Presented by Stella Melo Environment Canada, Science and Technology, Cloud Physics and Severe Weather Research Section

Transcription

1 Validation/Verification of the microphysical and dynamic characteristics of Arctic Cloud systems: what infrastructure is required to meet the challenge? Presented by Stella Melo Environment Canada, Science and Technology, Cloud Physics and Severe Weather Research Section

2 Motivation Provision of accurate meteorological predictions over the Arctic is increasing with the expansion of activities in this region. To meet the challenge we require an observing system conceptually integrating satellite, upper air, and ground-based measurements. Validation/characterization activities, both statistical and physically based, need to be conceived and integrated at the system design level. A major issue is the need for merging (data fusion?) data with different spatial and temporal characteristics. Data quality is intrinsically dependent on the user application: different users require different level of data characterization and validation. Environment Canada's Cloud Physics and Severe Weather Research Section (ARMP) has strong heritage in satellite data validation/characterization over Canada, including during cold seasons. We are currently supporting MSC in the development of an integrated observing system that will meet our needs for observations, particularly over the Arctic. We would like to take this opportunity to discuss possible collaborations!

3 EC Science Strategy FEDERAL PRIORITY ISSUES Providing early warnings about weather, climate and other environmental conditions ENVIRONMENT CANADA S SCIENCE GOALS Support the development and operation of monitoring and modelling systems and tools in order to improve prediction and forecasting of weather, climate and other environmental systems, and to provide high quality, sciencebased tools and services to Canadians, policy makers and targeted economic sectors SPECIFIC ACTIVITIES Develop, refine and apply tools and methodologies for high resolution modelling to improve weather and air quality forecasting, nowcasting and climate prediction Collect, assimilate and integrate consistent nationwide data on weather systems. Improve regional and national climate scenario analyses, including modelling weather and climate extremes Improve access to water, climate and air quality information for partners and Canadians as part of open science initiatives

4 EC Space Activities Science & Technology Operations Data Assimilation Nowcasting / Warnings Climate and Atmospheric Processes Numerical Weather Prediction Air Quality and Atmospheric Chemistry Cloud Physics and Severe Weather Sea Ice, Iceberg Monitoring and Forecasts SAR Winds Ecosystem Assessment and Monitoring Pollution Detection and Deterrence (ISTOP) Inland Waters ( water quality ) Environmental Emergency (VAAC) Coastal Sensitivity Mapping and Emergency Pollution Incident Preparedness

5 Supporting MSC Space Activities Weather Forecast, Nowcast and Warnings Numerical Weather Prediction (NWP) Regulations Aviation safety Integration of new datasets ADM_Aeolus, GPM, GOES R, EarthCare, Ticfire (CSA Microsatellite), PCW,

6 ARMP Capacity Observing infrastructure: Aviation and ground based instrumentation Enhanced data products development Exploitation of science data Space: support data characterization and cal/val, mission design and requirements definition, and data applications development Focus: scientific development supporting meteorological applications

7 Airborne studies at Environment Canada More than 30 years experience in flight operations and instruments design and installation: - NRC Convair NRC Twin Otter - NRC T-33 - NASA Twin Otter - NASA WB-57 - UoW King Air - NCAR C AWI Polar 5/6 - SAFIRE Falcon-20 UoW King Air NCAR C-130 NRC Twin Otter Polar 5 NASA WB-57

8 Airborne studies at Environment Canada 1. Support to aviation industry, developing airworthiness regulations AIRS( ) aircraft icing (SLD, Appendix C, O) HIAC/HIWC (2014) engine icing (Appendix D) 2. Remote sensing validation C3VP(2006) CLOUDSAT satellite validation GPEX(2012) radar validation AID3(2013) radar validation 3. Cloud processes, parameterization for cloud and climate models, weather prediction validations BASE(1994) climate implications of Arctic weather systems FIRE.ACE(1998) impact of Arctic Clouds on our climate CFDE(1995/98) forecast and mechanisms of freezing drizzle formation Hurricane (2000/03) extra-tropical transition of hurricanes and their impact on Atlantic Canada ISDAC(2008) cloud-aerosol interactions in Arctic clouds

9 Airborne studies at Environment Canada Cloud microphysical measurements NRC Convair 580 is the EC primary research platform Aerosol measurements Size distribution of cloud droplets Size distribution of ice particles Extinction coefficient Liquid Water Content Total Water Content Phase discrimination capability Radar measurements Lidar measurements Microwave radiometry Gust velocity State parameters Trace gases

10 Aircraft campaigns: cloud physics BASE 1994 (Convair 580), Inuvik FIRE ACE 1998 (Convair 580), Inuvik Cape Barrow ISDAC 2008 (Convair 580), Fairbanks Cape Barrow PAM ARCMIP 2009 (Polar 5), Resolute Bay Eureka Alert Station Nord Russian Drifting Station Longyearbyen Tromsoe TCFIRE 2014 (Polar 6), Resolute Bay Alert Inuvik

11 Ground based infra structure: Weather Radar

12 Goose Bay Field Campaign: precipitation and snow microphysics, fog, radiative fluxes, wind and turbulence, cloud boundaries, and thermodynamical profiles

13 Satellite validation - CloudSat CloudSat reflectivity product during one the of C3VP overpasses: C3VP Aircraft Underflight of CloudSat Detection by CloudSat of the aircraft downward pointing W band radar beam (CloudSat EM transmitter provided to NRC by CSA) Confirmation that the aircraft was under the satellite track at overpass time. On C3VP, we were successful 21/21 times at doing so.

