Copula-based interpolation methods for air temperature data using collocated covariates

2018 ◽  
Vol 28 ◽  
pp. 128-140 ◽  
Author(s):  
Fakhereh Alidoost ◽  
Alfred Stein ◽  
Zhongbo Su
Keyword(s):  
Air Temperature ◽  
Temperature Data ◽  
Interpolation Methods

scholarly journals ASSESSMENT OF SOME METEOROLOGY DATA OF AVERAGE MONTHLY AIR TEMPERATURE OVER MONGOLIA USING DIGITAL ELEVATION MODEL (DEM) AND GIS TECHNIQUES

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 117-121
Author(s):  
B. Natsagdorj ◽  
S. Dalantai ◽  
E. Sumiya ◽  
Y. Bao ◽  
S. Bayarsaikhan ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Digital Elevation Model ◽  
Air Temperature ◽  
Statistical Significance ◽  
Meteorological Station ◽  
Temperature Data ◽  
Kriging Method ◽  
Interpolation Methods ◽  
Digital Elevation ◽  
Elevation Model

Abstract. The climate of Mongolia is a harsh continental climate with four distinctive seasons, high annual and diurnal temperature fluctuations, and low rainfall. Because of the country’s high altitude, it is generally colder than that of other countries in the same latitude. This study focuses on evaluating the suitability of two interpolation methods in terms of their accuracy at the air temperature data in Mongolia. Four data sets of air temperature from 1982 to 2019 in 60 meteorological stations located in Mongolia and elaborated from a 90 m resolution digital elevation model (DEM), latitude and longitude using two interpolation methods. ArcGIS is used to produce the spatially distributed air temperature data by using IDW and ordinary kriging. Three statistical methods are multiple regression, RMSE and bias, which showed that the IDW the best for this data from other methods by the results that have been obtained. Statistics on the latitude, longitude and surface elevation of each of the 37 years in Mongolia at 60 meteorological stations have been statistically valid with dependent coefficients at 95–99.9%. As the average air temperature, recorded at the meteorological stations, had a statistical correlation of −0.606 with latitude, 0.295 with longitude, and −0.432 with altitude, a multiple regression equation was developed and a highly accurate map for long terms air temperature covering 1982–2019 using interpolation IDW and Kriging method. Also, the highest RMSE value for maps used IDW was 1.38 while the lowest and average values were 0.03 and 0.44, respectively, and the highest bias was 1.21, lowest 0.95, and average 1.01. As opposed to, highest RMSE value for maps that used Kriging, was 6.16, lowest 0.27 and average 1.08 while highest bias was 1.29 and lowest was 0.85, with 1.01 as average. This demonstrates that IDW offers much better accuracy as opposed to Kriging and shows less bias errors. When the air temperature map that used the IDW method is compared against the meteorological station data the significance was 0.98 and when compared against ERA5 model results, significance was 0.95 showing strong statistical significance. Also, a comparison of air temperature map, processed by Kriging method and the meteorological station data shows 0.97 statistical significance, and comparison with ERA5 model shows (validation) 0.94 significance, which is very high. The mean value of the calculated temperature regression model in Mongolia and the root mean square error 0.02–0.09 for each station indicates that the estimation method is good and can be used in the future.

scholarly journals On the Spatial Patterns of Urban Thermal Conditions Using Indoor and Outdoor Temperatures

2021 ◽  
Vol 13 (4) ◽  
pp. 640
Author(s):  
Sadroddin Alavipanah ◽  
Dagmar Haase ◽  
Mohsen Makki ◽  
Mir Muhammad Nizamani ◽  
Salman Qureshi
Keyword(s):  
Heat Stress ◽  
Air Temperature ◽  
Temperature Data ◽  
Cold Spot ◽  
Temperature Pattern ◽  
Outdoor Temperature ◽  
Residential Units ◽  
Urban Settlements ◽  
The Impact ◽  
Indoor And Outdoor

