This study investigates anomalous low cloud fractions (LCFs) in the Mascarene High(MH) environment of subtropical Indian Ocean (SIO) during June-September, and their sub-seasonal (10-90 day) circulation changes in the SIO and associated variations of the Indian summer monsoon (ISM) using observations and ERA5 circulation products based on 1999-2014 period. Periods of anomalous excess and deficits in LCFs in the SIO clearly reveal different sub-seasonal circulation attributes across the equator with precursor signals to the strength of ISM. Anomalous circulation composites from the excess LCF periods shows mean sea level pressure (MSLP) enhancements of about 2 hPa in the MH region in correspondence with increasing areal extent and intensifications in LCFs, and a net increase in low-level southerly momentum between MH and monsoon trough (MT) environments. The MSLP reinforcements in the MH are clearly demonstrated to emerge from the strength of cloud-top radiative cooling and associated winds and mass adjustments. The 10-20 [30 -50] day modes of the circulation in the SIO further elucidates zonally propagating [quasi-stationary] manifestations on MH reinforcements. There is an increase in meridional transport of moisture fluxes, by about 7 times relative to deficit LCF periods, channelled through aconduit region (15-30°S, 60-90°E) juxtaposing the cross-equatorial circulation (CEC) from both western and eastern sides of the Indian Ocean. This occurs in tandem with a zone of moisture flux convergence in the ISM region advancing poleward towards the climatological MT region - implying that excess LCF periods portend the likelihood of stronger ISM. Deficit LCF periods, on the contrary, show a mirrored scenario of the above with a net northerly low-level wind anomalies between MH and MT, pressure deficits in the MH region, and also portend the likelihood of weaker ISM. Low cloudsin the SIO are not only instrumental for MH stability, but also essential for circulation and moisture support across the equator and the signals for the strength of ISM on sub-seasonal scale.
An analysis of observed typhoon tracks and daily gl obal wind data for 56 years (1948–2003) reveals that largescale circulation anomalies associated with the inte rannual variability of the Indian monsoon play an i mportant role in influencing the tropical Pacific c yclone activity. The cyclogenesis over northwest and tropical west-central Pacific is found to be about 1.33 times higher during weak monsoon years compared to strong monsoon years. Also, there is greater tendency for the P acific cyclones to move northward and recurve (to the north of 20 °N) during weak monsoon years. The enhanced cyclogenesis during weak monsoon years is found to be associated with enrichment of low-level cyclonic vorticity anomalies over a wide region of the subtropical P acific extending from the China Sea, Taiwan and the Philippines region to the central Pacific; while the mov ement of the tropical cyclones is associated with anomalies of upper-tropospheric steering currents. Given that the interannual variability of the large-scale circulation over the Indo-Pacific sector is cr ucially determined by the El Nino/Southern Oscillation (ENSO) conditions, the present findings raise several questions pertaining to interactions among the large-scale circulation anomalies, tropical convection and the Pacific cyclonic distu rbances, which are likely to provide better understanding of the dynamical linkages between monsoon variability and ENSO. ONE of the interesting aspects of interannual variability in the tropics is the association b etween the Indian summer monsoon circulation and the convective activity over the west Pacific. The recent monsoon drought over India du ring 2002 is a good example that illustrates this point. The m ajor decrease in the Indian monsoon rainfall during 2002 o ccurred in July, when the rainfall was deficient by nearly 50% of the long-term normal
Macroscale hydrologic models (MHMs) were developed to study changes in land surface hydrology due to changing climate over large domains, such as continents or large river basins. However, there are many sources of uncertainty introduced in MHM hydrological simulation, such as model structure error, ineffective model parameters, and low‐accuracy model input or validation data. It is hence important to model the uncertainty arising in projection results from an MHM. The objective of this study is to present a Bayesian statistical inference framework for parameter uncertainty modeling of a macroscale hydrologic model. The Bayesian approach implemented using Markov Chain Monte Carlo (MCMC) methods is used in this study to model uncertainty arising from calibration parameters of the Variable Infiltration Capacity (VIC) MHM. The study examines large‐scale hydrologic impacts for Indian river basins and changes in discharges for three major river basins with distinct climatic and geographic characteristics, under climate change. Observed/reanalysis meteorological variables such as precipitation, temperature