Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models

Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean–atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959–1979) are closer to the ‘perfect model’ (attainable) score but, large differences are observed between ‘actual’ skill and ‘perfect model’ skill in the recent period (1980–2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.     

New regression model for Indian summer monsoon rainfall

Summary Based on the study of 45 years (1948–1992) data, the average lowest MSL pressure of heat low over central Pakistan and adjoining northwest India of the month of May is found to have potential as a parameter for predicting all India Summer monsoon seasonal rainfall. This new parameter is seen to have stable and significant correlation with monsoon rainfall. Its correlation coefficients for different periods are found significant at 0.1% to 1% level of significance. The stability of the correlation coefficients was tested using 10, 20 and 30 year sliding windows. This test revealed that it is the most dependable parameter in comparison with 7 of the well known parameters analysed in this study. Regression models have been developed considering this new parameter along with other circulation parameters. The regression models developed are seen to perform very well for the independent data. The Root Mean Square Error (RMSE) values of some of these models, for independent data, are smaller than those of similar regression models reported in literature.With 8 Figures     

Pacific decadal oscillation and variability of the Indian summer monsoon rainfall

Recent studies have furnished evidence for interdecadal variability in the tropical Pacific Ocean. The importance of this phenomenon in causing persistent anomalies over different regions of the globe has drawn considerable attention in view of its relevance in climate assessment. Here, we examine multi-source climate records in order to identify possible signatures of this longer time scale variability on the Indian summer monsoon. The findings indicate a coherent inverse relationship between the inter-decadal fluctuations of Pacific Ocean sea surface temperature (SST) and the Indian monsoon rainfall during the last century. A warm (cold) phase of the Pacific interdecadal variability is characterized by a decrease (increase) in the monsoon rainfall and a corresponding increase (decrease) in the surface air temperature over the Indian subcontinent. This interdecadal relationship can also be confirmed from the teleconnection patterns evident from long-period sea level pressure (SLP) dataset. The SLP anomalies over South and Southeast Asia and the equatorial west Pacific are dynamically consistent in showing an out-of-phase pattern with the SLP anomalies over the tropical central-eastern Pacific. The remote influence of the Pacific interdecadal variability on the monsoon is shown to be associated with prominent signals in the tropical and southern Indian Ocean indicative of coherent inter-basin variability on decadal time scales. If indeed, the atmosphere–ocean coupling associated with the Pacific interdecadal variability is independent from that of the interannual El Niño-Southern Oscillation (ENSO), then the climate response should depend on the evolutionary characteristics of both the time scales. It is seen from our analysis that the Indian monsoon is more vulnerable to drought situations, when El Niño events occur during warm phases of the Pacific interdecadal variability. Conversely, wet monsoons are more likely to prevail, when La Niña events coincide during cold phases of the Pacific interdecadal variability.     

A common mode of variability of African and Indian monsoon rainfall at decadal timescale

There are many factors and mechanisms capable of influencing and perturbing rainfall in both African and Indian monsoon regions. Using observed data and ensembles of Atmospheric General Circulation Model simulations, evidence is presented that an association between the two systems exists on decadal timescales and the mechanism responsible for this common mode is suggested. Decadal variability of rainfall in the two monsoon systems results from a large scale forcing induced by an interplay of different ocean basins. The emerging pattern is characterized by warmer (cooler) equatorial and cooler (warmer) extratropical regions, more visible in the northern hemisphere. This large scale forcing pattern leads to an upper-level pressure gradient between the equator and the monsoon regions which modifies also the Tropical Easterly Jet, thus providing a potential link between the African and Indian monsoon. The response is baroclinic, therefore at low levels, the pressure gradient reverses and leads to increased (reduced) pressure over the Saharan and Indian region, both being favourable for a weakening (strengthening) of the respective monsoons. Therefore, the predictability of the monsoon trends depends mainly on how well the sea surface temperature modes, which modulate the monsoons variability, can be predicted.     

The Interannual variability of rainfall over homogeneous regions of Indian summer monsoon

Theoretical and Applied Climatology - The Indian subcontinent, due to its enormous variety of geographical features, is associated with inhomogeneity. Hence, in the present study, we have...     

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.     

