scholarly journals Five Decadal Trends in Averages and Extremes of Rainfall and Temperature in Sri Lanka

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
G. Naveendrakumar ◽  
Meththika Vithanage ◽  
Hyun-Han Kwon ◽  
M. C. M. Iqbal ◽  
S. Pathmarajah ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Global Climate ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Southwest Monsoon ◽  
Maximum Temperature ◽  
Daily Temperature Range ◽  
Average Temperature ◽  
Mann Kendall Test ◽  
Annual Average Temperature

In this study, we used a comprehensive set of statistical metrics to investigate the historical trends in averages and extremes of rainfall and temperature in Sri Lanka. The data consist of 55 years (1961–2015) of daily rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) records from 20 stations scattered throughout Sri Lanka. The linear trends were analyzed using the nonparametric Mann–Kendall test and Sen–Theil regression. The prewhitening method was first used to remove autocorrelation from the time series, and the modified seasonal Mann–Kendall test was then applied for the seasonal data. The results show that, during May, 15% of the stations showed a significant decrease in wet days, which may be due to the delayed southwest monsoon (SWM) to Sri Lanka. A remarkable increase in the annual average temperature of Tmin and Tmax was observed as 70% and 55% of the stations, respectively. For the entire period, 80% of the stations demonstrated statistically significant increases of Tmin during June and July. The daily temperature range (DTR) exhibited a widespread increase at the stations located within the southwestern coast region of Sri Lanka. Although changes in global climate, teleconnections, and local deforestation in recent decades at least partially influence the trends observed in Sri Lanka, a formal trend attribution study should be conducted.

scholarly journals Rainfall Dynamics of Terengganu Malaysia and Its Recent Trends Analysis Using the Mann-Kendall Test.

2014 ◽  
Vol 4 (2) ◽  
pp. 372-381 ◽  
Author(s):  
Musa Garba Abdullahi ◽  
Mohd Ekhwan Toriman ◽  
Mohd Barzani Gasim ◽  
Hafizan Juahir
Keyword(s):  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Southwest Monsoon ◽  
The State ◽  
Northeast Monsoon ◽  
Monsoon Period ◽  
Mann Kendall Test ◽  
Recent Trends ◽  
Increasing Trends

This study investigated the pattern and trends of the daily rainfall data in Terengganu Malaysia based on seasonal rainfall indices. The statistics of rainfall indices were calculated in terms of their means for seven stations in Terengganu Malaysia for the period 2000 to 2012. The findings indicate that the trend in the study area has no significant changes in stations (1, 4 and 6) while station (2, 3, 5 and 7) shows significant changes and southwest monsoon had the greatest impact on the whole stations, particularly in characterizing the rainfall pattern of the area. During this season, the study area could be considered as the wettest region since all rainfall indices tested are higher than in other neighboring state of the Peninsula. Otherwise, the northwest of the area is denoted as the driest part of the state during the northeast monsoon period. The northwest of the state is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks some part of the region from receiving heavy rainfall. On the other hand, it is found that the areas with lowlands are strongly characterized by the northeast monsoonal flow.The results of the Mann-Kendall test, shows that, trends of the total amount of rainfall during the southwest monsoon decrease at some of the stations. The rainfall intensity increases in contrast, increasing trends in the total amount of rainfall were observed at three stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for the combined stations in both seasons indicate that there are no significant changes in trends during the extreme events for the Terengganu Malaysia. However, a smaller number of significant trends were found for extreme intensity. 

scholarly journals Homogeneity Test and Correction of Daily Temperature and Precipitation Data (1978–2015) in North China

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Lingling Shen ◽  
Li Lu ◽  
Tianjie Hu ◽  
Runsheng Lin ◽  
Ji Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
North China ◽  
Maximum Temperature ◽  
Homogeneity Test ◽  
Climate Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Daily Data ◽  
Before And After ◽  
Annual Average Temperature

