New Features

Atmospheric Diagnostics Expansion: Added new compiled diagnostics and Python bindings for atmospheric-column workflows, including DCAPE and the updated tropical-cyclone / growth-rate calculation paths.
Hybrid and Sigma Interpolation Modernization: Expanded the vinth2p family with clearer column-major and C-order entry points, improved ECMWF handling, and updated hybrid / sigma remapping helpers.

Improvements

Spharm and Wind Analysis Refactoring: Refined spherical-harmonic and reduced-vector-wind internals to reduce wrapper overhead, improve caching, and make the public flow clearer.
Plotting Pipeline Acceleration: Moved more scatter and curly-vector validation / sampling work into native helpers to reduce Python-side overhead and temporary-array churn.
Build and Documentation Cleanup: Continued Meson build modernization and refreshed documentation and tests around the reorganized interfaces.

Cleanup

Legacy API Removal: Removed the old Iris interface and other unused legacy paths, and tightened the wind-analysis / spectral-helper APIs.
Regression Coverage: Added focused tests for the updated interpolation, plotting, spectral-helper, and wind-analysis paths.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu about 1 month ago

Improvements

Tropical cyclone potential intensity diagnostics modernization: aligned the workflow with recent upstream validation data and decomposition conventions while keeping the compiled backend as the primary execution path.
spharm internal optimization: improved the internal spherical-harmonic helper flow so repeated potential-field reconstruction can reuse intermediate spectral results more efficiently.
windspharm performance improvements: reduced Python-side overhead in the tested wind-decomposition workflow family while preserving established public numerical conventions.
Growth-rate and pressure-interpolation additions: added compiled atmospheric-column growth diagnostics and pressure-coordinate interpolation support for Chemke-style workflows, including batch evaluation, spectral smoothing, and zonal-wavenumber mode support.

Bug Fixes

Tropical cyclone potential intensity parity and robustness: fixed remaining pressure, outflow, and missing-column handling issues and improved agreement with the current upstream reference implementation.
spharm and windspharm regression coverage: added focused tests for updated internal spectral-helper and wind-analysis paths, including shape-validation coverage for the optimized flow.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu about 1 month ago

Skyborn - v0.3.21 (Apr 30, 2026)

Improvements

Scatter Placement Acceleration: Moved the cell-interior candidate
generation path in skyborn.plot.scatter into the native C helper so
projected stippling workflows spend less time in Python loops and
temporary array construction
Curly-Vector Display-Space Sampling Optimization: Moved
_NCLDisplaySampler display-cell validation and batch display-grid
sampling into the native plotting helper, reducing intermediate-array
overhead and lowering memory use for projected curly_vector
workflows on larger grids
Display-Curve Validation Fast Path: Extended the native
curly-vector tracer so it can return both data-space and display-space
curves in one pass and run the display-curve quality screening in C
while preserving the previous plotted geometry

Cleanup

Plot Internal Simplification: Removed unused internal helper aliases
from skyborn.plot.vector and kept the low-level plotting tests
importing their implementation modules directly

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu about 2 months ago

Skyborn - v0.3.20 (Apr 20, 2026)

Skyborn 0.3.20

This release expands Mann-Kendall trend analysis, adds modern interpolation kernels and diagnostics, modernizes several regridding and interpolation backends, and improves scatter stippling plus cross-section handling.

New Features

Expanded Mann-Kendall trend analysis to support the same core test families as pymannkendall, while extending them to multidimensional NumPy and xarray workflows.
Added public support for grouped multivariate, regional, correlated multivariate, seasonal, correlated seasonal, pre-whitening, trend-free pre-whitening, Hamed-Rao, Yue-Wang, and partial Mann-Kendall workflows.
Added standalone partial-Mann-Kendall APIs for one-dimensional, multidimensional, and xarray inputs.
Added modern Fortran kernels for hybrid-to-pressure and sigma-to-hybrid interpolation in skyborn.interp.
Added public hybrid-level diagnostics: skyborn.interp.pressure_at_hybrid_levels and skyborn.interp.delta_pressure_hybrid.

