J. Sanjay

Deciphering the desiccation trend of the South Asian monsoon hydroclimate in a warming world

Rising propensity of precipitation extremes and concomitant decline of summer-monsoon rains are amongst the most distinctive hydroclimatic signals that have emerged over South Asia since 1950s. A clear understanding of the underlying causes driving these monsoon hydroclimatic signals has remained elusive. Using a state-of-the-art global climate model with high-resolution zooming over South Asia, we demonstrate that a juxtaposition of regional land-use changes, anthropogenic-aerosol forcing and the rapid warming signal of the equatorial Indian Ocean is crucial to produce the observed monsoon weakening in recent decades. Our findings also show that this monsoonal weakening significantly enhances occurrence of localized intense precipitation events, as compared to the global-warming response. A 21st century climate projection using the same high-resolution model indicates persistent decrease of monsoonal rains and prolongation of soil drying. Critical value-additions from this study include (1) realistic simulation of the mean and long-term historical trends in the Indian monsoon rainfall (2) robust attributions of changes in moderate and heavy precipitation events over Central India (3) a 21st century projection of drying trend of the South Asian monsoon. The present findings have profound bearing on the regional water-security, which is already under severe hydrological-stress.

A new approach to the cumulus parameterization issue

Can the superensemble methodology provide improved precipitation forecasts by combining existing physical parameterizations? We recently addressed this question in the context of Numerical Weather Prediction (NWP).We feel, however, that the information provided here may be useful for seasonal climate modeling as well. In theNWPcontext, we have developed multi-model forecasts from six versions of the Florida State University global spectral model (at a horizontal resolution of 170 waves, triangular truncation). These different versions deployed six different cumulus parameterization schemes; these models were identical in all other aspects, including the initial states. Making the assumption that differences in short-range (one day) forecasts of precipitation arise largely from differences in the cumulus parameterization, a superensemble methodology, following a recent study, was deployed to assign geographically distributed weights to convective heating for the different cumulus parameterization schemes. This was done after completion of some 85 experiments for each model for the training phase of the superensemble. A new single spectral model was next designed that included the weighted sum of the six cumulus parameterization schemes strung out within this model. This model was next shown to outperform in NWP forecasts of precipitation compared to any of those models that used a single cumulus parameterization scheme. This merely suggests that no single, present scheme is superior to all other schemes over the entire tropical belt; they all seem to have some virtues over different geographical regions. This Unified collective scheme is physically based since it does carry mechanisms such as mass flux, moisture convergence, cloud detrainment, downdrafts, effects of sea surface temperature etc. that are explicitly carried within one or the other schemes. This collective scheme is, however, based on optimized weights for these processes that vary geographically. It is our premise that even if a new breakthrough in cumulus parameterization were to occur from the development of a new scheme, that scheme, at best, may only achieve a skill ranking of number three for precipitation forecasts. The first place, we noted, still belongs to a multi-model superensemble, based on the optimal combination of six separate models. The second place belongs to the single model that utilizes a strung out weighted sum of many cumulus parameterization schemes within it. The individual member models have larger precipitation forecast errors compared to the two above. The skills, here, are evaluated using standard metrics such as correlations, root mean square errors and the equitable threat scores; finally we also present the vertical profiles of the apparent heat source and the apparent moisture sink that also confirm these above findings.

Numerical simulation of a super cyclonic storm, Orissa 1999: impact of initial conditions

Numerical simulations are performed using the Penn State University/ National Center for Atmospheric Research Mesoscale Model (MM5) to study the impact of initial conditions on the super cyclone which hit the coast of Orissa in 1999. Because analysis of the cyclones circulation was inadequate in the initial fields owing to the coarse resolution of the operational analysis systems and sparse oceanic data coverage, synthetic vortex data were generated using empirical relations and used in the analysis. Four-dimensional data assimilation is performed in order to assimilate the synthetic vortex in the initial stage to the model. Considerable improvement in the track is obtained by using the synthetic vortex. With better specification of the initial vortex structure, the model successfully simulated the typical tropical cyclone characteristics, such as asymmetries in the wind field: the strongest winds occurred in the east and close to the cyclones centre, strong wind gradients were found between the centre and the maximum wind region, and there was a slow decrease in wind speed up to the middle troposphere. Despite failing to produce the intense pressure drop observed for this cyclone, the model shows much better cyclone development with enhanced initial condition than the analysis. Copyright

Evaluation of several different planetary boundary layer schemes within a single model, a unified model and a multimodel superensemble

This paper addresses the forecasts of latent heat fluxes from five different formulations of the planetary boundary layer (PBL). Different formulations are deployed within the Florida State University global spectral model. Hundreds of short range forecast experiments are carried out using daily data sets for summer 2002 with each model. The primary goal of this study is to compare the performance of the diverse family of PBL algorithms for the latent heat fluxes within the PBL. Benchmark fluxes are calculated from the vertical integrals of Yanai’s formulation of the apparent moisture sink and a precipitation using Physical Initialization. This provides indirectly observed estimates of the vertical fluxes of latent heat in the PBL. This comparison reveals that no single scheme shows a global spread of improvement over other models for forecasts of latent heat fluxes in the PBL. Among these diverse models the turbulent kinetic energy based closure provides somewhat better results. The construction of a multimodel superensemble provides a synthesis of these different PBL formulations and shows improved forecasts of the surface fluxes. A single unified model utilizing weighted PBL algorithms where all the five schemes are retained within a single model shows some promise for improving a single model.

