Engineering

Satellite Observational Infrastructure

Feasibility of and timeline to bring sufficient satellite observational infrastructure online
Uncertainty
High
Decision relevance
Medium
Resolvability scale
In silico

Baseline monitoring of background stratospheric conditions and variability would be invaluable for at least a few years prior to any deployment. Development time for satellite-borne remote sensing instruments can be significant, and some existing infrastructure is retiring without replacement. However, time-to-launch can be short for instruments which already have a high Technology Readiness Level  (TRL-6 or higher; e.g., the continuity-MLS instrument could be operational within 3.5 years from funding), and several relevant instruments are in development or available, including  the Aerosol Radiometer for Global Observation of the Stratosphere (ARGOS) and solar occultation missions GLOTemp (Laboratory Gas Filter Correlation Radiometer for Limb Occultation demo for upper atmosphere Temperature) and ALTIUS (ESA’s Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere). We indicate that this is resolvable "In silico" because it does not require SO2 injection, even though it would not in reality be resolved exclusively via modeling.

Time to develop, build, and launch new satellite infrastructure is more than 5 years from first large-scale funding

High

Observational requirements have not yet been defined in detail, so it is unclear what infrastructure is needed or how difficult this will be to put in place. Uncertain features include what spatial and time resolution of observation is required, and what satellites will carry instruments. The reason for uncertainty here isn't because we don't know how to measure relevant quantities; it is because it may take a long time to get sufficient assets in place, particularly given existing instrument retirements.

Medium

Delay in satellite launch either delays deployment (until sufficient baselining is done), or means insufficient monitoring and/or insufficient baselining, which would add to uncertainty in the assessments of SAI's impacts and efficacy.

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