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First 1368 results for ” R Betts”

1. Comparison of dust-layer heights from active and passive satellite sensors

   Aerosol-layer height is essential for understanding the impact of aerosols on the climate system....

   Kylling, A.; Vandenbussche, S.; Capelle, V.; Cuesta, J.; Klüser, L.; Lelli, L.; Popp, T.; Stebel, K.; Veefkind, P. | Journal: Atmospheric Measurement Techniques | Year: 2018 | doi: https://doi.org/10.5194/amt-11-2911-2018

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2. Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals

   Air mass factor (AMF) calculation is the largest source of uncertainty in NO2 and HCHO satellite ...

   Lorente, A., Folkert Boersma, K., Yu, H., Dörner, S., Hilboll, A., Richter, A., Liu, M., Lamsal, L. N., Barkley, M., De Smedt, I., Van Roozendael, M., Wang, Y., Wagner, T., Beirle, S., Lin, J.-T., Krotkov, N., Stammes, P., Wang, P., Eskes, H. J., and Krol, M | Journal: Atmospheric Measurement Techniques | Year: 2017 | doi: https://doi.org/10.5194/amt-10-759-2017

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3. Tropospheric emissions: Monitoring of pollution (TEMPO)

   TEMPO was selected in 2012 by NASA as the first Earth Venture Instrument, for launch between 2018...

   Zoogman, P.; Liu, X.; Suleiman, R.M.; Pennington, W.F.; Flittner, D.E.; Al-Saadi, J.A.; Hilton, B.B.; Nicks, D.K.; Newchurch, M.J.; Carr, J.L.; Janz, S.J.; Andraschko, M.R.; Arola, A.; Baker, B.D.; Canova, B.P.; Chan Miller, C.; Cohen, R.C.; Davis, J.E.; Dussault, M.E.; Edwards, D.P.; Fishman, J.; Ghulam, A.; González Abad, G.; Grutter, M.; Herman, J.R.; Houck, J.; Jacob, D.J.; Joiner, J.; Kerridge, B.J.; Kim, J.; Krotkov, N.A.; Lamsal, L.; Li, C.; Lindfors, A.; Martin, R.V.; McElroy, C.T.; McLinden, C.; Natraj, V.; Neil, D.O.; Nowlan, C.R.; O׳Sullivan, E.J.; Palmer, P.I.; Pierce, R.B.; Pippin, M.R.; Saiz-Lopez, A.; Spurr, R.J.D.; Szykman, J.J.; Torres, O.; Veefkind, J.P.; Veihelmann, B.; Wang, H.; Wang, J.; Chance, K. | Journal: Satellite Remote Sensing and Spectroscopy: Joint ACE-Odin Meeting, October 2015 | Year: 2017 | doi: https://doi.org/10.1016/j.jqsrt.2016.05.008

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4. Simulating hydrological extremes for different warming levels–combining large scale climate ensembles with local observation based machine learning models

   Climate change has a large influence on the occurrence of extreme hydrological events. However, r...

   SM Hauswirth, K van der Wiel, MFP Bierkens, V Beijk, N Wanders | Journal: Frontiers in Water | Volume: 5 | Year: 2023 | First page: 11008108 | doi: 10.3389/frwa.2023.1108108

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5. Evaluation of CMIP6 model simulations of PM2.5 and its components over China

   Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phas...

   F Ren, J Lin, C Xu, JA Adeniran, J Wang, RV Martin, A van Donkelaar, MS Hammer, LW Horowitz, ST Turnock, N Oshima, J Zhang, S Bauer, K Tsigaridis, Ø Seland, P Nabat, D Neubauer, G Strand, T van Noije, P Le Sager, T Takemura | Journal: Geosci. Model Dev. | Volume: 17 | Year: 2024 | First page: 4821 | Last page: 4836 | doi: 10.5194/gmd-17-4821-2024

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