A Report to the WWRP Working Group on Nowcasting Research, 9 February 2011

Science of Nowcasting Winter Weather for Vancouver 2010 (SNOW-V10)

by

George Isaac

Cloud Physics and Severe Weather Research SectionEnvironment Canada

Presentation Shortened to Remove Material Still Under Review

Conclusions Remain the Same

Acknowledgements

Paul Joe1, Jocelyn Mailhot2, Monika Bailey1, Stephane Bélair2, Faisal Boudala1, Mindy Brugman4, Edwin Campos1, Richard Carpenter3, Stewart Cober1, Bertrand Denis4, Chris Doyle4. Doug Forsyth5, Ismail Gultepe1, Thomas Haiden6, Ivan Heckman1, Laura Huang1, Jason Milbrandt2, Ruping Mo4, Roy Rasmussen7, Janti Reid1, Trevor Smith4, Ron Stewart 8, and Donghai Wang9

1 Cloud Physics and Severe Weather Research Section, Environment Canada2 Recherche en prévision numérique, Environment Canada3Weather Decision Technologies, Oklahoma, USA4 Meteorological Service of Canada, Environment Canada5National Severe Storms Laboratory, Norman, Oklahoma, USA6Central Institute for Meteorology and Geodynamics (ZAMG), Austria7 National Center for Atmospheric Research, Colorado, USA8 Department of Environment and Geography, University of Manitoba9Chinese Academy of Meteorological Science, China

Main Goals of SNOW-V10Related to Nowcasting in Complex Terrain

(Developed at March 08 Workshop)

• To improve our understanding and ability to forecast/nowcast low cloud, and visibility;

• To improve our understanding and ability to forecast precipitation amount and type;

• To improve forecasts of wind speed, gusts and direction;

• To develop better forecast system production system(s).

• Assess and evaluate value to end users;• To increase the capacity of WMO member

states (Training component).

Participating GroupsObserving Systems and Associated Nowcast Systems

EC Region OAN Sites EC Research Sites UBC (McKendry) and U. Manitoba (Stewart) NCAR WSDDM System + (Rasmussen) BOM STEPS System (Seed) NSSL Radar (Forsyth) FMI (Koistinen) Modeling Systems EC Research Models WDT (Carpenter) China (Donghai Wang) Austria INCA (Haiden) Germany (Bott) Switzerland (Mueller)Verification EC Team NCAR (Brown)

Others:

CSU (Chandra & Vaisala)

U. Washington (House)

The Winter Olympic Challenge

Steep topography, highly variable weather elements in space and time

5 km

Village Creekside

Cypress Mountain

Summary of Instruments• Callaghan scanning C-Band Radar located near Whistler. • NOAA/OU X-Band Dual- Polarization Radar located at Canada/U.S. Border south of Vancouver. • Vertically Pointing X-Band Radars were located at TFT, RND and WWA.• A 915 MHz Boundary Layer Wind Profiler located at Squamish Airport (WSK).• A profiling microwave radiometer located at Timing Flats (TFT)• A rawindsonde system located at Nesters (VOC).• Ceilometers located at YVR, WWA, TFT, WSK, WGP, and VOG, • Recording visibility meters located at VOA, VOL, RND, VOT, VOG and YVR. • Hot Plates located at YVR, VOG, RND, VOA, VOL and TFT • Present weather sensors, either the Vaisala FD12P, Parsivel or POSS located at VOA, VOL, VOD, WWA,

WSK, YVR, TFT, VOT, RND, and VOG, • A 3D anemometer located at the ski jump (VOW). • Temperature, relative humidity and GPS sensors were installed on the Whistler Village to Roundhouse

Gondola, and the Whistler to Blackcomb gondola.• The Roundhouse site, near the helipad, was instrumented with a significant list of equipment. as an

extension of the Fog Remote Sensing and Modeling Project (FRAM) (Gultepe et al., 2009).• Special surface sites measuring temperature and humidity were installed by UBC up Whistler Mountain • Snow Density measurements were made at some selected sites, mainly VOA, VOL RND and VOC after

significant snowstorms.• Snow Photographs were made continuously at RND as a special project during some intensive periods and

then irregularly outside those periods. •  

Whistler Peak Looking East Towards the Telecomm Tower

Roundhouse Helipad Site (RND)

