MonWatch-UI v3.0.3

A Windows tool for browsing, previewing, and analyzing satellite imagery — now with native SATAID support.

MonWatch-UI lets you explore geostationary satellite data from multiple sources: Himawari AWS, local SATAID (.Z) archives, and more. Navigate by date, time, and spectral band, preview at multiple quality levels, view with georeferenced overlays, and switch between four interface modes tailored for professionals, enthusiasts, and users familiar with the classic SATAID workflow.

Developed by PWARDS-weather — the Pasacao Weather Atmospheric and Real-Time Data System.

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True_RGB_Animation_Preview.mp4

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Features

• Full SATAID Support – Native handling of .Z files, dedicated SATAID mode & tab, classic interface replication
• Four UI Modes – Casual (simplified), Professional (advanced), Hobby (weather enthusiasts), SATAID (classic interface)
• Drag-and-drop loading – Drop Himawari .tif (depreciated), NetCDF, or SATAID .Z files directly into the UI
• Floating panels – Detach Center Viewport & Right Panel for multi‑monitor setups
• Robust crash logging – Global exception hook + threading support (no more silent crashes)
• Live brightness/contrast controls and SATAID Cache Manager
• Dynamic Date & Time selector – Shows only dates with actual data available
• Non‑blocking caching bands dialogue – Prevents interface freezes during band caching
• CRS georeferencing – Lat/lon grid + coastline overlays (works on standard formats)
• Multi-quality preview – View imagery at 0.25x, 0.5x, and 1x resolution (removed)
• Automatic setup – run.exe handles all dependencies on first launch (no admin required)
• RGB composites – Support for JMA recipes, with more planned
• Area of Responsibility (AoR) overlays – PAGASA PAR, JMA, TCAD, TCID, Manila FIR

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Requirements

• Windows 10 or 11
• RAM: 2 GB minimum, 4 GB required for smooth performance
• Internet connection (for AWS data access; offline SATAID processing works without internet)
• No Python pre-installation needed – run.exe sets up a portable Python environment automatically

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Installation

1. Clone or download this repository: git clone https://github.com/PWARDS-weather/MonWatch-UI.git
2. Run run.exe (double‑click)
3. The app launches automatically after initial dependency installation

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Usage

Drag and Drop
Drop any supported file (.tif (depreciated), .nc, SATAID .Z*) into the main panel to load and preview it.

Manual Navigation
Click Open Folder to browse local directories. For Himawari data, navigate a date → time → spectral band structure. For SATAID files, select the folder containing .Z* archives.

Interface Modes
Switch between Casual, Professional, Hobby, and SATAID modes from the menu. Each mode tailors the visible panels and options to your workflow.

Data Sources

• NOAA Himawari AWS buckets (requires internet)
• Local SATAID archives (.Z format)
• NetCDF/TIFF files processed by the included tools

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Dependencies

All dependencies are installed automatically by run.exe via pip. The core packages include:

Package	Purpose
PySide6	UI framework
Pillow	Image processing
tifffile	TIFF/GeoTIFF reading
numpy	Array operations
xarray, netCDF4	SATAID & NetCDF data handling
boto3, botocore	AWS S3 access for Himawari data
satpy	Satellite product generation & compositing
rasterio	Geospatial raster I/O
pyproj	Coordinate transformations
pyshp	Shapefile support for overlays
cartopy	Map projections & georeferencing
requests	HTTP downloads
cupy-cuda12x	GPU-accelerated array operations (optional)
numba	JIT-compiled numerical routines (optional)

(Full list with exact versions is in requirements.txt.)

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Legend

• [x] — Fully added / completed in a recent release
• [x+] — Improving / in active development (partial or ongoing work)
• [~] — Planned / in the works (explicitly mentioned for future)
• [ ] — Not yet started

Animation & Visualization

• Brand new Animation tab — play, pause, scrub, loop + smooth real‑time zoom/pan with prefetching
• Live mouse readout (Latitude/Longitude, B13 Brightness Temperature, AoR status instantly)
• Proper handling for storms crossing the dateline (Pacific systems now display correctly)
• Three UI modes: Professional, Casual, and Hobby (now four with SATAID mode)
• Cleaner map overlays with gridlines + coastlines + better viewport centering
• Better performance on lower‑VRAM GPUs with smart cache management
• Area of Responsibility (AoR) overlays: PAGASA (PAR), JMA, TCAD, TCID, Manila FIR
• Floating panels — detachable Center Viewport & Right Panel
• SATAID‑style Options menu restored
• Dynamic Date & Time selector (shows only available data)
• Non‑blocking caching bands dialogue
• Live brightness/contrast controls for SATAID imagery

