Data assimilation: making sense of Earth Observation

WA Lahoz, P Schneider - Frontiers in Environmental Science, 2014 - frontiersin.org
Climate change, air quality, and environmental degradation are important societal
challenges for the Twenty-first Century. These challenges require an intelligent response …

[HTML][HTML] A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

V Marécal, VH Peuch, C Andersson… - Geoscientific Model …, 2015 - gmd.copernicus.org
This paper describes the pre-operational analysis and forecasting system developed during
MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II …

Current state of the global operational aerosol multi‐model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)

P **an, JS Reid, EJ Hyer, CR Sampson… - Quarterly Journal of …, 2019 - Wiley Online Library
Since the first International Cooperative for Aerosol Prediction (ICAP) multi‐model ensemble
(MME) study, the number of ICAP global operational aerosol models has increased from five …

Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS

A Inness, AM Blechschmidt, I Bouarar… - Atmospheric …, 2015 - acp.copernicus.org
Daily global analyses and 5-day forecasts are generated in the context of the European
Monitoring Atmospheric Composition and Climate (MACC) project using an extended …

A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data

K Miyazaki, HJ Eskes, K Sudo - Atmospheric Chemistry and …, 2015 - acp.copernicus.org
We present the results from an 8-year tropospheric chemistry reanalysis for the period 2005–
2012 obtained by assimilating multiple data sets from the OMI, MLS, TES, and MOPITT …

A comparison of the impact of TROPOMI and OMI tropospheric NO2 on global chemical data assimilation

T Sekiya, K Miyazaki, H Eskes, K Sudo… - Atmospheric …, 2022 - amt.copernicus.org
This study gives a systematic comparison of the Tropospheric Monitoring Instrument
(TROPOMI) version 1.2 and Ozone Monitoring Instrument (OMI) QA4ECV tropospheric NO 2 …

Generalized background error covariance matrix model (GEN_BE v2. 0)

G Descombes, T Auligné… - Geoscientific Model …, 2015 - gmd.copernicus.org
The specification of state background error statistics is a key component of data assimilation
since it affects the impact observations will have on the analysis. In the variational data …

First implementation of secondary inorganic aerosols in the MOCAGE version R2. 15.0 chemistry transport model

J Guth, B Josse, V Marécal, M Joly… - Geoscientific Model …, 2016 - gmd.copernicus.org
In this study we develop a secondary inorganic aerosol (SIA) module for the MOCAGE
chemistry transport model developed at CNRM. The aim is to have a module suitable for …

Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM‐CAM‐chem and DART

J Barré, B Gaubert, AFJ Arellano… - Journal of …, 2015 - Wiley Online Library
We show the results and evaluation with independent measurements from assimilating both
MOPITT (Measurements Of Pollution In The Troposphere) and IASI (Infrared Atmospheric …

Assimilation des luminances IASI dans un modèle de chimie transport pour la surveillance de l'ozone et des poussières désertiques

M El Aabaribaoune - 2022 - theses.hal.science
L'ozone et les poussières désertiques jouent un rôle crucial dans notre atmosphère
nécessitant une surveillance continue. Cette surveillance est effectuée par le biais des …