Daily rainfall records for 50 years (1961 to 2010) were used to determine the start and end of rainy seasons in the southwestern region of Sri Lanka. The study was based on data records obtained from two weather stations in Colombo and Galle situated in the western and southern coastal belts of Sri Lanka, respectively, that have two growing seasons, Yala and Maha. The start and end dates were determined by using a method that is based on cumulative rainfall measured during a season. Substantial interannual variability is seen in start and end of rainy seasons in this study. For the Yala season, the mean start and end dates are in the standard weeks 12.0 ± 2.3 and 24.1 ± 2.0 (March 24 to June 20), respectively. For the Maha season, the mean start and end dates are in the standard weeks 35.4 ± 2.0 and 49.6 ± 2.0 (September 5 to December 15), respectively. The mean durations of the rainy season for Yala and Maha are 12.1 ± 2.6 weeks and 14.2 ± 2.3 weeks respectively. The start date and the duration of the rainy season for both Yala and Maha are correlated, leading to early start dates resulting in longer rainy seasons. It can be concluded from this study that it is possible to use daily rainfall records to determine the mean start and end dates of rainy seasons in the southwestern region of Sri Lanka.
Long-term changes in extreme air temperature at Nuwara Eliya (a high-elevation observatory located in the western slopes of the central mountainous region of Sri Lanka) are examined. The present work is limited to a linear trend analysis of daily maximum and minimum air temperature series of the period 1926–2015. The statistical significance of the trend is estimated using the Mann-Kendall test. There is a significant reduction in the diurnal temperature range (DTR) in Nuwara Eliya. The magnitude of the reduction is −0.23 degC per decade and is due to the increase in the daily minimum air temperature. No significant increase or decrease in the daily maximum air temperature was evident from the data. There is a strong inverse correlation between the standard deviation (which is related to the temperature variability) and the mean daily minimum air temperature. The increase in minimum temperature is not uniform throughout the year as the minimum temperature of the cold season has increased, while it has remained the same for the warm season, thereby reducing the overall DTR.
Many parts of Sri Lanka are vulnerable to extreme rainfall events leading to floods and droughts. This study was focused on a trend analysis of climate extremes derived from daily rainfall records. The daily rainfall data from 13 meteorological stations representing different geographical regions in Sri Lanka for the period 1961–2010 were chosen. The analysis was carried out separately for summer half year (March-August) and winter half year (September-February) to capture the possible changes in two growing seasons, Yala and Maha. Magnitudes of trends were derived using linear regression analysis while the statistical significance was determined using the Mann-Kendall test. Spatial maps were used to study the regional differences in climate extremes. Extreme rainfall events were found to be isolated events without coherent increasing or decreasing trends. However, statistically significant increasing (decreasing) trends were observed for number of dry days (wet days) ranging from 1.1 to 3.1 days/decade in most parts of the island during the summer half year, except for the coastal areas of the dry zone. No increasing or decreasing trends in extremes were observed for the winter half year. Based on the analysis, it was concluded that there is widespread climate change leading to increasing (decreasing) dry days (wet days) during the summer half year receiving rainfall predominantly from the South-West monsoon. However, mixed results were obtained for the winter half year.
Seventeen years of remotely sensed satellite mounted Lightning Imaging Sensor (LIS) data were used to determine the characteristics of lightning activities over Sri Lanka. From 1998 to 2014, there were 12.5 million lightning flashes over the land mass covered by Sri Lanka. There is an increasing trend in the intensity of lightning activities with 22,000 flashes year−1. The annual cycle of lightning flashes shows a clear spatial difference of lightning activities during the southwest and northeast monsoon seasons. The highest occurrence of lighting activities is confined to the highly populated western region of the island while the coastal areas in the northern and eastern regions and central hills show relatively low occurrences. The estimated maximum cloud to ground lightning flash density was 53 flashes year−1 km−2 and the average being 7.7 flashes year−1 km−2. The density of lightning in the wet zone tends to be twice as much compared to the dry zone. The onset and retreat of lightning seasons are February 25 through May 15 for the warm season which coincides with the first inter-monsoon season and July 31 through November 19 for the cold season which coincides with the latter part of the southwest monsoon season and second inter-monsoon season. Based on thunder day measurements, it is shown that a simple linear relationship can be used to estimate lightning flash densities from thunder days. We have also examined the relationship between lightning flash activities and sea surface temperature over the Arabian Sea and the Bay of Bengal and conclude that sea surface temperature can be used as a proxy to estimate change in lightning activities as sea surface temperatures have strong persistence in the temporal characteristics.
