PREDICTABILITY OF SOUTH ASIAN MONSOON CIRCULATION IN THE NCEP CLIMATE FORECAST SYSTEM

Author(s):  
V. KRISHNAMURTHY ◽  
SHAILENDRA RAI
2008 ◽  
Vol 21 (15) ◽  
pp. 3755-3775 ◽  
Author(s):  
Song Yang ◽  
Zuqiang Zhang ◽  
Vernon E. Kousky ◽  
R. Wayne Higgins ◽  
Soo-Hyun Yoo ◽  
...  

Abstract Analysis of the retrospective ensemble predictions (hindcasts) of the NCEP Climate Forecast System (CFS) indicates that the model successfully simulates many major features of the Asian summer monsoon including the climatology and interannual variability of major precipitation centers and atmospheric circulation systems. The model captures the onset of the monsoon better than the retreat of the monsoon, and it simulates the seasonal march of monsoon rainfall over Southeast Asia more realistically than that over South Asia. The CFS predicts the major dynamical monsoon indices and monsoon precipitation patterns several months in advance. It also depicts the interactive oceanic–atmospheric processes associated with the precipitation anomalies reasonably well at different time leads. Overall, the skill of monsoon prediction by the CFS mainly comes from the impact of El Niño–Southern Oscillation (ENSO). The CFS produces weaker-than-observed large-scale monsoon circulation, due partially to the cold bias over the Asian continent. It tends to overemphasize the relationship between ENSO and the Asian monsoon, as well as the impact of ENSO on the Asian and Indo-Pacific climate. A higher-resolution version of the CFS (T126) captures the climatology and variability of the Asian monsoon more realistically than does the current resolution version (T62). The largest improvement occurs in the simulations of precipitation near the Tibetan Plateau and over the tropical Indian Ocean associated with the zonal dipole mode structure. The analysis suggests that NCEP’s next operational model may perform better in simulating and predicting the monsoon climate over Asia and the Indo-Pacific Oceans.


2013 ◽  
Vol 42 (7-8) ◽  
pp. 1925-1947 ◽  
Author(s):  
J. S. Chowdary ◽  
H. S. Chaudhari ◽  
C. Gnanaseelan ◽  
Anant Parekh ◽  
A. Suryachandra Rao ◽  
...  

2018 ◽  
Vol 33 (3) ◽  
pp. 615-640 ◽  
Author(s):  
Tan Phan-Van ◽  
Thanh Nguyen-Xuan ◽  
Hiep Van Nguyen ◽  
Patrick Laux ◽  
Ha Pham-Thanh ◽  
...  

Abstract This study investigates the ability to apply National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) products and their downscaling by using the Regional Climate Model version 4.2 (RegCM4.2) on seasonal rainfall forecasts over Vietnam. First, the CFS hindcasts (CFS_Rfc) from 1982 to 2009 are used to assess the ability of the CFS to predict the overall circulation and precipitation patterns at forecast lead times of up to 6 months. Second, the operational CFS forecasts (CFS_Ope) and its RegCM4.2 downscaling (RegCM_CFS) for the period 2012–14 are used to derive seasonal rainfall forecasts over Vietnam. The CFS_Rfc and CFS_Ope are validated against the ECMWF interim reanalysis, the Global Precipitation Climatology Centre (GPCC) analyzed rainfall, and observations from 150 meteorological stations across Vietnam. The results show that the CFS_Rfc can capture the seasonal variability of the Asian monsoon circulation and rainfall distribution. The higher-resolution RegCM_CFS product is advantageous over the raw CFS in specific climatic subregions during the transitional, dry, and rainy seasons, particularly in the northern part of Vietnam in January and in the country’s central highlands during July.


2011 ◽  
Vol 24 (1) ◽  
pp. 94-108 ◽  
Author(s):  
Hui Gao ◽  
Song Yang ◽  
Arun Kumar ◽  
Zeng-Zhen Hu ◽  
Bohua Huang ◽  
...  

Abstract The East Asian mei-yu (EAMY), which includes the mei-yu over eastern China, baiu over Japan, and changma over Korea, is an important component of the Asia summer monsoon system. The EAMY rain belt jumps northward to the Yangtze and Huaihe River valleys (in China), Japan, and Korea from mid-June to mid-July, with remarkable interannual variability. In this study, the variability and predictability of EAMY are investigated using the retrospective ensemble predictions of the NCEP Climate Forecast System (CFS). The CFS reasonably captures the centers, magnitude, northward jump, and other features of EAMY over most regions. It also reasonably simulates the interannual variations of EAMY and its main influencing factors such as the western Pacific subtropical high, the East Asian monsoon circulation, and El Niño–Southern Oscillation (ENSO). The CFS is skillful in predicting EAMY and related circulation patterns with a lead time of one month. An empirical orthogonal function analysis with maximized signal-to-noise ratio is applied to determine the most predictable patterns of EAMY. Furthermore, experiments in which the CFS is forced by observed sea surface temperature (SST) exhibit lower skill in EAMY simulation, suggesting the importance of ocean–atmosphere coupling in predicting EAMY. The CFS, which exaggerates the precipitation over the southern–southeastern hills of the Tibetan Plateau, overestimates the relationship between EAMY and tropical–subtropical atmospheric circulation due to the overly strong ENSO signals in the model, whereas the experiments forced by observed SST produce a weaker relationship. On the contrary, the CFS underestimates the link of EAMY to higher-latitude processes. An increase in the horizontal resolution of the CFS is expected to reduce some of these errors.


2013 ◽  
Vol 118 (3) ◽  
pp. 1312-1328 ◽  
Author(s):  
Xingwen Jiang ◽  
Song Yang ◽  
Yueqing Li ◽  
Arun Kumar ◽  
Wanqiu Wang ◽  
...  

2015 ◽  
Vol 143 (11) ◽  
pp. 4660-4677 ◽  
Author(s):  
Stephen G. Penny ◽  
David W. Behringer ◽  
James A. Carton ◽  
Eugenia Kalnay

Abstract Seasonal forecasting with a coupled model requires accurate initial conditions for the ocean. A hybrid data assimilation has been implemented within the National Centers for Environmental Prediction (NCEP) Global Ocean Data Assimilation System (GODAS) as a future replacement of the operational three-dimensional variational data assimilation (3DVar) method. This Hybrid-GODAS provides improved representation of model uncertainties by using a combination of dynamic and static background error covariances, and by using an ensemble forced by different realizations of atmospheric surface conditions. An observing system simulation experiment (OSSE) is presented spanning January 1991 to January 1999, with a bias imposed on the surface forcing conditions to emulate an imperfect model. The OSSE compares the 3DVar used by the NCEP Climate Forecast System (CFSv2) with the new hybrid, using simulated in situ ocean observations corresponding to those used for the NCEP Climate Forecast System Reanalysis (CFSR). The Hybrid-GODAS reduces errors for all prognostic model variables over the majority of the experiment duration, both globally and regionally. Compared to an ensemble Kalman filter (EnKF) used alone, the hybrid further reduces errors in the tropical Pacific. The hybrid eliminates growth in biases of temperature and salinity present in the EnKF and 3DVar, respectively. A preliminary reanalysis using real data shows that reductions in errors and biases are qualitatively similar to the results from the OSSE. The Hybrid-GODAS is currently being implemented as the ocean component in a prototype next-generation CFSv3, and will be used in studies by the Climate Prediction Center to evaluate impacts on ENSO prediction.


Sign in / Sign up

Export Citation Format

Share Document