Design Weather Prediction System - System Design | WinJob

Global NWP platform framing and forecast consumers

Frame Design Weather Prediction System as an operational NWP factory—not a static weather app. This section covers global nwp platform framing and forecast consumers with mechanisms interviewers at Google, IBM, or NOAA expect.

Numbers to state early

Metric A: 2.1B API calls/day
Metric B: hourly deterministic + 6h ensemble
Metric C: CAP/XML alerts

Mechanism

Anchor a three-plane system: observation ingest (satellite, radar, METAR, buoys), HPC numerical weather prediction (WRF/GFS-class), and forecast products (grid tiles, point APIs, severe alerts). Consumers span mobile apps, airlines, energy traders, and emergency managers—not a hobby temperature widget.

Failure and edge cases

Treating weather as a CRUD app ignores model run cadence, lead-time validity, and licensed redistribution of third-party radar feeds.

When discussing Global NWP platform framing and forecast consumers, cite 2.1B API calls/day and trace Observations → Assimilation → Serving through assimilation cutoff, immutable run publication, and CAP alert idempotency—distinct from generic CRUD or social feed scale math.

Java

javaOne Dark Pro

1 public record ModelRun(String id, Instant validTime, int leadHours) {}

Python

pythonOne Dark Pro

1 @dataclass(frozen=True)
2 class ModelRun:
3     run_id: str
4     valid_time: datetime
5     lead_hours: int

TypeScript

typescriptOne Dark Pro

1 export interface ModelRun {
2   runId: string;
3   validTime: string;
4   leadHours: number;
5 }

Why interviewers care

Weather Prediction System interviews reward crisp scope, explicit trade-offs, and failure stories—not generic microservice diagrams.

Interview checkpoint

Name one failure story for Global NWP platform framing and forecast consumers that proves you understand real outages, not happy-path diagrams.

Key Highlights

•2.1B API calls/day
•Observations → Assimilation → Serving
•Anchor a three-plane system: observation ingest (satellite, radar, METAR, buoys), HPC nume

1	@dataclass(frozen=True)
2	class ModelRun:
3	run_id: str
4	valid_time: datetime
5	lead_hours: int

1	export interface ModelRun {
2	runId: string;
3	validTime: string;
4	leadHours: number;
5	}