1. NOAA/NESDIS/Center for Satellite Applications and Research
Possible Microwave Sounder References and Their Use for Re-Calibration of Other Satellites Cheng-Zhi Zou, Mitch Goldberg, Xianjun Hao, and Hui Xu
Thanks Bruce for the introduction. The title of my talk is ‘MSU/AMSU/SSU CDR development. I gave a talk three years ago in the STAR science forum about the MSU inter-calibration and trend and I kept talking this subject in the last few years in various occasions and hope people don’t get tired of it. But today I try to provide a comprehensive review of the current status and a discussion of various science issues include various bias correction, validation, inter-comparisons, web data support, and so on. I have reserved the room for two hours, but I will only talk about 45 minutes to one hour and allow plenty of time for questions. So don’t get scared about the length of the talk as suggested in the announcement.
NOAA/NESDIS/Center for Satellite Applications and Research
The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration or U.S. Government position, policy, or decision.
GSICS Annual Meeting 2019, March 4-8; Frascati, Italy

2. Requirement on Microwave Sounder Reference
Requirements of reference measurements can be different for weather prediction and climate change detection, unless an absolute zero bias is achieved
Weather Requirement: absolute accuracy better than 0.1~0.2 K is required for satellite data to be assimilated into NWP models without a bias correction
Unstable small biases are no good for climate change detection--unstable bias of ±0.1K may still give a large non-climate trend signal
Climate Requirement: stability is the primary requirement for climate change detection
large bias is not a big concern as long as it is stable
Temperature measurement stability (Ohring et al. 2005): 0.04K/Decade for tropospheric temperature
0.08K/Decade for stratospheric temperature
Need at least 33 years of measurement for the uncertainty of the global mean temperature trend to be within 20%
Satellite merging can produce longer time series
Continuity in channel frequency in instrument design
Mitch provided long time support for project from the program side, such as leveraging funding.
And Fuzhong also provides program support and coordinate the CRTM team to work with our product development team. You may notice that most of my SDS science team members are from his Branch.
I also want to thank Changyong for his long time support from scince side. I can always count on his support when I need a discussion on science. even when I need support from his team members.

3. Atmospheric Temperature CDR Development:
Involving Microwave/Infrared Sounders on NOAA/NASA/MetOp Satellite Series from 1978 to the present and onward to the future
MSU
SSU
AMSU-A
AIRS
NOAA-20
ATMS
CrIS
AMSU-A
IASI
MWS
IASI-NG
Present

4. ATMS Channels
Mitch provided long time support for project from the program side, such as leveraging funding.
And Fuzhong also provides program support and coordinate the CRTM team to work with our product development team. You may notice that most of my SDS science team members are from his Branch.
I also want to thank Changyong for his long time support from scince side. I can always count on his support when I need a discussion on science. even when I need support from his team members.
Weighting functions for ATMS channels 5 to 15. The AMSU-A weighting functions are the same as those of the ATMS counterpart channels.

5. Satellite Orbital Drifts
MetOp-A, -B, and future –C have close to the same 9:30am stable morning orbits
Aqua, SNPP, NOAA-20, and future JPSS have close to the same 13:30pm stable afternoon orbits
Terra has a stable 10:30am morning orbit
All other satellite’s orbits drifted with time
Mitch provided long time support for project from the program side, such as leveraging funding.
And Fuzhong also provides program support and coordinate the CRTM team to work with our product development team. You may notice that most of my SDS science team members are from his Branch.
I also want to thank Changyong for his long time support from scince side. I can always count on his support when I need a discussion on science. even when I need support from his team members.
Satellite local equator crossing time (LECT) for ascending orbits
(Plot is provided by STAR calibration team)

6. Challenges in Defining Reference Satellites —Satellite Orbital Drifts Induce Bias Drifts
Satellite Orbital Drifts Cause
Changes with time in diurnal Sampling
Biases change with time
Need complicated bias correction algorithms to remove these time-varying biases
This project focus on developing MSU/AMSU atmospheric temperature CDRs. The window channels will be addressed by another NOAA group.
In summary, we work on 15 atmospheric temperature channels, involving 15 satellites, with tempral coverage from late 1978 to present.
Each channel needs to be intercalibrated seperately.
With that, let me first talk about the MSU atmospheric temperature CDR development. The MSU started from 1978 on TIROS-N and ended on NOAA-14 in May So we don’t have MSU observations now. We have already completed the MSU CDR development and gained a lot of experiences. We have developed many new techniques for various bias correction procedure. So I am going to talk with more details on this instrument.
Inter-satellite difference time series for AMSU-A
satellite pairs.