The changing climate has introduced new and unique challenges and threats to humans and their environment. Urban dwellers in particular have suffered from increased levels of heat stress, and the situation is predicted to continue to worsen in the future. Attention toward urban climate change adaptation has increased more than ever before, but previous studies have focused on indoor and outdoor temperature patterns separately. The objective of this research is to assess the indoor and outdoor temperature patterns of different urban settlements. Remote sensing data, together with air temperature data collected with temperature data loggers, were used to analyze land surface temperature (outdoor temperature) and air temperature (indoor temperature). A hot and cold spot analysis was performed to identify the statistically significant clusters of high and low temperature data. The results showed a distinct temperature pattern across different residential units. Districts with dense urban settlements show a warmer outdoor temperature than do more sparsely developed districts. Dense urban settlements show cooler indoor temperatures during the day and night, while newly built districts show cooler outdoor temperatures during the warm season. Understanding indoor and outdoor temperature patterns simultaneously could help to better identify districts that are vulnerable to heat stress in each city. Recognizing vulnerable districts could minimize the impact of heat stress on inhabitants.

scholarly journals <i>Brief communication</i> "A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method"

2010 ◽  
Vol 17 (3) ◽  
pp. 269-272 ◽  
Author(s):  
S. Nicolay ◽  
G. Mabille ◽  
X. Fettweis ◽  
M. Erpicum
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Weather Forecast ◽  
Temperature Data ◽  
Temperature Time Series ◽  
Climatic Data ◽  
Statistical Validation ◽  
Confidence Levels ◽  
Temperature Time

Abstract. Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.

scholarly journals Historical and future temporal trends in the summer Urban Heat Island of Athens (Greece) 

2021 ◽  
Author(s):  
Tim van der Schriek ◽  
Konstantinos V. Varotsos ◽  
Dimitra Founda ◽  
Christos Giannakopoulos
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Temperature ◽  
Temporal Trends ◽  
Temperature Data ◽  
Climate Change Scenarios ◽  
Heat Island ◽  
Hot Days ◽  
The Future ◽  
Urban Heat

&lt;p&gt;Historical changes, spanning 1971&amp;#8211;2016, in the Athens Urban Heat Island (UHI) over summer were assessed by contrasting two air temperature records from established meteorological stations in urban and rural settings. When contrasting two 20-year historical periods (1976&amp;#8211;1995 and 1996&amp;#8211;2015), there is a significant difference in summer UHI regimes. The stronger UHI-intensity of the second period (1996&amp;#8211;2015) is likely linked to increased pollution and heat input. Observations suggest that the Athens summer UHI characteristics even fluctuate on multi-annual basis. Specifically, the reduction in air pollution during the Greek Economic Recession (2008-2016) probable subtly changed the UHI regime, through lowering the frequencies of extremely hot days (T&lt;sub&gt;max&lt;/sub&gt; &gt; 37 &amp;#176;C) and nights (T&lt;sub&gt;min&lt;/sub&gt; &gt; 26 &amp;#176;C).&lt;/p&gt;&lt;p&gt;Subsequently, we examined the future temporal trends of two different UHIs in Athens (Greece) under three climate change scenarios. A five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11&amp;#176; (~12 &amp;#215; 12 km) simulated air temperature data, spanning the period 1976&amp;#8211;2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5 and RCP8.5) were implanted in the simulations after 2005. The observed daily maximum and minimum air temperature data (T&lt;sub&gt;max&lt;/sub&gt; and T&lt;sub&gt;min&lt;/sub&gt;) from two historical UHI regimes (1976&amp;#8211;1995 and 1996&amp;#8211;2015, respectively) were used, separately, to bias-adjust the model simulations thus creating two sets of results.&lt;/p&gt;&lt;p&gt;This novel approach allowed us to assess future temperature developments in Athens under two different UHI intensity regimes. We found that the future frequency of days with T&lt;sub&gt;max&lt;/sub&gt; &gt; 37 &amp;#176;C in Athens was only different from rural background values under the intense UHI regime. There is a large increase in the future frequency of nights with T&lt;sub&gt;min&lt;/sub&gt; &gt; 26 &amp;#176;C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site.&lt;/p&gt;&lt;p&gt;This study shows a large urban amplification of the frequency of extremely hot days and nights which is likely forced by increasing air pollution and heat input. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be also effective in reducing urban temperatures during extreme heat events in Athens under all future climate change scenarios. Such policies therefore have multiple benefits, including: reducing electricity (energy) needs, improving living quality and decreasing heat- and pollution related illnesses/deaths.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Increase in Air Temperature in The Region of South Sumatra Province as the Indicator of Global Warming and the Effect on Transpiration of Lansium domesticum Corr.

