Monthly Precipitation Rate in July 2006 TRMM MMF DIFF RH84 New Scheme 3.3 Evaluate MMF Results with TRMM Data Zonal Mean Hydrometeor Profile TRMM TMI CONTROL.

Slides:



Advertisements
Similar presentations
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
Advertisements

Hou/JTST Exploring new pathways in precipitation assimilation Arthur Hou and Sara Zhang NASA Goddard Space Flight Center Symposium on the 50 th.
The Role of High-value Observations for Forecast Simulations in a Multi- scale Climate Modeling Framework Gabriel J. Kooperman, Michael S. Pritchard, and.
Limited Area Models Adam Sobel Banff Summer School.
The Problem of Parameterization in Numerical Models METEO 6030 Xuanli Li University of Utah Department of Meteorology Spring 2005.
Evaluation of ECHAM5 General Circulation Model using ISCCP simulator Swati Gehlot & Johannes Quaas Max-Planck-Institut für Meteorologie Hamburg, Germany.
A Cloud Resolving Model with an Adaptive Vertical Grid Roger Marchand and Thomas Ackerman - University of Washington, Joint Institute for the Study of.
Wesley Berg, Tristan L’Ecuyer, and Sue van den Heever Department of Atmospheric Science Colorado State University Evaluating the impact of aerosols on.
The causes of extreme rainfall in East Africa: insights from observed data and GCMs Emily Black, Julia Slingo and Ken Sperber.
Ju-Hye Kim and Dong-Bin Shin* Department of Atmospheric Sciences
Andrew L. Molthan 1,2, Jonathan L. Case 3, Scott R. Dembek 4, Gary J. Jedlovec 1 and William M. Lapenta 5 American Meteorological Society 24 th Conference.
Applications to Global Climate Modeling Tom Ackerman Lecture II.7b.
The Radiative Budget of an Atmospheric Column in Tropical Western Pacific Zheng Liu Department of Atmospheric Science University of Washington.
Water/energy cycle against data from field programs Semi-Real and Real Time at GPM Super sites and TC4 Hurricane/Typhoon (Impact of microphysics and land.
Elevation-dependent Trends in Precipitation during NAME Angela K. Rowe, Steven A. Rutledge, and Timothy J. Lang Colorado State University, Fort Collins,
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar by S. A. Rutledge, R. Cifelli, T. Lang and S. W. Nesbitt EGU 2009.
Hydrometeors Injected into the Large-scale Environment by Tropical Cloud Systems Robert A. Houze & Courtney Schumacher Co-PIs ARM Science Team Meeting,
The Radiative Budget of an Atmospheric Column in Tropical Western Pacific Zheng Liu 1 Thomas Ackerman 1,2, Sally McFarlane 2, Jim Mather 2, University.
Cirrus Production by Tropical Mesoscale Convective Systems Jasmine Cetrone and Robert Houze 8 February 2008.
Mesoscale Convective Systems Robert Houze Department of Atmospheric Sciences University of Washington Nebraska Kansas Oklahoma Arkansas.
Cirrus Production by Tropical Mesoscale Convective Systems Jasmine Cetrone and Robert Houze University of Washington Motivation Atmospheric heating by.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
Heating Profiles Associated with Deep Convection Estimated from TRMM and Future Satellites Robert Houze University of Washington 19th Scientific Steering.
Convective-scale diagnostics Rob Rogers NOAA/AOML Hurricane Research Division.
A “New” One-moment 4ICE Scheme for the GCE Stephen Lang, SSAI W.-K. Tao, NASA GSFC Jiundar Chern, Morgan State U. Xiaowen Li, Morgan State U. Di Wu, SSAI.
Test of Microphysical Schemes (WRF) with C3VP Snow Events J.-J. Shi, T. Matsui, S. Lang A. Hou, G. S. Jackson, C. Peters-Lidard W. Petersen, R. Cifelli,
“The Goddard Multi-Scale Modeling System & Satellite Simulator for NASA PMM” Wei-Kuo Tao & Toshi Matsui Representing Goddard Mesoscale Dynamics and Modeling.
Understanding the effects of aerosols on deep convective clouds Eric Wilcox, Desert Research Institute, Reno NV Tianle.
Clouds, Aerosols and Precipitation GRP Meeting August 2011 Susan C van den Heever Department of Atmospheric Science Colorado State University Fort Collins,
Using TWP-ICE Observations and CRM Simulations to Retrieve Cloud Microphysics Processes Xiping Zeng 1,2, Wei-Kuo Tao 2, Shaocheng Xie 3, Minghua Zhang.
Aerosol, Cumulus Congestus, MJO Xiaowen Li GEST/UMBC Wei-Kuo Tao NASA/GSFC Aerocenter Annual Meeting April 2010.
Project Title: High Performance Simulation using NASA Model and Observation Products for the Study of Land Atmosphere Coupling and its Impact on Water.
