A study of vertical cloud structure of the Indian summer monsoon using CloudSat data

Precise specification of the vertical distribution of cloud optical properties is important to reduce the uncertainty in quantifying the radiative impacts of clouds. The new global observations of vertical profiles of clouds from the CloudSat mission provide opportunities to describe cloud structures and to improve parameterization of clouds in the weather and climate prediction models. In this study, four years (2007–2010) of observations of vertical structure of clouds from the CloudSat cloud profiling radar have been used to document the mean vertical structure of clouds associated with the Indian summer monsoon (ISM) and its intra-seasonal variability. Active and break monsoon spells associated with the intra-seasonal variability of ISM have been identified by an objective criterion. For the present analysis, we considered CloudSat derived column integrated cloud liquid and ice water, and vertically profiles of cloud liquid and ice water content. Over the South Asian monsoon region, deep convective clouds with large vertical extent (up to 14 km) and large values of cloud water and ice content are observed over the north Bay of Bengal. Deep clouds with large ice water content are also observed over north Arabian Sea and adjoining northwest India, along the west coast of India and the south equatorial Indian Ocean. The active monsoon spells are characterized by enhanced deep convection over the Bay of Bengal, west coast of India and northeast Arabian Sea and suppressed convection over the equatorial Indian Ocean. Over the Bay of Bengal, cloud liquid water content and ice water content is enhanced by ~90 and ~200 % respectively during the active spells. An interesting feature associated with the active spell is the vertical tilting structure of positive CLWC and CIWC anomalies over the Arabian Sea and the Bay of Bengal, which suggests a pre-conditioning process for the northward propagation of the boreal summer intra-seasonal variability. It is also observed that during the break spells, clouds are not completely suppressed over central India. Instead, clouds with smaller vertical extent (3–5 km) are observed due to the presence of a heat low type of circulation. The present results will be useful for validating the vertical structure of clouds in weather and climate prediction models.     

Comparison of intra-seasonal forecast of Indian summer monsoon between two versions of NCEP coupled models

The real-time forecasting of monsoon activity over India on extended range time scale (about 3 weeks) is analyzed for the monsoon season of 2012 during June to September (JJAS) by using the outputs from latest (CFSv2 [Climate Forecast System version 2]) and previous version (CFSv1 [Climate Forecast System version 1]) of NCEP coupled modeling system. The skill of monsoon rainfall forecast is found to be much better in CFSv2 than CFSv1. For the country as a whole the correlation coefficient (CC) between weekly observed and forecast rainfall departure was found to be statistically significant (99 % level) at least for 2 weeks (up to 18 days) and also having positive CC during week 3 (days 19–25) in CFSv2. The other skill scores like the mean absolute error (MAE) and the root mean square error (RMSE) also had better performance in CFSv2 compared to that of CFSv1. Over the four homogeneous regions of India the forecast skill is found to be better in CFSv2 with almost all four regions with CC significant at 95 % level up to 2 weeks, whereas the CFSv1 forecast had significant CC only over northwest India during week 1 (days 5–11) forecast. The improvement in CFSv2 was very prominent over central India and northwest India compared to other two regions. On the meteorological subdivision level (India is divided into 36 meteorological subdivisions) the percentage of correct category forecast was found to be much higher than the climatology normal forecast in CFSv2 as well as in CFSv1, with CFSv2 being 8–10 % higher in the category of correct to partially correct (one category out) forecast compared to that in CFSv1. Thus, it is concluded that the latest version of CFS coupled model has higher skill in predicting Indian monsoon rainfall on extended range time scale up to about 25 days.     

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.     

