Radar and Lidar Sensor for Precipitation Method Measurement
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GROUP MEMBERS:
Khairil Ali MizamAzierahNurul AthirahEmiliaNur Ritasha
REMOTE SENSINGTECHNIQUES FORPRECIPITATION
MEASUREMENTUSINGRADAR/LIDAR
SENSOR
REMOTE SENSINGFOR HYDROLOGYAND WATER
RESOURCES
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RADAR SENSOR FOR
PRECIPITATIONMETHOD
MEASUREMENT
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Sense precipitation by using electromagnetic
radiation (examines inside of the cloud) Wavelength: 3cm10cm microwave pulse (large
cloud water droplets, raindrops, hail, snow particles,and other solid forms of precipitation reflect emittedradiation)
Sends out signals into the atmosphere. If anyprecipitation is present, the radar signal scatteredback to the RADAR transmitter (also called RADARechoes) used to produce RADAR images.
The precipitation intensity is measured by the
strength of the echo in the units of decibels dbZ.Larger/numerous particles reflect waves with greaterintensity than smaller/fewer particles.
An image showing precipitation intensity is called a"reflectivity image."
Basic Concept
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Sensing Precipitation & CloudsWith RADAR
Principles:
Use a relationship between radar reflectivity
factor Z (or Ze) and the rainfall rate, Rr(mm/hour) in the form (called Z-Rrelationships)
Where A and b are constants depending onthe type of rains.
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Sensing Precipitation & CloudsWith RADAR (cont)
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TROPICAL RAINFALLMEASURING MISSION(TRMM)
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BACKGROUND
Joint mission between NASA and theJapan Aerospace Exploration Agency
(JAXA).
Launched on November 27, 1997 fromTanegashima, Japan
Designed to monitor and measure rainfall
which covers tropical and sub-tropicalregions of the earth.
TROPICAL RAINFALLMEASURING MISSION(TRMM)
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SPECIFICATIONS
Orbit: 350 km
Inclination Angle: 35
Non-sun-synchronous
Revisit Frequency: 11-12 hours
Track Speed: 6.9 km/s
Area covered: 35N to 35S
TROPICAL RAINFALLMEASURING MISSION(TRMM)
Reference: TRMM 2009
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INSTRUMENTS ON BOARD
TRMM Microwave Imager (TMI)
Precipitation Radar (PR)
Visible and Infrared Scanner (VIRS)
Cloud and Earths Radiant Energy System(CERES)
Lightning Imaging Sensor (LIS)
TROPICAL RAINFALLMEASURING MISSION(TRMM)
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TRMM MICROWAVE IMAGER
(TMI)
9-channel passive microwave radiometer
Frequencies: 10.65, 19.35, 21.3, 37, 85.5 GHz
Horizontal and vertical polarizations Reads rainfall, water vapor, and cloud
water
Scan Geometry
Swath: 758.5 km Off-nadir: 52.8 Incident Angle
Conical Scan: 130
TROPICAL RAINFALLMEASURING MISSION(TRMM)
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PRECIPITATION RADAR (PR)
Active Rain Radar
Frequency: 13.8 GHz
Scan Geometry:
Nadir
Spatial Resolution: 4.3 km
Range Resolution: 250 m
Swath: 215 km
TROPICAL RAINFALLMEASURING MISSION(TRMM)
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VISIBLE INFRARED SCANNER
(VIRS)
5-channel visible and infrared passiveradiometer
Wavelengths: 0.6-12m Reads brightness and temperature
Scan Geometry
Swath: 720 km
IFOV: 2.11 km nadir Radiometric Properties:
Channels 1 and 2 read solar energy
Channels 3-5 read thermal energy
TROPICAL RAINFALLMEASURING MISSION(TRMM)
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TROPICAL RAINFALLMEASURING MISSION(TRMM)
TROPICAL RAINFALL
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TRMM precipitation radar
TROPICAL RAINFALLMEASURING MISSION(TRMM)
GLOBAL PRECIPITATION
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GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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BACKGROUND International network
of satellites that
provide the next-generation globalobservations of rainand snow data forevery three hours.
Joint mission betweenNASA and JAXA(Japan AerospaceExploration Agency).
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
Illustration of the GPM satelliteconstellation.
GLOBAL PRECIPITATION
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SPECIFICATIONS
Orbit: 407 km
Inclination Angle: 65
Non-sun-synchronous
Revisit Frequency: 3 hours
Track Speed: 7.2 km/s
Area covered: Entire globe
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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GPM MICROWAVE IMAGER
(GMI)
13-channel passive microwaveradiometer
Frequencies: 10-183 GHz Horizontal and vertical polarizations
New high frequency channels toimprove ice and snow measurements
Reads rainfall, water vapor, cloudwater, ice and snow
Scan Geometry
Swath: 885 km
Off-nadir: 52.8 Incident Angle
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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DUAL FREQUENCY RADAR (DFR)Active Rain Radar operating at two frequencies
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
Frequency: 13.8 GHz(KuPR)
Scan Geometry:
Nadir
Spatial Resolution: 5 km
Range Resolution: 250m
Swath: 215 km
Frequency: 35.5 GHz(KaPR)
Scan Geometry:
Nadir
Spatial Resolution: 5 km
Range Resolution: 250 -500 m
Swath: 245 km
Data collected from the KuPR and KaPR units will provide 3-Dobservations of rain and will also provide an accurate estimation
of rainfall rate
GLOBAL PRECIPITATION
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GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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APPLICATIONS
Precipitation Monitoring
Flood and Landslide Potential
Global Climatology
Tropical Storm Monitoring
Fire Detection
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
GLOBAL PRECIPITATION
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PRECIPITATION
MONITORING
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
Reference: TRMM 2009
FLOOD
POTENTIAL
Reference: TRMM 2009
GLOBAL PRECIPITATION
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LANDSLIDE
POTENTIAL
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
Reference: TRMM 2009
TROPICAL STORM
MONITORING
Reference: TRMM 2009
GLOBAL PRECIPITATION
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FIRE MONITORING
GLOBAL PRECIPITATIONMEASUREMENT (GPM)
Reference: TRMM 2009
TRMM VS GPM
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TRMM VS GPM
TRMM vs. GPM
General TRMM GPM
Orbit Altitude 350 km 407 km
Inclination Angle 35 65
Revisit Frequency 11-12 hrs 3hrs
Track Speed 6.9 km/s 7.2 km/s
Coverage Tropics Global
Microwave Imager
Swath 758.5 km 885 km
Incident Angle 52.8 52.8
Number of Channels 9 13
Precipitation RadarSwath 215 km 245 km
Number of Channels 1 2
Spatial Resolution 4.3 km 5 km
Range Resolution 250 m 250, 500 m
CONCLUSION
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TRMM data greatly expanded knowledgeof global hydrology but it is limited incoverage area
Errors associated with TRMM data
GPM provide more frequent andaccurate data with better technology. Italso expand the coverage area fromArtic Circle to Antartic Circle.
