AMSR Sensor Team Workshop

Day 3 (December 8, 1999)

Session: AMSR Sensor Team Workshop
Room: 104
Agenda:

Summary of Major Discussions

1. Soil Moisture (Dr. Jackson)
Dr. Jackson presented the status of the algorithm development and focused on SGP 99. His presentation covered the following topics.

Multi-year Soil Moisture Estimation using SSM/I over the SGP
SGP99; objectives, goal, sensing systems, results
NOAA ETL Polarimetric Scanning Radiometer; RFI.

Questions & Answers, and comments:
Dr. Njoku didn't detect persistence evidence of RFI at 6.6GHz with the data taken over Oklahoma area in 1987.

2. Soil Moisture (SM) (Dr. Palocia)
Dr. Palocia presented the status of the algorithm development and focused on SGP 99. Her presentation covered the following topics.

Use of Polarization Indices (PI) and Brightness Temperatures at C and X band for estimating soil moisture using AMSR data
Temperature trends of Tb and PI at C band and SMC
Proposed algorithm.
Sensitivity to vegetation of PI at X-band
Retrieval of SMC from PI data at C band corrected by PI data at X-band
The use of Tb at C-band for measuring SMC.
Future work; IROE experimental campaigns 1999-2000.

Questions & Answers, and comments:
Dr. Jackson: Ground test provides one point data for 150km spacecraft data footprint. Because of this fact, it is difficult to validate spacecraft data using ground data. TMI data is better than SSM/I because of its higher resolution.
Dr. Koike: The total number of match-up dataset is 50 and only 4 are good. The NDVI is 0.3. You need to select good sites for meaningful evaluation.

3. Soil Moisture (SM) (Dr. Njoku)
Dr. Njoku presented the status of the algorithm development. His presentation covered the following topics.

Algorithm flowchart.
Retrieval method; interactive algorithm, regression algorithm.
Simulation results; AMSR-A land classification
SMMR estimated soil moisture southern great plains (and 6.6 GHz Polarization difference)
SGP99; PALS instrument on C130 aircraft, brightness temperature data.
Land surface hydrology workshop (November 2-3, 1999); soil moisture breakout group was interested in joining the ASMR soil moisture team.

Questions & Answers, and comments:
Question (Dr. Jackson): Do you use radar data?
Answer: Yes. Simon uses radar data. We will get radar data by the end of this month.

4. Match-up dataset (RESTEC Mr. Muto)
Mr. Muto presented a generation plan of match-up dataset that will be used for AMSR validation. His presentation covered the following topics.

Objectives.
ASMR algorithm validation flow.
Outline of match-up datasets; operational path and experimental path.
Outline of main data source; GTS data, Radar- AMeDAS data.
Match-up datasets; water vapor, cloud liquid water, sea surface wind speed, precipitation, sea ice concentration, snow water equivalent, soil moisture
Plan for achieving match-up datasets.

Questions & Answers, and comments: Question (Dr. Njoku): There are useful data of Illinois. Can you add these data to the match-up datasets?
Answer (Dr. Koike): Yes, it is possible. However, the data have to be routinely taken.
Comment (Dr. Jackson): I guess Tibet is chosen because of its low vegetation level. Illinois is in high vegetation level throughout the year.
Question (Dr. Comiso): For Sea Ice data, we need high-resolution data such as Landsat and AVHRR data. Can you add those data to the match-up datasets?
Answer (Dr. Koike): This was discussed in the Cal/Val session on December 9^th.
Question (Dr. Hwang): Do you plan to archive all experimental datasets in a central location?
Answer (Dr. Shibata): No. It would be a big project to implement a central archive for all experimental datasets.
Comment (Dr. Koike): JAXA will not prepare all match-up datasets.

5.SWE (Cal/Val) (Dr. Koike)
Dr. Koike presented the status of calibration/validation activities for snow water equivalent measurement. His presentation covered the following topics.

Post-launch and pre-launch validation plans.
GAME-Tibet IOP in 1998.
Proposed activities during the data collection phase (2001- 2002)
CEOP configuration.

