Averaging bias correction for the future space-borne methane IPDA lidar mission MERLIN
-
Published:2018-10-24
Issue:10
Volume:11
Page:5865-5884
-
ISSN:1867-8548
-
Container-title:Atmospheric Measurement Techniques
-
language:en
-
Short-container-title:Atmos. Meas. Tech.
Author:
Tellier Yoann, Pierangelo Clémence, Wirth MartinORCID, Gibert Fabien, Marnas Fabien
Abstract
Abstract. The CNES (French Space
Agency) and DLR (German Space Agency) project MERLIN is a future integrated
path differential absorption (IPDA) lidar satellite mission that aims at
measuring methane dry-air mixing ratio columns (XCH4) in order
to improve surface flux estimates of this key greenhouse gas. To reach a
1 % relative random error on XCH4 measurements, MERLIN
signal processing performs an averaging of data over 50 km along the
satellite trajectory. This article discusses how to process this horizontal
averaging in order to avoid the bias caused by the non-linearity of the
measurement equation and measurements affected by random noise and horizontal
geophysical variability. Three averaging schemes are presented: averaging of
columns of XCH4, averaging of columns of differential absorption
optical depth (DAOD) and averaging of signals. The three schemes are affected
both by statistical and geophysical biases that are discussed and compared,
and correction algorithms are developed for the three schemes. These
algorithms are tested and their biases are compared on modelled scenes from
real satellite data. To achieve the accuracy requirements that are limited to
0.2 % relative systematic error (for a reference value of 1780 ppb), we
recommend performing the averaging of signals corrected from the statistical
bias due to the measurement noise and from the geophysical bias mainly due to
variations of methane optical depth and surface reflectivity along the
averaging track. The proposed method is compliant with the mission relative
systematic error requirements dedicated to averaging algorithms of 0.06 %
(±1 ppb for XCH4=1780ppb) for all tested scenes
and all tested ground reflectivity values.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference17 articles.
1. Bösenberg, J.: Ground-based differential absorption lidar for water-vapor
and temperature profiling: methodology, Appl. Optics, 37,
3845–3860, https://doi.org/10.1364/AO.37.003845, 1998. 2. Chéruy, F., Scott, N. A., Armante, R., Tournier, B., and Chedin, A.:
Contribution to the development of radiative transfer models for high
spectral resolution observations in the infrared, J. Quant. Spectrosc. Ra.,
53, 597–611, https://doi.org/10.1016/0022-4073(95)00026-H, 1995. 3. Chevallier, F., Chédin, A., Chéruy, F., and Morcrette, J.-J.:
TIGR-like atmospheric-profile databases for accurate radiative-flux
computation, Q. J. Roy. Meteor. Soc., 126, 777–785, https://doi.org/10.1002/qj.49712656319, 2000. 4. Chevallier, F., Broquet, G., Pierangelo, C., and Crisp, D.: Probabilistic
global maps of the CO2 column at daily and monthly scales from sparse
satellite measurements, J. Geophys. Res., 122, 7614–7629, https://doi.org/10.1002/2017JD026453, 2017. 5. Ehret, G., Kiemle, C., Wirth, M., Amediek, A., Fix, A., and Houweling, S.:
Space-borne remote sensing of CO2,CH4,and N2O by integrated
path differential absorption lidar: a sensitivity analysis, Appl. Phys.
B.-Lasers O., 90, 593–608, https://doi.org/10.1007/s00340-007-2892-3, 2008.
Cited by
12 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|