The accuracy of reconstructing missing daily temperature extremes in the Jaffna climatological station, situated in the northern part of the dry zone of Sri Lanka, is presented. The adopted method utilizes standard departures of daily maximum and minimum temperature values at four neighbouring stations, Mannar, Anuradhapura, Puttalam and Trincomalee to estimate the standard departures of daily maximum and minimum temperatures at the target station, Jaffna. The daily maximum and minimum temperatures from 1966 to 1980 (15 years) were used to test the validity of the method. The accuracy of the estimation is higher for daily maximum temperature compared to daily minimum temperature. About 95% of the estimated daily maximum temperatures are within ±1.5 °C of the observed values. For daily minimum temperature, the percentage is about 92. By calculating the standard deviation of the difference in estimated and observed values, we have shown that the error in estimating the daily maximum and minimum temperatures is ±0.7 and ±0.9 °C, respectively. To obtain the best accuracy when estimating the missing daily temperature extremes, it is important to include Mannar which is the nearest station to the target station, Jaffna. We conclude from the analysis that the method can be applied successfully to reconstruct the missing daily temperature extremes in Jaffna where no data is available due to frequent disruptions caused by civil unrests and hostilities in the region during the period, 1984 to 2000.
Spatial and temporal variation of frequencies of thunderstorms over Sri Lanka using thunder day data is presented. A thunder day is simply a calendar day in which thunder is heard at least once at a given location. Two sets of data were collected and analyzed: annual totals for 10 climatological stations for a period of 50 years and monthly totals for 20 climatological stations for a period of 20 years. The average annual thunder days over Sri Lanka was found to be 76. Among the climatological stations considered, a high number of annual thunder days was recorded in Ratnapura (150 days/year), followed by Colombo (108 days/year) and Bandarawela (106 days/year). It appears that there are no widespread long-term increasing or decreasing trends in thunderstorm frequencies. However, Colombo, the capital of Sri Lanka which has over two million people shows an increasing trend of 0.8 thunder days per year. Although there is a high variability between stations reporting the number of thunder days, the overall pattern within a year is clear. Thunderstorm frequencies are high during two periods: March–May and September–November, which coincide with the first inter-monsoon and second inter-monsoon periods. Compared to the dry zone, the wet zone, especially the southwestern region, has high thunderstorm activity. There is a clear spatial difference in thunderstorm activities during the southwest and northeast monsoon seasons. During both these seasons, enhanced thunderstorm activities are reported on the leeward side of the mountain range. A slight reduction in the thunderstorm activities was found in the high elevation areas of the hill country compared to the surrounding areas. A lightning ground flash density map derived using annual thunder days is also presented.
In this study, an analysis of century scale climate trends in the central highlands of Sri Lanka is presented. Monthly rainfall and temperature records of the period 1869–2006 from five climatological stations were analyzed. The trend is calculated by the least square regression analysis and the significance of the observed trend is estimated using the Mann–Kendall statistic. The results clearly show that there is a statistically significant decrease in annual rainfall in the western slopes of the central highlands. Throughout the last century, the annual reduction of rainfall in Nuwara Eliya which is at an altitude of 1895 m was 5.2 mm/year. The decrease is largely due to the reduction in southwest monsoon rainfall which contributes to 75% of the total reduction. No significant change was observed on the eastern side of the central highlands which receives rainfall predominantly from the northeast monsoons. The mean annual temperature in the mountainous region shows a uniform increasing trend which is in line with the 100-year global temperature increase of 0.8 ± 0.2∘C. Kandy, which is at an altitude of 477 m and closely linked with the rainfall climatology of Nuwara Eliya, showed no significant change in the mean annual temperature. If the current trend continues, in another 100 years, western and eastern slopes of central highlands will receive the same amount of rainfall from the southwest monsoon and the northeast monsoon which will have far reaching consequences for Sri Lanka’s economy and the ecology of the hill country.
In this study, we present an assessment of the Conformal Cubic Atmospheric Model (CCAM) 50 km simulations forced by the sea surface temperature and sea ice concentration of six global climate models (GCMs) (ACCESS1-0, CCSM4, GFDL-CM3, NorESM, MPI-ESM and CNRM-CM5) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) over South Asia, centred on Sri Lanka. The model simulations were compared with the data provided by the Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation of Water Resource (APHRODITE) project and ERA-Interim from the European Centre for Medium range Weather Forecast (ECMWF) over a broad region centred on Sri Lanka. This broad region includes South Asia and northern Indian Ocean. Statistical measures such as pattern correlations, mean biases and root mean square errors were calculated separately for the four seasons. Results based on statistical tests indicate that the current CCAM simulations capture the spatial patterns of 10 m wind speed, mean sea level pressure, temperature and rainfall over a broad region over South Asia fairly well. The annual cycles of temperature and rainfall were also compared against observations over the northern and southern regions of Sri Lanka by taking the field average of each model and the observed data. The characteristics of the observed annual variations of rainfall and temperature over the smaller domains are not very well captured by the CCAM simulations. There are differences in the magnitudes of the temperature and rainfall in the six member CCAM simulations. Comparatively, the two CCAM simulations CNRM-CM5 and GFDL-CM3 show slightly better agreement over the Sri Lankan region.
