NOAA'S SECOND-GENERATION GLOBAL MEDIUM-RANGE ENSEMBLE REFORECAST DATASET

被引:276
作者
Hamill, Thomas M. [1 ]
Bates, Gary T. [2 ]
Whitaker, Jeffrey S. [1 ]
Murray, Donald R. [2 ]
Fiorino, Michael [3 ]
Galarneau, Thomas J., Jr. [4 ]
Zhu, Yuejian [5 ]
Lapenta, William [5 ]
机构
[1] NOAA, Earth Syst Res Lab, Div Phys Sci, Boulder, CO 80305 USA
[2] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA
[3] NOAA, Global Syst Div, Earth Syst Res Lab, Boulder, CO 80305 USA
[4] Natl Ctr Atmospher Res, Boulder, CO 80307 USA
[5] NOAA, Environm Modeling Ctr, Natl Ctr Environm Predict, College Pk, MD USA
关键词
QUANTITATIVE PRECIPITATION FORECASTS; AMERICAN REGIONAL REANALYSIS; DATA ASSIMILATION SYSTEM; MODEL; PREDICTION; PARAMETERIZATION; CLOUDS; INDEX; SKILL; ECMWF;
D O I
10.1175/BAMS-D-12-00014.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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 degrees grid spacing, 42 levels) for week +1 forecasts and T190L42 (approximately 3/4 degrees 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 dataset relative to the first-generation NOAA reforecast is that (i) a modern, currently operational version of the forecast model is used (the previous reforecast used a model version from 1998); (ii) a much larger set of output data has been saved, including variables relevant for precipitation, hydrologic, wind energy, solar energy, severe weather, and tropical cyclone forecasting; and (iii) the archived data are at much higher resolution. The article describes more about the reforecast configuration and provides a few examples of how this second-generation reforecast data may be used for research and a variety of weather forecast applications.
引用
收藏
页码:1553 / 1565
页数:13
相关论文
共 50 条
  • [1] Utility of Global Ensemble Forecast System (GEFS) Reforecast for Medium-Range Drought Prediction in India
    Shah, Reepal D.
    Mishra, Vimal
    JOURNAL OF HYDROMETEOROLOGY, 2016, 17 (06) : 1781 - 1800
  • [2] Medium-range multimodel ensemble combination and calibration
    Johnson, Christine
    Swinbank, Richard
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2009, 135 (640) : 777 - 794
  • [3] Development and Validation of NOAA's 20-Year Global Wave Ensemble Reforecast
    Campos, Ricardo M.
    Abdolali, Ali
    Alves, Jose-Henrique
    Masarik, Matthew
    Meixner, Jessica
    Mehra, Avichal
    Figurskey, Darin
    Banihashemi, Saeideh
    Sienkiewicz, Joseph
    Lumpkin, Rick
    WEATHER AND FORECASTING, 2024, 39 (11) : 1651 - 1672
  • [4] Skill of medium-range reforecast for summertime extraordinary Arctic Cyclones in 1986-2016
    Yamagami, Akio
    Matsueda, Mio
    Tanaka, Hiroshi L.
    POLAR SCIENCE, 2019, 20 : 107 - 116
  • [5] Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins
    Ye, J.
    He, Y.
    Pappenberger, F.
    Cloke, H. L.
    Manful, D. Y.
    Li, Z.
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2014, 140 (682) : 1615 - 1628
  • [6] Blocking Predictability in Operational Medium-Range Ensemble Forecasts
    Matsueda, Mio
    SOLA, 2009, 5 : 113 - 116
  • [7] Medium-Range Probabilistic Forecasts of Wind Power Generation and Ramps in Japan Based on a Hybrid Ensemble
    Ohba, Masamichi
    Kadokura, Shinji
    Nohara, Daisuke
    ATMOSPHERE, 2018, 9 (11):
  • [8] Skill of ensemble flood inundation forecasts at short- to medium-range timescales
    Gomez, Michael
    Sharma, Sanjib
    Reed, Seann
    Mejia, Alfonso
    JOURNAL OF HYDROLOGY, 2019, 568 : 207 - 220
  • [9] Ensemble sensitivity analysis of Greenland blocking in medium-range forecasts
    Parker, Tess
    Woollings, Tim
    Weisheimer, Antje
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2018, 144 (716) : 2358 - 2379
  • [10] The Use of Ensemble Clustering on a Multimodel Ensemble for Medium-Range Forecasting at the Weather Prediction Center
    Lamberson, William S.
    Bodner, Michael J.
    Nelson, James A.
    Sienkiewicz, Sara A.
    WEATHER AND FORECASTING, 2023, 38 (04) : 539 - 554