scholarly journals Modeling of Climatic Records for the Province of Villa Clara, Cuba

2021 ◽  
Vol 2 (12) ◽  
pp. 1304-1308
Author(s):  
Ricardo Oses Rodriguez ◽  
Rigoberto Fimia Duarte
Keyword(s):  
Minimum Temperature ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Weather Stations ◽  
Explained Variance ◽  
Temperature Records ◽  
Predicted Values ◽  
Climatic Records

The objective of this work is to model the extreme temperature climatic records of Villa Clara Cuba and see if there is a trend in them, in addition the variable date on which they occurred was modeled, with the help of the Regressive Objective Regression (ROR). A database from 1966 to 2020 of the 4 weather stations with the account of the province of Villa Clara is used. The explained variance of the models is 100% for the maximum temperature and 99.8 for the minimum with errors of 0.58 and 1.4ºC. You can estimate the graphs for the maximum temperature as for the minimum with the predicted values ​​and the errors that the model commits. The trend for the date of the maximum trend is negative while for the minimum it is positive. The records depend on the temperature returned in 1 month (LAG1T) and the temperature returned in 12 months (LAG12T), both for the maximum TX and for the minimum TN, as well as the station value. The correlations between the actual and predicted value for the maximum and minimum temperature records and for the date models are high, greater than 90% and 99% variable.

scholarly journals Heat waves in Africa 1981–2015, observations and reanalysis

2017 ◽  
Vol 17 (1) ◽  
pp. 115-125 ◽  
Author(s):  
Guido Ceccherini ◽  
Simone Russo ◽  
Iban Ameztoy ◽  
Andrea Francesco Marchese ◽  
Cesar Carmona-Moreno
Keyword(s):  
Heat Wave ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Reanalysis Data ◽  
Maximum Temperature ◽  
Wave Analysis ◽  
Land Area ◽  
Spatial Coverage ◽  
Temperature Records ◽  
Numerical Index

Abstract. The purpose of this article is to show the extreme temperature regime of heat waves across Africa over recent years (1981–2015). Heat waves have been quantified using the Heat Wave Magnitude Index daily (HWMId), which merges the duration and the intensity of extreme temperature events into a single numerical index. The HWMId enables a comparison between heat waves with different timing and location, and it has been applied to maximum and minimum temperature records. The time series used in this study have been derived from (1) observations from the Global Summary of the Day (GSOD) and (2) reanalysis data from ERA-Interim. The analysis shows an increasing number of heat waves of both maxima and minima temperatures in the last decades. Results from heat wave analysis of maximum temperature (HWMIdtx) indicate an increase in intensity and frequency of extreme events. Specifically, from 1996 onwards it is possible to observe HWMIdtx spread with the maximum presence during 2006–2015. Between 2006 and 2015 the frequency (spatial coverage) of extreme heat waves had increased to 24.5 observations per year (60.1 % of land cover), as compared to 12.3 per year (37.3 % of land area) in the period from 1981 to 2005 for GSOD stations (reanalysis).

scholarly journals Changes of Extreme Temperature and Its Influencing Factors in Shiyang River Basin, Northwest China

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1171
Author(s):  
Junju Zhou ◽  
Jumei Huang ◽  
Xi Zhao ◽  
Li Lei ◽  
Wei Shi ◽  
...  
Keyword(s):  
Global Warming ◽  
River Basin ◽  
Minimum Temperature ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Extreme Temperatures ◽  
Shiyang River Basin

