Boreal summer intraseasonal variability simulated in the NCEP climate forecast system: insights from moist static energy budget and sensitivity to convective moistening

2012 ◽  
Vol 41 (5-6) ◽  
pp. 1569-1594 ◽  
Author(s):  
K. P. Sooraj ◽  
Kyong-Hwan Seo
Keyword(s):  
Energy Budget ◽  
Intraseasonal Variability ◽  
Boreal Summer ◽  
Climate Forecast ◽  
Moist Static Energy ◽  
Forecast System ◽  
Climate Forecast System ◽  
Moist Static Energy Budget ◽  
Static Energy ◽  
Ncep Climate Forecast System

scholarly journals Improved Tropical Modes of Variability in the NCEP Climate Forecast System (Version 2) via a Stochastic Multicloud Model

2017 ◽  
Vol 74 (10) ◽  
pp. 3339-3366 ◽  
Author(s):  
B. B. Goswami ◽  
B. Khouider ◽  
R. Phani ◽  
P. Mukhopadhyay ◽  
A. J. Majda
Keyword(s):  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Climate Simulation ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Convective Systems ◽  
Modes Of Variability ◽  
Environmental Prediction ◽  
Ncep Climate Forecast System

Abstract A stochastic multicloud model (SMCM) convective parameterization, which mimics the interactions at subgrid scales of multiple cloud types, is incorporated into the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), model (CFSsmcm) in lieu of the preexisting simplified Arakawa–Schubert (SAS) cumulus scheme. A detailed analysis of the tropical intraseasonal variability (TISV) and convectively coupled equatorial waves (CCEW) in comparison with the original (control) model and with observations is presented here. The last 10 years of a 15-yr-long climate simulation are analyzed. Significant improvements are seen in the simulation of the Madden–Julian oscillation (MJO) and most of the CCEWs as well as the Indian summer monsoon (ISM) intraseasonal oscillation (MISO). These improvements appear in the form of improved morphology and physical features of these waves. This can be regarded as a validation of the central idea behind the SMCM according to which organized tropical convection is based on three cloud types, namely, the congestus, deep, and stratiform cloud decks, that interact with each other and form a building block for multiscale convective systems. An adequate accounting of the dynamical interactions of this cloud hierarchy thus constitutes an important requirement for cumulus parameterizations to succeed in representing atmospheric tropical variability. SAS fails to fulfill this requirement, which is evident in the unrealistic physical structures of the major intraseasonal modes simulated by CFSv2 as documented here.

Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

2015 ◽  
Vol 46 (9-10) ◽  
pp. 3287-3303 ◽  
Author(s):  
S. Abhik ◽  
P. Mukhopadhyay ◽  
R. P. M. Krishna ◽  
Kiran D. Salunke ◽  
Ashish R. Dhakate ◽  
...  
Keyword(s):  
High Resolution ◽  
Intraseasonal Oscillation ◽  
Boreal Summer ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Ncep Climate Forecast System

Dynamical prediction of the East Asian winter monsoon by the NCEP Climate Forecast System

2013 ◽  
Vol 118 (3) ◽  
pp. 1312-1328 ◽  
Author(s):  
Xingwen Jiang ◽  
Song Yang ◽  
Yueqing Li ◽  
Arun Kumar ◽  
Wanqiu Wang ◽  
...  
Keyword(s):  
East Asian Winter Monsoon ◽  
East Asian ◽  
Winter Monsoon ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Asian Winter Monsoon ◽  
Ncep Climate Forecast System

Summer monsoon circulation and precipitation over the tropical Indian Ocean during ENSO in the NCEP climate forecast system

2013 ◽  
Vol 42 (7-8) ◽  
pp. 1925-1947 ◽  
Author(s):  
J. S. Chowdary ◽  
H. S. Chaudhari ◽  
C. Gnanaseelan ◽  
Anant Parekh ◽  
A. Suryachandra Rao ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Summer Monsoon ◽  
Tropical Indian Ocean ◽  
Monsoon Circulation ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Ncep Climate Forecast System

scholarly journals A Hybrid Global Ocean Data Assimilation System at NCEP

2015 ◽  
Vol 143 (11) ◽  
pp. 4660-4677 ◽  
Author(s):  
Stephen G. Penny ◽  
David W. Behringer ◽  
James A. Carton ◽  
Eugenia Kalnay
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Global Ocean ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Ocean Data Assimilation ◽  
Data Assimilation System ◽  
Ncep Climate Forecast System ◽  
Assimilation System

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.

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