TY - JOUR
T1 - Evaluation of CLM4 solar radiation partitioning scheme using remote sensing and site level FPAR datasets
AU - Wang, Kai
AU - Mao, Jiafu
AU - Dickinson, Robert E.
AU - Shi, Xiaoying
AU - Post, Wilfred M.
AU - Zhu, Zaichun
AU - Myneni, Ranga B.
PY - 2013/6
Y1 - 2013/6
N2 - This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset, derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR's seasonal cycle, diurnal cycle, long-term trends, and spatial patterns. Our findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns, but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. We identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.
AB - This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset, derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR's seasonal cycle, diurnal cycle, long-term trends, and spatial patterns. Our findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns, but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. We identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.
KW - Climate modeling
KW - Evaluation
KW - Land surface
KW - Solar radiation partitioning
UR - http://www.scopus.com/inward/record.url?scp=84880448288&partnerID=8YFLogxK
U2 - 10.3390/rs5062857
DO - 10.3390/rs5062857
M3 - Article
AN - SCOPUS:84880448288
SN - 2072-4292
VL - 5
SP - 2857
EP - 2882
JO - Remote Sensing
JF - Remote Sensing
IS - 6
ER -