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Northeasterly cold surges strongly influence the rainfall patterns over the Malay Peninsula during the northeast monsoon season. This study looks at the changes in the cold surges and Madden–Julian oscillation (MJO) characteristics through the northeast monsoon season and their interaction. Nearly 75% of the cold surge events tend to cross the equator around the Java Sea area (100°–110°E) in February–March with drier conditions prevailing over the Malay Peninsula and increased rainfall over Java. Both the cold surges and the MJO undergo seasonal variations with well-defined regional features. Wavelet analysis shows that MJO amplitude and high-frequency rainfall variations over Southeast Asia peak in November–December. MJO amplitude is suppressed during February and March. This is linked to the high-frequency surges of meridional winds that are prominent during the early part of the season, but February–March is dominated by low-frequency (~20–90 days) cross-equatorial monsoon flow. These prolonged periods of strong meridional flow at the equator interact with the MJO both dynamically and thermodynamically and act as a barrier for convection from propagating from the Indian Ocean to the Maritime Continent (MC). These interactions may have implications for weather and seasonal forecasting over the region. An evaluation of the properties of cold surges and their interaction with the seasonal cycle in the Met Office Unified Model is performed. The atmosphere–ocean coupled model performs better in representing the pattern of influence of the cold surges despite the biases in intensity and spatial distribution of rainfall extremes. These diagnostics are presented with the aim of developing a set of model evaluation metrics for global and regional models.

A wind profiler radar at 205 MHz is operational since January 2017, at Cochin ($$10.04^\circ \hbox {N}$$; $$76.33^\circ \hbox {E}$$), a region lying in the west coast of Southern Peninsular India, which also is the entry point of the Indian summer monsoon. Using the radar wind profiles obtained during April to September, the detailed vertical structure of wind during the pre-monsoon and monsoon period was studied for the years 2017 and 2018. The gradual transition from pre-monsoon to monsoon season as manifested by the development of monsoon circulations in the lower and upper troposphere is well captured by the radar observations. Parameters which characterize the strength of monsoon circulations have been derived which are shown to be potential predictors for declaring the monsoon onset over Kerala in an objective manner. The monsoon circulation during the year 2018 was studied in detail in the backdrop of extreme heavy rainfall over Kerala. It is observed that there is an anomalous decrease in the core height, but with high core speed in the Low-level Jet stream (LLJ) during 2018 as compared to year 2017. Owing to this unique placement of LLJ, it can be concluded that intense orographic lifting could have played a role in causing heavy rainfall over Kerala in 2018. The transitions in LLJ prior to heavy rainfall over south-west coast are aptly captured by the radar observations which opens up the possibility of predicting heavy rainfall events through continuous monitoring of monsoon circulation using radar.

The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Amongst other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific description of these components are in companion papers), and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictabiity on shorter timescales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extra-tropical variability and top-of-atmosphere & surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

In depth examination of the extreme precipitation over Kerala during 15–17th August 2018 – triggering major flood episode in the peninsular Indian state - have been made via the National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model. A rare alignment of an intense low pressure area (LPA) over head Bay of Bengal (BoB) and a couple of typhoons over South China Sea and West Pacific, driven by anomalous sea surface conditions along the south-east Asian coastal belts, kept the low level jet meander from central Arabian Sea to West North Pacific (WNP) and remain relentless throughout the episode. Positive velocity potentials (VP, at 850 hPa) were seen prevailing for the region and some of these VP fringes unevenly crossed over to Kerala - suggestive of an uneven wind convergence – and associated rainfall necessarily not dictated by orography alone. A single system of negative stream functions (SF) suggested the prevalence of a conveyor belt like flow – termed, the ‘Remotely Aligned Intense Tropical Circulations’ (RAITC) – helping bring ‘an additional supply of moisture’ from WNP to Kerala; the cyclones over the WNP provided large amounts of moisture to the upper air and while some of these cyclones were weakening, a part of this moisture got injected to the south-westward flow and was then propelled further by the BoB LPA. While the NCUM global forecasts could capture the general circulation pattern for the intense precipitation over Kerala in the medium range, the spatial distribution of the heavy spells couldn’t be captured well in day-7 forecast; the strength and movement of the BoB LPA as well as the alignment and intensity modulation of the multiple tropical circulations showed some deviations. The convection permitting regional version of the model, NCUM-R (4 km grid length), exhibited lesser frequency for the light rainfall events, while over-predicting the frequency for the extreme precipitations.