Questions & Answers, and comments:
Question (Dr. Chang): Who is the leader of the Canadian team.
Answer: Dr. Ron Stewart is the leader of the science team. For snow, Dr. Barry Goodson is the lead.
Question (Dr. Comiso): What kind of snow radiometric characterization is planned? Will you have a dielectric probe or microwave radiometer?
Answer: We don't have such a plan. If we can cooperate with the AMSR-E team, we can do. It is difficult for ground measurements.

6.SWE (Cal/Val) (Dr. Chang)
Dr. Chang presented the status of calibration/validation activities for snow water equivalent measurement. His presentation covered the following topics.

Validation; February 2000 with MODIS/ snow validation, March 2000 with Prof. Tsang, March 2001 with Prof. Hallikainen, 2001/2002 EOS post 2002 cold land/ snow mission.
Theo. Roosevelt N.P.
Finland experiments.

Questions & Answers, and comments: None

7. AP (Cal/Val) (Dr. Aonashi)
Dr. Aonashi presented the status of calibration/validation activities for precipitation measurement. His presentation covered the following topics.

Outline; objectives, strategy, status report.
Objectives; focus on precipitation in winter for high altitude areas.
Strategy; operational path, experimental path, and use of TRMM (TMI, PR) data.
Pre-launch validation; use of TRMM TMI data, Wakasa Bay field
Post-launch validation; format of match-up dataset, Wakasa Bay field campaign in January - February 2001 and 2002, Tibet field campaign in May - August of 2001 and 2002, Ishigaki-jima Island in May - June of 200X.

Questions & Answers, and comments:
Comment (Dr. Petty): This is an excellent opportunity to do cold season precipitation validation that has never been conducted enough in the past. The proposed validation will give more insight into the relationship between snow fall and microwave measurement.
Comment (Dr. Lobl): The AMSR-E team plans the validation plans separately from the AMSR team. We need to talk and combine efforts. This subject will be further discussed on Thursday morning.

8. SIC (Dr. Nishio)
Dr. Nishio presented the status of calibration/validation activities for precipitation measurement. His presentation covered the following topics.

Validation plan; validation criteria.
Validation method.
Brightness temperature of different sea ice concentration.
Validation schedule (Year 2000 - 2006); Arctic & Okhotsk Sea, Antarctica.

Questions & Answers, and comments:
Comment (Dr. Cavalieri):AMSR-E snow depth on sea ice is a standard product. 3 aircraft campaigns are planned for the next three years.

9. SIC (Dr. Comiso)
Dr. Comiso presented the status of calibration/validation activities for precipitation measurement. His presentation covered the following topics.

Validation techniques; in situ/ship, aircraft, satellite high resolution data.
Basic types of sea ice and their signatures; grease ice, pancakes, Nilas, young ice, first year ice, and multiyear ice.
Pre-launch validation; historical cruises/ice camps, historical aircraft data, and historical high resolution satellite data.
FIRE-3/SHEBA Validation studies; aircraft data (ER-2 and C130) and satellite data.
Planned post-launch validation program; Antarctic campaigns, arctic campaigns, and synergistic studies with MODIS, GLI, Landsat, Buoy, and other data sets.
Antarctic 2001.

Questions & Answers, and comments: None

10. SST (Cal/Val) (Dr. Shibata)
Dr. Shibata presented the status of calibration/validation activities for SST measurement.
Questions & Answers, and comments:None
Question (Dr. Takeuchi): Temporal accuracy is important. Do you plan to continue WVP-1500?
Answer (Mr. Imaoka): Yes. A minimum time for observation is 15 minutes.

11. SST (Cal/Val) (Dr. Chille Gentlemann for Dr. Wentz)
Dr. Gentlemann presented the status of SST calibration and validation activities. Her presentation covered the following topics.

