MERRA2_CNN_HAQAST_PM25: Hourly Bias‐Corrected <scp>PM2</scp> .5 Datasets for Global Air Quality Assessment
ABSTRACT This product provides MERRA‐2 bias‐corrected global hourly surface total PM2.5 mass concentration with the exact horizontal spatial resolution as MERRA‐2, covering a temporal range from 2000 to 2024. It is derived using a machine learning (ML) approach with a convolutional neural network (CNN) method. It is specifically developed for the NASA Health and Air Quality Applied Sciences Team (HAQAST). The dataset consists of two parameters: MERRA2_CNN_Surface_PM25 and QFLAG. MERRA2_CNN_Surface_PM25, a 3‐dimensional variable (time, latitude, longitude), represents the surface PM2.5 concentrations in μg/m 3 . QFLAG denotes the quality of data at each grid point, where four indicates the highest quality and 1 indicates the lowest quality. It is recommended to use QFLAG values of 3 and 4 for quantitative analysis.
Authors
- Alqamah Sayeed (ORCID: https://orcid.org/0000-0001-6898-8148)
- Pawan Gupta
Institutions
- Marshall Space Flight Center (US)
- Goddard Space Flight Center (US)
- University of Alabama in Huntsville (US)
Publication Details
- Journal
- Geoscience Data Journal
- Published
- 2026-03-27
- DOI
- https://doi.org/10.1002/gdj3.70070
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00