and wind speed are used to drive the VIC macroscale hydrologic model. An objective function describing the fit between observed and simulated discharges at four stations is used to compute the likelihood of the parameters. An MCMC approach using the Metropolis‐Hastings algorithm is used to update probability distributions of the parameters. For future hydrologic simulations, bias‐corrected GCM projections of climatic variables are used. The posterior distributions of VIC parameters are used for projection of 5th and 95th percentile discharge statistics at four stations, namely, Farakka, Jamtara, Garudeshwar, and Vijayawada for an ensemble of three GCMs and three scenarios, for two time slices. Spatial differences in uncertainty projections of runoff and evapotranspiration for years 2056–2065 for the a1b scenario at the 5th and 95th percentile levels are also projected. Results from the study show increased mean monthly discharges for Farakka and Vijayawada stations, and increased low, mid and high duration flows at Farakka, Jamtara and Vijayawada for the future. However, it is seen that uncertainty introduced due to choice of GCM, is larger than that due to parameter uncertainty for the VIC MHM. The largest effects of runoff predictive uncertainty due to uncertainty in VIC parameters are seen in the Himalayan foothills belt, and the high‐precipitation Northeast region of the country. It is demonstrated through the study that it is relevant and feasible to provide Bayesian uncertainty estimates for macroscale models in projection of large‐scale and regional hydrologic impacts.
Abstract Midtropospheric cyclones (MTCs) are a distinct class of synoptic disturbances, characterized by quasi-stationary cyclonic circulation in midtropospheric levels, which often produce heavy rainfall and floods over western India during the summer monsoon. This study presents a composite and diagnostic process study of long-lived (>5 days) midtropospheric cyclonic circulation events identified by the India Meteorological Department (IMD). Reanalysis data confirm earlier studies in revealing that the MTC composite has its strongest circulation in the midtroposphere. Lagged composites show that these events co-occur with broader-scale monsoon evolution, including larger synoptic-scale low pressure systems over the Bay of Bengal (BoB) and east coast, and the active phase of regional-scale poleward-propagating intraseasonal rain belts, with associated drying ahead (north) of the convectively active area. Diabatic heating composites, in particular the TRMM latent heating and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)-derived radiative cooling in the dry inland areas of southwest Asia north of the rain belt, are used to drive a nonlinear multilayer dynamical model in a forced-damped reconstruction of the global circulation. Results show that the midlevel circulation is largely attributable to top-heavy latent heating, indicative of the prevalence of stratiform-type precipitation in mesoscale convective systems in these moist, active larger-scale settings. Both the west coast and BoB latent heating are important, while the radiative cooling over southwest Asia plays a modest role in sharpening some of the simulated features. A conceptual model encapsulates the paradigm based on this composite and diagnostic modeling, a diabatic update of early theoretical studies that emphasized hydrodynamic flow instabilities.
Abstract Anthropogenic sea-level rise poses challenges to coastal areas globally. The combined influence of rising mean sea level (MSL) and storm surges exacerbate the extreme sea level (ESL). Increasing ESL poses a major challenge for climate change adaptation of nearly 2.6 billion inhabitants in the Indian Ocean region. Yet, knowledge about past occurrences of ESL and its progression is limited. Combining multiple tide-gauge and satellite-derived sea-level data, we show that ESL has become more frequent, longer-lasting and intense along the Indian Ocean coastlines. We detect a 2–3-fold increase in ESL occurrence, with higher risk along the Arabian Sea coastline and the Indian Ocean Islands. Our results reveal that rising MSL is the primary contributor to ESL increase (more than 75%), with additional contribution from intensifying tropical cyclones. A two-fold increase in ESL along the Indian Ocean coastline is detected with an additional 0.5 °C warming of the Indian Ocean relative to pre-industrial levels. Utilizing the likely range (17th–83rd percentile as the spread) of Intergovernmental Panel on Climate Change MSL projections with considerable inter-model spread, we show that the Indian Ocean region will be exposed annually to the present-day 100 year ESL event by 2100, irrespective of the greenhouse-gas emission pathways, and by 2050 under the moderate-emission-mitigation-policy scenario. The study provides a robust regional estimate of ESL and its progression with rising MSL, which is important for climate change adaptation policies.
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