Homogeneity of climate data is the basis for quantitative assessment of climate change. By using the MASH method, this work examined and corrected the homogeneity of the daily data including average, minimum, and maximum temperature and precipitation during 1978–2015 from 404/397 national meteorological stations in North China. Based on the meteorological station metadata, the results are analyzed and the differences before and after homogenization are compared. The results show that breakpoints are present pervasively in these temperature data. Most of them appeared after 2000. The stations with a host of breakpoints are mainly located in Beijing, Tianjin, and Hebei Province, where meteorological stations are densely distributed. The numbers of breakpoints in the daily precipitation series in North China during 1978–2015 also culminated in 2000. The reason for these breakpoints, called inhomogeneity, may be the large-scale replacement of meteorological instruments after 2000. After correction by the MASH method, the annual average temperature and minimum temperature decrease by 0.04°C and 0.06°C, respectively, while the maximum temperature increases by 0.01°C. The annual precipitation declines by 0.96 mm. The overall trends of temperature change before and after the correction are largely consistent, while the homogeneity of individual stations is significantly improved. Besides, due to the correction, the majority series of the precipitation are reduced and the correction amplitude is relatively large. During 1978–2015, the temperature in North China shows a rise trend, while the precipitation tends to decrease.

scholarly journals INFLUENCE OF TEMPERATURE AND ALTITUDE ON THE EXPANSION OF COFFEE CROPS IN MATAS DE MINAS, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 157-165
Author(s):  
Karine Rabelo Oliveira ◽  
Williams Pinto Marques Ferreira ◽  
Humberto Paiva Fonseca ◽  
Cecília Fátima Souza
Keyword(s):  
Area Under The Curve ◽  
Growth Potential ◽  
Maximum Temperature ◽  
Annual Average ◽  
Jackknife Test ◽  
Average Temperature ◽  
Annual Minimum Temperature ◽  
Precipitation Seasonality ◽  
Omission Rate ◽  
Annual Average Temperature

Coffee is among the most significant products in Brazil. Minas Gerais is the largest state producer of Arabica coffee. Coffee activity has excellent growth potential, which justifies the identification of new areas for expansion of the culture. This study aimed to determine factors that affect the spatial distribution of coffee plantations the most, as well as to identify areas with a greater aptitude for its expansion in the region of the Matas de Minas (63 municipalities). The MaxEnt software was used to elaborate a model capable of describing the area with the highest potential for estimating the probability of coffee adequacy. The elaboration of the model considered the records of occurrence, climatic and topographic variables of Matas de Minas, the second largest state producing region. The area under the curve (AUC), the omission rate and the Jackknife test were used for validation and analysis of the model. The model was accurate with an AUC of 0.816 and omission rate of 0.54% for the ‘test’. It was identified that the potential distribution of coffee in Matas de Minas is determined by changes in the annual maximum temperature, although it did not generate a significant gain when omitted, accounting for a considerable loss in the model. However, the most influential variables on the delineation of distribution were, the altitude and the annual average temperature. The most favorable areas for expansion of coffee culture in the Matas de Minas were found in the vicinity of the region of Alto Caparaó.Abbreviations used: A1 (altitude); A2 (maximum annual temperature); A3 (annual minimum temperature); BIO 1 (annual average temperature 1); BIO 4 (temperature seasonality), BIO 12 (annual precipitation); BIO 15 (precipitation seasonality); csv (comma-separated values); AUC (area under the curve).

scholarly journals Effect of climate change and deforestation on vector borne diseases in the North-Eastern Indian state of Mizoram bordering Myanmar

2020 ◽  
Author(s):  
Balasubramani Karuppusamy ◽  
Devojit Kumar Sarma ◽  
Pachuau Lalmalsawma ◽  
Lalfakzuala Pautu ◽  
Krishanpal Karmodiya ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Forest Cover ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Monsoon Period ◽  
Vector Borne Diseases ◽  
Sen’S Slope ◽  
Mann Kendall Test ◽  
Vector Borne

