Indian Summer Monsoon Rainfall Characteristics During Contrasting Monsoon Years

The present paper presents a diagnostic study of two recent monsoon years, of which one is dry monsoon year (2009) and the other is wet monsoon year (2010). The study utilized the IMD gridded rainfall data set in addition to the Reynolds SST, NCEP-NCAR reanalysis wind and temperature products, and NOAA OLR. The study revealed that the months July and August are the most crucial months to decide whether the ISMR is wet or dry. However, during July 2009, most of the Indian subcontinent received more than 60 % in the central and western coastal regions. In a wet monsoon year, about 35–45 % of rainfall is contributed during June and July in most parts of India. During these years, the influence of features in the Pacific Ocean played vital role on the Indian summer monsoon rainfall. During 2009, Pacific SST was above normal in nino regions, characteristic of the El Nino structure; however, during 2010, the nino regions were clearly below normal temperature, indicating the La Nina pattern. The associated atmospheric general circulation through equatorial Walker and regional Hadley circulation modulates the tropospheric temperature, and hence the organized convective cloud bands. These cloud bands show different characteristics in northward propagation during dry and wet years of ISMR. During a dry year, the propagation speed and magnitudes are considerably higher than during a wet monsoon year.     

Role of the Himalayan Orography in Simulation of the Indian Summer Monsoon using RegCM3

In this study, sensitivity of the Indian summer monsoon simulation to the Himalayan orography representation in a regional climate model (RegCM) is examined. The prescribed height of the Himalayan orography is less in the RegCM model than the actual height of the Himalayas. Therefore, in order to understand the impact of the Himalayan orography representation on the Indian summer monsoon, the height of the Himalayan orography is increased (decreased) by 10 % from its control height in the RegCM model. Three distinct monsoon years such as deficit (1987), excess (1988) and normal rainfall years are considered for this study. The performance of the RegCM model is tested with the use of a driving force from the reanalysis data and a global model output. IMD gridded rainfall and the reanalysis-2 data are used as verification analysis to validate the model results. The RegCM model has the potential to represent mean rainfall distribution over India as well as the upper air circulation patterns and some of the semi-permanent features during the Indian summer monsoon season. The skill of RegCM is reasonable in representing the variation in circulation and precipitation pattern and intensity during two contrasting rainfall years. The simulated seasonal mean rainfall over many parts of India especially, the foothills of the Himalaya, west coast of India and over the north east India along with the whole of India are more when the orography height is increased. The low level southwesterly wind including the Somali jet stream as well as upper air circulation associated with the tropical easterly jet stream become stronger with the enhancement of the Himalayan orography. Statistical analysis suggests that the distribution and intensity of rainfall is represented better with the increased orography of RegCM by 10 % from its control height. Thus, representation of the Himalayan orography in the model is close to actual and may enhance the skill in seasonal scale simulation of the Indian summer monsoon.     

Role of Ocean in the Variability of Indian Summer Monsoon Rainfall

Asian summer monsoon sets in over India after the Intertropical Convergence Zone moves across the equator to the northern hemisphere over the Indian Ocean. Sea surface temperature (SST) anomalies on either side of the equator in Indian and Pacific oceans are found related to the date of monsoon onset over Kerala (India). Droughts in the June to September monsoon rainfall of India are followed by warm SST anomalies over tropical Indian Ocean and cold SST anomalies over west Pacific Ocean. These anomalies persist till the following monsoon which gives normal or excess rainfall (tropospheric biennial oscillation). Thus, we do not get in India many successive drought years as in sub-Saharan Africa, thanks to the ocean. Monsoon rainfall of India has a decadal variability in the form of 30-year epochs of frequent (infrequent) drought monsoons occurring alternately. Decadal oscillations of monsoon rainfall and the well-known decadal oscillation in SST of the Atlantic Ocean (also of the Pacific Ocean) are found to run parallel with about the same period close to 60 years and the same phase. In the active–break cycle of the Asian summer monsoon, the ocean and the atmosphere are found to interact on the time scale of 30–60 days. Net heat flux at the ocean surface, monsoon low-level jetstream (LLJ) and the seasonally persisting shallow mixed layer of the ocean north of the LLJ axis play important roles in this interaction. In an El Niño year, the LLJ extends eastwards up to the date line creating an area of shallow ocean mixed layer there, which is hypothesised to lengthen the active–break (AB) cycle typically from 1 month in a La Niña to 2 months in an El Niño year. Indian monsoon droughts are known to be associated with El Niños, and long break monsoon spells are found to be a major cause of monsoon droughts. In the global warming scenario, the observed rapid warming of the equatorial Indian ocean SST has caused the weakening of both the monsoon Hadley circulation and the monsoon LLJ which has been related to the observed rapid decreasing trend in the seasonal number of monsoon depressions.     

