Surface and upper air temperatures over India in relation to monsoon rainfall

Summary The relationship between the all-India summer monsoon rainfall and surface/upper air (850, 700, 500 and 200 mb levels) temperatures over the Indian region and its spatial and temporal characteristics have been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India and subdivisional summer monsoon rainfall and various seasonal air temperatures at 73 surface observatories and 9 radiosonde stations (1951–1980) have been used in the analysis. The Correlation Coefficients (CCs) between all-India monsoon rainfall and seasonal surface air temperatures with different lags relative to the monsoon season indicate a systematic relationship.The CCs between the monsoon rainfall and surface-air temperature of the preceding MAM (pre-monsoon spring) season are positive over many parts of India and highly significant over central and northwestern regions. The average surface air temperature of six stations i.e., Jodhpur, Ahmedabad, Bombay, Indore, Sagar and Akola in this region (Western Central India, WCI) showed a highly significant CC of 0.60 during the period 1951–1980. This relationship is also found to be consistently significant for the period from 1950 to present, though decreasing in magnitude after 1975. WCI MAM surface air temperature has shown significant CCs with the monsoon rainfall over eleven sub-divisions mainly in northwestern India, i.e., north of 15 °N and west of 80 °E.Upper air temperatures of the MAM season at almost all the stations and all levels considered show positive CCs with the subsequent monsoon rainfall. These correlations are significant at some central and north Indian stations for the lower and middle tropospheric temperatures.The simple regression equation developed for the period 1951–1980 isy = – 183.20 + 8.83x, wherey is the all-India monsoon rainfall in cm andx is the WCI average surface air temperature of MAM season in °C. This equation is significant at 0.1% level. The suitability of this parameter for inclusion in a predictive regression model along with five other global and regional parameters has been discussed. Multiple regression analysis for the long-range prediction of monsoon rainfall, using several combinations of these parameters indicates that the improvement of predictive skill considerably depends upon the selection of the predictors.With 9 Figures     

Zonal circulation indices, 500 hPa April ridge position along 75° E and Indian summer monsoon rainfall: Statistical relationships

Summary This paper presents an examination of the statistical relationship between summer monsoon rainfall over all India, and two sub-regions (north west India and peninsular India) and the indices of mid-latitude (35° to 70° N) zonal circulation at 500 hPa level, over different sectors of the hemisphere, based on 19 years (1971–1989) data. The results indicate that summer monsoon rainfall (June–September) over India shows; (i) a significant and direct relationship with the strength of the zonal circulation index during concurrent July over the sector 90° E to 160° E. (ii) a significant inverse relationship with the strength of the zonal index during the previous April over the sector 160° E to 45° W and a similar relationship with the whole northern hemisphere and (iii) a significant and direct relationship with the frequency of the zonal index during the previous January over the sector 45° W to 90° E.Significant relationships are also observed between the zonal circulation indices of the above mentioned months and sectors with the 500 hPa ridge location in April at 75° E over India.With 4 Figures     

Pattern characteristics of Indian monsoon rainfall using principal component analysis (PCA)

In the present study the Principal Component Analysis (PCA) is used to determine the dominant rainfall patterns from rainfall records over India. Pattern characteristics of seasonal monsoon rainfall (June–September) over India for the period 1940 to 1990 are studied for 68 stations. The stations have been chosen on the basis of their correlation with all India seasonal rainfall after taking the ‘t’ Student distribution test (5% level). The PCA is carried out on the rainfall data to find out the nature of rainfall distribution and percentage of variance is estimated. The first principal component explains 55.50% of the variance and exhibits factor of one positive value throughout the Indian subcontinent. It is characterized by an area of large positive variation between 10°N and 20°N extending through west coast of India. These types of patterns mostly occur due to the monsoon depression in the head Bay of Bengal and mid-tropospheric low over west coast of India. The analysis identifies the spatial and temporal characteristics of possible physical significance. The first eight principal component patterns explain for 96.70% of the total variance.     

