A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction

2011 ◽  
Vol 38 (13) ◽  
pp. n/a-n/a ◽  
Author(s):  
Xing Yuan ◽  
Eric F. Wood ◽  
Lifeng Luo ◽  
Ming Pan
Keyword(s):  
Seasonal Prediction ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System

scholarly journals A Comparison of Skill between Two Versions of the NCEP Climate Forecast System (CFS) and CPC’s Operational Short-Lead Seasonal Outlooks

2013 ◽  
Vol 28 (2) ◽  
pp. 445-462 ◽  
Author(s):  
Peitao Peng ◽  
Anthony G. Barnston ◽  
Arun Kumar
Keyword(s):  
Surface Temperature ◽  
Co2 Concentration ◽  
Seasonal Prediction ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Use Of Time ◽  
Predictive Skill ◽  
Two Generations ◽  
Decision Making Processes

Abstract Analyses of the relative prediction skills of NOAA’s Climate Forecast System versions 1 and 2 (CFSv1 and CFSv2, respectively), and the NOAA/Climate Prediction Center’s (CPC) operational seasonal outlook, are conducted over the 15-yr common period of 1995–2009. The analyses are applied to predictions of seasonal mean surface temperature and total precipitation over the conterminous United States for the shortest and most commonly used lead time of 0.5 months. The assessments include both categorical and probabilistic verification diagnostics—their seasonalities, spatial distributions, and probabilistic reliability. Attribution of skill to specific physical sources is attempted when possible. Motivations for the analyses are to document improvements in skill between two generations of NOAA’s dynamical seasonal prediction system and to inform the forecast producers, but more importantly the user community, of the skill of the CFS model now in use (CFSv2) to help guide the users’ decision-making processes. The CFSv2 model is found to deliver generally higher mean predictive skill than CFSv1. This result is strongest for surface temperature predictions, and may be related to the use of time-evolving CO2 concentration in CFSv2, in contrast to a fixed (and now outdated) concentration used in CFSv1. CFSv2, and especially CFSv1, exhibit more forecast “overconfidence” than the official seasonal outlooks, despite that the CFSv2 hindcasts have outperformed the outlooks more than half of the time. Results justify the greater weight given to CFSv2 in developing the final outlooks than given to previous dynamical input tools (e.g., CFSv1) and indicate that CFSv2 should be of greater interest to users.

scholarly journals The NCEP Climate Forecast System Version 2

2014 ◽  
Vol 27 (6) ◽  
pp. 2185-2208 ◽  
Author(s):  
Suranjana Saha ◽  
Shrinivas Moorthi ◽  
Xingren Wu ◽  
Jiande Wang ◽  
Sudhir Nadiga ◽  
...  
Keyword(s):  
Energy Use ◽  
Initial Conditions ◽  
Forecast Model ◽  
Seasonal Prediction ◽  
The United States ◽  
Climate Forecast ◽  
Seasonal Forecasts ◽  
Forecast System ◽  
Climate Forecast System ◽  
Ncep Climate Forecast System

Abstract The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period (1979–2010), which provided the initial conditions to carry out a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts over its predecessor. The CFSv2 not only provides greatly improved guidance at these time scales but also creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision making processes in areas such as water management for rivers and agriculture, transportation, energy use by utilities, wind and other sustainable energy, and seasonal prediction of the hurricane season.

scholarly journals Seasonal Prediction Skills in the CAMS-CSM Climate Forecast System

2021 ◽  
Author(s):  
Bo Liu ◽  
Jingzhi SU ◽  
Libin MA ◽  
Yanli TANG ◽  
Xinyao RONG ◽  
...  
Keyword(s):  
East Asia ◽  
Air Temperature ◽  
Lead Time ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Good Prediction ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Enso Events

Abstract The seasonal predictability in the CAMS-CSM climate forecast system is evaluated with a set of retrospective forecast experiments during the period of 1981-2019. The CAMS-CSM, which has been registered for the sixth phase of the coupled model intercomparison project (CMIP6), is an atmosphere-ocean-land-sea ice fully coupled general model. The assimilation scheme used in the forecast system is the 3-dimentional nudging, including both the atmospheric and oceanic components. The analyses mainly focus on the seasonal predictable skill of sea surface temperature, 2-m air temperature, and precipitation anomalies. The analyses revealed that the model shows a good prediction skill for the SST anomalies, especially in the tropical Pacific, such as El Niño-Southern Oscillation (ENSO) events. The anomaly correlation coefficient (ACC) score for ENSO can reach 0.75 at 6-month lead time. Furthermore, the extreme warm/cold Indian Ocean dipole (IOD) events are successfully predicted at 3- and even 6-month lead times. The whole ACC of IOD events between the observation and the prediction can reach 0.51 at 2-month lead time. There are reliable seasonal prediction skills for 2-m air temperature anomalies over most of the Northern Hemisphere, where the correlation is mainly above 0.4 at 2-month lead time, especially over the East Asia, North America and South America. However, the seasonal prediction for precipitation still faces a big challenge. The source of precipitation predictability over the East Asia can be partly related to strong ENSO events. Additionally, the anomalous anticyclone over the western North Pacific (WPAC) which connects the ENSO events and the East Asian summer monsoon (EASM) can be well predicted at 6-month lead time.

