NOAA's Second-Generation Global Medium-Range Ensemble Reforecast Dataset
01 Oct 2013-Bulletin of the American Meteorological Society (American Meteorological Society)-Vol. 94, Iss: 10, pp 1553-1565
TL;DR: A multidecadal ensemble reforecast dataset is available that is approximately consistent with the operational 0000 UTC cycle of the 2012 NOAA Global Ensemble Forecast System (GEFS).
Abstract: A multidecadal ensemble reforecast database is now available that is approximately consistent with the operational 0000 UTC cycle of the 2012 NOAA Global Ensemble Forecast System (GEFS) The reforecast dataset consists of an 11-member ensemble run once each day from 0000 UTC initial conditions Reforecasts are run to +16 days As with the operational 2012 GEFS, the reforecast is run at T254L42 resolution (approximately 1/2° grid spacing, 42 levels) for week +1 forecasts and T190L42 (approximately 3/4° grid spacing) for the week +2 forecasts Reforecasts were initialized with Climate Forecast System Reanalysis initial conditions, and perturbations were generated using the ensemble transform with rescaling technique Reforecast data are available from 1985 to present Reforecast datasets were previously demonstrated to be very valuable for detecting and correcting systematic errors in forecasts, especially forecasts of relatively rare events and longer-lead forecasts What is novel about this reforecast dat
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TL;DR: The skill and value of AnEn predictions are compared with forecasts from a state-of-the-science NWP ensemble and a 12–15-month-long training period of forecasts and observations.
Abstract: This study explores an analog-based method to generate an ensemble [analog ensemble (AnEn)] in which the probability distribution of the future state of the atmosphere is estimated with a set of past observations that correspond to the best analogs of a deterministic numerical weather prediction (NWP). An analog for a given location and forecast lead time is defined as a past prediction, from the same model, that has similar values for selected features of the current model forecast. The AnEn is evaluated for 0–48-h probabilistic predictions of 10-m wind speed and 2-m temperature over the contiguous United States and against observations provided by 550 surface stations, over the 23 April–31 July 2011 period. The AnEn is generated from the Environment Canada (EC) deterministic Global Environmental Multiscale (GEM) model and a 12–15-month-long training period of forecasts and observations. The skill and value of AnEn predictions are compared with forecasts from a state-of-the-science NWP ensemble s...
261 citations
Cites background from "NOAA's Second-Generation Global Med..."
...…http://journals.am etsoc.org/m w r/article-pdf/141/10/3498/4282112/m w r-d-12-00281_1.pdf by guest on 20 Septem ber 2020 centers to support successful forecast calibration (Hamill et al. 2004, 2006, 2008, 2013; HW06;Hamill andWhitaker 2007;Wilks andHamill 2007; Hagedorn et al. 2008;Wilks 2009)....
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...It is worth noting that in operational settings much longer (i.e., multiyear reforecasts; Hamill et al. 2006, 2013) training datasets may be available to further improve these forecast systems....
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TL;DR: The National Weather Service (NWS) is implementing a short-to-long-range Hydrologic Ensemble Forecast Service (HEFS) as mentioned in this paper to quantify uncertainty in hydrologic forecasts for flood risk management, water supply management, streamflow regulation, recreation planning, and ecosystem management.
Abstract: NOAA's National Weather Service (NWS) is implementing a short- to long-range Hydrologic Ensemble Forecast Service (HEFS). The HEFS addresses the need to quantify uncertainty in hydrologic forecasts for flood risk management, water supply management, streamflow regulation, recreation planning, and ecosystem management, among other applications. The HEFS extends the existing hydrologic ensemble services to include short-range forecasts, incorporate additional weather and climate information, and better quantify the major uncertainties in hydrologic forecasting. It provides, at forecast horizons ranging from 6 h to about a year, ensemble forecasts and verification products that can be tailored to users' needs. Based on separate modeling of the input and hydrologic uncertainties, the HEFS includes 1) the Meteorological Ensemble Forecast Processor, which ingests weather and climate forecasts from multiple numerical weather prediction models to produce bias-corrected forcing ensembles at the hydrologic basin sc...
215 citations
TL;DR: In this article, a parametric statistical postprocessing method is presented that transforms raw ensemble forecasts from the Global Ensemble Forecast System (GEFS) into reliable predictive probability distributions for precipitation accumulations.
Abstract: A parametric statistical postprocessing method is presented that transforms raw (and frequently biased) ensemble forecasts from the Global Ensemble Forecast System (GEFS) into reliable predictive probability distributions for precipitation accumulations. Exploratory analysis based on 12 years of reforecast data and ⅛° climatology-calibrated precipitation analyses shows that censored, shifted gamma distributions can well approximate the conditional distribution of observed precipitation accumulations given the ensemble forecasts. A nonhomogeneous regression model is set up to link the parameters of this distribution to ensemble statistics that summarize the mean and spread of predicted precipitation amounts within a certain neighborhood of the location of interest, and in addition the predicted mean of precipitable water. The proposed method is demonstrated with precipitation reforecasts over the conterminous United States using common metrics such as Brier skill scores and reliability diagrams. It...
173 citations
George Mason University1, University of Miami2, National Oceanic and Atmospheric Administration3, Florida International University4, United States Naval Research Laboratory5, Goddard Space Flight Center6, Columbia University7, Cooperative Institute for Research in Environmental Sciences8, State University of New York System9
TL;DR: The Subseasonal Experiment (SubX) as discussed by the authors is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving sub-seasonal forecasts.
Abstract: The Subseasonal Experiment (SubX) is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global m...
158 citations
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DOI•
01 Jan 2008
TL;DR: The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication.
Abstract: The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions ; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.