Abstract Background Malaria and dengue are the two major vector-borne diseases in Mizoram. Malaria is endemic in Mizoram, and dengue was first reported only in 2012. It is well documented that climate change has a direct influence on the incidence and spread of vector-borne diseases. The study was designed to study the trends and impact of climate variables (temperature, rainfall and humidity) in the monsoon period (May to September) and deforestation on the incidence of dengue and malaria in Mizoram. Methods Temperature, rainfall and humidity data of Mizoram from 1979–2013 were obtained from the National Centers for Environmental Prediction Climate Forecast System Reanalysis and analyzed. Forest cover data of Mizoram was extracted from India State of Forest Report (IFSR) and Land Processes Distributed Active Archive Centre. Percent tree cover datasets of Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer missions were also used to study the association between deforestation and incidence of vector-borne diseases. The study used non-parametric tests to estimate long-term trends in the climate (temperature, rainfall, humidity) and forest cover variables. The trend and its magnitude are estimated through Mann-Kendall test and Sen's slope method. Year-wise dengue and malaria data were obtained from the State Vector Borne Disease Control Program, Mizoram. Results The Mann-Kendall test indicates that compared to maximum temperature, minimum temperature during the monsoon period is increasing (p < 0.001). The Sen’s slope estimation also shows an average annual 0.020C (0.01–0.03 at 95% CI) monotonic increasing trend of minimum temperature. The residuals of Sen’s estimate show that temperature is increasing at an average of about 0.10C/year after 2007.Trends indicate that both rainfall and humidity are increasing (p <. 0.001); on an average, there is a 20.45 mm increase in monsoon rainfall per year (5.90–34.37 at 95% CI), while there is a 0.08% (0.02–0.18 at 95% CI) increase in relative humidity annually. IFSR data shows that there is an annual average decrease of 162 sq.km (272.81–37.53 at 95% CI, p < 0.001) in the dense forest cover. Mizoram in 2012 was the last state in India to report the incidence of dengue. Malaria transmission continues to be stable in Mizoram; compared to 2007, the cases have increased in 2019. Conclusion Over the study period, there is an ~ 0.80C rise in the minimum temperature in the monsoon season which could have facilitated the establishment of Aedes aegypti, the major dengue vector in Mizoram. In addition, the increase in rainfall and humidity may have also helped the biology of Ae. aegypti. Deforestation could be one of the major factors responsible for the consistently high number of malaria cases in Mizoram.

scholarly journals Comparison of Statistical, Graphical, and Wavelet Transform Analyses for Rainfall Trends and Patterns in Badulu Oya Catchment, Sri Lanka

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ashika M. Ruwangika ◽  
Anushka Perera ◽  
Upaka Rathnayake
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Trend Analysis ◽  
Wavelet Transforms ◽  
Kendall Test ◽  
Discrete Wavelet ◽  
Rainfall Trend ◽  
Analysis Methods ◽  
Rainfall Trends ◽  
Mann Kendall Test

Climate change has adversely influenced many activities. It has increased the intensified precipitation events in some places and decreased the precipitation in some other places. In addition, some research studies revealed that the climate change has moved seasons in the temporal scale. Therefore, the changes can be seen in both spatial and temporal scales. Thus, analyzing climate change in the localized environments is highly essential. Rainfall trend analysis in a localized catchment can improve many aspects of water resource management not only to the catchment itself but also to some of the related other catchments. This research is carried to identify the rainfall trends in Badulu Oya catchment, Sri Lanka. The catchment is important as it is in the intermediate climate zone and rich in agricultural productions. Four rain gauges (namely, Badulla, Kandekatiya, Lower Spring Valley, and Ledgerwatte Estate) were used to analyze the rainfalls in the resolutions of monthly, seasonally, and annually. 30-year monthly cumulative rainfall data for the above four gauging stations are analyzed using various standard tests. Nonparametric tests including Mann–Kendall test and sequential Mann–Kendall test and innovative trend analysis methods are used to identify the potential rainfall trends in Badulu Oya catchment. In addition, continuous wavelet transforms and discrete wavelet transforms tests are carried out to check the patterns on rainfall to the catchment. The trend analysis methods are compared against each other to identify the better technique. The results reveal that the nonparametric Mann–Kendall test is powerful to produce the statistically significant rainfall trends in qualitative and quantitative manner. Mann–Kendall analysis shows a positive trend to Ledgerwatte Estate in monthly (3.7 mm in February and 7.4 mm in October), seasonal (6.9 mm in the 2ndintermonsoon), and annual (3 mm annually) scales. However, the analysis records one decreasing rainfall trend to Kandekatiya (8.1 mm in December) only in monthly scale. Nevertheless, it was found that the graphical method can be easily used in qualitative analysis, while discrete wavelet transformations are efficient in identifying the rainfall patterns effectively.