CONCLUSION
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LIDAR SENSOR FOR
PRECIPITATIONMETHODMEASUREMENT
JOURNAL (LIDAR)
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Lidar-Based Estimation of Small-
Scale Rainfall: Empirical EvidenceBy: P.ALewandowski et al.
From: JOURNAL OF ATMOSPHERIC AND OCEANICTECHNOLOGY
Year: 2008
JOURNAL (LIDAR)
JOURNAL (LIDAR)
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Instruments
Disdrometer (in-situ)Scanning Elastic
Lidar
JOURNAL (LIDAR)
JOURNAL (LIDAR)
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Instrument: Scanning
Elastic LidarElastic backscattering is designed to determine the distribution and
properties of atmospheric particulates.
Elasticrefers to scattering in which no energy is lost by the photons, so
that the detected light is at the same wavelength as the emitted light.
The system is entirely computer controlled using PC cards to control
the motors, the laser, the digitizers, and other auxiliary equipment such
as GPS.
Lidar can be operated remotely and autonomously, using pre-
programmed sequences that only require an operator to start.
JOURNAL (LIDAR)
JOURNAL (LIDAR)
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Methodology: Inversion
MethodThe inversion algorithm transforms measured quantities(the intensity of the backscattered light as a function of
distance) into rainfall amounts.
Determination ofthe extinction
coefficients fromraw Lidar data
Calculation of thecorresponding rain
rates.
Step 1 Step 2
JOURNAL (LIDAR)
JOURNAL (LIDAR)
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Step 1: Determination of
Existence Coefficient(1)
(2)
(3&4)
(5)
(6)
JOURNAL (LIDAR)
JOURNAL (LIDAR)
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Step 2:Calculating Rain Rates
Where,
(8)
(9)
(10)
(11)
(12)
( )
JOURNAL (LIDAR)
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Results
Upper graph presents
the full time series of
Lidar backscattered
power measured
directly over the
disdrometer during the
event on 5 Oct 2005 in
Iowa City, IA.
Bottom graph shows a
time series of full-rangelidar profiles (color
coded)
( )
JOURNAL (LIDAR)
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ResultsFrom Eq (13) parameters C3 and C4 are determined by fitting the
Lidar data and result is presented in following formula:
( )
JOURNAL (LIDAR)
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Results
Mean fractional difference (fractional difference between
the Lidar and the disdrometer rain rates for the entire
sample with values above the detection limit of 0.1 mm
h)
( )
JOURNAL (LIDAR)
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Conclusion
Lidar-based estimates of rainfall at small spatial and
temporal scales might be the most accurate of all
instruments available in compared with tipping-bucket
rain gauges, optical and mechanical disdrometers andradar.
A concurrent application of Lidar and a limited number
of disdrometers capable of mapping horizontal
distribution of rainfall with high spatial (~5 m) andtemporal (~1min) resolution.
( )
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Edward H. Bair, Robert E. Davis,David C. Finnegan, Adam L.
LeWinter, Ethan Guttmann, and JeffDozier
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Measure accurate snowfallmeasurements in windy areas.
Effective snow depth mappingover a small study area ofseveral hundred m2
LiDAR also produces dense point cloudsbydetectingfallingandblowing hydrometeors during storms
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Riegl LMS-Z390i
IR withwavelength 1.55
m
Capable of 360azimuthaland
80 elevationalcoverage at 0.09angularincrements
Mounted on a
steel platform,approximately 7m above snow-free ground.
Automaticallyscans every houror every 15 min.
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Produces file in 3dd formatwhich thenconverted to ASCII format contain (X,Y,Z) andrelative intensities (0-1) for each detection.
From the coordinates, we recorded the numberof detections in the sample volumeand theassociated scan time.
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Beam Geometry
Illustrationduring readingbeing taken.
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Daily manual SWE and summed lidar counts, hourly fromMarch 2011-April 2012.
The correlation coefficient r=0.58.
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Daily manual SWE and summed lidar counts, 15 min fromFeb-April 2012.
The correlation coefficient r=0.73.
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1. It is shown that, in addition of snow depth
mapping, LiDAR can also be used for snowmass flux estimation.
2. Found a good empirical agreement betweenLiDAR counts in sample volume, summedover one day, and manually weighed SWE.
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