Description
This product provides MERRA-2 bias-corrected global hourly surface total PM2.5 mass concentration with the same 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 and 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/m³. QFLAG denotes the quality of data at each grid point, where 4 indicates the highest quality and 1 indicates the lowest quality. It is recommended to use QFLAG values of 3 and 4 for quantitative analysis.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Download this dataset through a directory map | HTML | Access the data via HTTPS. | Open resource |
| View this dataset's read me document | README Document | Open resource | |
| Use OPeNDAP to access the dataset's data | HTML | Access the data via the OPeNDAP protocol. | Open resource |
| This dataset's landing page | HTML | Access the dataset landing page from the GES DISC website. | Open resource |
| View this dataset's how-to documentation | HTML | Documentation with step-by-step instructions on accessing and reading data at GES DISC | Open resource |
| Get a related visualization | PNG | The MERRA-2 bias corrected surface total PM2.5 mass concentration for 00:30Z Jan 1, 2023. | Open resource |
| The dataset's project home page | HTML | The science project page | Open resource |
| Google Scholar search results | HTML | Search results for publications that cite this dataset by its DOI. | Open resource |
| Download this dataset through Earthdata Search | HTML | Use the Earthdata Search to find and retrieve data sets across multiple data centers. | Open resource |