Central Arctic weather forecasting: Confronting the ECMWF IFS with observations from the Arctic Ocean 2018 expedition

被引:29
作者
Tjernstrom, Michael [1 ,2 ]
Svensson, Gunilla [1 ,2 ]
Magnusson, Linus [3 ]
Brooks, Ian M. [4 ]
Prytherch, John [1 ,2 ]
Vullers, Jutta [4 ]
Young, Gillian [4 ]
机构
[1] Stockholm Univ, Dept Meteorol, S-10691 Stockholm, Sweden
[2] Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden
[3] European Ctr Medium Range Weather Forecasts, Reading, Berks, England
[4] Univ Leeds, Sch Earth & Environm, Leeds, W Yorkshire, England
基金
英国自然环境研究理事会; 欧盟地平线“2020”;
关键词
Arctic boundary layer; Arctic climate; Arctic clouds; Arctic reanalysis; Arctic weather prediction; model error; model evaluation; surface energy budget; SUMMER CLOUD OCEAN; SEA-ICE; BOUNDARY-LAYER; REANALYSES; AMPLIFICATION; RADIATION;
D O I
10.1002/qj.3971
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Forecasts with the European Centre for Medium-Range Weather Forecasts' numerical weather prediction model are evaluated using an extensive set of observations from the Arctic Ocean 2018 expedition on the Swedish icebreaker Oden. The atmospheric model (Cy45r1) is similar to that used for the ERA5 reanalysis (Cy41r2). The evaluation covers 1 month, with the icebreaker moored to drifting sea ice near the North Pole; a total of 125 forecasts issued four times per day were used. Standard surface observations and 6-hourly soundings were assimilated to ensure that the initial model error is small. Model errors can be divided into two groups. First, variables related to dynamics feature errors that grow with forecast length; error spread also grows with time. Initial errors are small, facilitating a robust evaluation of the second group; thermodynamic variables. These feature fast error growth for 6-12 hr, after which errors saturates; error spread is roughly constant. Both surface and near-surface air temperatures are too warm in the model. During the summer both are typically above zero in spite of the ongoing melt; however, the warm bias increases as the surface freezes. The warm bias is due to a too warm atmosphere; errors in surface sensible heat flux transfer additional heat from the atmosphere to the surface. The lower troposphere temperature error has a distinct vertical structure: a substantial warm bias in the lowest few 100 m and a large cold bias around 1 km; this structure features a significant diurnal cycle and is tightly coupled to errors in the modelled clouds. Clouds appear too often and in a too deep layer of the lower atmosphere; the lowest clouds essentially never break up. The largest error in cloud presence is aligned with the largest cold bias at around 1 km.
引用
收藏
页码:1278 / 1299
页数:22
相关论文
共 47 条
  • [21] REANALYSES AND OBSERVATIONS What's the Difference?
    Parker, Wendy S.
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2016, 97 (09) : 1565 - +
  • [22] Portner H.O., 2019, IPCC SPECIAL REPORT
  • [23] Motion-correlated flow distortion and wave-induced biases in air-sea flux measurements from ships
    Prytherch, J.
    Yelland, M. J.
    Brooks, I. M.
    Tupman, D. J.
    Pascal, R. W.
    Moat, B. I.
    Norris, S. J.
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2015, 15 (18) : 10619 - 10629
  • [24] Direct determination of the air-sea CO2 gas transfer velocity in Arctic sea ice regions
    Prytherch, John
    Brooks, Ian M.
    Crill, Patrick M.
    Thornton, Brett F.
    Salisbury, Dominic J.
    Tjernstrom, Michael
    Anderson, Leif G.
    Geibel, Marc C.
    Humborg, Christoph
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2017, 44 (08) : 3770 - 3778
  • [25] Atmospheric sensitivity to marginal-ice-zone drag: Local and global responses
    Renfrew, Ian A.
    Elvidge, Andrew D.
    Edwards, John M.
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2019, 145 (720) : 1165 - 1179
  • [26] A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data
    Ricker, Robert
    Hendricks, Stefan
    Kaleschke, Lars
    Tian-Kunze, Xiangshan
    King, Jennifer
    Haas, Christian
    [J]. CRYOSPHERE, 2017, 11 (04) : 1607 - 1623
  • [27] Comparison of SAFNWC/MSG Satellite Cloud Type with Vaisala CL51 Ceilometer-Detected Cloud Base Layer Using the Sky Condition Algorithm and Vaisala BL-View Software
    Salek, Milan
    Szabo-Takacs, Beata
    [J]. ATMOSPHERE, 2019, 10 (06):
  • [28] Confronting Arctic Troposphere, Clouds, and Surface Energy Budget Representations in Regional Climate Models With Observations
    Sedlar, Joseph
    Tjernstrom, Michael
    Rinke, Annette
    Orr, Andrew
    Cassano, John
    Fettweis, Xavier
    Heinemann, Guenther
    Seefeldt, Mark
    Solomon, Amy
    Matthes, Heidrun
    Phillips, Tony
    Webster, Stuart
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2020, 125 (06)
  • [29] A transitioning Arctic surface energy budget: the impacts of solar zenith angle, surface albedo and cloud radiative forcing
    Sedlar, Joseph
    Tjernstrom, Michael
    Mauritsen, Thorsten
    Shupe, Matthew D.
    Brooks, Ian M.
    Persson, P. Ola G.
    Birch, Cathryn E.
    Leck, Caroline
    Sirevaag, Anders
    Nicolaus, Marcel
    [J]. CLIMATE DYNAMICS, 2011, 37 (7-8) : 1643 - 1660
  • [30] The arctic amplification debate
    Serreze, Mark C.
    Francis, Jennifer A.
    [J]. CLIMATIC CHANGE, 2006, 76 (3-4) : 241 - 264