Preliminary Results of Global Climate Simulations With a High- Resolution Atmospheric Model P. B. Duffy, B. Govindasamy, J. Milovich, K. Taylor, S. Thompson,
Precipitation Retrievals Over Land Using SSMIS Nai-Yu Wang 1 and Ralph R. Ferraro 2 1 University of Maryland/ESSIC/CICS 2 NOAA/NESDIS/STAR.
The Role of Polarimetric Radar for Validating Cloud Models Robert Cifelli 1, Timothy Lang 1, Stephen Nesbitt 1, S.A. Rutledge 1 S. Lang 2, and W.K. Tao.
13 June, 2013 Dymecs Meeting, Reading Tropical convective organisation in the UM Chris Holloway NCAS-Climate, Dept. of Meteorology, University of Reading.
Characterization of tropical convective systems Henri Laurent IRD/LTHE Cooperation with Brazil CTA (Centro Técnico Aeroespacial) CPTEC (Centro de Previsião.
CPPA Past/Ongoing Activities - Ocean-Atmosphere Interactions - Address systematic ocean-atmosphere model biases - Eastern Pacific Investigation of Climate.
Assessing Heating in Climate Models  Top: Atmospheric diabatic heating estimates from the TRMM satellite quantify the response of regional energy budgets.
LBA/Physical Climate Moist Convection in the Amazon.
Evaluating Cloud Microphysics Schemes in the WRF Model Fifth Meeting of the Science Advisory Committee November, 2009 Andrew Molthan transitioning.
On the Definition of Precipitation Efficiency Sui, C.-H., X. Li, and M.-J. Yang, 2007: On the definition of precipitation efficiency. J. Atmos. Sci., 64,
Yuying Zhang, Jim Boyle, and Steve Klein Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory Jay Mace University.
2nd International GPM GV Workshop Taipei, Taiwan, September 27-29, 2005 Characteristics of Convective Systems Observed During TRMM-LBA Rob Cifelli, Steve.
Robert Wood, Atmospheric Sciences, University of Washington The importance of precipitation in marine boundary layer cloud.
Hou/JTST NASA GEOS-3/TRMM Re-Analysis: Capturing Observed Rainfall Variability in Global Analysis Arthur Hou NASA Goddard Space Flight Center 2.
Thomas Ackerman Roger Marchand University of Washington.
B.-W. Shen 1, W.-K. Tao 2, R. Atlas 3, T. Lee 4, O. Reale 5, J.-D. Chern 5, S.-J. Lin 6, J. Chang 7, C. Henze 7, J.-L. Li 8 1 UMCP/ESSIC; 2 NASA/GSFC;
Entrainment Ratio, A R -  R = c p  i / c p  s  sfc  ent c p  i c p  s PBL Schemes  = YSU  = MYJ  = MRF 12Z 00Z  adv Science issue: Assess.
Observed & Simulated Profiles of Cloud Occurrence by Atmospheric State A Comparison of Observed Profiles of Cloud Occurrence with Multiscale Modeling Framework.
DRAFT – Page 1 – January 14, 2016 Development of a Convective Scale Ensemble Kalman Filter at Environment Canada Luc Fillion 1, Kao-Shen Chung 1, Monique.
MJO Breakout Group. MJO Breakout Group Agenda Jim Benedict - Structure of the MJO in MMF Bo-wen Shen - Comparison of CSU & NASA Goddard MMFs Mitch Moncrieff.
Atmospheric aerosols, cloud microphysics, and climate Wojciech Grabowski National Center for Atmospheric Research, Boulder, Colorado, USA.
MMF Tasks Global Visualization of 4-month Simulations 30-day MJO Simulations Preliminary Analysis on Simulated Cloud Liquid Water Path (removed from this.
MMF Tasks Global Visualization of 4-month Simulations 30-day MJO Simulations Preliminary Analysis on Simulated Cloud Liquid Water Path (removed from this.
Kinematic, Microphysical, and Precipitation Characteristics of MCSs in TRMM-LBA Robert Cifelli, Walter Petersen, Lawrence Carey, and Steven A. Rutledge.
Remote sensing and modeling of cloud contents and precipitation efficiency Chung-Hsiung Sui Institute of Hydrological Sciences National Central University.
Convective Transport of Carbon Monoxide: An intercomparison of remote sensing observations and cloud-modeling simulations 1. Introduction The pollution.
Important data of cloud properties for assessing the response of GCM clouds in climate change simulations Yoko Tsushima JAMSTEC/Frontier Research Center.
Role of cold pool formation on the diurnal cycle of precipitation over the maritime continent Tomonori Sato (CCSR, Univ of Tokyo) Hiroaki Miura (JAMSTEC.
NOAA Northeast Regional Climate Center Dr. Lee Tryhorn NOAA Climate Literacy Workshop April 2010 NOAA Northeast Regional Climate.
A modeling study of cloud microphysics: Part I: Effects of Hydrometeor Convergence on Precipitation Efficiency. C.-H. Sui and Xiaofan Li.
Matthew Christensen and Graeme Stephens
Multiscale aspects of cloud-resolving simulations over complex terrain
Using A-train observations to evaluate clouds in CAM
The representation of ice hydrometeors in ECHAM-HAM
Validation of GCM, and the need of High resolution atmospheric and hydrological model Vicente Barros and Mariano Re San José de Costa Rica 28 May 2003.
