D. S. Pai

Increasing Trend of “Break-Monsoon” Conditions Over India—Role of Ocean–Atmosphere Processes in the Indian Ocean

Analysis of daily rainfall data over India during the period 1951-2007 reveal an increased propensity in the occurrence of ldquomonsoon-breaksrdquo over the subcontinent. The increasing trend is seen both in the duration and frequency of monsoon-breaks over the subcontinent, the causes for which are investigated using in situ, satellite, and reanalysis data products. While noting that the increasing trend of break-monsoon conditions is consistently related to changes in large-scale monsoon circulation and vertically integrated moisture transport; the findings also point to the role of sea surface temperature (SST) warming trend (0.015 degC middotyear-1) in the tropical eastern Indian Ocean (IO) in inducing anomalous changes favorable for the increased propensity of monsoon-breaks. The results indicate that the SST warming in the tropical eastern IO has altered the ocean-atmosphere processes in a manner as to intensify the near-equatorial trough over the IO, but has led to a weakening of the southwest summer monsoon flow in recent decades into the Indian landmass.

Comparison of TMPA-3B42 Versions 6 and 7 Precipitation Products with Gauge-Based Data over India for the Southwest Monsoon Period

AbstractThe upgraded version 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products is available to the user community. In this paper, two successive versions of the TMPA-3B42 research monitoring product, version 6 (V6) and V7, at the daily scale are evaluated over India during the southwest monsoon with gauge-based data for a 13-yr (1998–2010) period. Over typical monsoon rainfall zones, biases are improved by 5%–10% in V7 over the regions of higher rainfall like the west coast, northeastern, and central India. A similar reduced bias is seen in V7 over the rain-shadow region located in southeastern India. In terms of correlation, anomaly correlation, and RMSE, a marginal improvement is seen in V7. Additionally, in all-India summer monsoon rainfall amounts, mean, interannual values, and standard deviation show an overall improvement in V7. Different skill metrics over typical subregions within India show an improvement of the monsoon rainfall represe...

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

SummaryUsing 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.

Variability and Trends of Extreme Rainfall and Rainstorms

In this chapter, variability and long-term trends of heavy rainfall events and rainstorms over India during the monsoon season (June to September) are documented. For analyzing extreme rainfall events, rain gauge station and gridded data for the period 1901–2010 have been used. For studying rainstorms, another gridded rainfall data set of 1951–2010 also has been used. The trend analyses revealed increasing trends in the frequency of dry days in most parts of the country during the winter, pre-monsoon, and southwest monsoon seasons. Frequency of very light rain and light-to-moderate rain events has decreased significantly over most of the country. Both the station and gridded data have shown significant increasing trends of very heavy to extremely heavy rainfall events over most parts of the country. Over Central India, extreme rainfall events show significant decadal variations which could be related to variations in sea surface temperatures over the tropical oceans. Over the period 1901–2010, heavy rainfall events show an increasing trend of six percent per decade. Further, an analysis is made on rainstorms over North India where majority of rainstorms cause floods over North India. Frequency of rainstorms has shown an increasing trend of 4 rainstorms (50 % increase) in 65 years (1951–2015). Similarly, the duration of rainstorms has shown an increase of about 15 days (80 % increase) during the period 1951–2015, which is also significant. Both the increases are statistically significant at the 99 % confidence level.

On the spatial coherence of sub-seasonal to seasonal Indian rainfall anomalies

The spatial coherence of interannual variations of sub-seasonal to seasonal anomalies in Indian summer monsoon rainfall is investigated at 0.25° spatial resolution using various metrics, including estimates of the number of degrees of freedom, the spatial scale of daily wet “patches”, as well as relationships between local and regional-scale rainfall anomalies and the monsoon circulation. Spatial coherence of interannual rainfall variations is generally found to peak near monsoon onset, in late May–June over Monsoonal India, and again during the withdrawal stage in September–October. However, the spatial coherence and correlations between local rainfall and the regional-scale monsoon circulation decrease during the core phase of the monsoon between early July and late August, when the interannual variability of local-scale amounts tend to be more tightly related to mean daily intensity rather than to the frequency of wet days. The drop in spatial coherence during the core phase is related to increases in the number and intensity of wet “patches” of daily rainfall while their mean spatial extent remains similar throughout the monsoon season. The core phase, with large values of precipitable water, is characterized by very variable daily rainfall amounts across gridpoints, as a consequence of the near exponential distribution of daily rainfall. The interannual variations of sub-seasonal amounts are then dominated by very wet days, which tend to be rather randomly distributed. This contrasts with the onset and withdrawal phases where the mean of the exponential is smaller, and where interannual variations in the timing of regional-scale onset and end of the monsoon predominate. The early and late phases may thus be more potentially predictable than the core of the monsoon season.

