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Classical error analysis in remote sounding distinguishes between fourclasses: "smoothing errors," "model parameter errors," "forward modelerrors," and "retrieval noise errors". For infrared sounding"interference errors", which, in general, cannot be described by thesefour terms, can be significant. Interference errors originate from spectralresiduals due to "interfering species" whose spectral features overlapwith the signatures of the target species. A general method forquantification of interference errors is presented, which covers allpossible algorithmic implementations, i.e., fine-grid retrievals of theinterfering species or coarse-grid retrievals, and cases where theinterfering species are not retrieved. In classical retrieval setupsinterference errors can exceed smoothing errors and can vary by orders ofmagnitude due to state dependency. An optimum strategy is suggested whichpractically eliminates interference errors by systematically minimizing theregularization strength applied to joint profile retrieval of theinterfering species. This leads to an interfering-species selectivedeweighting of the retrieval. Details of microwindow selection are no longercritical for this optimum retrieval and widened microwindows even lead toreduced overall (smoothing and interference) errors. Since computationalpower will increase, more and more operational algorithms will be able toutilize this optimum strategy in the future. The findings of this paper canbe applied to soundings of all infrared-active atmospheric species, whichinclude more than two dozen different gases relevant to climate and ozone.This holds for all kinds of infrared remote sounding systems, i.e.,retrievals from ground-based, balloon-borne, airborne, or satellitespectroradiometers

Technical Note: Interference errors in infrared remote sounding of the atmosphere