The increase in the frequency and intensity of extreme weather events around the world has led to the frequent occurrence of global disasters, which have had serious impacts on the society, economic and ecological environment, especially fragile arid areas. Based on the daily maximum temperature and daily minimum temperature data of four meteorological stations in Shiyang River Basin (SRB) from 1960 to 2015, the spatio-temporal variation characteristics of extreme temperature indices were analyzed by means of univariate linear regression analysis, Mann–Kendall test and correlation analysis. The results showed that the extreme temperatures warming indices and the minimum of daily maximum temperature (TXn) and the minimum of daily minimum temperature (TNn) of cold indices showed an increasing trend from 1960 to 2016, especially since the 1990s, where the growth rate was fast and the response to global warming was sensitive. Except TXn and TNn, other cold indices showed a decreasing trend, especially Diurnal temperature (DTR) range, which decreased rapidly, indicating that the increasing speed of daily min-temperature were greater than of daily max-temperature in SRB. In space, the change tendency rate of the warm index basically showed an obvious altitude gradient effect that decreased with the altitude, which was consistent with Frost day (FD0) and Cool nights (TN10p) in the cold index, while Ice days (ID0) and Cool days (TX10p) are opposite. The mutation of the cold indices occurred earlier than the warm indices, illustrating that the cold indices in SRB were more sensitive to global warming. The change in extreme temperatures that would have a significant impact on the vegetation and glacier permafrost in the basin was the result of the combined function of different atmospheric circulation systems, which included the Arctic polar vortex, Western Pacific subtropical high and Qinghai-tibet Plateau circulation.

A comment on temperature measurement at automatic weather stations in Australia

2019 ◽  
Vol 69 (1) ◽  
pp. 172
Author(s):  
G. P. Ayers
Keyword(s):  
Air Temperature ◽  
Thermal Inertia ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Data Sets ◽  
Frequency Distributions ◽  
Measurement Systems ◽  
Weather Stations ◽  
The Difference ◽  
Temperature Records

Two versions of 1-min air-temperature data recorded at Bureau Automatic Weather Stations (AWSs) were compared in three case studies. The aim was to evaluate the difference between 1-min data represented by a measurement at the last second of each minute, compared with an average of four or five 1-s measurements made during the minute. Frequency distributions of the difference between these two values were produced for 44 000 min in three monthly data sets, January and July 2016 and September 2017. Diurnal and seasonal changes in standard deviation of the temperature differences showed that minute-to-minute fluctuations were driven by solar irradiance as the source of turbulent kinetic energy in the planetary boundary layer. Fluctuations in the difference between the two versions of 1-min data were so small overnight in all months that minimum temperature (Tmin) was the same using both methods. In midsummer, any difference between the two values for maximum temperature (Tmax) was greatest at midday. Tmax could be up by 0.1 K higher in the 1-s data compared with Tmax averaged from four measurements in the minute, but less often than 1 min in five. A follow-up test for September 2017 at Mildura when a new Tmax record was set found the difference immaterial, with Tmax the same for the averaged or 1-s values. Thus while the two versions of 1-min air-temperature data showed fluctuating small differences, largest at midday in summer, for the 3 months studied at both sites, fluctuations were too small to cause bias in climatological air-temperature records. This accorded with a numerical experiment confirming the Bureau’s advice that thermal inertia in the AWS measurement systems ensured that its 1-s data represented averages over the prior 40–80 s, providing a 1-min average of air temperature in accord with World Meteorological Organization requirements.

scholarly journals Observed Changes in Return Values of Annual Temperature Extremes over Argentina

2008 ◽  
Vol 21 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
Matilde Rusticucci ◽  
Bárbara Tencer
Keyword(s):  
Minimum Temperature ◽  
Extreme Temperature ◽  
Value Theory ◽  
Extreme Value ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Frequency Of Occurrence ◽  
Extreme Temperature Events ◽  
Huge Impact ◽  
Maximum Minimum

