Observed and reanalysis cloud fraction

被引:10
作者
Clark, Joseph V. [1 ]
Walsh, John E. [1 ]
机构
[1] Univ Illinois, Dept Atmospher Sci, Urbana, IL 61821 USA
关键词
PREDICTION SCHEME; ARCTIC CLOUD; VARIABILITY; MODEL;
D O I
10.1029/2009JD013235
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Because the Arctic climate is particularly sensitive to cloud-radiative interactions, climate models must represent Arctic clouds realistically in order to capture the variations and feedbacks in high-latitude climate. Observations of clouds and radiative fluxes for the North Slope of Alaska are available from the Department of Energy's Atmospheric Radiation Measurement (ARM) program. Reanalysis models also calculate cloud and radiative variables. In this study, ARM measurements and North American Regional Reanalysis output for four midseason months are used to show that boundary layer clouds are not only the most common type of cloud observed on the North Slope but they are also a major cause for error by the reanalysis. Near-surface clouds are associated with large overestimates of the cloud fraction during the cold season and large underestimates during the warm season. These results were synthesized with other data to produce a comprehensive picture of synoptic conditions that are commonly present when the reanalysis fails to simulate the cloud fraction. When errors in the simulated cloud fraction are largest during the cold season, anomalously high pressure is observed north of the Bering Strait, with the departure being largest in magnitude and most widespread spatially in January. Large undersimulations in the summer are associated with a + 9 hPa deviation from climatology over the Arctic Ocean, a configuration that favors onshore flow from the northeast and east. More generally, large undersimulations in the summer clouds at Barrow are almost exclusively associated with onshore flow.
引用
收藏
页数:16
相关论文
共 23 条
  • [1] [Anonymous], 2005, Arctic climate impact assessment
  • [2] [Anonymous], 2005, ARCTIC CLIMATE SYSTE, DOI DOI 10.1017/CBO9780511535888
  • [3] Bayesian confidence intervals for true fractional coverage from finite transect measurements: Implications for cloud studies from space
    Astin, I
    Di Girolamo, L
    van de Poll, HM
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2001, 106 (D15): : 17303 - 17310
  • [4] A general formalism for the distribution of the total length of a geophysical parameter along a finite transect
    Astin, I
    Di Girolamo, L
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (01): : 508 - 512
  • [5] Clothiaux EE, 1999, J ATMOS OCEAN TECH, V16, P819, DOI 10.1175/1520-0426(1999)016<0819:TARMPC>2.0.CO
  • [6] 2
  • [7] Curry JA, 1996, J CLIMATE, V9, P1731, DOI 10.1175/1520-0442(1996)009<1731:OOACAR>2.0.CO
  • [8] 2
  • [9] *INT PAN CLIM CHAN, 2007, PHYS BAS CLIM CHANG
  • [10] Intrieri JM, 2004, J CLIMATE, V17, P2953, DOI 10.1175/1520-0442(2004)017<2953:CAREOD>2.0.CO