Activemicrowaveremotesensing/principles

DmitriMoisseevUniversityofHelsinki

Whatwillbediscussed

• ActiveMicrowaveremotesensingplatforms

Rain• DSD,Precipitationrateandradarreflectivityfactor• WaystoconstrainZ-R• Dual-frequencyradarapproach

Whatifitisnotrain• Connectionbetweenparticlephysicalandscatteringproperties• Apparentfrequencydependence• Ze-S

Oct.3,2016 8thIPWGand5thIWSSM,TrainingEvent 2

Cloudandprecipitationsatellites

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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 (

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

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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

4  

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

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MaxwellGarnettformulaisnotsymmetric

NowwecangotoZe

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Expressingeverythingintermsofparameters

Snowfallrate

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mass velocity

AndfinallyZ-S

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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

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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