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© Crown copyright Met Office
GNSS and Weather Forecasting
Dr Jonathan Jones, UK Met Office GfG2 Summer School 2013, GFZ, Potsdam
© Crown copyright Met Office
Contents
• Meteorological observing systems
• GNSS-meteorology in Europe
• Meteorological applications:
• Numerical Weather Prediction models
• Forecasters
• Climate
• Future developments
Met. Observing Systems
Some of the obs. used in making the analysis: Surface pressure, radiosondes, aircraft data, satellite radiances, satellite clouds and winds, wind profiler radars, buoys, ships, radar data, etc.
Aircraft data - Ascending, descending, and cruising obs. of wind speed, wind direction and temperature
Data assimilation system provide ”Analysis”
(=initial conditions) Numerical weather
prediction model
Observations Boundary values from external
model
Old model state
Computer generated forecast products
Forecasts by forecasters
Non-global NWP System
© Crown copyright Met Office
Global Model:
25km
4D-VAR
NAE Model:
12km
4D-VAR
UK Models:
1.5km
3D-VAR
NWP Models (UK Met Office)
Number of obs. ~10,000 –> 1M Number of model variables ~100M –> 1B We need more observations !!
Timeline of European GNSS-Met Projects
1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
Today
COST Action GNSS4SWEC
E-GVAP
E.C. supported TOUGH Project
COST Action 716
E.C. supported MAGIC Project
E.C. supported WAVEFRONT Project
© Crown copyright Met Office
Current Status in Europe (E-GVAP)
• Project focusing on GPS-only hourly processing, delivering only Zenith Total Delay (ZTD) in 90mins
• Operational assimilation at a few Euro National Met Services, many others under testing. Use of ZTD has a positive impact on NWP forecast skill
• ~1800 European sites’ delivering >12M ZTDs per month
• Surface T and P used for conversion to Integrated Water Vapour (IWV)
• GPS IWV has been used in research experiments for more than 10 years
• Data monitoring and Quality Checking in place (+improving)
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Data Outputs
• ASCII COST716 format for scientific use
• Binary ‘BUFR’ format for NWP assimilation
• Water vapour maps and animations made available to the forecasters and for case studies
• High quality reprocessed data available for climate applications
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Customers of the Data
• NWP
Assimilation impact trials show positive impact (in precipitation forecasts and also cloud cover and surface temperature)
• Forecasters
GNSS WV images give more detail than satellite WV. Useful for forecasters especially in unstable, high humidity convective conditions.
• Climate
Data potentially of great use to climate community but still in its infancy (+time consuming reprocessing is necessary)
© Crown copyright Met Office
ZTD to ZWD
• Dry component of delay, ZHD is modelled a-priori in GPS processing using a model such as Saastamoinen:
• The Zenith Wet Delay (ZWD), is simply the difference between ZTD and ZHD, i.e.
( )rsrs hhPP −−= 119.0
( ) ( )( )[ ]100028.02cos00266.010022768.0 −−−= ss hPZHD φ
ZWDZHDZTD +=
© Crown copyright Met Office
ZWD to IWV
• If surface temperature is known ZWD can be converted to Integrated Water Vapour (IWV)
• Which reduces to:
dzTRk
dzRkRkZWDrr z
wwz wdw ∫∫
∞∞ −− +−=ρ
ρ 3612
6 10)(10
IWVTR
kRkRkZWDm
wdw )(10 312
6 +−= −
© Crown copyright Met Office
NWP Observation Operator
∫∞=
=
−=z
z
NdzZTD0
610
2321
Tpk
Tpk
TpkN vdd ++=
2Tbp
TapN v+=
Bevis et al. 1994
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Observation Operator
))(exp( 11 levellevellevellevel zzcNN −−= ++
1
1ln
+
+
−
⎟⎟⎠
⎞⎜⎜⎝
⎛
=levellevel
level
level
zzNN
c
))exp())(exp(exp(10 161
levellevellevellevellevel
level czczczcNZTD −−= +
−+
© Crown copyright Met Office
• NWP is better at estimating ZHD than ZTD.
• Assimilation of GNSS ZTD provides information on atmospheric water vapour.
Information Content
NWP ZTD Bias
NWP ZHD Bias
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Factors affecting GNSS ZTD Data Assimilation
• Station lists (whitelist vs. blacklist)
• Bias Correction (site and AC specific)
• Height difference correction
• Spatial and temporal thinning (useful in coarse models and regions where too many obs.)
• Observation errors
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NWP Impact Study, KNMI, 2010
• Precipitation in KNMI HIRLAM model with no GNSS assimilation
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NWP Impact Study, KNMI, 2010
• Precipitation from weather radar observations
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NWP Impact Study, KNMI, 2010
• Precipitation in KNMI HIRLAM model with GNSS assimilation
• Note - much better precipitation forecast over Dutch region
37
Impact on Meteo France AROME forecasts
Accumulated rainfall between 03UTC and 15UTC, 19 July 2008
WITHOUT ZTD data assimilation
AROME, 15h forecast starting from the 00UTC analysis, 19 july 2008
WITH ZTD data assimilation
Observations
15/06/2010 – 06UTC
AROME_WMED (D031) OBS (24h accumul.) AROME_WMED (D03Q)
Old white list New white list Rain gauge obs.