Improvements

Modernized the compiled rcm2rgrid, rcm2points, triple2grid, grid2triple, and shared linint2 sources to free-form Fortran .f90 while keeping the public entry points unchanged.
Improved interpolation performance and build behavior by reducing eager-wrapper overhead, trimming temporary-array use, splitting duplicated support-library compilation in src/skyborn/interp/meson.build, and renaming the internal vinth2p acceleration module from vinth2p_backend to vinth2p_kernels.
Improved skyborn.plot.scatter so cell-interior stippling now works better for masked rectilinear grids and also supports inferred curvilinear cell geometry.

Bug Fixes

Extended skyborn.calc.troposphere WMO tropopause workflows to handle time-varying single-axis isobaric cross-sections such as (time, level, lat) and (time, level, lon) while preserving the correct output dimensions.
Dropped incompatible 2D auxiliary source-grid coordinates such as TLAT and TLONG after rcm2rgrid remapping instead of raising coordinate-size conflicts.
Restored legacy exact-hit missing-value behavior in rcm2points and rgrid2rcm so unresolved fields can still fall through to the historical interpolation logic when appropriate.
Added focused tests for the updated Mann-Kendall, troposphere, and interpolation dispatch and wrapper paths.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu about 2 months ago

Skyborn - v0.3.19 (Apr 7, 2026)

New Feature

Added skyborn.plot.scatter for gridded map and profile stippling with
NCL-style display-space thinning.
Added skyborn.plot.scatter to the explicit skyborn.plot public API.
Added focused plotting tests, examples, and documentation for the new
scatter-stippling workflow.
Implemented the public scatter entry point in its own
skyborn.plot.scatter module so the display-space thinning logic stays
isolated and easier to maintain.
Added skyborn.plot.vector as the unified public facade for the
curly-vector feature family:
- skyborn.plot.vector.curly_vector
- skyborn.plot.vector.curly_vector_key
- skyborn.plot.vector.CurlyVectorPlotSet
- skyborn.plot.vector.CurlyVectorKey
Consolidated the curly-vector implementation into
skyborn.plot.vector so the public wrapper logic and the low-level
vector helper surface now live in one top-level module.
Removed the separate top-level implementation files
ncl_vector.py, vector_key.py, and vector_plot.py from
skyborn.plot.
Kept historical module imports working through package-level
compatibility aliases, so existing imports do not need to break
immediately.
Narrowed the skyborn.plot package-root export surface so the common
public entry points are now function-first:
- skyborn.plot.curly_vector
- skyborn.plot.curly_vector_key
- skyborn.plot.scatter
- skyborn.plot.add_equal_axes
- skyborn.plot.createFigure
Removed the temporary package-level compatibility aliases for the deleted
historical modules skyborn.plot.ncl_vector, skyborn.plot.vector_key,
and skyborn.plot.vector_plot.
Updated plotting examples and user-facing documentation to recommend
skyborn.plot.vector as the module-oriented import path for curly-vector
usage while preserving the existing package-level skyborn.plot exports.

Interpolation

Enhanced model-level interpolation in
skyborn.interp.interpolation.
Improved skyborn.interp.interp_hybrid_to_pressure so hybrid-sigma to
pressure remapping now chooses a more suitable execution path for ordinary
in-memory arrays and Dask-backed arrays instead of always forcing the older
chunked workaround.
Added public hybrid-level diagnostics:
- skyborn.interp.pressure_at_hybrid_levels
- skyborn.interp.delta_pressure_hybrid
Improved below-ground temperature extrapolation support in the hybrid-level
interpolation workflow while keeping compatibility with the older Skyborn
helper calling pattern.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 2 months ago

Skyborn - v0.3.18 (Apr 2, 2026)

Plotting API Cleanup

Renamed the NCL-like vector plotting public API to the new names:
- skyborn.plot.curly_vector (unified arrays + xarray entry point)
- skyborn.plot.curly_vector_key
- skyborn.plot.CurlyVectorPlotSet
- skyborn.plot.CurlyVectorKey
Removed the legacy plotting API names from the public surface:
- velovect
- velovect_vertical_profile
- dataset_curly_vector
- curved_quiver
- add_curved_quiverkey
- CurvedQuiverplotSet
- CurvedQuiverLegend
Split the plotting implementation into clearer modules:
- skyborn.plot.vector_plot for the core curly-vector renderer
- skyborn.plot.ncl_vector for the xarray / Cartopy dataset wrapper
- skyborn.plot.vector_key for the reference-vector annotation artist
Replaced wildcard plotting exports with an explicit skyborn.plot public API.
Added type annotations to the renamed public plotting entry points and key artist class.
Updated plotting tests, examples, and documentation to the new curly-vector API only.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 2 months ago

Skyborn - v0.3.17 (Mar 30, 2026)

v0.3.17

Skyborn v0.3.17 introduces optional CDO integration, expands platform support, and includes several important fixes and performance improvements.

