KNMI research topics. Validation of cloud parameter retrievals from MSG and AVHRR Arnout Feijt, Rob Roebeling Clear-sky shortwave radiation closure Wouter.

Slides:

Advertisements

Similar presentations

Anthony Illingworth, + Robin Hogan, Ewan OConnor, U of Reading, UK and the CloudNET team (F, D, NL, S, Su). Reading: 19 Feb 08 – Meeting with Met office.

Advertisements

BBOS meeting on Boundary Layers and Turbulence, 7 November 2008 De Roode, S. R. and A. Los, QJRMS, Corresponding paper available from

Integrated Profiling at the AMF

Hirlam Physics Developments Sander Tijm Hirlam Project leader for physics.

Veldhoven, Large-eddy simulation of stratocumulus – cloud albedo and cloud inhomogeneity Stephan de Roode (1,2) & Alexander Los (2)

Classification of Low Level Jets at Cabauw Fred Bosveld, Peter Baas and Henk Klein Baltink KNMI Contents: Motivation Observations Definition of Low Level.

Validation of SCIA’s reflectance and polarisation (Acarreta, de Graaf, Tilstra, Stammes, Krijger ) Envisat Validation Workshop, Frascati, 9-13 December.

Marc Schröder et al., FUB BBC2 Workshop, De Bilt, 10.´04 Problems related to absorption dependent retrievals and their validation Marc Schröder 1, Rene.

BBC2 Overview Scientific aims Atmospheric conditions Events.

GABLS workshop, Stockholm, June 2007 Simple but realistic cases from Cabauw for GABLS Fred Bosveld (KNMI) with contributions from: Peter Baas Gert.

A new unified boundary-layer scheme for RACMO: The DualM-TKE scheme Stephan de Roode with contributions from Geert Lenderink Roel Neggers Reinder Ronda.

Impact of entrainmnet and mixing on optical properties of boundary layer clouds Wojciech W. Grabowski, Hugh Morrison, NCAR, Boulder, Colorado, USA Joanna.

Evaluation of HARMONIE using a single column model in the KNMI

Application of Cloudnet data in the validation of SCIAMACHY cloud height products Ping Wang Piet Stammes KNMI, De Bilt, The Netherlands CESAR Science day,

A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.

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.

Analysis of SPUV aerosol data for the May 2003 BBC2 campaign Piet Stammes Wouter Knap KNMI.

Eduardo Barbaro * with contributions of: Jordi Vila, Maarten Krol, Huug Ouwersloot, Henk Baltink, Fred Bosveld, Dave Donovan, Wouter Knap, Ping Wang *

3D Radiative Transfer in Cloudy Atmospheres: Diffusion Approximation and Monte Carlo Simulation for Thermal Emission K. N. Liou, Y. Chen, and Y. Gu Department.

EGU-Boers (2006) Accuracy assessment of an integrated profiling technique for temperature, humidity and liquid water content profiles U. Lohnert (1), E.

Low clouds in the atmosphere: Never a dull moment Stephan de Roode (GRS) stratocumulus cumulus.

Buoyancy driven turbulence in the atmosphere

Iterative and constrained algorithms to generate cloud fields with measured properties Victor Venema Clemens Simmer Susanne Crewell Bonn University

Observed Updraft & Mass Flux in Shallow Cumulus at ARM Southern Great Plains site Preliminary results Yunyan Zhang, Steve Klein & Pavlos Kollias CFMIP/GCSS.

The role of the mean relative humidity on the dynamics of shallow cumuli - LES Sensitivity experiments Stephan de Roode (KNMI/IMAU) Simon Axelsen (IMAU)

Lee Smith Anthony Illingworth

GFS Deep and Shallow Cumulus Convection Schemes

Observed and modelled long-term water cloud statistics for the Murg Valley Kerstin Ebell, Susanne Crewell, Ulrich Löhnert Institute for Geophysics and.