The NCEP Climate Forecast System

2006 ◽  
Vol 19 (15) ◽  
pp. 3483-3517 ◽  
Author(s):  
S. Saha ◽  
S. Nadiga ◽  
C. Thiaw ◽  
J. Wang ◽  
W. Wang ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Seasonal Prediction ◽  
Ocean Model ◽  
Climate Forecast ◽  
Seasonal Forecasts ◽  
Forecast System ◽  
Coupled Modeling ◽  
Dynamical Modeling ◽  
Climate Forecast System ◽  
Fully Coupled

Abstract The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric component of the CFS is a lower-resolution version of the Global Forecast System (GFS) that was the operational global weather prediction model at NCEP during 2003. The ocean component is the GFDL Modular Ocean Model version 3 (MOM3). There are several important improvements inherent in the new CFS relative to the previous dynamical forecast system. These include (i) the atmosphere–ocean coupling spans almost all of the globe (as opposed to the tropical Pacific only); (ii) the CFS is a fully coupled modeling system with no flux correction (as opposed to the previous uncoupled “tier-2” system, which employed multiple bias and flux corrections); and (iii) a set of fully coupled retrospective forecasts covering a 24-yr period (1981–2004), with 15 forecasts per calendar month out to nine months into the future, have been produced with the CFS. These 24 years of fully coupled retrospective forecasts are of paramount importance to the proper calibration (bias correction) of subsequent operational seasonal forecasts. They provide a meaningful a priori estimate of model skill that is critical in determining the utility of the real-time dynamical forecast in the operational framework. The retrospective dataset also provides a wealth of information for researchers to study interactive atmosphere–land–ocean processes.

scholarly journals Seasonal prediction skills in the CAMS-CSM climate forecast system

2021 ◽  
Author(s):  
Bo Liu ◽  
Jingzhi Su ◽  
Libin Ma ◽  
Yanli Tang ◽  
Xinyao Rong ◽  
...  
Keyword(s):  
Seasonal Prediction ◽  
Climate Forecast ◽  
Forecast System ◽  
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

scholarly journals The German Climate Forecast System: GCFS

2020 ◽  
Author(s):  
Kristina Fröhlich ◽  
Mikhail Dobrynin ◽  
Katharina Isensee ◽  
Claudia Gessner ◽  
Andreas Paxian ◽  
...  
Keyword(s):  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System

scholarly journals Reanalysis intercomparisons of stratospheric polar processing diagnostics

2018 ◽  
Vol 18 (18) ◽  
pp. 13547-13579 ◽  
Author(s):  
Zachary D. Lawrence ◽  
Gloria L. Manney ◽  
Krzysztof Wargan
Keyword(s):  
Interannual Variability ◽  
Winter Season ◽  
Polar Vortex ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Stratospheric Polar Vortex ◽  
Scientific Results ◽  
Environmental Prediction ◽  
Low Sensitivity

Abstract. We compare herein polar processing diagnostics derived from the four most recent “full-input” reanalysis datasets: the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2), the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). We focus on diagnostics based on temperatures and potential vorticity (PV) in the lower-to-middle stratosphere that are related to formation of polar stratospheric clouds (PSCs), chlorine activation, and the strength, size, and longevity of the stratospheric polar vortex. Polar minimum temperatures (Tmin) and the area of regions having temperatures below PSC formation thresholds (APSC) show large persistent differences between the reanalyses, especially in the Southern Hemisphere (SH), for years prior to 1999. Average absolute differences of the reanalyses from the reanalysis ensemble mean (REM) in Tmin are as large as 3 K at some levels in the SH (1.5 K in the Northern Hemisphere – NH), and absolute differences of reanalysis APSC from the REM up to 1.5 % of a hemisphere (0.75 % of a hemisphere in the NH). After 1999, the reanalyses converge toward better agreement in both hemispheres, dramatically so in the SH: average Tmin differences from the REM are generally less than 1 K in both hemispheres, and average APSC differences less than 0.3 % of a hemisphere. The comparisons of diagnostics based on isentropic PV for assessing polar vortex characteristics, including maximum PV gradients (MPVGs) and the area of the vortex in sunlight (or sunlit vortex area, SVA), show more complex behavior: SH MPVGs showed convergence toward better agreement with the REM after 1999, while NH MPVGs differences remained largely constant over time; differences in SVA remained relatively constant in both hemispheres. While the average differences from the REM are generally small for these vortex diagnostics, understanding such differences among the reanalyses is complicated by the need to use different methods to obtain vertically resolved PV for the different reanalyses. We also evaluated other winter season summary diagnostics, including the winter mean volume of air below PSC thresholds, and vortex decay dates. For the volume of air below PSC thresholds, the reanalyses generally agree best in the SH, where relatively small interannual variability has led to many winter seasons with similar polar processing potential and duration, and thus low sensitivity to differences in meteorological conditions among the reanalyses. In contrast, the large interannual variability of NH winters has given rise to many seasons with marginal conditions that are more sensitive to reanalysis differences. For vortex decay dates, larger differences are seen in the SH than in the NH; in general, the differences in decay dates among the reanalyses follow from persistent differences in their vortex areas. Our results indicate that the transition from the reanalyses assimilating Tiros Operational Vertical Sounder (TOVS) data to advanced TOVS and other data around 1998–2000 resulted in a profound improvement in the agreement of the temperature diagnostics presented (especially in the SH) and to a lesser extent the agreement of the vortex diagnostics. We present several recommendations for using reanalyses in polar processing studies, particularly related to the sensitivity to changes in data inputs and assimilation. Because of these sensitivities, we urge great caution for studies aiming to assess trends derived from reanalysis temperatures. We also argue that one of the best ways to assess the sensitivity of scientific results on polar processing is to use multiple reanalysis datasets.

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
Sign in / Sign up

Export Citation Format

Share Document