Zong-Liang Yang The University of Texas at Austin

1. Introduction to Land Surface Modeling Zong-Liang Yang The University of Texas at Austin Prepared for the TCEQ Meeting May 24, 2006 www.geo.utexas.edu/climate

2. Why Land Surface Modeling? • An important component of the weather, climate or environmental system. • exchangesof momentum, energy, water vapor, CO2, VOC, and other trace gases between land surface and the overlying atmosphere • statesof land surface (e.g., soil moisture, soil temperature, canopy temperature, snow water equivalent) • characteristicsof land surface (e.g., roughness, albedo, emissivity, soil texture, vegetation type, cover extent, leaf area index, and seasonality) • Critical for weather, climate, hydrological, and environmental forecasts. NCAR CLM Website

3. The Development of Climate models, Past, Present and Future Late 1960s Early 1980s Mid 1990s Present day Late 2000s? Mid 1950s Atmosphere Atmosphere Atmosphere Atmosphere Atmosphere Atmosphere Land surface Land surface Land surface Land surface Land surface Ocean & sea-ice Ocean & sea-ice Ocean & sea-ice Ocean & sea-ice Sulphate aerosol Sulphate aerosol Sulphate aerosol Non-sulphate aerosol Non-sulphate aerosol Carbon cycle Carbon cycle Atmospheric chemistry Sulphur cycle model Non-sulphate aerosols Ocean & sea-ice model Off-line model development Strengthening colours denote improvements in models Land carbon cycle model Carbon cycle model Ocean carbon cycle model Atmospheric chemistry Atmospheric chemistry John Houghton

4. Integrated Environmental Modeling Framework Climate Change and Variability Remote Sensing and GIS Water Resources Applications Coupled Ocean-Atmosphere Models Air Quality Air Quality Models Mesoscale Models Soil-Vegetation-Atmosphere Transfer E Policy P Qs Hydrologic/Routing Models D Ss Qg D Sg Ig In Situ Data Water Quality and Quantity

5. Accurate Land Surface Modeling Is Critical for Seamless Suite of Forecasts Forecast Uncertainty Outlook Years Seasons Guidance Months Threats Assessments 2 Week Forecast Lead Time 1 Week Forecasts Days Watches Hours Warnings & Alert Coordination Minutes Benefits State/Local Planning Energy Health Reservoir Control Space Operation Agriculture Recreation Commerce Ecosystem Hydropower Protection of Life & Property Environment Fire Weather Flood Mitigation & Navigation Transportation Boundary Conditions Initial Conditions Paul Houser

6. Land-Atmosphere Coupling Strength Koster et al. (2004), Science

7. What Are Land Surface Processes Land surface processes function as • lower boundary conditionin Atmospheric Models • Atmospheric Boundary Layer Simulation • Climate Simulation • Numerical Weather Prediction • 4-D Data Assimilation • upper boundary conditionin Hydrological Models • Water Resources Estimation • Crop Water Use • Runoff Simulation • interfacefor coupled Atmospheric / Hydrological / Ecological Models

8. Land Surface Models (LSMs) • Computer code describing land surface processes (also called LSSs, LSPs, SVATs) • FORTRAN, C, … ... • Tens to thousands of lines • There are a huge number of LSMs (100+ examples in literature) • many are just “research models’’, local-scale oriented, with specific process emphasis • up to ~100 canopy, ~100 soil, ~100 snow, even ~100 atmosphere layers! • LSMs in GCMs and Hydrological Models are less diverse • one dimensional, with 1-2 canopy, 1-10 soil, 1-10 snow layers • three general classes • “Bucket” Models (no vegetation canopy) • “Micrometeorological” Models (detailed soil/snow/canopy processes) + Greening • “Intermediate” Models (some soil/snow/canopy features)

9. Four Basic Requirements Frequently-sampled (hourly or sub-hourly) weather “forcing data” to “drive” LSMs • precipitation (rate; coverage, large-scale/convective) • radiation (shortwave, longwave) • temperature • wind components (u, v) • specific humidity • surface pressure Initialization of state variables • soil moisture (liquid, frozen) • deep soil temperature Specification of surface characteristics • vegetation cover percent and composition (ET, BVOC…) • soil type (soil moisture & hydrology) • topography (hydrology) • albedo (solar radiation & energy balance) • roughness (turbulence & momentum exchange) • root depth (water holding capacity & hydrology) Validation of simulations of state variables and fluxes • soil moisture • sensible/latent heat fluxes • skin temperature

