Speakers
Description
Earth observation systems face a critical scale gap: satellites provide broad coverage at coarse resolution, while meteorological stations deliver continuous measurements only at sparse locations. This lack of intermediate-scale observations (10–100 km²) limits satellite validation, weather model calibration, and detection of mesoscale atmospheric phenomena that drive extreme events. Cosmic-ray muon flux provides a unique atmospheric observable through the positive temperature effect, where warmer stratospheric conditions increase meson decay probability, enhancing surface muon rates. The underground Main Injector Neutrino Oscillation Search (MINOS) experiment established correlation with stratospheric temperature and first detected sudden stratospheric warmings as muon rate excursions. The deep underground Large Volume Detector (LVD) at Gran Sasso revealed multi-year atmospheric cycles invisible to conventional proxies. The shallow-depth DANSS reactor neutrino detector and the underwater KM3NeT neutrino telescope confirmed similar modulations across detector configurations. However, these results remain confined to astroparticle physics, muon atmospheric observables have never been systematically integrated with satellite data or operational Earth observation workflows.
We present a proposal of a data integration framework transforming LHC experiments into dual-use atmospheric observatories. LHC detectors (CMS, ATLAS, ALICE,LHCb) opportunistically record cosmic muon tracks during routine maintenance and data taking periods for alignment, which can cover large areas at zero additional cost. As first implementation using CMS, we will start with comparing cosmic muon data during extreme atmospheric events (sudden stratospheric warmings, severe storms) against normal conditions, then cross-validate against satellite temperature sensors, atmospheric reanalysis models, and weather stations. Using Geographic Information Systems and standardized pipelines, we shall then align these datasets spatially and temporally to identify consistent atmospheric signals.
So, if the findings show enough sensitivity, we'll also try testing the idea of using the framework to check the historical accuracy of low-resolution satellite products from before 2012 using historical LHC data. Future work will extend this to other LHC experiments and connect to international Earth observation networks. It will also involve deploying portable surface muon detectors at strategic locations based on sensitivity requirements established from LHC analysis.
Keywords: Earth observation scale gap; cosmic-ray muons; LHC experiments; data integration framework; atmospheric monitoring; portable detectors