The article of record as published may be found at http://dx.doi.org/10.1175/JCLI-D-16-0546.1 TRMM rainfall data from 1998–2012 are used to study the impacts and interactions of cold surges (CSs) and the Madden–Julian oscillation (MJO) on rainfall over Southeast Asia during the boreal winter season from November to February. CSs are identified using a new large-scale index. The frequencies of occurrences of these two large-scale events are comparable (about 20% of the days each), but the spatial pattern of impacts show differences resulting from the interactions of the general flow with the complex orography of the region. The largest impact of CSs occurs in and around the southern South China Sea as a result of increased low-level convergence on the windward side of the terrain and increased shear vorticity off Borneo that enhances the Borneo vortex. The largest impact of the MJO is in the eastern equatorial Indian Ocean, sheltered from CSs by Sumatra. In general CSs are significantly more likely to trigger extreme rainfall. When both systems are present, the rainfall pattern is mainly controlled by the CSs. However, the MJO makes the environment more favorable for convection by moistening the atmosphere and facilitating conditional instability, resulting in a significant increased rainfall response compared to CSs alone. In addition to the interactions of the two systems in convection, this study confirms a previously identified mechanism in which theMJOmay reduce CS frequency through opposing dynamic structures. Centre for Climate Research Singapore, Meteorological Service Singapore (MSS) World Meteorological Organization and the World Weather Research Programme GA01101

The “Vertical Structure of Diabatic Processes of the Madden-Julian Oscillation” global-model evaluation project developed a novel experimental framework, which produces a complete characterization of models’ abilities to simulate the Madden-Julian oscillation (MJO). The three components of the project comprise 2-day and 20-day hindcasts and 20-year simulations; each obtained heating, moistening and momentum tendencies from the models’ sub-grid parameterizations. Thirty-five centers provided output for at least one component; nine centers provided data for all three. The models vary greatly in MJO fidelity in climate and hindcast experiments, yet fidelity in one was not correlated with fidelity in the other. In 20-year simulations, strong MJO models demonstrated heating, vertical-velocity and zonal-wind profiles that tilted westward with height, as in reanalysis data. The 20-day hindcasts showed no correspondence between the shape of the heating profile and hindcast skill. Low-to-mid-level moistening at moderate rain rates was a consistent feature of high-skill models and absent from low-skill models, suggesting a role for boundary-layer and congestus clouds in the MJO transition, which was confirmed by timestep data from the 2-day hindcasts. These hindcasts revealed a poor simulation of the MJO transition phase, even at short leads, with large mid-tropospheric dry biases and discrepancies in radiative-heating profiles.

The aim of this work is to determine to what extent precipitation modulated by the Madden–Julian Oscillation (MJO) over East Africa can be forecast by the operational global Met Office Unified Model (MetUM). Observed patterns of rainfall were analysed over Kenya, Tanzania and Uganda and used to validate MetUM forecasts made over the period 2005–2012. It was found that there is a large seasonal dependence on the MJO for episodes of enhancement and suppression of rainfall over the inland highlands and the coastal lowlands, particularly from March to May and October to December, when the Intertropical Convergence Zone is located directly over the region. In phases 2–4 of the MJO lifecycle, there is an enhancement of precipitation over the highland regions and suppression over the coast. This dipole is reversed throughout phases 6–8. These findings corroborate previous studies undertaken over the region. The observed patterns were replicated well by the MetUM global model, even up to a forecast lead time of 5 days (T + 120 h), though some minor drift is apparent and convective and suppressed centres tend to stray from those of the observed rainfall. Model resolution is thought to be a key component of this difference. The systematic errors will likely improve with further plans for model resolution and physics upgrades, although the overall quality of the MetUM's ability to forecast the MJO over this region is sound.

This study investigates the impact of a full interactive ocean on daily initialized 15 day hindcasts of the Madden-Julian Oscillation (MJO), measured against a Met Office Unified Model atmosphere control simulation (atmospheric general circulation model (AGCM)) during a 3 month period of the Year of Tropical Convection. Results indicate that the coupled configuration (coupled general circulation model (CGCM)) extends MJO predictability over that of the AGCM, by up to 3–5 days. Propagation is improved in the CGCM, which we partly attribute to a more realistic phase relationship between sea surface temperature (SST) and convection. In addition, the CGCM demonstrates skill in representing downwelling oceanic Kelvin and Rossby waves which warm SSTs along their trajectory, with the potential to feedback on the atmosphere. These results imply that an ocean model capable of simulating internal ocean waves may be required to capture the full effect of air-sea coupling for the MJO.

