Providing modifiability and robustness in the science and software for atmospheric retrievals

This paper introduces Strategy software that is developed for performing atmospheric retrievals fo r the Tropospheric Emission Spectrometer (TES) data processing system. This software automates selection of initial parameters needed to perform an atmospheric retrieval for the Tropospheric Emission Spectrometer (TES) data processing system. Atmospheric retrievals consist of scientific algorithms used to ascertain the actual state of the atmosphere in terms of its temperature and chemical constituents. Atmospheric retrieval algorithms are computationally expensive and convergence of the retrieval is sens itive to input, therefore it is important to provide the best input that will result in the best atmospheric profile. TES has complex requirements in terms of the variety of input data and observations. So it requires a sophisticated system such as Strateg y Builder to automate the selection of the optimum strategy for performing the retrieval algorithm on its various types of observation. Strategy Software also increases the lifetime of the retrieval software by improving its flexibility in implementing var ious research approaches. Strategy software uses strategy selection logic based on specific strategy selection rules for retrieval of various target scenes. This paper also addresses our approach in providing design solutions for specific challenges that existed in designing software for atmospheric retrieval software that retrieves the atmosphere of one target scene in a sequence of retrievals and performs error analysis for each retrieval. In Strategy software, we have achieved our goals for providing ro bustness to TES atmospheric retrieval software. Due to this robustness and modifiability, retrieval software can be used for a longer time and more research can be conducted without the need of large additional costs of software changes.