scholarly journals Evaluation of Infilling Methods for Time Series of Daily Temperature Data: Case Study of Limpopo Province, South Africa

Climate ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 86 ◽  
Author(s):  
Zakhele Phumlani Shabalala ◽  
Mokhele Edmond Moeletsi ◽  
Mphethe Isaac Tongwane ◽  
Sabelo Marvin Mazibuko

Incomplete climate records pose a major challenge to decision makers that utilize climate data as one of their main inputs. In this study, different climate data infilling methods (arithmetic averaging, inverse distance weighting, UK traditional, normal ratio and multiple regression) were evaluated against measured daily minimum and maximum temperatures. Eight target stations that are evenly distributed in Limpopo province, South Africa, were used. The objective was to recommend the best approach that results in lowest errors. The optimum number of buddy/neighboring weather stations required for best estimate for each of the approaches was determined. The evaluation indices employed in this study were the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), accuracy rate (AR) and mean bias error (MBE). The results showed high correlation (r > 0.92) for all the stations, different methods and varying number of neighboring stations utilised. The MAE [RMSE] for the best performing methods (multiple regression and UK traditional) of estimating daily minimum temperature and maximum temperature was less than 1.8 °C [2.3 °C] and 1.0 °C [1.6 °C], respectively. The AR technique showed the MR method as the best approach of estimating daily minimum and maximum temperatures. The other recommended methods are the UK traditional and normal ratio. The MBEs for the arithmetic averaging and inverse-distance weighing techniques are large, indicating either over- or underestimating of the air temperature in the province. Based on the low values for the error estimating statistics, these data infilling methods for daily minimum and maximum air temperatures using neighboring stations data can be utilised to complete the datasets that are used in various applications.

Irriga ◽  
2018 ◽  
Vol 22 (1) ◽  
pp. 177-193 ◽  
Author(s):  
Iug Lopes ◽  
Juliana Maria M De Melo ◽  
Brauliro Gonçalves Leal

ESPACIALIZAÇÃO DA TEMPERATURA DO AR PARA A REGIÃO DO SUBMÉDIO SÃO FRANCISCO  IUG LOPES¹; JULIANA MARIA MEDRADO DE MELO² E BRAULIRO GONÇALVES LEAL³ ¹ Departamento de Engenharia Agrícola, Universidade Federal Rural de Pernambuco, Rua Dom Manoel de Medeiros, Dois Irmão, CEP: 52171-900 – Recife, PE. [email protected]² Departamento de Agronomia, Universidade do Estado da Bahia, Rua Edgar Chastinet, s/n - São Geraldo, BA, 48905-680 – Juazeiro, BA. [email protected]³ Colegiado de Engenharia da Computação, Universidade Federal do Vale do São Francisco – Campus Juazeiro, Av. Antonio Carlos Magalhães, 510 Country Club, CEP: 48.902-300 – Juazeiro, BA. [email protected]  1 RESUMO  Dentre as variáveis meteorológicas requeridas para o cálculo do balanço hídrico destacam-se as temperaturas mínimas, médias e máximas do ar, que apresentam uma continuidade no quantitativo de distância e assim permitem de uma maneira mais simples a criação de campos contínuos utilizando métodos de interpolação espacial. O objetivo deste trabalho foi avaliar potências para o método de interpolação do Inverso da Potência da Distância (IPD) na espacialização de valores diários da temperatura no Submédio São Francisco, para os períodos de um ano, das estações do ano (inverno, primavera, verão e outono). Foram obtidos os parâmetros de potência do interpolador Inverso da Potência da Distância das temperaturas mínimas, médias e máximas a partir dos dados medidos em 14 estações meteorológicas automáticas do INMET em operação no Pólo de Desenvolvimento Petrolina-Juazeiro. Foram realizadas interpolações para as épocas: anual, inverno, primavera, verão e outono. A variação diária do erro relativo médio obtida, para a época ano, calculado utilizando os dados de temperatura mínima, média e máxima utilizando o valor da potência do interpolador foram iguais a 3,3; 3,4; e 3,4, respectivamente. Os valores de erro médio foram pequenos quando comparados com o erro instrumental. Palavras-chave: interpolação, validação cruzada, estação meteorológica  LOPES, I; MELO, J. M. M.; LEAL, B. G. SPATIALIZATION OF AIR TEMPERATURE TO THE REGION OF SUBMEDIO SÃO FRANCISCO  2 ABSTRACT Among the meteorological variables required for the calculation of the water balance are the temperatures, which present a continuity in the quantitative distance and thus allow in a simpler way the creation of continuous fields using spatial interpolation methods. The objective of this work was to evaluate the power of the Inverse Distance Power (IPD) in the spatialization of daily values of temperature in the Submedia of São Francisco, for the one-year periods of the seasons (winter, spring, summer it's fall). The power parameters of the Inverse Distance Power Interpolator were obtained from the minimum, average and maximum temperatures from the data measured in 14 INMET automatic meteorological stations operating at the Petrolina-Juazeiro Development Pole. Interpolations were performed for annual, winter, spring, summer and fall seasons. The daily variation of the average relative error obtained for the year time, calculated using the data of minimum, average and maximum temperature using the value of the power of the interpolator were equal to 3.3; 3.4; and 3.4, respectively. The mean error values were small when compared to instrumental error. Keywords: interpolation, validation cross, meteorological station


Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 147
Author(s):  
Abubakar Hadisu Bello ◽  
Mary Scholes ◽  
Solomon W. Newete

The majority of people in South Africa eat maize, which is grown as a rain-fed crop in the summer rainfall areas of the country, as their staple food. The country is usually food secure except in drought years, which are expected to increase in severity and frequency. This study investigated the impacts of rainfall and minimum and maximum temperatures on maize yield in the Setsoto municipality of the Free State province of South Africa from 1985 to 2016. The variation of the agroclimatic variables, including the Palmer stress diversity index (PSDI), was investigated over the growing period (Oct–Apr) which varied across the four target stations (Clocolan, Senekal, Marquard and Ficksburg). The highest coefficients of variance (CV) recorded for the minimum and maximum temperatures and rainfall were 16.2%, 6.2% and 29% during the growing period. Non-parametric Mann Kendal and Sen’s slope estimator were used for the trend analysis. The result showed significant positive trends in minimum temperature across the stations except for Clocolan where a negative trend of 0.2 to 0.12 °C year−1 was observed. The maximum temperature increased significantly across all the stations by 0.04–0.05 °C year−1 during the growing period. The temperature effects were most noticeable in the months of November and February when leaf initiation and kernel filling occur, respectively. The changes in rainfall were significant only in Ficksburg in the month of January with a value of 2.34 mm year−1. Nevertheless, the rainfall showed a strong positive correlation with yield (r 0.46, p = < 0.05). The overall variation in maize production is explained by the contribution of the agroclimatic parameters; the minimum temperature (R2 0.13–0.152), maximum temperature (R2 0.214–0.432) and rainfall (R2 0.17–0.473) for the growing period across the stations during the study period. The PSDI showed dry years and wet years but with most of the years recording close to normal rainfall. An increase in both the minimum and maximum temperatures over time will have a negative impact on crop yield.


1988 ◽  
Vol 78 (2) ◽  
pp. 235-240 ◽  
Author(s):  
J. N. Matthiessen ◽  
M. J. Palmer

AbstractIn studies in Western Australia, temperatures in air and one- and two-litre pads of cattle dung set out weekly and ranging from one to 20 days old were measured hourly for 438 days over all seasons, producing 1437 day x dung-pad observations. Daily maximum temperatures (and hence thermal accumulation) in cattle dung pads could not be accurately predicted using meteorological data alone. An accurate predictor of daily maximum dung temperature, using multiple regression analysis, required measurement of the following factors: maximum air temperature, hours of sunshine, rainfall, a seasonal factor (the day number derived from a linear interpolation of day number from day 0 at the winter solstice to day 182 at the preceding and following summer solstices) and a dung-pad age-specific intercept term, giving an equation that explained a 91·4% of the variation in maximum dung temperature. Daily maximum temperature in two-litre dung pads was 0·6°C cooler than in one-litre pads. Daily minimum dung temperature equalled minimum air temperature, and daily minimum dung temperatures occurred at 05.00 h and maximum temperatures at 14.00 h for one-litre and 14.30 h for two-litre pads. Thus, thermal summation in a dung pad above any threshold temperature can be computed using a skewed sine curve fitted to daily minimum air temperature and the calculated maximum dung temperature.


1966 ◽  
Vol 17 (1) ◽  
pp. 55 ◽  
Author(s):  
JG Baldwin

Time of bud burst for sultana vines at Merbein has been closely related to sums of daily temperatures at four periods during bud dormancy by a multiple regression covering 17 years, the result being supported by field trials of vine heating. Bud burst is delayed by higher daily maximum temperatures in May. Higher daily minimum temperatures in late June and in July, or higher daily maximum temperatures in August and until burst, are associated with earlier bud burst. Studies of bud dry weight and moisture have suggested that the change-over between the association of higher daily minimum temperatures and higher daily maximum temperatures with earlier bud burst occurs at a specified sum of degrees by which daily minimum temperatures fall below 50°F, giving dates ranging from July 5 to August 7 for the years of the regression. This appears to be the beginning of imposed dormancy. Use of the regression for predicting time of bud burst is discussed.


