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Inverse Methods for Atmospheric Sounding: Theory and Practice

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TLDR
This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely.
Abstract
Remote sounding of the atmosphere has proved to be a fruitful method of obtaining global information about the atmospheres of the earth and planets. This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely. Inverse theory is treated in depth from an estimation-theory point of view, but practical questions are also emphasized, for example designing observing systems to obtain the maximum quantity of information, efficient numerical implementation of algorithms for processing of large quantities of data, error analysis and approaches to the validation of the resulting retrievals, The book is targeted at both graduate students and working scientists.

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Journal ArticleDOI

A Neural Network for Real-Time Retrievals of PWV and LWP From Arctic Millimeter-Wave Ground-Based Observations

TL;DR: It is shown that the GVR alone can provide overall improved PWV and LWP retrievals when the PWV amount is less than 10 mm, and, when combined with the MWR, can provide improved retrieevals over the whole water-vapor range.
Journal ArticleDOI

Tracking city CO 2 emissions from space using a high-resolution inversemodelling approach: a case study for Berlin, Germany

TL;DR: In this paper, the authors investigated the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat) which was proposed to the European Space Agency (ESA) to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport.

A variational scheme for retrieving rainfall rate and hail reflectivity fraction from polarization radar

TL;DR: In this article, a variational retrieval scheme is described that overcomes these problems by employing a forward model for differential reflectivity Zdr and differential phase shift dp and iteratively refining the coefficient a in the relationship Z aR b such that the difference between the forward model and the measurements is minimized in a least squares sense.
Journal ArticleDOI

Retrieval of snowflake microphysical properties from multifrequency radar observations

TL;DR: An algorithm that retrieves the size, number concentration and density of falling snow from multifrequency radar observations is developed, based on a Bayesian framework, using lookup tables mapping the measurement space to the state space, which allows fast and robust retrieval.
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