2019 ◽  
Author(s):  
Ari Sugiarto ◽  
Hanifa Marisa ◽  
Sarno
Keyword(s):  
Global Warming ◽  
Air Temperature ◽  
Transpiration Rate ◽  
Temperature Increase ◽  
Secondary Data ◽  
Temperature Data ◽  
Randomized Design ◽  
Maximum Air Temperature ◽  
Lansium Domesticum ◽  
Minimum Air Temperature

Abstract Global warming is one of biggest problems faced in the 21st century. One of the impacts of global warming is that it can affect the transpiration rate of plants that °Ccur. This study purpose to see how much increase in air temperature that occurred in the region of South Sumatra Province and to know the effect of increase in ari temperature in the region of South Sumatra Province on transpiration rate of Lansium domesticum Corr. This study used a complete randomized design with 9 treatments (22.9 °C, 23.6 °C, 24.6 °C, 26.3 °C, 27 °C, 27.8 °C, 31.7 °C, 32.5 °C, and 32.9 °C) and 3 replications. Air temperature data as secondary data obtained from the Meteorology, Climatology and Geophysics Agency (MCGA) Palembang Climatology Station in South Sumatra Province. The measurement of transpiration rate is done by modified potometer method with additional glass box. The data obtained are presented in the form of tables and graphs. Transpiration rate (mm3/g plant/hour) at temperture 22.9 °C = 4.37, 23.6 °C = 7.03, 24.6 °C = 8.03, 26.3 °C = 10.11, 27 °C = 13.13, 27.8 °C = 17.87, 31.7 °C = 23.21, 32.5 °C= 25.45 and 32.9 °C= 27.24. At the minimum air temperature in the region of South Sumatra Province there is increase in air temperature of 1.5 °C, average daily air temperature increase 1.3 °C and maximum air temperature increase 1.2 °C.

Estimating Solar Irradiance for Crop Modeling Using Daily Air Temperature Data

1999 ◽  
Vol 91 (5) ◽  
pp. 845-851 ◽  
Author(s):  
Douglas G. Goodin ◽  
J. M. S. Hutchinson ◽  
Richard L. Vanderlip ◽  
M. C. Knapp
Keyword(s):  
Air Temperature ◽  
Solar Irradiance ◽  
Temperature Data ◽  
Crop Modeling

scholarly journals Air Temperature Change in the Southern Tarim River Basin, China, 1964–2011

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Benfu Zhao ◽  
Jianhua Xu ◽  
Zhongsheng Chen ◽  
Ling Bai ◽  
Peng Li
Keyword(s):  
Correlation Analysis ◽  
River Basin ◽  
Air Temperature ◽  
Negative Correlation ◽  
Kendall Test ◽  
Temperature Data ◽  
Tarim River ◽  
Tarim River Basin ◽  
Change Rate ◽  
Mann Kendall Test

The temperature data from 3 meteorological stations (Kashi, Ruoqiang, and Hotan) in the South of Tarim River Basin (STRB) during 1964–2011 were analyzed by Mann-Kendall test and correlation analysis. The results from Mann-Kendall test show that the surface temperature (ST), 850 hPa temperature (T850), and 700 hPa temperature (T700) exhibited upward trends, while 300 hPa temperature (T300) revealed a downward trend. On the whole, the change rate of ST, T850, T700, and T300 was 0.26~0.46°C/10a, 0.15~0.40°C/10a, 0.03~0.10°C/10a, and −0.38~−0.13°C/10a, respectively. For the periods, ST and T850 declined during 1964–1997 and then rose during 1998–2011. T700 declined during 1964–2005 and then rose during 2006–2011, while T300 rose from 1964 to 1970s and then declined. The results from correlation analysis show that T850 and T700 positively correlated with ST (P<0.01) at the all three stations and there was a negative correlation between T300 and ST at Hotan (P<0.1), while the correlation is not significant at Kashi and Ruoqiang. The results indicate that there were gradient differences in the response of upper-air temperature (UT) to ST change.

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