Process-oriented diagnostics for Madden–Julian oscillation (MJO) simulations are being developed to facilitate improvements in the representation of the MJO in weather and climate models. These process-oriented diagnostics are intended to provide insights into how parameterizations of physical processes in climate models should be improved for a better MJO simulation. This paper proposes one such process-oriented diagnostic, which is designed to represent sensitivity of simulated convection to environmental moisture: composites of a relative humidity (RH) profile based on precipitation percentiles. The ability of the RH composite diagnostic to represent the diversity of MJO simulation skill is demonstrated using a group of climate model simulations participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). A set of scalar process metrics that captures the key physical attributes of the RH diagnostic is derived and their statistical relationship with indices that quantify the fidelity of the MJO simulation is tested. It is found that a process metric that represents the amount of lower-tropospheric humidity increase required for a transition from weak to strong rain regimes has a robust statistical relationship with MJO simulation skill. The results herein suggest that moisture sensitivity of convection is closely related to a GCM’s ability to simulate the MJO.

The influence of Madden-Julian Oscillation (MJO) on the rainfall distribution of Southeast Asia is studied using TRMM satellite-derived rainfall and rain gauge data. It is shown that convectively active (suppressed) phases of MJO can increase (decrease) the probability of extreme rain events over the land regions by about 30–50% (20–25%) during November–March season. The influence of MJO on localized rainfall extremes are also observed both in rainfall intensity and duration. The Met Office Global Seasonal forecasting system seasonal forecasting system is shown to reproduce the MJO influence on rainfall distribution well despite the model biases over land. Skills scores for forecasting 90th percentile extreme rainfall shows significant skills for convective phases. This study demonstrates the feasibility of deriving probabilistic forecasts of extreme rainfall at medium range.

This article describes the UK Met Office Global Seasonal forecast system version 5 (GloSea5). GloSea5 upgrades include an increase in horizontal resolution in the atmosphere (N216–0.7°) and the ocean (0.25°), and implementation of a 3D-Var assimilation system for ocean and sea-ice conditions. GloSea5 shows improved year-to-year predictions of the major modes of variability. In the Tropics, predictions of the El Nino–Southern Oscillation are improved with reduced errors in the West Pacific. In the Extratropics, GloSea5 shows unprecedented levels of forecast skill and reliability for both the North Atlantic Oscillation and the Arctic Oscillation. We also find useful levels of skill for the western North Pacific Subtropical High which largely determines summer precipitation over East Asia.

International audience; Numerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north–south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains.

Seasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Niño–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Niño-3.4 SST forecasts starting in November. Global ENSO teleconnections and Madden–Julian oscillation anomalies are well represented in GloSea4. Remote forcings of the North Atlantic Oscillation by ENSO and the quasi-biennial oscillation are captured albeit the anomalies are weaker than those found in observations. Hindcast length issues and their implications for seasonal forecasting are also discussed.

The intraseasonal variability (ISV) of the Asian summer monsoon represented in seven coupled general circulation models (CGCMs) as part of the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) project is analyzed and evaluated against observations. The focus is on the spatial and seasonal variations of ISV of outgoing longwave radiation (OLR). The large-scale organization of convection, the propagation characteristics, and the air–sea coupling related to the monsoon ISV are also evaluated. A multivariate local mode analysis (LMA) reveals that most models produce less organized convection and ISV events of shorter duration than observed. Compared to the real atmosphere, these simulated patterns of perturbations are poorly reproducible from one event to the other. Most models simulate too weak sea surface temperature (SST) perturbations and systematic phase quadrature between OLR, surface winds, and SST—indicative of a slab-ocean-like response of the SST to surface flux perturbations. The relatively coarse vertical resolution of the different ocean GCMs (OGCMs) limits their ability to represent intraseasonal processes, such as diurnal warm layer formation, which are important for realistic simulation of the SST perturbations at intraseasonal time scales. Models with the same atmospheric GCM (AGCM) and different OGCMs tend to have similar biases of the simulated ISV, indicating the dominant role of atmospheric models in fixing the nature of the intraseasonal variability. It is, therefore, implied that improvements in the representation of ISV in coupled models have to fundamentally arise from fixing problems in the large-scale organization of convection in AGCMs.