Evaluation of precipitation prediction skill of IMD operational NWP system over Indian monsoon region

Summary The study provides a concise and synthesized documentation of the current level of skill of the operational NWP model of India Meteorological Department based on daily 24 hours forecast run of the model during two normal monsoon years 2001 and 2003 making detailed inter-comparison with daily rainfall analysis from the use of high dense land rain gauge observations. The study shows that the model, in general, is able to capture three regions of climatologically heavy rainfall domains along Western Ghats, Northeast India and over east central India, over the domain of monsoon trough. However, the accuracy in prediction of location and magnitude of rainfall fluctuates considerably. The inter-comparison reveals that performance of the model rainfall forecast deteriorated in 2003 when rainfall over most parts of the region was significantly under-predicted. These features are also reflected in the error statistics. The study suggests that there is a need to maximize the data ingest in the model with a better data assimilation scheme to improve the rainfall forecast skill.     

Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system

We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satellite (oceanic surface wind, cloud motion wind, and cloud top temperature) observations obtained from the India Meteorological Department (IMD). After the successful inclusion of additional observational data using the 3DVAR data assimilation technique, the resulting reanalysis was able to successfully reproduce the structure of convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC). The location and intensity of the MTC were better simulated in the 3DV-ANA as compared to the CNTL. The results demonstrate that the improved initial conditions of the mesoscale model using 3DVAR enhanced the location and amount of rainfall over the Indian monsoon region. Model verification and statistical skill were assessed with the help of available upper-air sounding data. The objective verification further highlighted the efficiency of the data assimilation system. The improvements in the 3DVAR run are uniformly better as compared to the CNTL run for all the three cases. The mesoscale 3DVAR data assimilation system is not operational in the weather forecasting centers in India and a significant finding in this study is that the assimilation of Indian conventional and non-conventional observation datasets into numerical weather forecast models can help improve the simulation accuracy of meso-convective activities over the Indian monsoon region. Results from the control experiments also highlight that weather and regional climate model simulations with coarse analysis have high uncertainty in simulating heavy rain events over the Indian monsoon region and assimilation approaches, such as the 3DVAR can help reduce this uncertainty.     

Relationships between interannual variability in the Arabian Sea and Indian summer monsoon rainfall

Summary The interannual variability of the monthly mean upper layer thickness for the central Arabian Sea (5°N-15° N and 60° E-70° E) from a numerical model of the Indian Ocean during the period 1954–1976 is investigated in relation to Indian monsoon rainfall variability. The variability in the surface structure of the Somali Current in the western Arabian Sea is also briefly discussed. It is found that these fields show a great deal of interannual variability that is correlated with variability in Indian monsoon rainfall. Model upper layer thickness (H) is taken as a surrogate variable for thermocline depth, which is assumed to be correlated with sea surface temperature. In general, during the period 1967 to 1974, which is a period of lower than normal monsoon rainfall, the upper ocean warm water sphere is thicker (deeper thermocline which implies warmer surface water); in contrast, during the period 1954–1966, which is a period of higher than normal monsoon rainfall, the upper warm water sphere is thinner (shallower thermocline which implies cooler surface water). The filtered time series of uppper layer thickness indieates the presence of a quasi-biennial oscillation (QBO) during the wet monsoon period, but this QBO signal is conspicuously absent during the dry monsoon period.Since model H primarily responds to wind stress curl, the interannual variability of the stress curl is investigated by means of an empirical orthogonal function (EOF) analysis. The first three EOF modes represent more than 72% of the curl variance. The spatial patterns for these modes exhibit many elements of central Arabian Sea climatology. Features observed include the annual variation in the intensity of the summer monsoon ridge in the Arabian Sea and the annual zonal oscillation of the ridge during pre- and post-monsoon seasons. The time coefficients for the first EOF amplitude indicate the presence of a QBO during the wet monsoon period only, as seen in the ocean upper layer thickness.The variability in the model upper layer thickness is a passive response to variability in the wind field, or more specifically to variability in the Findlater Jet. When the winds are stronger, they drive stronger currents in the ocean and have stronger curl fields associated with them, driving stronger Ekman pumping. They transport more moisture from the southern hemisphere toward the Indian subcontinent, and they also drive a greater evaporative heat flux beneath the Findlater Jet in the Arabian Sea. It has been suggested that variability in the heat content of the Arabian Sea drives variability in Indian monsoon rainfall. The results of this study suggest that the opposite is true, that the northern Arabian Sea responds passively to variability in the monsoon system.With 10 Figures     

