AMSR Data Catalog – AMSR web at JAXA Earth Observation Research Center (EORC)

Data Catalog
Mission Requirement
AMSR3
Standard Product

AMSR3 Mission Requirement: Standard Product

Product ^*1		Stored Physical Quantity	ID	Area	Spatial Resolution (Approx. size)	Required Accuracy ^*2		Range	Remarks
Product ^*1		Stored Physical Quantity	ID	Area	Spatial Resolution (Approx. size)	Release ^*3	Standard ^*4	Range	Remarks
Brightness Temp.	Brightness Temp.	Brightness Temp. (6-89GHz)	Depends on processing level	Global	5 – 50 km	±1.5 K	±0.3 K	2.7 – 340 K	Difference between ascending and descending orbits of global average after bias removal based on brightness temperature estimation of AMSR2 or numerical weather prediction model over ocean and clear sky areas.
	Brightness Temp.	Brightness Temp. (166, 183GHz)	Depends on processing level	Global	10 km	±1.5 K	±1.0 K	2.7 – 340 K
	Resampled Brightness Temp.	Brightness Temp. (6-89GHz)	Depends on processing level	Global	5 – 50 km	±1.5 K	±0.3 K	2.7 – 340 K	Difference between ascending and descending orbits of global average after bias removal based on brightness temperature estimation of AMSR2 or numerical weather prediction model over ocean and clear sky areas.
	Resampled Brightness Temp.	Brightness Temp. (166, 183GHz)	Depends on processing level	Global	10 km	±1.5 K	±1.0 K	2.7 – 340 K
Atmosphere	Total Precipitable Water	TPW over Ocean	TPW	Global over ocean	15 km	3.5 kg/m²	3.0 kg/m²	0 – 70 kg/m²	RMSE compared to GPS and radiosonde
	Total Precipitable Water	TPW over Land	TPW	Global over land*	15 km	6.5 kg/m²	3.5 kg/m²	0 – 70 kg/m²	RMSE compared to GPS and radiosonde. *Excludes vegetated and cryosphere areas.
	Cloud Liquid Water Content	Cloud Liquid Water Content	CLW	Global over ocean	15 km	0.10 kg/m²	0.05 kg/m²	0 – 1.0 kg/m²	RMSE compared to optical sensors
	Precipitation	Rainfall Rate	PRC	Global	15 km	Ocean 50 % Land 120 %	Ocean 50 % Land 120 %	0 – 20 mm/h	Relative error in 0.5-degree grid average compared to GPM/DPR, ground radar networks, etc.
	Precipitation	Snowfall Rate	PRC	Global	10 km	Ocean 130%* Land 200%*	Ocean 130%* Land 200%*	0 – 4 mm/h	Relative error in 0.5-degree grid average compared to GPM/DPR. *Evaluated by monthly accumulation for 1mm/month or more.
Ocean	Sea Surface Temp.	6GHz Sea Surface Temp.	SST	Global over ocean	50 km	0.8 °C	0.5 °C	-2 – 35 °C	RMSE compared to buoys
		10GHz Sea Surface Temp.	SST		30 km		0.6 °C
		Multi-band SST	SST		30 km		0.6 °C
	Sea Surface Wind Speed	Sea Surface Wind Speed	SSW	Global over ocean	15 km	1.5 m/s	1.0 m/s	0 – 30 m/s	RMSE compared to buoys
	All-weather Sea Surface Wind Speed	All-weather Sea Surface Wind Speed	ASW	Global over ocean	50 km	7 m/s	5 m/s	0 – 70 m/s	RMSE compared to dropsondes (wind speed over 15 m/s)
Cryosphere	Sea Ice Concentration	Sea Ice Concentration	SIC	Polar region over ocean	15 km	10 %	10 %	0 – 100 %	RMSE compared to optical sensors
	High-resolution Sea Ice Concentration	High-resolution Sea Ice Concentration	HSI	Polar region over ocean	15 km	15 %	15 %	0 – 100 %	RMSE compared to optical sensors
	Sea Ice Motion Vector	Sea Ice Motion Vector	SIM	Polar region over ocean	50 km	6 cm/s	6 cm/s	0-40 cm/s	RMSE compared to buoys
Land	Snow Depth	Snow Depth (Snow Water Equivalent)	SND	Global over land	30 km	20 cm	20 cm	0 – 100 cm	Mean absolute error compared to ground observations
Land	Soil Moisture Content	Soil Moisture Content	SMC	Global over land	50 km	10 %	5 %	0 – 40 %	Mean absolute error compared to ground observations

The brightness temperature was converted from the sensor output to the most basic observed quantity. Other physical quantities were converted from brightness temperature to physical quantities via a conversion algorithm.
Accuracy is expressed as root mean square error (RMSE) of the instantaneous value unless otherwise indicated. The accuracy of brightness temperature depends on the calibration accuracy of the on-board and ground processing. Accuracy of geophysical quantities depends on brightness temperature accuracy, algorithm performance, and validation methods.
Release accuracy is the minimum accuracy that can be released as data that can contribute to climate change analysis.
Standard accuracy is a useful and standard accuracy level based on AMSR-E and AMSR2 results.

AMSR3 Mission Requirement Revision History (Standard Product)

Data Catalog
Mission Requirement
AMSR3
Research Product

AMSR3 Mission Requirement: Research Product

Product		ID	Area	Spatial Resolution (Approx. size)	Release Accuracy ^*1	Range	Remarks
Brightness Temp.	L1C Center Position Co-registered Brightness Temp.	Depends on processing level	Global	5-50km	±1.5 K	2.7 – 340 K	Difference between ascending and descending orbits of global average after bias removal based on brightness temperature estimation of AMSR2 or numerical weather prediction model over ocean and clear sky areas.
Brightness Temp.	L1H High-resolution Brightness Temp.	Depends on processing level	Global	20-30km	±1.5 K	2.7 – 340 K	6-89GHz only. Difference between ascending and descending orbits of global average after bias removal based on brightness temperature estimation of AMSR2 or numerical weather prediction model over ocean and clear sky areas.
Ocean	High-resolution Sea Surface Temp.	HST	Global over ocean	20 km*	0.8°C	-2 – 35 °C	RMSE compared to buoys *Inputs High-resolution Brightness Temp.
Cryosphere	Detection of Thin Sea Ice	TSI	Polar region over ocean	15 km	80 %	N/A	Detects thin ice of 30 cm or less. Accuracy is the correct answer rate.
Cryosphere	Sea Ice Motion Vector	SIM	Polar region over ocean	50 km	6 cm/s	0 – 40cm/s	North-south and east-west components
Land	Land Surface Temp.	LST	Global over land	15 km	Forest: 3 °C Sparse vegetation: 4 °C	0 – 50 °C	RMSE compared to ground observations
Land	Vegetation Water Content	VWC	Global over land	10 km	1.0 kg/m²	0 – 4 kg/m²	RMSE compared to optical sensors or in-situ observations

Accuracy level, including research items such as algorithm performance and calibration accuracy improvement. Unless otherwise indicated, represents the root mean square error (RMSE) of instantaneous values. However, for thin ice thickness (thermal ice thickness), soil moisture content, and soil moisture and vegetation water content based on land data assimilation, mean absolute error (MAE) is expressed.

AMSR3 Mission Requirement Revision History (Research Product)