Added optional CDO integration through the new skyborn.cdo namespace.
Added official Python 3.14 support across Linux, macOS, and Windows.
Added manylinux2014 wheel builds for better compatibility with older Linux environments.
Removed the skyborn.conversion GRIB-to-NetCDF conversion module and its related tests and documentation.
Fixed numerical drift in the modern spharm Fortran implementation to better match legacy SPHEREPACK behavior.
Improved windspharm performance by speeding up the modern spharm backend while keeping results equivalent.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 3 months ago

Skyborn - v0.3.16 (Dec 28, 2025)

What's Changed

🐛 Bug Fixes

Fix mann_kendall_xarray dimension handling for scalar dimensions and preserve dimension order
Remove deprecated macOS Intel (macos-13) CI support
Enhance .zenodo.json metadata for accurate package description and academic citations

📦 Dependencies

Bump pypa/cibuildwheel from 3.2.1 to 3.3.0
Bump actions/checkout from 5 to 6

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 6 months ago

Skyborn - v0.3.15 (Oct 29, 2025)

New Features in the interp Submodule: Enhanced Interpolation and Regridding Capabilities

Added rcm2points: Nearest neighbor interpolation from curvilinear grids to arbitrary point sets
Added rcm2rgrid: Regridding from curvilinear grids to regular latitude-longitude grids
Added rgrid2rcm: Reverse regridding from regular latitude-longitude grids to curvilinear grids
Added grid_to_triple: Convert regular grids to irregular triplet representation (x, y, value)
Added triple_to_grid: Map irregular triplets to regular grids (nearest neighbor, supports search radius/spherical distance)

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 8 months ago

Skyborn - v0.3.14 (Sept 9, 2025)

🌀 New TC Genesis Potential Index (GPI) Module

Tropical Cyclone Potential Intensity Calculations: Complete implementation of Emanuel's potential intensity theory
- 19-25x Performance Acceleration: Achieves 19-25 times speedup compared to pure Python implementations
- Multi-Dimensional Support: Handles single profiles, 3D gridded, and 4D time series data
- Comprehensive Unit Handling: Automatic unit detection and conversion for temperature, pressure, and humidity
- xarray Native Interface: Full integration with xarray data structures and metadata preservation
Key Features:
- Potential Intensity Calculation: Maximum sustained wind speed and minimum central pressure
- Smart Dimension Detection: Automatically identifies time, level, lat, and lon dimensions
- Extensive Unit Support: Handles various unit formats (K/°C/°F, Pa/hPa/mb/atm, kg/kg/g/kg/%)

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 9 months ago

Skyborn - v0.3.13 (Aug 31, 2025)

🔧 Breaking Changes

Removed Iris Support: Removed fill_cube function and iris dependencies from gridfill module
- Use skyborn.gridfill.xarray.fill for xarray DataArrays instead
- Iris cube support was causing package conflicts and installation difficulties
- Focus shifted to xarray-based workflows which are more common in the scientific Python ecosystem

🎯 Tropopause Calculation Enhancements

New Comprehensive Tropopause Module: Complete implementation of WMO tropopause calculation with multi-dimensional support
- 1D Profile Support: New trop_wmo_profile() function for single atmospheric profiles
- 2D Spatial Analysis: Support for (level, lat) and (level, lon) cross-sections
- 3D & 4D Gridded Data: Enhanced support for spatial and temporal datasets
- Simplified xarray Interface: Auto-generates pressure from level coordinates
- Performance: Optimized Fortran backend with 0.38ms per profile processing
Enhanced xarray Integration:
- Automatic Pressure Generation: trop_wmo(temperature) - no pressure array needed
- Smart Dimension Detection: Automatically detects lat, lon, level, and time dimensions
- Metadata Preservation: Maintains coordinate information and CF-compliant attributes
- Flexible Input Formats: Works with any dimension ordering and coordinate names
Improved Code Quality:
- Simplified Imports: Removed try-except blocks, direct Fortran module importing
- Parameter Consistency: Updated interface with temperature, pressure parameter order
- Better Documentation: Comprehensive examples for all supported data formats
- Removed Unused Code: Cleaned up _detect_cyclic_longitude function