An anomalous cooling event observed in the Bay of Bengal during June 2009

Sea surface temperature (SST) variability over the Bay of Bengal (BoB) has the potential to trigger deep moist convection thereby affecting the active-break cycle of the monsoons. Normally, during the summer monsoon season, SST over the BoB is observed to be greater than 28°C which is a pre-requisite for convection. During June 2009, satellite observations revealed an anomalous basin-wide cooling and the month is noted for reduced rainfall over the Indian subcontinent. In this study, we analyze the likely mechanisms of this cooling event using both satellite and moored buoy observations. Observations showed deepened mixed layer, stronger surface currents, and enhanced heat loss at the surface in the BoB. Mixed layer heat balance analysis is carried out to resolve the relative importance of various processes involved. We show that the cooling event is primarily induced by the heat losses at the surface resulting from the strong wind anomalies, and advection and vertical entrainment playing secondary roles.     

Seasonal Prediction for the Indian Monsoon Region with FSU Ocean-atmosphere Coupled Model: Model Mean and 2002 Anomalous Drought

Seasonal climate prediction for the Indian summer monsoon season is critical for strategic planning of the region. The mean features of the Indian summer monsoon and its variability, produced by versions of the ‘Florida State University Coupled Ocean-Atmosphere General Circulation Model’ (FSUCGCM) hindcasts, are investigated for the period 1987 to 2002. The coupled system has full global ocean and atmospheric models with coupled assimilation. Four member models were created by choosing different combinations of parameterizations of the physical processes in the atmospheric model component. Lower level wind flow patterns and rainfall associated with the summer monsoon season are examined from this fully coupled model seasonal integrations. By comparing with observations, the mean monsoon condition simulated by this coupled model for the June, July and August periods is seen to be reasonably realistic. The overall spatial low-level wind flow patterns and the precipitation distributions over the Indian continent and adjoining oceanic regions are comparable with the respective analyses. The anomalous below normal large-scale precipitation and the associated anomalous low-level wind circulation pattern for the summer monsoon season of 2002 was predicted by the model three months in advance. For the Indian summer monsoon, the ensemble mean is able to reproduce the mean features better compared to individual member models.     

Numerical Study of the Intertropical Convergence Zone Over the Indian Ocean During the 1997 and 1998 Northeast Monsoon Episodes

—?The hydrostatic Naval Research Laboratory/North Carolina State University (NRL/NCSU) model was used to study the mesoscale dynamics and diurnal variability of the Intertropical Convergence Zone (ITCZ) over the Indian Ocean in the short-range period. To achieve this objective the initial conditions from two northeast monsoon episodes (29 January, 1997 and 29 January, 1998) were run for 48-hour simulations using a triple-nested grid version of the model with 1.5°?×?1.5°, 0.5°?×?0.5° and 0.17°?×?0.17° resolutions. The 1997 case represents a typical northeast monsoon episode, while the 1998 case depicts an abnormal monsoon episode during an El Niño event.¶Comparisons between the model-produced and analyzed mean circulation, wind speed, and associated rainfall for different spatial scales are presented. During the active northeast monsoon season in 1997, the major low-level westerly winds and associated high rainfall rates between 0° and 15°S were simulated reasonably well up to 24 hours. During the 1998 El Niño event, the model was capable of simulating weak anomalous easterly winds (between 0° and 15°S) with much lower rainfall rates up to 48 hours. In both simulations, the finest grid size resulted in largest rainfall rates consistent with Outgoing Longwave Radiation data.¶The model performance was further evaluated using the vertical profiles of the vertical velocity, the specific humidity and temperature differences between the model outputs and the analyses. It is found that during a typical northeast monsoon year, 1997, the water vapor content in the middle troposphere was largely controlled by the low-level convergence determined by strong oceanic heat flux gradient. In contrast, during the 1998 El Niño year moisture was present only in the lower troposphere. Due to strong subsidence associated with Walker circulation over the central and eastern Indian Ocean, deep convection was not present. Finally, the diurnal variations of the maximum rainfall, vertical velocity and total heat flux were noticeable only during the 1997 northeast monsoon year.     

