23 citations as recorded by crossref.

1. Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium E. Beele et al. 10.5194/essd-14-4681-2022
2. Machine learning-based tsunami inundation prediction derived from offshore observations I. Mulia et al. 10.1038/s41467-022-33253-5
3. CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications D. Fenner et al. 10.3389/fenvs.2021.720747
4. Ensemble-based statistical interpolation with Gaussian anamorphosis for the spatial analysis of precipitation C. Lussana et al. 10.5194/npg-28-61-2021
5. Evaluation of city-scale PALM model simulations and intra-urban thermal variability in Vienna, Austria using operational and crowdsourced data M. Žuvela-Aloise et al. 10.1016/j.uclim.2024.102245
6. Quantifying Local and Mesoscale Drivers of the Urban Heat Island of Moscow with Reference and Crowdsourced Observations M. Varentsov et al. 10.3389/fenvs.2021.716968
7. Towards high-resolution gridded climatology stemming from the combination of official and crowdsourced weather observations using multi-fidelity methods D. van Beekvelt et al. 10.1371/journal.pclm.0000216
8. High-Resolution Air Temperature Forecasts in Urban Areas: A Meteorological Perspective on Their Added Value S. Oswald et al. 10.3390/atmos15121544
9. “Come as you are”: Reconsidering the need for complex quality control when gridding crowd‐sourced weather data J. de Baar & G. van der Schrier 10.1002/qj.4890
10. Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC) K. Ośródka et al. 10.5194/amt-15-5581-2022
11. Observations from Personal Weather Stations—EUMETNET Interests and Experience C. Hahn et al. 10.3390/cli10120192
12. From proof‐of‐concept to proof‐of‐value: Approaching third‐party data to operational workflows of national meteorological services I. Garcia‐Marti et al. 10.1002/joc.7757
13. Using machine learning to produce a very high resolution land-cover map for Ireland E. Walsh et al. 10.5194/asr-18-65-2021
14. Quality management system and design of an integrated mesoscale meteorological network in Central Italy L. Silvestri et al. 10.1002/met.2060
15. The importance of crowdsourced observations for urban climate services T. Mitchell & M. Fry 10.1002/joc.8390
16. A Quality Control Method Applicable to Precipitation at Hydrological Rainfall Stations 莉. 赵 10.12677/ccrl.2024.135124
17. Assessing the Trustworthiness of Crowdsourced Rainfall Networks: A Reputation System Approach A. Chen et al. 10.1029/2021WR029721
18. Exploratory analysis of citizen observations of hourly precipitation over Scandinavia C. Lussana et al. 10.5194/asr-20-35-2023
19. MetObs - a Python toolkit for using non-traditional meteorological observations T. Vergauwen et al. 10.21105/joss.05916
20. The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models H. Lean et al. 10.1002/qj.4858
21. Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates J. Nielsen et al. 10.1016/j.atmosres.2024.107228
22. Merging with crowdsourced rain gauge data improves pan-European radar precipitation estimates A. Overeem et al. 10.5194/hess-28-649-2024
23. Areal reduction factors from gridded data products J. Lutz et al. 10.1016/j.jhydrol.2024.131177