🌊 New Geostrophic Wind Module

Complete Geostrophic Wind Implementation: New high-performance module for calculating geostrophic wind components from geopotential height fields
- SIMD-Optimized Fortran Backend: Vectorized calculations with OpenMP parallelization for optimal performance
- Multi-Dimensional Support: Handles 2D, 3D, and 4D data arrays with automatic dimension handling
- Automatic Parameter Detection: Smart longitude cyclicity detection and south-to-north latitude ordering
- Dual Interface Design: Both NumPy arrays and xarray DataArrays supported
xarray Integration: Seamless integration following established patterns
- Auto-Coordinate Detection: from skyborn.calc.geostrophic.xarray import geostrophic_wind
- Zero Manual Parameters: result = geostrophic_wind(z) - that's it!
- CF-Compliant Output: Standard metadata with eastward/northward wind components
- Multi-Resolution Support: Adaptive algorithms work with 0.25° to 10° grids
Optimized Algorithms: Production-ready implementation
- Finite Difference Method: Uses geostrophic balance equations with proper boundary conditions
- Coriolis Parameter Handling: Accurate f-plane approximation with pole region handling
- Memory Efficient: Single precision (float32) processing with minimal memory footprint
- Flexible Grid Support: Works with both cyclic and regional domains

🔧 Technical Improvements

Hybrid Build System: Implemented innovative meson-setuptools hybrid architecture for seamless extension development
- Zero-Configuration Module Addition: New Cython/C/Fortran modules automatically discovered and built
- Unified Workflow: Single command python setup.py build_ext --inplace builds all extensions
- Cross-Platform Optimization: Automatic compiler detection and platform-specific optimization flags
- Smart Extension Discovery: setup.py automatically finds and compiles all submodules with meson.build files
- Backwards Compatible: Maintains existing CI/CD workflows while enabling modern build features
- Developer Friendly: Copy template meson.build, modify module name, and it's ready to build
Enhanced Extension Building: Streamlined process for adding compiled extensions
- Template-Based: Simple copy and modify approach for new extensions
- Automatic Integration: No manual setup.py modifications required for new modules
- Parallel Builds: Meson enables efficient parallel compilation
- Incremental Updates: Only rebuilds changed modules for faster development cycles
Fortran Extensions: Added 2D and 1D specific interfaces (prepared for future compilation)
Enhanced Error Handling: Better validation for different data dimensionalities
Memory Optimization: Efficient processing of large multi-dimensional arrays
CF Compliance: Output follows Climate and Forecast metadata conventions

📊 New Functionality

Spatial Correlation Analysis: Added skyborn.calc.spatial_correlation function for analyzing spatial patterns of correlation between gridded data and time series
Enhanced Linear Regression: Improved linear_regression function with robust NaN value handling for climate data with missing observations
Multi-Scale Analysis: Seamlessly analyze from single profiles to global climate datasets
Time Series Support: Process multi-year datasets with preserved temporal coordinates
Cross-Section Analysis: Dedicated support for meridional and zonal cross-sections
Automatic Sorting: Intelligent pressure level ordering with user override options

🧪 Validation & Testing

Successfully tested on realistic atmospheric data (CESM2 model output)
Verified accuracy: 99.96% success rate on 663,552 grid points
Performance validated: 100 profiles processed in 38ms
Cross-validated against standard atmospheric profiles

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 10 months ago

Skyborn - v0.3.12 post1 (Aug 21, 2025)

v0.3.12.post1 - Fix spharm module wheel packaging

Bug Fixes

Fixed spharm module wheel packaging: Resolved issue where compiled Fortran extensions (_spherepack*.pyd files) were missing from wheel distributions built via GitHub CI
Improved meson integration: Updated setup.py to use meson's native installation capabilities instead of manual file copying
Enhanced build system: Streamlined meson.build configuration for better wheel compatibility
Fixed macOS wheel building: Set MACOSX_DEPLOYMENT_TARGET=14.0 to resolve OpenMP dependency compatibility issues

