Simulations and Seasonal Prediction of the Asian Summer Monsoon in the NCEP Climate Forecast System

Yang, Song; Zhang, Zuqiang; Kousky, Vernon E.; Higgins, R. Wayne; Yoo, Seunghwa; Jiang, Liang; Fan, Yun

doi:10.1175/2008jcli1961.1

Cited by 147 publications

(89 citation statements)

References 45 publications

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“…3 The climatological mean for the annual range of precipitation (mm/day) defined by the boreal summer mean (JJA) minus winter mean (DJF) precipitation in (a) observation, (b) SYS4 and (c) CFSv2. Contour interval is 5 mm/day high are weaker than observed in a manner similar to CFSv1 (Yang et al 2008). In both modeling systems, the stronger-than-observed easterly trade wind and convergence over the western North Pacific is consistent with the wet bias over the western Pacific warm pool and central Pacific (Fig.…”

Section: Seasonal Mean Bias and Prediction Skillsupporting

confidence: 67%

“…System 4 utilizes ECMWF's the most recent atmospheric model version, with higher resolution and a higher top of the atmosphere, more ensemble members and a larger reforecast data set . The NCEP CFSv1 has been examined in simulating and predicting El Nino-Southern Oscillation (ENSO) variability (Wang et al 2005b); Asian-Australian/Indian monsoon (Yang et al 2008;Liang et al 2009;Pattanaik and Kumar 2010) and climatic variation in the U.S. ). The NCEP CFSv2 (http://cfs.ncep.noaa.gov/) is an upgraded version of CFSv1 (Saha et al 2006) and became operational since 2011.…”

Section: Introductionmentioning

confidence: 99%

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Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

et al. 2012

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The seasonal prediction skill of the Asian summer monsoon is assessed using retrospective predictions ) from the ECMWF System 4 (SYS4) and NCEP CFS version 2 (CFSv2) seasonal prediction systems. In both SYS4 and CFSv2, a cold bias of sea-surface temperature (SST) is found over the equatorial Pacific, North Atlantic, Indian Oceans and over a broad region in the Southern Hemisphere relative to observations. In contrast, a warm bias is found over the northern part of North Pacific and North Atlantic. Excessive precipitation is found along the ITCZ, equatorial Atlantic, equatorial Indian Ocean and the maritime continent. The southwest monsoon flow and the Somali Jet are stronger in SYS4, while the southeasterly trade winds over the tropical Indian Ocean, the Somali Jet and the subtropical northwestern Pacific high are weaker in CFSv2 relative to the reanalysis. In both systems, the prediction of SST, precipitation and low-level zonal wind has greatest skill in the tropical belt, especially over the central and eastern Pacific where the influence of El Nino-Southern Oscillation (ENSO) is dominant. Both modeling systems capture the global monsoon and the large-scale monsoon wind variability well, while at the same time performing poorly in simulating monsoon precipitation. The Asian monsoon prediction skill increases with the ENSO amplitude, although the models simulate an overly strong impact of ENSO on the monsoon. Overall, the monsoon predictive skill is lower than the ENSO skill in both modeling systems but both systems show greater predictive skill compared to persistence.

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Section: Seasonal Mean Bias and Prediction Skillsupporting

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

et al. 2012

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“…These results are in agreement with the climatological values [e.g., Joseph et al, 1994;Fasullo and Webster, 2002]. The CTRL experiment does not realistically represent the northwestward evolution of the Indian Summer Monsoon (Figures 4b and 4e), a problem that was also found in the first version of the CFS model [Yang et al, 2008].…”

Section: Journal Of Advances In Modeling Earth Systems 101002/2016mssupporting

confidence: 88%

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

Bombardi

Tawfik

Manganello

et al. 2016

J Adv Model Earth Syst

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An updated version of the Heated Condensation Framework (HCF) is implemented as a convective triggering criterion into the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). The new trigger replaces the original criteria in both the deep (Simplified Arakawa‐Schubert – SAS) and shallow (SAS based) convective schemes. The performance of the original and new triggering criteria is first compared against radiosonde observations. Then, a series of hindcasts are performed to evaluate the influence of the triggering criterion in the CFSv2 representation of summer precipitation, the diurnal cycle of precipitation, and hurricanes that made landfall. The observational analysis shows that the HCF trigger better captures the frequency of convection, where the original SAS trigger initiates convection too often. When implemented in CFSv2, the HCF trigger improves the seasonal forecast of the Indian summer monsoon rainfall, including the representation of the onset dates of the rainy season over India. On the other hand, the HCF trigger increases error in the seasonal forecast of precipitation over the eastern United States. The HCF trigger also improves the representation of the intensity of hurricanes. Moreover, the simulation of hurricanes provides insights on the mechanism whereby the HCF trigger impacts the representation of convection.

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“…Skill of the CFS model has been examined in simulating and predicting El NinoSouthern Oscillation (ENSO) variability (Wang et al 2005b), Asian-Australian/Indian monsoon (Yang et al 2008;Wang et al 2008;Pattanaik and Kumar 2010) and climatic variation in the US (Yang et al 2009). The NCEP CFS version 2 (CFSv2, http://cfs.ncep.noaa.gov/cfsv2.info/) represents a substantial change to all aspects of the forecast system including model components, data assimilation system and ensemble configuration.…”

Section: Introductionmentioning

confidence: 99%

“…The seasonal predictions of individual coupled seasonal forecast systems has been analyzed separately for various target of seasons, different time periods and regions with wide range of variables using regression and correlation analysis, composite analysis and principal component analysis (Wang et al 2005b;Saha et al 2006;Yang et al 2008Yang et al , 2009Lee et al 2010;Tompkins and Feudale 2010;Wang et al 2010;Stockdale et al 2011). However, the ECMWF and NCEP CFS seasonal forecast systems have not been compared with the same validation matrix.…”

Section: Introductionmentioning

confidence: 99%

Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

2012

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The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere-ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe.

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Simulations and Seasonal Prediction of the Asian Summer Monsoon in the NCEP Climate Forecast System

Cited by 147 publications

References 45 publications

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

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