Interannual and long-term variability in the North Atlantic Oscillation and Indian Summer monsoon rainfall

Summary The interannual and decadal scale variability in the North Atlantic Oscillation (NAO) and its relationship with Indian Summer monsoon rainfall has been investigated using 108 years (1881–1988) of data. The analysis is carried out for two homogeneous regions in India, (Peninsular India and Northwest India) and the whole of India. The analysis reveals that the NAO of the preceding year in January has a statistically significant inverse relationship with the summer monsoon rainfall for the whole of India and Peninsular India, but not with the rainfall of Northwest India. The decadal scale analysis reveals that the NAO during winter (December–January–February) and spring (March–April–May) has a statistically significant inverse relationship with the summer monsoon rainfall of Northwest India, Peninsular India and the whole of India. The highest correlation is observed with the winter NAO. The NAO and Northwest India rainfall relationship is stronger than that for the Peninsular and whole of India rainfall on climatological and sub-climatological scales.Trend analysis of summer monsoon rainfall over the three regions has also been carried out. From the early 1930s the Peninsular India and whole of India rainfall show a significant decreasing trend (1% level) whereas the Northwest India rainfall shows an increasing trend from 1896 onwards.Interestingly, the NAO on both climatological and subclimatological scales during winter, reveals periods of trends very similar to that of Northwest Indian summer monsoon rainfall but with opposite phases.The decadal scale variability in ridge position at 500 hPa over India in April at 75° E (an important parameter used for the long-range forecast of monsoon) and NAO is also investigated.With 4 Figures     

A possible mechanism for the weakening of El Niño-monsoon relationship during the recent decade

Summary Observational data are used to explore the relationship between surface air temperature anomaly gradients and Indian summer monsoon rainfall (ISMR). The meridional temperature anomaly gradient across Eurasia during January directed towards equator (pole) is a very good precursor of subsequent excess (deficient) Indian summer monsoon rainfall (ISMR). This gradient directed towards equator (pole) indicates below (above) normal blocking activity over Eurasia, which leads to less (more) than normal southward penetration of dry and cold mid latitude westerlies over the Indian monsoon region, which ultimately strengthens (weakens) the normal monsoon circulation. These findings suggest a mechanism for the weakening of relationship between El Niño and ISMR.Though there is a strong fundamental association between El Niño (warm ENSO) and deficient Indian summer monsoon rainfall (ISMR), this relationship was weak during the period 1921–1940 and the recent decade (1991–1998). During the El Niño years of 1921–1940 and 1901–1998, the meridional temperature anomaly gradient across Eurasia (Eurasian forcing) during January was directed towards equator. On the other hand, during the El Niño years of 1901–1920 and 1941–1990 this gradient was directed towards pole. Thus during 1921–1940 and 1991–1998, the adverse impact of El Niño on Indian monsoon was reduced by the favorable Eurasian forcing resulting in the weak association between El Niño and ISMR. This finding disagrees with the hypothesis of winter warming over the Eurasian continent as the reason for the observed weakening of this relationship during recent decade.     

Surface pressure and summer monsoon rainfall over India

The relationship between the all-India summer monsoon rainfall and surface pressure over the Indian region has been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India monsoon rainfall and the mean pressures of three seasons before and after the monsoon season as well as the winter-to-spring pressure tendency (MAM-DJF) at 100 stations for the period 1951-1980 have been used in the analysis. The all-India monsoon rainfall is negatively correlated with the pressure of the spring (MAM) season preceding the monsoon and winter-to-spring seasonal difference as pressure tendency (MAM-DJF), at almost all the stations in India, and significantly with the pressures over central and northwestern regions. The average mean sea level pressure of six stations (Jodhpur, Ahmedabed, Bombay, Indore, Sagar and Akola) in the Western Central Indian (WCI) region showed highly significant (at 1% level) and consistent CCs of -0.63 for MAM and -0.56 for MAM-DJF for the period 1951–1980. Thus, the pre-monsoon seasonal pressure anomalies over WCI could provide a useful parameter for the long-range forecasting scheme of the Indian monsoon rainfall.     

