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     

Stratospheric zonal wind and temperature in relation to summer monsoon rainfall over India

Summary  The interannual variability of the Indian summer monsoon (June–September) rainfall is examined in relation to the stratospheric zonal wind and temperature fluctuations at three stations, widely spaced apart. The data analyzed are for Balboa, Ascension and Singapore, equatorial stations using recent period (1964–1994) data, at each of the 10, 30 and 50 hPa levels. The 10 hPa zonal wind for Balboa and Ascension during January and the 30 hPa zonal wind for Balboa during April are found to be positively correlated with the subsequent Indian summer monsoon rainfall, whereas the temperature at 10 hPa for Ascension during May is negatively correlated with Indian summer monsoon rainfall. The relationship with stratospheric temperatures appears to be the best, and is found to be stable over the period of analysis. Stratospheric temperature is also significantly correlated with the summer monsoon rainfall over a large and coherent region, in the north-west of India. Thus, the 10 hPa temperature for Ascension in May appears to be useful for forecasting summer monsoon rainfall for not only the whole of India, but also for a smaller region lying to the north-west of India. Received July 30, 1999 Revised March 17, 2000     

Interannual variability of summertime outgoing longwave radiation over the Maritime Continent in relation to East Asian summer monsoon anomalies

The Maritime Continent (MC) is under influences of both the tropical Pacific and the Indian Ocean. Anomalous convective activities over the MC have significant impacts on the East Asian summer monsoon (EASM) and climate in China. In the present study, the variation in convective activity over the MC in boreal summer and its relationship to EASM anomalies are investigated based on regression analysis of NCEP–NCAR reanalysis and CMAP [Climate Prediction Center (CPC) Merged Analysis of Precipitation] data, with a focus on the impacts of ENSO and the Indian Ocean Dipole (IOD). The most significant interannual variability of convective activity is found over 10°S–10°N, 95°–145°E, which can be roughly defined as the key area of the MC (hereafter, KMC). Outgoing longwave radiation anomaly (OLRA) exhibits 3- to 7-yr periodicities over the KMC, and around 70% of the OLRA variance can be explained by the ENSO signal. However, distinct convection and precipitation anomalies still exist over this region after the ENSO and IOD signals are removed. Abnormally low precipitation always corresponds to positive OLRA over the KMC when negative diabatic heating anomalies and anomalous cooling of the atmospheric column lead to abnormal descending motion over this region. Correspondingly, abnormal divergence occurs in the lower troposphere while convergence occurs in the upper troposphere, triggering an East Asia–Pacific/Pacific–Japan (EAP/PJ)-like anomalous wave train that propagates northeastward and leads to a significant positive precipitation anomaly from the Yangtze River valley in China to the islands of Japan. This EAP/PJ-like wave pattern becomes even clearer after the removal of the ENSO signal and the combined effects of ENSO and IOD, suggesting that convective anomalies over the KMC have an important impact on EASM anomalies. The above results provide important clues for the prediction of EASM anomalies and associated summer precipitation anomalies in China.     

Periodicity in intraseasonal variation of summer monsoon rainfall over Orissa, India in relation to synoptic disturbances

Summary The summer monsoon rainfall over Orissa, a state of eastern India, shows characteristic intraseasonal and interannual variability, due to interaction of basic westerly flow with orography and the synoptic scale monsoon disturbances including low-pressure systems and cyclonic circulations extending upto mid-tropospheric level (LPSC). These systems normally develop over the north Bay of Bengal and move west-northwestwards along the monsoon trough. The essence of this study is to find out the main features of the intraseasonal variability of daily monsoon rainfall over Orissa in relation to synoptic systems like LPSC and its implication on the interannual variation of rainfall. For this purpose, the actual and mean daily rainfall data of 31 uniformly distributed stations, six homogeneous regions and Orissa as a whole during monsoon season (June–September) over a period of 20 years (1980–1999) are subjected to auto-correlation and power spectrum analyses. The actual and average daily scores of significant EOFs and actual daily occurrence along with daily probability of occurrence of the LPSC influencing rainfall over Orissa during the same period are also subjected to auto-correlation and power spectrum analyses. The intraseasonal variation of monsoon rainfall over Orissa and different homogeneous regions is dominated by the synoptic mode (3–9 days) of variation due to the similar mode of variation in the occurrence of LPSC influencing the rainfall. The seasonal rainfall and hence the interannual variation depends on the intraseasonal variation of rainfall modulated with the synoptic mode of variation in the occurrence of the LPSC. The occurrence of LPSC over the northwest (NW) Bay/NW and adjoining northeast (NE) Bay and its subsequent movement and persistence over Orissa and east Madhya Pradesh & Chhattisgarh in synoptic mode (3–6 days) alongwith absence of similar mode in the occurrence of the LPSC over NE Bay, Gangetic West Bengal (GWB) in the north and west central (WC) Bay to the south leads to excess rainfall over different homogeneous regions and Orissa as a whole. The reverse is the case in deficient years over Orissa and all homogeneous regions except southwest Orissa. The occurrence of the LPSC over GWB in synoptic mode (about 5 days) alongwith absence of synoptic mode in the occurrence of the LPSC over NW Bay leads to deficient rainfall year over southwest Orissa. Correspondence: U. C. Mohanty, Centre for Atmospheric Sciences, Indian Institute of Technology, Delhi Hauz Khas, New Delhi 110016, India     