Changes

setup.py

Configured meson to install directly to setuptools build directory using --python.purelibdir and --python.platlibdir parameters
Added auto-discovery of meson modules for better extensibility
Simplified build logic by removing complex file copying mechanisms

meson.build

Changed from install: false to install: true with proper install_dir configuration
Maintained smart copying logic for --inplace builds
Enhanced cross-platform compatibility

GitHub Actions (.github/workflows/build-wheels.yml)

Set MACOSX_DEPLOYMENT_TARGET=14.0 for macOS arm64 builds to match OpenMP library requirements
Ensures compatibility with libgomp.1.dylib minimum target version
Compatibility: x86_64 (Intel) wheels are built for macOS 13 and later; arm64 (Apple Silicon) wheels require macOS 14 and later. Users running older macOS versions may need to build from source or use an x86_64 wheel under Rosetta where applicable.

Validation

Successfully tested wheel building and installation
Confirmed _spherepack*.pyd files are now correctly included in wheel distributions
Verified functionality across different installation methods

Installation

Install the updated version:

pip install --upgrade skyborn==0.3.12.post1

Or install from source:

pip install --upgrade git+https://github.com/QianyeSu/Skyborn.git@v0.3.12.post1

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 10 months ago

Skyborn - v0.3.12 (Aug 19, 2025)

Major Performance Enhancements

Modernized Spherical Harmonics (spharm) Submodule: Complete Fortran code modernization for significantly improved windspharm performance:
- Modern Fortran Standards: Updated legacy Fortran code to modern standards with improved memory management and vectorization
- ~25% Performance Boost: Windspharm calculations now run approximately 25% faster across all operations
- Optimized Algorithms: Enhanced spherical harmonic transformations with better numerical efficiency
- Memory Optimization: Improved memory layout and access patterns for better cache performance
- Cross-Platform Compatibility: Better compiler optimization support across different platforms and architectures
- Maintained Accuracy: All numerical results remain identical while achieving significant speed improvements
Enhanced Build System: Streamlined compilation process for the modernized Fortran components
Python 3.13 Support: Added full compatibility with Python 3.13:
- Wheel Distribution: Pre-compiled wheels now available for Python 3.13 across all supported platforms
- Build System Compatibility: Updated build configuration to support Python 3.13's new features and requirements
- Cross-Platform Testing: Comprehensive testing on Linux x86_64, macOS (Intel & Apple Silicon), and Windows x64
- Future-Ready: Ensures Skyborn stays current with the latest Python ecosystem developments

🔧 Technical Improvements

Fortran Modernization:
- Replaced obsolete Fortran constructs with modern equivalents
- Improved array bounds checking and memory safety
- Enhanced numerical stability in edge cases
- Better integration with F2PY for Python bindings
Performance Optimizations:
- Vectorized mathematical operations in spherical harmonic calculations
- Optimized Legendre polynomial computations
- Reduced function call overhead in critical computation paths
- Enhanced caching strategies for frequently used calculations
Platform and Build Improvements:
- Extended Python Support: Now supports Python 3.9, 3.10, 3.11, 3.12, and 3.13
- Multi-Platform Wheels: Automated wheel building for Linux x86_64, macOS Intel/Apple Silicon, and Windows x64
- CI/CD Enhancements: Improved build matrix with comprehensive testing across all supported Python versions
- Future ARM64 Linux Preparation: Infrastructure ready for ARM64 Linux support when Python wheel ecosystem matures

Performance Benchmarks

Windspharm operation speedups compared to previous version:

Vorticity Calculation: ~25% faster execution time
Divergence Calculation: ~25% faster execution time
Helmholtz Decomposition: ~25% faster execution time
Streamfunction/Velocity Potential: ~25% faster execution time
Combined Operations: ~25% faster execution time

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 10 months ago

Skyborn - v0.3.11 (Aug 9, 2025)

