The role of an advanced land model in seasonal dynamical downscaling for crop model application

被引:24
|
作者
Shin, D. W. [1 ]
Bellow, J. G. [1 ]
LaRow, T. E. [1 ]
Cocke, S. [1 ]
O'Brien, James J. [1 ]
机构
[1] Florida State Univ, Ctr Ocean Atmospher Predict Studies, Tallahassee, FL 32306 USA
关键词
D O I
10.1175/JAM2366.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
An advanced land model [ the National Center for Atmospheric Research (NCAR) Community Land Model, version 2 (CLM2)] is coupled to the Florida State University (FSU) regional spectral model to improve seasonal surface climate outlooks at very high spatial and temporal resolution and to examine its potential for crop yield estimation. The regional model domain is over the southeast United States and is run at 20-km resolution, roughly resolving the county level. Warm-season (March-September) simulations from the regional model coupled to the CLM2 are compared with those from the model with a simple land surface scheme (i.e., the original FSU model). In this comparison, two convective schemes are also used to evaluate their roles in simulating seasonal climate, primarily for rainfall. It is shown that the inclusion of the CLM2 produces consistently better seasonal climate scenarios of surface maximum and minimum temperatures, precipitation, and shortwave radiation, and hence provides superior inputs to a site-based crop model to simulate crop yields. The FSU regional model with the CLM2 exhibits some capability in the simulation of peanut (Arachis hypogaea L.) yields, depending upon the convective scheme employed and the site selected.
引用
收藏
页码:686 / 701
页数:16
相关论文
共 50 条
  • [1] Sensitivity of Dynamical Downscaling Seasonal Precipitation Forecasts to Convection and Land Surface Parameterization in a High-Resolution Regional Climate Model
    Li, Yuan
    Lu, Guihua
    He, Hai
    Wu, Zhiyong
    ADVANCES IN METEOROLOGY, 2019, 2019
  • [2] Using a coupled lake model with WRF for dynamical downscaling
    Mallard, Megan S.
    Nolte, Christopher G.
    Bullock, O. Russell
    Spero, Tanya L.
    Gula, Jonathan
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (12) : 7193 - 7208
  • [3] Comparison of statistical and dynamical downscaling results from the WRF model
    Le Roux, Renan
    Katurji, Marwan
    Zawar-Reza, Peyman
    Quenol, Herve
    Sturman, Andrew
    ENVIRONMENTAL MODELLING & SOFTWARE, 2018, 100 : 67 - 73
  • [4] Implications of climate model biases and downscaling on crop model simulated climate change impacts
    Cammarano, D.
    Rivington, M.
    Matthews, K. B.
    Miller, D. G.
    Bellocchi, G.
    EUROPEAN JOURNAL OF AGRONOMY, 2017, 88 : 63 - 75
  • [5] Dynamical downscaling of CSIRO-Mk3.6 seasonal forecasts over Iran with the regional climate model version 4
    Alizadeh-Choobari, Omid
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 39 (07) : 3313 - 3322
  • [6] The WOFOST simulation model of crop growth and its application for the analysis of land resources
    Savin, IY
    Ovechkin, SV
    Aleksandrova, EV
    EURASIAN SOIL SCIENCE, 1997, 30 (07) : 758 - 765
  • [7] Dynamical seasonal predictions with the COLA atmospheric model
    Shukla, J
    Paolino, DA
    Straus, DM
    De Witt, D
    Fennessy, M
    Kinter, JL
    Marx, L
    Mo, R
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2000, 126 (567) : 2265 - 2291
  • [8] A DYNAMICAL MODEL FOR INFLUENZA UNDER SEASONAL VARIABLES
    Taherian, Masomeh
    Toomanian, Megerdich
    Molaei, Mohammadreza
    THEORETICAL BIOLOGY FORUM, 2014, 107 (1-2): : 151 - 162
  • [9] Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs
    Wood, AW
    Leung, LR
    Sridhar, V
    Lettenmaier, DP
    CLIMATIC CHANGE, 2004, 62 (1-3) : 189 - 216
  • [10] Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs
    A. W. Wood
    L. R. Leung
    V. Sridhar
    D. P. Lettenmaier
    Climatic Change, 2004, 62 : 189 - 216