Large-Eddy Simulation of a stratocumulus to cumulus transition as observed during the First Lagrangian of ASTEX Stephan de Roode and Johan van der Dussen.

7 oktober 2009 Challenge the future Delft University of Technology Clouds and Climate KNMI Climate Course 2011 A. Pier Siebesma KNMI & TU Delft Multiscale.

BALTEX BRIDGE Cloud Campaign part 2. Guide What is BBC2? Why BBC2? Instrumentation Organisation.

WMO Cloud Modelling Workshop, Hamburg, 12. Juli 2004 The BALTEX BRIDGE Campaign (BBC) cases Susanne Crewell, Nicole van Lipzig, Wenchieh Yen Meteorological.

The representation of stratocumulus with eddy diffusivity closure models Stephan de Roode KNMI.

Optical Measurements of Aerosols for MIRAGE-MEX University of Iowa Bill Eichinger John Prueger Piotr Lewandowski Heidi Holder.

Atmospheric TU Delft Stephan de Roode, Harm Jonker clouds, climate and weather air quality in the urban environmentenergy.

Can we use a statistical cloud scheme coupled to convection and moist turbulence parameterisations to simulate all cloud types? Colin Jones CRCM/UQAM

Stephan de Roode (KNMI) Entrainment in stratocumulus clouds.

Budgets of second order moments for cloudy boundary layers 1 Systematische Untersuchung höherer statistischer Momente und ihrer Bilanzen 1 LES der atmosphärischen.

TECO-2010, Helsinki | 30 August 2010 Laboratory and Field Evaluation of the NubiScope Wiel Wauben * Fred Bosveld Henk Klein Baltink KNMI * R&D Information.

The ASTEX Lagrangian model intercomparison case Stephan de Roode and Johan van der Dussen TU Delft, Netherlands.

EMS Sep Reading UK Evaluating modelled surface long wave downward radiation with Cabauw observations: The GABLS3 SCM case. Fred Bosveld (KNMI)

II: Progress of EDMF, III: comparison/validation of convection schemes I: some other stuff Sander Tijm (HIRLAM) Contributions of: Siebesma, De Rooy, Lenderink,

Evaluating forecasts of the evolution of the cloudy boundary layer using radar and lidar observations Andrew Barrett, Robin Hogan and Ewan O’Connor Submitted.

RICO Modeling Studies Group interests RICO data in support of studies.

Vertical Structure of the Atmosphere within Clouds Revealed by COSMIC Data Xiaolei Zou, Li Lin Florida State University Rick Anthes, Bill Kuo, UCAR Fourth.

Matthew Shupe Ola Persson Paul Johnston Duane Hazen Clouds during ASCOS U. of Colorado and NOAA.

Status, Evaluation and New Developments of the Automated Cloud Observations in the Netherlands Wiel Wauben, Henk Klein Baltink, Marijn de Haij, Nico Maat,

KNMI 35 GHz Cloud Radar & Cloud Classification* Henk Klein Baltink * Robin Hogan (Univ. of Reading, UK)

Simulation of boundary layer clouds with double-moment microphysics and microphysics-oriented subgrid-scale modeling Dorota Jarecka 1, W. W. Grabowski.

Modelling and observations of droplet growth in clouds A Coals 1, A M Blyth 1, J-L Brenguier 2, A M Gadian 1 and W W Grabowski 3 Understanding the detailed.

K. Pfeilsticker Institut für Umweltphysik, University of Heidelberg, Germany K. Pfeilsticker, and T. Scholl, IUP, University of Heidelberg, Germany A.

A Thermal Plume Model for the Boundary Layer Convection: Representation of Cumulus Clouds C. RIO, F. HOURDIN Laboratoire de Météorologie Dynamique, CNRS,

Development and testing of the moist second-order turbulence-convection model including transport equations for the scalar variances Ekaterina Machulskaya.

