Validation of Microwave Moisture Retrievals Over Land

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Validation of Microwave Moisture Retrievals Over
Land

• Presented by
• Matthew J. Nielsen
• Cooperative Institute for Research in the
  Atmosphere

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Research Scope

• Attempt to estimate water vapor over land
• Created C1DOE retrieval (used AMSU data)
• Examined analytical Jacobian
• Validated retrieval with radiosondes and GPS

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C1DOE retrieval

• Uses Optimal Estimation to produce layer T, skin
  T, emissivity, TPW, and layer q
• Layer information calculated at 100, 200, 300,
  500, 700, 850, and 1000 mb.
• Emissivities calculated at 23, 31, 50, 89, and
  150 GHz

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Cost function

• The cost function used in the C1DOE is given by
• The first term is a penalty for deviating from
  the first guess (first guess and a priori are
  equivalent in this retrieval). This limits the
  outcome to only physical solutions.
• The second term is a penalty for deviations of
  the simulated radiances from the forward model
  output. This is a way to constrain the forward
  model and observational errors.

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First guess data

• AGRMET surface temperature first guess from
  three hour average data
• MEM emissivity first guess at all five
  frequencies
• Radiosondes temperature and moisture profile
  first guess

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Data flow

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AMSU

• Data came from the Advanced Microwave Sounding
  Unit (AMSU)
• 20 channel microwave radiometer
• Ch. 1-15 used for temperature
• (AMSU-A)
• Ch. 16-20 used for water vapor
• (AMSU-B)

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AMSU-B Channelization
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AMSU-B Antenna Pattern Correction

• AMSU-B mainbeam only receives 95 of total power
• 5 comes from Earth, cold space, and satellite
• Sidelobe contamination can cause bias up to 3 or
  4 K in retrieved brightness temperatures
  (corresponds to values up to 4x the NE?T)

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AMSU APC (cont.)
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Analytical Jacobian

• Defined as a derivative of the forward model with
  respect to the state vector parameters
• Important because it provides information on
  sensitivity of forward model to changes in state
  vector
• Shows performance of each channel, along with
  denoting which channels have signal and which do
  not
• Good for channelization and retrieval setup

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Retrieval configuration

• Retrieval was run with highly accurate first
  guess in order to detect bias
• Data was from September 21-September 30, 2003
• Radiosonde match-up dataset created (50 km and
  two-hour window) with 555 data points
• GPS match-up dataset created (30 km and 30 min
  window) with 26 data points

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Validation

• GPS calculations of TPW considered highly
  accurate (within 1mm)
• TPW calculated from a tropospheric wet delay
• Ground receivers are sent signals from satellites
  to calculate delay

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Conclusions

• Antenna pattern correction fixed a consistent 3
  K bias from observed Tbs
• Jacobian illustrated where retrieval did well and
  where it provided little information. Also
  highlighted the channels that were best suited to
  retrieve water vapor
• Retrieval bias detection showed issues near
  coastlines due to poor first guess and ocean
  contamination
• GPS validation yet to be satisfactory due to
  dataset constraints and coastline issues

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Future work

• Cloud liquid and ice module to be added
• Need improved emissivity first guess Add soil
  moisture module
• Explore better covariance matrix options
• Provide water vapor and temperature first guess
  from GDAS (better spatial coverage and able to be
  performed in real time)
• Validate TPW with increased of GPS stations
• Will be used in CloudSat project