in field conditions.

scholarly journals Correlation Between Local Air Temperature and the COVID-19 Pandemic in Hubei, China

2021 ◽  
Vol 8 ◽  
Author(s):  
Cheng-yi Hu ◽  
Lu-shan Xiao ◽  
Hong-bo Zhu ◽  
Hong Zhu ◽  
Li Liu
Keyword(s):  
Air Temperature ◽  
Minimum Temperature ◽  
Regression Models ◽  
Hubei Province ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Influence Of Temperature ◽  
Influence Of Temperature On ◽  
Almost All

Objective: To clarify the correlation between temperature and the COVID-19 pandemic in Hubei.Methods: We collected daily newly confirmed COVID-19 cases and daily temperature for six cities in Hubei Province, assessed their correlations, and established regression models.Results: For temperatures ranging from −3.9 to 16.5°C, daily newly confirmed cases were positively correlated with the maximum temperature ~0–4 days prior or the minimum temperature ~11–14 days prior to the diagnosis in almost all selected cities. An increase in the maximum temperature 4 days prior by 1°C was associated with an increase in the daily newly confirmed cases (~129) in Wuhan. The influence of temperature on the daily newly confirmed cases in Wuhan was much more significant than in other cities.Conclusion: Government departments in areas where temperatures range between −3.9 and 16.5°C and rise gradually must take more active measures to address the COVID-19 pandemic.

scholarly journals Effects of Climate Change on Precipitation and the Maximum Daily Temperature (Tmax) at Two US Military Bases with Different Present-Day Climates

Climate ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 18
Author(s):  
Jovan Tadić ◽  
Sébastien Biraud
Keyword(s):  
Climate Change ◽  
North Carolina ◽  
Emission Scenario ◽  
Daily Temperature ◽  
Military Bases ◽  
Climate Change Signal ◽  
Maximum Daily Temperature ◽  
Us Military ◽  
Cross Covariance ◽  
Tail Distributions

In this study, the effects of climate change on precipitation and the maximum daily temperature (Tmax) at two USA locations that have different climates—the Travis Airforce Base (AFB) in California [38.27° N, 121.93° W] and Fort Bragg (FBR) in North Carolina [35.14 N, 79.00 W]—are analyzed. The effects of climate change on central tendency, tail distributions, and both auto- and cross-covariance structures in precipitation and Tmax fields for three time periods in the 21st century centered on the years 2020, 2050, and 2100 were analyzed. It was found that, on average, Tmax under the Representative Concentration Pathway (RCP) 4.5 emission scenario is projected to increase for the years 2020, 2050, and 2100 by 1.1, 2.0, and 2.2 °C, respectively, for AFB, and 0.9, 1.2, and 1.6 °C, respectively, for FBR, while under the RCP8.5 emission scenario Tmax will increase by 1.1, 1.9, and 2.7 °C, respectively, for AFB, and 0.1, 1.5, and 2.2 °C, respectively, for FBR. The climate change signal in precipitation is weak. The results show that, under different emission scenarios, events considered to be within 1% of the most extreme events in the past will become ~13–30 times more frequent for Tmax, ~and 0.05–3 times more frequent for precipitation in both locations. Several analytical methods were deployed in a sequence, creating an easily scalable framework for similar analyses in the future.

scholarly journals Analysis of Climate Change and Sustainable Development in Peru and Its Departments during the Year 2006 - 2018

2021 ◽  
pp. 31-46
Author(s):  
Vladimir Villarroel Diaz ◽  
Ronald Révolo Acevedo ◽  
Uriel Quispe Quezada ◽  
Elvis Carmen Delgadillo ◽  
Joel Colonio Llacua ◽  
...  
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Minimum Temperature ◽  
Regression Models ◽  
Environmental Data ◽  
Maximum Temperature ◽  
Climate Index ◽  
P Value ◽  
Climatic Data ◽  
General Index