中国东部降水特征及其与印度、北美降水的关系

本文应用了10年平均的旬、候和日平均降水资料,研究了中国东部4—9月降水分布特点。结果指出,华南、华中4—9月候降水量高值中心区存在准一个月的振荡现象,东北、华北4—9月的日平均降水量低值中心区具有准一周的振荡现象。而在长江流域,4—9月的旬降水量高值中心区以不连续跳跃方式在东西方向上传播,高值中心区“重现”的准周期约为一个月左右。 同时,本文也应用了1957—1985年月平均降水资料,计算了中国东部和印度中部、北美西部同期降水相关系数。结果指出,华南、华中5—7月降水相关场的分布作反时针旋转。在6月梅雨季节,长江中下游地区是降水正相关区,而华南是负相关区。在6—8月,中国东部和北美西部的月平均降水量之间存在稳定的负相关关系。     

Principal component analysis of satellite-observed outgoing long-wave radiation during the monsoon period (June–September) over India

Summary In this study, Principal Component Analysis (PCA) has been used to identify the major modes of the outgoing long-wave radiation data for the period (1979–2002) during the Indian monsoon period (June–September), using seasonal mean values over the Indian region covering 143 grid points (5° N–35° N and 70° E–95° E at 2.5° Longitude–Latitude intervals. The five principal components explain up to 98.0% of the total variance. The first principal component explains 60% of the total variance with a pronounced variation in the outgoing long-wave radiation over the region 10° N to 25° N. It appears that the major reason for the monsoon variability is the intensity and associated fluctuations in the two major semi-permanent seasonal systems. This is largely indicative of strong seasonal shift of the major area of cloudiness associated with convergence zone. The second principal component explaining 20% of the total variance exhibits higher positive component loadings along 25° N and east of 80° E. The possible reason for this could be the synoptic systems such as monsoon depression/lows over the north bay and trough/vortices off the west-coast in the Arabian sea.     

An improvement in cumulus parameterization by invoking outgoing longwave radiation

Summary The Kuo-type cumulus parameterization and rainfall rate scheme is extended by including the outgoing longwave radiation (OLR), the local time rate of change of OLR, and the horizontal Laplacian of OLR to include the additional source of mesoscale moisture supply. The extended scheme remains simple and efficient. A series of 5-day forecasts of the 1979 monsoon for the tropical belt between the Arabian Sea and the western Pacific Ocean show improvement in the 3-day forecast in the daily accumulated precipitation in both the amount and location. Further RMS error analyses indicate that using OLR and the Laplacian of OLR also produces a significant improvement in a 3-day forecast. Additional tests of the extended scheme for the 1987 and 1988 monsoons produced consistent and characteristic areal rainfall rates in the tropics. The improvement in the OLR model forecasts is attributed to the improved skill of OLR forecast in the forecast model as the RMS errors for 5 consecutive days in the 6 experimental forecasts are smaller than those of the 3 control forecasts.With 12 Figures     

Correlation analysis of persistent heavy rainfall events in the vicinity of the Yangtze River valley and global outgoing longwave radiation in the preceding month

Based on the National Oceanic and Atmospheric Administration (NOAA) daily satellite dataset of global outgoing longwave radiation (OLR) for the period of 1974--2004 and the NCEP-NCAR reanalysis for 1971--2004, the linkage between persistent heavy rainfall (PHR) events in the vicinity of the Yangtze River valley and global OLR leading up to those events (with 1- to 30-day lag) was investigated. The results reveal that there is a significant connection between the initiation of PHR events over the study area and anomalous convective activity over the tropical Indian Ocean, maritime continent, and tropical western Pacific Ocean. During the 30-day period prior to the onset of PHR events, the major significantly anomalous convective centers have an apparent dipole structure, always with enhanced convection in the west and suppressed convection in the east. This dipole structure continuously shifts eastward with time during the 30-day lead period. The influence of the anomalous convective activity over the tropical oceans on the initiation of PHR events over the study area is achieved via an interaction between tropical and extratropical latitudes. More specifically, anomalous convective activity weakens the Walker circulation cell over the tropical Indian Ocean first. This is followed by a weakening of the Indian summer monsoon background state and the excitation and dispersion of Rossby wave activity over Eurasia. Finally, a major modulation of the large scale background circulation occurs. As a result, the condition of a phase-lock among major large scale circulation features favoring PHR events is established over the study area.     

