Post on 19-Jan-2016
description
1Song.2.Yang@noaa.govOctober 16, 2008
Special Sensor Microwave Imager (SSM/I) Intersensor Calibration and Impact on
Precipitation Trend
Song Yang, Fuzhong Weng, Banghai Yan, and Ninghai Sun
NOAA/NESDIS/STARCamp Springs, MD 20746
4th Workshop of International Precipitation Working Group (IPWG), Beijing, Oct 13-17, 2008
2Song.2.Yang@noaa.govOctober 16, 2008
Outline
• Why need SSM/I TDR Calibration• SCO Calibration Technique• Impacts on TDRs/EDRs/CDRs• Impacts on Rainfall Climate Trend• Conclusions
3Song.2.Yang@noaa.govOctober 16, 2008
Ascending Descending
Overall
SSM/I Oceanic Rain-free Ta Difference against Scan Central Pixel before Calibration (60°S-60°N)
4Song.2.Yang@noaa.govOctober 16, 2008
SSM/I Monthly Oceanic Rain-free TDR Time Series
before Calibration
SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta
Ta (
K)
37V
Ta B
ias
(K)
Oceanic Rain-Free Monthly Mean Ta
5Song.2.Yang@noaa.govOctober 16, 2008
F13 provides the stable and longest time series for inter-sensor calibration
SSM/I Orbit Draft
6Song.2.Yang@noaa.govOctober 16, 2008
North Pole Region South Pole Region
DMSP Satellite SCO Intersections
7Song.2.Yang@noaa.govOctober 16, 2008
Analysis of SCO Pixels Ta - Water t 30 sec & d 3 Km)
19H
22V
F11
F14
F14
F11
Std 5
F11
Std 2
F11
Std 2|Ta| 20
100 140 180 220 260 300 100 140 180 220 260 300 100 140 180 220 260 300 100 140 180 220 260 300
8Song.2.Yang@noaa.govOctober 16, 2008
85 H
Bia
s °K
Std 2|Ta|
20
F13-F11 SCO Pixels Ta Bias (Water - with scan angle adjustment)
F13-F14 SCO Pixels Ta Bias - Water (t 30 sec & d 3 Km, with scan angle adj.)
9Song.2.Yang@noaa.govOctober 16, 2008
19V 19H 22V 37V 37H 85V 85H Satellite
Surface Type Bias Bias Bias Bias Bias Bias Bias
W 0 0 0 0 0 0 0 0 0 0 0 0 0 0
L 0 0 0 0 0 0 0 0 0 0 0 0 0 0
I 0 0 0 0 0 0 0 0 0 0 0 0 0 0 F08
C 0 0 0 0 0 0 0 0 0 0 0 0 0 0
W -0.16 2.66 -0.12 2.19 -0.20 2.27 -0.16 1.42 -0.09 2.65 -0.30 1.61 -0.29 2.81
L 0.54 1.19 0.33 1.32 0.53 1.32 0.44 1.36 0.49 1.49 0.11 2.31 0.12 2.39
I -0.05 1.23 -0.03 2.01 -0.04 1.10 -0.04 0.91 0 2.13 -0.07 1.19 -0.09 3.96 F10
C 0.11 0.57 0.23 1.13 0.09 0.46 0.08 0.62 0.23 1.22 -0.02 1.20 0.10 1.28
W -0.56 0.55 0.09 1.07 -0.88 1.03 -0.34 0.55 0.39 1.58 -0.92 1.46 -0.17 1.10
L 0.02 1.01 0.21 1.05 -0.17 1.08 -0.19 0.96 0.01 1.04 -0.56 1.69 -0.62 1.56
I 0.23 0.90 0.35 0.98 -0.05 0.92 0.03 0.87 0.28 1.11 -0.26 2.01 -0.24 1.99 F11
C -0.10 1.83 0.21 2.50 -0.42 1.90 -0.07 1.82 0.19 2.58 -0.03 3.32 -0.03 3.49
W -0.43 0.64 0.32 0.54 -0.32 0.85 -0.81 0.45 0.21 0.63 -0.32 0.89 0.32 1.29
L 0 0.85 0.11 0.75 0.10 0.97 -0.42 0.67 -0.06 0.98 -0.01 1.54 0.23 1.30
I 0.06 0.76 0.25 0.87 0.13 0.91 -0.32 0.88 -0.05 0.83 0.23 1.32 0.43 1.33 F14
C 0.20 1.25 0.38 1.85 0.30 1.28 -0.08 1.16 0.25 1.73 0.39 2.67 0.74 2.86
W 0.42 0.65 -0.23 0.55 0.03 0.87 -0.17 0.51 -0.04 0.67 -0.05 0.87 -0.02 1.32
L 0.15 0.85 0.06 0.71 0.02 0.75 -0.02 0.59 -0.04 0.56 -0.02 0.81 -0.09 0.74
I 0.83 0.81 0.23 0.85 0.43 0.83 0.50 0.63 0.30 0.72 0.71 1.19 0.35 1.65 F15
C 0.16 1.10 -0.13 1.55 -0.07 1.08 0.12 1.10 0.09 1.64 0.33 1.91 0.41 2.30
Criteria: | t| 0.5 min; d 3 km; 2 K;Ta| 20 K; : Standard deviation (K) Surface Type Category: W Š Water; L Š Land; I Š Ice; C Š Coast
