Emily Becker

The NCEP Climate Forecast System Version 2

AbstractThe 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 ...

The North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2...

Predictability and Forecast Skill in NMME

AbstractForecast skill and potential predictability of 2-m temperature, precipitation rate, and sea surface temperature are assessed using 29 yr of hindcast data from models included in phase 1 of the North American Multimodel Ensemble (NMME) project. Forecast skill is examined using the anomaly correlation (AC); skill of the bias-corrected ensemble means (EMs) of the individual models and of the NMME 7-model EM are verified against the observed value. Forecast skill is also assessed using the root-mean-square error. The models’ representation of the size of forecast anomalies is also studied. Predictability was considered from two angles: homogeneous, where one model is verified against a single member from its own ensemble, and heterogeneous, where a model’s EM is compared to a single member from another model. This study provides insight both into the physical predictability of the three fields and into the NMME and its contributing models.Most of the models in the NMME have fairly realistic spread, as...

Observing and Predicting the 2015/16 El Niño

AbstractThe El Nino of 2015/16 was among the strongest El Nino events observed since 1950 and took place almost two decades after the previous major event in 1997/98. Here, perspectives of the event are shared by scientists from three national meteorological or climate services that issue regular operational updates on the status and prediction of El Nino–Southern Oscillation (ENSO). Public advisories on the unfolding El Nino were issued in the first half of 2015. This was followed by significant growth in sea surface temperature (SST) anomalies, a peak during November 2015–January 2016, subsequent decay, and its demise during May 2016. The life cycle and magnitude of the 2015/16 El Nino was well predicted by most models used by national meteorological services, in contrast to the generally overexuberant model predictions made the previous year. The evolution of multiple atmospheric and oceanic measures demonstrates the rich complexity of ENSO, as a coupled ocean–atmosphere phenomenon with pronounced glob...

Understanding the Characteristics of Daily Precipitation over the United States Using the North American Regional Reanalysis

Abstract This study examines the seasonal characteristics of daily precipitation over the United States using the North American Regional Reanalysis (NARR). To help understand the physical mechanisms that contribute to changes in the characteristics of daily precipitation, vertically integrated moisture flux convergence (MFC) and precipitable water were included in the study. First, an analysis of the NARR precipitation was carried out because while observed precipitation is indirectly assimilated in the system, differences exist. The NARR mean seasonal amount is very close to that of observations throughout the year, although NARR exhibits a slight systematic bias toward more-frequent, lighter precipitation. Particularly during summer, the precipitation intensity and the probability distribution function (PDF) indicate that NARR somewhat underestimates extremes and overestimates lighter events in the eastern half of the United States. The intensity and PDF of moisture flux convergence exhibit a strong si...

Short-Term Climate Extremes: Prediction Skill and Predictability

Forecasts for extremes in short-term climate (monthly means) are examined to understand the current prediction capability and potential predictability. This study focuses on 2-m surface temperature and pre- cipitationextremes overNorthandSouthAmerica,andseasurfacetemperatureextremesinthe Nino-3.4and Atlantic hurricane main development regions, using the Climate Forecast System (CFS) global climate model, for the period of 1982-2010. The primary skill measures employed are the anomaly correlation (AC) and root-mean-square error (RMSE). The success rate of forecasts is also assessed using contingency tables. The AC, a signal-to-noise skill measure, is routinely higher for extremes in short-term climate than those when all forecasts are considered. While the RMSE for extremes also rises, especially when skill is inherently low, it is found that the signal rises faster than the noise. Permutation tests confirm that this is not simply an effect of reduced sample size. Both 2-m temperature and precipitation forecasts have higher anomaly cor- relations in the area of South America than North America; credible skill in precipitation is very low over South America and absent over North America, even for extremes. Anomaly correlations for SST are very high in the Nino-3.4 region, especially for extremes, and moderate to high in the Atlantic hurricane main development region. Prediction skill for forecast extremes is similar to skill for observed extremes. Assess- ment of the potentialpredictability under perfect-model assumptionsshowsthat predictability and prediction skill have very similar space-time dependence. While prediction skill is higher in CFS version 2 than in CFS version 1, the potential predictability is not.

Modulation of Cold-Season U.S. Daily Precipitation by the Madden–Julian Oscillation

AbstractThis study examines the characteristics of cold-season (November–March) daily precipitation over the contiguous United States during active periods of the Madden–Julian oscillation (MJO). A large response in the precipitation rate anomaly is found over the eastern United States when MJO-related enhanced tropical convection is moving through the far western to central Pacific (conventionally known as phases 5, 6, and 7 of the MJO). Positive anomalies occur in the region of the eastern Mississippi River basin, and negative anomalies occur in the Southeast. The relative stability of this pattern throughout the three phases suggests that they can be considered together. During phases 5–7, the central United States has a daily precipitation rate between 110% and 150% of normal, while the precipitation rate over much of Florida is less than 70% of normal. Much of the lower Mississippi River basin region receives somewhat more frequent daily precipitation during MJO phases 5–7, but a greater increase is ...

The Diurnal Cycle of Precipitation over the North American Monsoon Region during the NAME 2004 Field Campaign

Abstract The structure of the diurnal cycle of warm-season precipitation and its associated fields during the North American monsoon are examined for the core monsoon region and for the southwestern United States, using a diverse set of observations, analyses, and forecasts from the North American Monsoon Experiment field campaign of 2004. Included are rain gauge and satellite estimates of precipitation, Eta Model forecasts, and the North American Regional Reanalysis (NARR). Daily rain rates are of about the same magnitude in all datasets with the exception of the Climate Prediction Center (CPC) Morphing (CMORPH) technique, which exhibits markedly higher precipitation values. The diurnal cycle of precipitation within the core region occurs earlier in the day at higher topographic elevations, evolving with a westward shift of the maximum. This shift appears in the observations, reanalysis, and, while less pronounced, in the model forecasts. Examination of some of the fields associated with this cycle, incl...

NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded their operational CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR), and the purpose of this dataset is to extend CFSR. The 6-hourly atmospheric, oceanic and land surface analyzed products and forecasts, available at 0.2, 0.5, 1.0, and 2.5 degree horizontal resolutions, are archived here beginning with January 1, 2011 as an extension of CFSR. The RDA is not archiving any of the CFS seasonal forecasts. For more information about CFS, please see http://cfs.ncep.noaa.gov/ [http://cfs.ncep.noaa.gov/].

ENSO Precipitation and Temperature Forecasts in the North American Multimodel Ensemble: Composite Analysis and Validation

AbstractIn this study, precipitation and temperature forecasts during El Nino–Southern Oscillation (ENSO) events are examined in six models in the North American Multimodel Ensemble (NMME), including the CFSv2, CanCM3, CanCM4, the Forecast-Oriented Low Ocean Resolution (FLOR) version of GFDL CM2.5, GEOS-5, and CCSM4 models, by comparing the model-based ENSO composites to the observed. The composite analysis is conducted using the 1982–2010 hindcasts for each of the six models with selected ENSO episodes based on the seasonal oceanic Nino index just prior to the date the forecasts were initiated. Two types of composites are constructed over the North American continent: one based on mean precipitation and temperature anomalies and the other based on their probability of occurrence in a tercile-based system. The composites apply to monthly mean conditions in November, December, January, February, and March as well as to the 5-month aggregates representing the winter conditions. For anomaly composites, the a...