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Develop a moist physics scheme that accounts for variability in global cloud systems to improve short-range cloud forecasts for operational and tactical planning.
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Moist Physics Development for the NRL Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) Jerome M. Schmidt Naval Research Laboratory
Shuttle-based Lidar Observations Motivation: The Navy has a need for accurate short-range cloud forecasts to support operational and tactical planning at their central and regional forecast centers Challenge: Develop a moist physics scheme(s) that reliably accounts for the inherent variability in global cloud systems Long-term Goal: Develop a more advanced linkage between the moist physics, numerics (advection), and other particle size-dependent physical processes (mixing, radiative transfer, and aerosol prediction) for use in high resolution research and forecasting applications - 10 km -5 km
Model Description (COAMPS) • Features: Globally Relocatable User-Defined Grid Resolution and Dimensions Idealized and Real-data Simulations Suitable for Central Site (FNMOC) and On-Scene (TAMS-RT) Applications Full Atmosphere-Wave-Ocean Coupling (In Progress) Applicable to Distributed Shared Memory Architecture Concurrent Version System (CVS) Make (SGI, ALPHA, CRAY, IBM, SUN, HP)
Model Description (COAMPS) Dynamics, Numerics: Nonhydrostatic, Compressible Equations (Klemp and Wilhelmson 1978) Scheme C grid(Arakawa and Lamb, 1974) Sigma-z Vertical Coordinate(Gal-Chen and Somerville, 1975) Multiple Nested Grid Option Centered leap-frog time integration Distributed/shared memory architecture (NRL/LLNL,2000) Physics: Level 2.5 TKE Closure(Mellor and Yamada 1982) Surface Layer(Louis 1979) Surface Energy Budget(Deardorff 1978) Explicit Moist Physics(Rutledge and Hobbs 1983) Convective Parameterization(Kain and Fritsch 1990) Radiation(Harshvardhan et al. 1987)
Model Description (COAMPS) • Complex Data Quality Control • Analysis: Multivariate Optimum Interpolation (MVOI) of Heights and Winds Univariate Analyses of Temperature and Moisture NAVDAS (NRL Atmospheric Variational Data Assimilation System, 2001) • Initialization: NOGAPS First Guess and lateral B.C.’s(Cold Start) COAMPS First Guess and NOGAPS B.C.’s (Data Assimilation) Terrain (100m and 1km), Land Table (400m), Vegetation (1 km) - NIMAdata sets (DTED1 and DTED0) Real-timeSST’s Optimal Thermal Interpolation System (OTIS)
Analysis and Verification Methods 81 km 36 km 27 km 12 km E-Th Scores RMS Statistics Idealized and Case Study Analyses Term by Term Budget Analyses Sublimation Deposition
COAMPS Grid Spacing RMS STATISTICS Validation within the Mediterranean 27 km area (Tau 12) 1 Oct 1998-31 Dec 1999 Pressure (mb) (Figure Courtesy of Jason Nachamkin, Rich Hodur, and Sue Chen)
COAMPS Grid Spacing BIAS STATISTICS Validatation within the Mediterranean 27 km area (Tau 12) 1 Oct 1998-31 Dec 1999 Pressure (mb) 81 km 81 km 81 km 12 km 12 km 12 km 81 km 36 km 27 km 12 km (Figure Courtesy of Jason Nachamkin, Rich Hodur, and Sue Chen)
High-Resolution Mesoscale Prediction/Validation QPF Scores: Rain Analysis (against RFC) July, 1999 31 Aug – 02 Oct, 1999 (3 tropical cyclones made landfall over CONUS) E-Th Scores E-Th Scores (mm/day) (mm/day) Bias Scores Bias Scores (mm/day) (mm/day) The higher QPF scores in September is associated with tropical cyclones, in contrast to July when convection dominated (Courtesy of Jim Doyle and Chi-Sann Liou)
COAMPS Moist Physics Numerical Treatment: Advection: Leapfrog Forward/Upstream technique with time splitting for terminal velocity terms Subgrid Scale Mixing: Solved Implicitly Horizontal Diffusion: 4th order on interior points Source Terms: Rutledge and Hobbs (1983)
Features of the Rutledge and Hobbs (1983) Microphysics Scheme in COAMPS Complexity:Bulk scheme with single moment prediction on mixing ratio (vapor, cloud water, rain, pristine ice, snow) • Autoconversion:Kessler (1969) • Primary ice nucleation:Fletcher (1962) • Particle size spectra:Marshall and Palmer (1948) • Adjustment to saturation: Sequential adjustment to initial Temperature and vapor profiles • Original scheme lacked homogeneous freezing, ice multiplication mechanisms, CCN, graupel, drizzle, hail, aggregrates, and rain to ice conversion
Rutledge and Hobbs (1983) Pristine Ice Phase Nucleation Budget Analysis probe1 Sublimation probe1 10 Adjust T,q Deposition Deposition/ Sublimation probe2 Height (km) 5 probe2 Adjust T,q -.0016 0 .0018 Other processes
Idealized Orographic Structure(Pristine Ice: RH83) Pristine Ice and Temperature -30 C -15 C Height 0 C 3600 s 175 km Internal assumptions may lead to clustering of ceilings along specific isotherms
Turbulence Closure 24 hour forecast Valid 0000 UTC 12/28/97 24 hour forecast Valid 0000 UTC 12/28/97 Max .9 g/kg Max .3 g/kg Low-level Cloud Water (g/kg)
Turbulence Closure TAMS-RT Settings (MY82):
Turbulence Closure TKE Equation: Shear Production: Dissipation Term: Buoyancy Production Term:
Persistence of shallow cloud layers near the top of the ABL W- Level Mass Level . k Z after averaging Cloud layer k+1 Hypothetical Atmospheric profiles on mass levels Depending on the thermodynamic variable, the model may or may not see the instability due to averaging across the grid stagger and “variable switching” between clear and cloudy regions
Adjustments to COAMPS Bulk MicrophysicsUnder Development at NRL • Modified Adjustment to Saturation Scheme: Implicit solution for T,q (Soong and Ogura, 1974) Normalized microphysical rates • Modified ice nucleation (Meyers et al. 1992; Hobbs and Rangno, 1985; Hallet and Mossop, 1974) • Allow nonzero fall speed for pristine ice and homogeneous freezing • Implemented various autoconversion schemes • Adapted the two-moment Khairoutdinov and Kogan (2000) drizzle parameterization (originally implemented by Dave Mechem) • Implemented the RH84 graupel scheme • Modified the turbulence closure for mixed-phase clouds • Implementing and testing a Hybrid time scheme • Implementing and testing a forward positive definite advection scheme • Developing a full two-moment mixed-phase microphysics scheme (Reisner et al., 1998; Meyers et al., 1997; KK 2000 ) • Coupling of cloud microphysics with aerosol model(s)
Future Plans NRL BASE NAAPS Data (Westphal) • Continue development of a hybrid • forward time scheme for COAMPS 3 • Continue to test and improve the • mixed-phase mixing algorithm • Upgrade to more advanced • microphysical schemes • Participate in relevant microphysical field programs • Ultimately couple spatially and temporally varying aerosol distributions with the cloud microphysical scheme(s) Moving Nest Coupled Aerosol and Moist Physics