9,022 citations
"NOAA's Second-Generation Global Med..." refers methods in this paper
...Here, an 11-member ensemble 72-h forecast initialized at 0000 UTC 22 September 2005 for Tropical Cyclone (TC) Rita was generated using version 3.3 of the Advanced Hurricane Weather Research and Forecasting model (AHW), with 36 vertical levels up to 20 hPa (Skamarock et al. 2008)....
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TL;DR: A rapid and accurate radiative transfer model (RRTM) for climate applications has been developed and the results extensively evaluated as discussed by the authors, which is performed using the correlated-k method: the k distributions are attained directly from the LBLRTM line-byline model, which connects the absorption coefficients used by RRTM to high-resolution radiance validations done with observations.
Abstract: A rapid and accurate radiative transfer model (RRTM) for climate applications has been developed and the results extensively evaluated. The current version of RRTM calculates fluxes and cooling rates for the longwave spectral region (10–3000 cm−1) for an arbitrary clear atmosphere. The molecular species treated in the model are water vapor, carbon dioxide, ozone, methane, nitrous oxide, and the common halocarbons. The radiative transfer in RRTM is performed using the correlated-k method: the k distributions are attained directly from the LBLRTM line-by-line model, which connects the absorption coefficients used by RRTM to high-resolution radiance validations done with observations. Refined methods have been developed for treating bands containing gases with overlapping absorption, for the determination of values of the Planck function appropriate for use in the correlated-k approach, and for the inclusion of minor absorbing species in a band. The flux and cooling rate results of RRTM are linked to measurement through the use of LBLRTM, which has been substantially validated with observations. Validations of RRTM using LBLRTM have been performed for the midlatitude summer, tropical, midlatitude winter, subarctic winter, and four atmospheres from the Spectral Radiance Experiment campaign. On the basis of these validations the longwave accuracy of RRTM for any atmosphere is as follows: 0.6 W m−2 (relative to LBLRTM) for net flux in each band at all altitudes, with a total (10–3000 cm−1) error of less than 1.0 W m−2 at any altitude; 0.07 K d−1 for total cooling rate error in the troposphere and lower stratosphere, and 0.75 K d−1 in the upper stratosphere and above. Other comparisons have been performed on RRTM using LBLRTM to gauge its sensitivity to changes in the abundance of specific species, including the halocarbons and carbon dioxide. The radiative forcing due to doubling the concentration of carbon dioxide is attained with an accuracy of 0.24 W m−2, an error of less than 5%. The speed of execution of RRTM compares favorably with that of other rapid radiation models, indicating that the model is suitable for use in general circulation models.
6,861 citations
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...Two-way moving nests of 12 and 4 km are located within the 36-km domain, and the movement of these nests is determined by the TC’s motion during the previous 6 h. Specifics on the AHW configuration are as follows: WRF single-moment 6-class microphysics (Hong et al. 2004), modified Tiedtke convective parameterization (Zhang et al. 2011) on the 36- and 12-km domains (no parameterization on the 4-km domain), Yonsei University boundary layer scheme (Hong et al. 2006), Goddard shortwave scheme (Chou and Suarez 1994), Rapid Radiative Transfer Model (Mlawer et al. 1997), and Noah land surface model (Ek et al. 2003)....
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...…(Zhang et al. 2011) on the 36- and 12-km domains (no parameterization on the 4-km domain), Yonsei University boundary layer scheme (Hong et al. 2006), Goddard shortwave scheme (Chou and Suarez 1994), Rapid Radiative Transfer Model (Mlawer et al. 1997), and Noah land surface model (Ek et al. 2003)....
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TL;DR: In this article, a revised vertical diffusion algorithm with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL) is proposed for weather forecasting and climate prediction models, which improves several features compared with the Hong and Pan implementation.
Abstract: This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presenc...
5,363 citations
Additional excerpts
...…parameterization (Zhang et al. 2011) on the 36- and 12-km domains (no parameterization on the 4-km domain), Yonsei University boundary layer scheme (Hong et al. 2006), Goddard shortwave scheme (Chou and Suarez 1994), Rapid Radiative Transfer Model (Mlawer et al. 1997), and Noah land surface model…...
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TL;DR: The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010 as mentioned in this paper, which was designed and executed as a global, high-resolution coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this period.
Abstract: The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice m...
4,520 citations
"NOAA's Second-Generation Global Med..." refers methods in this paper
...Accordingly, for the angle θ defined by the arctangent of RMM1 and RMM2, we define the Indian Ocean “strong MJO” as occurring if –(π/2 + π/8) ≤ θ ≤ –π/2 + π/8, and if the amplitude (RMM1 2 + RMM2 2)1/2 is in the upper quartile of the climatology of analyzed amplitudes for this phase and for DJF. Figure 7a shows the CFSR analyzed unconditional December–February 1985–2010 blocking statistics and the blocking statistics under a strong Indian Ocean MJO 6 days prior to the analysis....
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...Daily lagged reforecasts were also generated for the NCEP Climate Forecast System (CFS) seasonal forecasts (Saha et al. 2010)....
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...This is at least in part due to greater changes in the forecast skill of the steering flow in the tropics, owing to improvements in the CFSR analyses over time....
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...Through 20 February 2011, control initial conditions were generated by the Climate Forecast System Reanalysis (CFSR) (Saha et al. 2010)....
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TL;DR: The North American Regional Reanalysis (NARR) project as mentioned in this paper uses the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output) to capture regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.
Abstract: In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improv...
3,080 citations
"NOAA's Second-Generation Global Med..." refers methods in this paper
...North American Regional Reanalysis (NARR) 24-h accumulated precipitation analysis data (Mesinger et al. 2006; Fan et al. 2006) were used both for training (cross validated by year) and verification....
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