The relationship between Indian monsoon rainfall and low-pressure systems

Indian summer monsoon precipitation is significantly modulated by synoptic-scale tropical low pressure areas (LPAs), the strongest of which are known as monsoon depressions (MDs). Despite their apparent importance, previous studies attempting to constrain the fraction of monsoon precipitation for which such systems are responsible have yielded an unsatisfyingly wide range of estimates. Here, a variant of the DBSCAN algorithm is implemented to identify nontrivial, coherent rainfall structures in TRMM-3B42 precipitation data. Using theoretical considerations and an idealised model, an effective capture radius is computed to be 200 km, providing upper-bound attribution fractions of 57% (17%) for LPAs (MDs) over the monsoon core zone and 44% (12%) over all India. These results are also placed in the context of simpler attribution techniques. A climatology of these clusters suggests that the central Bay of Bengal (BoB) is the region of strongest synoptic organisation. A k-means clustering technique is used to identify four distinct partitions of LPA (and two of MD) track, and their regional contributions to monsoon precipitation are assessed. Most synoptic rainfall over India is attributable to short-lived LPAs originating at the head of the BoB, though longer-lived systems are required to bring rain to west India and east Pakistan. Secondary contributions from systems originating in the Arabian Sea and south BoB are shown to be important for west Pakistan and Sri Lanka respectively. Finally, a database of precipitating-event types is used to show that small-scale deep convection happens independently of MDs, whereas the density of larger-scale convective and stratiform events are sensitive to their presence - justifying the use of a noise-rejecting algorithm

Representation of western disturbances in CMIP5 models

Western disturbances (WDs) are synoptic extratropical disturbances embedded in the subtropical westerly jet stream. They are an integral part of the South Asian winter climate, both for the agriculture-supporting precipitation they bring to the region and for the associated isolated extreme events that can induce devastating flash flooding. Here, WD behaviour and impacts are characterised in 23 CMIP5 historical simulations and compared with reanalysis and observations. It is found that WD frequency has a strong relationship with model resolution: higher resolution models produce significantly more WDs, and a disproportionately high fraction of extreme events. Exploring metrics of jet strength and shape, we find that the most probable cause of this relationship is that the jet is wider in models with coarser resolution, and therefore the northern edge in which WDs are spun up sits too far north of India. The frequency of WDs in both winter and summer is found to be overestimated by most models, and thus the winter frequency of WDs estimated from the multi-model mean (30 winter−1) is above the reanalysis mean (26 winter−1). In this case, the error cannot be adequately explained by local jet position and strength. Instead, we show that it is linked with a positive bias in upstream mid-tropospheric baroclinicity. Despite a positive winter precipitation bias in CMIP5 models over most of India and Pakistan and a dry bias in the western Himalaya, the fraction of winter precipitation for which WDs are responsible is accurately represented. Using partial correlation, it is shown that the overestimation in WD frequency is the largest contributor to this bias, with a secondary, spatially heterogeneous contribution coming from the overestimation of WD intensity

Falling trend of western disturbances in future climate simulations

Western disturbances (WDs) are synoptic-scale cyclonic weather systems advected over Pakistan and north India by the subtropical westerly jet stream. There, they are responsible for most of the winter precipitation, crucial for agriculture of the rabi crop, as well as more extreme precipitation events, which can lead to local flooding and avalanches. Despite their importance, there has not yet been an attempt to objectively determine the fate of WDs in future climate GCMs. Here, a tracking algorithm is used to build up a catalogue of WDs in both CMIP5 historical and representative concentration pathway (RCP) experiments of the future. It is shown that in business-as-usual (RCP8.5) future climate simulations, WD frequency falls by around 15% by the end of the twenty-first century, with the largest relative changes coming in pre- and post-monsoon months. Meanwhile, mean WD intensity will decrease, with central vorticity expected to become less cyclonic by about 12% over the same period. Changes in WD frequency are attributed to the projected widening and weakening of the winter subtropical jet; as well as decreasing meridional wind shear and mid-tropospheric baroclinic vorticity tendency, which also explain the changes in intensity. Finally, the impact of these changes on regional precipitation is explored. The decline in WD frequency and intensity will cause a decrease in mean winter rainfall over Pakistan and north India amounting to about 15% of the mean -- subject to the ability of the models to represent the processes responsible. The effect on extreme precipitation events, however, remains unclear

