A Linear Method for the Retrieval of Sun-Induced Chlorophyll Fluorescence from GOME-2 Data

Abstract

Global retrievals of sun-induced chlorophyll fluorescence (SIF) have been achieved in the last years by means of space-borne atmospheric chemistry sensors. In particular, the Global Ozone Monitoring Experiment (GOME-2) in- strument on-board EUMETSAT‘s polar orbiting Meteoro- logical Operational Satellite (MetOp-A) provides a radio- metric performance which allows to disentangle the small amount of SIF (about 1 %) from the total incoming radi- ance at the sensor. Here, we present a statistical retrieval approach similar to that Joiner et al. proposed in 2013 [3], whereas the presented forward model to describe the measurement is linear. Furthermore, we use a backward elimination algorithm to reduce the number of coefficients to fit, which reduces also the noise in the retrieval. This new method shows comparable results to both results from Joiner et al. [3] and a fundamentally different SIF retrieval method using GOSAT (Greenhouse Gases Observing Satel- lite) data. In addition, we assess the impact of clouds on the retrieval through the analysis of the effect of different cloud fraction thresholds on SIF time series. Our results indicate only a low sensitivity of the SIF retrieval to cloud contam- ination, at which the SIF signal decreases slightly with an increasing cloud fraction, whereby the temporal pattern re- mains almost unaffected.