technological innovations in meteorology
TRANSCRIPT
Technological Innovations in MeteorologyDate 6th February 2014Date 6th February 2014
CONTENT
01 Introduction to Weather Services
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Hexagon’s contribution in Weather services
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GPS Meteorology and current networks
Accuracy and comparisons of GPS MET with conventional04
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Accuracy and comparisons of GPS MET with conventional
GPS MET Network details at IMD
06 Other Technologies
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Providing Weather services includes
• Measurement of Meteorological parameters at well distributed places with • Measurement of Meteorological parameters at well distributed places with accurate instrumentation which includes AWS having accurate meteorological sensors and data loggers, Weather radars, GPS based IWV measurements and many other modern techniques.IWV measurements and many other modern techniques.
• Developing, continuously verifying and modifying the weather models ( Numerical weather prediction).
• Use the effective models to do Weather forecasting( short term, medium term and long term forecasting)
• Use the Weather data and Geospatial data to make intelligent information in GIS compatible format
• Disseminating the Weather data and forecast to various users in different
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• Disseminating the Weather data and forecast to various users in different formats as desired for a particular user/application
Hexagon’s contribution in Weather Services
• Turnkey solution for estimating Integrated PrecipitableWater Vapour ( IPWV) content in the atmosphere.Water Vapour ( IPWV) content in the atmosphere.
• Integrated solutions in the field of Micrometeorological • Integrated solutions in the field of Micrometeorological measurements.
• Automatic Weather Stations• Automatic Weather Stations
• Data loggers and high end meteorological sensors
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• Why is it important to determine Integrated Precipitable Water Vapor (IPWV)?
• Water vapor is the main driver of atmospheric events.
• Significant changes in the horizontal and vertical distribution of water vapor• Significant changes in the horizontal and vertical distribution of water vaporcan occur rapidly during active weather.
• Improved short-term moisture observations mean improved forecasts of• Improved short-term moisture observations mean improved forecasts ofprecipitation and severe weather developments.
•Such forecasts impact decisions related to transportation, safety, agriculture,•Such forecasts impact decisions related to transportation, safety, agriculture,commerce, reservoirs, and flood mitigation projects.
•Concerned agencies in the India include IMD, Department of Science and
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•Concerned agencies in the India include IMD, Department of Science andTechnology, Ministry of Agriculture, Disaster Management group.
• What is the advantage of GPS-MET versus conventional methods to determine water vapor in the atmosphere?the atmosphere?
• Most moisture observations are made with weather balloons that• Most moisture observations are made with weather balloons thatare launched twice daily.
• Radiosondes are launched every day around the country. This is• Radiosondes are launched every day around the country. This isan expensive process and cannot provide data under severeweather conditions.
• GPS-based Meteorology is an all-weather system that is both costeffective and reliable.
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effective and reliable.
Atmospheric Delay• Dry delay (ZHD) is a result of the total mass of the
atmosphere. Wet delay is caused by the total
How do we calculate IPWV?
Atmospheric Delay
Ionospheric Delay Tropospheric Delay
atmosphere. Wet delay is caused by the totalamount of water vapor (IPWV) along the GPSsignal path.
• To calculate the delay, first the dry delay (ZHD) isIonospheric Delay Tropospheric Delay(ZTD)
Wet DelayHydrostatic (Dry) Delay
• To calculate the delay, first the dry delay (ZHD) iscalculated from surface measurements. Then drydelay is subtracted from the tropospheric delay(ZTD), yielding zenith wet delay (ZWD). The wetsignal delay maps into IPWV via a mappingWet Delay
(ZWD)Hydrostatic (Dry) Delay
(ZHD)signal delay maps into IPWV via a mappingfunction that is almost proportional to the meanvapor pressure weighted temperature of theatmosphere.
Current observation systems can determine the amount of moisture in the atmosphere with an accuracy of 3 to 5 mm. The goal of GPS-MET is to determine the moisture at the 1 mm level. This can be achieved with appropriate meteorological
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the 1 mm level. This can be achieved with appropriate meteorological instrumentation and analysis.
How Does the Atmosphere Effect the GPS Signal?• The largest signal delays come from the
ionosphere, the region of charged particles between 50 and 500 kilometers above the
480 km
between 50 and 500 kilometers above the Earth's surface.
• Since the ionosphere is a dispersive medium, the propagation velocity of radio waves is
80 km
the propagation velocity of radio waves is frequency dependent.
• If you form a linear combination of L1 & L2 (called L3), and you use L3 to calculate your
50 km
(called L3), and you use L3 to calculate your distances, you can virtually eliminate the ionosphere as a source of POS/NAV error.
• But if you measure the difference in arrival time 9-16 km
• But if you measure the difference in arrival time of L1 and L2, you can estimate the total electron plasma density (TEC) of the ionosphere for Space Weather Forecasting, since TEC is a
0 km
1
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Space Weather Forecasting, since TEC is a tracer for geomagnetic activity.
fTEC
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• The promise of GPS Meteorology to improve short-termweather forecasts has attracted world-wide attention.weather forecasts has attracted world-wide attention.
• The initial goal for most GPS networks was geodeticapplications. Over time, as GPS-MET techniques wereapplications. Over time, as GPS-MET techniques wererefined, many of these networks started co-locating a METpackage with GPS receivers.package with GPS receivers.
• A number of networks are in operation to focus on GPS-Meteorology including the USA, Germany and Japan.Meteorology including the USA, Germany and Japan.
• Indian Meteorological Department have already tested thesystem in last 6 years with 5 systems and is in process of
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system in last 6 years with 5 systems and is in process ofincreasing the network.
