Simulation of Monsoon Disturbances in the LMD GCM

Sabre, Maeva; Hodges, Kevin I.; Laval, K.; Polcher‬, Jan; Désalmand, Françoise

doi:10.1175/1520-0493(2001)129<3752:somdit>2.0.co;2

Cited by 24 publications

(13 citation statements)

References 22 publications

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“…6. Consistent with previous studies with the MetUM and other GCMs (Ashok et al 2000;Sabre et al 2000;Stowasser et al 2009), there are far fewer LPS detected in the MetUM than in ERA-Interim or the IMD e-atlas, and the resolution sensitivity is very small compared to the size of the bias. Variation between ensemble members is also large compared to the resolution sensitivity.…”

Section: Monsoon Low Pressure Systemssupporting

confidence: 88%

“…Monsoon low pressure systems (LPS), including the more intense monsoon depressions and less intense monsoon lows, are synoptic systems that generally develop in the Bay of Bengal and pass up the monsoon trough, increasing precipitation in central and northern India and generating many of the most intense rain events in the monsoon (Sikka 1977;Krishnamurthy and Misra 2010). These systems are often too infrequent and too weak in GCMs (Ashok et al 2000;Sabre et al 2000;Stowasser et al 2009). …”

Section: Introductionmentioning

confidence: 99%

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The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

et al. 2015

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and the Maritime Continent results in more precipitation over the Maritime Continent islands at the expense of reduced precipitation further north. We also evaluate the resolution sensitivity of monsoon depressions and lows, which contribute more precipitation over northeast India at higher resolution. We conclude that while increasing resolution at these scales does not solve the many monsoon biases that exist in GCMs, it has a number of small, beneficial impacts.

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Section: Monsoon Low Pressure Systemssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

et al. 2015

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“…Instead, the resolution varies in a smooth and continuous fashion along longitude and latitude. The basic formulation and validation of the model adopted here [version LMDZ3 developed at the Laboratoire de Météorologie Dynamique (LMD), France], including formulation of variable resolution, have been described in detail in earlier works (Sadourny and Laval 1984;Sharma et al 1987;Sabre et al 2000;Goswami andGouda 2009, 2010). The variable resolution is prescribed as a continuous variation (stretching) in the coordinate with respect to a point (zoom).…”

Section: A Model Configurationmentioning

confidence: 99%

Objective Debiasing for Improved Forecasting of Tropical Cyclone Intensity with a Global Circulation Model

Goswami¹,

Mallick²,

Gouda³

2011

Monthly Weather Review

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The damage potential of a tropical cyclone is proportional to a power (generally greater than one) of intensity, which demands high accuracy in forecasting intensity for managing this natural disaster. However, the current skill in forecasting cyclone intensity is rather limited, especially over the north Indian Ocean, with very little improvement over the years. A methodology is presented here for objective nonlinear debiasing to generate intensity forecasts with enhanced reliability from raw forecasts. The intensity forecast is generated using an optimized configuration of a variable resolution global circulation model (VR-GCM) that combines the advantages of a limited area model and a global model. The hindcasts were carried out in a completely operational setting, that is, without assuming any observed information beyond the day of the initial condition. The VR-GCM and a nonlinear debiasing were found to provide skill (skill score ;0.5) in forecasting tropical cyclone intensity 2-7 days (variable depending on event) in advance for the 30 cases including storms and cyclones representing different locations, seasons, and years (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) over the Bay of Bengal. Two types of debiasing are considered: nonlinear debiasing with all observations (potential skill) and nonlinear debiasing for realizable skill (training without in-sample data). It is shown that while skill scores without debiasing are only marginally better than a climatological forecast (null hypothesis), the skill score with a nonlinear debiasing is appreciable. The climatological forecast has zero skill score, a mean absolute error of 12.9 m s 21 , and 20% of the cases are in the error bin 25 to 15 m s 21 ; the corresponding numbers for debiased forecasts for realizable skill are 0.65, 6.4 m s 21 , and 57%. It is further shown that the nonlinear debiasing is also effective in improving forecast of (3-hourly) intensity change. While a strict comparison of skill with other methods requires experiments to be carried out for the same events, a comparison of the skill of other methods and over different ocean basins based on available data shows the present method to have comparable skill. However, it may be noted that the present conclusions are based on a relatively small (30 events) sample size; evaluation with a much large sample size is desirable for actual application.

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“…Like in 2002, TID03 (Figure 9(e)), TAF03 (Figure 9(k)), and EMAO03 (Figure 9(n)) have also overestimated the rainfall over the Arabian Sea. The poor rainfall simulation over the Western Ghats may also be due to the coarse horizontal resolution, namely, 3.8°longitude and 2.5°l atitude (Sabre et al, 2000), and the absence of vegetation in the model. In the present simulations, climatological soil moisture, sea ice, and albedo are used, despite the fact that the importance of evolving soil moisture and related land-surface parameters for monsoon simulations is well known (Meehl, 1994;Douville et al, 2001;Douville, 2002Douville, , 2003.…”

Section: Hpa Windsmentioning

confidence: 99%

Simulation of Indian summer monsoon: sensitivity to cumulus parameterization in a GCM

Deb¹,

Upadhyaya²,

Sharma³

et al. 2006

Intl Journal of Climatology

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Abstract:Hindcasts for the Indian summer monsoons (ISMs) of 2002 and 2003 have been produced from a series of numerical simulations performed with a general circulation model using different cumulus parameterization schemes. Ten sets of ensemble simulations have been produced without using any vegetation scheme but by prescribing the monthly observed SST from the ECMWF (European Centre for Medium Range Weather Forecasts) analyses. For each ensemble, ten simulations have been realised with different initial conditions that are also prepared from the ECMWF data: five each from the April and May analyses of both the years. Stream function, velocity potential with divergent winds at 200 hPa, winds at 850 hPa and rainfall patterns with their anomalies have been analysed and interpreted. The large-scale upper and lower level circulation features are simulated satisfactorily. The spatial structure of predicted July monsoon rainfall over India shows a fair agreement with the GPCP (observed) pentad rainfall distribution. The variability associated with all-India June-July simulated rainfall time series matches reasonably well with the observations in 2003, but the model fails to simulate the observed variability in July 2002. Further evaluation of the model-produced precipitation in seasonal simulations is done with the help of empirical orthogonal functions (EOFs) of the GPCP rainfall over India. Since the first four EOFs explain a significant part of the total variance of the observed rainfall, the simulated precipitation is projected on to these modes. Thus, the differences in simulated and observed rainfall fields manifest in the time series of their expansion coefficients, which are utilised for inter-comparison/evaluation of model simulations.

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Simulation of Monsoon Disturbances in the LMD GCM

Cited by 24 publications

References 22 publications

The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

Objective Debiasing for Improved Forecasting of Tropical Cyclone Intensity with a Global Circulation Model

Simulation of Indian summer monsoon: sensitivity to cumulus parameterization in a GCM

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