Southwest Monsoon Rainfall Research Articles

TREND OF DAILY RAINFALL AND TEMPERATURE IN PENINSULAR MALAYSIA BASED ON GRIDDED DATA SET

A gridded data set with the size of 0.05 degree resolution (approximately 5.5km) which representing ground observations of daily rainfall and temperature of Peninsular Malaysia has been created over 1975-2006. The integration and processing of the variety of data sources and data assessment is also presented. The 32-year period of the daily gridded rainfall and temperature data set were assessed to see how the daily mean rainfall and temperature have changed over time and space. Northeast monsoon (NEM) contributes more rainfall over the country compare to southwest monsoon (SWM). The rainfall trend during NEM is found significantly increased at the 95% confidence level (7mm/season/year), meanwhile SWM rainfall does not pose any significant trends. Both NEM and SWM temperature trends show significant increasing trends at 95% confidence level at 0.32oC/decade and 0.31oC/decade, respectively over the 32-year period. A drastic increased of mean temperature (1.20oC) was found in Klang Valley over the 20-year period. The mean decadal temperature was found consistently decrease as it approached the northern, east coast and southern part of the country.

New spatial and temporal indices of Indian summer monsoon rainfall

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Effect of Southwest Monsoon Withdrawal on Mass Loading and Chemical Characteristics of Aerosols in an Urban City over the Indo-Gangetic Basin

The southwest monsoon rainfall not only provides water and food security over the Indo-Gangetic Basin, it also plays an important role in reducing atmospheric pollution by removing ambient particles via wet deposition processes. In addition to rainfall, aerosol loading and its removal from ambient air are also governed by other meteorological parameters, such as the temperature, humidity, wind speed, and wind direction. To understand the effect of southwest monsoon withdrawal on aerosol loading over the Indo-Gangetic Basin, airborne particles (PM10 size fraction) and meteorological parameters, including the temperature, humidity, rainfall, wind speed, and wind direction data were collected between July and October 2015 at Kanpur, India, which is a large industrial city in the central part of the Indo-Gangetic Basin. The study shows that withdrawal of the southwest monsoon since July 2015 increased the aerosol loading in the ambient air by up to 28, 43 and 152% during August, September, and October, respec...

Investigating the Teleconnection between Warm ENSO Phases and Seasonal Rainfall over Kotmale Catchment in Sri Lanka

Seasonal rainfall over Kotmale reservoir is changing at an alarming rate due to atmospheric oscillations taking place over Sri Lanka. Therefore, this study focused on the teleconnection between warm El-Nino Southern Oscillation (ENSO) phases and rainfall over the Kotmale catchment. Daily rainfall data obtained from 11 meteorological stations were used to identify the behaviour of the annual rainfall climatologies of the catchment. Inflow data of the Kotmale reservoir obtained for the period 1984 to 2012 were analysed to understand reservoir inflow trends. Sea surface temperatures were obtained from Japan Meteorological Agency to determine the warm El- Nino Southern Oscillation phase. The rainfall at the stations and the inflow to the reservoir have declined over the period selected. However, the rate of decrease has varied from station to station. Seasonal rainfall at all the stations considered between December and September showed a negative correlation with the mean sea surface temperature of the Nino 3 region. Warm El-Nino Southern Oscillation caused below average seasonal rainfall over the catchment between December and September. The northeast and southwest monsoon rainfall over the catchment has weakened because of warm El-Nino Southern Oscillation phase in the Nino 3 region. However, the effect has got reduced with the onset of monsoons.

