Remote Sensing | ALEX MATUS PORTFOLIO

Enhancing Surface PM2.5 Air Quality Estimates in GEOS Using CATS Lidar Data

Thu, 01 May 2025 00:00:00 +0000

This work introduces a pioneering data-fusion strategy that bridges the gap between columnar satellite observations and ground-level exposure by incorporating vertical profiles from spaceborne lidar.

Key Methodology Updates

1-D EnsVar Technique: An ensemble-based variational retrieval workflow that optimizes speciated mass data from the GEOS model utilizing real-time 1064-nm lidar backscatter.
Vertical Profiling: Overcomes traditional column-integrated limits by resolving complex aerosol layering systems that decouple standard satellite AOD signals from surface levels.
Forecast Integration: Showcases near real-time processing capabilities critical for global air quality models and public health alerts.

Observation-Based Radiative Kernels From CloudSat/CALIPSO

Fri, 31 May 2019 00:00:00 +0000

This research establishes a framework for evaluating global climate feedbacks by replacing standard model-derived radiative kernels with observational profiles constructed from the A-Train satellite track.

Key Innovations & Framework Updates

Elimination of GCM Base-State Bias: Traditional climate sensitivity diagnostics inherit systematic discrepancies from model assumptions. This tool uses empirical vertical measurements to ensure a neutral diagnostic base state.
Active Sensor Synergy: Built upon high vertical-resolution measurements from the 2B-FLXHR-LIDAR multi-sensor product, mapping distinct layers of the atmosphere simultaneously.
Cloud Masking Corrections: Clarifies longwave feedback mechanics by mapping exactly how cloud layers interact with, mask, and structurally alter the flux signals of non-cloud climate variables.

The role of cloud phase in Earth's radiation budget

Thu, 16 Mar 2017 00:00:00 +0000

This research establishes an observational framework to decompose the Earth’s Top-of-Atmosphere (TOA) Cloud Radiative Effects (CRE) by thermodynamic phase, isolating the unique roles played by liquid, ice, and mixed-phase clouds.

Key Takeaways

Global Radiative Baselines: Liquid water profiles remain the heaviest driver of solar planetary albedo cooling, while ice clouds act as the dominant atmospheric thermal greenhouse traps.
The Mixed-Phase Impact: Mixed-phase structures are shown to exert strong, disproportionate net cooling spikes concentrated along mid-to-high latitude marine storm tracks.
Model Benchmarking: Offers an absolute, multi-year active sensor validation record designed to pinpoint and correct systematic phase-transition biases within global climate simulation runs.