We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Ground-based validation of the MetopA and B GOME-2 OClO measurements.
- Authors
Pinardi, Gaia; Van Roozendael, Michel; Hendrick, François; Richter, Andreas; Valks, Pieter; Alwarda, Ramina; Bognar, Kristof; Frieß, Udo; Granville, José; Myojeong Gu; Johnston, Paul; Prados-Roman, Cristina; Querel, Richard; Strong, Kimberly; Wagner, Thomas; Wittrock, Folkard; Gonzalez, Margarita Yela
- Abstract
This paper reports on ground-based validation of the atmospheric OClO data record produced in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the GOME2-A and -B instruments over the 2007-2016 and 2013-2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from 9 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % between the different ground-based data analysis, reaching total uncertainties ranging from about 26 % to 33 % for the different stations. Time-series at the different sites show good agreement between satellite and ground-based data, both for the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be nosier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes of 0.64 and 0.72, respectively. Biases are within 8 x 1013 molec/cm2 with some differences between GOME-2A and GOME- 2B, depending on the station. Overall, considering all the stations, a median bias of about -2.2 x 1013 molec/cm2 is found for both GOME-2 instruments.
- Subjects
ATMOSPHERIC chemistry; REGRESSION analysis; LINEAR statistical models; SEASONS; STATISTICAL correlation
- Publication
Atmospheric Measurement Techniques Discussions, 2021, p1
- ISSN
1867-8610
- Publication type
Article
- DOI
10.5194/amt-2021-356