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Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS University of Wisconsin, Madison

Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

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Page 1: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed

Observations 

Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson

CIMSSUniversity of Wisconsin, Madison

Page 2: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

WVSS-II Moisture SensorWVSS-II is a laser diode mixing ratio measurement system manufactured by

During this WVSS-II validation experiment, between 25 and 30 UPS B757 aircraft were equipped with WVSS-II sensors.

Page 3: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

WVSS-II Validation Experiment Details: AERIBago Location

Kentucky Air National Guard Base, Louisville Airport

Page 4: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Atmospheric Emitted Radiance Interferometer (AERI)

VAISALA 25K Ceilometer

WVSS-II Validation Experiment Ground-Based Instrumentation

Vaisala DigiCORA III RS-92 GPS Sounding System

VAISALA Surface PTU Station

GPS Receiver

http://cimss.ssec.wisc.edu/aeribago/

Page 5: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Key Experiment Logistics

Dates June 14-24, 2005

# of Matching Aircraft17

(10 version 1, 7 version 2)

# of Rawinsonde launches per day

3 (Mon-Thurs)

2 (Fri)

None on Sat, Sun

Total # Rawinsonde Launches 27

Total # Rawinsonde/WVSS-II matches (ascending only)

49

Approximate Launch Times (UTC)

0645, 0240 (Mon-Fri) 0930 (Mon-Thurs only)

Page 6: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Validation Methodology

Match Criteria:

1) WVSS-II time was within +/- 60 minutes of Rawinsonde Launch time

2) Distance between WVSS-II and Rawinsonde was less than 50 km

RMS/Bias statistics were calculated at the aircraft reported pressure level and then grouped into 10 mb bins. At least 20 matches were required to calculate statistics at any level.

Page 7: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Additional Constraints

1) Only profiles obtained from ascending aircraft were included. This is due to the occasional erroneous report in areas of high humidity and clouds, but only on descent. This problem will be addressed through a future hardware change.  

2) Results were calculated by limiting assessment to regions where the observed mixing ratio was greater than 2 g/kg.

3) Assessment of moisture was made in terms of the primary WVSS-II water vapor observation, mixing ratio (or specific humidity). This is to eliminate the carry-over of any instrument temperature bias in the moisture assessment, as would be the case for Relative Humidity.

Page 8: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Sample Specific Humidity profiles

Both WVSS-II profiles at this time match the rawinsonde profile well. Profiles are from 16 minutes (red) and 39 minutes (green) before the rawinsonde launch.

These reports show a much greater spread between the individual aircraft reports and the rawinsonde report. Of 3 ‘outlying’ reports, one was taken significantly before the rawinsonde launch (52 minutes), one of the others had the exact same starting time.

Page 9: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Specific Humidity (g/kg) Statistics

Bias ranges from about 0.1 to 0.3 g/kg, and RMS ranges from about 0.6 to 1 g/kg between the surface and 800 hPa. Above 800 hPa, the bias increases to between 0.3 and 0.5 g/kg, and the RMS increased to between 1 and 1.4 k/kg.

Page 10: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Temperature (oC) Statistics

Aircraft temperature measurements exhibit a clear warm bias (about 0.5oC) at all levels above the immediate boundary layer. This error would be amplified in the calculation of RH (%), resulting in artificially dry values.

Page 11: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

RH(%) Statistics: Calculated vs. Reported

RH (%) values were calculated using the WVSS-II specific humidity value and the rawinsonde temperature value. Calculated RH values show almost no bias between the surface and 800 hPa, while the original reported values show a negative bias of between 2% and 4% at most levels.

Page 12: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Data Precision Issues

•The method used to transmit the WVSS-II data from aircraft to ground limits the precision of the reports to only 3 digits: two for the mantissa of the report and 1 for the power of 10.

•Unfortunately, the process of rounding or truncating data to the nearest two-digit integer can add substantial error to the moisture reports exceeding 10 k/kg.

•This error varies according to the value of the reported mixing ratio itself. For example:

Observations of both 10.6 and 11.4 g/kg would be reported as 11 g/kg, even though the measurements themselves were separated by 0.8 k/kg.

Page 13: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Data Precision Issues

< 10 g/kg

10 g/kg

Note that the minimum requirement of 20 matches per bin was relaxed to 5 matches per bin due to the reduced number of data points with values 10 g/kg. However, the increase in RMS, Bias and SD for larger SH is clear.

Eliminating the low precision reports reduced the RMS and Standard Deviation by as much as 50% in the lowest 100 mb.

Page 14: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Proposed Data Encoding Alternative

Mixing Ratio to Encoded Report Value

using (Mixing Ratio) 0.4 Scheme

0

100

200

300

400

500

600

700

800

900

1000

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Mixing Ratio

En

co

de

d V

alu

e (

0 -

99

9)

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

Pre

cis

ion

(g/k

g)

ReportedValue

Precision

Page 15: Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS

Conclusions• Moisture observations made by WVSS-II equipped commercial (UPS) aircraft show a small, but positive bias in the boundary layer, with slightly larger values above. • Specific humidity RMS and standard deviation average around 1 g/kg at all levels. These specific humidity statistics correspond to RH biases of nearly zero throughout the lowest 200 hPa of the atmosphere and increasing to about 5% aloft.

•Mixing ratio values above 10 g/kg show dramatically higher RMS and Bias than those below 10 g/kg, probably due to the encoding precision conventions used in constructing the transmitted reports.

- Eliminating low precision reports reduced the RMS by as much as 50% (about 0.6 g/kg) in the lowest 100 mb.