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First 539 results for ” M Demircan”

1. High-resolution mapping of urban NO2 concentrations using Retina v2: a case study on data assimilation of surface and satellite observations in Madrid

   Urban air pollution poses a significant health risk, with over half the global population living ...

   Bas Mijling, Henk Eskes, Sascha Hofmann, Pau Moreno, David García Falin, María Encarnación de Vega Pastor | Journal: Geoscientific Model Development | Volume: 18 | Year: 2025 | First page: 6439 | Last page: 6460 | doi: 10.5194/gmd-18-6439-2025

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2. Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite

   Methane is the second largest greenhouse gas. The detection of methane superemitters and the qua...

   Lu, T., Z. Li, C. Fan, Z. He, X. Jiang, Y. Zhang, Y. Gao, Y. Xuan, G. de Leeuw | Journal: Atmosphere | Volume: 16 | Year: 2025 | First page: 1 | Last page: 18 | doi: https://doi.org/10.3390/atmos16050510

   Publication

3. Evolution of aerosol optical depth over China in 2010–2024: increasing importance of meteorological influences

   Time series of Collection 6.1 of the MODerate resolution Imaging Spectroradiometer Multi-Angle Im...

   Fan, C., de Leeuw, G., Yan, X., Dong, J., Kang, H., Fang, C., Li, Z., and Zhang, Y | Journal: Atmos. Chem. Phys | Volume: 25 | Year: 2025 | First page: 11951 | Last page: 11973 | doi: https://doi.org/10.5194/acp-25-11951-2025, 2025.

   Publication

4. Retrieval of aerosol properties over the ocean using data from the second-generation Directional Polarization Camera (DPC-2) onboard the GF-5(02) satellite

   The second‐generation Directional Polarization Camera (DPC‐2) onboard the GF‐5(02) satellitefills...

   Ji, Z., Li, Z., Zhang, Z., Fu, G., Hasekamp, O., Fan, C., Liu, Q. and de Leeuw, G. | Journal: Journal of Geophysical Research: Atmospheres, 130 | Volume: 130 | Year: 2025 | First page: 1 | Last page: 18 | doi: https://doi.org/10.1029/2025JD043908.

   Publication

5. Probabilistic Forecasting of Cloud-Base Height and Visibility Using Quantile Regression Forests, Based on NWP and Observation Features

   We have applied quantile regression forests (QRFs) to generate probabilistic forecasts of weather...

   D. Wolters, M. Schmeits, and K. Whan | Journal: Wea. Forecasting | Volume: 40 | Year: 2025 | First page: 543 | Last page: 559 | doi: https://doi.org/10.1175/WAF-D-23-0231.1

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