Experimental Seasonal Forecast of Monsoon 2005 Using T170L42 AGCM on PARAM Padma

As a part of the Experimental Extended Range Monsoon Prediction Experiment, ensemble mode seasonal runs for the monsoon season of 2005 were made using the National Centre for Environmental Prediction (NCEP), T170L42 AGCM. The seasonal runs were made using six initial atmospheric conditions based on the NCEP operational analysis and with forecast monthly sea-surface temperature (SST) of the NCEP Coupled forecast system (CFS). These simulations were carried out on the PARAM Padma supercomputer of Centre for Development of Advanced Computing (C-DAC), India. The model climatology was prepared by integrating the model for ten years using climatological SST as the lower boundary. The climatology of the model compares well with the observed, in terms of the spatial distribution of rainfall over the Indian land mass. The model-simulated rainfall compares well with the Tropical Rainfall Measuring Mission (TRMM) estimates for the 2005 monsoon season. Compared to the model climatology (7.81 mm/day), the model had simulated a normal rainfall (7.75 mm/day) for the year 2005 which is in agreement with the observations (99% of long-term mean). However, the model could not capture the observed increase in September rainfall from that of a low value in August 2005. The circulation patterns simulated by the model are also comparable to the observed patterns. The ensemble mean onset is found to be nearer to the observed onset date within one pentad.     

Evaluation of Short-Range Forecasts from a Mesoscale Model Over the Indian Region During Monsoon 2006

This study examines the short-range forecast accuracy of the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) as applied to the July 2006 episode of the Indian summer monsoon (ISM) and the model's sensitivity to the choice of different cumulus parameterization schemes (CPSs), namely Betts-Miller, Grell (GR) and Kain-Fritsch (KF). The results showed that MM5 day 1 (0–24 h prediction) and day 2 (24–48 h prediction) forecasts using all three CPSs overpredicted monsoon rainfall over the Indian landmass, with the larger overprediction seen in the day 2 forecasts. Among the CPSs, the rainfall distribution over the Indian landmass was better simulated in forecasts using the KF scheme. The KF scheme showed better skill in predicting the area of rainfall for most of the rainfall thresholds. The root mean square error (RMSE) in day 1 and day 2 rainfall forecasts using different CPSs showed that rainfall simulated using the KF scheme agreed better with the observed rainfall. As compared to other CPSs, simulation using the GR scheme showed larger RMSE in wind speed prediction at 850 and 200 hPa over the Indian landmass. MM5 24-h temperature forecasts at 850 hPa with all the CPSs showed a warm bias of the order of 1 K over the Indian landmass and the bias doubled in 48-h model forecasts. The mean error in temperature prediction at 850 hPa over the Indian region using the KF scheme was comparatively smaller for all the forecast intervals. The model with all the CPSs overpredicted humidity at 850 hPa. The improved prediction by MM5 with the KF scheme is well complemented by the smaller error shown by the KF scheme in vertical distribution of heat and mean moist static energy in the lower troposphere. In this study, the KF scheme which explicitly resolve the downdrafts in the cloud column tended to produce more realistic precipitation forecasts as compared to other schemes which did not explicitly incorporate downdraft effects. This is an important result especially given that the area covered by monsoon-precipitating systems is largely from stratiform-type clouds which are associated with strong downdrafts in the lower levels. This result is useful for improving the treatment of cumulus convection in numerical models over the ISM region.     

