1 1 Estimation of Oceanic Rainfall using Passive Estimation of Oceanic Rainfall using Passive and Active Measurements from SeaWinds SeaWinds and Active Measurements from Spaceborne Microwave Sensor Microwave Sensor Spaceborne Khalil Ali Ahmad Ali Ahmad Khalil Doctoral Dissertation Defense Doctoral Dissertation Defense th 2007 October 26 th 2007 October 26
Presentation Outline: Presentation Outline: 2 2 Introduction Introduction � � � Dissertation objectives Dissertation objectives � � Why measure rainfall from space ? Why measure rainfall from space ? � � Background Background � � Microwave Microwave scatterometry scatterometry � � Microwave radiometry Microwave radiometry � � SeaWinds SeaWinds sensor sensor � � SeaWinds SeaWinds sampling contribution sampling contribution – – GPM mission GPM mission �
Presentation Outline: Presentation Outline: 3 3 � SeaWinds SeaWinds Rain Algorithm Rain Algorithm � � QRad QRad Rain Rate Algorithm Rain Rate Algorithm � � Passive excess brightness Passive excess brightness – – rain rate relationship rain rate relationship � � Validation: TRMM 3B42RT, 2A12 Validation: TRMM 3B42RT, 2A12 � � Modeling Modeling SeaWinds SeaWinds backscatter in presence of rain backscatter in presence of rain � � Combined passive / active rain retrievals Combined passive / active rain retrievals � � Methodology Methodology � � Performance comparison with Performance comparison with QRad QRad � � Validation: Validation: TRMM 2A12, JPL IMUDH flag TRMM 2A12, JPL IMUDH flag � � Summary & Conclusions Summary & Conclusions �
Dissertation Objectives: Dissertation Objectives: 4 4 σ º � Utilize the rain sensitivity of passive T Utilize the rain sensitivity of passive T B / active σ º B / active � measurements acquired by SeaWinds SeaWinds sensor sensor measurements acquired by to infer global oceanic rainfall to infer global oceanic rainfall � Characterize the effects of rain on passive / active Characterize the effects of rain on passive / active � measurements measurements � Develop a statistical inversion algorithm Develop a statistical inversion algorithm � � Validate the quality of Validate the quality of SeaWinds SeaWinds oceanic rain oceanic rain � retrievals retrievals
Why measure rainfall from space ? Why measure rainfall from space ? 5 5 � Essential source for fresh water Essential source for fresh water � Valuable for a wide range of research Valuable for a wide range of research � areas and related applications: areas and related applications: � Earth's hydrological cycle Earth's hydrological cycle � � Earth's energy cycle Earth's energy cycle � � Weather forecasting / climate change Weather forecasting / climate change � � Rainfall tend to be random in Rainfall tend to be random in � character and also evolve very rapidly character and also evolve very rapidly
Why measure rainfall from space ? Why measure rainfall from space ? 6 6 � Radar / rain gauges can provide reliable measurements Radar / rain gauges can provide reliable measurements over small land areas over small land areas � Difficult to quantify on regional / global scale Difficult to quantify on regional / global scale � � Impractical over ocean surface Impractical over ocean surface � � Space Space- -based microwave based microwave � remote sensing instruments remote sensing instruments are indispensable tools in are indispensable tools in providing useful regional / providing useful regional / global scale precipitation global scale precipitation measurements measurements � Wide (global) coverage Wide (global) coverage � � Frequent / uniform sampling Frequent / uniform sampling SeaWinds daily coverage ~ 90% �
7 7 Background Background
Microwave Scatterometry Scatterometry Microwave 8 8 � Scatterometer Scatterometer : : A special purpose radar to measure σ º A special purpose radar to measure σ º � λ 2 2 P G ∫∫ = σ o t P dA π 3 4 r ( 4 ) R A � σ o : Normalized Radar Cross Section Bragg scattering from short waves (NRCS) of the ocean surface ( ) σ = υ χ θ 0 , , , , … M p M : Geophysical Model Function (GMF) χ = α − ϕ 2 L θ = = sin , 1 , 2 , 3 , … n n λ Ocean Surface
Microwave Scatterometry Scatterometry Microwave 9 9 Radar Backscatter σ º (dB) 30º 40º 50º Wind speed m/s Azimuth angle