The 2018 Kerala floods: a climate change perspective

In August 2018, the Indian state of Kerala received an extended period of very heavy rainfall as a result of a low-pressure system near the beginning of the month being followed several days later by a monsoon depression. The resulting floods killed over 400 people and displaced a million more. Here, a high resolution setup (4 km) of the Weather Research and Forecasting (WRF) model is used in conjunction with a hydrological model (WRF-Hydro, run at 125 m resolution) to explore the circumstances that caused the floods. In addition to a control experiment, two additional experiments are performed by perturbing the boundary conditions to simulate the event in pre-industrial and RCP8.5 background climates. Modelled rainfall closely matched observations over the study period, and it is found that this would this would have been about 18% heavier in the pre-industrial due to recent weakening of monsoon low-pressure systems, but would be 36% heavier in an RCP8.5 climate due to moistening of the tropical troposphere. Modelled river streamflow responds accordingly: it is shown the six major reservoirs that serve the state would have needed to have 34% more capacity to handle the heavy rainfall, and 43% had the deluge been amplified by an RCP8.5 climate. It is further shown that this future climate would have significantly extended the southern boundary of the flooding. Thus it is concluded that while climate change to date may well have mitigated the impacts of the flooding, future climate change would likely exacerbate them

The effect of soil moisture perturbations on Indian Monsoon Depressions in a numerical weather prediction model

Indian monsoon depressions (MDs) are synoptic-scale cyclonic systems that propagate across peninsular India three or four times per monsoon season. They are responsible for the majority of rainfall in agrarian north India, thus constraining precipitation estimates is of high importance. Here, we use a case study from August 2014 to explore the relationship between varying soil moisture and the resulting track and structure of an incident MD using the Met Office Unified Model. We use this case study with the view to increasing understanding of the general impact of soil moisture perturbations on monsoon depressions. It is found that increasing soil moisture in the monsoon trough region results in deeper inland penetration and a more developed structure - e.g. a warmer core in the mid-troposphere and a stronger bimodal potential vorticity core in the middle/lower troposphere - with more precipitation, and a structure that in general more closely resembles that found in depressions over the ocean, indicating that soil moisture may enhance the convective mechanism that drives depressions over land. This experiment also shows that these changes are most significant when the depression is deep, and negligible when it is weakening. Increasing soil moisture in the sub-Himalayan arable zone, a region with large irrigation coverage, also caused deeper inland penetration and some feature enhancement in the upper troposphere but no significant changes were found in the track heading or lower-tropospheric structure

The interaction of Indian monsoon depressions with northwesterly mid-level dry intrusions

Monsoon depressions (MDs) bring substantial monsoon rainfall to northern and central India. These events usually form over the Bay of Bengal and travel across northern India toward Pakistan. Using European Centre for Medium-Range Weather Forecasting Interim Reanalysis, an MD tracking algorithm, and an objective identification method, we find that about 40% of MDs interact with northerly intrusions of dry desert air masses as the MDs traverse the subcontinent. MD interactions with dry intrusions are often preceded by positive potential vorticity anomalies on the subtropical jet and low level anticyclonic anomalies over the north Arabian Sea. Dry intrusions nearly halve the precipitation rate in the southwest quadrant of MDs, where MDs rain the most. However, dry intrusions increase the rainfall rate near the MD center. Similarly, ascent is reduced west of the MD center and enhanced at the MD center, especially in the upper troposphere. The reduced ascent west of MD centers is likely attributable to changes in vertical shear reducing differential cyclonic vorticity advection. Dry intrusions slightly reduce MDs’ propagation speed. For the mid-upper level vortex, this can be explained by anomalous westerlies reducing propagation by adiabatic advection. For the lower tropospheric vortex, it is likely that reduced diabatic generation of PV plays a role in slowing propagation, along with reduced adiabatic advection

Comparison of the prediction of Indian monsoon low pressure systems by subseasonal-to-seasonal prediction models