TMI SST- IR SST comparison; Reynolds weekly, MCSST, Pathfinder v4.1, GOES warmest Pix, and GOES hourly.
Check with Analysis of high wind events.
Check with rain attenuation.
Algorithm validation using buoy data.
Cloud algorithm validation; ASMR, SSM/I, GOES

Question: TMI results are fantastic. Infrared SST validation strategy (using buoys) isn't well liked. Do you regress to buoys?
Answer: No, we use RTM based algorithm.
Question: Pathfinder is systematically bad. Those results show Pathfinder having a larger bias in Water Vapor than MCSST.
Answer:Yes, larger bias, maybe due to Pathfinder interim version rather than Version 4.1 (not available yet).
Question (Dr. Comiso): The Reynolds data were used as input to the Pathfinder algorithm. The latter algorithm actually made the input product worth. Is this true?
Answer: Yes.
Question (Dr. Dunbori): What is penetration depth?
Answer: 1mm.
Question (Dr. Njoku): How do you know which of these products is an accurate one with respect to water vapor?
Answer: Atmosphere 97% transparent, we retrieve Water Vapor so our SSTs are not biased. Bias shown due to fact that SST & Water Vapor are correlated and also possible Water Vapor biasing in infrared SSTs.

12. SM (Cal/Val) (Dr. Koike)
Dr. Koike presented the status of SM calibration and validation activities. His presentation covered the following topics.

Match-up dataset for soil moisture.
GAME- Tibet IOP in 1998.
Schedule.
Validation sites for AMSR.
CEOP configuration.
Proposed activities during the data collection phase (2001 - 2002).

Questions & Answers, and comments:
Question (Dr. Jackson): Are you purchasing Chinese and Mongolian data?
Answer: No. We are establishing a corroborative arrangement. Next year is an anniversary.
Measurement taken 0 - 10 cm in depth. Similar to Russian data. There will be a problem.
Answer: Yes, it is similar.

13. SM (Cal/Val) (Dr. Jackson)
Dr. Jackson presented the status of SM calibration and validation activities. His presentation covered the following topics.

Operational versus experimental.
SGP2001; need more resources.
Key elements; funding, SGP site, July 2001, PSR-C (including 10.7GHz), 2-D instruments + conventional.
Additional sites; Iowa- corn and soybeans.
Can large satellite footprints be validated? : Grayson and Western (1998)
Soil climate analysis network (SCAN); data available hourly.

Questions & Answers, and comments: None.

14. SM (Cal/Val) (Dr. Palocia)
Dr. Palocia presented the status of SM calibration and validation activities. Her presentation covered the following topics.

IROE experimental campaigns 1999 - 2000; Morsex, ForMon, MAP, SRTM.
Formon 99 - Phase 1; instrument configuration.

Questions & Answers, and comments:
Question: How quickly can you measure pitch and roll?
Answer: No problem because the aircraft is rather stable and the incident angle very large. We have some problems with helicopter stability.

15. SM (Cal/Val) (Dr. Njoku)
Dr. Njoku skipped his presentation because the previous presenters covered what he planned to cover.

16. Home Page (Ms.Kachi)
Dr.Kachi summarized two home pages that EORC have built on AMSR.

EORC ADEOS-II/ AMSR Home Page
EORC Home Page
FTP service.
Data subsetting service
Level 3 product images.
Data order service.
On-line data distribution service.
Demonstration.

Questions & Answers, and comments: None.

17. Presentation by New PI's

(1) G. Heygster
Dr. Heygster presented a study proposal and covered the following topics.

High resolved ice edge with IED procedure.
Synergetic algorithm AMSR - Sea winds.
Sea ice
20 year mean ice data available via Internet.
Cloud liquid water over the marginal ice zone.
Temperature profiling.

Questions & Answers, and comments:
Question (Dr. Cavalieri): Have you compared sea ice drift results with Arctic Ocean buoy data?
Answer: Yes, they compared well.
Question (Dr.Takeuchi): Do you intend to find boundaries of sea ice?
Answer: The original purpose of the study is

(2) D. Cavalieri
Dr. Cavalieri presented a study proposal and covered the following topics.

Revised NASA team algorithm attributes.
Revised NASA team sea ice algorithm.
Sample data.
Algorithm modifications for new and young ice types in the Bering and Okhotsk Seas.

Questions & Answers, and comments: Question (Dr. Comiso): There are cases when the 85 GHz channel is opaque to the atmosphere. How does your algorithm handle this problem?
Answer: Much less than 1% of pixels are saturated.
Question (Dr. Comiso): In the Odden region the effect of storm is to increase the ice concentration by about 30% when the 85GHz channel is utilized. This can be the reason why he retrieval over the Antarctic is almost 100% everywhere.
Answer: This is not true. The algorithm saturates. We make use of atmospheric radiative transfer model to correct for atmospheric effects.

