maritime_export_speeds
Export raw speed samples with full metadata for statistical analysis. Supports filtering by voyage, date, location, and wind conditions for flexible grouping and testing.
Instructions
Export raw speed samples for downstream statistical analysis.
Returns individual speed records with full metadata (voyage_id, year, month, direction, nationality, ship_name, wind data) so models can perform arbitrary grouping and statistical tests.
Unlike maritime_aggregate_track_speeds which groups and summarises, this tool returns the underlying data. Essential for analyses requiring non-contiguous year comparisons (e.g. ENSO phase classification, volcanic event detection, arbitrary epoch testing).
Args: lat_min/lat_max/lon_min/lon_max: Bounding box nationality: Filter by nationality code year_start/year_end: Filter by year range direction: Filter by "eastbound" or "westbound" month_start/month_end: Month filter (supports wrap-around) aggregate_by: "voyage" (one mean speed per voyage, recommended for statistical independence) or "observation" (each daily speed with position and wind data) min_speed_km_day: Minimum speed filter (default: 5.0) max_speed_km_day: Maximum speed filter (default: 400.0) wind_force_min/wind_force_max: Beaufort force bounds max_results: Records per page (default: 500). Use with offset for pagination through large result sets. offset: Skip this many records (default: 0). Use next_offset from previous response to get the next page. fields: Comma-separated list of fields to include in output. Observation fields: voyage_id, date, year, month, day, direction, speed_km_day, nationality, ship_name, lat, lon, wind_force, wind_direction. Voyage fields: voyage_id, year, month, direction, speed_km_day, nationality, ship_name, n_observations. Omit for all fields. output_mode: Response format - "json" (default), "text", or "csv". Use "csv" for compact tabular output (~3-4x fewer tokens than JSON). CSV includes a # metadata header.
Returns: JSON, text, or CSV with speed samples and metadata
Tips for LLMs: - Use output_mode="csv" to reduce token usage by ~3-4x - Combine fields="voyage_id,year,speed_km_day" with csv for minimal token footprint (~10 tokens/row vs ~50 in JSON) - Use aggregate_by="observation" to get individual dated records with full date (ISO YYYY-MM-DD), lat, lon, wind data — essential for lunar phase, tidal, or day-level temporal analyses - Use aggregate_by="voyage" for statistically independent samples - Each observation-level sample includes date, year, month, day for precise temporal correlation (e.g. lunar phase, tidal cycles) - Combine with known ENSO chronology to classify years and compute El Nino vs La Nina vs Neutral speed distributions - For tidal analysis: export observations in narrow channels (e.g. Mozambique Channel lat -26/-12, lon 35/45), use date field to compute lunar phase, correlate with speed - For Laki 1783: compare 1782-1784 samples vs surrounding years - Paginate large results: check has_more and use next_offset - Default page size is 500 records; adjust max_results as needed
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lat_min | No | ||
| lat_max | No | ||
| lon_min | No | ||
| lon_max | No | ||
| nationality | No | ||
| year_start | No | ||
| year_end | No | ||
| direction | No | ||
| month_start | No | ||
| month_end | No | ||
| aggregate_by | No | voyage | |
| min_speed_km_day | No | ||
| max_speed_km_day | No | ||
| wind_force_min | No | ||
| wind_force_max | No | ||
| max_results | No | ||
| offset | No | ||
| fields | No | ||
| output_mode | No | json |