1. Evaluation and simulation of global terrestrial latent heat flux by merging CMIP5 climate models and surface eddy covariance observations Yunjun Yao 1, Shunlin Liang 1, Xianglan Li 1 & Jiquan Chen 2 1.College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China ; 2. Geography Building 673, Department of Geography, Michigan State, Auditorium Rd, Room 206 East Lansing, MI 48824, USA Yunjun Yao’s email:yaoyunjun@126.com

2. Introduction: 1. Latent heat flux of global surface, the heat of water evaporating for the process of soil evaporation, vegetation transpiration, and evaporation from canopy intercepted precipitation, is a fundamental quantity in applications such as general circulation models (GCMs), global climatic forecasting and land surface models (LSMs) (Wang and Dickinson 2012; Wild et al. 2014; Yao et al. 2013). 2. The Coupled Model Intercomparison Project phase 5 (CMIP5) for the latest 5th Intergovernmental Panel on Climate Change (IPCC) assessment report (IPCC- AR5) has provided an opportunity for assessing global terrestrial LE variations and attributions by coupling land-atmosphere interactions processes. 3. A large number of EC observations from FLUXNET project have the potential to be used as a reference dataset to assess the accuracy of CMIP5 LE results, but a detailed comparison between CMIP5 modeled versus global EC observed LE among different land cover types is rare. 4. We evaluated LE simulations of 45 CMIP5 models and improved global terrestrial LE simulation among different land cover types by merging 7 good CMIP5 models based on BMA method and FLUXNET EC observations.

3. Data: 2. Data at eddy covariance flux tower sites A comprehensive data of LE observations collected at 240 EC flux tower sites were used in this study. These flux tower sites are located in six continents (Asia, Europe, Africa, North America, South America and Australia) and mainly cover 9 global land cover types 1. CMIP5 GCM latent heat flux simulation The LE simulations of historical experiment for the GCMs were used in this study. All LE outputs were simulated using the same initial approach, initial time, and rattled physics with ensemble member set at r1i1p1 (Taylor et al. 2012). The monthly CMIP5 GCM LE simulations with 0.56-3.75 degree spatial resolution were used in this study.

4. Method: Skillful score model: is the maximum correlation coefficient and is set to 1.0 in this study, is the correlation coefficient,is the normalized standard deviation of LE simulates over the standard deviation of the corresponding LE observations.

5. Results: Validation results shows that 45 GCMs illustrate substantial differences in monthly LE and CESM1-CAM5 has the best performance with highest predictive skill. S R2R2 RMSE

6. Results: Spatial distribution of annual global terrestrial LE averaged for 1970-2005 at spatial resolution of 1° from 7 CMIP5 GCMs. Unit: W/m2

7. Conclusion: 1. Almost all CMIP5 GCMs overestimate LE to some extent and present positive bias for all flux tower sites. Among these models, CESM1- CAM5 has the best performance and its LE simulation show higher predictive skill for different land cover types. 2. The merged LE based on seven good CMIP5 GCMs LE datasets is able to obtain spatial and inter-annual variation in LE at global scale. 3. The merged global annual terrestrial LE increased on average during 1970-2005 and we found a large difference from the previous studies in the continuous increasing without a cease after 1998 due to the different input variables.