Northeast monsoon variations during the Holocene inferred from palaeochannels and active channels of the Palar River basin, Southern Peninsular India

The present-day Palar River and its palaeochannel located in the Southern Peninsular India were investigated with a multidisciplinary approach. The main aim of the study was to reconstruct the palaeoenvironment history of the Palar River basin and to delineate the role of Holocene fluctuations that played a major role in the geomorphological evolution of the region since the Holocene period. The results obtained based on sedimentary facies analysis supported by elemental concentrations and optically stimulated luminescence (OSL) dates reveal distinct seven climatic phases since the past ~10 ka. Phase 1 signifies a very high precipitation as attested by the low CWI with high Rb/Sr ratio. Subsequent to Phase 1, a decreasing trend in the northeast monsoon rainfall (NEMR) is observed (Phase 2). Phase 3 (~4.83–3.59 ka) reflects a decrease in NEMR further supported by low Mn/Al, Mg/Al and Chemical Index of Alteration (CIA) values. Phase 4 (~3.59 ka) is marked by high sand flux, higher K/Al, Ti/Al, Rb/Sr and Ba/Sr ratios coupled with lower values of CaO/MgO, Mn/Al and Fe/Al indicating wetter conditions in the catchment area resulting in the intense weathering of the bedrocks caused owing to the increase in NEMR precipitation. Phase 5 (3.26–2.42 ka) reveals a decline in NEMR precipitation coupled with rapid upstream avulsion because of neotectonic activity that occurred in an intense dry phase. Phase 6 (~1.88–1.44 ka) is marked by an augment NEMR causing higher K/Al, Mg/Al, Ti/Al ratios, CIA and CWI values. Finally, Phase 7 (~1.44 ka–present) is marked by lowered elemental solubility and mobility reflecting short periods of weaker or deteriorated NEMR. The documented record of the Palar River and palaeochannels suggests Holocene NEMR variability in the study region and is synchronous with the various proxy records of NEMR-dominated regions, however, revealing an inverse coupling with southwest monsoon rainfall (SWMR) during the Holocene period.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979–2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude–longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

Trends and variability of meteorological drought over the districts of India using standardized precipitation index

Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901–2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than −10% or below normal, for those years all India SPI was found as −1 or less. Composite analysis of SPI for the below normal years, viz., less than −15% and −20% of normal rainfall years indicate that during those years more than 30% of country’s area was under drought condition, whenever all India southwest monsoon rainfall was –15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.

Trend Analysis of Rainfall Variability in Western Agro Climatic Zone of Tamil Nadu

An analytical examination was done to work out the unevenness in point location and time to time variability in rainfall at Coimbatore and Erode district of Western agro climatic zone of Tamil Nadu (India) for 100 years (1916-2015). Simple descriptive statistics along with Co-efficient of Variation (CV) were worked to understand the rainfall variability. The long term mean seasonal and annual rainfall analysis showed that South West Monsoon (SWM) rainfall observed was (176.9 mm) & (257.9 mm) and North East Monsoon (NEM) of (336.9 mm) & (323.3 mm) and annual rainfall of (674.8 mm) & (764.4 mm) at Coimbatore and Erode respectively. The CV for seasonal and annual rainfall showed high dependability status by recording appropriate threshold level of CV for seasonal and annual rainfall. The time series rainfall data for 100 years were divided into ten year period and the correlation was carried out for the SWM and NEM using Spearman’s rank-order correlation. The results indicated the correlation between two monsoons for Coimbatore (0.14) and for erode (0.07) which indicates that there was less relation between SWM and NEM. Major emphasis was given to analyse annual and seasonal (SWM and NEM) rainfall time sequence over an extensive time gap to identify probable trend and to measure their implication. For Coimbatore and Erode districts, in both the monsoon seasons and annual analysis revealed an increasing trend for long term (100 years-1916-2015) period.

Similarity-based multi-model ensemble approach for 1–15-day advance prediction of monsoon rainfall over India