Abstract Extreme temperature events are one of the most studied extreme events since their occurrence has a huge impact on society. In this study, the frequency of occurrence of absolute extreme temperature events in Argentina is analyzed. Four annual extremes are defined based on minimum and maximum daily data: the highest maximum (minimum) temperature of the year, and the lowest maximum (minimum) temperature of the year. Applying the extreme value theory (EVT), a generalized extreme value (GEV) distribution is fitted to these extreme indices and return values are calculated for the period 1956–2003. Its spatial distribution indicates that, for warm extremes, maximum temperature (Tx) is expected to be greater than 32°C at least once every 100 yr throughout the country (reaching values even higher than 46°C in the central region), while minimum temperature (Tn) is expected to exceed 16°C (reaching 30°C in the central and northern regions). Cold annual extremes show larger gradients across the country, with Tx being lower than 8°C at least once every 100 yr, and Tn lower than 0°C every 2 yr, with values even less than −10°C in the southwestern part of the country. However, the frequency of occurrence of climatic extremes has changed throughout the globe during the twentieth century. Changes in return values of annual temperature extremes due to the 1976–77 climatic shift at six long-term datasets are then analyzed. The lowest Tx of the year is the variable in which the 1976–77 shift is less noticeable. At all the stations studied there is a decrease in the probability of occurrence of the highest Tx if the study is based on more recent records, while the frequency of occurrence of the highest Tn increases at some stations and decreases at others. This implies that in the “present climate” (after 1977) there is a greater frequency of occurrence of high values of Tn at Observatorio Central Buenos Aires and Río Gallegos together with a lower frequency of occurrence of high values of Tx, leading to a decrease in the annual temperature range. The most noticeable change in return values due to the 1976–77 shift is seen in Patagonia where the 10-yr return value for the highest Tn increases from 13.7°C before 1976 to 18.6°C after 1977. That is, values of the highest Tn that occurred at least once every 10 yr in the “past climate” (before 1976) now happened more than once every 2 yr.

scholarly journals Time Series Trend and Variability Analysis of Temperature and Rainfall in West Shewa Zone of Oromia, Ethiopia

2021 ◽  
Author(s):  
Daniel Assefa ◽  
Mesfin Mengistu
Keyword(s):  
Time Series ◽  
Minimum Temperature ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Variability Analysis ◽  
Increasing Trend ◽  
Systematic Planning ◽  
Temperature Records ◽  
C 30

Abstract BackgroundThe paper focus on time series trend and variability analysis of observed rainfall and temperature records from 16 stations during 1985-2015. ResultsBoth the summer and annual rainfall have an increasing trend but not statistically significant. Regards to variability, low to very high levels of variability were recorded according to the seasons and annual rainfall, whereas, moderate to extremely high levels of variability were observed. The result of the Mann Kendall test portrays that the mean minimum temperature was raised by 0.05 oC, while the maximum temperature was increased rose by 0.03 oC/30 years. The monthly maximum temperature also shows an increasing trend with the lowest record during August (22.05 oC) and the highest in the March (26.49 oC) except in the month of November and December. Similarly, an increasing trend was observed with a mean monthly minimum temperature with the lowest mean of 8.42Co in December and the highest mean of 11.12 oC recorded in April. Besides, a low level of variability was seen both in the case of minimum and maximum temperature were observed in all months. ConclusionsTherefore, since the observed trends of both temperature and total rainfall show abnormal shifts, there is an urgent need for policymakers to design systematic planning and management activities to rain-fed agriculture.

scholarly journals Investigation of the maximum and minimum temperatures in the semi-arid region of northeastern Brazil

2011 ◽  
Vol 5 (2) ◽  
pp. 82
Author(s):  
Eunice Maia Andrade ◽  
Meilla Marielle Araújo Rodrigues ◽  
Marcos Amauri Bezerra Mendonça ◽  
Luiz Carlos Guerreiro Chaves ◽  
Rebeca Mendes Feitoza
Keyword(s):  
Minimum Temperature ◽  
Northeastern Brazil ◽  
Maximum Temperature ◽  
Data Sets ◽  
Air Temperatures ◽  
Irregular Pattern ◽  
Temperature Records ◽  
Earth’S Climate ◽  
Semi Arid Region ◽  
Semi Arid

Temperature records all over the world provide evidence that the earth’s climate is changing. To investigate changes in the extreme temperatures of semi-arid regions, we analyzed 33 years (1975-2008) of monthly maximum and minimum air temperatures for three weather stations located in Quixeramobim, Crateús and Barbalha Cities, Ceará, Brazil. The data sets were provided by INMET (Instituto Nacional de Meteorologia), Brazil. Dataset of each station was shared in decades to better understand the temperature tendency as well as to identify the warmest one. The two most recent decades were the warmest at all three stations investigated, and the highest temperature values were observed for Barbalha station. The highest increases of maximum temperature occurred during the dry season (May/Dec), and the warmest month was October, during which temperature increases of up to 1.63 °C were observed in the 1980s. The minimum temperature increased substantially during the rainy season (Jan/Apr) and during the coldest months (Jun/Jul). The highest increase of minimum temperature (3.08°C) was observed in July at the Barbalha station. The Quixeramobim station showed no significant increases in minimum temperature. The results indicate that temperature increases occur in an irregular pattern, suggesting that various regional agents affect changes in temperature.