MODELING OF SUBGRID-SCALE MIXING IN LARGE-EDDY SIMULATION OF SHALLOW CONVECTION Dorota Jarecka 1 Wojciech W. Grabowski 2 Hanna Pawlowska 1 Sylwester Arabas.

Cloudnet Workshop April 2003 A.Tompkins 1 Changes to the ECMWF cloud scheme  Recent package of changes for 25r3:  COMPLETE REWRITE OF NUMERICS FOR CLOUD.

Atmospheric profile and precipitation properties derived from radar and radiosondes during RICO Louise Nuijens With thanks to: Bjorn Stevens (UCLA) Margreet.

Stephan de Roode The art of modeling stratocumulus clouds.

Shallow Moist Convection Basic Moist Thermodynamics Remarkable Features of Moist Convection Shallow Cumulus (Stratocumulus) Courtesy: Dave Stevens.

A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO Wim de Rooy & Pier Siebesma Royal Netherlands Meteorological Institute.

COSMO model simulations for COPS IOP 8b, 15 July 2007 Jörg Trentmann, Björn Brötz, Heini Wernli Institute for Atmospheric Physics, Johannes Gutenberg-University.

Rutherford Appleton Laboratory PM2 MSG cloud model 17 th February 2008 Comparisons with Calipso and Cloudsat C. Poulsen R.Siddans.

CLARIFY-2016 Cloud characterisation and aerosol-cloud-interaction flight planning Steven Abel, 29 th February 2016, Birmingham.

Jon A. Arrillaga (UCM, SP)

"CRIME Investigations" Henk Klein Baltink (RDWD, KNMI)

Matthew Christensen and Graeme Stephens

The Cabauw Experimental Site for Atmospheric Research (CESAR): New developments Fred C. Bosveld (KNMI) Content CESAR and its research themes Long term.

Theories of Mixing in Cumulus Convection

Entrainment rates in stratocumulus computed from a 1D TKE model

RCA and CLIWANET results

transport equations for the scalar variances

Presentation transcript:

KNMI research topics

Validation of cloud parameter retrievals from MSG and AVHRR Arnout Feijt, Rob Roebeling Clear-sky shortwave radiation closure Wouter Knap, Piet Stammes Cloudy sky radiation closure Reinout Boers, Rob van Dorland, Wouter Knap Validation of cloud and aerosol data products from SCIAMACHY Piet Stammes, Juan Acarreta, Martin de Graaf

KNMI research topics Evaluating Statistical Cloud Schemes A. Pier Siebesma Entrainment in cumulus clouds A. Pier Siebesma, Stephan de Roode (IMAU) Trigger Function of Cumulus Convection A. Pier Siebesma Top-Entrainment of the (Clear and) Scu topped boundary Layer A. Pier Siebesma Turbulent structure of the convective boundary layer Fred Bosveld (KNMI), Henk Klein Baltink (KNMI), Cindy Werner (G&NS), Jordi Vila (WUR), Eddy Moors (WUR), Alex Vermeulen (ECN),

KNMI research topics Validation of combined lidar and radar derived Ice Cloud radiative and micophysical properties Dave Donovan (KNMI) Occurance of oriented ice crystals Dave Donovan (KNMI), S. Crewell (Uni. Bonn) Quality of Water Vapour Profiles and Boundary layer height observations Iwan Holleman (KNMI), Sylvia Balag (KNMI)

Evaluation of Statistical Cloud Scheme Required: aircraft (Merlin) fast measurements of: specific humidity (qv) liquid water, (ql) temperature, (T) pressure(P) for legs of typically 50 km. A. Pier Siebesma

Motivation: Cloud cover Bechtold and Cuijpers JAS 1995 Bechtold and Siebesma JAS 1999 Data from LES: Pseudo Observations Suggest a one-to–one correspondence between Q and cloud cover a.

How about real BBC2- data???? Determine from flight legs: cloud cover : a Spatial average of: s = q t –q sat (so called saturation deficit) Standard deviation of s:  s Construct: Plot against cloud cover a !!!!