14 CloudSat GEOPROF Validation: geolocating measurements from different sensors Left panels: cloud boundaries (CPR on CloudSat, CALIOP lidar on CALIPSO, aircraft Ka band radar, aircraft dual channel lidar, and aircraft temperature and humidity measurements) Right panel: comparison of the liquid water and ice water content from the CloudSat CWC product and the aircraft in situ sensors. Result: CloudSat underestimated the cirrus due to sensitivity, underestimated the liquid water in the middle supercooled cloud, and overestimated the low cloud extent due to sublimating ice crystals

15 Global Precipitation Measurement Mission GPM Goal: to provide instantaneous precipitation estimates from space, particularly for light rainfall and cold season solid precipitation GPM Flown at an altitude 407 kilometers in a non Sun synchronous orbit that covers the Earth from 65 S to 65 N GPM Microwave Imager: thirteen microwave channels ranging in frequency from 10 GHz to 183 GHz. Dual frequency precipitation radar (Kuband and Ka band Launch Date Feb. 27, 2014 Launch Site: Tanegashima Space Center, Japan

16 GPM orbits over Canada for a 10 day period. Iqaluit King City

17 The GPM Cold Season Precipitation Experiment (GCPEx 2011/12) A GPM pre launch physical validation experiment Designed to address shortcomings in GPM snowfall retrieval algorithm with: in situ data on microphysical properties in winter cloud systems associated remote sensing obs coordinated model simulations To characterize the ability of multifrequency active and passive microwave sensors to detect and estimate falling snow. Skofronick Jackson et al, 2014: Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow. Bull. Amer. Meteorol. Soc., in press.

18 GOES R Satellite Launch spring 2016 Operational spring 2017 Improvements (ABI) Increased spatial (4x) / temporal (5x) resolution 16 channels (2 vis, 4 near IR, 10 IR) ARMP Applications Convection nowcasting (e.g. icast) Fog nowcasting Field and case studies Limitations Arctic coverage is limited due to viewing angle

19 GOES R Lightning Mapper The Geostationary Lightning Mapper (GLM) will be on the GOES R satellite Allows optical detection of total lightning at high time resolution ARMP applications Severe thunderstorm nowcasting (e.g. icast) Convection nowcasting for aviation Comparison with SOLMA, CLDN and new lightning parameterization in HRDPS

20 ESA JAXA EarthCare mission Objectives: Direct: improve representations of cloud, aerosol, and radiation in global models Indirect: improve forecasts of weather and climate EarthCARE is a process mission whose aim is to improve representations of cloud, aerosol, precipitation, and radiation basic physics in global atmospheric models

21 EarthCare: EC Participation H. Barker (MRD) (~0.75 PY) Mission Advisory Group (MAG) member since 2005 co developer of EarthCARE simulator system lead for EarthCARE radiation studies J. Cole and M. Shephard (CRD) develop official radiative transfer + 3D scene construction algorithms software (Fortran90 codes) to ESA specifications Algorithm Theoretical Basis Documents (ATBDs) Software User Manuals (SUMs) Added value: the 3D radiation codes developed by EC for EarthCARE is being ported to EC s global prediction models.

22 Satellite support CloudSat: focused on validation under cold climate GPM: supporting refine requirements with pre campaign. Validation for Northern latitudes (over Canada) ADM_Aeolus: data characterization and validation over Canada. Supporting optimization of products for weather systems (assimilation) GOES R: Lightning data EarthCare: supporting missing design Ticfire: supporting instrument concept development and validation SnowSat: from the needs towards a solution

23 Summary To meet the challenge: move towards a view of an integrated observing system where satellite data is integrated by conception to other observing platforms towards generation of products that addresses the user needs Bridge with applications need to be an integral part of the observing system design: It supports optimization of requirements and guide the system implementation International collaborative approach is a must.

24 Backup slides

25 Summary Environment Canada Cloud Physics and Severe Weather Research Section supports MSC to: Optimize existent network; design and implement the next generation; Integrate new satellites data preparing for operational use; Develop the concept of an integrated observing system for the Arctic. Current interest in satellites: GPM (Precipitation): Validation of products and bridge integration into operational systems; ADM_Aeolus (Winds): support data characterization and optimizing product for weather assimilation systems; GOES R (lightning): validation and integration of lightning data into NWP systems; EarthCare (Radiation and cloud properties): support misison design and implementation; data cal/val and bridging to applications; Ticfire (Radiation): sensor design and validation, bridging to applications. To meet the challenge: move towards a view of an integrated observing system where satellite data is integrated by conception to other observing platforms towards generation of products that addresses the user needs Bridge with applications need to be an integral part of the observing system design: supports optimization of requirements and guide the system implementation International collaborative approach is a must.

26 Airborne studies at Environment Canada Cloud microphysical measurements Radar measurements Ka-band radar (vertical up/down) (EC) W-band / Dual pol./ Doppler / Vrt&Hrz (NRC) X-band / Dual pol. / Doppler / Vrt&Hrz (NRC) A ltitu d e ( k m ) Ka-band Hurricane Michael Longitude (deg) dbz W & X band radars

27 Airborne studies at Environment Canada Cloud microphysical measurements Airborne elastic lidar (Alpenglow Inc.) =355 m dual polarized zenith / nadir off-axis receiving aperture Phase discrimination capability EC/NRC lidars

28 Vertical Structure of Winter precipitation Z Lake Effect Height (km) Z Synoptic system Algorithm Considerations Vertical evolution of precipitation Horizontal advection for ground validation Skofronick Jackson et al, 2014: Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow. Bull. Amer. Meteorol. Soc., in press. Frequency Contours with Height of Radar Reflectivity Frontal Upper Trof Cyclone Lake effect Height (km) GPM MDS GPM MDS GPM Detectability of Snowfall is weather system dependent Reflectivity (dbz)