Cirrus cloud diagnosis using numerical weather prediction model and a comparison with observations

被引:0
|
作者
Mahalov, A. [1 ]
Lefevre, R. [2 ]
Cocks, S. [3 ]
机构
[1] Arizona State Univ, Dept Math & Stat, Dept Mech & Aerosp Engn, Ctr Environm Fluid Dynam, Tempe, AZ 85287 USA
[2] ATK, Albuquerque, NM 87110 USA
[3] 1350 Wyoming Ave SE Bldg 20200, Kirtland AFB, NM 87117 USA
关键词
upper troposphere and lower stratosphere; high resolution simulations; cirrus cloud diagnosis;
D O I
10.1117/12.812080
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Cirrus clouds in the upper troposphere and lower stratosphere (UTLS) can impact the efficiency and effectiveness of infrared directed energy (laser) applications, including laser communications systems, due to attenuation (absorption and scattering) of energy. The accurate prediction of cirrus clouds, including subvisual cirrus, is often difficult for operational numerical weather prediction (NWP) models because the models require high resolution and advanced cloud microphysics schemes. We solved the fully three-dimensional, moist, compressible, non-hydrostatic Navier-Stokes equations using a vertically-stretched adaptive grid nested within the Weather Research and Forecasting (WRF) model over a geographical region of interest. We used an adaptive time-split integration scheme for the temporal discretization. We used the Thompson cloud microphysical parameterization scheme for the cirrus cloud development. The initial conditions and boundary conditions for the WRF simulations were extracted from the European Centre for Medium Range Weather Forecasting (ECMWF) T799L91 global analyses. We ran the simulation for a domain centered on the coast of Southern California and the results are compared to meteorological satellite and radiosonde observations for selected locations.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] INITIALIZATION OF CLOUD WATER IN A NUMERICAL WEATHER PREDICTION MODEL
    KRISTJANSSON, JE
    [J]. METEOROLOGY AND ATMOSPHERIC PHYSICS, 1992, 50 (1-3) : 21 - 30
  • [2] Cloud detection using meteosat imagery and numerical weather prediction model data
    Feijt, A
    de Valk, P
    van der Veen, S
    [J]. JOURNAL OF APPLIED METEOROLOGY, 2000, 39 (07): : 1017 - 1030
  • [3] Estimating the Impact of Assimilating Cirrus Cloud-Contaminated Hyperspectral Infrared Radiances for Numerical Weather Prediction
    Marquis, Jared W.
    Dolinar, Erica K.
    Garnier, Anne
    Campbell, James R.
    Ruston, Benjamin C.
    Yang, Ping
    Zhang, Jianglong
    [J]. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2023, 40 (03) : 327 - 340
  • [4] Climatology of cloud and radiation fields in a numerical weather prediction model
    Cullather, RI
    Harshvardhan
    Campana, KA
    [J]. THEORETICAL AND APPLIED CLIMATOLOGY, 1997, 57 (1-2) : 11 - 33
  • [5] Climatology of cloud and radiation fields in a numerical weather prediction model
    R. I. Cullather
    K. A. Harshvardhan
    [J]. Theoretical and Applied Climatology, 1997, 57 : 11 - 33
  • [6] Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents
    Martin, Anne
    Weissmann, Martin
    Reitebuch, Oliver
    Rennie, Michael
    Geiss, Alexander
    Cress, Alexander
    [J]. ATMOSPHERIC MEASUREMENT TECHNIQUES, 2021, 14 (03) : 2167 - 2183
  • [7] Simulating the equivalent radar reflectivity of cirrus at 94 GHz using an ensemble model of cirrus ice crystals: a test of the Met Office global numerical weather prediction model
    Baran, Anthony. J.
    Bodas-Salcedo, Alejandro
    Cotton, Richard
    Lee, Clare
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (659) : 1547 - 1560
  • [8] CONDENSATION AND CLOUD PARAMETERIZATION STUDIES WITH A MESOSCALE NUMERICAL WEATHER PREDICTION MODEL
    SUNDQVIST, H
    BERGE, E
    KRISTJANSSON, JE
    [J]. MONTHLY WEATHER REVIEW, 1989, 117 (08) : 1641 - 1657
  • [9] Representativity of cloud-profiling radar observations for data assimilation in numerical weather prediction
    Barker, Howard W.
    Gabriel, Philip M.
    Qu, Zhipeng
    Kato, Seiji
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2021, 147 (736) : 1801 - 1822
  • [10] Representativity of cloud-profiling radar observations for data assimilation in numerical weather prediction
    Barker, Howard W.
    Gabriel, Philip M.
    Qu, Zhipeng
    Kato, Seiji
    [J]. Quarterly Journal of the Royal Meteorological Society, 2021, 147 (736): : 1801 - 1822