🚀 Major Performance Improvements

Optimized Mann-Kendall Trend Analysis: Completely rewritten for significantly improved performance:
- Vectorized Implementation: True vectorization of Mann-Kendall S-score calculation using advanced NumPy operations
- 15-30x Performance Boost: Processing speeds increased from ~19 to ~1,853 grid points per second for large climate datasets
- Climate Data Optimized: Specifically tuned for typical climate data dimensions (40×192×288) with ~30-second processing time
- Memory Efficient: Intelligent chunking strategy with only ~25MB memory usage for full climate grids
- Batch Processing: Vectorized statistical calculations for clean data series, individual handling for series with missing values
- Enhanced Dask Support: Improved map_blocks implementation for distributed computing workflows
Method Parameter Updates: Replaced deprecated method="auto" with method="theilslopes" throughout the codebase for consistency

🔧 Technical Improvements

Simplified Import Structure: Removed conditional/backup import logic in favor of direct scipy.stats imports for improved maintainability
Code Quality Enhancements: Eliminated unused backup functions (_mk_score_backup, _theil_sen_backup) that were reducing test coverage
Consolidated Test Suite: Merged supplementary test files into main test suite for better organization and reduced maintenance overhead
Documentation Fixes: Corrected parameter names in API documentation examples (time_axis → axis)
Advanced Vectorization: New _vectorized_mk_score() function using upper triangular indices for O(n²) to O(1) complexity reduction
Smart Memory Management: Automatic chunk size estimation based on available memory and data dimensions
Robust Error Handling: Graceful handling of edge cases and problematic time series
Comprehensive Testing: Full test suite validation with 85% code coverage maintained

🎨 UI/UX Improvements

Dark Mode Compatibility: Fixed notification color gradients for better visibility in dark themes:
- Updated notification system to use deep blue to light blue gradient for improved contrast
- Enhanced table responsiveness styling for better dark mode support
Documentation Accuracy: Corrected function documentation to match actual codebase:
- Fixed plot module function listings to reflect actual available functions
- Removed non-existent functions from documentation (plot_field, plot_vector_field, plot_streamlines, plot_contour)
- Added proper documentation for actual functions (add_equal_axes, createFigure, curved_quiver, add_curved_quiverkey)
- Updated windspharm interface references for accurate Sphinx linking
- Standardized "XArray" to "Xarray" throughout documentation

📊 Performance Benchmarks

For typical climate data analysis scenarios:

Small datasets (50×20×30): 6.3x speedup (251 → 1,578 points/sec)
Medium datasets (100×30×40): 14.8x speedup (74 → 1,093 points/sec)
Large datasets (200×40×50): 31.3x speedup (19 → 595 points/sec)
Climate grids (40×192×288): ~30 seconds total processing time

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 10 months ago

Skyborn - v0.3.10 (Aug 8, 2025)

🚀 New Features

Advanced GridFill Module: Major expansion of grid filling capabilities for atmospheric data interpolation:
- New XArray Interface: Modern skyborn.gridfill.xarray module with automatic coordinate detection
- Comprehensive Tutorial: Interactive Jupyter notebook demonstrating wind field gap filling techniques
- Multiple Interpolation Methods: Basic Poisson, high-precision, zonal initialization, and relaxation parameter tuning
- Physical Validation: Component-wise vs direct speed filling comparison for vector wind fields
- Quality Assessment: Grid coverage validation and interpolation accuracy metrics
Rossby Wave Source Analysis: Added comprehensive Rossby wave source calculation capabilities to the windspharm module:
- New rossbywavesource() method in both standard and xarray interfaces
- Implements the Sardeshmukh & Hoskins (1988) formulation: S = -ζₐ∇·v - v_χ·∇ζₐ
- Support for custom truncation levels and Earth's angular velocity parameters
- CF-compliant metadata for xarray output with proper units and standard names

🔧 Improvements

Test File Consolidation: Merged duplicate gridfill test files for better maintainability
Better Grid Handling: Improved spherical harmonic truncation validation for different grid sizes
Documentation Updates: Enhanced gallery with new Rossby wave source visualization examples

