Cloud Occurrence at Arctic Atmospheric Observatories Matthew Shupe, Taneil Uttal, Daniel Wolfe, David Welsh AMS Polar Meteorology and Oceanography 2007.

Slides:



Advertisements
Similar presentations
Gareth Berry University of Reading, UK. Evaluation of some daytime boundary layer forecast techniques. Undergraduate project presentation.
Advertisements

Lidar observations of mixed-phase clouds Robin Hogan, Anthony Illingworth, Ewan OConnor & Mukunda Dev Behera University of Reading UK Overview Enhanced.
Ewan OConnor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat Liquid water path from microwave radiometers.
Proposed new uses for the Ceilometer Network
Robin Hogan Department of Meteorology University of Reading Cloud and Climate Studies using the Chilbolton Observatory.
Application of Cloudnet data in the validation of SCIAMACHY cloud height products Ping Wang Piet Stammes KNMI, De Bilt, The Netherlands CESAR Science day,
Atmospheric data for Arctic modeling John Walsh International Arctic Research Center University of Alaska, Fairbanks Arctic System Modeling Workshop, Montreal,
Microphysical and radiative properties of ice clouds Evaluation of the representation of clouds in models J. Delanoë and A. Protat IPSL / CETP Assessment.
Matthew Shupe Ola Persson Paul Johnston Cassie Wheeler Michael Tjernstrom Surface-Based Remote-Sensing of Clouds during ASCOS Univ of Colorado, NOAA and.
Aerosol and Cloud Microphysics Working Group Dietrich Althausen, Andrea Riede, Herman Russchenberg, Aldo Amodeo, Susanne Crewell, Paolo Di Girolamo, Stephen.
Balloon-Borne Sounding System (BBSS) Used for atmospheric profiling Measures P, T, RH, wind speed and direction Uncertainties arise from incorrect surface.
Seasonal and Inter-annual Variations of Polar Cloud Cover Seiji Kato 1, Norman G. Loeb 2, Patrick Minnis 3, Jennifer A. Francis 4, Thomas P. Charlock 3,
Matthew Shupe Von Walden David Turner U. Colorado/NOAA-ESRL U. Idaho NOAA - NSSL New Cloud Observations at Summit, Greenland: Expanding the IASOA Network.
Lidar algorithms to retrieve cloud distribution, phase and optical depth Y. Morille, M. Haeffelin, B. Cadet, V. Noel Institut Pierre Simon Laplace SYMPOSIUM.
A climatology of Arctic clouds and aerosols for Eureka, Canada Ed Eloranta University of Wisconsin
The Arctic Climate Paquita Zuidema, RSMAS/MPO, MSC 118, Feb, 29, 2008.
Utilization of Observations at the Russian Drifting Stations “North Pole” for Improved Description of Air–Sea-Ice-Ocean Interactions in the Arctic Ocean.
Measuring Atmospheric Changes in the Arctic Christopher J Cox University of Idaho, Geography.
A Combined Measurement and Modelling Source Apportionment of Long-Range Transported Dust and its Impacts on Cloud and Precipitation Formation in California.
Lisa Darby and Taneil Uttal NOAA/Earth System Research Laboratory, Boulder, CO, USA USGS Circumpolar Conference on Geospatial Sciences and Applications.
The Arctic Climate Paquita Zuidema, RSMAS/MPO, MSC 118, March
Characterization of Arctic Mixed-Phase Cloudy Boundary Layers with the Adiabatic Assumption Paquita Zuidema*, Janet Intrieri, Sergey Matrosov, Matthew.
The RADAGAST project Tony Slingo Environmental Systems Science Centre University of Reading Background and motivation Aims Methodology GIST 23, Deutscher.
Retrieving cloud optical depth and ice particle size using thermal infrared radiometry: Application to the monitoring of thin ice clouds in an arctic environment.
Boundary layer temperature profile observations using ground-based microwave radiometers Bernhard Pospichal, ISARS 2006 Garmisch-Partenkirchen AMMA - Benin.
DOE’s Flagship Global Climate Change Program ARM Climate Research Facilities in Alaska The North Slope of Alaska Team at Sandia Labs/NM: Bernie Zak, Jeff.
Chapter 12 Meteorology. Meteorology = the study of meteors? Meteoros = anything high in the air Meteorologists study: – Hydrometeors: rain, snow, sleet,
Matthew Shupe, Ola Persson, Amy Solomon CIRES – Univ. of Colorado & NOAA/ESRL David Turner NOAA/NSSL Dynamical and Microphysical Characteristics and Interactions.
Cloud observations: the state of the art Alexander Chernokulsky A.M. Obukhov Institute of Atmospheric Physics Russian Academy of Sciences
Anthony Illingworth, Robin Hogan, Ewan O’Connor, U of Reading, UK Nicolas Gaussiat Damian Wilson, Malcolm Brooks Met Office, UK Dominique Bouniol, Alain.
A Thunderstorm Nowcasting System for the Beijing 2008 Olympics: A U.S./China Collaboration by James Wilson 1 and Mingxuan Chen 2 1. National Center for.