FD12P MRR VRG GEONOR K-Z Solar Radiation Wind LPM Parsivel 3D Anemometer Sentry Vis FMD YorkU PC TPU SFC Radiometer 4X SW IR Radiation/Surface Radiatioin WXT Aerosol TPU Icing Detector

GCIP

DMIST

VOAThree Platforms

SNOW-V10

OAN

WhistlerMaintenance

VOA (Pig Alley)Precipitation Occurrence Sensing System (POSS)-X Band, Continuous Wave Radar-Large sample volume-Present weather, precipitation type and intensity-Doppler Spectrum, Drop Size Distribution

Parsivel - Laser-imaging system,particle shadows- Present weather, precipitation type and intensity- Doppler Spectrum, Drop Size Distribution-Visibility due to precipitation reported

Hot Plate – heated top/bottom surface-Designed for snowfall precipitation measurements-Wind

Vaisala FD12P – laser scattering system- Present weather, precipitation type and intensity- Doppler Spectrum, Drop Size Distribution- Visibility

All 1 minute (1 and 1)!

VOL Mid-station/Raven’s Nest

Harvey Fellowes

VOB(No Power, 15/1 min data)

Timing Flats

Timing Flats (VOT)

Ceilometer 25K, (also CL31 – aerosol mode) Radiometer Parsivel OAN (1 min) POSS MRR

Move in summer

Whistler Village Gondola (WVG)

Local Beer Company

1 degree

P2P (Peak to Peak)

Snow PhotographyMcGill UniversityU Manitoba

Need to help develop higher accuracy radar retrievals.

Network Radar Coverage

100 km

NSSLXBandDualPol

Whistler Radar

Whistler Doppler Weather Radar

Blocked flow (downslope winds)means Intenseprecipitation is on the slope and not on mountain peak

Doppler velocity: Blue means air is moving to the left or downslope

Precipitation: the intense precipitation is on the slope.

EC OANSquamish Airport LAP-3000 Wind Profiler co-located withFull compound autostation.

Site also had Remote Video System and Automatic Weather Station

Wind Profile for 12 hours duration.

Normally, just 1 profile with radiosondes.

Considerable structure within 12 hours.

Model Name Organization Country Spatial Resolution

Temporal Resolution Available

Times of Day Run (UTC)

Length of Forecst (hours)

General Description

ABOMLAM1km Environment Canada Canada 1 Km 15 min Every 15 min Max 6 h

Adaptive Blending of Observation and Models

using GEM LAM1k

ABOMREG Environment Canada Canada 15 km 15 min Every 15 min Max 6 h

Adaptive Blending of Observation and Models

using GEM Regional

INTW Environment Canada Canada 1 and 15

km 15 min Every 15 min Max 6 hINTegrated Weighted

Model using LAM1k, GEM Regional and Observations

LAM1k Environment Canada Canada 1 km

30 s (Model), 15 min

(Tables)

11 and 20 UTC 19 h Limited-Area version of

GEM model

LAM2.5k Environment Canada Canada 2.5 km

1 min (Model), 15 min (Tables)

06 and 15 UTC 33 h Limited-Area version of

GEM model

REG Environment Canada Canada 15 km

7.5 min (Model), 15 min (Tables)

00, 06, 12, 18 UTC 48 h

Regional version of GEM (Global Environmental

Multiscale) model

Canadian Models Used in SNOW-V10

Model Name Organization Country Spatial Resolution

Temporal Resolution Available

Times of Day Run (UTC)

Length of Forecst (hours) General Description

CMAChinese

Meteorological Administration

China 15 km & 3 km 1 hour 00 and 12 UTC 48 h & 24 h CMA GRAPES-Meso NWP model

WDTUSL

Weather Decision

Technologies and

NanoWeather

USA pointwise or 100 m grid 02, 08, 14, 20 UTC 48 h

Surface layer model nested in NAM. Works particularly well in

quiescent condistions..

WSDDM

National Center for Atmospheric

Research (NCAR)

USA Radar Resolution

10 min (based on

radar update)

Every 10 min 2 hours

Nowcast based on storm tracking of radar echo using cross correlation and real-time calibration with surface

precipitation gauges.