A physically based empirical real-time forecasting strategy to predict the subseasonal variations of the Indian summer monsoon up to four–five pentads (20–25 days) in advance has been developed. The method is based on the event-to-event similarity in the properties of monsoon intraseasonal oscillations (ISOs). This two-tier analog method is applied to NOAA outgoing longwave radiation (OLR) pentad averaged data that have sufficiently long records of observation and are available in nearly real time. High-frequency modes in the data are eliminated by reconstructing the data using the first 10 empirical orthogonal functions (EOFs), which together explain about 75% of the total variance. In the first level of the method, the spatial analogs of initial condition pattern are identified from the modeling data. The principal components (PCs) of these spatial analogs, whose evolution history of the latest five pentads matches that of the initial condition pattern, are considered the temporal PC analogs. Predictions are generated for each PC as the average evolution of PC analogs for the given lead time. Predicted OLR values are constructed using the EOFs and predicted PCs. OLR data for 1979–99 are used as the modeling data and independent hindcasts are generated for the period 2000–05. The skill of anomaly predictions is rather high over the central and northern Indian region for lead times of four–five pentads. The phases and amplitude of intraseasonal convective spells are predicted well, especially the long midseason break of 2002 that resulted in large-scale drought conditions. Skillful predictions can be made up to five pentads when started from an active initial state, whereas the limit of useful predictions is about two–three pentads when started from break initial conditions. An important feature of this method is that unlike some other empirical methods to forecast monsoon ISOs, it uses minimal time filtering to avoid any possible endpoint effects and hence may be readily used for real-time applications. Moreover, as the modeling data grow with time as a result of the increased number of observations, the number of analogs would also increase and eventually the quality of forecasts would improve.

The concept of an interannually varying Indian summer monsoon season is introduced here, considering that the duration of the primary driving of the Indian monsoon – the large-scale meridional gradient of the deep tropospheric heat source – may vary from one year to another. Onset (withdrawal) is defined as the day when the tropospheric heat source shifts from south to north (north to south). This physical principle leads to a new thermodynamic index of the seasonal mean monsoon. While the traditional measure of seasonal rainfall, averaged from 1 June to 30 September, indicates a breakdown of the ENSO–monsoon relationship in recent decades, it is argued that this breakdown is partly due to the inappropriate definition of a fixed monsoon season. With a new physically based definition of the seasonal mean, the ENSO–monsoon relationship has remained steady over the decades. El Nino (La Nina) events contract (expand) the season, and thus decrease (increase) the seasonal mean monsoon by setting up persistent negative (positive) tropospheric temperature (TT) anomalies over the southern Eurasian region. Thus, we propose a new pathway, whereby the Indian summer monsoon could be influenced by remote climatic phenomena via modification of TT over Eurasia. Diagnostics of the onset and withdrawal processes suggest that onset delay is due to the enhanced adiabatic zubsidence that inhibits vertical mixing of sensible heating from warm landmass during the pre-monsoon months. On the other hand, the major factor that determines whether the withdrawal is early or late is the horizontal advective cooling. Most of the late (early) onsets and early (late) withdrawals are associated with El Nino (La Nina). This link between the ENSO and the monsoon is realized through vertical and horizontal advections associated with the stationary waves in the upper troposphere set up by the tropical ENSO heating.

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high- and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO. © 2015 American Geophysical Union. All Rights Reserved.

The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.

An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the “Vertical structure and physical processes of the Madden‐Julian Oscillation (MJO)” project. A lead time of 12–36 h is chosen to constrain the large‐scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin‐up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large‐scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems., Key Points Uncertainties in modeling convection in GCMs are highlightedRadiation and clouds is a key driver of some of the model uncertaintiesConvection dynamics link is key to time step intermittency of convection

Using a new data set we demonstrate the variability of upper troposphere humidity (UTH) associated with the Indian Summer Monsoon (ISM). The main advantage of the new data set is its all-sky repres ...