Improvement of Monsoon Depressions Forecast with Assimilation of Indian DWR Data Using WRF-3DVAR Analysis System

An attempt is made to evaluate the impact of Doppler Weather Radar (DWR) radial velocity and reflectivity in Weather Research and Forecasting (WRF)-3D variational data assimilation (3DVAR) system for prediction of Bay of Bengal (BoB) monsoon depressions (MDs). Few numerical experiments are carried out to examine the individual impact of the DWR radial velocity and the reflectivity as well as collectively along with Global Telecommunication System (GTS) observations over the Indian monsoon region. The averaged 12 and 24 h forecast errors for wind, temperature and moisture at different pressure levels are analyzed. This evidently explains that the assimilation of radial velocity and reflectivity collectively enhanced the performance of the WRF-3DVAR system over the Indian region. After identifying the optimal combination of DWR data, this study has also investigated the impact of assimilation of Indian DWR radial velocity and reflectivity data on simulation of the four different summer MDs that occurred over BoB. For this study, three numerical experiments (control no assimilation, with GTS and GTS along with DWR) are carried out to evaluate the impact of DWR data on simulation of MDs. The results of the study indicate that the assimilation of DWR data has a positive impact on the prediction of the location, propagation and development of rain bands associated with the MDs. The simulated meteorological parameters and tracks of the MDs are reasonably improved after assimilation of DWR observations as compared to the other experiments. The root mean square errors (RMSE) of wind fields at different pressure levels, equitable skill score and frequency bias are significantly improved in the assimilation experiments mainly in DWR assimilation experiment for all MD cases. The mean Vector Displacement Errors (VDEs) are significantly decreased due to the assimilation of DWR observations as compared to the CNTL and 3DV_GTS experiments. The study clearly suggests that the performance of the model simulation for the intense convective system which influences the large scale monsoonal flow is significantly improved after assimilation of the Indian DWR data from even one coastal locale within the MDs track.     

Observed and Forecasted Intraseasonal Activity of Southwest Monsoon Rainfall over India During 2010, 2011 and 2012

The monsoon seasons of 2010 and 2011, with almost identical seasonal total rainfall over India from June to September, are associated with slightly different patterns of intraseasonal rainfall fluctuations. Similarly, the year 2012, with relatively less rainfall compared to 2010 and 2011, also witnessed different intraseasonal rainfall fluctuations, leading to drought-like situations over some parts of the country. The present article discusses the forecasting aspect of monsoon activity over India during these 3 years on an extended range time scale (up to 3 weeks) by using the multimodel ensemble (MME), based on operational coupled model outputs from the ECMWF monthly forecasting system and the NCEP’s Climate Forecast System (CFS). The average correlation coefficient (CC) of weekly observed all-India rainfall (AIR) and the corresponding MME forecast AIR is found to be significant, above the 98 % level up to 2 weeks (up to 18 days) with a slight positive CC for the week 3 (days 19–25) forecast. However, like the variation of observed intraseasonal rainfall fluctuations during 2010, 2011 and 2012 monsoon seasons, the MME forecast skills of weekly AIR are also found to be different from one another, with the 2012 monsoon season indicating significant CC (above 99 % level) up to week 2 (12–18 days), and also a comparatively higher CC (0.45) during the week 3 forecast (days 19–25). The average CC between observed and forecasted weekly AIR rainfall over four homogeneous regions of India is found to be the lowest over the southern peninsula of India (SPI), and northeast India (NEI) is found to be significant only for the week 1 (days 5–11) forecast. However, the CC is found to be significant over northwest India (NWI) and central India (CEI), at least above the 90 % level up to 18 days, with NWI having slightly better skill compared to the CEI. For the individual monsoon seasons of 2010, 2011 and 2012, there is some variation in CC and other skill scores over the four homogeneous regions. Thus the slight variations in the characteristics of intraseasonal monsoon rainfall over India is associated with variations in predictive skill of the coupled models and the MME-based predictions of intraseasonal monsoon fluctuations for 2–3 weeks, providing encouraging results. The MME forecast in 2010 is also able to provide useful guidance, well in advance, about an active September associated with a delayed withdrawal of the monsoon and also the heavy rainfall over north Pakistan.     