ARM Data Overview Chuck Long Jim Mather Tom Ackerman.
Comparison on Cloud and radiation properties at Barrow between ARM/NSA measurements and GCM outputs Qun Miao and Zhien Wang University of Wyoming 1. Introduction.
Boundary layer observations in West Africa using a ground-based 14-channel microwave radiometer Bernhard Pospichal and Susanne Crewell University of Cologne.
Robin Hogan Ewan O’Connor The Instrument Synergy/ Target Categorization product.
Matthew Shupe Ola Persson Paul Johnston Duane Hazen Clouds during ASCOS U. of Colorado and NOAA.
Overview of NOAA’s Arctic Climate Science Activities Current or Proposed Activities Expected to Persist in FY
New observations of clouds, atmosphere, and precipitation at Summit, Greenland Matthew Shupe, Von Walden, David Turner Ryan Neely, Ben Castellani, Chris.
BBHRP Assessment Part 2: Cirrus Radiative Flux Study Using Radar/Lidar/AERI Derived Cloud Properties David Tobin, Lori Borg, David Turner, Robert Holz,
Towards a Characterization of Arctic Mixed-Phase Clouds Matthew D. Shupe a, Pavlos Kollias b, Ed Luke b a Cooperative Institute for Research in Environmental.
Processes Controlling the Seasonal Cycle of Arctic Aerosol Number and Size B. Croft 1, R. V. Martin 1,2, W. R. Leaitch 3, P. Tunved 4, T. J. Breider 5,
ARCTIC CLIMATE CHARACTERISTICS AND RECENT TRENDS FROM SPACE Xuanji Wang 1, Jeffrey R. Key 2, Taneil Uttal 3, and Shelby Frisch 4 1 Cooperative Institute.
Layered Water Vapor Quick Guide by NASA / SPoRT and CIRA Why is the Layered Water Vapor Product important? Water vapor is essential for creating clouds,
Multidisciplinary drifting Observatory for the Study of Arctic Climate
Point Comparison in the Arctic (Barrow N, 156.6W ) Part I - Assessing Satellite (and surface) Capabilities for Determining Cloud Fraction, Cloud.
The Multidisciplinary drifting Observatory
Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment, Part II: Multi-layered cloud GCSS.
SeaWiFS Views Equatorial Pacific Waves Gene Feldman NASA Goddard Space Flight Center, Lab. For Hydrospheric Processes, This.
An Evaluation of Cloud Microphysics and Radiation Calculations at the NSA Matthew D. Shupe a, David D. Turner b, Eli Mlawer c, Timothy Shippert d a CIRES.
Effect of BrO Mixing Height to Ozone Depletion Events Sunny Choi.
Climate Change in the Arctic Ocean NABOS 2013 Atmospheric Boundary Layer (ABL) and Turbulence Tobias Wolf, Nansen Environmental and Remote Sensing Center.
Sarah Callaghan British Atmospheric Data Centre, UK, The effects of climate change on rain The consensus in the climate change.
SHEBA model intercomparison of weakly-forced Arctic mixed-phase stratus Hugh Morrison National Center for Atmospheric Research Thanks to Paquita Zuidema.
ATM OCN 100 Summer ATM OCN 100 – Summer 2002 LECTURE 5 (con’t.) AIR TEMPERATURE: A Fundamental Weather Element u A. Background & Definitions u B.
Cloudnet meeting Oct Martial Haeffelin SIRTA Cloud and Radiation Observatory M. Haeffelin, A. Armstrong, L. Barthès, O. Bock, C. Boitel, D.
The Lifecyle of a Springtime Arctic Mixed-Phase Cloudy Boundary Layer observed during SHEBA Paquita Zuidema University of Colorado/ NOAA Environmental.
Observations of Air-sea Interaction in the Northeast Tropical Atlantic C.W. Fairall, L. Bariteau, S. Pezoa, D. Wolfe NOAA/ Earth System Research Laboratory,
MODIS, AIRS, and Midlevel Cloud Phase Shaima Nasiri CIMSS/SSEC, UW-Madison Brian Kahn Jet Propulsion Laboratory MURI Hyperspectral Workshop 7-9 June, 2005.
DOE ARM Calibration / Validation Instrumentation Data essentially available in real-time –ARM (Atmospheric Radiation Measurement) –CART (Cloud And Radiation.
Cloud Detection: Optical Depth Thresholds and FOV Considerations Steven A. Ackerman, Richard A. Frey, Edwin Eloranta, and Robert Holz Cloud Detection Issues.
Chilbolton Site Instrument Availability Major Chilbolton Instrumentation Availability during CloudNet Major Chilbolton Instrumentation Availability during.
AON enables the U.S. Study of Environmental ARctic CHange (SEARCH) GOALS: record the full suite of changes inform research on the causes and consequences.
International Arctic System for Observing the Atmosphere (IASOA)
Observations of the Arctic boundary layer clouds during ACSE 2014
CHUVA Project CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation.
OBSERVATIONS of EARTH'S ATMOSPHERE
Radar-lidar synergy for the retrieval of water cloud parameters
European Conference on Applications of Meteorology/ EMS Annual Meeting
Meteorological Measurements for Improved Air Quality Modeling
Presentation transcript:

Cloud Occurrence at Arctic Atmospheric Observatories Matthew Shupe, Taneil Uttal, Daniel Wolfe, David Welsh AMS Polar Meteorology and Oceanography 2007 Special Thanks for Ny’Alesund MPL Data: Masataka Shiobara, James Campbell

Arctic Cloud Stations Barrow SHEBA Eureka Alert Ny’Alesund Tiksi RadarLidar An Example Station Summit

SiteInstrumentsDates SHEBA, Arctic OceanRadar, lidar, ceilometer Barrow, USARadar, lidar, ceilometer 1998 – Present Ny’Alesund, NorwayLidar2002 – Present Eureka, CanadaRadar, lidar2005 – Present Alert, CanadaCeilometer? Tiksi, RussiaNone yetNot yet Summit, GreenlandNone yetNot yet Observatories

Data Processing Considerations Use a combination of cloud radar and lidar, depending on station “Cloud fraction” is from the perspective of vertically- pointing, surface-based instruments All but SHEBA must be considered preliminary in nature, more detailed multi-instrument analyses will follow

Very cloudy in general at all stations (~75% total) Summer/Fall maximum? Total Cloud Fraction Radar Lidar Surface observations

Vertical Distribution Bimodal Dist’n in Vertical Lots of Low-level Clouds Radar Lidar

Annual and Vertical Distribution

Instruments: radar, lidar, microwave radiometer, radiosonde. Manually classified. Automated system has been developed but not yet applied to all observations at all sites. 1 year of data at SHEBA and 7 years at Barrow. Cloud Type Classification

Annual Cycles of Cloud Type Mixed-phase clouds: Maxima in transition seasons. Similar trends and magnitudes between SHEBA and Barrow

Liquid is present throughout the year more than half of the time! Occurrence of Cloud Liquid

Remarkable similarities Slightly different balance at surface. Vertical Distributions of Cloud Type

Annual & Vertical Dist’n of Type

High annual fraction: ~75% Remarkable similarities in vertical. Similar dist’n of phase for W. Arctic sites. Liquid is frequent (and important!) Radar-lidar combination at all sites. Classification work at all sites using new algorithm. More detailed analysis of boundaries Conclusions Future Work Thank You.