SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

Uni Bonn contributions to SMOS Validation

Ralf LindauBonn University

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

Bonn contributions Detection of Radio Frequency Interference

- Found in SMMR, AMSR etc.- Expected also in SMOS

Comparison of SMOS soil moisture with existing data- Direct measurements from GSMDB - AMSR-derived SM

Pixel-intern variance- Necessary to interprete the intended validations with point

measurements properly.- build and operate a transportable polarized L-Band radiometer

Investigate signal noise due to rain and vegetation

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOSRadio Frequency

Interference

Time series of 6 GHz brightness temperature from SMMR in France

Until 1981 the normal annual cycle is found.

After 1981 the 6 Ghz signal is completely unusable due to noise.

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

SMMR RFI in 6 GHz

The scatter is low in Sibiria, increases westward and reaches maximum values near St. Petersburg

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

ASMR RFI

In Europe the 10 GHz channel is completely noisy in England and Italy.

In the USA the 6 GHz measurements are corrupted over New York, Boulder etc.

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

AMSR 10 GHz RFI

• RFI is detectable by

• high monthly averages

• high monthly stddev.

250 K

300 K

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

Simple RFI Scheme

• TB > 260 K

• Stddev > 5 K

• TB > 20 K

compared to a 10° x 30°

surrounding

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

Soil Moisture from AMSR

Longtime mean + 10-day anomalies

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

2-Step Retrieval

SMOS Workshop – Hamburg, 9.-10. November 2006

SMOS

Pixel-intern VarianceBelarussian soil moisture data

21 stations, 10 daily during about 10 years

Average spatially and compare the reduced variance to the total variance

40% are left for 400-km-Pixels59% are left for SMMR-Pixels

The left external variance is equal to the maximum correlation between point measurements and area averages