Client-side wrapper to MET tooling
Push verification computation and data access into the browser itself — minimizing servers, installs, and round-trips. How much of the documented MET workflow can run entirely client-side against modern model output?
In-browser execution of documented MET approaches
Re-express MET's verification methods so they run directly in the client against analysis-ready data, faithful to the published methodology.
Why: removes the install/server barrier; lets anyone reproduce a verification from a URL.
Open Qs: which line types / methods are tractable client-side? how do we guarantee parity with reference MET output?
Analysis-ready gridded model output
Read chunked, cloud-native model fields directly in the browser instead of staging large files through a server.
Why: lazy, range-request access to only the chunks a view needs; scales to large grids without a download step.
Open Qs: how do we map MET's expected inputs onto chunked stores? regridding & masking client-side?
Columnar point & station data
Treat point observations and matched pairs as columnar tables queried in place, rather than parsing ASCII stat files.
Why: fast filtering/aggregation over millions of matched pairs; a natural fit for interactive exploration.
Open Qs: a schema for MET matched pairs? interop with existing
.stat outputs?
GPU compute for verification math
Offload heavy per-cell or per-pair statistics to the GPU for near-instant recomputation as the user changes thresholds or regions.
Why: interactive "what-if" on metrics that are otherwise a batch job.
Open Qs: which computations are GPU-amenable? numerical reproducibility vs. reference results?
Zero-install, shareable analyses
An entire exploration (data refs + selections + view) captured in a link or a small file, reopened by anyone with a browser.
Why: collaboration and reproducibility without environment setup.
Open Qs: what's the minimal portable "analysis state" to serialize?
Modern interaction with stat data
Let users directly steer what they see — selecting metrics, regions, thresholds, and groupings fluidly — instead of pre-baking plots in a batch step.
Direct-manipulation control of stat views
Users pick line types, metrics, and filters through the UI and the plot responds immediately, including recomputation where needed.
Why: shrinks the loop between "I wonder if…" and an answer.
Open Qs: what's the right vocabulary of controls that covers MET's breadth without overwhelming?
Data rendered straight to the GPU surface
Drive plots from stat data into a shader pipeline so very large series stay smooth.
Why: keeps dense, high-cardinality stat plots responsive.
Open Qs: where does GPU rendering pay off vs. add complexity?
Natural-language querying of results
Ask for a comparison in plain language and have it resolved into a concrete selection over the stat data.
Why: lowers the expertise needed to drive verification analysis.
Open Qs: how to keep it auditable and grounded in the actual data?
Cross-filtered linked views
Brushing one panel (time, region, threshold, lead time) filters all the others.
Why: verification questions are inherently multi-dimensional; linked views make the slices obvious.
Open Qs: which dimensions are the universal axes of MET output?
Novel plotting & verification visuals
Beyond static line plots — new ways to render, interact with, and reason about verification, including spatial and object-based methods.
3D / volumetric statistics
Render verification across a third axis (height, lead time, threshold) as an explorable volume rather than a stack of 2D plots.
Why: some structure only shows up across the full cube.
Open Qs: when does 3D aid insight vs. obscure it?
Object-based verification, visually
Interactive exploration of object-oriented verification — matched/unmatched objects, attributes, and how they pair across forecast and observation.
Why: object methods are powerful but hard to inspect in tables.
Open Qs: best visual language for object matching & attribute diffs?
Map-native spatial verification
Explore where forecasts succeed or fail on a pannable, zoomable map, with stats tied to geography and masks.
Why: spatial error is fundamentally geographic; show it that way.
Open Qs: projections, regridding, and overlaying masks client-side?
First-class uncertainty
Make confidence intervals and bootstrap spread a built-in, always-visible part of every comparison rather than an afterthought.
Why: differences without uncertainty invite over-interpretation.
Open Qs: how to show uncertainty without cluttering dense plots?
Ensemble verification views
Purpose-built visuals for rank histograms, spread-skill, reliability, and other ensemble diagnostics with interactive drill-down.
Why: ensemble diagnostics have rich structure underused in static form.
Open Qs: which ensemble diagnostics benefit most from interaction?
Animated & scrubbable plot interaction
Scrub through time, lead time, or threshold and watch verification evolve, with smooth transitions that reveal trends.
Why: motion exposes temporal/threshold structure tables hide.
Open Qs: which axes are worth animating, and where does it mislead?
Other modernization directions
Cross-cutting ideas that could raise the floor for the whole experience — provenance, collaboration, accessibility, and interpretation.
Assisted interpretation & narration
Generate plain-language summaries of what a verification result is showing, grounded in the underlying numbers.
Why: turns metrics into decisions for non-specialist stakeholders.
Open Qs: how to keep narration honest and traceable to data?
Provenance & reproducibility by default
Every plot carries the data sources, selections, and method versions needed to regenerate it exactly.
Why: verification results are evidence; they should be reproducible.
Open Qs: what minimal metadata makes a result fully reproducible?
Notebook-style reproducible sessions
A narrative document interleaving explanation, live controls, and verification views that re-runs end to end.
Why: bridges exploration and the report that comes out of it.
Open Qs: how live vs. static should a shared session be?
Collaborative annotation
Comment on and mark up specific plots/regions so a team can discuss results in context.
Why: verification is rarely a solo activity.
Open Qs: annotations tied to data selections, not pixels?
Accessible & responsive by design
Color-vision-safe palettes, keyboard navigation, screen-reader-friendly summaries, and layouts that work beyond the desktop.
Why: broadens who can use verification output and how.
Open Qs: how to make dense scientific plots genuinely accessible?
Interoperability with the MET ecosystem
Play well with existing MET / METplus outputs and companion tooling so this augments rather than replaces established workflows.
Why: adoption depends on fitting the world users already have.
Open Qs: which existing formats/outputs are the integration seams?
Guided exploration / diagnostic storytelling
Opinionated paths that walk a user from "is my forecast good?" through the diagnostics that answer it.
Why: lowers the expertise floor and standardizes good practice.
Open Qs: which diagnostic journeys are worth encoding first?
Scale to large result sets
Stay responsive when the stat data is large — streaming, summarization, and level-of-detail rather than "load everything."
Why: real verification campaigns produce a lot of output.
Open Qs: where are the performance cliffs in a client-first design?