Optimization of the raingauges for a representative all-India and subdivisional rainfall series

Summary An objective approach similar to the forward selection of independent variables in the multiple linear regression has been attempted to optimize the network of raingauges for the summer monsoon rainfall (June–September total) series (1871–1984) of India as well as its 29 selected meteorological subdivisions prepared involving the data of 306 raingauges. For the all-India monsoon rainfall series twenty seven gauges entered the selection whose mean showed the correlation coefficient (CC) of 0.9869. Keeping in view the difficulties of getting data from all the 306 gauges, 35 India Meteorological Department (IMD) gauges with mean showing CC of 0.9898 have been identified for updating this series. The constructed all-India monsoon rainfall series for the period 1871–1992 using 35 selected observations is presented. It was interesting to note that the set of 35 gauges selected for the monsoon total has shown equally promising results for the all-India monsoon monthly (June–September) as well as the annual rainfall series.For the 29 subdivisional monsoon rainfall series, however, in total 188 IMD-gauges (62% of the total of 306 gauges) entered the selection. For 17 subdivisions the CC exceeded 0.98, for 3 subdivisions it varied between 0.97 and 0.98, for 5 subdivisions between 0.96 and 0.97 and for the remaining 4 subdivisions between 0.90 and 0.94. They showed equally encouraging results for the monsoon monthly and annual rainfall series for the different subdivisions.Limitations and implications of the optimization technique are also briefly discussed.With 9 Figures     

The Concurrent Record-breaking Rainfall over Northwest India and North China in September 2021

Extremely heavy rainfall occurred over both Northwest India and North China in September 2021. The precipitation anomalies were 4.1 and 6.2 times interannual standard deviation over the two regions, respectively, and broke the record since the observational data were available, i.e., 1901 for India and 1951 for China. In this month, the Asian uppertropospheric westerly jet was greatly displaced poleward over West Asia, and correspondingly, an anomalous cyclone appeared over India. The anomalous ...     

20th-CENTURY CHANGES OF TEMPERATURE IN THE MOUNTAIN REGIONS OF CENTRAL EUROPE

Daily maximum and minimum temperatures from 29 low-lying and mountain stations of 7 countries in Central Europe were analyzed. The analysis of the annual variation of diurnal temperature range helps to distinguish unique climatic characteristics of high and low altitude stations. A comparison of the time series of extreme daily temperatures as well as mean temperature shows a good agreement between the low-lying stations and the mountain stations. Many of the pronounced warm and cold periods are present in all time series and are therefore representative for the whole region. A linear trend analysis of the station data for the period 1901–1990 (19 stations) and 1951–1990 (all 29 stations) shows spatial patterns of similar changes in maximum and minimum daily temperatures and diurnal temperature range. Mountain stations show only small changes of the diurnal temperature range over the 1901–1990 period, whereas the low-lying stations in the western part of the Alps show a significant decrease of diurnal temperature range, caused by strong increase of the minimum temperature. For the shorter period 1951–1990, the diurnal temperature range decreases at the western low-lying stations, mainly in spring, whereas it remains roughly constant at the mountain stations. The decrease of diurnal temperature range is stronger in the western part than in the eastern part of the Alps.     

Temperature variability over the Indian Ocean and its relationship with Indian summer monsoon rainfall

Summary The present study examines the long term trend in sea surface temperatures (SSTs) of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean in the context of global warming for the period 1901–2002 and for a subset period 1971–2002. An attempt has also been made to identify the relationship between SST variations over three different ocean areas, and All-India and homogeneous region summer monsoon rainfall variability, including the role of El-Ni?o/Southern Oscillation (ENSO). Annual sea surface temperatures of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean show a significant warming trend of 0.7 °C, 0.6 °C and 0.5 °C per hundred years, respectively, and a relatively accelerated warming of 0.16 °C, 0.14 °C and 0.14 °C per decade during the 1971–2002 period. There is a positive and statistically significant relationship between SSTs over the Arabian Sea from the preceding November to the current February, and Indian monsoon rainfall during the period 1901–2002. The correlation coefficient increases from October and peaks in December, decreasing from February to September. This significant relationship is also found in the recent period 1971–2002, whereas, during 1901–70, the relationship is not significant. On the seasonal scale, Arabian Sea winter SSTs are positively and significantly correlated with Indian monsoon rainfall, while spring SSTs have no significant positive relationship. Nino3 spring SSTs have a negative significant relationship with Indian monsoon rainfall and it is postulated that there is a combined effect of Nino3 and Arabian Sea SSTs on Indian monsoon. If the Nino3 SST effect is removed, the spring SSTs over the Arabian Sea also have a significant relationship with monsoon rainfall. Similarly, the Bay of Bengal and Equatorial South Indian Ocean spring SSTs are significantly and positively correlated with Indian monsoon rainfall after removing the Nino3 effect, and correlation values are more pronounced than for the Arabian Sea. Authors’ address: Dr. D. R. Kothawale, A. A. Munot, H. P. Borgaonkar, Climatology and Hydrometeorology divisions, Indian Institute of Tropical Meteorology, Pune 411008, India.     