International audience; The intraseasonal variability (ISV) is an intermittent phenomenon with variable perturbation patterns. To assess the robustness of the simulated ISV in climate models, it is thus interesting to consider the distribution of perturbation patterns rather than only one average pattern. To inspect this distribution, the authors first introduce a distance that measures the similarity between two patterns. The reproducibility (realism) of the simulated intraseasonal patterns is then defined as the distribution of distances between each pattern and the average simulated (observed) pattern. A good reproducibility is required to analyze the physical source of the simulated disturbances. The realism distribution is required to estimate the proportion of simulated events that have a perturbation pattern similar to observed patterns. The median value of this realism distribution is introduced as an ISV metric. The reproducibility and realism distributions are used to evaluate boreal summer ISV of precipitations over the Indian Ocean for 19 phase 3 of the Coupled Model Intercomparison Project (CMIP3) models. The 19 models are classified in increasing ISV metric order. In agreement with previous studies, the four best ISV metrics are obtained for models having a convective closure totally or partly based on the moisture convergence. Models with high metric values (poorly realistic) tend to give (i) poorly reproducible intraseasonal patterns, (ii) rainfall perturbations poorly organized at large scales, (iii) small day-to-day variability with overly red temporal spectra, and (iv) less accurate summer monsoon rainfall distribution. This confirms that the ISV is an important link in the seamless system that connects weather and climate. © 2010 American Meteorological Society.

Against a backdrop of rising global surface temperature, the stability of the Indian monsoon rainfall over the past century has been a puzzle. By using a daily rainfall data set, we show (i) significant rising trends in the frequency and the magnitude of extreme rain events and (ii) a significant decreasing trend in the frequency of moderate events over central India during the monsoon seasons from 1951 to 2000. The seasonal mean rainfall does not show a significant trend, because the contribution from increasing heavy events is offset by decreasing moderate events. A substantial increase in hazards related to heavy rain is expected over central India in the future.

[1] Being an integral effect of sub-seasonal rain spells over the season, the seasonal mean south Asian monsoon (SAM) rainfall could be affected by change in the length of the rainy season (LRS). An objective definition of the duration of the SAM season has, however, been lacking. Here we show that the meridional gradient of tropospheric temperature (ΔTT) over the SAM region controls the LRS and defines the SAM season. It is further shown that ENSO induces decreased SAM rainfall by regulating the LRS. The atmospheric response to tropical sea surface temperature (SST) over the tropical Pacific during an evolving El Nino reduces ΔTT over the SAM region and shortens LRS by delaying the onset and advancing the withdrawal. The strong negative correlation between LRS and ENSO related SST has remained steady and provides basis for improved prediction of seasonal mean SAM rainfall variability.

Extended range prediction (two to three weeks in advance) of Indian summer monsoon active (rainy) and break (dry) phases are of great importance for agricultural planning and water management. Using daily rainfall and circulation data for 23 years, a fundamental property of the monsoon intraseasonal oscillations (ISO's) is discovered and shown that the potential predictability limit (~20 days) of monsoon breaks is significantly higher than that for active conditions (~10 days). An empirical model for prediction of monsoon ISO's is then constructed and feasibility of useful prediction of monsoon breaks up to 18 days in advance is demonstrated.

[1] Active and break phases of the Indian summer monsoon are characterized by enhancement and decrease of precipitation over the monsoon trough region. Using genesis data of monsoon low pressure systems (LPS) and circulation data for the period 1954 to 1993, it is shown that the frequency of occurrence of LPS is nearly 3.5 times higher in the active phase of monsoon as compared to the break phase. In addition, the tracks of these synoptic systems are also strongly spatially clustered along the monsoon trough during the active phase of the monsoon. The enhanced (decreased) frequency of occurrence of LPS during active (break) phases is due to modulation of meridional shear of zonal winds and cyclonic vorticity along the monsoon trough by the intraseasonal oscillations (ISO).

International audience; Preindustrial control simulations with the third Hadley Centre Global Environmental Model,run in the Global Coupled configuration 3.1 of the Met Office Unified Model (HadGEM3-GC3.1) are presented at two resolutions. These are N216ORCA025, which has a horizontal resolution of 60 km in the atmosphere and 0.25° in the ocean, and N96ORCA1, which has a horizontal resolution of 130 km in the atmosphere and 1∘in the ocean. The aim of this study is to document the climate variability in these simulations, make comparisons against present-day observations (albeit under different forcing), and discuss differences arising due to resolution. In terms of interannual variability in the leading modes of climate variability the two resolutions behave generally very similarly. Notable differences are in the westward extent of El Niñ oand the pattern of Atlantic multidecadal variability, in which N216ORCA025 compares more favorably to observations, and in the Antarctic Circumpolar Current, which is far too weak in N216ORCA025. In the North Atlantic region, N216ORCA025 has a stronger and deeper Atlantic Meridional Overturning Circulation, which compares well against observations, and reduced biases in temperature and salinity in the North Atlantic subpolar gyre. These simulations are being provided to the sixth Coupled Model Intercomparison Project(CMIP6) and provide a baseline against which further forced experiments may be assessed.