Abstract

Abstract. This paper presents a validation study of SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) carbon monoxide (CO) total column measurements from the Iterative Maximum Likelihood Method (IMLM) algorithm using ground-based spectrometer observations from twenty surface stations for the five year time period of 2003–2007. Overall we find a good agreement between SCIAMACHY and ground-based observations for both mean values as well as seasonal variations. For high-latitude Northern Hemisphere stations absolute differences between SCIAMACHY and ground-based measurements are close to or fall within the SCIAMACHY CO 2σ precision of 0.2 × 1018 molecules/cm2 (∼10%) indicating that SCIAMACHY can observe CO accurately at high Northern Hemisphere latitudes. For Northern Hemisphere mid-latitude stations the validation is complicated due to the vicinity of emission sources for almost all stations, leading to higher ground-based measurements compared to SCIAMACHY CO within its typical sampling area of 8° × 8°. Comparisons with Northern Hemisphere mountain stations are hampered by elevation effects. After accounting for these effects, the validation provides satisfactory results. At Southern Hemisphere mid- to high latitudes SCIAMACHY is systematically lower than the ground-based measurements for 2003 and 2004, but for 2005 and later years the differences between SCIAMACHY and ground-based measurements fall within the SCIAMACHY precision. The 2003–2004 bias is consistent with previously reported results although its origin remains under investigation. No other systematic spatial or temporal biases could be identified based on the validation presented in this paper. Validation results are robust with regard to the choices of the instrument-noise error filter, sampling area, and time averaging required for the validation of SCIAMACHY CO total column measurements. Finally, our results show that the spatial coverage of the ground-based measurements available for the validation of the 2003–2007 SCIAMACHY CO columns is sub-optimal for validation purposes, and that the recent and ongoing expansion of the ground-based network by carefully selecting new locations may be very beneficial for SCIAMACHY CO and other satellite trace gas measurements validation efforts.

Highlights

  • The SCIAMACHY instrument (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY; launched March 2002) onboard of the ENVISAT satellite (Bovensmann et al, 1999) has provided over five years of carbon monoxide (CO) data based on reflected sunlight measurements in the short-wave infrared around 2.3 μm.Validation of SCIAMACHY CO with Ground Based Spectrometer (GBS) observations is complicated by the need for spatio-temporal averaging to obtain an acceptable precision of the SCIAMACHY CO columns

  • The ocean observations greatly improve the spatial coverage of SCIAMACHY CO observations considerably and enhance the possibilities for validation of SCIAMACHY CO total column measurements with GBS measurements as a number of GBS stations are located on islands or close to sea

  • In this paper we present a validation of five years (2003–2007) of SCIAMACHY CO observations from the Iterative Maximum Likelihood Method (IMLM) algorithm using twenty GBS stations

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Summary

Introduction

The SCIAMACHY instrument (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY; launched March 2002) onboard of the ENVISAT satellite (Bovensmann et al, 1999) has provided over five years of carbon monoxide (CO) data based on reflected sunlight measurements in the short-wave infrared around 2.3 μm. Dils et al (2006) presented a first validation using 11 GBS stations for one year (2003) of SCIAMACHY CO columns Their results clearly showed that validation with GBS observations was difficult. They concluded that the data set used was too small to make an honest assessment of whether monthly mean values over their collocation grid of 2.5◦ × 10◦ or 5◦ × 10◦ latitude-longitude do reach the target precision of 10% for CO. Results from the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm – developed at the Netherlands Institute for Space Research (SRON) – were used in the Dils et al (2006) study This algorithm has been improved since and the length of the observational record covers five years (2003–2007) including observations over both land and oceans (Gloudemans et al, 2009).

SCIAMACHY CO
Ground-based data
Global chemistry-transport model TM4
GBS columns and seasonal cycles
The area for comparison
Southern Hemisphere locations
Northern Hemisphere mountain stations
Northern Hemisphere mid-latitude low altitude stations
Northern Hemisphere high latitude stations
Global validation results
Summary and conclusions
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