Validation of AIRS Cloud-Clearing Algorithms C. Cho, C. - - PowerPoint PPT Presentation

▶
validation of airs cloud clearing algorithms
SMART_READER_LITE
LIVE PREVIEW

Validation of AIRS Cloud-Clearing Algorithms C. Cho, C. - - PowerPoint PPT Presentation

Dec 04, 2023 530 likes •703 views

Validation of AIRS Cloud-Clearing Algorithms C. Cho, C. Surussavadee, and D. Staelin Presented to the AIRS Team Meeting Nov. 30, 2004 MIT Cho, Chen, REMOTE SENSING AND ESTIMATION GROUP Surussavadee, http://rseg.mit.edu Staelin 1

slide-1
SLIDE 1

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

1

Cho, Chen, Surussavadee, Staelin

Validation of AIRS Cloud-Clearing Algorithms

  • C. Cho, C. Surussavadee, and D. Staelin

Presented to the AIRS Team Meeting

  • Nov. 30, 2004
slide-2
SLIDE 2

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

2

Cho, Chen, Surussavadee, Staelin

Overview

  • Cloud Clearing (C.Y. Cho)
  • Stochastic cloud-clearing and estimation of NCEP SST
  • Cloud-clearing enhancement with AMSU
  • Stochastic cloud-clearing vs ECMWF + SARTA 1.05
  • Diurnal Variations of Precipitation (F.W. Chen)
  • ECMWF/MM5 + RTE vs HSB Precipitation TB’s

(C. Surussavadee)

slide-3
SLIDE 3

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

3

Cho, Chen, Surussavadee, Staelin

Data Used for AIRS SST Retrieval vs NCEP

  • 24 focus-day granules: 2003: 1/3, 4/9, 7/14
  • Ocean, |LAT| < 40 °, |_|<16°, daytime
  • Training: 1755 golfballs; testing: 1365 golfballs
  • Must pass AIRS Retrieval_QA_flag test (~29% yield)
  • QA-approved golfballs ranked using AIRS-cleared

1217cm-1 window (v.3.5.0) minus observed radiance.

Choongyeun Cho

slide-4
SLIDE 4

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

4

Cho, Chen, Surussavadee, Staelin

SST Retrieval Results

AMSU Contribution

= 29 percent of total

Choongyeun Cho

slide-5
SLIDE 5

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

5

Cho, Chen, Surussavadee, Staelin

ECMWF Data Set Used

  • Global data 2003: 8/21, 9/3, 10/12
  • Ocean, |LAT| < 40 °, |_|<16°, daytime
  • 499 golf balls for training; 499 for testing (SARTA v1.05)
  • “Clear” means: (CC – observed) < 1K (17% of all GB)
  • AIRS instrument noise was reduced by averaging the 2

to 9 warmest pixels as WF-peak altitude increases from the surface to ~10 km

Choongyeun Cho

slide-6
SLIDE 6

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

6

Cho, Chen, Surussavadee, Staelin

AIRS Cloud-Clearing vs. ECMWF

AMSU Contribution

(best 17 percent)

AMSU Contribution

Choongyeun Cho

slide-7
SLIDE 7

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

7

Cho, Chen, Surussavadee, Staelin

Cloud-Cleared Image

Granule# 208 7/1/03 1219 cm-1 (0.22 km WF) Baselines are QA-OK pixels Interpolated with 2-D 3rd-order polynomial

Choongyeun Cho

Masked out 75% brightest vis3 pixels RMS for QA “OK” pixels

slide-8
SLIDE 8

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

8

Cho, Chen, Surussavadee, Staelin

Cloud-cleared RMS relative to baseline

0.49 (34%) 0.51 (34%) 0.26 (34%) 7/14/03 #208 0.39 (31%) 0.49 (31%) 0.28 (31%) 1/3/03 #208 0.63 (48%) 0.74 (48%) 0.38 (48%) 4/9/03 #92 8.2 µm (WF peak ~0.2 km) 13.1 µm (WF peak ~1.7 km) 13.9 µm (WF peak ~2.9 km) Channels Data used

  • RMS (oK) with respect to the baseline determined by 2-D

3rd order polynomial fit to clearest pixels

  • RMS is for AIRS QA “OK” pixels; percentages given below

Choongyeun Cho

slide-9
SLIDE 9

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

9

Cho, Chen, Surussavadee, Staelin

Diurnal Variation of Precipitation – AMSU

Precipitation Frequency, ~LT maximum

25W 155E 25W 155E 60N 60S 8/2001 - 7/2002 8/2002 - 7/2003

DHS 1104 -9-

FW Chen

Frederick W. Chen

slide-10
SLIDE 10

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

10

Cho, Chen, Surussavadee, Staelin

Diurnal Variation of Precipitation – AMSU

Mean-Normalized Diurnal Amplitude

25W 155E 25W 155E 60N 60S 8/2001 - 7/2002 8/2002 - 7/2003

DHS 1104 -10-

Frederick W. Chen

slide-11
SLIDE 11

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

11

Cho, Chen, Surussavadee, Staelin

183±7 GHz June 22, 2003 15-km resolution

MM5 Brightness Temperatures vs. AMSU

AMSU

Chinnawat Surussavadee

MM5 + NCEP 1x1o

slide-12
SLIDE 12

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

12

Cho, Chen, Surussavadee, Staelin

MM5 Brightness Temperatures vs. AMSU

MM5 + ECMWF

Chinnawat Surussavadee

AMSU 183±3 GHz June 22, 2003 15-km resolution MM5 + NCEP 1x1o

Chinnawat Surussavadee

slide-13
SLIDE 13

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

13

Cho, Chen, Surussavadee, Staelin

1

HISTOGRAMS OF MM5 vs. AMSU-B TB’S

Channel 5: 183 ± 7 GHz Channel 4 183 ± 3 GHz 1 Average of 20 storm systems at 15-KM resolution

Chinnawat Surussavadee

slide-14
SLIDE 14

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

14

Cho, Chen, Surussavadee, Staelin

Summary of Results

  • Cloud Clearing:

 AIRS CC (v.3.5.0) yielded ~0.67 K rms w.r.t. NCEP SST (~20% of all pixels; 24 granules)  Stochastic cloud-clearing yielded: <~1° rms vs. ECMWF (>3-km); <0.6K rms (>7 km)  AMSU improves cloud-clearing vs SST and ECMWF  ~0.26 - 0.74K rms w.r.t. “baseline” for 0.2-2.9 km sample  Residual “CC” errors may not be due only to clouds

  • Precipitation

 Diurnal variations robust and informative; AMSU unique  MM5 brightness statistics consistent with AMSU/HSB (early results most consistent with 3-D snow )

slide-15
SLIDE 15

MIT

REMOTE SENSING AND ESTIMATION GROUP http://rseg.mit.edu

15

Cho, Chen, Surussavadee, Staelin

AIRS Stochastic Cloud-Clearing Algorithm

AIRS TB AMSU ch.5,6,8,9,10 cosine (scan angle) Land fraction AIRS 4 Delta-cloud PC’s Δcloud AIRS stochastic cloud-cleared TB’s Find warmest* among 9 pixels Find coldest* among 9 pixels NAPC 2 Take 3 PC’s NAPC 1 Take 7 PC’s

L I N E A R E S T I M A T O R

PC-1 NCEP SST 294 7 3 5 4 ΔTB

  • +

+ + * Warmest/coldest based on 38 channels peaking 3-5km

269 15-µm channels 25 8-µm channels

Training data 294 294 294 ECMWF + SARTA (v.1.05)