Simulation of the Indian summer monsoon regional climate using advanced research WRF model

Srinivas, C. V.; Hariprasad, D.; Rao, D. V. Subba; Anjaneyulu, Y.; Baskaran, R.; Venkatraman, B.

doi:10.1002/joc.3505

Cited by 117 publications

(99 citation statements)

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“…The simula-tion shows improvement of pentad rainfall in both area and quantity over NNRP data which is evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India in both simulation and IMD observations. The simulation has missed a few isolated peaks of high pentad rainfall (10-20 cm) over the west coast and the northeast zone, which is due to underestimation of orographic rainfall in these zones (Srinivas et al, 2012). The simulated rainfall for the period (11-15 June) shows spread of rainfall (2-5 cm) into Maharashtra and Chhattisgarh states in the central peninsula and Orissa, West Bengal and Bihar states in eastern India, as in observations.…”

Section: Spatial Pentad Rainfall Distributionmentioning

confidence: 61%

“…Zone 1 is located in drysemiarid northern India, zone 2 in the arid northwest, zone 3 in dry-subhumid central India, zone 4 in moist-subhumid central northeast, zone 5 in the perhumid northeast, zone 6 along the perhumid west coast and zone 7 in the semi-arid southeast peninsular of India, respectively. The climatological mean monsoonal rainfall is 700 mm in zone 1 (Thornthwaite moisture index I m between −33.4 to −83.3), 850 mm in zone 2 (I m < −66.7), 1025 mm in zone 3 (I m in the range −33.3 to 0), 1000 mm in zone 4 (0 < I m < 20), 1450 mm in zone 5 (20 < I m < 100), 3000 mm in zone 6 (I m > 100) and 850 mm in zone 7 (−49.9 < I m < −33.4) respectively (Srinivas et al, 2012). As the onset phase is characterized by a sudden increase in rainfall (Rao, 1976), pentad (5-day running total) rainfall is used to examine the advancement of the onset phase and to analyze the onset time in different zones.…”

Section: Discussionmentioning

confidence: 99%

“…1a). A description of these zones is given in our earlier work (Srinivas et al, 2012). Zone 1 is located in drysemiarid northern India, zone 2 in the arid northwest, zone 3 in dry-subhumid central India, zone 4 in moist-subhumid central northeast, zone 5 in the perhumid northeast, zone 6 along the perhumid west coast and zone 7 in the semi-arid southeast peninsular of India, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…The selected physics options are WRF single moment 3-class (WSM3) explicit microphysics , Dudhia scheme (Dudhia, 1989) for shortwave radiation processes, RRTM (rapid radiation transfer model) scheme for long-wave radiation processes (Mlawer et al, 1997), the Yonsei University scheme for the boundary layer turbulence Hong et al, 2006) and Noah (Chen and Dudhia, 2001) scheme for land surface processes. The Betts-Miller-Janjic (BMJ) scheme (Betts and Miller, 1986;Janjic, 2000) is used for cumulus convection following the recent sensitivity studies with ARW for ISM rainfall (Hari Prasad et al, 2011;Mukhopadhyay et al, 2010;Srinivas et al, 2012).…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…In recent studies, the Advanced Research Weather Research and Forecasting (ARW) regional model has been used to simulate the ISM and its rainfall climatology (Hari Prasad et al, 2011;Mukhopadhyay et al, 2010;Srinivas et al, 2014;Raju et al, 2013Raju et al, , 2014. Srinivas et al (2012) made seasonal-scale simulations of the ISM regional climate with ARW for the decade 2000-2009 and reported that the model reproduces the interannual variations in monsoon characteristics in terms of the pressure, temperature, winds and rainfall associated with ENSO phases and that the simulated monsoon rainfall is sensitive to the convective parameterization. The objective of the present study is to assess the performance of the ARW model in simulating the time and distribution of the ISM rainfall during the onset phase (June) through the simulation of 10 continuous ISM seasons, which included deficit, normal and surplus ISM rainfall.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

