Cloud-Climate Analytics for Wildfire Intelligence
Overview
SciSynth supported a wildfire intelligence platform by developing a tailored diagnostic framework that links wildfire occurrence with lightning climatology and atmospheric conditions. The project focused on improving the understanding of convective events that elevate fire ignition risks.
Our Role
Data Integration
We brought together wildfire archives, lightning strike datasets, and radiosonde-based atmospheric profiles to assess spatiotemporal fire patterns and their meteorological drivers.
Convective Diagnostics
By analyzing upper-air soundings, we characterized cloud base and storm initiation parameters, including indicators of dry lightning potential and storm downdraft intensity.
Risk Seasonality & Diurnal Patterns
We examined seasonal and daily patterns of lightning and convective instability to inform risk-aware decision-making for fire mitigation.
Cloud Microphysics & Boundary Layer Interactions
A detailed investigation of cloud lifecycle dynamics, mixing layers, and wind shear patterns provided insights into how certain atmospheric setups contribute to fire ignition and spread.
Deliverables
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A modular framework for identifying high-risk convective environments using atmospheric soundings
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Insights into the timing and structure of lightning events relevant for wildfire early warning
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A refined understanding of storm-wildfire coupling mechanisms tailored to local terrain and climatology
Why It Matters
This work potentially helps in more precise identification of wildfire-conducive weather patterns, supporting proactive risk management and operational planning.
It demonstrated the value of integrating meteorological diagnostics with fire intelligence systems, especially in data-scarce but lightning-prone regions.