Aims: Analyze and relate the general index of climate change and sustainable development of Peru and its departments during the year 2006 - 2018. Study Design:  The research is not intended to deliberately manipulate the variables, therefore, it is non-experimental; is descriptive, correlational and longitudinal. Place and Duration of Study: The research project was carried out in the Faculty of Forestry and Environmental Sciences of the UNCP, likewise the collection of information data was carried out during 2020 and 2021, due to the Covid19 pandemic. Methodology: Two economic data, four social data and five environmental data were selected, in addition climatic data of precipitation, maximum and minimum temperature of the 24 departments of Peru were collected during the years 2006 - 2018; To estimate the climatic and sustainable indices, the Prescott-Allen methodology was applied, the interpretation and assessment scale (climate change and sustainable development) was carried out using the barometric analysis of McCarthy. Five regression models were applied [dependent variable GISD; independent variable IGCC], hypothesis testing was performed using Karl Pearson's r coefficient and p-value at 0.05. Results: It is stated that Peru presents an economic sustainable index [EcSI] of 0.066 low, social sustainability [SoSI]: 0.225 medium, environmental sustainability [EnSI]: 0.282 high and general index of sustainable development [GISD] is 0.572 medium. In itself the climate index of precipitation is [CPrI]: 0.079 weak, the climate index maximum temperature [CTxI]: 0.251 severe, climate index minimum temperature [CTnI]: 0.138 weak and the general index of climate change [GICC] is 0.468 moderate. Two appropriate regression models [linear and exponential] were determined to estimate the GISD as a function of the GICC, CPrI, CTxI and CTnI. Conclusion: It was found that during the year 2006 to 2018 Peru presented a low economic, social medium, high environmental situation and therefore its sustainable development is in a medium situation; while precipitation is weak, severe maximum temperature, weak minimum temperature, and therefore, climate change has a moderate impact. Likewise, it is stated that there are two linear and exponential regression models to estimate the GISD based on the GICC, CPrI, CTxI and CTnI. It is recommended to collect more climatic data and economic indicators to be able to differentiate the economic and climatic situation that Peru and departments represent during its thirteen years of development.

scholarly journals Seasonal and Annual Trends in Australian Minimum/Maximum Daily Temperatures

2016 ◽  
Vol 10 (1) ◽  
pp. 39-55 ◽  
Author(s):  
W. A. van Wijngaarden ◽  
A. Mouraviev
Keyword(s):  
Temperature Trend ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Rural Environment ◽  
Maximum Daily Temperature ◽  
Temperature Trends ◽  
Significant Step ◽  
Annual Trends ◽  
Maximum Temperatures ◽  
Minimum Daily Temperature

Seasonal and annual trends in Australian minimum and maximum temperatures were studied. Records of daily minimum and maximum temperatures averaged over each month, extending as far back as 1856 were examined. Over 1/2 million monthly temperature values were retrieved from the Australian Bureau of Meteorology for 299 stations. Each station had an average of 89 years of observations. Significant step discontinuities affected the maximum temperature data in the 19th century when Stevenson screens were installed. The temperature trends were found after such spurious data were removed and averaged over all stations. The resulting trend in the minimum (maximum) daily temperature was 0.67 ± 0.19 (0.58 ± 0.26) oC per century for the period 1907-2014. Decadal fluctuations were evident in the maximum daily temperature with most of the increase occurring in the late 20th century. The minimum and maximum daily temperature trends were also found for the various seasons. The minimum daily temperature trend exceeded the maximum daily temperature trend for all seasons except during June to August. The largest increases in minimum temperature as well as the smallest maximum temperature increases were found for the region north of 30 oS latitude and east of 140 oE longitude. There was also evidence that urban stations had greater increases in maximum daily temperature than those located in a rural environment.

scholarly journals Different Time Windows Provide Divergent Estimates of Climate Variability and Change Impacts on Maize Yield in Northeast China

2019 ◽  
Vol 11 (23) ◽  
pp. 6659 ◽  
Author(s):  
Xi Deng ◽  
Yao Huang ◽  
Wenjuan Sun ◽  
Lingfei Yu ◽  
Xunyu Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Northeast China ◽  
Regression Models ◽  
Time Window ◽  
Time Windows ◽  
Maize Yield ◽  
Climate Impacts ◽  
Maximum Temperature ◽  
Climate Variability And Change

Maize is the main crop in Northeast China (NEC), but is susceptible to climate variations. Using county-level data from 1980 to 2010, we established multiple linear regression models between detrended changes in maize yield and climate variables at two time windows—whole-season and vegetative and reproductive (V&R) phases. Based on climate change trends, these regression models were used to assess climate variability and change impacts on maize yield in different regions of NEC. The results show that different time windows provide divergent estimates. Climate change over the 31 years induced a 1.3% reduction in maize yield at the time window of whole-season, but an increase of 9.1% was estimated at the time window of V&R phases. The yield improvement is attributed to an increase in minimum temperature at the vegetative phase when the temperatures were much lower than the optimum. Yield fluctuations due to inter-annual climate variability were estimated to be ±9% per year at the time window of V&R phases, suggesting that the impact of climate variability on maize yield is much greater than climate change. Trends in precipitation were not responsible for the yield change, but precipitation anomalies contributed to the yield fluctuations. The impacts of warming on maize yield are regional specific, depending on the local temperatures relative to the optimum. Increase in maximum temperature led to a reduction of maize yield in western NEC, but to an increase in mid-east part of NEC. Our findings highlight the necessity of taking into account the phenological phase when assessing the climate impacts on crop yield, and the importance of buffering future crop production from climate change in NEC.