Application of radar observations to the evaluation and improvement of cloud permitting regional model simulations of MJO Samson M. Hagos, Zhe Feng, Kiranmayi.
Winter QPF Sensitivities to Snow Parameterizations and
Kurowski, M .J., K. Suselj, W. W. Grabowski, and J. Teixeira, 2018
Presentation transcript:

Monthly Precipitation Rate in July 2006 TRMM MMF DIFF RH84 New Scheme 3.3 Evaluate MMF Results with TRMM Data Zonal Mean Hydrometeor Profile TRMM TMI CONTROL ELASTIC NEW MICROPHYS Mean Vertical Profile of Hydrometeors (40S-40N) TRMM TMI Control Microphys Elastic 3.4 Evaluate MMF Results with CloudSat Data To compare the first two-month (July and August, 2006) observations from newly launched CloudSat, QuickBeam radar simulator developed by John Haynes at CSU is used to produces profiles of cloud radar reflectivity from model outputs. Evaluation and Improvements of Cloud Model Dynamics and Microphysics in Multi-Scale Modeling System Jiun-Dar Chern (1), Wei-Kuo Tao (1), Bo-Wen Shen (1), R. Atlas (2),Steve Lang (1), Z. Johnny Luo (3), and Graeme L. Stephens (3) (1) NASA/GSFC; (2) NOAA/AOML; (3) Department of Atmospheric Science, Colorado State University 1. Multi-Scale Modeling Framework (MMF) One of the major uncertainties in climate modeling is the representation of sub-grid processes in the General Circulations Models (GCMs). The ideal of MMF or a super parameterization, which replaces the conventional cloud parameterizations with a Cloud Resolving Model (CRM) in each grid column of a GCM, is a promising approach to break the deadlock of conventional parameterizations in GCMs (Grabowski 2001; Randall et al. 2003; Khairoutdinov et al. 2005). The Goddard MMF (Tao et al. 2007) includes the fvGCM running at 2.5 o x 2 o resolution and a two-dimensional GCE embedded in each GCM grid box. Globally, there are a total of 13,104 GCEs running at the same time and interact with the host GCM through a “forcing-feeback” coupling mechanism. 2. Evaluate Cloud Dynamics in the MMF Although most of CRMs use dynamics with anelastic assumption, the host GCMs in MMFs are usually constructed with elastic dynamics. To be consistent with the dynamics of host fvGCM, an elastic dynamical core has been implemented into the 2D GCE. To study the impacts of elastic system on the performance of MMF, one-month MMF simulations with anelastic and elastic dynamics have been carried out using observed NOAA weekly OI SST in July Monthly Precipitation Rate in July 2006 TRMM MMF DIFF Anelastic Elastic Radar Profile Classification Follow Stephens and Wood 2006: CFAD and ETH for 30S-30N (Jul-Aug 2006) CloudSat Control. Elastic New Microphys 4. Summary and Conclusion 1)Both elastic dynamic and the new bulk micro- physics improve the MMF simulations by reducing the excessive precipitation over Asia summer monsoon region and increasing cloud ice water content in upper atmosphere. 2)Preliminary results show the usefulness of cloudsat simulator and reflectivity CFAD statistical analyses to understand and improve the cloud microphysical processes in the model. 3)Comparisons with observations show some model deficiencies. More works need to be done to use observations from in-situ and remote sensing platforms as model constrains. 5. References Lang S., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective systems from TRMM LBA: Easterly and westerly regimes, J. Atmps. Sci. (in press). Tao, W.-K. and coauthors, 2007: A multi-scale modeling: Developments, applications and critical Issues. J. Geophys. Res. (submitted) 3. Evaluate Cloud Microphysics in the MMF 3.1 A new Bulk Microphysic scheme (Lang et al. 2007) During TRMM LBA experiment in Brazil, dual- Doppler radar observations were collected on 26 January 1999 by the NASA TOGA and NCAR S-Pol radars. The case is an example of an easterly regime mesoscale convective system (MCS) that propagated into the TRMM-LBA domain from the northeast. The 3D GCE model was used to simulate this squall line case with the modified Rutledge and Hobbs (1984) three-class ice scheme. CFADs (contoured frequency by altitude diagrams) analyses from radar are used to evaluate the model simulation and lead to improvements in cloud microphysical processes. Rain Radar Reflectivity and CFADS OBS CONTROL NEW Vertical Profile of Hydrometeors from 3D GCE Simulations of TRMM LBA Experiment RH84 New Scheme 3.2 Impacts of the New Microphysical scheme in MMF system One of the advantages of the MMF approach is it can provide global coverage and long-term simulation. The new microphysics was implemented into the embedded 2D GCE in the MMF to assess their effects on large scale circulation and climate. Z => P Z <= P Large-scale forcings Background profiles (T, q, u, v, w) Moist physics tendencies (T and q) Cloud and precipitation