Long Term Trends in the Extreme Rainfall Events over India

Rainfall and surface air temperature are the two key elements of climate that are commonly used as indicators of global climate change due to the availability of long time series of these elements from most parts of the world. Rainfall, a component of terrestrial hydrological cycle, determines the availability of water and the level of the soil moisture. During the last few decades, rainfall extremes have been found to be increasing around the world with distinct regional differences, and the increase is linked to the warming of the atmosphere which has taken place since pre-industrial times (IPCC 2007). Its immediate implication is the increased flood risk around the world. In India, there have been several studies on daily extreme rainfall events over the region based on station and grid point rainfall data (Sen Roy and Balling 2004; Joshi and Rajeevan 2006; Goswami et al. 2006; Rajeevan et al. 2008; Ghosh et al. 2009; Guhathakurta et al. 2011).

Variability of Meteorological Droughts Over India

The variability of meteorological droughts over India for the period 1901–2010 is examined using district-wise and all-India drought indices, viz Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI). All-India droughts were observed during 18 % of the years considered. Even though frequency of moderate district-wide drought conditions occurs over most parts of the country, more intense droughts are mainly observed over north and northwest India and neighboring Central India. The warmer SSTs over the tropical oceans are found to be significantly associated with the variability of meteorological droughts over India. The present analysis reveals that there is a significant increasing trend in the intensity and areal coverage of moderate droughts over India during the recent years, since 1950s.

Heat and Cold Waves Over India

Using daily maximum temperature of 103 stations during the hot weather season (April–June or AMJ) for the period 1961–2010 and daily minimum temperature data of 86 stations during the cold weather season (December–February or DJF) for the period 1971–2010 from Indian main land, various statistical aspects of heat waves (HWs) and cold waves (CWs) have been examined. The trends in the season frequency of these extreme temperature events and their association with the El Nino/La Nina events have also been examined. During AMJ, HWs are generally experienced over the north, north-west, central, east India and north-east Peninsula [together called core HW zone (CHZ)] with highest frequency during May. During DJF, the CWs are generally experienced in the core CW zone (CCZ) that is nearly same as CHZ but includes Jammu and Kashmir and excludes coastal Andhra Pradesh with highest frequency during January. Appreciable increase (decrease) in the frequency of the HW days was observed during El Nino (La Nina) events. Exactly opposite association was observed in case of CW days. Appreciable decadal variation was observed in the frequency, spatial coverage and area of maximum frequency both in the HW/SHW and CW/SCW days. Significant increasing (decreasing) trends in the HW (CW) days were observed in many stations from CHZ (CCZ). The observed trends in HWs and CWs over India are in tune with similar trends observed over various other parts of the world. It is desired to have a proper operational service system in the country for the advance warning of the HWs and CWs and proper public information campaigns on the dangers of these extreme temperature events.

Evaluation of multi-satellite rainfall products over India during monsoon

Simulation and prediction of Indian monsoon rainfall at scales from days-to-season is a challenging task for numerical modelling community worldwide. Gridded estimates of daily rainfall data are required for both land and oceanic regions for model validation, process studies and in turn for model development. Due to recent developments in satellite meteorology, it has become possible to produce realistic near real-time gridded rainfall datasets at operational basis by combining satellite estimates with rain gauge values and other available in-situ observations. Microwave and space based radar based estimates of rainfall has revolutionised the preparation of rainfall datasets especially for tropics. However, a variety of multi-satellite products are available over Indian monsoon region from a variety of sources. Popular products like TRMM TMPA3B42 (RT and V7), GsMaP, CPC/RFE, GPCP and GPM are available to end users in various space/time scales for applications and model validation. In this study, we show the representation and skill of monsoon rainfall from a variety of multi-satellite products over the Indian region. The bias and skill of multi-satellite rainfall are evaluated against gauge based observations. It was found that the TRMM based TMPA was one of the best dataset for Indian monsoon region. Attempt is made to compare the latest GPM based data with other products. The GPM based rainfall product is seen to be superior compared to TRMM.