Print Email Facebook Twitter Evaluation criteria on the design for assimilating remote sensing data using variational approaches Title Evaluation criteria on the design for assimilating remote sensing data using variational approaches Author Lu, S. (TU Delft Mathematical Physics) Heemink, A.W. (TU Delft Mathematical Physics) Lin, H.X. (TU Delft Mathematical Physics) Segers, Arjo (TNO) Fu, Guangliang (TU Delft Mathematical Physics) Date 2017-03-01 Abstract Remote sensing, as a powerful tool for monitoring atmospheric phenomena, has been playing an increasingly important role in inverse modeling. Remote sensing instruments measure quantities that often combine several state variables as one. This creates very strong correlations between the state variables that share the same observation variable. This may cause numerical problems resulting in a low convergence rate or inaccurate estimates in gradient-based variational assimilation if improper error statistics are used. In this paper, two criteria or scoring rules are proposed to quantify the numerical robustness of assimilating a specific set of remote sensing observations and to quantify the reliability of the estimates of the parameters. The criteria are derived by analyzing how the correlations are created via shared observation data and how they may influence the process of variational data assimilation. Experimental tests are conducted and show a good level of agreement with theory. The results illustrate the capability of the criteria to indicate the reliability of the assimilation process. Both criteria can be used with observing system simulation experiments (OSSEs) and in combination with other verification scores. Subject Remote sensingInverse methodsVariational data assimilationforecast evaluationOA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:945e3eee-a6fe-4063-ac86-d0814eeb4301 DOI https://doi.org/10.1175/MWR-D-16-0289.1 ISSN 0027-0644 Source Monthly Weather Review, 145 (6), 2165-2175 Part of collection Institutional Repository Document type journal article Rights © 2017 S. Lu, A.W. Heemink, H.X. Lin, Arjo Segers, Guangliang Fu Files PDF mwr_d_16_0289.1.pdf 1.07 MB Close viewer /islandora/object/uuid:945e3eee-a6fe-4063-ac86-d0814eeb4301/datastream/OBJ/view