耶鲁大学 - 南京信息工程大学大气环境中心. Yale-NUIST Center on Atmospheric Environment. climate simulations. By Subin. Reporter: Meihua Piao

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1 耶鲁大学 - 南京信息工程大学大气环境中心 Yale-NUIST Center on Atmospheric Environment An improved lake model for climate simulations By Subin Reporter: Meihua Piao 1

2 Outline 1.Background 2.Objective 3.Method 4.Results 5.Discussion 6.Conclusion 7.Implication 2

3 1.Background Lakes tend to have different albedo,greater subsurface heat conductance and effective heat capacity, and much lower surface roughness than surrounding land area. These properties are important for accurate prediction of climate at the regional scale in regions with large lake area,and are important in regional energy budgets. 3

4 This paper focused on the treatment of lakes in CLM4 (Community Land Model 4), the land component of the Community Earth System Model 1 (CESM1). The existing CLM4 lake model is largely untested and has a number of deficiencies,it performed poorly at all sites tested.for temperate lakes,summer surface water temperature predictions were lower than observations. 4

5 This paper developed an improved lake model in CLM4 (referred to as CLM4-VRLS) by (1) improving the treatment of snow; (2) including freezing and melting and ice physics; (3) including a sediment thermal model; (4) allowing for variable depth; (5) improving the parameterization of lake surface properties; (6) improving the treatment of mixing under ice and in deep lakes. He also corrected previous errors in eddy diffusivity, surface flux, and surface temperature calculations. 5

6 2.Objective To improve lake thermodynamics model and make it suitable for inclusion in GCMs. 6

7 3.Method 3.1 Model Description 3.2 Model Evaluation 3.3Modeled Sensitivity of Surface Fluxes and Water Temperature to Processes and dparameters 7

8 3.1Model Description Figure 1. Lake Model Schematic 8

9 1.Surface properties and parameters (1)Surface albedo a a 0.05 cos z 0.15 a 1 x) a 0 ( 1 x, x (2)Extinction coefficient η d (3)Thermal diffusivity K ed ( ) T exp( 95 T f T f s ) Eq.1 Eq.2 Eq.3 n Eq.4 9

10 (4)Friction velocity Eq.5 10

11 (5)Momentum roughness length Aerodynamically smooth flow at the surface and an established viscous sub-layer : Z 0 m u Highly turbulent flow just above the surface: (6)Reynolds number cu g * 2 * Z m Eq.6 0 Eq.7 Eq.8 (7)Fetch-limited c A B c c exp min( A, B ) 0 max 1 / 3 F g u / 2 dg u f c 11 Eq.9

12 2.Surface fluxes and diffusion solution (1) Radiation balance equation Rn=S -S +L -L (2)Conservation of energy at the lake surface Eq.10 S L H E G Eq.11 12

13 (3)Radiation transfer T T c k t z z d dz Eq.12 Eq.13 13

14 3.2Model Evaluation A:Sparkling Lake (46.01 N,89.70 W) 8970 W) B: Kossenblatter Lake (52.13 N,14.1 E) C:Valkea-Kotinen Lake (61.24 N,25.06 E) 14

15 Table 1: Simulated Lakes 15

16 3.3Model Sensitivity of Surface Fluxes and Water Temperature to Processes and Parameters 1.No heat of fusion for phase change. 2.No snow insulation. 3.No enhanced diffusion. 4.Lake L k puddling. 5.Lake depth = 50 m. 6.Lake depth = 5 m. 7.η = 1.0 m -1 8.z0m = 1 mm. 9.z0m = 1cm. 10.Unfrozen albedo = No albedo correction for melting lakes. 12.Mixing times Mixing times m fetch.

17 4.Results 17

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30 5.Discussion In order to bridge the gap between large and small lakes in GCM-scale lake models, future research should systematically investigate the relationship between mixing i strength th and lake geometry, additional research should also be undertaken to couple k-ε models into climate models. Global data on lake opacity may be more important than global data on lake depth, future work is needed to understand the relationship between lake opacity and albedo. lbd Global Glbldt data on lake lk fetch fthis less important. t 30

31 Lake opacity interact with climate change. Changes in climate and watershed properties can affect lake biology by changing gtemperature and the concentrations of dissolved nutrients and oxygen, and lake biology is a primary determinant of opacity. Modeling lake hydrology and biogeochemistry, including gwater and nutrient t input put, sothat the lake water content, dissolved nutrient and oxygen concentrations, and biological activity can be predicted. 31

32 6.Conclusion Improved lake thermodynamics model suitable for inclusion in GCMs. The model performs very well for small lakes and adequately for large lakes. Surface fluxes are most sensitive to lake snow, ice, and optical properties. 32

33 7.Implication Whether CLM4-VRLS is suitable for inclusion in Lake Taihu climate studies or not? 33

34 耶鲁大学 - 南京信息工程大学大气环境中心 Yale-NUIST Center on Atmospheric Environment 34