The southwest (SW) monsoon season (June, July, August and September) is the major period of rainfall over the Indian region. The present study focuses on the development of a new multi-model ensemble approach based on the similarity criterion (SMME) for the prediction of SW monsoon rainfall in the extended range. This approach is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional MME approaches. In this approach, the training dataset has been selected by matching the present day condition to the archived dataset and days with the most similar conditions were identified and used for training the model. The coefficients thus generated were used for the rainfall prediction. The precipitation forecasts from four general circulation models (GCMs), viz. European Centre for Medium-Range Weather Forecasts (ECMWF), United Kingdom Meteorological Office (UKMO), National Centre for Environment Prediction (NCEP) and China Meteorological Administration (CMA) have been used for developing the SMME forecasts. The forecasts of 1–5, 6–10 and 11–15 days were generated using the newly developed approach for each pentad of June–September during the years 2008–2013 and the skill of the model was analysed using verification scores, viz. equitable skill score (ETS), mean absolute error (MAE), Pearson’s correlation coefficient and Nash–Sutcliffe model efficiency index. Statistical analysis of SMME forecasts shows superior forecast skill compared to the conventional MME and the individual models for all the pentads, viz. 1–5, 6–10 and 11–15 days.

Southwest monsoon rainfall in Assam: An application of principal component analysis for understanding of variability

The principal component analysis (PCA) is applied to understand the spatial and temporal variability of monsoonal rainfall in the state Assam in India. The Southwest Monsoon (SWM) rainfall data over 12 widely spread stations located over the state has been analyzed for a period of 60 years for understanding variability. A statistically significant trend and a above/below transition signal has been observed for a few stations and the corresponding principal components (PCs). Coherent regions of Northern and Southern Assam have been identified through PCA to bring out the possible significant signals. It is observed that some of PCs for state-wise and coherent regions have positive or negative trend and significant above/below transition.

Modeling and forecasting rainfall patterns of southwest monsoons in North–East India as a SARIMA process

Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North–East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

Performance of the Operational and Experimental Long-Range Forecasts for the 2015 Southwest Monsoon Rainfall

India experienced deficient monsoon rainfall in 2015 that followed the deficient monsoon of 2014. India Meteorological Department (IMD) correctly predicted the large rainfall deficiency (86% of long period average) in 2015. Incidentally, this was the first ever deficient monsoon forecast issued by IMD, though it had earlier issued below-normal rainfall forecasts in the previous two deficient monsoon years (2009 and 2014) and was partially correct. The fact that there were only three previous occasions of consecutive two deficient monsoon years during the last 114 years (1901-2014) was itself a challenge to IMD to issue the forecast in 2015. It may be mentioned that IMD persisted with the deficient monsoon forecast for 2015, even though there were predictions from private agencies for a normal monsoon and apprehensions from the press and media about the low probability of two consecutive deficient years. IMD was also able to correctly predict the regional distribution of seasonal rainfall during the season. IMD's first deficient monsoon forecast was based on the state-of-the-art operational statistical forecasting system, which was introduced in 2007. IMD was further confident for a deficient monsoon due to the clear indications of a strong El Nino event by June itself. Forecasts from high-resolution coupled forecasting system (CFS) developed by the Indian Institute of Tropical Meteorology, Pune, under the Monsoon Mission also suggested a deficient monsoon in 2015. In this article we provide details of the operational forecasting models and verification of these forecasts. Brief description about the experimental CFS developed under the Monsoon Mission and CFS forecast for the 2015 southwest monsoon season is also presented.

Some characteristics of southwest monsoon rainfall over urban entres in Andhra Pradesh and Telangana

In the present study daily rainfall data for 46 years (1969-2014) was selected for the urban stations and surrounding stations for coastal areas of Coastal Andhra Pradesh (CAP) and inland areas of Telanagana (TEL) and Rayalaseema (RSM). The statistics such as regression, standard deviation and coefficient of variance, significance test using t-test, Mann-Kandell test were worked out for the entire period for the stations. The stations were selected on the basis where the period of data is same. The t-test thus performed for all stations showed significance (p < 0.001) in seasonal rainfall (JJAS) for all the stations. Further z-statistics using Mann-Kandell test was performed that showed significant increase at 95% confidence level for Gannavaram, Machilipatnam and Visakhapatnam along the coast of Andhra Pradesh state. Over Telengana, Hyderabad (Urban centre) an inland station, showed significant increase at 90% level of confidence for extreme heavy rainfall events. Henceforth, seperate studies for each urban centre (Visakhapatnam, Gannavaram, Machilipatnam and Hyderabad) were done and results showed significant increase in rainfall over urban centres compared to other surrounding stations and the significant increase in rainfall was observed for the coastal stations along Andhra Pradesh coast when compared to inland stations of Telanagana and Rayalaseema.