中国与印度夏季风降水的比较研究

本文用1951—1980年中国和印度的降水资料研究了两个地区在西南季风时期(6—9月)总雨量变化的关系。发现印度的雨量变化与中国各地雨量的相关关系有正、有负,最明显的是印度中西部与我国华北地区有较高的正相关。进一步对两个地区降水存在遥相关的原因进行了分析,发现南亚次大陆低压是联系两个季风区雨量变化的重要环节。中国季风雨量与印度季风雨量的相关趋势,主要决定于中国各地雨量与东亚夏季风强度的关系。      

Spatial and temporal relationships between global land surface air temperature anomalies and Indian summer monsoon rainfall

Summary Using the 60 year period (1931–1990) gridded land surface air temperature anomalies data, the spatial and temporal relationships between Indian summer monsoon rainfall and temperature anomalies were examined. Composite temperature anomalies were prepared in respect of 11 deficient monsoon years and 9 excess monsoon years. Statistical tests were carried out to examine the significance of the composites. In addition, correlation coefficients between the temperature anomalies and Indian summer monsoon rainfall were also calculated to examine the teleconnection patterns.There were statistically significant differences in the composite of temperature anomaly patterns between excess and deficient monsoon years over north Europe, central Asia and north America during January and May, over NW India during May, over central parts of Africa during May and July and over Indian sub-continent and eastern parts of Asia during July. It has been also found that temperature anomalies over NW Europe, central parts of Africa and NW India during January and May were positively correlated with Indian summer monsoon rainfall. Similarly temperature anomalies over central Asia during January and temperature anomalies over central Africa and Indian region during July were negatively correlated. There were secular variations in the strength of relationships between temperature anomalies and Indian summer monsoon rainfall. In general, temperature anomalies over NW Europe and NW India showed stronger correlations during the recent years. It has been also found that during excess (deficient) monsoon years temperature gradient over Eurasian land mass from sub-tropics to higher latitudes was directed equatowards (polewards) indicating strong (weak) zonal flow. This temperature anomaly gradient index was found to be a useful predictor for long range forecasting of Indian summer monsoon rainfall.With 12 Figures     

Some features of the periods contributing specified percentages of rainfall to annual total in Kerala,India

Based on daily rainfall data over a period of 80 years (1901–1980) taken at 75 stations, this paper reports interannual and long term fluctuations of the following parameters of the periods contributing each of 2, 5, 10, 20–90 and 95% rainfall to annual total over each of North Kerala and South Kerala rainfall subregions of India:

Increasing trend of northeast monsoon rainfall over the equatorial Indian Ocean and peninsular India

Peninsular India and Sri Lanka receive major part of their annual rainfall during the northeast monsoon season (October–December). The long-term trend in the northeast monsoon rainfall over the Indian Ocean and peninsular India is examined in the vicinity of global warming scenario using the Global Precipitation Climatology Project (GPCP) dataset available for the period 1979–2010. The result shows a significant increasing trend in rainfall rate of about 0.5 mm day^?1 decade^?1 over a large region bounded by 10 °S–10 °N and 55 °E–100 °E. The interannual variability of seasonal rainfall rate over peninsular India using conventional rain gauge data is also investigated in conjunction to the Indian Ocean dipole. The homogeneous rain gauge data developed by Indian Institute of Tropical Meteorology over peninsular India also exhibit the considerable upward rainfall trend of about 0.4 mm day^?1 decade^?1 during this period. The associated outgoing longwave radiation shows coherent decrease in the order of 2 W?m^?2 decade^?1 over the rainfall increase region.     

Simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for present and future times in a global time-slice experiment

In this study the simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for the present-day and the future climate is investigated. This is done on the basis of a global time-slice experiment (TSL) with the ECHAM4 atmospheric general circulation model (GCM) at a high horizontal resolution of T106. The first time-slice (period: 1970–1999) represents the present-day climate and the second (2060–2089) the future climate. Moreover, observational rainfall data from the Global Precipitation Climatology Project (GPCP, 1997–2002) and rainfall data from the ECMWF re-analysis (ERA, 1958–2001) are considered. ERA reveals serious deficiencies in its representation of the variability and extremes of daily rainfall during the Indian summer monsoon. These are mainly a severe overestimation of the frequency of wet days over the oceans and in the Himalayas, where also the rainfall intensity is overestimated. Further, ERA shows unrealistically heavy rainfall events over the tropical Indian Ocean. The ECHAM4 atmospheric GCM at a horizontal resolution of T106, on the other hand, simulates the variability and extremes of daily rainfall in good agreement with the observations. The only marked deficiencies are an underestimation of the rainfall intensity on the west coast of the Indian peninsula and in Bangladesh, an overestimation over the tropical Indian Ocean, due to an erroneous northwestward extension of the tropical convergence zone, and an overestimation of the frequency of wet days in Tibet. Further, heavy rainfall events are relatively strong in the centre of the Indian peninsula. For the future, TSL predicts large increases in the rainfall intensity over the tropical Indian Ocean as well as in northern Pakistan and northwest India, but decreases in southern Pakistan, in the centre of the Indian peninsula, and over the western part of the Bay of Bengal. The frequency of wet days is markedly increased over the tropical Indian Ocean and decreased over the northern part of the Arabian Sea and in Tibet. The intensity of heavy rainfall events is generally increased in the future, with large increases over the Arabian Sea and the tropical Indian Ocean, in northern Pakistan and northwest India as well as in northeast India, Bangladesh, and Myanmar.     

Pre-monsoon surface pressure and summer monsoon rainfall over India

Summary The relationship between the surface air pressure field during the pre-monsoon months and the Indian summer monsoon rainfall is analysed using climate data from 105 stations situated in Eurasia between 0°–60° N and 20°–100° E. Moreover, grid-point data for the whole northern hemisphere are used. Pressure during April over an area around 50° N and 35° E is found to show a significant negative correlation with the subsequent monsoon rainfall. During May the pressure over a large part of the study area south of 40° N shows a significant correlation with its highest value in the heat low region over Pakistan. It is assumed that monitoring of pressure variations over this region may be useful in predicting monsoon rainfall, particularly the rainfall during the first half of the season. Certain limitations of the climate data in this region are also discussed.With 5 Figures     

A study on the decreasing trend in tropical easterly jet stream (TEJ) and its impact on Indian summer monsoon rainfall

Using the NCEP/NCAR reanalysis wind and temperature data (1948–2011) and India Meteorological Department (IMD) rainfall data, a long-term trend in the tropical easterly jet stream and its effect on Indian summer monsoon rainfall has been explained in the present study. A decreasing trend in zonal wind speed at 100 mb (maximum decrease), 150 mb, and 200 mb (minimum) is observed. The upper-level (100, 150, and 200 mb) zonal wind speed has been correlated with the surface air temperature anomaly index (ATAI) in the month of May, which is taken as the difference in temperature anomaly over land (22.5°N–27.5°N, 80°E–90°E) and Ocean (5°S–0°S, 75°E–85°E). Significant high correlation is observed between May ATAI and tropical easterly jet stream (TEJ) which suggests that the decreasing land–sea temperature contrast could be one major reason behind the decreasing trend in TEJ. The analysis of spatial distribution of rainfall over India shows a decreasing trend in rainfall over Jammu and Kashmir, Arunachal Pradesh, central Indian region, and western coast of India. Increasing trend in rainfall is observed over south peninsular and northeastern part of India. From the spatial correlation analysis of zonal wind with gridded rainfall, it is observed that the correlation of rainfall is found to be high with the TEJ speed over the regions where the decreasing trend in rainfall is observed. Similarly, from the analysis of spatial correlation between rainfall and May ATAI, positive spatial correlation is observed between May ATAI and summer monsoon rainfall over the regions such as south peninsular India where the rainfall trend is positive, and negative correlation is observed over the places such as Jammu and Kashmir where negative rainfall trend is observed. The decreased land–sea temperature contrast in the pre-monsoon month could be one major reason behind the decreased trend in TEJ as well as the observed spatial variation in the summer monsoon rainfall trend. Thus, the study explained the long-term trend in TEJ and its relation with May month temperature over the Indian Ocean and land region and its effect on the trend and spatial distribution of Indian summer monsoon rainfall.     