Microwave Radiometry Microwave Radiometry 10 10 Lossless V d V out Antenna P sys Noise-free receiver Square Law Low-Pass + Gain=G Detector Filter Bandwidth=B P rec Receiver Receiver Noise � Power collected by antenna is Power collected by antenna is: • • K is Boltzmann K is Boltzmann’ ’s s constant constant out = • • B is receiver bandwidth B is receiver bandwidth P k T B ap • • T AP T AP is the scene brightness temperature is the scene brightness temperature � Radiometer sensitivity or radiometric resolution ( Δ T): T • • τ is the integration time is the integration time τ sys ∆ = T B τ ⋅
Microwave Radiometry Microwave Radiometry 11 11
SeaWinds Microwave Sensor Microwave Sensor SeaWinds 12 12 � SeaWinds SeaWinds is a Ku is a Ku- -band microwave band microwave � scatterometer flown onboard two satellite flown onboard two satellite scatterometer missions: missions: � QuikSCAT QuikSCAT (June (June ‘ ‘99 ~ present) 99 ~ present) � � ADEOS ADEOS- -II (Dec. II (Dec. ‘ ‘02 ~ Oct. 02 ~ Oct. ‘ ‘03) 03) � � Instrument description: Instrument description: � � Radar: 13.4 GHz / 110 W pulse / 189 Hz PRF Radar: 13.4 GHz / 110 W pulse / 189 Hz PRF � � Mass / power: 200 kg / 220 W Mass / power: 200 kg / 220 W � � Antenna: 1 Antenna: 1- -meter meter- -diameter parabolic dish diameter parabolic dish � Dual Pol Pol (H / V) (H / V) Dual SeaWinds on on QuikSCAT QuikSCAT SeaWinds
SeaWinds Microwave Sensor Microwave Sensor SeaWinds 13 13 � Originally designed to measure marine wind vector by Originally designed to measure marine wind vector by � relating the measured surface backscatter to a GMF. To relating the measured surface backscatter to a GMF. To get an accurate backscatter measurement the instrument get an accurate backscatter measurement the instrument utilizes: utilizes: Received Spectrum Echo Channel Be Power � Echo channel Echo channel � Radar Echo Noise Channel � Noise channel (~ 1 MHz) Noise channel (~ 1 MHz) � Bn Frequency � Q QuikSCAT uikSCAT / / S SeaWinds eaWinds Rad Radiometer ( iometer (QRad QRad / / SRad SRad) ) � transforms observed noise into apparent brightness transforms observed noise into apparent brightness temperature: temperature: � Implemented through signal processing Implemented through signal processing � � Calibrated against TMI observations Calibrated against TMI observations � � Not an optimum Not an optimum radiometer ( radiometer ( ∆ ∆ T ~ 25 Kelvin /pulse ) T ~ 25 Kelvin /pulse ) � � Improved Improved ∆ ∆ T by averaging / spatial filtering T by averaging / spatial filtering �
SeaWinds Microwave Sensor Microwave Sensor SeaWinds 14 14
15 15 SeaWinds Rain Algorithm Rain Algorithm SeaWinds � Introduction Introduction �
SeaWinds Rain Algorithm Rain Algorithm SeaWinds 16 16 � Oceanic instantaneous integrated rain rate, Oceanic instantaneous integrated rain rate, 25 km 25 km resolution resolution � on WVC measurement grid on WVC measurement grid � Data source: Data source: � � Polarized microwave brightness temperatures (L2A) Polarized microwave brightness temperatures (L2A) � � Polarized microwave backscatter (L2A) Polarized microwave backscatter (L2A) � � Collocated NCEP wind speeds (L2B) Collocated NCEP wind speeds (L2B) � : � Statistical retrieval algorithm Statistical retrieval algorithm : � � Empirical T Empirical T ex vs. IRR relationship ex vs. IRR relationship � σ 0 � Empirical Empirical σ 0 vs. IRR relationship ex vs. IRR relationship � ex � Trained using near Trained using near- -simultaneous collocations with TRMM simultaneous collocations with TRMM � Microwave Imager (TMI) oceanic rain rates Microwave Imager (TMI) oceanic rain rates
SeaWinds Rain Algorithm Rain Algorithm SeaWinds 17 17 � Utility of Utility of SeaWinds SeaWinds rain product: rain product: � � Provides simultaneous, collocated precipitation measurements Provides simultaneous, collocated precipitation measurements � with QuikSCAT QuikSCAT ocean surface wind vectors for rain ocean surface wind vectors for rain- -flagging flagging with contaminated wind vector retrievals contaminated wind vector retrievals � Increase oceanic rain sampling ~10% Increase oceanic rain sampling ~10% � � NASA NASA’ ’s GPM mission: s GPM mission: � OBJECTIVES • Provide sufficient global sampling to reduce uncertainties in short-term rainfall accumulations. • Understand horizontal & vertical structure of rainfall, its associated latent heating.
SeaWinds sampling sampling – – 3 hr window 3 hr window SeaWinds 18 18
Daily average revisit time – – 3 hr window 3 hr window Daily average revisit time 19 19 TMI & SSMI (3 satellites) Time QRad, TMI & SSMI (3 satellites)
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