ZAMGINCA

Central Institute for Meteorology

and Geodynamics

(ZAMG)

Austria 1 km 1 hour Every hour 18 hours

The Integrated Nowcasting Through Comprehensive Analysis (INCA) system uses downscaled ECMWF forecasts as a first guess and applies corrections according

to the latest observation.

ZAMGINCARR

Central Institute for Meteorology

and Geodynamics

(ZAMG)

Austria 1 km 15 min Every 15 min 18 hours

The precipitation module of INCA combines raingauge and radar

data, taking into account intensity-dependant elevation effects. The

forecasting mode is based on displacement by INCA motion

vectors, merging into the ECMWF model through prescribed

weighting.

Other Countries Models Used in SNOW-V10

Products During Olympics• Each group produced a Table showing 24 hour forecast

of significant variables for main venue sites (hourly intervals and 10 to 15 min intervals in first two hours). Similar to what forecasters produce

• A Research Support Desk was run during Olympics and Paralympics (virtual and on-site) providing real time support to forecasters.

• A SNOW-V10 Web site was created with many of the products (time series for sites, remote sensing products, area displays, soundings (gondola and others), and a very successful Blog.

VANOCChris Doyle

Central Forecast OfficeTrevor Smith et al.

Venue ForecastersCypress FreestyleCallaghan Nordic

Callaghan Ski JumpWhistler AlpineWhistler Sliding

SNOW-V10Research Support Desk (RSD)

On-Site (3 scientists)WebEx (at least once per day)

SNOW-V10 Web SiteSNOW-V10 Blog

1 min Data from Research SitesWhistler Radar

Microwave RadarMRR

Wind ProfilerGondola Profiles

Model and Data ChartsForecast Tables

Nowcastsetc

Pacfic Weather Centre Data15 Min DataSoundings

MeteogramsSatellite Data

Other Model Data

Harvey’s Cloud

Equipment on Whistler mountain provided good data for forecasters and help in understanding weather processes

Most of SNOW-V10 data from instruments are now being displayed on Web site (http://www.snow-v10.ca). Model data is also being shown.

Remote Sensors

Weather Decision Technologies (WDT) Products for Vancouver 2010

INCA (Integrated Nowcasting through ComprehensiveAnalysis) developed at the Austrian national weather service

Products were available in real time for forecaster use and evaluation

Adaptive Blending of Observations and Model (ABOM): What is it how does it work

• Statistical method for generating point forecasts using model and observation data

• The current observation + a weighted combination of forecasts from three different methods:

1) Extrapolation of the current observation trend

2) The change predicted by a model forecast

3) Observation persistence • The weights are determined from recent history

and are updated every 15 minutes with new observation data (an hour was used in the studies here)

Background of INTW

• INTW refers to integrated weighted modelINTW refers to integrated weighted model

• LAM 1k, LAM 2.5k and REG 15k were selected to generate INTW

• Major steps of INTW generationMajor steps of INTW generation– Data pre-checking - defining the available NWP models and

observations

– Extracting the available data for specific variable and location

– Calculating statistics from NWP model data, e.g. MAE, RMSE

– Deriving weights from model variables based on model performance

– Defining and performing dynamic and variational bias correction

– Generating Integrated Model forecasts (INTW)

min max

2/24/10 6:00 Wet snow/fog 0 -0.6 96 SE 0 0 0.2 0.5 1 1 0 02/24/10 7:00 Wet snow/fog 0 0 100 SE 1 3 0.2 0.5 2 3 0 02/24/10 8:00 Wet snow/fog 0 0 100 SE 1 3 0.2 0.5 2 5 0 02/24/10 9:00 Wet snow/fog 0 0 100 SE 1 3 0.2 0.5 2 7 0 0

