Skill of Medium-Range Forecasts over the Indian Monsoon Region Using Different Parameterizations of Deep Convection

Das, Someshwar; Mitra, Ashis K.; Iyengar, G. R.; Singh, Jagvir

doi:10.1175/1520-0434(2002)017<1194:somrfo>2.0.co;2

Cited by 37 publications

(17 citation statements)

References 26 publications

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“…They concluded that SAS performed better in simulating the regional features of ISM. Das et al (2002) carried out another sensitivity study using the above CCS to observe the skill of medium range forecast over the Indian region which corroborates their previous findings. Dash et al (2006) investigated the sensitivity of ISM on cumulus convection for a four-yr. period (1993)(1994)(1995)(1996) using RegCM3 and concluded that the Grell scheme (Grell, 1993;Grell et al, 1994) performed better.…”

Section: Introductionsupporting

confidence: 80%

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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Section: Introductionsupporting

confidence: 80%

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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“…The basic feature that differentiates CPSs is the closure assumptions upon which they are based. The schemes vary in complexity from simple moist convective adjustment to sophisticated mass flux-type schemes (DAS et al, 2002). It is recognized that convection in nature often develops mesoscale organization and these resolvable mesoscale structures develop from initially unresolvable cumulonimbus clouds that in itself provides a major challenge to mesoscale modelers.…”

Section: Introductionmentioning

confidence: 99%

“…The adequate representation of convective processes is particularly important in numerical models, but there is no universally accepted framework for representing such processes with grid scales that prohibit fully explicit representation (GOCHIS et al, 2002). CPSs are developed for specific synoptic conditions, and are evaluated in a limited number of cases (KUO et al, 1996;WANG and SEAMAN, 1997;PENG and TSUBOKI, 1997;YANG et al, 2000;GOCHIS et al, 2002;YANG and TUNG, 2003;DAS et al, 2002). YANG and TUNG (2003) performed an evaluative study to discern the performance of four CPSs, the Anthes-Kuo (ANTHES, 1977), Betts-Miller (BETTS and MILLER, 1986), Grell (GRELL, 1993), and Kain-Fritsch scheme (KAIN and FRITSCH, 1993) in the rainfall forecasts over Taiwan using MM5.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

Rakesh

Singh

Pal

et al. 2007

Pure appl. geophys.

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The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, KainFritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, rootmean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.

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“…From this study, it is concluded that the major defects of excessive precipitation over the tropical land areas, and overestimates of light precipitation events in the Kuo scheme (e.g., Pan and Wu 1995;Bélair et al 2000;Das et al 2002), can be improved significantly by the inclusion of moist downdrafts. Our results also indicate that modifying the low level properties in the convective parameterization scheme, is very important in improving the skill for precipitation forecasts.…”

Section: A Summary and Concluding Remarksmentioning

confidence: 89%

An Evaluation of a Mass-Flux Cumulus Parameterization Scheme in the KMA Global Forecast System

Park

Hong

2007

Journal of the Meteorological Society of Japan

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A mass-flux type cumulus parameterization scheme is evaluated in the Korea Meteorological Administration (KMA)'s Global Data Assimilation and Prediction System (GDAPS). Two sets of parallel assimilation runs, with a horizontal resolution corresponding to the spectral truncation of T213, approximately 50 km, are designed, one with the operational Kuo convection scheme, and another with a simplified Arakawa-Schubert (SAS) convection scheme, for the month of July 2001, which was a typical summer monsoon period in Korea. An additional sensitivity experiment, that excludes the moist downdrafts in the SAS scheme, is conducted. A 10-day forecast cycle is run, within a data assimilation window, beginning at every 1200 UTC in July 2001. A heavy rainfall event, that occurred in the Korean peninsula on 14-15 July 2001, is investigated in detail.For the heavy rainfall case, the SAS scheme tends to reduce the precipitation amount, as compared to the Kuo scheme. It is found that the exclusion of moist downdrafts in the SAS scheme, increases drying and heating rates, resulting in enhanced rainfall, as shown in the Kuo scheme. The monthly verification demonstrates that the systematic warm bias in the lower troposphere in the operational model is nearly absent when the SAS scheme is employed. In terms of statistical measure of the skill for the predicted sea-level pressure, and that for the upper level patterns, the experiment with the SAS (Kuo) scheme outperforms in the northern (southern) hemisphere. In the case of precipitation forecasts, the SAS scheme effectively corrects the spurious excessive precipitation over the tropical land area, due to the inclusion of moist downdrafts. However, the reduction in precipitation in the SAS scheme, deteriorates the forecast skill for high precipitation categories.

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Skill of Medium-Range Forecasts over the Indian Monsoon Region Using Different Parameterizations of Deep Convection

Cited by 37 publications

References 26 publications

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

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

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

An Evaluation of a Mass-Flux Cumulus Parameterization Scheme in the KMA Global Forecast System

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