Variability of the TRMM-PR total and convective and stratiform rain fractions over the Indian region during the summer monsoon

Level 3 (3A25) TRMM Precipitation Radar (PR) data are used for 13 years period (1998–2010) to prepare climatology of TRMM PR derived near surface rain (Total rain) and rain fractions for the 4-months duration of Indian Summer Monsoon season (June–September) as well as for individual months. It is found that the total rain is contributed mostly (99 %) by two rain fractions i.e. stratiform and convective rain fractions for the season as well as on the monthly basis. It is also found that total rain estimates by PR are about 65 % of the gauge measured rain over continental India as well as on sub-regional basis. Inter-annual variability of TRMM-PR rain estimates for India mainland and its sub-regions as well as over the neighboring oceanic regions, in terms of coefficient of variability (CV) is discussed. The heaviest rain region over north Bay of Bengal (BoB) is found to have the lowest CV. Another sub-region of low CV lies over the eastern equatorial Indian ocean (EEIO). The CVs of total rain as well as its two major constituents are found to be higher on monthly basis compared to seasonal basis. Existence of a well known dipole between the EEIO and the north BoB is well recognized in PR data also. Significant variation in PR rainfall is found over continental India between excess and deficit monsoon seasons as well as between excess and deficit rainfall months of July and August. Examination of rainfall fractions between the BoB and Central India on year to year basis shows that compensation in rainfall fractions exists on monthly scale on both the regions. Also on the seasonal and monthly scales, compensation is observed in extreme monsoon seasons between the two regions. However, much less compensation is observed between the north BoB and EEIO belts in extreme rain months. This leads to speculation that the deficit and excess seasons over India may result from slight shift of the rainfall from Central India to the neighboring oceanic regions of north BoB. Contribution of stratiform and convective rain fractions have been also examined and the two fractions are found to contribute almost equally to the total rain. Results are further discussed in terms of the possible impact of the two rain fractions on circulation based on possible difference is vertical profiles of latent heat of two types of rain. Substantial differences in the lower and upper tropospheric circulation regimes are noticed in both deficit and excess monsoon months/seasons, emphasizing the interaction between rainfall (latent heat) and circulation.     

Impact of domain size on the simulation of Indian summer monsoon in RegCM4 using mixed convection scheme and driven by HadGEM2

In this study, a smaller domain over India alone and a larger South Asia (SA) domain have been used in the Regional Climate Model version 4.2 (RegCM4.2) to examine the effect of the domain size on the Indian summer monsoon simulations. These simulations were carried out over a period of 36 years at 50 km horizontal resolution with the lateral boundary forcings of the UK Met Office Hadley Centre Global Circulation Model Version 2.0. Results show that the Indian summer monsoon rainfall is significantly reduced when the domain size for the model integration is reduced from SA to the Indian domain. In case of SA domain simulation, the Equitable Threat Scores have higher values in case of very light, light and moderate rainfall events than those in case of the Indian domain simulation. It is also found that the domain size of model integration has dominant impact on the simulated convective precipitation. The cross-equatorial flow and the Somali Jet are better represented in the SA simulation than those in the Indian domain simulation. The vertically integrated moisture flux over the Arabian Sea in the SA domain simulation is close to that in the NCEP/NCAR reanalysis while it is underestimated in the Indian domain simulation. It is important to note that when RegCM4.2 is integrated over the smaller Indian domain, the effects of the Himalayas and the moisture advection from the Indian seas are not properly represented in the model simulation and hence the monsoon circulation and associated rainfall are underestimated over 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.     

Cloud–aerosol coupled index in estimating the break phase of Indian summer monsoon

The Indian summer monsoon (ISM) is largely influenced by intra-seasonal variability like break and active phases of monsoon. In the present study, different cloud and aerosol parameters are considered and analyzed to formulate a cloud–aerosol coupled index (CACI) that can aid in forecasting the break phase of ISM. The method of principal component analysis is implemented to identify the significant cloud and aerosol parameters during break and active phases of ISM. The threshold ranges of each parameter are evaluated by using the normal probability density function. The result reveals that for break phase, the significant parameters are cloud water path (CWP), cloud optical depth, aerosol index, zonal wind (ZW), and meridional wind (MW) at 850 hPa pressure level whereas for active phase, the parameters found to be important are aerosol optical depth, CWP, ZW, and MW at 850 hPa pressure level. The significantly correlated (p?相似文献   

