Validation of Microwave Moisture Retrievals Over Land

Validation of Microwave Validation of Microwave Moisture Retrievals Over Moisture Retrievals Over

LandLand

Presented by : Presented by :

Matthew J. NielsenMatthew J. NielsenCooperative Institute for Cooperative Institute for

Research in the AtmosphereResearch in the Atmosphere

CSU/CIRA Matthew Nielsen Cooperative Research Program 2nd Annual Science Symposium/Satellite Calibration & Validation

Research ScopeResearch Scope

Attempt to estimate water vapor Attempt to estimate water vapor over landover land

Created C1DOE retrieval (used Created C1DOE retrieval (used AMSU data)AMSU data)

Examined analytical JacobianExamined analytical Jacobian Validated retrieval with Validated retrieval with

radiosondes and GPSradiosondes and GPS


C1DOE retrievalC1DOE retrieval

Uses Optimal Estimation to Uses Optimal Estimation to produce layer T, skin T, emissivity, produce layer T, skin T, emissivity, TPW, and layer qTPW, and layer q

Layer information calculated at Layer information calculated at 100, 200, 300, 500, 700, 850, and 100, 200, 300, 500, 700, 850, and 1000 mb.1000 mb.

Emissivities calculated at 23, 31, Emissivities calculated at 23, 31, 50, 89, and 150 GHz50, 89, and 150 GHz


Cost functionCost function The cost function used in the C1DOE is given by:The cost function used in the C1DOE is given by:

The first term is a penalty for deviating from the The first term is a penalty for deviating from the first guess (first guess and a priori are first guess (first guess and a priori are equivalent in this retrieval). This limits the equivalent in this retrieval). This limits the outcome to only physical solutions.outcome to only physical solutions.

The second term is a penalty for deviations of The second term is a penalty for deviations of the simulated radiances from the forward model the simulated radiances from the forward model output. This is a way to constrain the forward output. This is a way to constrain the forward model and observational errors.model and observational errors.

xFySxFyxxSxx yT

aaT

a ˆˆ 11


First guess dataFirst guess data

AGRMET: surface temperature first AGRMET: surface temperature first guess from three hour average guess from three hour average data data

MEM: emissivity first guess at all MEM: emissivity first guess at all five frequenciesfive frequencies

Radiosondes: temperature and Radiosondes: temperature and moisture profile first guessmoisture profile first guess


Data flowData flow


AMSUAMSU

Data came from the Advanced Data came from the Advanced Microwave Sounding Unit (AMSU)Microwave Sounding Unit (AMSU)

20 channel microwave radiometer20 channel microwave radiometer Ch. 1-15 used for temperature Ch. 1-15 used for temperature (AMSU-A)(AMSU-A) Ch. 16-20 used for water vapor Ch. 16-20 used for water vapor

(AMSU-B)(AMSU-B)


AMSU-B ChannelizationAMSU-B ChannelizationCh. # Center freq. of

channel (GHz)No. of pass

bands

Bandwidth per passband

(MHz)

NEΔT Polarization angle

16 89.0 2 1000 0.37 90-θ17 150.0 2 1000 0.84 90-θ18 183.31±1.00 2 500 1.06 90-θ19 183.31±3.00 2 1000 0.70 90-θ20 183.31±7.00 2 2000 0.60 90-θ


AMSU-B Antenna Pattern AMSU-B Antenna Pattern CorrectionCorrection

AMSU-B mainbeam only receives AMSU-B mainbeam only receives ~95% of total power~95% of total power

5% comes from Earth, cold space, 5% comes from Earth, cold space, and satellite and satellite

Sidelobe contamination can cause Sidelobe contamination can cause bias up to 3 or 4 K in retrieved bias up to 3 or 4 K in retrieved brightness temperatures brightness temperatures (corresponds to values up to 4x (corresponds to values up to 4x the NEthe NET)T)


AMSU APC (cont.)AMSU APC (cont.)


Analytical JacobianAnalytical Jacobian Defined as a derivative of the forward Defined as a derivative of the forward

model with respect to the state vector model with respect to the state vector parametersparameters

Important because it provides information Important because it provides information on sensitivity of forward model to changes on sensitivity of forward model to changes in state vectorin state vector

Shows performance of each channel, along Shows performance of each channel, along with denoting which channels have signal with denoting which channels have signal and which do notand which do not

Good for channelization and retrieval setupGood for channelization and retrieval setup








Retrieval configurationRetrieval configuration

Retrieval was run with highly accurate Retrieval was run with highly accurate first guess in order to detect biasfirst guess in order to detect bias

Data was from September 21-Data was from September 21-September 30, 2003September 30, 2003

Radiosonde match-up dataset created Radiosonde match-up dataset created (50 km and two-hour window) with 555 (50 km and two-hour window) with 555 data pointsdata points

GPS match-up dataset created (30 km GPS match-up dataset created (30 km and 30 min window) with 26 data pointsand 30 min window) with 26 data points


ValidationValidation

GPS calculations of TPW GPS calculations of TPW considered highly accurate (within considered highly accurate (within 1mm) 1mm)

TPW calculated from a TPW calculated from a “tropospheric wet delay”“tropospheric wet delay”

Ground receivers are sent signals Ground receivers are sent signals from satellites to calculate delayfrom satellites to calculate delay








ConclusionsConclusions Antenna pattern correction fixed a consistent Antenna pattern correction fixed a consistent

~3 K bias from observed Tb’s~3 K bias from observed Tb’s Jacobian illustrated where retrieval did well Jacobian illustrated where retrieval did well

and where it provided little information. Also and where it provided little information. Also highlighted the channels that were best highlighted the channels that were best suited to retrieve water vaporsuited to retrieve water vapor

Retrieval bias detection showed issues near Retrieval bias detection showed issues near coastlines due to poor first guess and ocean coastlines due to poor first guess and ocean contaminationcontamination

GPS validation yet to be satisfactory due to GPS validation yet to be satisfactory due to dataset constraints and coastline issuesdataset constraints and coastline issues


Future workFuture work Cloud liquid and ice module to be added Cloud liquid and ice module to be added Need improved emissivity first guess Add Need improved emissivity first guess Add

soil moisture modulesoil moisture module Explore better covariance matrix optionsExplore better covariance matrix options Provide water vapor and temperature first Provide water vapor and temperature first

guess from GDAS (better spatial coverage guess from GDAS (better spatial coverage and able to be performed in real time)and able to be performed in real time)

Validate TPW with increased # of GPS Validate TPW with increased # of GPS stationsstations

Will be used in CloudSat projectWill be used in CloudSat project

Documents

Validation of Microwave Moisture Retrievals Over Land