A Study on the Impact of Observation Assimilation on the Numerical Simulation of Tropical Cyclones JAL and THANE Using 3DVAR

In this work, the impact of assimilation of conventional and satellite remote sensing observations (Oceansat-2 winds, MODIS temperature/humidity profiles) is studied on the simulation of two tropical cyclones in the Bay of Bengal region of the Indian Ocean using a three-dimensional variational data assimilation (3DVAR) technique. The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) mesoscale model is used to simulate the severe cyclone JAL: 5–8 November 2010 and the very severe cyclone THANE: 27–30 December 2011 with a double nested domain configuration and with a horizontal resolution of 27 × 9 km. Five numerical experiments are conducted for each cyclone. In the control run (CTL) the National Centers for Environmental Prediction global forecast system analysis and forecasts available at 50 km resolution were used for the initial and boundary conditions. In the second (VARAWS), third (VARSCAT), fourth (VARMODIS) and fifth (VARALL) experiments, the conventional surface observations, Oceansat-2 ocean surface wind vectors, temperature and humidity profiles of MODIS, and all observations were respectively used for assimilation. Results indicate meager impact with surface observations, and relatively higher impact with scatterometer wind data in the case of the JAL cyclone, and with MODIS temperature and humidity profiles in the case of THANE for the simulation of intensity and track parameters. These relative impacts are related to the area coverage of scatterometer winds and MODIS profiles in the respective storms, and are confirmed by the overall better results obtained with assimilation of all observations in both the cases. The improvements in track prediction are mainly contributed by the assimilation of scatterometer wind vector data, which reduced errors in the initial position and size of the cyclone vortices. The errors are reduced by 25, 21, 38 % in vector track position, and by 57, 36, 39 % in intensity, at 24, 48, 72 h predictions, respectively, for the two cases using assimilation of all observations. Simulated rainfall estimates indicate that while the assimilation of scatterometer wind data improves the location of the rainfall, the assimilation of MODIS profiles produces a realistic pattern and amount of rainfall, close to the observational estimates.     

Spatial and Temporal Variations in Indian Summer Monsoon Rainfall and Temperature: An Analysis Based on RegCM3 Simulations

Regional climate models are important tools to examine the spatial and temporal characteristics of rainfall and temperature at high resolutions. Such information has potential applications in sectors like agriculture and health. In this study, the Regional Climate Model Version 3 (RegCM3) has been integrated in the ensemble mode at 55 km resolution over India for the summer monsoon season during the years 1982–2009. Emphasis has been given on the validation of the model simulation at the regional level. In Central India, both rainfall and temperature show the best correlations with respective observed values. The model gives rise to large wet biases over Northwest and Peninsular India. RegCM3 slightly underestimates the summer monsoon precipitation over the Central and Northeast India. Nevertheless, over these regions, RegCM3 simulated rainfall is closer to the observations when compared to the other regions where rainfall is overestimated. The position of the monsoon trough simulated by the model lies to the north of its original observed position. This is similar to the usual monsoon break conditions leading to less rainfall over Central India. RegCM3 simulated surface maximum temperature shows a large negative bias over the country while the surface minimum temperature is close to the observation. Nevertheless, there is a strong correlation between the all India weighted average surface temperature simulated by RegCM3 and IMD observed values. While examining the extreme weather conditions in Central India, it is found that RegCM3 simulated frequencies of occurrence of very wet days, extremely wet days, warm days and warm nights more often as compared to those in IMD observed values. However, these are systematic biases. The model biases in the frequencies of distribution of rainfall extremes explain the wet and dry biases in different regions in the country. Overall, the inter-annual characteristics of both the rainfall and temperature extremes simulated by RegCM3 in Central India are well in phase with those found in the observed data.     

Projection of future rainfall for the North China Plain using two statistical downscaling models and its hydrological implications

This study projected the future rainfall (2046–2065 and 2081–2100) for the North China Plain (NCP) using two stochastic statistical downscaling models, the non-homogeneous hidden Markov model and the generalized linear model for daily climate time series, conditioned by the large-scale atmospheric predictors from six general circulation models for three emission scenarios (A1B, A2 and B1). The results indicated that the annual total rainfall, the extreme daily rainfall and the maximum length of consecutive wet/dry days would decline, while the number of annual rainfall days would slightly increase (correspondingly rainfall intensity would decrease) in the NCP, in comparison with the base period (1961–2010). Moreover, the summer monsoon rainfall, which accounted for 50–75 % of the total annual rainfalls in NCP, was projected to decrease in the latter half of twenty-first century. The spatial patterns of change showed generally north–south gradients with relatively larger magnitude decrease in the northern NCP and less decrease (or even slightly increase) in the southern NCP. This could result in decline of the annual runoff by ?5.5 % (A1B), ?3.3 % (A2) and ?4.1 % (B1) for 2046–2065 and ?5.3 % (A1B), ?4.6 % (A2) and ?1.9 % (B1) decrease for 2081–2100. These rainfall changes, combined with the warming temperature, could lead to drier catchment soil profiles and further reduce runoff potential, would hence provide valuable references for the water availability and related climate change adaption in the NCP.     