ENSO, IOD and Indian Summer Monsoon in NCEP climate forecast system

El Ni?o-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Indian Summer Monsoon rainfall features are explored statistically and dynamically using National Centers for Environment Prediction (NCEP) Climate Forecast System (CFSv1) freerun in relation to observations. The 100?years of freerun provides a sufficiently long homogeneous data set to find out the mean state, periodicity, coherence among these climatic events and also the influence of ENSO and IOD on the Indian monsoon. Differences in the occurrence of seasonal precipitation between the observations and CFS freerun are examined as a coupled ocean–atmosphere system. CFS simulated ENSO and IOD patterns and their associated tropical Walker and regional Hadley circulation in pure ENSO (PEN), pure IOD (PIO) and coexisting ENSO-IOD (PEI) events have some similarity to the observations. PEN composites are much closer to the observation as compared to PIO and PEI composites, which suggest a better ENSO prediction and its associated teleconnections as compared to IOD and combined phenomenon. Similar to the observation, the model simulation also show that the decrease in the Indian summer monsoon rainfall during ENSO phases is associated with a descending motion of anomalous Walker circulation and the increase in the Indian summer monsoon rainfall during IOD phase is associated with the ascending branch of anomalous regional Hadley circulation. During co-existing ENSO and IOD years, however, the fate of Indian summer monsoon is dictated by the combined influence of both of them. The shift in the anomalous descending and ascending branches of the Walker and Hadley circulation may be somewhat attributed to the cold (warm) bias over eastern (western) equatorial Indian Ocean basin, respectively in the model. This study will be useful for identifying some of the limitations of the CFS model and consequently it will be helpful in improving the model to unravel the realistic coupled ocean–atmosphere interactions for the better prediction of Indian Summer Monsoon.     

Local onset and demise of the Indian summer monsoon

This paper introduces an objective definition of local onset and demise of the Indian summer monsoon (ISM) at the native grid of the Indian Meteorological Department’s rainfall analysis based on more than 100 years of rain gauge observations. The variability of the local onset/demise of the ISM is shown to be closely associated with the All India averaged rainfall onset/demise. This association is consistent with the corresponding evolution of the slow large-scale reversals of upper air and ocean variables that raise the hope of predictability of local onset and demise of the ISM. The local onset/demise of the ISM also show robust internannual variations associated with El Nino and the Southern Oscillation and Indian Ocean dipole mode. It is also shown that the early monsoon rains over northeast India has a predictive potential for the following seasonal anomalies of rainfall and seasonal length of the monsoon over rest of India.

     

Seasonal prediction of Indian summer monsoon in NCEP coupled and uncoupled model

This study has identified probable factors that govern ISMR predictability. Furthermore, extensive analysis has been performed to evaluate factors leading to the predictability aspect of Indian Summer Monsoon Rainfall (ISMR) using uncoupled and coupled version of National Centers for Environmental Prediction Coupled Forecast System (CFS). It has been found that the coupled version (CFS) has outperformed the uncoupled version [Global Forecast System (GFS)] of the model in terms of prediction of rainfall over Indian land points. Even the spatial distribution of rainfall is much better represented in the CFS as compared to that of GFS. Even though these model skills are inadequate for the reliable forecasting of monsoon, it imparts the capacious knowledge about the model fidelity. The mean monsoon features and its evolution in terms of rainfall and large-scale circulation along with the zonal and meridional shear of winds, which govern the strength of the monsoon, are relatively closer to the observation in the CFS as compared to the GFS. Furthermore, sea surface temperature–rainfall relation is fairly realistic and intense in the coupled version of the model (CFS). It is found that the CFS is able to capture El Niño Southern Oscillation ISMR (ENSO-ISMR) teleconnections much strongly as compared to GFS; however, in the case of Indian Ocean Dipole ISMR teleconnections, GFS has the larger say. Coupled models have to be fine-tuned for the prediction of the transition of El Niño as well as the strength of the mature phase has to be improved. Thus, to sum up, CFS tends to have better predictive skill on account of following three factors: (a) better ability to replicate mean features, (b) comparatively better representation of air–sea interactions, and (c) much better portrayal of ENSO-ISMR teleconnections. This study clearly brings out that coupled model is the only way forward for improving the ISMR prediction skill. However, coupled model’s spurious representation of SST variability and mean model bias are detrimental in seasonal prediction.     

