active microwave remote sensing/principles
TRANSCRIPT
Activemicrowaveremotesensing/principles
DmitriMoisseevUniversityofHelsinki
Whatwillbediscussed
• ActiveMicrowaveremotesensingplatforms
Rain• DSD,Precipitationrateandradarreflectivityfactor• WaystoconstrainZ-R• Dual-frequencyradarapproach
Whatifitisnotrain• Connectionbetweenparticlephysicalandscatteringproperties• Apparentfrequencydependence• Ze-S
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 2
Cloudandprecipitationsatellites
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 3
TRMM11/1997-04/2015
TRMM– PR:coverage35Sto35NKu band 13.8GHz/2.17cmHorizontalresolution:4.3kmSwath:220kmVerticalresolution:250m(1.6us)Sensitivity:0.7mm/hor17dBZ
GPM02/2014-GPM– DPR:coverage65Sto65N
Kuband– 13.6GHz Ka band– 35.5GHzSwath:245km 120kmRangeresolution: 250m(1.6us) 250/500m(1.6/3.2us)Horizontalresolution: 5.2km 5.2kmSensetivity:0.5mm/hor18dBZ 0.2mm/hor12dBZ
Cloudandprecipitationsatellites
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 4
CloudSat
EarthCare
CPR:coverage90Sto90NWband 94GHz/3mmAlong-track:1.7kmCross-track:1.4kmVerticalresolution:500m(3.3us)– pulsecompressionSensitivity:-30dBZ
DopplerCPRWband 94GHz/3mmVerticalresolution:500m(3.3us)– pulsecompressionSensitivity:-35dBZ for10kmintergration
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 5
KaPRKuPR
Leinonen etal.,2011JAMC
2.1 Precipitation retrievals The quantitative estimation of precipitation on a global scale from satellite observations currently relies upon multi-spectral, multi-sensor approaches. While visible and/or infrared techniques have been the mainstay of retrievals for many years, the development of passive microwave (PM) sensors, the SSMI in particular, has lead to a range of PM-based techniques and enabled the development of physically-based methods (e.g. Kummerow et al., 2001). The launch in 1997 of the Tropical Rainfall Measurement Mission (TRMM; Kummerow et al., 2000; Simpson et al., 1996) with the active-microwave capabilities of the Precipitation Radar (PR; Iguchi et al., 2000) has provided a wealth of new observations and measurements that has greatly enhanced our understanding and knowledge of precipitation processes and subsequently, improved precipitation retrievals. The Cloud Profiling Radar (CPR) on the Cloudsat mission launched in 2006 (Stephens et al., 2008), while designed to observe clouds, has provided significant new information on precipitation systems outside the Tropics and on light precipitation not detected by the TRMM/PR: despite the limitations of coverage, Cloudsat has demonstrated significant potential for radar measurements of light rain and snowfall. In general, the availability of radar measurements, and the resulting detailed direct observation of the vertical structure of precipitating systems, has opened the doors to the development of several algorithms aiming at the exploitation of the complementary aspects of active and passive instruments for improved, and global estimates. The Global Precipitation Measurement (GPM) mission, planned for launch in 2013 aims at deploying the state of the art in such combined algorithms to provide measurements of precipitation every 3 hours. Such measurements, however, will not include precipitation in the Polar Regions (due to GPM’s core-spacecraft orbit), nor very light precipitation (due to the +12 dBZ minimum detectable sensitivity of the GPM Dual frequency Precipitation Radar - DPR). 2.1.1 Quantifying precipitation Fundamental to both techniques is the ability to correctly identify and quantify precipitation. Two main problems currently exist, namely the identification and retrieval of (i) light precipitation, and (ii) frozen precipitation. They arise from the fact that such regimes result in weak microwave signatures both for active and passive instruments, and highly ambiguous signatures in the VIS/IR range. The occurrence of light precipitation is an increasing problem towards the poles. In the Tropics the occurrence of light precipitation (<0.5 mmh-1) is relatively small, around 30% (see Figure 2.3), contributing only 4% of the accumulation. Over NW Europe, the occurrence of light precipitation increases to 70%, contributing 25% to the precipitation accumulation. Most current satellite precipitation retrieval techniques are insensitive to these light intensities, with many unable to identify precipitation less than 1 mmh-1, particularly over land surfaces.
Figure 2.3: The occurrence and accumulation of precipitation as measured by the TRMM Precipitation Radar (Tropics, 35˚N-35˚S) and the Nimrod surface radar network (Europe 40˚N-70˚N).
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@high-latitudes• Ka-bandPRcapturesmorethan70%ofrainfall
• Ku-bandPRcaptureslessthan50%ofrainfall
Itisbetterfortropicsandrainaccumulation
DSDanditsshape
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 6
Leinonen etal.,2011JAMC
LegacyandwidelyusedDSDdescription
N0 andµ arenotindependent!
