Key Challenges

• Large product taxonomy: multiple regions, product types and model outputs (including WRF variants).
• Need for fast, personalized access — live weather and location-aware predictions on the homepage.
• Clear separation between global products (9 regions × 11 products), WRF model outputs, and India location forecasts (133+ predictions).
• Future-proofing: modular architecture to support upcoming Aviation Module and miscellaneous customer-specific datasets.

Proposed Solution (High-level)

CnEL India proposed a modular, user-centered information architecture and a phased delivery plan that converts WeaClim’s product breadth into a clean, navigable mobile experience. The structure is designed to minimize cognitive load and maximize quick access to the most relevant forecasts.

1. Primary Navigation

1. Home (Live & Local): location-aware snapshot (current + short-term next 24–48hr). Quick access to live weather and local predictions based on the user’s device location.
2. Global Forecasts: region-first experience (9 regions). Each region expands to reveal the 11 product types as selectable layers or product cards.
3. India — Regional & Location-Specific: prominent placement for India with quick filters for State/UT, and a searchable list of the 133+ location forecasts.
4. WRF Model Outputs: dedicated model section (WRF 27km short-range etc.) with product-specific playback and time-step controls.
5. Aviation: reserved module placeholder (to be launched when finalized), integrated with model outputs and METAR/TAF where applicable.
6. Misc / Customer Sets: flexible area for ad-hoc customer datasets and future additions.

2. Product Layering & Presentation

Each product (e.g., Rainfall 24hrs, Clouds 2hrs, Winds at 200/500/700/850 hPa, MSLP, Max/Min Temp, etc.) is represented as a reusable “product card” consisting of:

• Thumbnail (animated gif or small loop for quick visual cue)
• Product name and short description
• Model source & timestamp
• Controls: time-slider, play/pause, opacity (for overlays), and download/share

3. Search & Filters

Robust search that supports region, product type, model source, and specific location names. Filters include:

• Region (Africa, Australia, East Asia, Eurasia, Europe, India, North America, South America, World)
• Product (Rainfall, Clouds, Winds at multiple levels, MSLP, Max/Min Temp, etc.)
• Model (WRF 27km — short range, other model sources)
• Time-range & data freshness

4. Homepage — Live & Personalized

The homepage is optimized for rapid situational awareness:

• Top card: Live location snapshot (auto-detected with quick permission controls)
• Quick toggles: Today / Next 24hrs / 3-day overview
• Favorites: users can pin regions, products, or locations for one-tap access

Technical Architecture (Summary)

A lightweight hybrid approach for performance and offline resilience:

• Frontend: React Native or Flutter (single codebase for Android & iOS) with native modules only where necessary for location and performance-sensitive rendering.
• Backend: Restful APIs / GraphQL to serve products, with CDN-backed raster/tiles and optionally vector tiles for overlays.
• Data & Models: Time-series product store, WRF outputs managed via object storage (S3-compatible) and cached tiles for fast retrieval.
• Realtime & Push: WebSocket or MQTT for live alerts, and push notifications for critical weather advisories.
• Analytics & Monitoring: Usage metrics, product access heatmaps, and error telemetry to inform product and UX improvements.

Implementation Roadmap (Phased)

1. Phase 1 — Foundation: Core navigation, Home live-location snapshot, Global & India region pages, product card UI, search & filters.
2. Phase 2 — Models & Playback: WRF integration, time-slider, playback controls, caching strategy.
3. Phase 3 — Location Forecasts: India 133+ location pages, state/UT filters, favorites & user profiles.
4. Phase 4 — Aviation & Misc: Aviation module launch, custom customer data sets, advanced sharing & export features.
5. Phase 5 — Optimization & Scale: Performance tuning, offline mode, A/B testing on key UX flows.

Deliverables per phase: clickable prototypes, API specifications, data ingestion pipeline, mobile builds (alpha/beta), release notes and documentation.

Why CnEL India Is the Right Team for This Project

• Domain-aware engineering: CnEL has experience translating meteorological datasets into performant, user-friendly interfaces — essential when presenting multi-layered weather products.
• Proven product architecture skills: We design modular architectures that make complex catalogs navigable and future-proof, enabling quick addition of modules like Aviation.
• Performance-first delivery: Image/tiles caching, prudent use of native rendering, and a CDN-first backend ensure fast map and playback performance even on constrained networks.
• UX for high-signal decisions: We prioritize clarity — concise product cards, meaningful defaults, and fast access to live/local information to support both professionals and the general public.
• Transparent collaboration: Iterative roadmap planning, regular demos, and detailed hand-offs to your technical team to reduce conceptual friction and speed delivery.

Sample User Flow

Scenario: Aviation operations manager needs 6-hour wind profile over North India.

1. Open app > Home > Quick search > type “North India”
2. Filter: Product > Winds (200/500/700/850 hPa) > select 200 hPa
3. Play time-slider to review the next 6 hours; use opacity control to overlay surface winds and MSLP
4. Save as favorite / export snapshot / send to operations team

Client Testimonial

“Working with CnEL India transformed our conceptual brief into a practical, actionable roadmap. Their team quickly understood the breadth of our products and proposed a clean, modular mobile structure that makes our forecasts instantly discoverable. The clarity they brought to the architecture has already improved the technical team’s confidence and progress.”

Expected Outcomes

• Reduced time-to-insight for end users with a location-first homepage.
• Scalable platform enabling addition of Aviation and custom datasets without major rework.
• Improved developer productivity due to a documented, modular architecture and reusable product components.

Next Steps

CnEL recommends a 2-week discovery sprint to finalize data contracts, a clickable prototype for Home & Global forecast flows, and alignment meeting with WeaClim’s technical team to hand over the roadmap and timelines.

Contact: For scheduling the discovery sprint and next demo, please reach out to the CnEL India Project Lead.