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.     

Meteorological subdivisional-level extended range forecast over India during southwest monsoon 2012

The real-time multi-model ensemble (MME)-based extended range (up to 3 weeks) forecast of monsoon rainfall over India during the 2012 monsoon season is analyzed using the outputs of European Centre for Medium Range Weather Forecasts (ECMWF) monthly forecast coupled model, National Centre for Environmental Prediction (NCEP) Climate Forecast System version 2 coupled model and Japan Meteorological Agency (JMA)’ ensemble prediction system. Although the individual models show useful skill in predicting the extended range forecast of monsoon, the MME forecast is found to be superior compared to these. For the country as a whole, the correlation coefficient (CC) between the observed and MME forecast rainfall departure is found to be statistically significant (99 % level) at least for 2 weeks (up to 18 days). Over the four homogeneous regions of India, the CC is found to be significant (above 95 % level) up to 2 weeks except in case of northeast India, which shows significant CC for week 1 (days 5–11) only. On the meteorological subdivision level (India is divided into 36 meteorological subdivisions) the mean percentage of correct forecast is found to be much higher than the climatology forecast. Considering the complex problem of forecasting of monsoon in the extended range timescales, the MME-based predictions for 2–3 weeks provide skillful results and useful guidance for application in agriculture and other sectors in India.     

A study on drought features of the Indian summer monsoon 2002

In this paper, a diagnostic study is carried out with global analysis data sets to determine how the large scale atmospheric circulation affecting the anomalous drought of the Indian summer monsoon 2002. The daily analysis obtained from National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) for the month of July is used to investigate the mean circulation characteristics and the large scale energetics over the Indian monsoon domain. Examination of rainfall revealed that the summer monsoon (JJAS) rainfall of 2002 over India is 22% below normal in which the large deficit of 56% below normal rainfall in July. The recent past drought during summer season of 2004 and 2009 are 12 and 23%, respectively, below normal rainfall. The large deficit of rainfall in 2009 is from the June month with 48% below normal rainfall, where as 2004 drought contributed from July (19%) and August (24%). Another significant facet of the rainfall in July 2002 is lowest ever recorded in the past 138 years (1871–2008). The circulation features illustrated weak low level westerly wind at 850 hPa (Somali Jet) in July during large deficit rainfall years of 1987 and 2002 with a reduction of about 30% when compared with the excess and normal rainfall years of 1988 and 2003. Also, tropical easterly jet at 150 hPa reduced by 15% during the deficit rainfall year of 2002 against the excess rainfall year of 1988. Both the jet streams are responsible for low level convergence and upper level divergence leading to build up moisture and convective activity to sustain the strength of the monsoon circulation. These changes are well reflected in reduction of tropospheric moisture profile considerably. It is found that the maximum number of west pacific cyclonic system during July 2002 is also influenced for large deficit rainfall over India. The dynamic, thermodynamic and energetic clearly show the monsoon break type situation over India in the month of July 2002 resulting less convective activity and the reduction of moisture. The large diabatic heating, flux convergence of heat and moisture over south east equatorial Indian Ocean are also responsible for drought situation in July 2002 over the Indian region.     

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.     

