Research Group Climate and Environmental Remote SensingDepartment of Geodesy and Geoinformation, TU Wien

wolfgang.preimesberger@geo.tuwien.ac.at

Homogeneity Testing of the Global CCI Soil Moisture Data Record [1]

Wolfgang Preimesberger, Chun-Hsu Su, Wouter Dorigo and Alexander Gruber

[1] Homogeneity of a global multi-satellite soil moisture climate data record, Su, C.-H., D. Ryu, W. Dorigo, S. Zwieback, A. Gruber, C. Albergel, R. H. Reichle, and W. Wagner (2016)

Wolfgang Preimesberger Homogeneity testing of the global CCI SM data set / 121

Long term data record from multiple earth observation products [1]

− …by blending different microwave remote sensing instruments with varying sensor characteristics (ACT, PASS)

− Breaks in the merged data set

Used version: ESA CCI SM v. 4.1 combined product• Hypothesis tests by comparison to reference data

− Use test results for TS adjustment

ESA CCI Soil Moisture – Background

[1] http://www.esa-soilmoisture-cci.org/

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Relative testing for breaks needs reference data for comparison• MERRA2 [1]

− Globally modeled geophysical parameters by NASA− Long term dataset, high temporal resolution− Rescaled to monthly resolution

• In-situ data from ISMN [2]

− Only data from stations in USA used− Soil moisture from merging…

...sensors in multiple depths (<0.1m)…from multiple stations

− Merged stations correspond to 643ground points

Reference Datasets

http://www.geo.tuwien.ac.at/insitu/data_viewer/ISMN.php[1] https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/[2] http://ismn.geo.tuwien.ac.at/

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Input data : Difference series for time frame• Between CCI SM and Reference SM• Monthly values

(1) Wilkoxon (WK) Rank Sum Test• Compares the statistical significance of correspondence in distributions of 2 ordered and

ranked datasets− Two sided test for differences in rank mean values (before vs. after break time)− Significance level: 1%

(2) Fligner-Killeen (FK) Variance Test• Test for significant differences in variance before / after break time

− Normalized rankings− FK statistics − χ2 distribution for probability estimation− Significance level: 1%

Break detection tests

n…Set size M…overall meanm…Set mean s2…overall variance

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Test Results and Coverage CCI SM 4.1 (RTM)Test results for break time 1991-07-01 not shown

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Test Results CCI SM 4.1(RTM)Test results for break time 2007-07 and 2011-10 not shown

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Version Comparison: test results and coverage

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CCI version comparison - Test coverage (comb. Datasets)

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Test coverage increases for newer CCI SMversions• Additional testing time frame could be added

Number of detected breaks decreases• Mainly for early break times

Mean-breaks more prominent than variance-breaks for all versions

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RTG follows same principles as RTM RTG mostly confirms RTM

• Number of tests depends on− Station measurement timeframe− RTM coverage

No in-situ measurementsfor 08-1991 and 07-1987 at stations around GPIs tested in RTM

Test confirmation with ISMN in-situ data (RTG)

Break time 07-1987 08-1991 01-1998 06-2002 01-2007 10-2007 01-2010 10-2011 07-2012#RTM ∩ #RTG 0 0 16 35 109 98 146 177 312

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Testing for break in time frame for pixel Correction of additive / multiplicative biases in SM values if break found

• No adjustment performed if correlation low

• Gauss-Markov model between reference data and CCI data (monthly values)− For before and after break time separately

• Fitting model parameters before break time− … to match model parameters after break time

• Adjustment of daily values before break time with modified model parameters

Time Series Adjustment

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Test Results CCI SM 4.1 (adjusted)

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Test Results CCI SM 4.1 (adjusted)Test results for break time 2007-01-01 not shown

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Comparison unadjusted / adjusted data

[years]

unadjusted adjusted (WK)

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RTM detects breaks for all break times • 2 break detection tests were implemented

− WK test, FK test

• Early break times show more breaks than latter

• Test coverage increases over time

RTG for stations in the USA Correction of CCI SM time series ongoing

• Mean breaks well removed (~90%)

• Variance breaks still appear− mostly for early break times

Impact of breaks on trends is being investigated• Impact of adjustment on trends

Conclusion and outlook

Su et al. (2016)

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