Simulation of Indian summer monsoon circulation and rainfall using RegCM3

Summary The Regional Climate Model RegCM3 has been used to examine its suitability in simulating the Indian summer monsoon circulation features and associated rainfall. The model is integrated at 55 km horizontal resolution over a South Asia domain for the period April–September of the years 1993 to 1996. The characteristics of wind at 850 hPa and 200 hPa, temperature at 500 hPa, surface pressure and rainfall simulated by the model over the Indian region are examined for two convective schemes (a Kuo-type and a mass flux scheme). The monsoon circulation features simulated by RegCM3 are compared with those of the NCEP/NCAR reanalysis and the simulated rainfall is validated against observations from the Global Precipitation Climatology Centre (GPCC) and the India Meteorological Department (IMD). Validation of the wind and temperature fields shows that the use of the Grell convection scheme yields results close to the NCEP/NCAR reanalysis. Similarly, the Indian Summer Monsoon Rainfall (ISMR) simulated by the model with the Grell convection scheme is close to the corresponding observed values. In order to test the model response to land surface changes such as the Tibetan snow depth, a sensitivity study has also been conducted. For such sensitivity experiment, NIMBUS-7 SMMR snow depth data in spring are used as initial conditions in the RegCM3. Preliminary results indicate that RegCM3 is very much sensitive to Tibetan snow. The model simulated Indian summer monsoon circulation becomes weaker and the associated rainfall is reduced by about 30% with the introduction of 10 cm of snow over the Tibetan region in the month of April.     

Probabilistic prediction of Indian summer monsoon rainfall using global climate models

Probabilistic seasonal predictions of rainfall that incorporate proper uncertainties are essential for climate risk management. In this study, three different multi-model ensemble (MME) approaches are used to generate probabilistic seasonal hindcasts of the Indian summer monsoon rainfall based on a set of eight global climate models for the 1982–2009 period. The three MME approaches differ in their calculation of spread of the forecast distribution, treated as a Gaussian, while all three use the simple multi-model subdivision average to define the mean of the forecast distribution. The first two approaches use the within-ensemble spread and error residuals of ensemble mean hindcasts, respectively, to compute the variance of the forecast distribution. The third approach makes use of the correlation between the ensemble mean hindcasts and the observations to define the spread using a signal-to-noise ratio. Hindcasts are verified against high-resolution gridded rainfall data from India Meteorological Department in terms of meteorological subdivision spatial averages. The use of correlation for calculating the spread provides better skill than the other two methods in terms of rank probability skill score. In order to further improve the skill, an additional method has been used to generate multi-model probabilistic predictions based on simple averaging of tercile category probabilities from individual models. It is also noted that when such a method is used, skill of probabilistic forecasts is improved as compared with using the multi-model ensemble mean to define the mean of the forecast distribution and then probabilities are estimated. However, skill of the probabilistic predictions of the Indian monsoon rainfall is too low.     

A coupled model study on ENSO, MJO and Indian summer monsoon rainfall relationships

Summary In this paper, we have tried to understand the ENSO, MJO and Indian summer monsoon rainfall relationships from observation as well as from coupled model results. It was the general feeling that El-Niño years are the deficient in Indian monsoon rainfall and converse being the case for the La-Niña years. Recent papers by several authors noted the failure of this relationship. We find that the model output does confirm a breakdown of this relationship. In this study we have seen that a statistically defined modified Indian summer monsoon rainfall (MISMR) index, a linearly regressed ISMR index and dynamical Webster index (WBSI), shows an inverse relationship with ENSO index during the entire period of integration (1987 to 1999). It is also seen from this study that the amplification of the MJO signals were large and the ENSO signals were less pronounced during the years of above normal ISMR. The MJO signal amplitudes were small and ENSO signals were strong during the years of deficient ISMR. It has been noted that here is a time lag between the MJO and ENSO signal in terms of their modulation aspect. If time lag is added with the ENSO signal then both signals maintain the amplitude modulation theory. A hypothesis is being proposed here to define a relationship between MJO and ENSO signals for the entire period between 1987 and 1999.Received September 18, 2002; revised November 22, 2002; accepted December 20, 2002 Published online: May 8, 2003     

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     

Indian summer monsoon rainfall predictability and variability associated with Northwest Pacific circulation in a suit of coupled model hindcasts

