Study of intraseasonal variability of Indian summer monsoon using a regional climate model

Maharana, P.; Dimri, A. P.

doi:10.1007/s00382-015-2631-0

Cited by 54 publications

(23 citation statements)

References 44 publications

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“…In RCLM, the negative bias is comparatively smaller than RBAT over the Gangetic plains and east peninsular India. Possible factors for these differences with observations could be the formulations used in the land surface schemes [see Saha et al , ; Maharana and Dimri , , ]. Biases in the formulation of radiation and convective parameterization can also partly contribute to the surface temperature bias.…”

Section: Resultssupporting

confidence: 82%

“…However, simulated wind speed is overestimated over the core region of the Somali Jet, the east equatorial Indian Ocean and also near the foothills of the Himalayas in both models (bias in Figure c is shown only for RBAT). Such biases have also been reported in earlier studies [ Saha et al , ; Maharana and Dimri , , ]. Increased wind speed over the ocean is associated with positive rainfall bias in the models (figure not shown), that is attributed to the lack of ocean‐atmosphere coupling [ Ratnam et al , ; Saha et al , ] and the choice of convective parameterization schemes [ Chow et al , ].…”

Section: Resultsmentioning

confidence: 67%

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Sensitivity of the mean and variability of Indian summer monsoon to land surface schemes in RegCM4: Understanding coupled land‐atmosphere feedbacks

2015

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A relatively simple land surface model, the Biosphere‐Atmosphere Transfer Scheme (BATS) and the more complex Community Land Model (CLM3.5) coupled to RegCM4 are used to investigate land‐atmosphere feedback processes during the Indian summer monsoon. Model simulations for 27 years show that the mean and interannual variability of rainfall and surface air temperature are affected significantly due to differences in the formulation of evapotranspiration and hydrological processes between BATS and CLM3.5, prescribed land use, land cover data and changes in net radiation. RegCM4 with CLM3.5 (RCLM) shows a reduction in surface moisture flux and precipitation but an increase in surface air temperature over most parts of India as compared to RegCM4 with BATS (RBAT). In terms of the mean and interannual variability of rainfall over central India, RBAT performs better than RCLM. Evapotranspiration over central India is found to be less (more) sensitive to soil wetness variations in RCLM (RBAT) compared to the multimodel estimate from the Global Soil Wetness Project, that is mainly attributed to the differences in ground evaporation and transpiration. Changes in evaporation efficiency between the models also lead to a reduction in the land‐atmosphere coupling strength for precipitation in RCLM. Furthermore, such changes decrease the convective instability over central and eastern India in RCLM leading to weakened convection, reduced large‐scale moisture convergence and precipitation over land. Observations of soil moisture, surface fluxes, and radiation are needed for better understanding and improvement of coupled land‐atmosphere feedbacks in models during the Indian summer monsoon.

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Section: Resultssupporting

confidence: 82%

Section: Resultsmentioning

confidence: 67%

Sensitivity of the mean and variability of Indian summer monsoon to land surface schemes in RegCM4: Understanding coupled land‐atmosphere feedbacks

2015

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“…The high concentration can be related to irregular 'break monsoon periods', i.e. the shifting of the eastern end of the seasonal monsoon trough to the foothills of the Himalayas in the north, when the monsoon activities are intensified (Maharana and Dimri 2015). The study of Dhar et al (1984) has shown that, on a 'break' day, positive percentage departures of rainfall as high as 100-300% have occurred at stations located in the outer Himalaya and the Fig.…”

