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A Comparison of Two Microwave Retrieval Schemes in the Vicinity of Tropical Storms

Jack DostalekCooperative Institute for Research in the Atmosphere, Colorado State University

Galina Chirokova and Kate MusgraveCooperative Institute for Research in the Atmosphere, Colorado State University

Mark DeMariaNational Hurricane Center

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CIRA has developed tropical cyclone (TC) products using remotely sensed data.

Microwave data is particularly helpful in tropical cyclones due to insensitivity to most clouds

Temperature retrievals derived from Advanced Microwave Sounding Unit (AMSU) data have been extensively used• Flies aboard NOAA-15 (1998), -16, -17, -18, -19, MetOp-A, MetOp-B,

Aqua satellites

The temperature retrievals can be used to derive the height field which can be used to derive a non-divergent wind field

Estimate values of interest to TC forecasters such as:• Minimum pressure• Intensity (maximum wind speed)• Radius of maximum winds• Radius of 34-, 50-, 64-kt winds

Background

AMSU Wind Analysis

Initial Estimates (Minimum Pressure, Intensity, Radius of Maximum Winds)

Statistical Fitting for Improved Estimates

Multiplatform Satellite Surface Wind Analysis

Surface Wind Estimate

Data

AMSU Temperature Profiles

GFS for Boundary Conditions

Operational Fix Entry Operational Fix Entry3

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AMSU temperature profiles for the TC products currently come from a statistical retrieval technique > 10 years old

NESDIS’ current operational microwave retrieval algorithm is the Microwave Integrated Retrieval System (MIRS)• 1D VAR retrieval scheme• Flexible, can use with AMSU, SSM/I, or ATMS• Also retrieves vertical profile of water vapor mixing ratio

An Issue

How does the quality of the initial estimates of the TC products compare when the temperature profiles come from the statistical technique vs. MIRS?

A Question

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How do the MIRS temperature retrievals compare to the statistical retrievals with respect to collocated dropsondes?

• MIRS data first available in 2012

• Dropsondes from 2012 Atlantic season (Ernesto, Isaac, Sandy)

• Statistical and MIRS retrievals from AMSU aboard NOAA-18

• Collocation: retrievals must be within 50 km and 1 hour of dropsonde

But First

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Do the higher quality soundings translate into better first estimates of minimum pressure, intensity, and radius of maximum wind?• 33 matchups from the 2012 Atlantic hurricane season (Chris, Debby,

Ernesto, Gordon, Isaac, Leslie, Sandy)

• Comparisons are made with respect to the best track

• The bias and rmse in the following plots are “large”, but in the flow of the processing, these estimates are of the first guess. Improvement from the statistical technique to the MIRS algorithm is what is sought

Overall the MIRS temperatures are closer to the dropsonde temperatures than the statistical technique

Results of Temperature Comparison

Back to the Main Question

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Both have high bias

Lower bias with MIRS

Lower RMSE with MIRS

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Both have low bias, consistent with high bias on minimum pressure (assuming similar environmental surface pressures)

MIRS bias smaller in magnitude

RMSE same

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Both have very high bias – again these values are refined later on

Larger bias with MIRS

Lower RMSE with MIRS

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Summary MIRS temperature soundings are an improvement over the older, statistical

technique

This improvement does translate into an (overall) improvement in the initial estimates of minimum pressure, intensity, and radius of maximum winds

Future Work More cases

Temperature profiles – Why isn’t the MIRS better at all levels?

Check quality of operational fix entries (definitely need more cases for this step)

Include moisture effects (MIRS also gives water vapor mixing ratio profile)

Other parameters (MPI, vertical velocity profile)