𝑁 𝐷 = 𝑁$𝐷% exp −Λ𝐷
Thatiswhythenormalizedformisnowused
z-R relation – pick one, if you dare
z = a•Rb
• As you will show in lab, “a” and “b” are not constant but vary depending on the rain DSD.
•To the right are just few (69 actually) examples of published z-R relations.
• Why so many?
• Implications for rainfall estimation from radar reflectivity?
“MarshallPalmer”
Source: Doviak and Zrnic (1993)
Rainratefromradarobservations
• a lotofuncertainty• canbeconstrainedif
additionalifadditionalDSDinfoisused
Dual-frequencyapproach
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 8
ObservationsatoneofthefrequenciesisinRayleighregimewhiletheotherisintheresonanceregion
WaystoconstrainZ-R;Dual-frequencyradar
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 9
Problematicarea
HowproblematicistheproblematicareaofD0?–- Itdepends…
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 10
90%ofraininFinlandhasD0 lessthan1.5mm
Finland
SouthKorea
Suh et al. 2016
RaindropsarelargerinS.Korea
Surfacereferencetechnique(SRT)
• Radarsignalsareattenuatedbyprecipitationandclouds• InrainthisattenuationdependsonDSDparameters• SolutionfortheattenuationwillyieldDSDparametersandthereforeconstrainZ-R• HBmethodisused• ToconstrainitPIAfromSRTisused
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Whatifitisnotrain
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Precipitationalsocomesintheformofsnow
2.1.2 Identification of frozen precipitation The accurate retrieval of precipitation is further complicated by the increasing contribution of frozen precipitation towards the Polar Regions. Figure 2.4 illustrates the contribution of light precipitation to the total precipitation occurrence divided into liquid, mixed and frozen hydrometeors. North and south of 40˚-50˚ latitude mixed and frozen light precipitation occurs, and dominates the light precipitation above 70˚ latitude.
Figure 2.4: The latitudinal occurrence of different light intensity precipitation types as a percentage of total precipitation occurrence derived from shipborne observations. In central and northern regions of Europe and Canada snowfall represents a significant amount of the total precipitation. In Canada, the average annual precipitation is 535 mm, of which 36% falls as snow. However, this average masks a significant latitudinal variation, with the northern regions of Canada experiencing more than 90% of the annual precipitation as snowfall (see Figure 2.5). The quantification of snowfall is critical to estimate snowmelt during Spring and Summer: in Sweden about half of the energy requirements is met through hydro-electricity, of which 90% is generated north of 60˚N.
Figure 2.5 Ratio of snow to total precipitation for Ottawa, Yellowknife and Alert. Several papers have specifically addressed the retrieval of frozen precipitation over the Polar Regions (e.g. Surussavadee and Staelin, 2009; Liu, 2008). Although the results have been encouraging, the quantification and accuracy of these estimates are yet to be fully determined. More importantly, these
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CourtesyofC.Kidd
Raineventsfrommeltingsnow
FieldandHeymsfield,2015
Fractionofprecip.eventsthataresnow
FieldandHeymsfield,2015
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 15
CourtesyofJ.Koistinen
KaPR
KuPR
CDFofequivalentreflectivityfactorinsnow
Whatarephysicalpropertiesofsnowflakes?
- Mass- Size(ambiguous)- Volume(ambiguous)- Density(ambiguous)
Connectingscatteringandphysicalproperties
Simplify
Small(?)dielectricinclusionsinthedielectricmediaf – fractionofthetotalvolumeoccupiedbytheinclusionphase1-f isvolumefractionofthehost
𝑓,-. =𝜌0123,-4.
𝜌,-.5𝑓1,2 = 1 − 𝑓,-.
Effectivemediaapproximation
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 18
MaxwellGarnettmixingformulaforaneffectivepermittivity
inclusionsmedia
Refractiveindex:𝑛 = 𝜖𝜇�
Bruggeman formula
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 19
MaxwellGarnettformulaisnotsymmetric
NowwecangotoZe
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 20
Expressingeverythingintermsofparameters
Snowfallrate
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 21
mass velocity
AndfinallyZ-S
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 22
Aggregation,cloudtopheight
Riming
Connectingscatteringandphysicalproperties
Simplify
Small dielectricinclusionsinthedielectricmedia
Whathappenswhenthewavelengthdecreases?
𝑓,-. =𝜌0123,-4.
𝜌,-.5𝑓1,2 = 1 − 𝑓,-.
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 24
Theestablishedrelationbetweensnowphysicalandscatteringpropertiesfails
Tyynela etal.2011
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 25
Orietal,2016
• Weunderestimateradarreflectivityathigherfrequencies
• Whichwouldleadtooverestimationofsnowfallrate(bystandardZe-S)
• Ifitisnottakenintoaccount
Takehome
Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 26
• ActiveMicrowaveremotesensingplatforms
Rain• DSD,Precipitationrateandradarreflectivityfactor• WaystoconstrainZ-R• Dual-frequencyradarapproach
Whatifitisnotrain• Connectionbetweenparticlephysicalandscatteringproperties• Ze-S• Apparentfrequencydependence