2020 ◽  
Vol 13 (1) ◽  
pp. 246-256
Author(s):  
Lungile Makondo ◽  
Abiodun Adeola ◽  
Thabo Makgoale ◽  
Joel Botai ◽  
Omolola Adisa ◽  
...  

Background: Malaria, though curable, continues to be a major health and socioeconomic challenge. Malaria cases have been on the rise for the last two years in the malaria-endemic region of South Africa. Thulamela Municipality in Limpopo, South Africa, which falls within several municipalities at Vhembe district that are affected by malaria. About 33,448 malaria cases were reported over a period of 20 years (1998 January-2018 December). Objective: The study aims to determine the influence of climate on the spatiotemporal distribution of malaria cases in Thulamela Municipality for the last two decades (1998 January-2018 December). Methods: The analysis is divided into two sections, including temporal and spatial distribution of malaria cases, and the correlating climatic and environmental factors. Time series analysis is conducted to determine the variations of malaria and climate. Malaria and climatic factors (rainfall, maximum temperature, minimum temperature) were globally correlated using matrix scatterplot spearman correlation with a certain significance level. The Ordinary Least Squares (OLS) regression was performed to determine the significant climate factors that locally affect the spatial distribution of malaria cases. The local environmental factor (rivers) was analyzed using buffering and terrain analysis. Results: A positive spearman correlation of the time series was found with the significance level of 0.01. The climate variables were not strongly significant to the spatial distribution of malaria at the village level. The villages which continued to record high malaria cases were in proximity to rivers by 2km. The Thulamela municipality falls within 20-30°C, which is essential for the incubation of mosquitoes and transmission of malaria. The areas receiving about 125 to 135 mm of total monthly rainfall record high malaria cases. The temperature, rainfall, and rivers are important factors for malaria transmission. Conclusion: Knowledge of the drivers of the spatiotemporal distribution of malaria is essential for a predicting system to enhance effective malaria control in communities such as the Thulamela municipality.


2004 ◽  
Vol 17 (22) ◽  
pp. 4453-4462 ◽  
Author(s):  
Binhui Liu ◽  
Ming Xu ◽  
Mark Henderson ◽  
Ye Qi ◽  
Yiqing Li

Abstract In analyzing daily climate data from 305 weather stations in China for the period from 1955 to 2000, the authors found that surface air temperatures are increasing with an accelerating trend after 1990. They also found that the daily maximum (Tmax) and minimum (Tmin) air temperature increased at a rate of 1.27° and 3.23°C (100 yr)−1 between 1955 and 2000. Both temperature trends were faster than those reported for the Northern Hemisphere, where Tmax and Tmin increased by 0.87° and 1.84°C (100 yr)−1 between 1950 and 1993. The daily temperature range (DTR) decreased rapidly by −2.5°C (100 yr)−1 from 1960 to 1990; during that time, minimum temperature increased while maximum temperature decreased slightly. Since 1990, the decline in DTR has halted because Tmax and Tmin increased at a similar pace during the 1990s. Increased minimum and maximum temperatures were most pronounced in northeast China and were lowest in the southwest. Cloud cover and precipitation correlated poorly with the decreasing temperature range. It is argued that a decline in solar irradiance better explains the decreasing range of daily temperatures through its influence on maximum temperature. With declining solar irradiance even on clear days, and with decreases in cloud cover, it is posited that atmospheric aerosols may be contributing to the changing solar irradiance and trends of daily temperatures observed in China.


Author(s):  
Camila Bermond Ruezzene ◽  
Renato Billia de Miranda ◽  
Talyson de Melo Bolleli ◽  
Frederico Fábio Mauad

The study of the hydric regime of rainfall helps in management analysis and decision-making in hydrographic basins, but a fundamental condition is the need for continuous time series of data. Therefore, this study compared gap filling methods in precipitation data and validated them using robust statistical techniques. Precipitation data from the municipality of Itirapina, which has four monitoring stations, were used. Four gap filling techniques were used, namely: normal ratio method, inverse distance weighting, multiple regression and artificial neural networks, in the period from 1979 to 1989. For validation and performance evaluation, the coefficient of determination (R²), mean absolute error (MAE), mean squared error (RMSE), Nash-Sutcliffe coefficient (Nash), agreement index (D), confidence index were used (C) and through non-parametric techniques with Mann-Witney and Kruskal-Wallis test. Excellent performances of real data were verified in comparison with estimated data, with values above 0.8 of the coefficient of determination (R²) and of Nash. Kruskal-Wallis and Mann-Whitney tests were not significant in Stations C1 and C2, demonstrating that there is a difference between real and estimated data and between the proposed methods. It was concluded that the multiple regression and neural network methods showed the best performance. From this study, efficient tools were found to fill the gap, thus promoting better management and operation of water resources. Keywords: artificial neural networks, inverse distance weighting, multiple regression, normal ratio method.