SSM/I TDR Bias Correction CoefficientsF13 as Reference Satellite
10Song.2.Yang@noaa.govOctober 16, 2008
SSM/I Monthly Oceanic Rain-free TDR Time Series after Calibration (F13 as Reference Satellite)
SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta
Ta (
K)
37V
Ta B
ias
(K)
Bef
ore
Cal
ibra
tion
Oceanic Rain-Free Monthly Mean Ta
Ta B
ias
(K)
37V
Ta (
K)
Oceanic Rain-Free Monthly Mean Ta
Aft
er C
alib
rati
on
SSM/I Intersensor Bias of Oceanic Rain-Free Monthly Mean Ta
11Song.2.Yang@noaa.govOctober 16, 2008
Before Calibration After CalibrationSSM/I Intersensor Bias of Oceanic Rain-Free Monthly Ta
12Song.2.Yang@noaa.govOctober 16, 2008
19V 19H 22V 37V 37H 85V 85H
Ta_Raw (K)
0.59 0.31 0.65 0.59 0.33 0.77 0.85
Ta_Cal
(K) 0.30 0.38 0.48 0.21 0.19 0.40 0.39
Chg (%)
-49 22 -26 -64 -42 -43 -54
Mean SSM/I TDR Absolute BiasF13 as Reference Satellite
13Song.2.Yang@noaa.govOctober 16, 2008
SSM/I Monthly Oceanic Rain-free TDR Trend (F13 as Reference Satellite)
Before C
alibration
After C
alibration
19V 19H 22V 37V 37H 85V 85H
S S S S S S S
Before 188.5 -0.92 125.2 -0.11 212.2 -0.74 208.3 -0.62 151.5 -0.18 251.8 -0.72 219.6 -0.46
After 188.2 -0.54 124.9 -0.23 211.9 -0.54 208.0 -0.58 151.4 -0.30 251.5 -0.36 219.3 -0.38
Comparison of SSM/I Monthly Oceanic Rain-free TDR before and after Calibration [(K), S (K/10yr)]
14Song.2.Yang@noaa.govOctober 16, 2008
F14 SSM/I Monthly Mean Surface Rainrate for December 2006 from NOAA Heritage Rain Algorithm and Matched TRMM 3B42
BeforeCalib.
AfterCalib.
Matched3B42
0.5°x0.5°grid scale
15Song.2.Yang@noaa.govOctober 16, 2008
F14 SSM/I Monthly Mean Surface Rainrates for December 2006 from NOAA Heritage Rain Algorithm
BeforeCalib.
AfterCalib.
Difference(aft - bef)
0.5°x0.5°grid scale
29% bias deduction with calibrated TDR against matched TRMM 3B42 Rain products
16Song.2.Yang@noaa.govOctober 16, 2008
F14 SSM/I Monthly Mean Total Precipitable Water (TPW) for December 2006 from NOAA Heritage Rain Algorithm
BeforeCalib.
AfterCalib.
Difference(aft - bef)
11% bias deduction with calibrated TDR against radiosonde measurement
17Song.2.Yang@noaa.govOctober 16, 2008
F14 SSM/I Monthly Mean Sea Ice Concentration (%) Near North Pole
Region for December 2006 from NOAA Heritage Algorithm
Before Calib. After Calib. Difference (aft - bef)
18Song.2.Yang@noaa.govOctober 16, 2008
GPCP
Climate Trend of Monthly Precipitation from SSM/I and GPCP
SSM/I
19Song.2.Yang@noaa.govOctober 16, 2008
Climate Trend of Oceanic Total Precipitable Water Path
20Song.2.Yang@noaa.govOctober 16, 2008
The importance of SSM/I intersensor calibration is presented.
NOAA/NESDIS SCO-based calibration scheme can dramatically reduce the intersensor biases of SSM/I TDRs.
Test results indicate that the SSM/I TDR calibration scheme shows significant impacts on EDRs/CDRs.
Although the bias correction of SSM/I TDRs is small, the calibration has a significant impact on TDR’s trend.
The very small decreasing trend of precipitation is evident, however, this trend could not be treated as the “truth” because of uncertainties associated with the calibrations and SSM/I sampling issue.
Conclusions