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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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GMD | Articles | Volume 11, issue 6
Geosci. Model Dev., 11, 2419–2427, 2018
https://doi.org/10.5194/gmd-11-2419-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 11, 2419–2427, 2018
https://doi.org/10.5194/gmd-11-2419-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 20 Jun 2018

Model description paper | 20 Jun 2018

High-performance software framework for the calculation of satellite-to-satellite data matchups (MMS version 1.2)

Thomas Block et al.

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Cited articles

Ault, M. R., Ault, M., Tumma, M., and Ranko, M.: Oracle 10g Grid & Real Application Clusters, Rampant TechPress., p. 24, 2004. 
Bali, M., Mittaz, J. P., Maturi, E., and Goldberg, M. D.: Comparisons of IASI-A and AATSR measurements of top-of-atmosphere radiance over an extended period, Atmos. Meas. Tech., 9, 3325–3336, https://doi.org/10.5194/amt-9-3325-2016, 2016. 
Beck, K.: Test Driven Development by Example, Addison-Wesley, ISBN-13: 978-0321146533, 2003. 
Böttcher, M., Quast, R., Storm, T., Corlett, G., Merchant, C., and Donlon, C.: Multi-sensor match-up database for SST CCI, ESA Sentinel-3 OLCI/SLSTR and MERIS/AATSR Workshop 2012 in Frascati, Italy, https://doi.org/10.6084/m9.figshare.1063282, 2012. 
Buehler, S. A., Kuvatov, M., Sreerekha, T. R., John, V. O., Rydberg, B., Eriksson, P., and Notholt, J.: A cloud filtering method for microwave upper tropospheric humidity measurements, Atmos. Chem. Phys., 7, 5531–5542, https://doi.org/10.5194/acp-7-5531-2007, 2007. 
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Short summary
For calibration and validation purposes it is necessary to detect simultaneous data acquisitions from different spaceborne platforms. We present an algorithm and a software system which implements a general approach to resolve this problem. The multisensor matchup system (MMS) can detect simultaneous acquisitions in a large dataset (> 100 TB) and extract data for matching locations for further analysis. The MMS implements a flexible software infrastructure and allows for high parallelization.
For calibration and validation purposes it is necessary to detect simultaneous data acquisitions...
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