Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments

Bhaskaran, B.; Jones, R. G.; Murphy, James M.; Noguer, M.

doi:10.1007/bf00216267

Cited by 117 publications

(63 citation statements)

References 24 publications

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“…It can be configured for any domain size and location has commonly been used for studies over Europe (Jones et al, 1995), the Arctic (Day et al, 2013) and Svalbard (Day et al, 2012), and the East Asian Monsoon region (Bhaskaran et al, 1996). It has also been used to model deep time (Haywood et al, 2004).…”

Section: Hadrm3bmentioning

confidence: 99%

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

et al. 2017

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Abstract. Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing withPublished by Copernicus Publications on behalf of the European Geosciences Union. observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

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Section: Hadrm3bmentioning

confidence: 99%

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

et al. 2017

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“…Due to its large impact on Indian economy, the ISM has been an important topic of research for more than a century now. Numerous studies have been conducted to understand the mechanism and physical processes (i.e., large scale circulation processes) of the ISM (Shukla and Paolino, 1983;Shukla and Fennessy, 1994;Bhaskaran et al, 1996;Goswami et al, 1998;Webster et al, 1998;Lal et al, 2000;Zhou and Li, 2002;Mohanty et al, 2002Mohanty et al, , 2005Kang et al, 2002;Rao et al, 2004;Singh et al, 2007;Raju et al, 2010;Zhou, 2013, 2014;Zhu, 2015;Almazroui et al, 2016). However, convection plays an important role in the development and maintenance of the ISM through the release of latent heat and vertical transport of heat, moisture and momentum (Ghosh et al, 1978;Kain, 1993;Zhu, 2015).…”

Section: Introductionmentioning

confidence: 99%

Performance of cumulus parameterization schemes in the simulation of Indian Summer Monsoon using RegCM4

Maity¹,

Mandal²,

Nayak³

et al. 2017

Atm

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El monzón de verano de la India (MVI) se origina a partir de una convección de gran escala, por lo que su simulación debe basarse en la representación adecuada de la convección de cumulus en el modelo. En este estudio se analiza el desempeño de diversos esquemas de parametrización en simulaciones del MVI. El modelo climático regional RegCM4 se acopla con el modelo de suelo CLM 3.5 con una resolución de 30 km para simular el MVI en el periodo comprendido entre el 1 de mayo y el 30 de septiembre en tres años consecutivos: 2007, 2008 y 2009. Se llevaron a cabo cinco experimentos numéricos con cinco esquemas de convección (Kuo, Grell, MIT, GO_ML [MIT sobre tierra y Grell sobre el océano] y GL_MO [Grell sobre tierra y MIT sobre el océano]) para cada uno de los años mencionados. Algunas características importantes del MVI simulado con el modelo, a saber la corriente en chorro del oeste de niveles bajos, la corriente en chorro del este de niveles altos, los sistemas de baja presión superficial y los de alta presión sobre la meseta tibetana, etc., se analizan y comparan con datos de reanálisis del National Center for Environmental Prediction (NCEP). Se encontró que el modelo con el esquema de convección MIT simula mejor los sistemas de baja presión superficial asociados con alta temperatura en el noroeste de la India y Paquistán durante los tres años, en tanto que el esquema GL_MO simula mejor la distribución espacial y exactitud de la temperatura. El modelo con el esquema de convección MIT reproduce adecuadamente la corriente en chorro del oeste de niveles bajos con fuerza algo menor que el reanálisis del NCEP. Todos los esquemas simularon aceptablemente la ubicación y fuerza de la corriente en chorro tropical del este, con cierta incertidumbre en cuanto a la fuerza, y mayor exactitud con el esquema MIT. La comparación entre la precipitación simulada y las bases de datos de la Unidad de Investigación del Clima con resolución de 0.5º (CRU TS3.22) indica que la precipitación media estacional y mensual se simula mejor con los esquemas de convección MIT y GO_ML. Sin embargo, todos los esquemas de convección del modelo subestiman de manera significativa estas mismas variables sobre el centro y el oeste de la India. Un flujo mayor de calor sensible y un flujo menor de calor latente afectan de manera significativa la simulación de temperatura superficial y precipitación con todos los esquemas. El análisis estadístico indica que los esquemas GL_MO y GO_ML del modelo reproducen de manera adecuada la temperatura superficial y la cantidad de precipitación, pero el esquema MIT simula mejor la circulación. Aunque este último implica una desviación ligeramente mayor a la de los dos esquemas combinados, se observó que la distribución espacial y otras características sinópticas de la temperatura superficial y la precipitación durante el MVI fueron bien simuladas por el esquema MIT. En conclusión, tomando en cuenta el desempeño de todos los esquemas, el modelo RegCM4 con el esquema MIT de convección de cumulus ofrece una mejor simulaci...

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“…RCMs dynamically downscale the GCM simulations (or reanalysis) and perform a climate simulation over a certain region of the globe (Prein et al, 2015;Giorgi, 2006). Using similar limited computing resources, RCMs are able to perform climate simulations at much higher spatial resolutions and are expected to better capture higher-frequency atmospheric variance and better resolve important regional forcings associated with topography, land-sea contrast, and land cover (Bhaskaran et al, 1996;Dash et al, 2006). Many previous studies found that better ISM and MISO simulations can be achieved in the high-resolution RCMs (typically with grid spacings 50 km or less) than those in the GCMs with coarser grid spacings (e.g., Bhaskaran et al, 1998;Kolusu et al, 2014;Lucas-Picher et al, 2011;Srinivas et al, 2013;Raju et al, 2015;Samala et al, 2013;Vernekar and Ji, 1999;Mukhopadhyay et al, 2010;Saeed et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

2018

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Abstract. Simulations of the Indian summer monsoon by the cloud-permitting Weather Research and Forecasting (WRF) model at gray-zone resolution are described in this study, with a particular emphasis on the model ability to capture the monsoon intraseasonal oscillations (MISOs). Five boreal summers are simulated from 2007 to 2011 using the ERA-Interim reanalysis as the lateral boundary forcing data. Our experimental setup relies on a horizontal grid spacing of 9 km to explicitly simulate deep convection without the use of cumulus parameterizations. When compared to simulations with coarser grid spacing (27 km) and using a cumulus scheme, the 9 km simulations reduce the biases in mean precipitation and produce more realistic low-frequency variability associated with MISOs. Results show that the model at the 9 km gray-zone resolution captures the salient features of the summer monsoon. The spatial distributions and temporal evolutions of monsoon rainfall in the WRF simulations verify qualitatively well against observations from the Tropical Rainfall Measurement Mission (TRMM), with regional maxima located over Western Ghats, central India, Himalaya foothills, and the west coast of Myanmar. The onset, breaks, and withdrawal of the summer monsoon in each year are also realistically captured by the model. The MISO-phase composites of monsoon rainfall, low-level wind, and precipitable water anomalies in the simulations also agree qualitatively with the observations. Both the simulations and observations show a northeastward propagation of the MISOs, with the intensification and weakening of the Somali Jet over the Arabian Sea during the active and break phases of the Indian summer monsoon.

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Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments

Cited by 117 publications

References 24 publications

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

Performance of cumulus parameterization schemes in the simulation of Indian Summer Monsoon using RegCM4

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

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