Determination of Forecast Errors Arising from Different Components of Model Physics and Dynamics

This paper addresses a procedure to extract error estimates for the physical and dynamical components of a forecast model. This is a two-step process in which contributions to the forecast tendencies from individual terms of the model equations are first determined using an elaborate bookkeeping of the forecast. The second step regresses these estimates of tendencies from individual terms of the model equations against the observed total tendencies. This process is executed separately for the entire horizontal and vertical transform grid points of a global model. The summary of results based on the corrections to the physics and dynamics provided by the regression coefficients highlights the component errors of the model arising from its formulation. This study provides information on geographical and vertical distribution of forecast errors contributed by features such as nonlinear advective dynamics, the rest of the dynamics, deep cumulus convection, large-scale condensation physics, radiative processes, and the rest of physics. Several future possibilities from this work are also discussed in this paper.

On the weakening of Hurricane Lili, October 2002

This paper addresses the weakening of Hurricane Lili of October 2002 just before it made landfall in Louisiana. This hurricane weakened from a category 4 storm on October 3, 2002 at 0000 UTC to a category 1 storm on October 3, 2002 at 1300 UTC. This sudden drop in intensity has been a subject of considerable interest. In this paper we explore a forecast model diagnostic approach that explores the contribution to the hurricane intensity changes arising from a number of dynamical and physical possibilities. Running several versions of a global model at very high resolution, the relative contribution to the intensity drop of Lili arising from cooler sea surface temperatures, dry air advection into the storm, advective non-linear dynamics, non-advective dynamics, and shallow and deep cumulus convection was examined. This line of inquiry led to the conclusion that dry air advection from the north into the storm and the slightly cold sea surface temperatures were not the primary contribution to the observed pressure rise by 22 hPa. The primary contribution to the pressure rise was found to be the ‘rest of dynamics’ (the non-advective dynamics). The shallow convection contributed slightly to an overall cooling, i.e. a weakening of the warm core of Lili. The effects of deep cumulus convection appeared to be opposite, i.e. towards maintaining a strong storm. A primary term in the ‘rest of dynamics’, the advection of Earth’s angular momentum into the storm, is identified as a major contributor for the intensity change in the analysis. This feature resembles an intrusion of dry air into the core of the storm. This intrusion contributes to a reduction of spin and an overall rapid weakening of the hurricane. The angular momentum partitioning appears quite revealing on the sudden demise of Lili.

Non-monsoonal precipitation response over the Western Himalayas to climate change

Winter-to-early spring non-monsoonal precipitation over the Western Himalayas (WH) primarily comes from eastward propagating synoptic-scale weather systems known as western disturbances (WDs). Earlier studies have noted that an increasing trend of synoptic-scale WD activity in the past few decades has contributed to enhanced propensity of daily precipitation extremes over the WH, although it remains unclear as to whether these regional changes are manifestations of climate change. This issue is addressed by conducting a suite of long-term climate experiments using a global variable-grid climate model with high-resolution telescopic zooming over the South Asian region. Our findings highlight that human-induced climate change has implications on the rising trend of synoptic-scale WD activity and precipitation extremes over the WH during the recent few decades, and these changes cannot be explained by natural forcing alone. A stronger surface warming, in response to climate change, is noted over the vast expanse of the high-elevated eastern Tibetan Plateau relative to the western side. The model simulations show that strengthening of positive east–west temperature gradient across the Tibetan Plateau tends to alter the background mean circulation in a manner as to favor amplitude enhancements of the synoptic-scale WDs and orographic precipitation over the WH. With continuation of global warming in future and enhancement in the east–west temperature gradient across the Tibetan highlands, the trend of precipitation extremes over the WH and synoptic-scale WD activity are projected to rise into the twenty-first century. While the high-resolution simulations of this study offers promising potential to understand changes in synoptic-scale WD activity and precipitation extremes over the WH, further investigations are necessary to decipher the multi-scale behavior and intricacies of the Himalayan precipitation variability under changing climate.

Regional Climate Change Scenarios

In this chapter, we discuss the results of downscaling the climate over the Indian sub-continent using regional climate models (RCMs) following the coordinated regional climate downscaling experiment (CORDEX) framework. The climate change projections of four atmosphere-ocean coupled-global climate models (AOGCMs) have been downscaled for the period 1950–2100. The results of the downscaled RCMs are compared to those of the driving AOGCMs for the present climate in the period 1976–2005, to investigate whether RCMs are able to show added value, at regional scale relative to the performances of their driving AOGCMs. It is found that the spatial patterns of surface air temperature and seasonal precipitation are strongly affected by the choice of the RCM and driving AOGCMs. The RCMs are, however, able to improve the representation of the annual cycle of temperature in particular over the central India. The CORDEX South Asia RCMs indicate significant increases in temperatures over India in the mid-term (2031–2060) future climate change projections with the RCP4.5 scenario. However, the magnitude and sign of the summer monsoon season precipitation change over India is uncertain.

Impact of modified physics in limited area model forecasts

A number of physical factors have been introduced to improve limited area model forecasts. The factors include land surface fluxes, shallow convection and radiation. The model including these additional physical factors (modified physics) is run for five cases of monsoon depression which made landfall over the Indian coast, and the results are compared with those of the control run. The forecasts are verified by computing the root mean square and mean errors. The differences in these skill scores between the two model runs are tested for their statistical significance. It is found that the modified physics has a statistically significant effect on the model skill with the maximum impact on the mean sea level pressure and the temperature.Detailed analyses of mean sea level pressure, wind, rainfall and temperature further confirm that the modified physics has maximum impact on mean sea level pressure and temperature and marginal impact on wind and rainfall. Furthermore, analyses of some model parameters related to physics at a grid point for one case of depression were done. The results show that the inclusion of the land surface physics, shallow convection and radiative processes have produced a better precipitation forecast over the grid point.