Verification of global radiation fluxes forecasted by numerical weather prediction model AROME for Hungary

被引:0
|
作者
Toth, Zoltan [1 ]
Nagy, Zoltan [1 ]
Szintai, Balazs [2 ]
机构
[1] Hungarian Meteorol Serv, Marczell Gyorgy Main Observ, Gilice Ter 39, H-1181 Budapest, Hungary
[2] Hungarian Meteorol Serv, Kitaibel P U 1, H-1024 Budapest, Hungary
来源
IDOJARAS | 2017年 / 121卷 / 02期
关键词
verification; solar radiation; global radiation; observed data; radiative transmission of the atmosphere; optical depth; METEOROLOGICAL SERVICE;
D O I
暂无
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Global radiation output fluxes predicted by numerical weather forecast model AROME were verified by using measured high accuracy global radiation data from the 19 most reliable network stations of the Hungarian Meteorological Service. Three suitably-selected months (April, June, August) from 2013 were used for the study. Differences between observed and forecasted values were analyzed separately for all cases, overcast cases, and cloudless (clear-sky) cases. It was found that AROME performs well for clear cases, and its goodness decreases as cloudiness increases. For cloudless cases, using aerosol optical depth, graybody optical depth, and relative global radiation to represent radiative transmission condition of the atmosphere, it was found that AROME overestimates atmospheric radiation transmission for cases of high turbidity and underestimates it for very clear conditions. It means that radiation transmission scale of the atmosphere produced by the model is more narrow than that of true atmosphere.
引用
收藏
页码:189 / 208
页数:20
相关论文
共 50 条
  • [1] Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
    Magnaldo, Marie-Adele
    Libois, Quentin
    Riette, Sebastien
    Lac, Christine
    [J]. GEOSCIENTIFIC MODEL DEVELOPMENT, 2024, 17 (03) : 1091 - 1109
  • [2] Recent developments in the data assimilation of AROME/HU numerical weather prediction model
    Toth, Helga
    Homonnai, Viktoria
    Mile, Mate
    Varkonyi, Aniko
    Kocsis, Zsofia
    Szanyi, Kristof
    Toth, Gabriella
    Szintai, Balazs
    Szepszo, Gabriella
    [J]. IDOJARAS, 2021, 125 (04): : 521 - 553
  • [3] Verification of GRAPES unified global and regional numerical weather prediction model dynamic core
    Yang XueSheng
    Hu JiangLin
    Chen DeHui
    Zhang HongLiang
    Shen XueShun
    Chen JiaBin
    Ji LiRen
    [J]. CHINESE SCIENCE BULLETIN, 2008, 53 (22): : 3458 - 3464
  • [4] Verification of GRAPES unified global and regional numerical weather prediction model dynamic core
    YANG XueSheng1
    2 National Meteorological Center
    3 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics
    [J]. Science Bulletin, 2008, (22) : 3458 - 3464
  • [5] Antarctic Verification of the Australian Numerical Weather Prediction Model
    Schroeter, Benjamin J. E.
    Reid, Phil
    Bindoff, Nathaniel L.
    Michael, Kelvin
    [J]. WEATHER AND FORECASTING, 2019, 34 (04) : 1081 - 1096
  • [6] Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation
    Voyant, Cyril
    Muselli, Marc
    Paoli, Christophe
    Nivet, Marie-Laure
    [J]. ENERGY, 2012, 39 (01) : 341 - 355
  • [7] A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model
    Sébastien Riette
    Christine Lac
    [J]. Boundary-Layer Meteorology, 2016, 160 : 269 - 297
  • [8] A global numerical weather prediction model with variable resolution
    Hardiker, V
    [J]. MONTHLY WEATHER REVIEW, 1997, 125 (01) : 59 - 73
  • [9] Generalized inversion of a global numerical weather prediction model
    Bennett, AF
    Chua, BS
    Leslie, LM
    [J]. METEOROLOGY AND ATMOSPHERIC PHYSICS, 1996, 60 (1-3) : 165 - 178
  • [10] Preparing the assimilation of the future MTG-IRS sounder into the mesoscale numerical weather prediction AROME model
    Coopmann, O.
    Fourrie, N.
    Chambon, P.
    Vidot, J.
    Brousseau, P.
    Martet, M.
    Birman, C.
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2023, 149 (757) : 3110 - 3134