📚 Documentation

New GridFill Tutorial: Complete interactive demonstration including:
- Advanced data interpolation techniques with real atmospheric wind data
- Missing data simulation and quality assessment methodologies
- Component-wise vs direct approach comparison for vector fields
- Publication-quality visualizations with integer colorbar formatting
- Performance analysis and best practices for atmospheric applications
New Tutorial Notebooks: Added comprehensive examples for:
- Rossby wave source analysis and visualization
- Grid filling techniques with atmospheric data
- Longitude coordinate system transformations
Enhanced Gallery: Updated with new visualization examples including:
- windspharm_rossby_wave_source_truncations.png showing truncation effects
- gridfill_missing_data_overview.png demonstrating gap filling scenarios
- gridfill_component_vs_direct_comparison.png showing physical constraint preservation
- Improved figure captions and mathematical formulations
- Better integration of notebook examples

🧪 Testing

Expanded Test Coverage: Added comprehensive tests for new Rossby wave source functionality
Grid Size Validation: Enhanced parameter validation for different grid resolutions
Cross-interface Testing: Verified consistency between standard and xarray interfaces

Technical Notes

All existing functionality remains backward compatible
Enhanced error handling for grid size limitations in spherical harmonic calculations
Improved memory efficiency for large-scale atmospheric analysis

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 10 months ago

Skyborn - v0.3.9 (Aug 5, 2025)

What's New

New Features

Enhanced Spherical Harmonics Module: Improved performance and stability for atmospheric data analysis
New Windspharm Submodule: Added comprehensive wind field analysis capabilities including:
- Vector wind analysis and spherical harmonic transforms
- Vorticity and divergence calculations
- Stream function and velocity potential computations
- Compatible with various grid types and coordinate systems
Optimized Build System: Streamlined compilation process for better cross-platform compatibility

🔧 Improvements

Better Error Handling: Enhanced error messages and debugging information
Performance Optimizations: Faster execution for large-scale atmospheric calculations
Code Quality: Improved type hints and documentation coverage

Bug Fixes

Fixed interpolation edge cases in atmospheric data processing
Fixed Dimension Handling in Regridding: Resolved dimension change issues in interp.regridding.py module that were causing inconsistent array
shapes during interpolation operations
Resolved compilation issues on various platforms
Improved numerical stability in spherical harmonic transforms

Documentation

Added comprehensive examples and tutorials
Enhanced API reference with mathematical formulations
Windspharm Module Documentation: Complete documentation and examples for wind field analysis functions
Improved installation and usage guides

Technical Details

Dependencies

Updated NumPy compatibility
Enhanced F2PY integration
Improved Fortran compiler support
Windspharm Dependencies: Added support for spherical harmonic wind analysis libraries

Platform Support

Linux x86_64 (manylinux2014)
macOS (Intel and Apple Silicon)
Windows x64

Installation

  pip install skyborn==0.3.9

🔗 Links

Qianye Su

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 11 months ago

Skyborn - v0.3.7 (Jul 10, 2025)

What's New in v0.3.7

New Features

Emergent Constraints Method: Added new emergent constraints analysis method for climate data analysis
Enhanced documentation with interactive particle effects entrance page

🔧 Improvements

Optimized documentation structure and user interface
Updated interactive documentation entry page with particle effects
Improved cross-platform compatibility
Enhanced code quality and test coverage

Documentation

New particle effects documentation entrance page
Updated API documentation
Improved code examples and usage guides
Enhanced Sphinx Book Theme with blue color scheme

Bug Fixes

Fixed minor issues and improved code quality
Resolved documentation build issues
Enhanced error handling

📦 Installation

pip install skyborn==0.3.7

🔗 Links

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 11 months ago

Skyborn - v0.3.6 (Jul 8, 2025)

Skyborn v0.3.6 - GRIB to NetCDF Conversion

New Features

GRIB to NetCDF Conversion

NEW: Convert GRIB files to NetCDF format using eccodes
NEW: Simple and batch conversion functions
NEW: Automatic compression and error handling

Documentation

NEW: Complete documentation site: https://qianyesu.github.io/Skyborn/
NEW: API reference and usage examples
NEW: Installation and quickstart guides

Improvements

Enhanced GitHub Actions workflows
Better test coverage and code quality
Modern package configuration
Support for Python 3.9-3.12