On northward movement of convergence zones along west coast of India in a real-time forecast

The present study addresses the depiction of regional features in the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) real-time products associated with the onset of Indian summer monsoon 2006 along the west coast of India. This study attempts to understand some atmospheric dynamical processes that give rise to the northward shifting of the convergence zones in the sub-daily scale leading to the onset over Mumbai. The comparison of analysis and forecast shows that NCEP GFS appears to follow the analysis till 24 h, but deviates thereafter. The most notable feature in analyses is the distinct meridional asymmetries in the vorticity field with respect to the convection center. It is identified that the equivalent barotropic structure of vorticity north of the convection center is the main forcing for the northward movement of convergence zones. The composite meridional–vertical structure of each term in the vorticity budget reveals the importance of convective term in the upper atmosphere (700–200 hPa) and the stretching term in the lower atmosphere (1,000–700 hPa) with a lesser contribution of the tilting term. From an analysis of a simplified vorticity equation by retaining these dominant terms and by comparing the evolution of the diabatic heating, it is concluded that the inaccuracies in the model’s representation of convection led to the weakening of barotropic westerlies in the forecast.     

Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001–2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.     

Eastward propagating MJO during boreal summer and Indian monsoon droughts

Improved understanding of underlying mechanism responsible for Indian summer monsoon (ISM) droughts is important due to their profound socio-economic impact over the region. While some droughts are associated with ‘external forcing’ such as the El-Niño and Southern Oscillation (ENSO), many ISM droughts are not related to any known ‘external forcing’. Here, we unravel a fundamental dynamic process responsible for droughts arising not only from external forcing but also those associated with internal dynamics. We show that most ISM droughts are associated with at least one very long break (VLB; breaks with duration of more than 10 days) and that the processes responsible for VLBs may also be the mechanism responsible for ISM droughts. Our analysis also reveals that all extended monsoon breaks (whether co-occurred with El-Niño or not) are associated with an eastward propagating Madden–Julian Oscillation (MJO) in the equatorial Indian Ocean and western Pacific extending to the dateline and westward propagating Rossby waves between 10° and 25°N. The divergent Rossby wave associated with the dry phase of equatorial convection propagates westward towards Indian land, couple with the northward propagating dry phase and leads to the sustenance of breaks. Thus, the propensity of eastward propagating MJO during boreal summer is largely the cause of monsoon droughts. While short breaks are not accompanied by westerly wind events (WWE) over equatorial western Pacific favorable for initiating air–sea interaction, all VLBs are accompanied by sustained WWE. The WWEs associated with all VLB during 1975–2005 initiate air–sea interaction on intraseasonal time scale, extend the warm pool eastward allowing the convectively coupled MJO to propagate further eastward and thereby sustaining the divergent circulation over India and the monsoon break. The ocean–atmosphere coupling on interannual time scale (such as El-Niño) can also produce VLB, but not necessary.     

Impacts of Land Process on the Onset and Evolution of Asian Summer Monsoon in the NCEP Climate Forecast System

Impacts of land models and initial land conditions(ICs) on the Asian summer monsoon,especially its onset,were investigated using the NCEP Climate Forecast System(CFS).Two land models,the Oregon State University(OSU) land model and the NCEP,OSU,Air Force,and Hydrologic Research Laboratory(Noah) land model,were used to get parallel experiments.The experiments also used land ICs from the NCEP/Department of Energy(DOE) Global Reanalysis 2(GR2) and the Global Land Data Assimilation System(GLDAS).Previous studies have demonstrated that,a systematic weak bias appears in the modeled monsoon,and this bias may be related to a cold bias over the Asian land mass.Results of the current study show that replacement of the OSU land model by the Noah land model improved the model’s cold bias and produced improved monsoon precipitation and circulation patterns.The CFS predicted monsoon with greater proficiency in El Nin o years,compared to La Nin a years,and the Noah model performed better than the OSU model in monsoon predictions for individual years.These improvements occurred not only in relation to monsoon onset in late spring but also to monsoon intensity in summer.Our analysis of the monsoon features over the India peninsula,the Indo-China peninsula,and the South Chinese Sea indicates different degrees of improvement.Furthermore,a change in the land models led to more remarkable improvement in monsoon prediction than did a change from the GR2 land ICs to the GLDAS land ICs.     