scholarly journals Effect of Climatic Factors on the Spread of COVID-19 Pandemic: Evidence from Tunisia

2020 ◽  
pp. 107-121
Author(s):  
Fatma Aribi ◽  
Mongi Sghaier
Keyword(s):  
Confidence Level ◽  
Social Life ◽  
Climatic Factors ◽  
Virus Disease ◽  
Kendall Test ◽  
Climatic Variables ◽  
Health Economy ◽  
Maximum Temperature ◽  
Mean Temperature ◽  
Mann Kendall Test

Since the end of December 2019, the COrona VIrus Disease (COVID-19) is sweeping the world and has caused huge damage to the health, economy, and social life of the communities. Meteorological variables are among the factors influencing the spread of contagious diseases. The aim of this study was to explore the correlation between climatic parameters and COVID-19 spread in Tunisia. To do this, we designed a daily dataset including the number of confirmed and deaths cases, minimum temperature (°C), maximum temperature (°C), mean temperature (°C), rainfall (mm), and wind speed (km/h) during the period of June 27 to October 22, 2020. To investigate the association between climatic variables and COVID-19, the Spearman correlation test was employed. The Mann-Kendall test has been also used to detect the direction of the COVID-19 trend. As many researchers have demonstrated that the incubation period of the ongoing pandemic varies from 1 to 14 days, the correlation of each parameter with COVID-19 was examined on the day of the confirmed cases and deaths, and before 7 and 14 days.  The results showed that out of the five selected climatic variables, four variables were correlated with COVID-19 cases and deaths (statistically significant at a 99% confidence level). A positive correlation of the rainfall with COVID-19 confirmed cases and deaths was observed, the highest was 14 days ago. However, negative correlations were observed for minimum, maximum, and mean temperature, the highest was on the day of the incident. Besides, the Mann-Kendall test showed increasing trends for COVID-19 cases and deaths (statistically significant at a 99% confidence level). The results of this study might be useful to understand the role of climatic factors in the spread of COVID-19 and provide insights for healthcare policymakers to well manage this global pandemic.

scholarly journals Characteristics of Climate Change in the Lancang-Mekong Sub-Region

Climate ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 115 ◽  
Author(s):  
Han Li ◽  
Wei Song
Keyword(s):  
Climate Change ◽  
Wavelet Analysis ◽  
Linear Trend ◽  
Kendall Test ◽  
Annual Precipitation ◽  
Climatic Data ◽  
Annual Average ◽  
Average Temperature ◽  
Mean Temperature ◽  
Annual Average Temperature

The Lancang-Mekong River is an important international river in Southeastern Asia. In recent years, due to climate change, natural disasters, such as drought and flooding, have frequently occurred in the region, which has a negative effect on the sustainable development of the social economy. Due to the lack of meteorological monitoring data in the six countries across the region, the study of the characteristics of climate change in this area is still scarce. In this paper, we analyze the characteristics of climate change in the Lancang-Mekong sub-region (LMSR) during 2020–2100 based on the climatic data of CMIP5, using the linear trend rate method, cumulative anomaly method, the Mann–Kendall test, and Morlet wavelet analysis. The results showed that the annual mean temperature and annual precipitation in the LMSR increased significantly. The annual average temperature in this area increased at a rate of 0.219 °C/10a (p < 0.05) and 0.578 °C/10a (p < 0.05) in the RCP4.5 and RCP8.5 scenarios, respectively; the annual precipitation in the area was 29.474 mm/10a (p < 0.05) and 50.733 mm/10a (p < 0.05), respectively. The annual average temperature in the region changed abruptly from low to high temperatures in 2059 for the RCP4.5 scenario and 2063 for RCP8.5. The annual precipitation in the area changed from less to more in 2051 for the RCP4.5 scenario and 2057 for RCP8.5. The results of wavelet analysis showed that the annual mean temperature in the LMSR had no significant change period at the 95% confidence level under the scenario of RCP4.5 and RCP8.5. Under the scenario of RCP4.5 and RCP8.5, the annual precipitation had a significant 3.5-year and 2.5-year periodicity, respectively. Extreme climate events tended to increase against the background of global warming, especially in high emission scenarios.

Sign in / Sign up

Export Citation Format

Share Document