亚洲夏季风水汽输送的年际年代际变化与中国旱涝的关系

利用1958～2002年的NCEP-R1和ERA-40逐日再分析资料以及中国160站点月平均降水资料探讨了亚洲夏季风水汽输送的年际年代际变化及其与中国降水异常的关系. 分析结果表明,亚洲夏季风水汽输送和中国夏季降水的异常主模态呈现显著的准两年变化周期. 当南亚夏季风纬向水汽输送偏强（弱）时,东亚—西北太平洋地区水汽输送的偶极型异常有利于长江中下游地区和江淮流域的水汽辐合负（正）异常与华南和华北地区的水汽辐合正（负）异常,从而引起中国东部的经向三极子雨型,即长江中下游地区和江淮流域的偏旱（涝）与华南和华北地区的偏涝（旱）. 1970s年代末之后,亚洲夏季风水汽输送的年代际减弱与西北太平洋地区水汽输送的偶极型异常相配合,导致长江中下游地区的持续偏涝与华南和华北地区的持续偏旱. 从中国夏季降水异常与水汽通量辐合异常的同相对应关系来看,ERA-40资料对亚洲夏季风水汽输送年际年代际变化的描述能力强于NCEP-R1资料.     

A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor

A relationship between summer monsoon rainfall and sea surface temperature anomalies was investigated with the aim of predicting the monthly scale rainfall during the summer monsoon period over a section (80°–90°E, 14°–24°N) of eastern India that depends heavily upon the rainfall during the summer monsoon months for its agricultural practices. The association between area-averaged rainfall of June over the study zone and global sea surface temperature (SST) anomalies for the period 1982–2008 was examined and the variability of rainfall in monthly scale was calculated. With a view to significant variability in the rainfall in the monthly scale, it was decided to implement the artificial neural network (ANN) for forecasting the monthly scale rainfall using the SST anomalies as a predictor. Finally, the potential of ANN in this prediction has been assessed.     

Predictability of Indian Monsoon Circulation with High Resolution ECMWF Model in the Perspective of Tropical Forecast During the Tropical Convection Year 2008

To address some of the issues of project Year of Tropical Convection (YOTC) and the project ATHENA as ongoing international activities, an endeavor has been made for the first time to study the predictability of Indian summer monsoon in the backdrop of tropical predictability using 850 hPa atmospheric circulations with the high resolution (T1279) ECMWF model during the boreal summer of 2008 as one of the focus years of YOTC. The major findings obtained from the statistical forecast have been substantiated by the dynamical prediction in terms of the systematic error energy, its growth rate and the attribution of the dominant nonlinear dynamical processes to error growth. The systematic error energy of T1279 (16 km resolution) ECMWF model are generated in African landmass, India and its adjoining oceanic region, in near equatorial west Pacific and around the Madagascar region where the root mean square errors are observed and the zonal wind anomaly shows poor forecast skill. As far as the inadequate predictability of Indian summer monsoon by T1279 ECMWF model (revealed from the results of project ATHENA) is concerned, the systematic error energy and the error growth over Arabian Sea, in the eastern and western India due to the nonlinear convergence and divergence of error flux along with the erroneous Mascarene high may possibly be the determining factors for not showing any discernable improvement in Indian monsoon during the medium range forecast up to 240 h. This work suggests that the higher resolution of ECMWF model may not necessarily lead to the better forecast of Indian monsoon circulations during 2008 unless a methodology can be devised to isolate the errors due to the nonlinear processes that are inherent within the system.     