2011 ◽  
Vol 50 (8) ◽  
pp. 1654-1665 ◽  
Author(s):  
Ron F. Hopkinson ◽  
Daniel W. McKenney ◽  
Ewa J. Milewska ◽  
Michael F. Hutchinson ◽  
Pia Papadopol ◽  
...  

AbstractOn 1 July 1961, the climatological day was redefined to end at 0600 UTC at all principal climate stations in Canada. Prior to that, the climatological day at principal stations ended at 1200 UTC for maximum temperature and precipitation and 0000 UTC for minimum temperature and was similar to the climatological day at ordinary stations. Hutchinson et al. reported occasional larger-than-expected residuals at 50 withheld stations when the Australian National University Spline (ANUSPLIN) interpolation scheme was applied to daily data for 1961–2003, and it was suggested that these larger residuals were in part due to the existence of different climatological days. In this study, daily minimum and maximum temperatures at principal stations were estimated using hourly temperatures for the same climatological day as local ordinary climate stations for the period 1953–2007. Daily precipitation was estimated at principal stations using synoptic precipitation data for the climatological day ending at 1200 UTC, which, for much of the country, was close to the time of the morning observation at ordinary climate stations. At withheld principal stations, the climatological-day adjustments led to the virtual elimination of large residuals in maximum and minimum temperature and a marked reduction in precipitation residuals. Across all 50 withheld stations the climatological day adjustments led to significant reductions, by around 12% for daily maximum temperature, 15% for daily minimum temperature, and 22% for precipitation, in the residuals reported by Hutchinson et al.


2009 ◽  
Vol 48 (10) ◽  
pp. 2160-2168 ◽  
Author(s):  
Lucie A. Vincent ◽  
Ewa J. Milewska ◽  
Ron Hopkinson ◽  
Leslie Malone

Abstract On 1 July 1961, the climatological day was redefined to end at 0600 UTC (coordinated universal time) at all synoptic (airport) stations in Canada. Prior to that, the climatological day ended at 1200 UTC for maximum temperature and 0000 UTC for minimum temperature. This study shows that the redefinition of the climatological day in 1961 has created a cold bias in the annual and seasonal means of daily minimum temperatures across the country while the means of daily maximum temperatures were not affected. Hourly temperatures taken at 121 stations for 1953–2007 are used to determine the magnitude of the bias and its spatial variation. It was found that the bias is more pronounced in the eastern regions; its annual mean varies from −0.2° in the west to −0.8°C in the east. Not all days are affected by this change in observing time, and the annual percentage of affected days ranges from 15% for locations in the west to 38% for locations in the east. An approach based on hourly values is proposed for adjusting the affected daily minimum temperatures over 1961–2007. The adjustment on any individual day varies from 0.5° to 12.5°C. The impact of the adjustment is assessed by examining the trends in the annual mean of the daily minimum temperatures for 1950–2007. Overall, with the adjustment, the trends are becoming either more positive or are reversing from negative to positive, and they have changed by as much as 1°C in numerous locations in the eastern regions.


Geografie ◽  
2008 ◽  
Vol 113 (4) ◽  
pp. 372-382
Author(s):  
Zbigniew W. Kundzewicz ◽  
Damian Józefczyk

This paper examines temperature-related climate extremes in the unique long-term gapfree record at the Secular Meteorological Station in Potsdam. Increasing tendencies in daily minimum temperature in winter and daily maximum temperature in summer, as well as monthly means of daily minimum temperatures in winter months and of daily maximum temperatures in summer months are illustrated. Also the numbers of hot days and of summer days (with maximum daily temperature exceeding 30 °C and 25 °C, respectively) have been increasing. In agreement with warming of winter minimum temperatures, the numbers of frost days (with minimum daily temperature below 0 °C) and of ice days (with maximum daily temperature below 0 °C) have been decreasing. However, low correlation coefficient and huge scatter illustrate strong natural variability, so that the occurrence of extremes departs from the general underlying tendency.


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