The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.

An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.

Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.

The GSnow-CHINA data set is a snow depth data set developed using the two Global Navigation Satellite System station networks in China. It includes snow depth of 24, 12, and 2/3/6 h records, if possible, for 80 sites from 2013–2022 over northern China (25–55° N, 70–140° E). The footprint of the data set is ~ 1000 m², and it can be used as an independent data source for validation purposes. It is also useful for regional climate research and other meteorological and hydrological applications.

The longest observational record available to study the mass balance of the Earth’s ice sheets comes from satellite altimeters. This record consists of multiple satellite missions with different measurements and quality, and it must be cross-calibrated and integrated into a consistent record for scientific use. Here, we present a novel approach for generating such a record providing a seamless record of elevation change for the Antarctic Ice Sheet that spans the period 1985 to 2020.

Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic data. High-quality information can help to transform evidence into decision-making. Taking advantage of big-data and remote sensing technics we developed a flexible workflow to reconstruct burned area and fire severity data for more than 8000 individual fires in Chile. The framework developed for the database can be applied anywhere in the world with minimal adaptation.