Homogeneous clusters over India using probability density function of daily rainfall

The Indian landmass has been divided into homogeneous clusters by applying the cluster analysis to the probability density function of a century-long time series of daily summer monsoon (June through September) rainfall at 357 grids over India, each of approximately 100 km × 100 km. The analysis gives five clusters over Indian landmass; only cluster 5 happened to be the contiguous region and all other clusters are dispersed away which confirms the erratic behavior of daily rainfall over India. The area averaged seasonal rainfall over cluster 5 has a very strong relationship with Indian summer monsoon rainfall; also, the rainfall variability over this region is modulated by the most important mode of climate system, i.e., El Nino Southern Oscillation (ENSO). This cluster could be considered as the representative of the entire Indian landmass to examine monsoon variability. The two-sample Kolmogorov-Smirnov test supports that the cumulative distribution functions of daily rainfall over cluster 5 and India as a whole do not differ significantly. The clustering algorithm is also applied to two time epochs 1901–1975 and 1976–2010 to examine the possible changes in clusters in a recent warming period. The clusters are drastically different in two time periods. They are more dispersed in recent period implying the more erroneous distribution of daily rainfall in recent period.

     

Effect of three different boundary-layer parameterisations in a regional atmospheric model on the simulation of summer monsoon circulation

Bulk, first-order and turbulent kinetic energy (TKE) closure schemes are used to parameterise the boundary-layer physics in a high resolution, limited area model. The model was used to simulate the summer monsoon circulations over India. The domain selected included the monsoon trough over northern India, a region of mesoscale convection. A monsoon depression was present at the time of the simulation. The results indicate that the TKE closure scheme combined with the Monin–Obukhov surface-layer similarity relation provided the best 48-hour simulation of the circulation and the rainfall associated with the monsoon depression.     

Spatial asymmetry of temperature trends over India and possible role of aerosols

Dissimilarities in temperature trends in space and time over the Indian region have been examined to look for signatures of aerosols’ influence. Separate temperature time series for North and South India were constructed for dry (November–May) and wet (June–October) seasons. Temperature trend for the entire period 1901–2007 and different subperiods of 1901–1950, 1951–1990, 1971–2007, and 1991–2007 have been examined to isolate the aerosol and other greenhouse gas influences on temperatures. Maximum (daytime) temperatures during dry season corresponding to North and South India show significant warming trend of 0.8 and 1.0?°C per hundred years during the period 1901–2007, while minimum temperature shows nebulous trend of 0.2 and 0.3?°C per hundred years over North and South India, respectively. During the wet season, maximum temperature shows nearly half of dry season maximum temperature warming trend. However, asymmetry is observed in dry season maximum temperature trend during post-industrial period 1951–1990 wherein the North/South India shows decreasing/increasing trends, while during the recent period 1991–2007 trends are uniformly positive for both the regions. Spatial and temporal asymmetry in observed trends clearly point to the role of aerosols in lowering temperature trends over northern India. Atmospheric aerosols could cause a negative climate forcing that can modulate the regional surface temperature trends in a significant way. As this forcing acts differentially on day and night temperatures, trends in diurnal temperature range (DTR) provide a direct assessment of impacts of aerosols on temperature trends. Time series of diurnal temperature range for dry and wet seasons have been examined separately for North and South India. Over North India, the DTR for dry season has increased gradually during the period 1901–1970 and thereafter showed decreasing trend, while trends in temperature range over Southern India were almost opposite in phase with North India. The aerosol and greenhouse gases seem to play an important role in the spatial and temporal variability of temperature range over India.