Climate Change - Climate Data Processing and Analysis - Fortran
Published by QianyeSu 11 months ago

Skyborn - v0.3.5 (June 12, 2025)

Updated the curved_quiver_plot.py file to enhance the implementation of the curved quiver key drawing function.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Skyborn - v0.3.4 (June 11, 2025)

Skyborn v0.3.4

🆕 New Features

Added Interpolation Module: Supports hybrid-σ coordinate and multidimensional data interpolation
- interp_hybrid_to_pressure() - Interpolate from hybrid coordinates to pressure levels
- interp_sigma_to_hybrid() - Interpolate from σ-coordinates to hybrid coordinates
- interp_multidim() - Interpolation for multidimensional data

🔧 Improvements

Removed deprecated io.py file
Code cleanup and optimizations

📦 Version Update

Version number: 0.3.3 → 0.3.4

Release Date: 2025-06-11

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Skyborn - 0.3.3

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Skyborn - 0.3.2

This is a minor release.

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Skyborn - 0.3.1

✨ New Features

This update primarily introduces two significant new features:

Enhanced Visualization: Curved Wind Vector Field Plotting 🌪️
- Added the capability to plot wind vector fields that account for airflow curvature.
- Compared to traditional straight-arrow vector plots, this new method provides a more realistic representation of wind patterns and airflow trajectories in the actual atmosphere, especially useful for analyzing complex weather systems like vortices and jet streams.
- (Optional: If you want to mention specific functions or modules used, you can add that here, e.g., "This is primarily implemented via the plot_curved_vectors() function.")
Causality Analysis Extension: Integrated Liang Information Flow (Liang Causality) 📊
- Integrated the Liang information flow/causality analysis method.
- This method helps quantify and identify directed causal relationships and the rate of information transfer between different time-series variables, offering a new tool for mechanistic analysis in atmospheric science research.
- (Optional: You can briefly describe its main application scenarios or advantages, e.g., "Suitable for analyzing interactions and influence pathways between different meteorological elements.")

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Skyborn - 0.1.0

skyborn-0.1.0.tar.gz

Climate Change - Climate Data Processing and Analysis - Fortran
Published by SQYQianYe about 1 year ago

Recent Releases of Skyborn

Skyborn - Skyborn 0.4.0

New Features

Improvements

Cleanup

Skyborn - Skyborn 0.3.22

Improvements

Bug Fixes

Skyborn - v0.3.21 (Apr 30, 2026)

Skyborn - v0.3.20 (Apr 20, 2026)

Skyborn - v0.3.19 (Apr 7, 2026)

Skyborn - v0.3.18 (Apr 2, 2026)

Skyborn - v0.3.17 (Mar 30, 2026)

Skyborn - v0.3.16 (Dec 28, 2025)

What's Changed

🐛 Bug Fixes

📦 Dependencies

Skyborn - v0.3.15 (Oct 29, 2025)

Skyborn - v0.3.14 (Sept 9, 2025)

Skyborn - v0.3.13 (Aug 31, 2025)

Skyborn - v0.3.12 post1 (Aug 21, 2025)

v0.3.12.post1 - Fix spharm module wheel packaging

Bug Fixes

Changes

setup.py

meson.build

GitHub Actions (.github/workflows/build-wheels.yml)

Validation

Installation

Skyborn - v0.3.12 (Aug 19, 2025)

Skyborn - v0.3.11 (Aug 9, 2025)

Skyborn - v0.3.10 (Aug 8, 2025)

Skyborn - v0.3.9 (Aug 5, 2025)

Qianye Su

Skyborn - v0.3.7 (Jul 10, 2025)

What's New in v0.3.7

New Features

🔧 Improvements

Documentation

Bug Fixes

📦 Installation

🔗 Links

Skyborn - v0.3.6 (Jul 8, 2025)

Skyborn v0.3.6 - GRIB to NetCDF Conversion

New Features

GRIB to NetCDF Conversion

Documentation

Improvements

Skyborn - v0.3.5 (June 12, 2025)

Skyborn - v0.3.4 (June 11, 2025)

Skyborn v0.3.4

Skyborn - 0.3.3

Skyborn - 0.3.2

Skyborn - 0.3.1

✨ New Features

Skyborn - 0.1.0