Empirical Orthogonal Function (EOF) analysis of monsoon rainfall and satellite-observed outgoing long-wave radiation for Indian monsoon: a comparative study

Summary The present study involves the use of Empirical Orthogonal Function (EOF) analysis/Principal Component Analysis (PCA) to compare the dominant rainfall patterns from normal rainfall records over India, coupled with the major modes of the Outgoing Long-wave Radiation (OLR) data for the period (1979–1988) during the monsoon period (June–September). To understand the intraseasonal and interannual variability of the monsoon rainfall, daily and seasonal anomalies have been obtained by using the (EOF) analysis. Importantly, pattern characteristics of seasonal monsoon rainfall covering 68 stations in India are highlighted.The purpose is to ascertain the nature of rainfall distribution over the Indian continent. Based on this, the percentage of variance for both the rainfall and OLR data is examined. OLR has a higher spatial coherence than rainfall. The first principal component of rainfall data shows high positive values, which are concentrated over northeast as well as southeast, whereas for the OLR, the area of large positive values is concentrated over northwest and lower value over south India apart from the Indian ocean. The first five principal components explain 92.20% of the total variance for the rainfall and 99.50% of the total variance for the outgoing long-wave radiation. The relationship between monsoon rainfall and Southern Oscillations has also been examined and for the Southern Oscillations, it is 0.69 for the monsoon season. The El-Niño events mostly occurred during Southern Oscillations, i.e. Walker circulation. It has been found that the average number of low pressure system/low pressure system days play an important role during active (flood) or inactive (drought) monsoon year, but low pressure system days play more important role in comparison to low pressure systems and their ratio are (16:51) and (13:25) respectively. Significantly, the analysis identifies the spatial and temporal pattern characteristics of possible physical significance.     

Extreme monsoonal rainfall deficits in India

Summary Data from 306 stations in India, for the 70 years (1901–70) of summer (June–September) monsoonal rainfall, are grouped into 32 sub-regions. Extreme event theory is used to analyse the return periods of extreme rainfall deficits within each of these sub-regions, using the log-Pearson type III frequency distribution in a spatial rather than a temporal context. The resultant estimates for 2, 5 and 10 year return periods are compared with the patterns derived from the Gaussian frequency distribution applied to the 306 stations individually; the 50 and 100 year return period estimates are also considered.

---

Zusammenfassung Die Daten über den sommerlichen Monsunregen (Juni–September) aus 70 Jahren (1901–70) von 306 Stationen in Indien werden in 32 Teilgebiete gruppiert. Zur Analyse der wiederkehrenden Perioden extremen Regendefizits in jedem dieser Teilgebiete wird die Theorie extremer Ereignisse verwendet, wobei die log-Pearson-Häufigkeitsverteilung vom Typ III eher in einem räumlichen als zeitlichen Zusammenhang verwendet wird. Die sich daraus ergebenden Schätzungen für wiederkehrende Perioden von 2, 5 und 10 Jahren werden mit den Mustern verglichen, die mit Hilfe der auf alle 306 Stationen einzeln angewandten Gaußschen Häufigkeitsverteilung gewonnen wurden. Die Abschätzung 50jähriger und 100jähriger Ereignisse wird ebenfalls besprochen.

---

---

With 6 Figures     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

Public perceptions of rainfall change in India

People’s perceptions of changes in local weather patterns are an important precursor to proactive adaptation to climate change. In this paper, we consider public perceptions of changes in average rainfall in India, analyzing the relationship between perceptions and the instrumental record. Using data from a national sample survey, we find that local instrumental records of precipitation are a strong predictor of perceived declines in rainfall. Perceptions of decreasing rainfall were also associated with perceptions of changes in extreme weather events, such as decreasing frequency of floods and severe storms, increasing frequency of droughts, and decreasing predictability of the monsoon. Higher social vulnerability—including low perceived adaptive capacity and greater food and livelihood dependence on local weather—was also associated with perceptions of decreasing rainfall. While both urban and rural respondents were likely to perceive local changes in precipitation, we show that rural respondents in general were more sensitive to actual changes in precipitation. Individual perceptions of changes in local climate may play an important role in shaping vulnerability to global climate change, adaptive behavior, and support for adaptation and mitigation policies. Awareness of local climate change is therefore particularly important in regions where much of the population is highly exposed and sensitive to the impacts of climate change.     

