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Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project
Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible...
KF Boersma, HJ Eskes, A Richter, I De Smedt, A Lorente, JHGM van Geffen, M Zara, RJ van der A | Status: published | Journal: Atmospheric Measurement Techniques | Volume: 11 | Year: 2018 | First page: 6651 | Last page: 6678 | doi: https://doi.org/10.5194/amt-11-6651-2018
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Satellite Observations of PM2.5 Changes and Driving Factors based Forecasting over China 2000-2025
In China, atmospheric fine particulate matter (PM2.5) pollution is a challenging
environmental pr...
Y Zhang, Z Li, W Chang, Y Zhang, G de Leeuw, JJ Schauer | Status: published | Journal: Remote Sensing | Volume: 12 | Year: 2020 | First page: 1 | Last page: 20 | doi: doi:10.3390/rs12162518
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An Ensemble Version of the E‐OBS Temperature and Precipitation Datasets
We describe the construction of a new version of the Europe‐wide E‐OBS temperature (daily minimum...
RC Cornes, G van der Schrier, EJM van den Besselaar, PD Jones | Status: published | Journal: J. Geophys. Res. | Year: 2018 | doi: doi:10.1029/2017JD028200
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Evaluation of SCIAMACHY Level-1 data versions using nadir ozone profile retrievals in the period 2003–2011
Ozone profile retrieval from nadir-viewing satellite instruments operating in the ultraviolet–vis...
S Shah, ONE Tuinder, JCA van Peet, ATJ de Laat, P Stammes | Status: published | Journal: Atmospheric Measurement Techniques | Year: 2018 | First page: 2345 | Last page: 2360 | doi: https://doi.org/10.5194/amt-11-2345-2018
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Comparing Area Probability Forecasts of (Extreme) Local Precipitation Using Parametric and Machine Learning Statistical Postprocessing Methods
Probabilistic forecasts, which communicate forecast uncertainties, enable users to make better we...
KRP Whan, MJ Schmeits | Status: published | Journal: Mon. Wea. Rev. | Volume: 146 | Year: 2018 | First page: 3651 | Last page: 3673 | doi: 10.1175/MWR-D-17-0290.1
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