Current issues in GFS moist physics Hua-Lu Pan, Stephen Lord, and Bill Lapenta.

Slides:



Advertisements
Similar presentations
Introduction Irina Surface layer and surface fluxes Anton
Advertisements

1 Numerical Weather Prediction Parameterization of diabatic processes Convection III The ECMWF convection scheme Christian Jakob and Peter Bechtold.
Numerical Weather Prediction Parametrization of Diabatic Processes Cloud Parametrization 2: Cloud Cover Richard Forbes and Adrian Tompkins
What’s quasi-equilibrium all about?
Moisture Transport in Baroclinic Waves Ian Boutle a, Stephen Belcher a, Bob Plant a Bob Beare b, Andy Brown c 24 April 2014.
Hirlam Physics Developments Sander Tijm Hirlam Project leader for physics.
Simulating cloud-microphysical processes in CRCM5 Ping Du, Éric Girard, Jean-Pierre Blanchet.
Evaluation of HARMONIE using a single column model in the KNMI
Clouds and Climate A. Pier Siebesma KNMI What are clouds? How do they form? Cloud climatology Clouds and Radiation Clouds in Climate models Cloud Climate.
Parameterization of convective momentum transport and energy conservation in GCMs N. McFarlane Canadian Centre for Climate Modelling and Analysis (CCCma.
The Problem of Parameterization in Numerical Models METEO 6030 Xuanli Li University of Utah Department of Meteorology Spring 2005.
TRMM Tropical Rainfall Measurement (Mission). Why TRMM? n Tropical Rainfall Measuring Mission (TRMM) is a joint US-Japan study initiated in 1997 to study.
WRF Physics Options Jimy Dudhia. diff_opt=1 2 nd order diffusion on model levels Constant coefficients (khdif and kvdif) km_opt ignored.
Simulation of Cloud Droplets in Parameterized Shallow Cumulus During RICO and ICARTT Knut von Salzen 1, Richard Leaitch 2, Nicole Shantz 3, Jonathan Abbatt.
Climate modeling Current state of climate knowledge – What does the historical data (temperature, CO 2, etc) tell us – What are trends in the current observational.
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology The Effect of Turbulence on Cloud Microstructure,
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 1 Joao Teixeira, Brian.
Geophysical Modelling: Climate Modelling How advection, diffusion, choice of grids, timesteps etc are defined in state of the art models.
Modeling Clouds and Climate: A computational challenge Stephan de Roode Clouds, Climate & Air Quality Multi-Scale Physics (MSP), Faculty of Applied Sciences.
Air Masses: Type, Modification, and Associated weather ENVI1400: Lecture 5.
GFS Deep and Shallow Cumulus Convection Schemes
The scheme: A short intro Some relevant case results Why a negative feedback? EDMF-DualM results for the CFMIP-GCSS intercomparison case: Impacts of a.
4. Models of the climate system. Earth’s Climate System Sun IceOceanLand Sub-surface Earth Atmosphere Climate model components.
The Hurricane Weather Research & Forecasting (HWRF) Prediction System Next generation non-hydrostatic weather research and hurricane prediction system.
GardeGarde Designing unified convection parameterizations: two proposals related to equation sets and entrainment. Jean-Marcel Piriou, Météo-France. GCSS.
1 Numerical Weather Prediction Parameterization of diabatic processes Convection III The ECMWF convection scheme Christian Jakob and Peter Bechtold.
Mesoscale Modeling Review the tutorial at: –In class.
29th EWGLAM meeting, Dubrovnik, October 2007 ALARO Physics developments Neva Pristov LACE Working group for physics.
Jerold Herwehe 1, Kiran Alapaty 1, Chris Nolte 1, Russ Bullock 1, Tanya Otte 1, Megan Mallard 1, Jimy Dudhia 2, and Jack Kain 3 1 Atmospheric Modeling.
Atmospheric TU Delft Stephan de Roode, Harm Jonker clouds, climate and weather air quality in the urban environmentenergy.
Unit 4 Lesson 5 Weather and Climate S8.D
Condensation. Atmospheric moisture has its most direct influence on land only when it is in its condensed form. Condensation is the direct cause of precipitation.
Can we use a statistical cloud scheme coupled to convection and moist turbulence parameterisations to simulate all cloud types? Colin Jones CRCM/UQAM
CONVECTIVE PARAMETERIZATION For the Lesson: Precipitation Processes December 1998.
Predictability of Seasonal Prediction Perfect prediction Theoretical limit (measured by perfect model correlation) Actual predictability (from DEMETER)
Weather Your Name. What is Weather? Insolation Atmosphere.
Convective Parameterization Options
Presentation Slides for Chapter 1 of Fundamentals of Atmospheric Modeling 2 nd Edition Mark Z. Jacobson Department of Civil & Environmental Engineering.
Case Study Example 29 August 2008 From the Cloud Radar Perspective 1)Low-level mixed- phase stratocumulus (ice falling from liquid cloud layer) 2)Brief.
Condensation in the Atmosphere The atmosphere contains a mixture of dry air and a variable amount of water vapor (0-4% or 0-30 g/kg) An air parcel is said.
Large Eddy Simulation of PBL turbulence and clouds Chin-Hoh Moeng National Center for Atmospheric Research.
Forecast simulations of Southeast Pacific Stratocumulus with CAM3 and CAM3-UW. Cécile Hannay (1), Jeffrey Kiehl (1), Dave Williamson (1), Jerry Olson (1),
Science Weather Review
Evaluating forecasts of the evolution of the cloudy boundary layer using radar and lidar observations Andrew Barrett, Robin Hogan and Ewan O’Connor Submitted.
Physics - Dynamics Interface The 14th ALADIN Workshop Innsbruck, 1-4 June 2004 Martina Tudor Meteorological and Hydrological Service, Grič 3, HR
EWGLAM Oct Some recent developments in the ECMWF model Mariano Hortal ECMWF Thanks to: A. Beljars (physics), E. Holm (humidity analysis)
Weather Variables and Forecasting Modified from National Weather Service
10 th COSMO General Meeting, Krakow, September 2008 Recent work on pressure bias problem Lucio TORRISI Italian Met. Service CNMCA – Pratica di Mare.
Boundary Layer Clouds.
Radiative Impacts of Cirrus on the Properties of Marine Stratocumulus M. Christensen 1,2, G. Carrió 1, G. Stephens 2, W. Cotton 1 Department of Atmospheric.
Weather Review Atmosphere in Motion. Winds blow from _____ pressure to _______ pressure.
1 Making upgrades to an operational model : An example Jongil Han and Hua-Lu Pan NCEP/EMC GRAPES-WRF Joint Workshop.
Simulating Stratocumulus clouds sensitivity to representation of: Drizzle Cloud top entrainment Cloud-Radiation interaction Large scale subsidence Vertical.
Continuous treatment of convection: from dry thermals to deep precipitating convection J.F. Guérémy CNRM/GMGEC.
Where are they? Why is there no weather?. Meteorology The study of weather Good sites for weather info: weather.com
Chapter 7 Water and Atmospheric Moisture Geosystems 6e An Introduction to Physical Geography Robert W. Christopherson Charles E. Thomsen.
PAPERSPECIFICS OF STUDYFINDINGS Kohler, 1936 (“The nucleus in and the growth of hygroscopic droplets”) Evaporate 2kg of hoar-frost and determined Cl content;
1)Consideration of fractional cloud coverage Ferrier microphysics scheme is designed for use in high- resolution mesoscale model and do not consider partial.
Update on progress with the implementation of a statistical cloud scheme: Prediction of cloud fraction using a PDF- based or “statistical” approach Ben.
Climate.  Climate: Long term weather patterns of an area  Patterns used to describe climate  Annual variation of temperature  Precipitation  Wind.
THE INFLUENCE OF WIND SPEED ON SHALLOW CUMULUS CONVECTION from LES and bulk theory Louise Nuijens and Bjorn Stevens University of California, Los Angeles.
Work Status: The project implementation is somewhat delayed due to the uncertainty about the future of some project participants A review about analogies.
1 Convection parameterization for Weather and Climate models Hua-Lu Pan and Jongil Han NCEP/EMC With help from EMC physics team Myong-In Lee and Sieg Schubert.
Radiative-Convective Model. Overview of Model: Convection The convection scheme of Emanuel and Živkovic-Rothman (1999) uses a buoyancy sorting algorithm.
CTB Science Plan for the CFS S. Moorthi Jae Schemm Steve Lord Hua-Lu Pan.
Performance of ALARO0 baseline in pre-operational testing
Clouds and Large Model Grid Boxes
Lecture 4 Effects of Cumulus on Large Scale Heat Budgets
Han, J. , W. Wang, Y. C. Kwon, S. -Y. Hong, V. Tallapragada, and F
NRL POST Stratocumulus Cloud Modeling Efforts
Presentation transcript:

