作者: T Borsdorff , P Tol , JE Williams , J de Laat , J Aan de Brugh
关键词: Environmental science 、 Atmospheric sciences 、 Water vapor 、 Smoothing 、 Albedo 、 Spectrometer 、 Calibration 、 Atmospheric radiative transfer codes 、 Remote sensing 、 SCIAMACHY 、 Chemical transport model
摘要: Abstract. We present a full-mission data product of carbon monoxide (CO) vertical column densities using the 2310–2338 nm SCIAMACHY reflectance measurements over clear-sky land scenes for period January 2003–April 2012. The retrieval employs SICOR algorithm, which will be used operational processing Sentinel-5 Precursor mission. approach infers simultaneously monoxide, methane and water vapour together with a Lambertian surface albedo from individual employing a non-scattering radiative transfer model. To account radiometric instrument degradation including formation an ice-layer on 2.3 µm detector array, we consider Sahara as a natural calibration target. For these specific measurements, spectrally calibrate determine a spectral offset width spectral response function a function time entire phase show that smoothing error CO retrievals is less than ±1 ppb thus this contribution does not need to accounted in validation considering much higher noise. validated against ground-based Fourier transform infrared spectrometers at 27 stations NDACC-IRWG TCCON network MOZAIC/IAGOS aircraft 26 airports worldwide. Overall, find a good agreement a mean bias b = −1.2 ppb a station-to-station σ = 7.2 ppb. negative sign means a low respect TCCON. network, obtain a larger mean station = −9.2 ppb σ = 8.1 ppb = −6.4 ppb = 5.6 ppb. set subject a small but significant trend 1.47 ± 0.25 ppb yr−1. After correction, observation 2.5 ppb, it −4.6 ppb −8.4 ppb. Hence, a discrepancy 3.8 ppb remains between global biases TCCON, confirmed by directly comparing measurements. Generally, scatter high dominated large measurement practical usage set, averaging required. As example, monthly retrievals, averaged separately Northern Southern Africa, reflect spatial temporal variability biomass burning events chemical transport model TM5.