Research on Integrated Earth System Modeling at Global and Regional Scales

1. Research on Integrated Earth System Modeling at Global and Regional Scales L. Ruby Leung Pacific Northwest National Laboratory, Richland, WA 2nd RASM Workshop Monterey, CA, May 15 – 17, 2012

2. The needs for model coupling and new development Understand the role of biosphere-atmosphere feedbacks on droughts in the southwestern U.S. Asses the impacts of climate change in the southeastern U.S. (e.g., hurricanes) Impacts of land-atmosphere (Amazon) and atmosphere-ocean (Atlantic) interactions on the tropical Atlantic biases Develop an integrated model to represent human-earth system interactions for modeling and analysis of climate change mitigation and adaptation, with a focus on the nexus of energy, water, and land use

3. Regional Earth System Model (RESM) CESM Atmospheric conditions • Consistent representations of land processes at global and regional scales • Flexibility to model land processes using resolution or grid different from the atmospheric model • Integrate human systems in CLM • Facilitate air-sea coupling at regional scale CLM CLM Global Flux Coupler Surface fluxes CAM WRF Atmosphere and ocean boundary conditions RESM Atmospheric conditions Regional Flux Coupler ROMS POP Surface fluxes A regional earth system model is being developed using WRF, CLM, and ROMS, following the flux coupling approach used in CESM

4. Model development Developed global high resolution (0.05o) input data for CLM based on MODIS Implemented the VIC surface/subsurface runoff and groundwater parameterizations to CLM Tested grid based vs subbasin based approaches Developed a new river routing model for CLM for both grid based and subbasin based approaches (including global input data at 6 different resolutions) Developing a water management model for CLM Adding subgrid elevation classification in CLM Applied UQ to understand model sensitivity to hydrologic parameters Developing WRF-ROMS coupling through CPL7

5. A 0.05-degree input dataset for CLM

6. Comparison of new and old CLM input data Bare soil Trees Shrubs Grass Crop

7. Introducing VIC soil hydrology to CLM Infiltration excess runoff Surface- and groundwater interactions Saturation excess runoff ARNO baseflow curve Hydraulic redistribution Interactions of water movement between the root system and soil porous media

8. Change of soil moisture Diffusion term Drainage term Change of water table depth qs porosity ne(t) effective porosity Change of total soil moisture in the unsaturated zone Net water recharge to the groundwater body Dynamic representation of surface and groundwater interactions Liang et al., JGR, 2003

9. Implementation of VICGROUND to CLM A runtime option activated through the namelist

10. Simulated water budget at Tonzi Ranch

11. Global testing of CLMVIC • CLM4-SP • Forcing: Qian et al. 2004 • Land cover: current (i.e., 2000) • Simulation period: 1995-2004 • Resolution: standard one-degree (i.e., 0.9 x 1.25) • CLM-CN • Forcing: CRU-NCEP • Land cover: potential vegetation (pre-industrial) • Simulation period: 1800-1900 (by randomizing 1901-1930) • Resolution: 0.5-degree grid

12. CLM4-SP: Summer LH, 1995-2004 CLM4 CLM4VIC CLM4VIC – CLM4 CLM4VIC – CLM4, global mean

13. CLM4-CN: Summer LH CLM4CN CLM4VICCN CLM4VICCN – CLM4CN CLM4VICCN – CLM4CN global mean, stabilized

14. Motivation for a new runoff routing model Features • Consistent process representation across various scales (global, regional, local) • Easy to be coupled with water management model • Easy to be coupled with other fluxes • To provide more accurate freshwater flux to the ocean from subdaily to daily time scales • To provide a linkage between the human (e.g., surface water withdrawal, reservoir operation) and natural systems • For transport of nutrients and sediments

15. River Transport Model (RTM) in CLM 4.0 Limitations • Over-simplification of river network • Over-simplification of physical processes • Global constant channel velocity (0.35m/s) • No account for sub-grid heterogeneity • Study area divided into cells • Flow direction is determined by D8 algorithm • Cell-to-cell routing with a linear advection model

16. Model for Scale-Adaptive River Transport (MOSART) Grid-based approach Subbasin-based approach Subbasin representation preserves the natural boundaries of runoff accumulation and river system organization This hierarchical dominant river tracing method preserves the baseline high resolution hydrography (flow direction, flow length, upstream drainage area) at any coarse resolution (Wu et al. 2011)

17. Conceptualizednetwork Model for Scale-Adaptive River Transport (MOSART) Hillslope routing Grid-based approach Sub-networkrouting Subbasin-based approach Mainchannel routing • Hillslope routing to account for event dynamics and impacts of overland flow on soil erosion, nutrient loading, etc. • Sub-network routing: scale adaptive across different resolutions to reduce scale dependence • Main channel routing: explicit estimation of in-stream status (velocity, water depth, etc.)

18. Inputs and Parameters • Daily runoff generation from UW VIC at 1/16o resolution for the Columbia River Basin • Spatial delineation and network based on HydroSHEDS • DRT algorithm for grid-based representation 1/16, 1/8, ¼ and ½ degree resolutions (available globally) • ArcSWAT package for subbasin-based representation (average size ~109km2) • Manning’s roughness for hillslope and channel routing set to 0.4 and 0.05, respectively • Evaluate against monthly naturalized streamflow data at selected major stations

19. Improved streamflow simulations Large drainage area Small drainage area

20. Water Resource Management Model: Conceptual Design • For full coupling in an earth system model: • Assume no knowledge of future inflow • Use generic operating rules • Two components: • Regulation module: extraction of water at the reservoir • Storage: stores water over extended period of time • Regulation: Follows monthly operating rules for flood control, environmental flow, irrigation and hydropower • Constrained extraction: Daily partitioning of reservoir releases for irrigation water supply, other consumptive uses and environmental constraints. It includes the distribution across demanding units. • Local surface water extraction module: extracts water at the unit • Hillslope surface runoff: represent irrigation retention ponds • Unit main stem if unpounded by an upstream reservoir

21. CLM-MOSART-WRM coupling Routing + reservoir model (T- Δt ) CLM (t) Aggregated demand (t- Δt) Local surface water (t- Δt) contribution to irrigation demand (t). Remaining demand? Loop over PFTs NO Irrigated fraction found NO YES YES Generated runoff, Agg. irrigation demand Natural flow in each units; irrigation demand YES Need irrigation Aggregated supply (t) NO Extraction from main stem if not impounded. Remaining demand? CLM Routing model WRM Regulated flow; Irrigation supply at each unit Agg. irrigation supply YES Updated ET, runoff, baseflow, irrigation demand Extraction from reservoir release to complement the local supply End of loop PFTs: vegetation types

22. Data Preprocessing Create a “unit-reservoir dependency database”: - Local approach: independent tributaries, elevation constraint, constrained distance-based buffer - Global approach: elevation constraint and distance-based buffer Distribute the demand across the reservoir based on the dependency database and maximum storage capacity of each dependent dam

23. Downscaling CCSM Simulations WRF-CLM is being used to downscale CMIP5 CCSM historical, RCP4.5, and RCP8.5 simulations from 1975 - 2100

24. Uncertainty quantification framework

25. Ranks of significance of input parameters over 10 Flux Tower Sites Larger sensitivity to parameters of subsurface processes

26. Effects of Barrier Layers on TC Intensification Balaguru et al. 2012 PNAS (in revision)

27. TC intensification rate is higher by 20% for TC that passes over BL than over non-BL