# Global OMI HCHO Level-3 oversampling dataset: high spatial resolution and lightweight uncertainty

## TL;DR

This paper introduces a high-resolution dataset of formaldehyde levels derived from satellite data, offering improved accuracy and flexibility for environmental studies.

## Contribution

A new global HCHO dataset with high spatial resolution and optimized uncertainty metrics is introduced.

## Key findings

- The OMHCHOS V1.0 dataset provides seven spatial resolutions up to 0.05° and twelve temporal resolutions.
- A spatio-temporal scale optimization model enables precise uncertainty quantification for HCHO data.

## Abstract

Satellite observations of tropospheric formaldehyde (HCHO) have been widely used to support diagnosing atmospheric environmental quality. As one of the most classic trace gas payloads, the Ozone Monitoring Instrument (OMI) releases HCHO Level-2 data, while coarse resolution and relatively high uncertainty reduce the potential value of the data. We report a global multi-scale HCHO oversampling dataset version 1.0 (referred to as OMHCHOS V1.0) produced by NASA Level-2 OMI HCHO product using self-developed oversampling algorithm, with data from 2005 to 2023 as of the date of submission. This comprehensive dataset encompasses seven distinct spatial resolutions (up to 0.05°) and twelve temporal resolutions (monthly and months), enabling precise quantification of uncertainty propagation and relative uncertainties. To facilitate on-demand retrieval by users, we have developed a matching spatio-temporal scale optimisation model that integrates three critical parameters of HCHO column: temporal resolution (TR), spatial resolution (SR), and relative uncertainty (UR). This dataset will provide researchers with more reliable sources for conducting high-resolution, high-accuracy studies on HCHO-related atmospheric environmental implications.