7. Challenges in Defining Reference Satellites —Calibration Drifts
Inaccurate instrument calibration could result in time-varying biases between satellite pairs
Need complicated inter-calibration/recalibration algorithms to remove these time-varying biases
σ : ~ 0.1 K; Bias~0.5-1K
This project focus on developing MSU/AMSU atmospheric temperature CDRs. The window channels will be addressed by another NOAA group.
In summary, we work on 15 atmospheric temperature channels, involving 15 satellites, with tempral coverage from late 1978 to present.
Each channel needs to be intercalibrated seperately.
With that, let me first talk about the MSU atmospheric temperature CDR development. The MSU started from 1978 on TIROS-N and ended on NOAA-14 in May So we don’t have MSU observations now. We have already completed the MSU CDR development and gained a lot of experiences. We have developed many new techniques for various bias correction procedure. So I am going to talk with more details on this instrument.
Inter-satellite difference time series for AMSU-A satellite pairs
showing calibration drifting errors (plot from Zou and Wang 2011)

8. New Analyses: Stable SNPP and JPSS Orbits Make A Difference
Diurnal sampling difference is absent
– diurnal sampling biases are naturally
removed by satellites with stable orbits
of the same overpass time
Time series from different satellites
match with each other nearly perfectly
without applying any diurnal drift
corrections or time-dependent inter-
calibration
Calibration drifts could be estimated quite accurately
Small trend differences suggest absolute stability on either instruments
Radiometric stability within 0.04K/Decade for SNPP/ATMS and Aqua/AMSU-A for all analyzed channels
This project focus on developing MSU/AMSU atmospheric temperature CDRs. The window channels will be addressed by another NOAA group.
In summary, we work on 15 atmospheric temperature channels, involving 15 satellites, with tempral coverage from late 1978 to present.
Each channel needs to be intercalibrated seperately.
With that, let me first talk about the MSU atmospheric temperature CDR development. The MSU started from 1978 on TIROS-N and ended on NOAA-14 in May So we don’t have MSU observations now. We have already completed the MSU CDR development and gained a lot of experiences. We have developed many new techniques for various bias correction procedure. So I am going to talk with more details on this instrument.
Monthly global mean anomaly time series of brightness temperatures for AMSU-A channel 8 onboard Aqua (blue, top panel) versus ATMS channel 9 onboard SNPP (red, top panel) and their difference time series (green, top and lower panels). The AMSU-A and ATMS data are respectively from June 2002 and December 2011 to April The AMSU-A anomaly time series are overlaid by ATMS during their overlapping period with their differences shown as nearly a constant zero line in the same temperature scale. Amplified scale of temperature is used in the bottom panel to show detailed features in the anomaly difference time series. Both ATMS and AMSU-A data are from limb-adjusted views and averaged over ascending and descending orbits (plot from Zou et al. 2018).

9. All analyzed channels
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.
Radiometric stability achieves 0.04K/Decade for most channels

10. Asymmetric Diurnal Temperature Trends
MetOp-A nighttime trend at 21:30 a.m. was warmer than its daytime trend at 9:30 p.m. by K/decade globally
SNPP nighttime trend at 1:30 a.m. was warmer than its daytime trend at 13:30 p.m. by K/decade globally
In average, the midnight trend is warmer than the noon time trend by 0.036K/Decade globally
Over the global land, the midnight trend is warmer than the noon time trend by 0.072K/Decade
Diurnal temperature range, defined as the differences between the daily maximum and minimum temperatures, was found decreasing at a rate of K/decade during 1950–2004 over the global land surface (Vose et al. 2005)
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.
Monthly global mean anomaly time series of brightness temperatures for AMSU-A channel 4 onboard MetOp-A versus ATMS channel 5 onboard SNPP and their difference time series. The top and bottom panels are for ascending and descending orbits, respectively.

11. Satellites with stable but different overpass orbits
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.
Monthly anomaly time series of global ocean mean brightness temperatures for AMSU-A channels 4, 5, and 10 through 14 onboard MetOp-A (blue, left panel) versus ATMS channels 5, 6, and 11 through 15 onboard SNPP (red, left panel) and their differences (right panel) for ascending orbits. The AMSUA and ATMS data are respectively from January 2007 and December 2011 to April The AMSU-A time series are overlaid by ATMS during their overlapping period from 2012 to Both ATMS and AMSU-A data are from limb-adjusted views.

12. Analyses of Other Satellites
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.
Jumps in MetOp-A and MetOp-B AMSU-A TB differences linked to gain jumps in MetOp-B

13. Extend Similar Analysis to Other Satellites
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.
MetOp-A and MetOp-B AMSU-A TB differences After Recalibration

14. Perspective—Improved CDR Development
Stable observations from SNPP/ATMS and Aqua and MetOp-A AMSU-A could be used as references
SNPP/JPSS/ATMS could be merged together without conducting diurnal drift correction
Adjusting satellites with orbital drifts to the references using their overlaps Developing CDRs from the stable satellites backward to the earlier satellites
Improved diurnal correction algorithms—need reference for best effect
Improved accuracy in trend determination from CDRs are expected
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.

15. Perspective—Impact on Other Type of Measurements
Radiosonde Measurements – Compare with GRUAN to understand if it drifts or not (presentation in current session)
Compare with GPSRO data – trend in GPR RO and Aqua are in agreement within 0.04K/Dec for stratospheric channels (Khaykin et al. 2017)
Climate Reanalysis – change its bias correction strategy?
NOAA group (M. Bali) has been proposing to use IMICA recalibrated microwave sounder series as microwave references. The stable SNPP/ATMS and MetOp- A/AMSU-A could help to produce even better recalibrated time series and make the concept even more appealing
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.

16. References
Zou, C.-Z., M. Goldberg and X. Hao, 2018: New Generation of US Microwave Sounder Achieves High Radiometric Stability Performance for Reliable Climate Change Detection, Science Advances, eaau0049, 4, 1-10.
So here is a summary that needs to be deal with in the MSU/AMSU reprocessing. These issues include, but are not limited to, ……….
In this talk, I’ll be focusing on the intersatellite biases and warm target temperature contamination; but also touch a little bit on other problems.