1. Interdisciplinary Modeling for Acquatic Ecosystems 11 18 July 2005 Atmospheric Modeling Vanda Grubišić Desert Research Institute Division of Atmospheric Sciences Vanda Grubišić Desert Research Institute Division of Atmospheric Sciences

2. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems2 Atmospheric Model A component of complex ecosystem models Provides external “forcing” (e.g., precipitation, temperature, winds, relative humidity, radiation, etc.) for a variety of other constituent models In jargon of many environmental modeling disciplines often referred to as “meteorology” A component of complex ecosystem models Provides external “forcing” (e.g., precipitation, temperature, winds, relative humidity, radiation, etc.) for a variety of other constituent models In jargon of many environmental modeling disciplines often referred to as “meteorology”

3. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems3 Model vs. Computer Model Model: A mathematical representation of a process (analytical model, parameterized model - insight is a key, empirical models - regression fit) Computer (Numerical) Model: Discretized model equations numerically solved with use of computers Model: A mathematical representation of a process (analytical model, parameterized model - insight is a key, empirical models - regression fit) Computer (Numerical) Model: Discretized model equations numerically solved with use of computers

4. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems4 How sophisticated atmospheric model one needs? Dictated by the importance of atmospheric forcing to the problem at hand (e.g. Lake Tahoe clarity vs. algae growth) Always be aware of uncertainties and errors (especially if atmospheric forcing is a key input into your model!) Dictated by the importance of atmospheric forcing to the problem at hand (e.g. Lake Tahoe clarity vs. algae growth) Always be aware of uncertainties and errors (especially if atmospheric forcing is a key input into your model!)

5. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems5 Important Scales Atmospheric processes encompass a wide range of scales Spatial and Temporal ScalesExample Process –Molecular ( min) Diffusion –Microscale (2 mm - 2 km, hours) In cloud processes –Mesoscale (2 - 2000 km, Tornadoes to hours to days)Thunderstorms –Synoptic (500 - 10,000 kmWeather Systems: days to weeks) Anticyclones, Cyclones, Fronts –Planetary (> 10,000 km, > weeks)Global Circulation Atmospheric processes encompass a wide range of scales Spatial and Temporal ScalesExample Process –Molecular ( min) Diffusion –Microscale (2 mm - 2 km, hours) In cloud processes –Mesoscale (2 - 2000 km, Tornadoes to hours to days)Thunderstorms –Synoptic (500 - 10,000 kmWeather Systems: days to weeks) Anticyclones, Cyclones, Fronts –Planetary (> 10,000 km, > weeks)Global Circulation

6. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems6 What Type of Atmospheric Numerical Model to Choose? ScalesModel –Molecular ( min) Diffusion Equation –Microscale Microphysical and Cloud –Mesoscale Mesoscale (limited area) –Synoptic Weather Prediction/ Regional Climate (regional to hemispheric) –Planetary Global Circulation Model ScalesModel –Molecular ( min) Diffusion Equation –Microscale Microphysical and Cloud –Mesoscale Mesoscale (limited area) –Synoptic Weather Prediction/ Regional Climate (regional to hemispheric) –Planetary Global Circulation Model

7. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems7 What about Vertical Scale? Air is a continuously stratified fluid (density function of height) All interesting meteorological phenomena occur in the troposphere Air is a continuously stratified fluid (density function of height) All interesting meteorological phenomena occur in the troposphere

8. Interdisciplinary Modeling for Acquatic Ecosystems 88 18 July 2005 Mesoscale The most interesting phenomenology The most challenging forecasting The most demanding computationally The most interesting phenomenology The most challenging forecasting The most demanding computationally

9. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems9 SynopticMesoscale Weather Severe Weather

10. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems10 Mesoscale Non-Hydrostatic Effects Important Buoyancy and Topographic Effects Dominate Hydrostatic Equilibrium vs. Lack of It

11. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems11 Equations and Approximations Set of coupled partial differential equations describing the motion (conservation of momentum), thermodynamic state of the atmosphere (1st law of thermodynamics), and continuity equations for air (+particles+chemical spiecies) (conservation of mass)

12. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems12 Momentum Equation Lagrangian Derivative } Coriolis Force Gravity Pressure Gradient Force Diffusion Eddy Diffusion “Turbulence” Air motion vector (wind vector) Function of space and time

13. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems13 First Attempts at Atmospheric Numerical Modeling Lewis Fry Richardson, 1913-1919 experiment (Richardson 1922) Numerical solutions to a simplified set of equations obtained by human “computers” John von Neumman 1946 Numerical solutions to a (different) simplified set obtained by an electronic computer (ENIAC) Lewis Fry Richardson, 1913-1919 experiment (Richardson 1922) Numerical solutions to a simplified set of equations obtained by human “computers” John von Neumman 1946 Numerical solutions to a (different) simplified set obtained by an electronic computer (ENIAC)

14. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems14 Common Theme That Continues to Today… It is impossible to explicitly numerically resolve all scales and processes  simplifications, approximations, and parameterizations necessary even as model resolution increases (grid spacing decreases) Lack of data for verification: Density of observational networks continues to lag increases in model resolutions (due to computing technology advances) It is impossible to explicitly numerically resolve all scales and processes  simplifications, approximations, and parameterizations necessary even as model resolution increases (grid spacing decreases) Lack of data for verification: Density of observational networks continues to lag increases in model resolutions (due to computing technology advances)

15. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems15 How Mesoscale Models Work?

16. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems16 Limited Area Models Need initial and boundary conditions from a larger-scale model!

17. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems17 Grid-Point Models Resolution Horizontal and Vertical

18. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems18 Vertical Coordinate and Resolution

19. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems19 Mesoscale Models Effects of Increased Resolution Price to be Paid Several-fold increase in computational time and cost!

20. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems20 How to Increase Resolution without Making Computation Prohibitively Expansive? Answer: Domain Nesting Horizontal resolution increased by the factor of 3 for each successive nested domain (two- way nesting) Nested domains can be spawned at any time Vertical resolution (commonly) the same in all domains

21. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems21 Importance of BC Updates and Assimilation of Observations Keep Models from Veering Off into Virtual Reality

22. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems22 Parameterizations of Subgrid-Scale Processes Parameterizations: Modeling the effect of a process (emulation) rather than modeling the process itself (simulation) Why do we need parameterizations? –Processes either too small or too complex to be resolved and directly simulated –Processes not understood enough –Yet, important for obtaining accurate simulation and/or forecast Parameterizations: Modeling the effect of a process (emulation) rather than modeling the process itself (simulation) Why do we need parameterizations? –Processes either too small or too complex to be resolved and directly simulated –Processes not understood enough –Yet, important for obtaining accurate simulation and/or forecast

23. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems23 Parameterizations Near Surface ProcessesConvective Mixing

24. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems24 How are Mesoscale Models Used? Real-Time Weather Forecasting (NWS-USA, Universities-regional forecasting efforts) Research Tool –Real-data simulations (“Case and Sensitivity Studies”) –Idealized simulations (uniform wind and/or stability profiles, simplified topography, simple initial and BC, 2D,…) Real-Time Weather Forecasting (NWS-USA, Universities-regional forecasting efforts) Research Tool –Real-data simulations (“Case and Sensitivity Studies”) –Idealized simulations (uniform wind and/or stability profiles, simplified topography, simple initial and BC, 2D,…)

25. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems25 Open Questions Continuous need for high-resolution observations for model verification [mesoscale field campaigns, e.g. Terrain-induced Rotor Experiment (T-REX) 2006 in Sierra Nevada, CA] Increase in horizontal resolution does not always lead to better results [e.g., Quantitative Precipitation Forecasting, model skill worse at 4.5 and 1.5 km than at 13.5 km, Grubišić et al. (2005), Colle et al. (2002) Range of validity of parameterizations Continuous need for high-resolution observations for model verification [mesoscale field campaigns, e.g. Terrain-induced Rotor Experiment (T-REX) 2006 in Sierra Nevada, CA] Increase in horizontal resolution does not always lead to better results [e.g., Quantitative Precipitation Forecasting, model skill worse at 4.5 and 1.5 km than at 13.5 km, Grubišić et al. (2005), Colle et al. (2002) Range of validity of parameterizations

26. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems26 Resources Beyond Meteorology 101 University Corporation for Atmospheric Research (UCAR) MetEd (Meteorology Education & Training) COMET Program pages http://meted.ucar.edu http://meted.ucar.edu Some of My Favorites: Rain Gauges: Are They Really Ground Truth? How Models Produce Precipitation & Clouds Intelligent Use of Model-Derived Products Beyond Meteorology 101 University Corporation for Atmospheric Research (UCAR) MetEd (Meteorology Education & Training) COMET Program pages http://meted.ucar.edu http://meted.ucar.edu Some of My Favorites: Rain Gauges: Are They Really Ground Truth? How Models Produce Precipitation & Clouds Intelligent Use of Model-Derived Products

27. 18 July 2005 Interdisciplinary Modeling for Acquatic Ecosystems27 Resources Mesoscale Models - Large Community Models, Open Source 1) MM5 - Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model v5 http://www.mmm.ucar.edu/mm5 http://www.mmm.ucar.edu/mm5 2) COAMPS - Naval Research Laboratory's Coupled Ocean/Atmosphere Prediction System http://www.nrlmry.navy.mil/coamps-web/web/home http://www.nrlmry.navy.mil/coamps-web/web/home 3) WRF - Weather Research & Forecasting Model National Center for Atmospheric Research (NCAR), National Oceanic and Atmospheric Administration (NOAA) Forecast System Laboratory (FSL) and the National Centers for Environmental Prediction (NCEP), Air Force Weather Agency (AFWA), Naval Research Laboratory (NRL), University of Oklahoma, Federal Aviation Administration (FAA) http://www.wrf-model.org http://www.wrf-model.org Mesoscale Models - Large Community Models, Open Source 1) MM5 - Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model v5 http://www.mmm.ucar.edu/mm5 http://www.mmm.ucar.edu/mm5 2) COAMPS - Naval Research Laboratory's Coupled Ocean/Atmosphere Prediction System http://www.nrlmry.navy.mil/coamps-web/web/home http://www.nrlmry.navy.mil/coamps-web/web/home 3) WRF - Weather Research & Forecasting Model National Center for Atmospheric Research (NCAR), National Oceanic and Atmospheric Administration (NOAA) Forecast System Laboratory (FSL) and the National Centers for Environmental Prediction (NCEP), Air Force Weather Agency (AFWA), Naval Research Laboratory (NRL), University of Oklahoma, Federal Aviation Administration (FAA) http://www.wrf-model.org http://www.wrf-model.org