Data Processing & Download Pipeline

• Complete range‑download overhaul using non‑blocking RangeS3DownloadWorker (full UI responsiveness)
• Full support for Japan and Target rapid‑scan sectors (correct HHMM filename prefixes, mixed rapid‑scan folders)
• Consistent flat local folder naming for both range and single‑file downloads
• Pre‑download check that automatically skips already‑downloaded .bz2 / .DAT files
• Automatically starts processing after download finishes
• Improved product‑type detection, wind data filtering, and sector handling
• Smarter micro‑group loader using band + area tokens (Rxxx/JPxx) for mixed rapid‑scan folders
• Incremental processing — only missing bands are handled
• NDMW Level‑2 wind data is now automatically merged into the _AHI.nc file
• Per‑band dimension naming to prevent shape conflicts
• Improved ADS sidecar files with geotransform, area metadata, and full band inventory
• New standalone --merge-wind command‑line option
• Large NetCDF files now load smoothly in the background without freezing the app
• Priority B03 band caching + overall improved caching system
• bg_to_nc.py v3.3.2 – fixed _sanitize_attrs to preserve list/tuple attributes, improved numpy handling

Other Recent Additions

• RGB composites support (JMA recipes; NOAA + other GEO satellites planned for future)
• Multi‑layer product improvements and general stability/usability enhancements
• SATAID Cache Manager
• Enhanced Professional Devkit – improved Channel Editor with RGB/Single/Dual/FG+BG modes and live preview
• Complete modular code refactor (split into products.py, Engine.py, Workers.py, etc.) for maintainability
• Windy Point forecast integration (live point forecasts inside Cyclone)

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🔄 Currently In Progress / Planned

• [x+] SATAID UI additional functions and UI fixes
• [~] MetraWeather Lightning & Point Forecast integration
• [~] Support for other geostationary satellites: GOES, Meteosat, FY‑4, etc. (GOES targeted for v3.0.4)
• [~] NWP & forecasting models – full GRIB2 integration for model data overlays
• [~] Multi‑viewport & stacking viewport – view multiple bands and forecast models simultaneously, with synchronized animation
• [~] Sea Surface Temperature (SST) – real‑time SST layers and analysis
• [~] 3D Globe – multi‑satellite imagery on a rotatable 3D view
• [~] Bird’s‑eye view – perspective viewing angle
• [~] Diagnostic tools – sounding profiles, cross‑section analysis, storm relative motion
• [~] Analysis tools – contouring, isotherm/isobar drawing, distance/area measurement
• [x+] Wind Overlay improvements + AMV (wind vectors) bug fixes and enhancements
• [~] Tracks tab + more customizability options
• [~] General GUI improvements (ongoing)
• [~] Export current view as PNG / GeoTIFF

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Roadmap

The team is dedicated to making MonWatch-UI the most powerful, free satellite & weather analysis platform. Upcoming features include:

• SST overlay
• [~] Additional geostationary satellites (GOES, Meteosat, FY‑4)
• [~] 3D Earth visualization
• [~] Multi‑viewport / stacking viewport
• [~] Full GRIB2 model integration
• [~] Diagnostic and analysis tools
• [~] Export current view as PNG / GeoTIFF

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Contributing

Contributions are welcome! To get started:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/my-feature)
3. Make your changes and test them
4. Open a Pull Request with a clear description

For bugs or feature requests, please open an issue.

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License

This project is licensed under the MIT License. See LICENSE for details.

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About PWARDS

PWARDS (Pasacao Weather Atmospheric and Real-Time Data System) is a small open‑source weather initiative based in Pasacao, Camarines Sur, Philippines, focused on building accessible meteorology tools for students and hobbyists.

GitHub · Facebook

Himawari‑8/9 data courtesy of the Japan Meteorological Agency (JMA), openly distributed via NOAA AWS Open Data Program.

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Screenshots (v3.0.3)

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🌐 Website: pwards.loophole.site
Happy forecasting!
– The PWARDS Weather Team