scholarly journals Analysis and Farmers Perception of Climate Change Trends in Kashmir Region of Union Territory-Jammu & Kashmir, India: North Western Himalayas

2021 ◽  
Author(s):  
S. Sheraz Mahdi ◽  
Bhagyashree Shankarao Dhekale ◽  
Ashaq Hussain ◽  
Intikhab Aalum Jehangir ◽  
Rukhsana Jan ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Management ◽  
Maximum Temperature ◽  
Mountainous Area ◽  
Western Himalayas ◽  
Kashmir Valley ◽  
Ground Water Recharge ◽  
North Western ◽  
Union Territory ◽  
Precipitation And Temperature

Abstract Analysis of climatic variables is important for detection and attribution of climate change trends and has received a considerable attention from researchers across the globe including India. Kashmir valley of newly formed Union Territory Jammu & Kashmir situated in north western part of India is having a rich repository of glaciers, a small change in the precipitation and temperature management could introduce about environmental, agricultural and economic penalties. To this end, current study aims to analyse changing patterns in precipitation and temperature variables over the various elevation zones of the Kashmir Valley using long term precipitation and temperature data obtained from National Data Centre, Indian Meteorological Department (IMD), Pune for the period of 40 years (1980–2019). The results revealed that average mean minimum and maximum temperature of the Kashmir valley has increased substantially at a rate of 0.02oC/year. Warming trends has been observed in all seasons, however, winter and spring season temperatures have shown statistically significant increasing trends. In addition, mean maximum and minimum temperature in plain and mountain areas have reported higher rates of increase in comparison to Karewah’s and foothill areas of Kashmir. Study of annual precipitation results for the same period indicates a diminishing pattern with a rate of -5.01 mm/year. Seasonal precipitation was also found decreasing at rate of -4.95, -0.30, -0.28 and − 0.06 mm/year for the spring, winter, autumn and summer seasons respectively and at different elevation zones, higher rates of precipitation decline have been observed in the mountainous area, which can be very detrimental to the agricultural crops of the Kashmir valley through water supply, climate regulation and ground water recharge. Further, the above statistical test results of increase in temperature and decrease in precipitation over different topographical zones of Kashmir were corroborated with the information attained from interview and involvement of the small farmer holders of 06 different locations representing the whole Kashmir and has been discussed in this paper to get a clearer understanding of climate change related instability and patterns in weather variables in the Kashmir Valley.

scholarly journals Maximum Daily Temperature, Precipitation, Ultraviolet Light, and Rates of Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in the United States

2020 ◽  
Author(s):  
Shiv T Sehra ◽  
Justin D Salciccioli ◽  
Douglas J Wiebe ◽  
Shelby Fundin ◽  
Joshua F Baker
Keyword(s):  
United States ◽  
Severe Acute Respiratory Syndrome ◽  
Negative Binomial ◽  
The United States ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Inverse Association ◽  
Maximum Daily Temperature ◽  
Uv Index

Abstract Background Previous reports have suggested that transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is reduced by higher temperatures and higher humidity. We analyzed case data from the United States to investigate the effects of temperature, precipitation, and ultraviolet (UV) light on community transmission of SARS-CoV-2. Methods Daily reported cases of SARS-CoV-2 across the United States from 22 January 2020 to 3 April 2020 were analyzed. We used negative binomial regression modeling to determine whether daily maximum temperature, precipitation, UV index, and the incidence 5 days later were related. Results A maximum temperature above 52°F on a given day was associated with a lower rate of new cases at 5 days (incidence rate ratio [IRR], 0.85 [0.76, 0.96]; P = .009). Among observations with daily temperatures below 52°F, there was a significant inverse association between the maximum daily temperature and the rate of cases at 5 days (IRR, 0.98 [0.97, 0.99]; P = .001). A 1-unit higher UV index was associated with a lower rate at 5 days (IRR, 0.97 [0.95, 0.99]; P = .004). Precipitation was not associated with a greater rate of cases at 5 days (IRR, 0.98 [0.89, 1.08]; P = .65). Conclusions The incidence of disease declines with increasing temperature up to 52°F and is lower at warmer vs cooler temperatures. However, the association between temperature and transmission is small, and transmission is likely to remain high at warmer temperatures.

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