Section: Rainfall Concentrationmentioning

confidence: 99%

Impact of the Darjeeling–Bhutan Himalayan front on rainfall hazard pattern

Prokop

Walanus

2017

Nat Hazards

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Multiscale interaction between monsoonal circulation and the local topography causes the southern front of the Darjeeling-Bhutan Himalaya to receive one of the highest annual rainfalls (3000-6000 mm) and most frequent heavy rains (up to 800 mm day -1 ) along the whole southern Himalayan margin. An examination of the patterns of annual rainfall, rainfall concentration, overland flow generation and slope instability indices in the Darjeeling-Bhutan Himalaya for 1986-2015 indicates that the mountain front disturbs rainfall gradient between the Bay of Bengal and the Tibetan Plateau. The results show that the precipitation concentration indices are lowest at the Himalayan front where the annual rainfall and the number of rainy days are highest. The Himalayan front has the highest predisposition to produce overland flow compared to adjacent foreland and the mountain interior. The average probability of the rainfall initialising the shallow landslides increases from 0.6% for a 1-day rainfall threshold of 144 mm to 6.1% for a 4-day rainfall threshold of 193 mm in the study area. The highest probability (up to 10%) of 2-day and longer lowintensity storms at the mountain front indicate that its area is threatened with particularly larger and deeper landslides. The multivariate regression analysis reveals statistically significant linear relationships of rainfall hazard indices with elevation and the distance to the mountain front in the mountain foreland and Himalaya, respectively. Regionally, the Darjeeling Himalaya reveals lower values of rainfall hazard indices, in comparison to the

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“…They also found the RCM simulation to be insensitive to the size of the domain used in simulating the Indian summer monsoon. Several studies have shown that RCMs are capable of realistically simulating the Indian summer monsoon precipitation at seasonal (Jacob & Podzum 1997, Vernekar & Ji 1999 as well as at subseasonal (Maharana & Dimri 2016, Umakanth et al 2016) time scales. However, the simulated precipitation has been found to be sensitive to the cumulus parameterization schemes used in the RCMs (Ratnam & Kumar 2005, Dash et al 2006, Mukhopadhyay et al 2010, Raju et al 2015, Umakanth et al 2016 at both seasonal and sub-seasonal time scales.…”

Section: Introductionmentioning

confidence: 99%

“…A number of studies have been carried out using the RCMs to simulate the spatial and temporal features of the Indian summer monsoon at intraseasonal and interannual time scales (Bhaskaran et al 1996, Jacob & Podzum 1997, Juang et al 1997, Vernekar & Ji 1999, Ratnam & Kumar 2005, Dash et al 2006, Ratnam & Cox 2006, Ratnam et al 2009, Muk ho padhyay et al 2010, Lucas-Picher et al 2011, Bhaskar Rao et al 2013, Vellore et al 2014, Raju et al 2015, Maharana & Dimri 2016, Uma kanth et al 2016. Using a regional climate model at 50 km resolution, which was driven by the United Kingdom Meteorological Office Unified Model (UM) global model output, Bhaskaran et al (1996) found that the RCM improved the UM-simulated precipitation due to its higher horizontal resolution.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Indian summer monsoon simulation to physical parameterization schemes in the WRF model

et al. 2017

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A set of 17 experiments, using various combinations of physical parameterization schemes in the Weather Research and Forecasting (WRF) model, were carried out to choose a combination suitable for simulating the Indian summer monsoon. The model experiments, forced with the ERA-Interim reanalysis data, were at 30 km horizontal resolution. The WRF model experiments were initialized on 1 May of each year and integrated until 30 September to cover the entire monsoon season for the years 1982 to 2013. The results indicate that the simulated Indian summer monsoon precipitation and 2 m air temperature are sensitive to the physical parameterization schemes in the WRF model and that choosing the correct combination of physical parameterization schemes is essential for simulating the Indian summer monsoon realistically. Our analysis shows that a model setup with the Kain−Fritsch cumulus scheme, a radiation package with the Dudhia shortwave and Rapid Radiative Transfer Model longwave schemes, the Yonsei State University planetary boundary layer scheme, the WRF Single-Moment 3-class microphysics scheme, the revised MM5 Monin-Obukhov surface layer scheme, and the Unified Noah land surface model is suitable for simulating the precipitation realistically. The model setup with a combination of these physical parameterization schemes was found to have smaller biases and root mean square errors in the simulated precipitation, along with a realistic simulation of intraseasonal and interannual variability of precipitation. The results of this study will be useful to researchers and forecasters using the WRF model to improve the Indian summer monsoon simulations/ forecasts over the Indian region.

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Study of intraseasonal variability of Indian summer monsoon using a regional climate model

Cited by 54 publications

References 44 publications

Sensitivity of the mean and variability of Indian summer monsoon to land surface schemes in RegCM4: Understanding coupled land‐atmosphere feedbacks

Sensitivity of the mean and variability of Indian summer monsoon to land surface schemes in RegCM4: Understanding coupled land‐atmosphere feedbacks

Impact of the Darjeeling–Bhutan Himalayan front on rainfall hazard pattern

Sensitivity of Indian summer monsoon simulation to physical parameterization schemes in the WRF model

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