10. Best Known Examples • “Biosphere-Atmosphere Transfer Scheme (BATS)” • “Simple Biosphere Model (SiB)” • Community Land Model (CLM) • Noah

11. Hydrology Biogeophysics Precipitation Evaporation Interception Canopy Water Momentum Flux Wind Speed Sensible Heat Flux Latent Heat Flux Photosynthesis 0 ua Transpiration Longwave Radiation Diffuse Solar Radiation Direct Solar Radiation Throughfall Stemflow Reflected Solar Radiation Sublimation Emitted Long- wave Radiation Evaporation Infiltration Surface Runoff Absorbed Solar Radiation Snow Melt Soil Water Redistribution Soil Heat Flux Drainage Heat Transfer Snow River Flow Soil Water Surface Runoff Ground Water Lake Ocean NCAR CLM Website Community Land Model

12. Sapwood 0 500 1000 0.01 PPFD (molm-2s-1) 0 15 30 Temperature (C) g CO2g-1s-1 0 -10 25 60 Temperature (C) 0 -1 -2 Foliage Water Potential (MPa) 0 1500 3000 Vapor Pressure Deficit (Pa) 0 500 1000 Ambient CO2 (ppm) 6 6 6 4 4 4 1 2 2 2 0 0 0 Relative Rate 0 0 100 Soil Water (% saturation) 0 1 2 Foliage Nitrogen (%) Foliage Root 0.5 0.3 g CO2g-1s-1 g CO2g-1s-1 0 0 -10 25 60 -10 25 60 Temperature (C) Temperature (C) 8 Relative Rate 1 15 0 30 Temperature (C) Community Land Model Dynamic Vegetation Ecosystem Carbon Balance Vegetation Dynamics Photosynthesis Growth Respiration g CO2g-1s-1 Autotrophic Respiration g CO2g-1s-1 Litterfall Heterotrophic Respiration g CO2g-1s-1 Nutrient Uptake NCAR CLM Website

13. Noah NCEP Noah Website

14. Research Issues • Obtaining and applying relevant “pure biome” data to test or calibrate LSMs • Dealing with spatial/temporal heterogeneity • area-average parameters or tiling of land covers? • defining space-time structure of atmospheric inputs • Making best use of remote sensing data for initialization, specification and validation • Improving key processes • Snow/Frozen soil • Runoff generation/routing • “Greening”of LSMs (carbon balance and vegetation dynamics) • Urban

15. CLM Subgrid Structure Gridcell Landunits Glacier Wetland Vegetated Lake Urban Columns Soil Type 1 PFTs Keith Oleson

16. CLM Subgrid Structure Gridcell Landunits Glacier Wetland Urban Lake Vegetated Industrial Columns/PFTs Medium Density Suburban Roof Sunlit Wall Shaded Wall Pervious Impervious Canyon Floor Keith Oleson

17. Climate Science Program at UT-Austin www.geo.utexas.edu/climate • NOAA, Understanding and Simulation of the Effects of Vegetation on North American Monsoon Precipitation. • NASA/NOAA, Parameterization of Snow Cover Fraction in Climate and Weather Prediction Models. • EPA, Impacts of Climate Change and Land Cover Change on Biogenic Volatile Organic Compounds (BVOCs) Emissions in Texas. • DHS, Regional Scale Flood Modeling for the San Antonio River Basin, 3-yr Graduate Fellowship to Marla Knebl. • NSF, Including Aquifer into the Community Land Model, 3-yr Graduate Fellowship to Lindsey Gulden. [Groundwater and Runoff] • NASA, Using MODIS Data to Characterize Climate Model Land Surface Processes and the Impacts of Land Use/Cover Change on Surface Hydrological Processes.

18. Integrated Environmental Modeling Framework Climate Change and Variability Remote Sensing and GIS Water Resources Applications Coupled Ocean-Atmosphere Models Air Quality Air Quality Models Mesoscale Models Soil-Vegetation-Atmosphere Transfer E Policy P Qs Hydrologic/Routing Models D Ss Qg D Sg Ig In Situ Data Water Quality and Quantity

19. Coupling Land Surface with Other Processes NCAR CLM Website