The Northwest Pacific (NWP) circulation (subtropical high) is an important component of the East Asian summer monsoon system. During summer (June–August), anomalous lower tropospheric anticyclonic (cyclonic) circulation appears over NWP in some years, which is an indicative of stronger (weaker) than normal subtropical high. The anomalous NWP cyclonic (anticyclonic) circulation years are associated with negative (positive) precipitation anomalies over most of Indian summer monsoon rainfall (ISMR) region. This indicates concurrent relationship between NWP circulation and convection over the ISMR region. Dry wind advection from subtropical land regions and moisture divergence over the southern peninsular India during the NWP cyclonic circulation years are mainly responsible for the negative rainfall anomalies over the ISMR region. In contrast, during anticyclonic years, warm north Indian Ocean and moisture divergence over the head Bay of Bengal-Gangetic Plain region support moisture instability and convergence in the southern flank of ridge region, which favors positive rainfall over most of the ISMR region. The interaction between NWP circulation (anticyclonic or cyclonic) and ISMR and their predictability during these anomalous years are examined in the present study. Seven coupled ocean–atmosphere general circulation models from the Asia-Pacific Economic Cooperation Climate Center and their multimodel ensemble mean skills in predicting the seasonal rainfall and circulation anomalies over the ISMR region and NWP for the period 1982–2004 are assessed. Analysis reveals that three (two) out of seven models are unable to predict negative (positive) precipitation anomalies over the Indian subcontinent during the NWP cyclonic (anticyclonic) circulation years at 1-month lead (model is initialized on 1 May). The limited westward extension of the NWP circulation and misrepresentation of SST anomalies over the north Indian Ocean are found to be the main reasons for the poor skill (of some models) in rainfall prediction over the Indian subcontinent. This study demonstrates the importance of the NWP circulation variability in predicting summer monsoon precipitation over South Asia. Considering the predictability of the NWP circulation, the current study provides an insight into the predictability of ISMR. Long lead prediction of the ISMR associated with anomalous NWP circulation is also discussed.     

A comparison of regional monsoon variability using monsoon indices

The present study aims to (a) examine meteorological basis for construction of regional monsoon indices and (b) explore the commonality and differences among tropical regional monsoons, especially the teleconnection and monsoon–ENSO relationship. We show that the area-averaged summer precipitation intensity is generally a meaningful precipitation index for tropical monsoons because it represents very well both the amplitude of annual cycle and the leading mode of year-to-year rainfall variability with a nearly uniform spatial pattern. The regional monsoon circulation indices can be defined in a unified way (measuring monsoon trough vorticity) for seven tropical monsoon regions, viz.: Indian, Australian, western North Pacific, North and South American, and Northern and Southern African monsoons. The structures of the tropical monsoons are commonly characterized by a pair of upper-level double anticyclones residing in the subtropics of both hemispheres; notably the winter hemispheric anticyclone has a barotropic structure and is a passive response. Two types of upper-level teleconnection patterns are identified. One is a zonal wave train emanating from the double anticyclones downstream along the westerly jets in both hemispheres, including Indian, Northern African and Australian monsoons; the other is a meridional wave train emanating from the double anticyclones polewards, such as the South American and western North Pacific monsoons. Over the past 55 years all regional summer monsoons have non-stationary relationship with ENSO except the Australian monsoon. The regional monsoon–ENSO relationship is found to have common changing points in 1970s. The relationships were enhanced for the western North Pacific, Northern African, North American and South American summer monsoons, but weakened for the Indian summer monsoon (with a recovery in late 1990s). Regardless the large regional differences, the monsoon precipitations over land areas of all tropical monsoon regions are significantly correlated with the ENSO, suggesting that ENSO drives global tropical monsoon rainfall variability. These results provide useful guidance for monitoring sub-seasonal to seasonal variations of the regional monsoons currently done at NCEP and for assessment of the climate models’ performances in representing regional and global monsoon variability.     

Mechanism of high rainfall over the Indian west coast region during the monsoon season

The mechanism responsible for high rainfall over the Indian west coast region has been investigated by studying dynamical, thermodynamical and microphysical processes over the region for the monsoon season of 2009. The European Centre for Medium-Range Weather Forecasts wind and NCEP flux data have been used to study the large scale dynamical parameters. The moist adiabatic and multi-level inversion stratifications are found to exist during the high and low rainfall spells, respectively. In the moist adiabatic stratification regime, shallow and deep convective clouds are found coexisting. The Cloud Aerosol Interaction and Precipitation Enhancement EXperiment aircraft data showed cloud updraft spectrum ranging from 1 to 10 m s^?1 having modal speed 1–2.5 m s^?1. The low updrafts rates provide sufficient time required for warm rain processes to produce rainfall from shallow clouds. The low cloud liquid water is observed above the freezing level indicating efficient warm rain process. The updrafts at the high spectrum end go above freezing level to generate ice particles produced due to mixed-phase rainfall process from deep convective clouds. With aging, deep convection gets transformed into stratiform type, which has been inferred through the vertical distribution of the large scale omega and heating fields. The stratiform heating, high latent heat flux, strong wind shear in the lower and middle tropospheric levels and low level convergence support the sustenance of convection for longer time to produce high rainfall spell. The advection of warm dry air in the middle tropospheric regions inhibits the convection and produce low rainfall spell. The mechanisms producing these spells have been summarized with the block diagram.