Current issues in GFS moist physics Hua-Lu Pan, Stephen Lord, and Bill Lapenta

Convective cloud fraction for radiation Convection scheme leaves only the detrained condensate to the condensate budget. Convective cloud is assumed to disappear at the end of each step. The mass flux scheme can be used to derive an ‘implied cloud’ that existed during the step. We can use this for radiation only. It does add to the total cloud fraction (mainly low and middle clouds in the convective region)

Moist turbulence Current GFS turbulence mixes temperature and moisture separately. This is not good for stratus and stratocumulus regions. Moist conserving variables would be a better way to go. In partial cloudy region, there is a computational problem separating the cloudy and clear region after mixing. A cloud fraction scheme is needed. We are looking into using a PDF assumption to solve the problem.

Cloud fraction We need cloud fraction for radiation, turbulence, and microphysics. Most of the advanced microphysics scheme assumes the grid to be saturated. For global models, we must deal with partial cloudiness. We are working on using simple PDF assumptions to provide a consistent cloud fraction scheme for all physics.

Extending SAS to meso-scale models The basic assumption in the SAS (and in the original AS) is that the updraft area is small. Compensating subsidence is the primary physics that does the warming and drying. Work is ongoing to remove this assumption is a way that will allow the SAS to work for model grids down to 1 km.

Hurricane intensity issue We are working with GFDL and HWRF to examine the impact of physics to the intensity problem. Cumulus momentum exchange may need to be studied more with LES and CRM.

‘Fast’ and ‘Slow’ physics Weather models need to deal with short-range forecasts of weather. So we have to emphasize fast physics : turbulence, onset of convections, diurnal signals of precipitation and evaporation. Climate models need to deal with longer-term response of the physics, e.g. cloud-radiation feedback, impact and interactions with aerosols, etc. Mixed problem also exist : land water budget. Sea ice budget, response to convective heating, restoration of CISK.