Long-term changes in the within-season temporal profile of southwest monsoon over western India

This paper presents results of a study of long term trends in the characteristics of the within-season temporal profile of southwest monsoon rainfall over western India during the last five decades in relation to global warming induced regional climate change. In contrast to recent climate change analyses and projections, no significant long-term trends have been observed in this study. Slow decadal scale variations observed are analysed in relation to Pacific Decadal Oscillations (PDO). Daily variations in rainfall anomaly show opposite characteristics during negative and positive phases of PDO. The above-normal rainfall (>25%) is found during the starting phase of monsoon in negative PDO. Over the last decade, i.e., during 2000–2007, the seasonal rainfall amount, as well as seasonal span of southwest monsoon over western India is indicative of a gradual increase.

Shift in Climate Class Over Tamil Nadu

Climate being a significant driver for best selection of crops in a region, allocation of similar climatic zones has always received plunge.Twenty per cent or more precipitation decrease is anticipated for many parts of the arid regions in the next century. Rainfall is a crucial agro-climatological factor in the seasonally arid parts of the world and its analysis is an essential prerequisite for agricultural planning in India. Ninety years (1911-2000) of both South West Monsoon (SWM) and North East Monsoon (NEM) rainfall data of Tamil Nadu (excluding urbanite Chennai)and potential evapotranspiration data were collected and analysed. The moisture index (Im) was computed based on Thornthwaite and Mather model. Based on the moisture index value of the SWM and NEM, the districts were classified under different climate groups.Over 90 years study, seven districts comes under arid (E), 17 under semi-arid(D), five under dry sub humid(C1) and one each in moist sub humid(C2) and per humid (A) class respectively(SWM period). During NEM no districts registered under (E) or (D) climate class. Further seven districts fell each in (C1) and (C2) class respectively and12 districts comes under Humid(B) and five districts under (A) climate class for Tamil Nadu.During SWM, both the data slice (30 years) and decadal (10 years) analysis explored Trichy district might experience severe moisture stress compared to the past. Madurai, Perambalur and Virudhunagar showed a change from (B1) to (C2) during NEM which showed there might be a change in reduction in soil moisture status among the data slice period. Remaining districts fell within the same climate group.

On the relation of vegetation and southwest monsoon rainfall over Western Ghats, India

This article presents the tendency of the normalized difference vegetation index (NDVI) and the dependence of vegetation on the rainfall and number of rainy and non-rainy days over Western Ghats. The study makes use of MODIS Terra NDVI data with 8-day intervals and 250-m resolution from 2000 to 2010 during the southwest monsoon (June to September) season. The results show an increasing tendency of the NDVI over different test sites in Western Ghats. The relation of the NDVI with the Antecedent Precipitation Index obtained from rainfall showed good agreement, and the relation of rainfall and the NDVI was mainly dependent on the available soil moisture levels and elevations of the test sites. Correlations were significant and positive with the number of rainy days and negative with the number of non-rainy days with a nearly 2-month lag.

Variability and trend analysis of rainfall data of Jhalawar district of Rajasthan, India