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• NOAA’s demonstration network has proven feasibility and is currently in operational use with around 400 stations.
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• SuomiNet has also proven feasibility.
Concerned Organizations in Japan:Concerned Organizations in Japan:• Universities• Geographical Survey Institute• Japan Meteorological Agency• National Astronomical Observatory• National Astronomical Observatory• Japanese Meteorological Research
Institute
• Japan has the most dense GPS network in the world with around 1,000 stations
• The GPS-MET project was launched in Japan in 1997 to use the existinggeodetic GPS network.
• Japan has the most dense GPS network in the world with around 1,000 stationsand an average spacing of 30 Km.
• For Integrated Precipitable Water Vapor calculations, the required density is100 Km.
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100 Km.
• Germany has a government operated GPS network of 200 stations with 50 Km spacing.
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• The network has been used for flash flood monitoring.
Current GPS Meteorology Applications
• Near Real Time Weather Forecasts• Flash Flood Monitoring• Flash Flood Monitoring• Long-Term Weather Studies
GPS Meteorology has the following present and future advantages:GPS Meteorology has the following present and future advantages:
•• GivesGives nearnear realreal timetime weatherweather forecastsforecasts..•• GivesGives nearnear realreal timetime weatherweather forecastsforecasts..
•• Delivers weather information in active weather when Delivers weather information in active weather when conventional systems are not effective.conventional systems are not effective.conventional systems are not effective.conventional systems are not effective.
•• Provides the total amount of Integrated Provides the total amount of Integrated PrecipitablePrecipitable Water Water Vapor above zenith. Vapor above zenith.
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Vapor above zenith. Vapor above zenith.
How Accurate is GPS IPW? 2000 ARM WVIOP PWV Summary
5.0
GPS vs. Sondes
3.5
4.0
4.5
5.0
Number of data points used = 114Mean difference = 0.07476Std. Dev of differences = 0.12344Correlation coefficient (r) = 0.99272Equation of linear best fit to data:
Y = 1.041080726 * X - 0.003357609039
2.5
3.0
3.5
sse
d G
PS
-PW
V (c
m)
1.0
1.5
2.0
Re
pro
ces
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0ARM Sonde PWV (cm)
0.0
0.5
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6.0
GPS & Radiosonde Comparisons
5.0
5.5
3.5
4.0
4.5
por
(c
m)
2.5
3.0
3.5
itabl
e
W
ater
V
ap
1.5
2.0Pre
cipi
0.0
0.5
1.0IHOP 2002 IPW Comparisons at Purcell, OK
GPSSonde (KOUN) at Norman, OKSonde at Purcell ARM CART Site
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133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175
DOY (2002)
0.0
Long-Term Comparison of GPS and Rawinsondes
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19961997
4
5
199719981999
3
4
IP
W
(c
m)
Sonde - GPS IPW 2
GP
S
Sonde - GPS IPW Comparisons ARM
SGP CART Site
Jan 1996 - Sep 19991
17 0 1 2 3 4 5 6
Sonde IPW (cm)
0
PWV vs actual Rainfall
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IPWV vs actual Rainfall
DryingLa Nina
El Nino
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NOAA Forecast Systems Laboratory NOAA Forecast Systems Laboratory 325 Broadway R/FS3
Boulder CO 80305
http://gpsmet.noaa.govhttp://gpsmet.noaa.gov
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Reference station NetworkSpider Network
Spider GUI Client
Spider Network
Spider ServerSite
Computer - ComputerComputer - GPS Sensor
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Computer - ComputerTransfer Database InformationSever / Client connection
Computer - GPS SensorTransfer of DataSensor ConfigurationStatus Info from Sensor
BLOCK DIAGRAM
Antenna
GPS RECEIVER
MET3
AntennaAX1202
PC
SPIDER S/WGPS RECEIVER
MET3
AntennaAX1202
PC
Modem Modem
RECEIVERGRX1200 SPIDER S/WRECEIVER
GRX1200 SPIDER S/W
PC(ftp Server)GAMIT S/W
+NOAA SCRIPTS&S/W
+NOAA SCRIPTS&S/W
Modem
GPS MET3
AntennaAX1202
PCMET3
AntennaAX1202
PC
ModemModem
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GPS RECEIVERGRX1200
PC
SPIDER S/WGPS RECEIVERGRX1200
MET3PC
SPIDER S/W
BLOCK DIAGRAM
RINEX file creationafter every 1 hour
SITE PC
ftp push to ftp server
Server download datafrom all sites includingrapid orbits, pole files etc.
Data processing using GAMIT
CENTRALPROCESSING CENTER
IPWV computation and presentation usingNOAA software
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Standard GPS-Met NRT Products
Blacksburg, VABlacksburg, VA
Data from RNK UA Site
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Automatic Weather Station
25Basic Automatic Weather Station is shown in above picture.
Micrometeorology Tower
26 50 meter tower based Micrometeorology Station is shown in above picture.
AWS components
• Data Acquisition System/ Data Loggers
• Air Temperature & Relative Humidity Sensor
• Wind Speed & Wind Direction Sensor
• Rain Gauge Sensor
• Solar Radiation Sensor• Solar Radiation Sensor
• Barometric Pressure Sensor
27• And many more
Advanced Equipment
• Ceilometer: for Cloud Height Measurement on LIDAR Principal.
• Present Weather Sensor: for • Present Weather Sensor: for measurement of different parameters of precipitation Like, particle size, velocity, Intensity and precipitation type.
• Doppler Weather Radar
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