et al. 2015

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Abstract. This study examines the ability of the Advanced Research WRF (ARW) regional model to simulate Indian summer monsoon (ISM) rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000-2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP) global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25 • IMD (India Meteorological Department) rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid) of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast) with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative) and above-normal onset (June positive) phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over northeast, east and west coast areas, the ARW captured these regional features showing improvement upon NNRP reanalysis, which may be due to the high resolution (30 km) employed. The onset-phase rainfall characteristics during the contrasting ISM of 2003 and 2009 are well simulated in terms of the variations in the strength of low-level jet (LLJ) and outgoing long-wave radiation (OLR).

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Section: Spatial Pentad Rainfall Distributionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Numerical Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

et al. 2015

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Impacts of urbanization on Indian summer monsoon rainfall extremes

et al. 2015

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Urban areas have different climatology with respect to their rural surroundings. Though urbanization is a worldwide phenomenon, it is especially prevalent in India, where urban areas have experienced an unprecedented rate of growth over the last 30 years. Here we take up an observational study to understand the influence of urbanization on the characteristics of precipitation (specifically extremes) in India. We identify 42 urban regions and compare their extreme rainfall characteristics with those of surrounding rural areas. We observe that, on an overall scale, the urban signatures on extreme rainfall are not prominently and consistently visible, but they are spatially nonuniform. Zonal analysis reveals significant impacts of urbanization on extreme rainfall in central and western regions of India. An additional examination, to understand the influences of urbanization on heavy rainfall climatology, is carried with station level data using a statistical method, quantile regression. This is performed for the most populated city of India, Mumbai, in pair with a nearby nonurban area, Alibaug; both having similar geographic location. The derived extreme rainfall regression quantiles reveal the sensitivity of extreme rainfall events to the increased urbanization. Overall the study identifies the climatological zones in India, where increased urbanization affects regional rainfall pattern and extremes, with a detailed case study of Mumbai. This also calls attention to the need of further experimental investigation, for the identification of the key climatological processes, in different regions of India, affected by increased urbanization.

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The NOW regional coupled model: Application to the tropical Indian Ocean climate and tropical cyclone activity

Samson

Masson

Lengaigne³

et al. 2014

J Adv Model Earth Syst

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This paper presents the NOW regional coupled ocean-atmosphere model built from the NEMO ocean and WRF atmospheric numerical models. This model is applied to the tropical Indian Ocean, with the oceanic and atmospheric components sharing a common 1 =4 horizontal grid. Long experiments are performed over the 1990-2009 period using the Betts-Miller-Janjic (BMJ) and Kain-Fritsch (KF) cumulus parameterizations. Both simulations produce a realistic distribution of seasonal rainfall and a realistic northward seasonal migration of monsoon rainfall over the Indian subcontinent. At subseasonal time scales, the model reasonably reproduces summer monsoon active and break phases, although with underestimated rainfall and surface wind signals. Its relatively high resolution results in realistic spatial and seasonal distributions of tropical cyclones, but it fails to reproduce the strongest observed cyclone categories. At interannual time scales, the model reproduces the observed variability associated with the Indian Ocean Dipole (IOD) and the delayed basin-wide warming/cooling induced by the El Niño Southern Oscillation (ENSO). The timing of IOD occurrence in the model generally matches that of the observed events, confirming the influence of ENSO on the IOD development (through the effect of lateral boundary conditions in our simulations). Although the KF and BMJ simulations share a lot in common, KF strongly overestimates rainfall at all time scales. KF also overestimates the number of simulated cyclones by a factor two, while simulating stronger events (up to 55 m s 21) compared to BMJ (up to 40 m s 21). These results could be related to an overly active cumulus parameterization in KF.

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Simulation of the Indian summer monsoon regional climate using advanced research WRF model

Cited by 117 publications

References 50 publications

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

Impacts of urbanization on Indian summer monsoon rainfall extremes

The NOW regional coupled model: Application to the tropical Indian Ocean climate and tropical cyclone activity

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