Suitability of North American Regional Reanalysis (NARR) output for hydrologic modelling and analysis in mountainous terrain

Meteorological observations at high elevations in mountainous regions are often lacking. One opportunity to fill this data gap is through the use of downscaled output from weather reanalysis models. In this study, we tested the accuracy of downscaled output from the North American Regional Reanalysis (NARR) against high‐elevation surface observations at four ridgetop locations in the southern Coast Mountains of British Columbia, Canada. NARR model output was downscaled to the surface observation locations through three‐dimensional interpolation for air temperature, vapour pressure and wind speed and two‐dimensional interpolation for radiation variables. Accuracy was tested at both the 3‐hourly and daily time scales. Air temperature displayed a high level of agreement, especially at the daily scale, with root mean square error (RMSE) values ranging from 0.98 to 1.21 °C across all sites. Vapour pressure downscaling accuracy was also quite high (RMSE of 0.06 to 0.11 hPa) but displayed some site specific bias. Although NARR overestimated wind speed, there were moderate to strong linear relations (r² from 0.38 to 0.84 for daily means), suggesting that the NARR output could be used as an index and bias‐corrected. NARR output reproduced the seasonal cycle for incoming short‐wave radiation, with Nash–Sutcliffe model efficiencies ranging from 0.78 to 0.87, but accuracy suffered on days with cloud cover, resulting in a positive bias and RMSE ranged from 42 to 46 Wm^{? 2}. Although fewer data were available, incoming long‐wave radiation from NARR had an RMSE of 19 Wm^{? 2} and outperformed common methods for estimating incoming long‐wave radiation. NARR air temperature showed potential to assist in hydrologic analysis and modelling during an atmospheric river storm event, which are characterized by warm and wet air masses with atypical vertical temperature gradients. The incorporation of a synthetic NARR air temperature station to better represent the higher freezing levels resulted in increased predicted peak flows, which better match the observed run‐off during the event. Copyright © 2016 John Wiley & Sons, Ltd.     

‘Thermohaline front’ off the east coast of India and its generating mechanism

Physical oceanography measurements reveal a strong salinity (0.18 psu km^?1) and temperature (0.07 °C km^?1) front off the east coast of India in December 1997. T–S diagrams suggest lateral mixing between the fresh water at the coast and the ambient warmer, saltier water. This front seems to be the result of southward advection of fresh and cool water, formed in the northern Bay of Bengal during the monsoon, by the East Indian Coastal Current, as suggested by the large-scale salinity structure in the SODA re-analysis and the anti-cyclonic gyre in the northwestern Bay of Bengal during winter. The data further reveals an offshore front in January, which appears to be the result of a meso-scale re-circulation around an eddy, bringing cold and freshwater from the northern Bay of Bengal further away from the shore. Our cruise data hence illustrates that very strong salinity fronts can appear in the Bay of Bengal after the monsoon, as a result of intense coastal circulation and stirring by eddies.     

Indian summer monsoon and El Nino

The associations between strong to moderate El Nino events and the all-India and subdivisional summer monsoon rainfall is examined for the period 1871 to 1978. The significance of the association is assessed by applying the Chi-square test to the contingency table. The analysis indicates that during 22 El Nino years the Indian monsoon rainfall was mostly below normal over most parts of the country. However, the association between El Nino and deficient rainfall or drought is statistically significant over the subdivisions west of longitude 80°E and north of 12°N. During the five strong El Nino years—1877, 1899, 1911, 1918, and 1972—many areas of India suffered large rainfall deficiencies and severe droughts. There are four moderate El Nino years—1887, 1914, 1953, and 1976—when the suffering was marginal. The relationship between El Nino and the Indian monsoon rainfall is expected to be useful in forecasting large-scale anomalies in the monsoon over India.     

Some aspects of the monsoon circulation and monsoon rainfall

Summary The south Asian summer monsoon from June to September accounts for the greater part of the annual rainfall over most of India and southeast Asia. The evolution of the summer and winter monsoon circulations over India is examined on the basis of the surface and upper air data of stations across India. The salient features of the seasonal reversals of temperature and pressure gradients and winds and the seasonal and synoptic fluctuations of atmospheric humidity are discussed. The space-time variations of rainfall are considered with the help of climatic pentad rainfall charts and diagrams. The rainfall of several north and central Indian stations shows a minimum around mid-August and a maximum around mid-February which seem to be connected with the extreme summer and winter positions of the ITCZ and the associated north-south shifts in the seasonal circulation patterns. Attention is drawn to the characteristic features of the monsoon rainfall that emerge from a study of daily and hourly rainfall of selected stations. Diurnal variations of temperature, pressure, wind and rainfall over the monsoon belt are briefly treated.