Groundwater depletion limits the scope for adaptation to increased rainfall variability in India

Recent studies have found that increasing intra-seasonal precipitation variability will lead to substantial reductions in rice production in India by 2050, independently of the effect of rising temperatures. However, these projections do not account for the possibility of adaptations, of which the expansion of irrigation is the primary candidate. Using historical data on irrigation, rice yields, and precipitation, I show that irrigated locations experience much lower damages from increasing precipitation variability, suggesting that the expansion of irrigation could protect Indian agriculture from this future threat. However, accounting for physical water availability shows that under current irrigation practices, sustainable use of irrigation water can mitigate less than a tenth of the climate change impact. Moreover, if India continues to deplete its groundwater resources, the impacts of increased variability are likely to increase by half.     

Wavelet-based combination approach for modeling sub-divisional rainfall in India

Agriculture in India is highly sensitive to climatic variations particularly to rainfall and temperature; therefore, any change in rainfall and temperature will influence crop yields. An understanding of the spatial and temporal distribution and changing patterns in climatic variables is important for planning and management of natural resources. Time series analysis of climate data can be a very valuable tool to investigate its variability pattern and, maybe, even to predict short- and long-term changes in the series. In this study, the sub-divisional rainfall data of India during the period 1871 to 2016 has been investigated. One of the widely used powerful nonparametric techniques namely wavelet analysis was used to decompose and de-noise the series into time–frequency component in order to study the local as well as global variation over different scales and time epochs. On the decomposed series, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models were applied and by means of inverse wavelet transform, the prediction of rainfall for different sub-divisions was obtained. To this end, empirical comparison was carried out toward forecast performance of the approaches namely Wavelet-ANN, Wavelet-ARIMA, and ARIMA. It is reported that Wavelet-ANN and Wavelet-ARIMA approach outperforms the usual ARIMA model for forecasting of rainfall for the data under consideration.     

SVD方法在前期500hPa环流与贵州春季降水关系中的应用

基于500hPa高度场资料和贵州春季降水场资料,采用奇异值分解(SVD)方法,分析高度场与降水场的关系。结果表明:奇异值分解方法前8个奇异向量占总方差的80%以上,取前8个奇异向量已能代表贵州春季降水的主要分布;春季降水与前期冬季500hPa高度场分布有很好的匹配关系,且不同年份可能呈反位相分布;贵州春季降水除了通常的一致偏多(或偏少)外,还存在东南—西北准对称型分布;当冬季500hPa高度场距平场呈反位相分布时,即除北美地区负距平外,其余地区均呈中低纬负距平、高纬度正距平分布,贵州春季降水为一致的正距平分布。     

Trends in the annual extreme rainfall events of 1 to 3 days duration over India

Summary In this paper, the annual extreme rainfall series in the time scale of 1 to 3 days duration at 316 stations, well distributed over the Indian region, covering 80-years of rainfall data from 1901 to 1980 were analysed for trend and persistence using standard statistical tests. It has been found that the annual extreme rainfall records of most stations are free from trend and persistence. However, the extreme rainfall series at stations over the west coast north of 12°N and at some stations to the east of the Western Ghats over the central parts of the Peninsula showed a significant increasing trend at 95% level of confidence. Stations over the southern Peninsula and over the lower Ganga valley have been found to exhibit a decreasing trend at the same level of significance. The data series of the stations which showed trends were subjected to a 10-year moving average and the resulting smoothed series have been discussed. It may be said that this increasing or decreasing trend in the annual extreme rainfall events at a few places will have tremendous implications in the hydrologic studies and dam design projects.With 9 Figures     

A further note on extreme monsoonal rainfall deficits in India

Summary In a previous paper, maps were provided of the extreme monsoonal rainfall deficits likely to occur somewhere within individual Standard Meteorological Sub-Divisions in India. The present paper extends this study to similar evaluations for areas of radius 150 km around each of the 306 stations used in the previous study. Maps are presented of percentage rainfall deficits (or percentage of average values) with return periods of 2, 5, 10 and 50 years, and of the spatial pattern of return periods for deficits of 40%, 50%, 60% and 70% below the average. In addition, there are graphs for 25 stations displaying the relationships between deficit intensity and return period.

---

Zusammenfassung In einer vorhergehenden Arbeit wurden Karten über extreme Monsonregendefizite vorgelegt, wie sie wahrscheinlich innerhalb der einzelnen meteorologischen Untereinheiten Indiens vorkommen. Diese Arbeit präzisiert diese Studien auf Gebiete im Umkreis von 150 km jeder der 306 schon früher verwendeten Meßstationen. Hierbei werden Karten vorgelegt, die sowohl Prozentsätze der Regendefizite (bzw. der Durchschnittswerte) für Wiederholungszeiten von 2, 5, 10 und 50 Jahren als auch räumliche Muster der Wiederholungszeiten für Defizite von 40, 50, 60 und 70% unter dem Durchschnittswert angeben. Dem sind Grafiken von 25 Stationen beigefügt, die die Zusammenhänge von Defizitintensität und Wiederholungszeit zeigen.

---

---

With 4 Figures