A comparative study of the Indian summer monsoon hydroclimate and its variations in three reanalyses

This study examines the Indian summer monsoon hydroclimate in the National Centers for Environmental Prediction (NCEP)-Department of Energy (DOE) Reanalysis (R2), the Climate Forecast System Reanalysis (CFSR), and the Modern Era Retrospective-Analysis for Research and Applications (MERRA). The three reanalyses show significant differences in the climatology of evaporation, low-level winds, and precipitable water fields over India. For example, the continental evaporation is significantly less in CFSR compared to R2 and MERRA. Likewise the mean boreal summer 925?hPa westerly winds in the northern Indian Ocean are stronger in R2. Similarly the continental precipitable water in R2 is much less while it is higher and comparable in MERRA and CFSR. Despite these climatological differences between the reanalyses, the climatological evaporative sources for rain events over central India show some qualitative similarities. Major differences however appear when interannual variations of the Indian summer monsoon are analyzed. The anomalous oceanic sources of moisture from the adjacent Bay of Bengal and Arabian Sea play a significant role in determining the wet or dry year of the Indian monsoon in CFSR. However in R2 the local evaporative sources from the continental region play a more significant role. We also find that the interannual variability of the evaporative sources in the break spells of the intraseasonal variations of the Indian monsoon is stronger than in the wet spells. We therefore claim that instead of rainfall, evaporative sources may be a more appropriate metric to observe the relationship between the seasonal monsoon strength and intraseasonal activity. These findings are consistent across the reanalyses and provide a basis to improve the predictability of intraseasonal variability of the Indian monsoon. This study also has a bearing on improving weather prediction for tropical cyclones in that we suggest targeting enhanced observations in the Bay of Bengal (where it is drawing the most moisture from) for improved analysis during active spells of the intraseasonal variability of the Indian monsoon. The analysis suggests that the land–atmosphere interactions contribute significant uncertainty to the Indian monsoon in the reanalyses, which is consistent with the fact that most of the global reanalyses do not assimilate any land-surface data because the data are not available. Therefore, the land–atmosphere interaction in the reanalyses is highly dependent on the land-surface model and it’s coupling with the atmospheric model.     

Possible role of warm SST bias in the simulation of boreal summer monsoon in SINTEX-F2 coupled model

Reasonably realistic climatology of atmospheric and oceanic parameters over the Asian monsoon region is a pre-requisite for models used for monsoon studies. The biases in representing these features lead to problems in representing the strength and variability of Indian summer monsoon (ISM). This study attempts to unravel the ability of a state-of-the-art coupled model, SINTEX-F2, in simulating these characteristics of ISM. The coupled model reproduces the precipitation and circulation climatology reasonably well. However, the mean ISM is weaker than observed, as evident from various monsoon indices. A wavenumber–frequency spectrum analysis reveals that the model intraseasonal oscillations are also weaker-than-observed. One possible reason for the weaker-than-observed ISM arises from the warm bias, over the tropical oceans, especially over the equatorial western Indian Ocean, inherent in the model. This warm bias is not only confined to the surface layers, but also extends through most of the troposphere. As a result of this warm bias, the coupled model has too weak meridional tropospheric temperature gradient to drive a realistic monsoon circulation. This in turn leads to a weakening of the moisture gradient as well as the vertical shear of easterlies required for sustained northward propagation of rain band, resulting in weak monsoon circulation. It is also noted that the recently documented interaction between the interannual and intraseasonal variabilities of ISM through very long breaks (VLBs) is poor in the model. This seems to be related to the inability of the model in simulating the eastward propagating Madden–Julian oscillation during VLBs.