(3) F. Wentz
Dr. Wentz presented a study proposal and covered the following topics.

Combine SeaWinds and AMSR on ADEOS-II; atmosphere data, wind speed, and wind direction.
Active - passive microwave remote sensing; correlation.
Modulation of surface winds by SST.
TMI SST, QuikScat friction velocity data.
Curl and divergence data.
Winds and SST in Hurricanes.

Questions & Answers, and comments: None

(4) A. Liu
Dr. Liu presented a study proposal and covered the following topics.

Antarctic sea ice drift by wavelet analysis of NSCAT ad SSM/I data on daily basis.
Sea - Ice motion algorithm.
Arctic Sea - Ice motion from SSM/I data.
Comparison among buoy, scatterometer, and SSM/I.

Questions & Answers, and comments:
Question (Dr. Comiso): How do you resolve differences when QuikScat and AMSR data results do not agree but there is no buoy data to verify which one is correct?
Answer: We can always find buoy data.
Question (Dr. Comiso): In the Antarctic region, there are large areas where there are no buoy data.
Answer: We can drop some buoys.

(5) J. Schulz (Dr. Petty for Dr. Schulz)
Dr. Petty presented a study proposal and covered the following topics.

Workpackage structure and time line.

Questions & Answers, and comments: None.

(6) V. Lakshmi
Dr. Lakshmi presented a study proposal and covered the following topics.

New way to calibrate land surface model.
Calibration/ Validation strategy.
Satellite algorithm calibration with model.
Issues.

Question (Dr. Koike): We have a lot of experiences of hydrological modeling. We can get a good validation for hydrological model using stream flow data even if simulated soil moisture distribution is not realistic.
Answer: Distributed validation strategy is effective.

(7) I. Kaihotsu
Dr. Kaihotsu presented a study proposal and covered the following topics.

Research objectives.
Mongolian plateau experiment.
Ground-based observations with the ADEOS-II measurement; AWS and ASSH.
Intensive observation in the experiment.
Anticipated results.
Schedule.

Questions & Answers, and comments:
Question (Dr. Jackson): Do you just record data with AWS and ASSH or transmit data from AWS and ASSH?
Answer: I just record the data.
Question (Dr. Jackson): What is the shallowest depth of the measured soil moisture? Is it 0 - 10cm?
Answer: We can measure at the different depth; 3cm, 8cm, 30cm, and 80cm.
Question (Dr. Jackson): Who does on-site data collection, yourself or somebody else?
Answer: We have a cooperative agreement with the Mongolian National Research Institute. The Mongolian National Research Institute does on-site data collection.

(8) H. Enomoto
Dr. Enomoto presented a study proposal and covered the following topics.

Research outline.
Automatic data collection stations.
Additional data measurement sites in Antarctica.
Snow property simulation model "Crocus".
Effects of heat wave on snow surface.

Questions & Answers, and comments: Question (Dr. Liu): The microwave temperature brightness data indicated large fluctuation. Is the fluctuation due to atmosphere?
Answer: Yes.

(9) W. Liu
Dr. Liu presented a study proposal and covered the following topics.

Ocean surface forcing and responses.
Seaflux from space.

Questions & Answers, and comments: None.

(10) K. Aonashi
Dr. Aonashi presented a study proposal and covered the following topics.

Background; higher resolution of global NWP model (from 50 km to 8km), MWR TB data.
Objective.
Method; TB, rain coverage, scattering/absorption ratio.

Question (Dr. Koike): Do you have any plan to use products other than precipitation?
Answer: I plan to use other products in addition to precipitation.

(11) M. Freilich
Dr. Freilich presented a study proposal and covered the following topics.

Multiple sensors to obtain data for steep topography of islands surrounded by ocean.
Winds around South Georgia Island.
Combination of scatterometer,

Comment (Dr. Petty): I saw a very similar signature of SSM/I wind retrieval in Gulf of Mexico in 1987 and thought the data was incorrect. Hearing your presentation I think the data represented the real wind data.