scholarly journals Heat waves in Africa 1981–2015, observations and reanalysis

2016 ◽  
Author(s):  
G. Ceccherini ◽  
S. Russo ◽  
I. Ameztoy ◽  
A. F. Marchese ◽  
C. Carmona-Moreno
Keyword(s):  
Heat Wave ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Reanalysis Data ◽  
Maximum Temperature ◽  
Wave Analysis ◽  
Land Area ◽  
Spatial Coverage ◽  
Temperature Records ◽  
Numerical Index

Abstract. The purpose of this article is to show the extreme temperature regime of heat waves across Africa over recent years (1981–2015). Heat waves have been quantified using the Heat Wave Magnitude Index daily (HWMId), which merges the duration and the intensity of extreme temperature events into a single numerical index. The HWMId enables a comparison between heat waves with different timing and location, and it has been applied to maximum and minimum temperature records. The time series used in this study have been derived from: (1) observations from the Global Summary of the Day (GSOD); and (2) reanalysis data from ERA-INTERIM. The analysis show an increasing numbers of heat waves of both maxima and minima temperatures in the last decades. Results from heat wave analysis of maximum temperature (HWMIdtx) indicate an increase in intensity and frequency of extreme events. Specifically, from 1996 onwards it is possible to observe HWMIdtx spread with the maximum presence during 2006–2015. Between 2006 and 2015 the frequency (spatial coverage) of extreme heat waves had increased to 24.5 observations (60.1 % of land cover) per year, as compared to 12.3 (37.3 % of land area) per year in the period from 1981 to 2005 for GSOD stations (reanalysis).

scholarly journals Network of Automatic Weather Stations : Pseudo random burst sequence type

MAUSAM ◽  
2021 ◽  
Vol 63 (4) ◽  
pp. 587-606
Author(s):  
M.R. RANALKAR ◽  
R.P. MISHRA ◽  
ANJIT ANJAN ◽  
S. KRISHNAIAH
Keyword(s):  
Soil Temperature ◽  
Real Time ◽  
Minimum Temperature ◽  
Dew Point ◽  
Maximum Temperature ◽  
Earth Station ◽  
Level Pressure ◽  
Station Data ◽  
Hourly Rainfall ◽  
Weather Stations

A network of 125 Automatic Weather Stations (AWS) has been set up by India Meteorological Department (IMD) during the year 2006-07 across India. Each station is configured to measure air temperature, hourly maximum temperature, hourly minimum temperature, relative humidity, station level pressure, hourly rainfall and cumulative rainfall for the day, Wind speed and Wind direction. In addition to these parameters, 25 stations provide data for global solar radiation and soil temperature. Five stations also provide soil moisture in addition to soil temperature. Each station transmits a data stream at an interval of an hour in a Pseudo Random Burst Sequence (PRBS) manner via UHF transmitter and a dedicated meteorological satellite KALPANA-1/ INSAT-3A to the central AWS data receiving Earth Station facility established at IMD, Pune. Mean sea level pressure, dew point temperature, duration of bright sunshine and daily maximum & minimum temperature are derived at the receiving Earth Station. Data archival in near real time is done at the receiving Earth Station. Data dissemination in WMO code form is also done in near real time through Global Telecommunication System. This paper provides technical description of various sub-systems of PRBS type Indian Automatic Weather Station network including instrument, satellite transmission technique, sensor characteristics, siting and exposure conditions and performance of a representative station.

scholarly journals Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Distribution Area ◽  
Spatiotemporal Pattern ◽  
Climate Factors ◽  
Important Indicator ◽  
Fractional Vegetation Cover ◽  
Annual Minimum Temperature ◽  
Total Study Area

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.

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