NSF NCAR · Research Applications Laboratory·working package — July 2026

Software opportunities under funding pressure

Where NCAR software can lead — a working package

A strategy scan, a fundable-project matrix, a funding pitch, and two working prototypes — assembled to explore where a software-focused RAL team can build distinctive, externally-fundable tools as core NSF support comes under pressure.

Strategy

Read the case

The argument, the evidence, and ten ranked project ideas you can re-weight yourself.

Interactive briefing

Software Opportunities Briefing

The funding context, the AI-weather landscape, documented software gaps, and a live, re-weightable matrix ranking ten project ideas across difficulty, usefulness, feasibility, fundability, and strategic fit.

Open the briefing Pitch deck

The Trusted Referee

An 11-slide pitch for the top-ranked idea — an open verification & benchmarking service for the AI-weather era, built on MET/METplus and the BEACON testbed. Press S for speaker notes.

Open the deck

Working prototypes

Try the tools

Three self-contained, browser-native prototypes that make hazard and design science legible — no install, no server, runs offline.

Prototype · dispersion

Plume Sentinel

A tunable Gaussian-plume hazard viewer: a 2D danger-band plan view and a WebGL 3D volume, colored by concentration mapped to danger levels. Presets for an SO₂ stack, a chlorine leak, and wildfire smoke.

Launch the viewer Prototype · impacts

Evacuation Decision Theater

A wind-driven wildfire (and hurricane) hazard coupled to a road-network evacuation model. Tune the winds, the rain, and when people leave — and watch the single road out gridlock, or everyone get out in time.

Launch the simulation Prototype · solar design

Shadow Study & Solar Design

Where the sun is, and where shadows fall, at any place, date, and time of year — for window placement, passive-solar gain, and orientation for fastest snow melt. Plan, isometric-3D, and sun-path views with a winter-sun exposure heatmap.

Open the tool

Deep dives

The project write-ups

Per-idea working documents: what to build (scope, architecture, phasing, risks) and how to position & fund it. Markdown — download or open as text.

#1 AI-model verification & benchmarking service #2 MPAS developer-experience kit #5 Evacuation & impact emulation #8 Open, verified generative downscaling + Browser-native plume visualization 2nd Private-sector, awareness & consumer ideas

Research

An honest investigation

Can fast neural weather models be made to handle 100-year storms? An ML-expert agenda, a devil's-advocate teardown, and the reconciled verdict.

▶ Synthesis & honest verdict (start here) A ML-expert: candidate approaches B Devil's-advocate: the teardown

The finding, in one line: for genuinely unprecedented events the honest lever isn't retraining the emulator — it's a fast ML model that knows when it's out of its depth and hands off to physics, with the handoff verified. Which is exactly the trusted-referee thesis, applied.

How to read this package. Start with the briefing for the argument and the ranking, skim the deck for the top bet, then open the two prototypes to see the "impact coupling" and "hazard visualization" ideas made real. The prototypes are deliberately simplified, illustrative tools — not operational forecasts. Everything here is a read-only research exploration compiled from public sources; verify institutional specifics internally before external use.