The onset, retreat and the length of growing season in the north-eastern region of Sri Lanka were investigated using daily rainfall data for the period 1961 to 2000. Data from three weather stations situated in the coastal belt in the northern and eastern parts of Sri Lanka (Jaffna, Trincomalee and Batticaloa) that receive rainfall predominantly from the northeast monsoon were selected for this study. A method based on cumulative rainy days was utilized in the determination of the onset and retreat dates. It is shown that there is substantial interannual variability in onset and retreat dates. The mean onset and retreat dates fall on the standard week 38.3 ± 2.7 and 53.0 ± 2.9, respectively. The mean duration of the growing season is 14.7 ± 3.4 weeks. The retreat date and thus the length of growing season could be extended by 2 weeks if the probability of occurrence of rain during the onset is favourable for the retreat. The results indicate that there has been no significant trend in the onset and retreat dates during the last 40 years in the dry zone of Sri Lanka. The onset date and the length of growing season are weakly correlated with early onset dates leading to longer growing seasons. The study concludes that rainy days could be used successfully to determine the mean rainfall onset and retreat dates in the dry zone of Sri Lanka.
Two different spectral analysis methods, the multitaper method (MTM) and the maximum entropy method (MEM) were applied to investigate the presence of low-frequency periodicities in precipitation records of 14 climatological stations in Sri Lanka. The spectral analysis revealed statistically significant periodicities in the range of 2 – 3 year and 3 – 6 year periods in all parts of Sri Lanka irrespective of the climatic variability. The 2 – 3 year band corresponds to the Quasi-Biennial oscillation (QBO), while the 3 – 6 year band corresponds to the El-Nino/Southern oscillation (ENSO) higher and lower frequency bands. Cross spectrum analysis showed statistically significant (at 5 %) coherencies for the Indian Ocean dipole (IOD) and Southern oscillation index (SOI) in the 2 – 3 year band and the 3 – 6 year band, respectively for most of the regions. Thus, it is concluded that the IOD and SOI play important roles as modulators of precipitation in Sri Lanka.
The hypothesis that the wet and dry patterns of daily precipitation observed in Colombo can be modeled by a first order Markov chain model was tested using daily rainfall data for a 60-year period (1941–2000). The probability of a day being wet or dry was defined with respect to the status of the previous day. Probabilities were assumed to be stationary within a given month. Except for isolated single events, the model is shown to describe the observed sequence of wet and dry spells satisfactorily depending on the season. The accuracy of modeling wet spells is high compared to dry spells. When the model-predicted mean length of wet spells for each month was compared with the estimated values from the data set, a reasonable agreement between the model prediction and estimation is seen (within ±0.1). In general, the data show a higher disagreement for the months having longer dry spells. The mean annual duration of wet spells is 2.6 days while the mean annual duration of dry spells is 3.8 days. It is shown that the model can be used to explore the return periods of long wet and dry spells. We conclude from the study that the Markov chain of order 1 is adequate to describe wet and dry patterns of weather in Colombo.
Performance of a feed-forward back-propagation artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a single meteorological station is presented. Both short-term and long-term forecasting was attempted, with ground level data collected by the meteorological station in Colombo, Sri Lanka (79° 52′E, 6° 54′N) during two time periods, 1994–2003 and 1869–2003. Two neural network models were developed; a one-day-ahead model for predicting the rainfall occurrence of the next day, which was able to make predictions with a 74·3% accuracy, and one-year-ahead model for yearly rainfall depth predictions with an 80·0% accuracy within a ± 5% error bound. Each of these models was extended to make predictions several time steps into the future, where accuracies were found to decrease rapidly with the number of time steps. The success rates and rainfall variability within the north-east and south-west monsoon seasons are also discussed.
Utilizing over 100 years of rainfall records in 15 meteorology stations, an analysis was carried out to extract the trends of annual rainfall depth in Sri Lanka over the last century. A statistically significant increasing trend of rate 3.15 mm/year was observed at Colombo and decreasing trends were observed at Nuwara Eliya and Kandy with rates of 4.87 mm/year and 2.88 mm/year respectively. Since no coherent increase or decrease of rainfall in any group of stations in the wet or dry zones was observed, the possibility of large scale change over the past century was ruled out. However, more recent data records (1949 onwards), revealed a decreasing trends in 13 of the 15 stations. Thus, traces of a temporal change seem to be apparent in the rainfall records over the last half century. In general, the downward trends in recent decades are steeper than the long term variations. For the recent data records, the largest downward trend of 11.16 mm/year was observed at Batticaloa.
Daily rainfall data recorded at 13 stations were analyzed to study the spatial patterns of rainfall in the dry zone of Sri Lanka. Principal component analysis was utilized to classify the dominant spatial regions. The first 2 eigenvectors accounted for 70.2% (the first eigenvector 54.8% and the second 15.4%) of the total variation, which clearly supports the commonly used major climatic division of Sri Lanka into wet and dry zones. Both the inverse distance weighting method and kriging successfully estimated weekly average rainfall in the North Central dry zone of Sri Lanka. For both methods, high correlation coefficients of 0.88 and 0.91 were observed for the southwest and northeast monsoon periods, respectively, with slightly lower values for intermonsoon periods. For inter-monsoon periods, the inverse distance weighting method produced better results than kriging. This work shows that the strength of the predictions depends on the rainfall seasons as well as the geometrical placement of the stations in the dry zone.