This study analyzes the prediction of Indian monsoon low pressure systems (LPSs) on an extended time scale of 15 days by models of the Subseasonal-to-Seasonal (S2S) prediction project. Using a feature-tracking algorithm, LPSs are identified in 11 S2S models during a common reforecast period of June–September 1999–2010, and then compared with 290 and 281 LPSs tracked in ERA-Interim and MERRA-2 reanalysis datasets. The results show that all S2S models underestimate the frequency of LPSs. They are able to represent transits, genesis, and lysis of LPSs; however, large biases are observed in the Australian Bureau of Meteorology, China Meteorological Administration (CMA), and Hydrometeorological Centre of Russia (HMCR) models. The CMA model exhibits large LPS track position error and the intensity of LPSs is overestimated (underestimated) by most models when verified against ERA-Interim (MERRA-2). The European Centre for Medium-Range Weather Forecasts and Met Office models have the best ensemble spread–error relationship for the track position and intensity, whereas the HMCR model has the worst. Most S2S models are underdispersive—more so for the intensity than the position. We find the influence of errors in the LPS simulation on the pattern of total precipitation biases in all S2S models. In most models, precipitation biases increase with forecast lead time over most of the monsoon core zone. These results demonstrate the potential for S2S models at simulating LPSs, thereby giving the possibility of improved disaster preparedness and water resources planning

Extreme daily rainfall in Pakistan and north India: scale-interactions, mechanisms, and precursors

While much of India is used to heavy precipitation and frequent low-pressure systems during the summer monsoon, towards the northwest and into Pakistan, such events are uncommon. Here, as much as a third of the annual rainfall is delivered sporadically during the winter monsoon by western disturbances. Such events of sparse but heavy precipitation in this region of typically mountainous valleys in the north and desert in the south can be catastrophic, as in the case of the Pakistan floods of July 2010. In this study, we identify extreme precipitation events (EPEs) in a box approximately covering this region (65◦ -78◦W, 25◦ -38◦N) using the APHRODITE gauge-based precipitation product. The role of the large-scale circulation in causing EPEs is investigated: it is found that, during winter, they often coexist with an upper-tropospheric Rossby wave train that has prominent anomalous southerlies over the region of interest. These winter EPEs are also found to be strongly colocated with incident western disturbances whereas those occurring during the summer are found to have a less direct relationship. Conversely, summer EPEs are found to have a strong relationship with tropical lows. A detailed Lagrangian method is used to explore possible sources of moisture for such events, and suggests that in winter, the moisture is mostly drawn from the Arabian Sea, whereas during the summer, it comes from along the African coast and the Indian monsoon trough region

How interactions between tropical depressions and western disturbances affect heavy precipitation in South Asia

Interactions over South Asia between tropical depressions (TDs) and extratropical storms known as western disturbances (WDs) are known to cause extreme precipitation events, including those responsible for the 2013 floods over northern India. In this study, existing databases of WD and TD tracks are used to identify potential WD–TD interactions from 1979–2015; these are filtered according to proximity and intensity, leaving 59 cases which form the basis of this paper. Synoptic charts, vorticity budgets, and moisture trajectory analyses are employed to identify and elucidate common interaction types among these cases. Two broad families of interaction emerge. Firstly, a dynamical coupling of the WD and TD, whereby either the upper- and lower-level vortices superpose (a vortex merger), or the TD is intensified as it passes into the entrance region of a jet streak associated with the WD (a jet-streak excitation). Secondly, a moisture exchange between the WD and TD, whereby either anomalous moisture is advected from the TD to the WD, resulting in anomalous precipitation near the WD (a TD-to-WD moisture exchange), or anomalous moisture is advected from the WD to the TD (a WD-to-TD moisture exchange). Interactions are most common in the post-monsoon period as the subtropical jet, which brings WDs to the subcontinent, returns south; there is a smaller peak in May and June, driven by monsoon onset vortices. Precipitation is heaviest in dynamically-coupled interactions, particularly jet–streak excitations. Criteria for automated identification of interaction types are proposed, and schematics for each type are presented to highlight key mechanisms

Forecasting the monsoon on daily to seasonal time‐scales in support of a field campaign

The successful planning and execution of a major field campaign relies on the availability and reliability of weather forecasts on a range of time‐scales. Here, we describe the wide range of forecast products generated in support of a field campaign that took place in India in 2016 as part of the Interaction of Convective Organization with Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) project. We show examples of the suite of plots generated every day from the forecasts and supplied to the mission scientists, and describe how these were used to plan the flights. We highlight the benefits of having access to forecasts from a range of model resolutions and configurations; these allowed judgements to be made about uncertainty, particularly in the amount and location of deep convective rainfall, which is an important consideration for flight planning. Finally, we discuss the legacy of the forecasting activity, which has not only advanced our understanding of monsoon forecasting but also created a large database of targeted model forecast products for the whole of the 2016 monsoon season. These can be used by researchers for comparisons with in situ observations as well as future modelling studies