Prediction Skill of North Pacific Variability in NCEP Climate Forecast System Version 2: Impact of ENSO and Beyond

2014 ◽  
Vol 27 (11) ◽  
pp. 4263-4272 ◽  
Author(s):  
Zeng-Zhen Hu ◽  
Arun Kumar ◽  
Bohua Huang ◽  
Jieshun Zhu ◽  
Yuanhong Guan
Keyword(s):  
North Pacific ◽  
Phase Relation ◽  
Southern Oscillation ◽  
Phase Relationship ◽  
Prediction Skill ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
The Impact ◽  
Ncep Climate Forecast System

Abstract This work examines the impact of El Niño–Southern Oscillation (ENSO) on the prediction skill of North Pacific variability (NPV) in retrospective predictions of the NCEP Climate Forecast System, version 2. It is noted that the phase relationship between ENSO and NPV at initial conditions (ICs) affects the prediction skill of NPV. For average lead times of 0–6 months, the prediction skills of sea surface temperature anomalies (SSTAs) in NPV (defined as the NPV index) increase from 0.42 to 0.63 from the cases of an out-of-phase relation between the Niño-3.4 and NPV indices in ICs to the cases of an in-phase relation. It is suggested that when ENSO and NPV are in phase in ICs, ENSO plays a constructive role in the NPV development and enhances its signals. Nevertheless, when ENSO and NPV are out of phase, some pronounced positive NPV events are still predictable. In these cases, the North Pacific is dominated by strong positive SSTAs, which may overcome the opposing influence from the tropical Pacific and display predictability.

The German Climate Forecast System 2.1: seasonal forecast performance over Europe

2021 ◽  
Author(s):  
Kristina Fröhlich ◽  
Katharina Isensee ◽  
Sascha Brandt ◽  
Sebastian Brune ◽  
Andreas Paxian ◽  
...  
Keyword(s):  
Large Scale ◽  
Atmospheric Model ◽  
Prediction Skill ◽  
Climate Forecast ◽  
Seasonal Forecasts ◽  
Max Planck ◽  
Forecast System ◽  
Climate Forecast System ◽  
Forecast Performance ◽  
The Impact

<p>In November 2020, the new version of the German Climate Forecast System, GCFS2.1, became operational at Deutscher Wetterdienst (DWD), providing new seasonal forecasts every month. The system <strong>is based</strong><strong> </strong>on the Max Planck Institute for Meteorology Earth-System Model <strong>(MPI-ESM-HR)</strong> and is developed jointly by DWD, the Max Planck Institute for Meteorology and Universität Hamburg.</p><p>In GCFS2.1, ERA5 and ORAS5 reanalyses are assimilated using atmospheric, oceanic and sea ice nudging, respectively. From the assimilation, 50-member 6-month forecast ensembles are initialized at the start of each month. Prediction skill is assessed with a 30-member 6-month hindcast ensemble covering the time period 1982-2019 for February, May, August and November start months, and 1990-2019 for the remaining start months. Both the forecast and hindcast ensembles are generated by oceanic bred vectors with additional physical perturbations applied to the upper atmospheric model layers.</p><p>Here, we investigate the performance of GCFS2.1 summer and winter forecasts over Europe. While our main focus is on the prediction of large scale patterns that control the weather regimes during these two seasons, e.g. European blockings, special emphasis is paid on the impact of the January 2021 sudden stratospheric warming (SSW) event on the performance of GCFS2.1. The inclusion of the early phases of the January 2021 SSW event in the forecast initialisation significantly changes the GCFS2.1 forecast for February 2021 European surface climate. Prediction skill of GCFS2.1 for summer European blocking events will be also compared to the previous version GCFS2.0.</p>

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

2008 ◽  
Vol 21 (15) ◽  
pp. 3755-3775 ◽  
Author(s):  
Song Yang ◽  
Zuqiang Zhang ◽  
Vernon E. Kousky ◽  
R. Wayne Higgins ◽  
Soo-Hyun Yoo ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Asian Monsoon ◽  
Asian Summer Monsoon ◽  
Monsoon Circulation ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Asian Summer ◽  
The Impact ◽  
Ncep Climate Forecast System

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.

scholarly journals Assessing Seasonal Predictability Sources and Windows of High Predictability in the Climate Forecast System, Version 2

2019 ◽  
Vol 32 (4) ◽  
pp. 1307-1326 ◽  
Author(s):  
Douglas E. Miller ◽  
Zhuo Wang
Keyword(s):  
Geopotential Height ◽  
Tropical Pacific ◽  
Arctic Sea Ice ◽  
Prediction Skill ◽  
The Arctic ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Enso Events ◽  
The Impact

The representation of ENSO and NAO are examined in the Climate Forecast System, version 2 (CFSv2), reforecasts with a focus on the physical processes related to teleconnections and predictability. CFSv2 predicts ENSO well, but an eastward shift of the tropical Pacific sea surface temperature (SST) anomalies is evident. Although it appears minor on the global scale, the shift in convection and the large-scale wave train affects the model prediction of regional climate. In contrast, NAO is predicted poorly. The anomaly correlation coefficient (ACC) between the model ensemble mean and the observation is 0.27 during 1982–2010, and the ensemble spread is large. The representation of three sources of NAO predictability—SST, the stratospheric polar vortex, and the Arctic sea ice concentration—is investigated. It is found that the link between tropical Pacific SST and NAO is not well represented in CFSv2, and that the tropospheric–stratospheric interactions are too weak, both contributing to the poor prediction of NAO. Additionally, the impact of ENSO and NAO on prediction skill of CFSv2 in boreal winter is analyzed in terms of the spatial ACC of geopotential height. Active ENSO events exhibit larger prediction skill than neutral years, especially during the ENSO+/NAO− and ENSO−/NAO+ winters. Spatial patterns of prediction skill are also examined, and larger skill of geopotential height and 2-m air temperature is found outlined by the nodes of the PNA pattern, consistent with the large signal-to-noise ratios associated with the ENSO teleconnection.

scholarly journals Variations of the East Asian Mei-Yu and Simulation and Prediction by the NCEP Climate Forecast System

2011 ◽  
Vol 24 (1) ◽  
pp. 94-108 ◽  
Author(s):  
Hui Gao ◽  
Song Yang ◽  
Arun Kumar ◽  
Zeng-Zhen Hu ◽  
Bohua Huang ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Function Analysis ◽  
East Asian ◽  
Eastern China ◽  
Monsoon Circulation ◽  
The Tibetan Plateau ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Ncep Climate Forecast System

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.

Prediction skill of monthly SST in the North Atlantic Ocean in NCEP Climate Forecast System version 2

2012 ◽  
Vol 40 (11-12) ◽  
pp. 2745-2759 ◽  
Author(s):  
Zeng-Zhen Hu ◽  
Arun Kumar ◽  
Bohua Huang ◽  
Wanqiu Wang ◽  
Jieshun Zhu ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Prediction Skill ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
The North ◽  
The North Atlantic ◽  
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
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