著者
Minghao Yang Ruiting Zuo Xin Li Liqiong Wang
出版者
Meteorological Society of Japan
雑誌
SOLA (ISSN:13496476)
巻号頁・発行日
vol.15, pp.166-171, 2019 (Released:2019-08-21)
参考文献数
40
被引用文献数
3

The Qian atmospheric forcing dataset is used to drive version 4.5 of the Community Land Model (CLM4.5) in off-line simulation tests. Based on the Global Land Evaporation Amsterdam Model (GLEAM) data, we attempt to ameliorate the canopy interception parameterization scheme in CLM4.5 by improving the empirical parameter and the physical structure. Considering that different plant functional types (PFTs) have different capacities to intercept rainfall is denoted as SEN1, and accounting for the influence of wind speed on canopy interception on the basis of SEN1 is denoted as SEN2. SEN1 shows obvious improvement in the simulated evaporation of intercepted water from vegetation canopy (Ec), not only greatly reduces the positive bias of the model to simulate Ec, especially in the equatorial region, but also significantly reduces the root mean square error (RMSE). SEN2 further improves the simulation of Ec by lowering the RMSE and increasing consistency with GLEAM data. In addition, the percentages of Ec over total evapotranspiration in both SEN1 and SEN2 are more reasonable and much closer to GLEAM data than that in CLM4.5.
著者
Minghao Yang Ruiting Zuo Liqiong Wang Xiong Chen Yanke Tan Xin Li
出版者
Meteorological Society of Japan
雑誌
SOLA (ISSN:13496476)
巻号頁・発行日
vol.14, pp.74-78, 2018 (Released:2018-06-26)
参考文献数
18
被引用文献数
3

Based on 55-yr output data from the historical runs of twelve Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) models and a NCEP (National Centers for Environmental Prediction) reanalysis, we evaluate the capability of those models to simulate the interannual variability of the winter North Atlantic storm track (WNAST). It is found that the multi-model ensemble (MME) is better than any single models in reflecting the spatial distribution of WNAST interannual variability and has the smallest root mean square error (RMSE). The strengths of the interannual variations in half of the models are universally weaker than in the NCEP reanalysis. In addition, the simulated interannual variability vary largely among these models in (55°N–65°N, 35°W–0°). MPI-ESM-LR, FGOALS-s2 and MRI-CGCM3 have relatively better abilities than other models to reflect the interannual variability of WNAST strength, longitude and latitude indices respectively. However, the interannual variability of WNAST longitude and latitude indices (strength index) are (is) overestimated (underestimated) in MME.