Impact on Meteo France AROME forecasts
GNSS improves location of rainfall
15/06/2010 – 09UTC
OBS (6h Accumul.)
195mm/6hr
AROME_WMED (D03Q)
130mm/6hr New white list
AROME_WMED (D031)
Old white list Rain gauge obs.
GNSS improves severity of rainfall
Impact on Meteo France AROME forecasts
© Crown copyright Met Office
Latest UK Impact Trials
• 41 day trial – July 2011
• 4km 3D-VAR
Control Trial 1 Trial 2 Trial 3 Assimilation as normal for operational model (observation error = 6mm)
ZTDs not assimilated
ZTD observation error = 9mm
ZTD observation error = 12mm
3.2% increase in Tsurface RMS error
1.2% increase in Tsurface RMS error
1.5% increase in Tsurface RMS error
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Latest UK Impact Trials
• 6 hour precipitation accumulation
• Yellow = Trial 1
• Green = Trial 3
• Blue = Trial 2
• Red = Control
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Latest Global impact trials
• 41 day Summer trial, 41 day Winter trial
• 40km horizontal resolution
Control Trial 1: Winter 2012 Trial 2: Summer 2012
Assimilation as normal for operational model (observation error = 9mm)
Observation error = 15mm
Observations from GOPG and METG added
Observation error = 15mm
Observations from GOPG and METG added
Zero impact on average 2% decrease in RMS errors across various parameters.
Improvements seen almost entirely in southern hemisphere and tropics
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Latest Global Impact Trials
Standard deviation of the difference in ZTD over ten months
σGOPG ZTD - NWP ZTD and σGOPG ZTD - IGS REPRO ZTD
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24th June 2005 Case Study
• Synoptically forced event with wide spread thunderstorms throughout Southern UK and the Midlands, flash flooding etc
• Trough progressing over southern UK from westerly direction with associated high IWV and convective thunderstorm cells
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Weather radar
• Traditional image to forecaster showing line of storms progressing over Southern UK
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GPS Water Vapour Animation
• GPS IWV identified ‘cold pool’ behind front which perpetuated instability and aided further convection
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28th July 2005 Case Study
• Low pressure system centred over S. Irish Sea
• Winds generally southerly
• High IWV and tornado in Birmingham at ~13:15
• High areas of IWV tracks East (not with prevailing wind direction) and second tornado in Peterborough at ~17:00 under sharp IWV gradient
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28th July 2005 Case Study
6.2micron Meteosat 8 water vapour image, 18:00UTC 28th July 2005
GPS Water Vapour plot, 17:30, 28th July 2005. White line on plot is manually drawn extent of dry intrusion
© Crown copyright Met Office Drier Upper Air
28th July 2005 Case Study
Dry tongue over South East not corresponding with satellite WV By combining satellite and ground based GPS water vapour you can infer dry intrusion is slanting giving added value to forecasters
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New Meteo Requirements
• New hi-res NWP models require ZTD with improved timeliness and greater spatial and temporal resolution (e.g. Met Office UKV 1.5km)
• Advanced GNSS products desired for obtaining more information about troposphere (vertical resolution of water vapour, azimuthal anisotropy etc.)
• Real-time processing would greatly increase the usefulness of GNSS products for nowcasting.
• Climate community only now starting to use GNSS tropospheric products (e.g. Hadley Centre)
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Recent GNSS Developments
• More GNSS constellations (GPS + GLONASS, Galileo etc…) = new geometries, increased number of observations
• Real-time raw data streaming
• R&D advanced tropospheric products (slants, gradients, tomography etc.)
• Single frequency processing
• Long-term, homogenised GPS products available (IGS/EPN/CODE/others), valuable for climate analysis ?
ES1206: Advanced GNSS Tropospheric Products for monitoring Severe Weather Events and Climate
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• 4 year COST Action May 2013 – May 2017
• 25 COST countries participating (+5 non-COST)
• 80+ participants from 50+ institutes, 3 WGs
• COST supports:
• Management Committee and Working Group meetings
• Scientific workshops
• Short Term Scientific Missions
• Training Schools
• Publications, website, public outreach
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Main Objectives of GNSS4SWEC
• Coordinate the development of new multi-GNSS solutions and assess the benefit to meteorology and climate analysis
• Assess the potential of new GNSS products for use in nowcasting and rapid cycle NWP
• Determine the added value of the re-processed GNSS tropospheric data to the current state-of-the-art climate research
• Establish a database of reference tropospheric solutions to validate reprocessed GNSS ZTD/IWV against climate quality data from a range of other instrumentation
• Stimulate the exploitation of atmospheric data as an input to improve Real-Time GNSS positioning and navigation
• Standardize the conversion of ZTD to IWV
• Stimulate exchange of data and expertise in the field of GNSS Meteorology
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Questions and answers [email protected] http://egvap.dmi.dk/
http://www.cost.eu/domains_actions/essem/Actions/ES1206