An attempt has been made to study the variability and trends of annual and seasonal rainfall for the period of 38 years (1973-2010) for all seven tehsils of Jhalawar district of Rajasthan. The mean annual rainfall of the district was found to 910 mm with standard deviation 218 mm and coefficient of variation 24 per cent. Annual rainfall varied from about 831 mm in Khanpur to more than 1022 mm in the Pirawa tehsil of the district. The annual rainfall showed declined trend (-0.23 to -17.41 mm/year) in all seven tehsils of the district. The negative trends at Pirawa (17.407 mm/year), Manoharthana (11.595 mm/year) and Aklera (5.789 mm/year) are statistically significant at less than 0.001, 0.05 and 0.05 levels, respectively. During the study period maximum dry period was recorded during postmonsoon and winter. Also, for the entire 38 years period maximum dry months were recorded during December till April. August was normal month for about 87 per cent followed by July and June for about 84 per cent and 66 per cent respectively. It was evident that the onset of south-west (SW) monsoon took place in the month of June and chancesof drought occurrence during kharif season were very low. Hence, SW monsoon rainfall is found ideal for raising kharif crops like soybeans, urd, moong, jowar, maize, tomato, brinjal, chilli, okra, kharif onion, amaranth, rainfed green gram, red gram, castor, etc in the district.

Century scale climate change in the central highlands of Sri Lanka

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.

Agricultural drought monitoring and management at sub district level in Telangana

The weather or climate is considered as an important natural resource and basic input for better planning of crop and cropping system in agriculture particularly rainfed environments. Every plant process, related with growth, development and yield of a crop and each of in-season and off-season farm operations depends on weather. Amongst the various weather elements, temperatures, radiation and rainfall play crucial role in deciding the crop growth, development and yield levels. Precipitation is one of the important weather factors being responsible for atmospheric and soil moisture and therefore has more agricultural importance, especially in rainfed agriculture.
 Rainfed crops like jowar, maize, groundnut, greengram, blackgram and sunflower and one water-intensive crop like rice are mainly affected owing to drought. The drought conditions occur due to failure of South West Monsoon, delay in arrival of SW monsoon, and break monsoon conditions or early cessation of SW monsoon. Rainfed agriculture in India depends on onset of monsoon and the rainfall distribution during crop growth season. The amount of rainfall and the time of onset of monsoon decides the type of the crop to be grown. The timely onset and well distribution of monsoon rain in the month of June and July decides the area coverage of rainfed crops. Any deviation in the onset and distribution of southwest monsoon rainfall causes huge impact on agriculture and its dependent activities. Close monitoring of progress of monsoon and distribution of rainfall and its impact on sowing of rainfed crops is essential at sub district level to suggest time to time crop management strategies thereby to minimize the impact of aberrant seasonal conditions. In this paper a monitoring of drought at national, state and sub district (Mandal) level using indices like MAI, WRSI etc. were presented. Management strategies to reduce the impact of drought like optimum time of sowing, strategic irrigation, crop calendar, contingency crop planning etc. were discussed. Agromet advisories for communication of real time weather information for benefit of farming community were presented.

Rainfall-Runoff Prediction Using Dynamic Typhoon Information and Surface Weather Characteristic Considering Monsoon Effects

In meteorology and engineering, the prediction of quantitative precipitation and streamflow during typhoon events is a vital research topic. In Southern Taiwan, typhoons often occur in the summer. The interaction between the typhoon circulation and southwesterly monsoon flow frequently transports abundant moisture into Southern Taiwan leading to the substantial pouring rains. This study proposes a rainfall-runoff prediction methodology for addressing the complicated inflow forecasts of southwest monsoon rainfall during typhoons in the upper Tsengwen River in Southern Taiwan. This paper is novel in that it incorporates various data types (reservoir inflows, watershed rainfalls, typhoon information, and ground-weather characteristics) that were applied as model inputs. The most frequently used support vector regressions were employed to construct the rainfall-runoff models on the basis of three designed data combination scenarios. Typhoons Kalmaegi (2008), Fung-wong (2008), Jangmi (2008), and Morakot (2009) were used as validation typhoons. The model cases, involving lead times of 1 h to 6 h, were evaluated. Six performance criteria were used in the three scenarios to highlight the scenario capable of identifying the optimal performance level. In addition, this study compared the error rates between accumulation observations and accumulation predictions. The results showed that Scenario 3, which considered typhoon information and ground-weather characteristics simultaneously, had superior watershed rainfall and runoff predictions to those of the other scenarios. Thus, this study demonstrated the feasibility of using the proposed methodology to increase the accuracy of rainfall-runoff predictions.