2/24/10 10:00 Wet snow/fog 1 1 100 SE 1 3 0.5 1 2 9 0 02/24/10 11:00 Drizzle/fog 1 1 100 S 1 3 0.5 1 0 9 0 02/24/10 12:00 Drizzle/fog 1 1 100 S 2 4 0.5 1 0 9 0.2 0.22/24/10 13:00 Drizzle/fog 1 1 100 S 2 4 0.5 2 0 9 0.2 0.42/24/10 14:00 Cloudy/Some fog 2 2 100 SW 2 4 0.5 2 0 9 0.2 0.62/24/10 15:00 Cloudy/Some fog 2 2 100 SW 2 4 0.5 2 0 9 0.2 0.82/24/10 16:00 Cloudy/mist 2 2 100 SW 2 4 0.5 2 0 9 0.2 12/24/10 17:00 Cloudy/mist 2 2 100 SW 2 4 0.5 2 0 9 0.2 1.22/24/10 18:00 Occasional rain 2 2 100 SW 2 4 0.5 5 0 9 0.5 1.72/24/10 19:00 Occasional rain 2 2 100 SW 2 3 0.5 5 0 9 0.5 2.22/24/10 20:00 Occasional rain 2 2 100 SW 1 3 0.5 3 0 9 0.5 2.72/24/10 21:00 Occasional rain 2 2 100 S 1 3 0.5 3 0 9 0.5 3.22/24/10 22:00 Rain/wet snow 2 2 100 S 1 3 0.5 3 0.5 9.5 1 4.22/24/10 23:00 Wet snow/fog 1 1 100 S 1 3 0.5 3 1 10.5 0 4.22/25/10 0:00 Wet snow/fog 1 1 100 S 1 3 0.5 3 1 11.5 0 4.22/25/10 3:00 Wet snow/fog 1 1 100 S 1 3 0.5 3 1 12.5 0 4.22/25/10 6:00 Wet flurries 1 1 100 S 1 3 1 5 0.5 13 0 4.22/25/10 9:00 Wet flurries 1 1 100 S 2 4 1 5 0.2 13.2 0 4.2

2/25/10 12:00 Mainly cloudy 2 1 93 SE 3 6 2 10 0 13.2 0 4.22/25/10 15:00 Mainly cloudy 2 1 93 SE 4 8 5 10 0 13.2 0 4.22/25/10 18:00 Mainly cloudy 3 1 87 SE 5 10 5 10 0 13.2 0 4.22/25/10 21:00 Cloudy 4 0 75 SE 6 11 10 10 0 13.2 0 4.22/26/10 0:00 Rain 3 1 87 SE 7 12 4 8 0 13.2 1 5.2

Snow past 3 hours Rain past 3 hoursafter midnight day 1 after midnight day 1

Forecast for Cypress Freestyle/Snowboard bottom, Issued:

Date (m/d/y) & Time(PST)

Temperature (Celsius)

Dew point (Celsius)

Relative Humidity

(%)Average wind speed (m/s)

February, 24 2010 at 600 PST

Visibility (km)Wind direction

Rain past hour * (mm)

Elevation: 960 m

Snow past hour * (cm)

Weather/Sky Condition

Gust wind speed (m/s)

Accumulated rain (mm)

Accumulated snow (cm)

Summary and Future …1• Many physical processes were well documented during SNOW-V10 such

as: diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, precipitation reductions and increases due to local terrain influences, etc

• Weather changes rapidly in complex terrain and it is necessary to get good measurements at time resolutions of at least 1 -15 min. SNOW-V10 attempted to get measurements at 1 min resolution where possible.

• Because of the rapidly changing nature of the weather, weather forecasts also must be given at high time resolution.

• There are many difficulties in measuring parameters, especially precipitation amount and type in this environment. Special scanning strategies were necessary for the scanning radar placed at Whistler and significant differences were observed with many different types of surface precipitation sensors placed at several locations.

Summary and Future …2• SNOW-V10 has made progress in forecasting “non traditional”

variables like ceiling, visibility, wind gusts, etc.• Nowcast schemes are showing skill.• There is value in presenting real-time obs and several models to

forecasters doing Nowcasting.• The techniques tested are not yet good enough to issue standalone

nowcasts. Significant errors exist of high impact events that require forecaster intervention.

• Weather Forecasts, both long and short term, were critical in the conduct of these games, both long term and short term.

• Statistical verification of models and nowcasts are continuing.• Papers are being written on SNOW-V10 data. • At the 4th SNOW-V10 Workshop held in Huntsville, north of Toronto,

11-14 January, with 35 participants, it was decided to prepare a special issue of Pure and Applied Geophysics (Pageoph) with a deadline of 1 October 2011 for submission of papers. 31 tentative titles have been received.

• The idea of a forecaster training workshop is being explored.

Questions?