Coupling a New Version of the Common Land Model (CoLM) to the Global/Regional Assimilation and Prediction System (GRAPES): Implementation, Experiment, and Preliminary Evaluation

Land surface processes can significantly influence weather and climate. The Common Land Model version 2005 (CoLM2005) has been coupled to the Global Forecast System of the Global/Regional Assimilation and Prediction System (GRAPES_GFS), which is independently developed by the China Meteorological Administration. Since a new version of CoLM has been developed (CoLM2014) with updated soil basic data and parts of hydrological processes, we coupled CoLM2014 with GRAPES_GFS to investigate whether the land surface model can help to improve the prediction skill of the weather forecast model. The forecast results were evaluated against global validation datasets at different forecasting lengths and over various regions. The results demonstrate that GRAPES_GFS coupled with CoLM2005 and CoLM2014 can both well reproduce the spatial patterns and magnitude of atmospheric variables, and the effective predictable lengths of time are up to 3 days on the global scale and even up to 6 days on regional scales. Moreover, the GRAPES_GFS coupled with CoLM2014 outperforms the original one in predicting atmospheric variables. In addition, GRAPES_GFS coupled with both versions of CoLM reproduce acceptably accurate spatial distribution and magnitude of land variables. GRAPES_GFS coupled with CoLM2014 significantly improves the forecast of land surface state variables compared to the one coupled with CoLM2005, and the improvement signal is more notable than that in atmospheric variables. Overall, this study shows that CoLM is suitable for coupling with GRAPES_GFS, and the improvement of the land surface model in a weather forecast model can significantly improve the prediction skill of both atmospheric and land variables.

Multi-column modelling of lake Geneva for climate applications

The interaction between large inland water bodies and the atmosphere impacts the evolution of regional weather and climate, which in turn affects the lake dynamics, thermodynamics, ice-formation, and, therefore, ecosystems. Over the last decades, various approaches have been used to model lake thermodynamics and dynamics in standalone mode or coupled to numerical atmospheric models. We assess a turbulence-closure \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k-\epsilon$$\end{document}k-ϵ multi-column lake model in standalone mode as a computationally-efficient alternative to a full three-dimensional hydrodynamic model in the case of Lake Geneva. While it struggles to reproduce some short-term features, the multi-column model reasonably reproduces the seasonal mean of the thermal horizontal and vertical structures governing heat and mass exchanges between the lake surface and the lower atmosphere (stratified period, thermocline depth, stability of the water column). As it requires typically two orders of magnitude less computational ressources, it may allow a two-way coupling with a RCM on timescales or spatial resolutions where full 3D lake models are too demanding.

Intra-Annual and Interannual Dynamics of Evaporation Over Western Lake Erie

Evaporation (E) is a critical component of the water and energy budget in lake systems yet is challenging to quantify directly and continuously. We examined the magnitude and changes of E and its drivers over Lake Erie-the shallowest and most southern lake of the Laurentian Great Lakes. We deployed two eddy-covariance tower sites in the western Lake Erie Basin-one located nearshore (CB) and one offshore (LI)-from September 2011 through May 2016. Monthly E varied from 5 to 120 mm, with maximum E occurring in August-October. The annual E was 635 ± 42 (±SD) mm at CB and 604 ± 32 mm at LI. Mean winter (October-March) E was 189 ± 61 mm at CB and 178 ± 25 mm at LI, accounting for 29.8% and 29.4% of annual E. Mean daily E was 1.8 mm during the coldest month (January) and 7.4 mm in the warmest month (July). Monthly E exhibited a strong positive linear relationship to the product of wind speed and vapor pressure deficit. Pronounced seasonal patterns in surface energy fluxes were observed with a 2-month lag in E from R n, due to the lake's heat storage. This lag was shorter than reports regarding other Great Lakes. Difference in E between the offshore and nearshore sites reflected within-lake spatial heterogeneity, likely attributable to climatic and bathymetric differences between them. These findings suggest that predictive models need to consider lake-specific heat storage and spatial heterogeneity in order to accurately simulate lake E and its seasonal dynamics.

Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau

The ability of FLake, WRF-Lake, and CoLM-Lake models in simulating the thermal features of Lake Nam Co in Central Tibetan Plateau has been evaluated in this study. All the three models with default settings exhibited distinct errors in the simulated vertical temperature profile. Then model calibration was conducted by adjusting three (four) key parameters within FLake and CoLM-Lake (WRF-Lake) in a series of sensitive experiments. Results showed that each model's performance is sensitive to the key parameters and becomes much better when adjusting all the key parameters relative to tuning single parameter. Overall, setting the temperature of maximum water density to 1.1 °C instead of 4 °C in the three models consistently leads to improved vertical thermal structure simulation during cold seasons; reducing the light extinction coefficient in FLake results in much deeper mixed layer and warmer thermocline during warm seasons in better agreement with the observation. The vertical thermal structure can be clearly improved by decreasing the light extinction coefficient and increasing the turbulent mixing in WRF-Lake and CoLM-Lake during warm seasons. Meanwhile, the modeled water temperature profile in warm seasons can be significantly improved by further replacing the constant surface roughness lengths by a parameterized scheme in WRF-Lake. Further intercomparison indicates that among the three calibrated models, FLake (WRF-Lake) performs the best to simulate the temporal evolution and intensity of temperature in the layers shallower (deeper) than 10 m, while WRF-Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths.

Modeling surface energy fluxes and thermal dynamics of a seasonally ice-covered hydroelectric reservoir

The thermal dynamics of human created northern reservoirs (e.g., water temperatures and ice cover dynamics) influence carbon processing and air-water gas exchange. Here, we developed a process-based one-dimensional model (Snow, Ice, WAater, and Sediment: SIWAS) to simulate a full year's surface energy fluxes and thermal dynamics for a moderately large (>500km(2)) boreal hydroelectric reservoir in northern Quebec, Canada. There is a lack of climate and weather data for most of the Canadian boreal so we designed SIWAS with a minimum of inputs and with a daily time step. The modeled surface energy fluxes were consistent with six years of observations from eddy covariance measurements taken in the middle of the reservoir. The simulated water temperature profiles agreed well with observations from over 100 sites across the reservoir. The model successfully captured the observed annual trend of ice cover timing, although the model overestimated the length of ice cover period (15days). Sensitivity analysis revealed that air temperature significantly affects the ice cover duration, water and sediment temperatures, but that dissolved organic carbon concentrations have little effect on the heat fluxes, and water and sediment temperatures. We conclude that the SIWAS model is capable of simulating surface energy fluxes and thermal dynamics for boreal reservoirs in regions where high temporal resolution climate data are not available. SIWAS is suitable for integration into biogeochemical models for simulating a reservoir's carbon cycle.

Lake-Atmosphere Feedbacks Associated with Paleolakes Bonneville and Lahontan

A high-resolution, regional climate model nested within a general circulation model was used to study the interactions between the atmosphere and the large Pleistocene lakes in the Great Basin of the United States. Simulations for January and July 18,000 years ago indicate that moisture provided by synoptic-scale atmospheric circulation features was the primary component of the hydrologic budgets of Lakes Lahontan and Bonneville. In addition, lake-generated precipitation was a substantial component of the hydrologic budget of Lake Bonneville at that time. This local lake-atmosphere interaction may help explain differences in the relative sizes of these lakes 18,000 years ago.