East River Winter Wind Storms Characteristics and the Relationship to Seasonal Sublimation and Water Resources.

Overview

Welcome to the repository for project focused on studying strong wind events within the East River valley, how often they occur, and their influence on sublimation and water resources within the river basin. This project is ongoing so check back for periodic updates!

Repository Structure

The repository is organized as follows:

repository_root/ ── 01_data/ └── outputs/ # ALL produced .nc / .csv go here ├── 02_notebooks/ │ ├── 01_data_preparation/ # cleaning, resampling, QC -> produce core datasets │ ├── 02_event_analysis/ # identify events, event-level processing │ ├── 03_precipitation_and_ceilometer_classification/ # merge/aggregate datasets across campaigns/seasons │ ├── 04_blowing_snow_sublimation_events/ # modeling / derived products / event modeling │ ├── 05_sublimation_event_classification/ # plotting, figures, final products

Project workflow & README

This repository contains the notebooks and data outputs used to process, analyze, and model hydrometeorological observations from several campaigns (SAIL, SPLASH, SOS, etc.). Notebooks are organized by execution order (00 → 05). All produced data files (.nc, .csv) are stored in 01_data/.

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How to re-run the workflow

1. Ensure environment dependencies are installed (see environment_clean.yml if present).
2. Run notebooks in numeric order, starting at 02_notebooks/01_data_preparation/ and finishing with notebooks/05_sublimation_event_classification/.
3. Reproduce figures using 03_results/.
4. All notebooks write outputs to 01_data/. Use relative paths (e.g. ../01_data/).

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Top-level folders

• 02_notebooks/01_data_preparation/ — cleaning, resampling, and QC; produces core .nc/.csv.
• 02_notebooks/02_event_analysis/ — event identification and event-level outputs.
• 02_notebooks/03_precipitation_and_ceilometer_classification/ — merged datasets and precipitation products along with ceilometer classifications.
• 02_notebooks/04_blowing_snow_sublimation_events/ — sublimation calculations and focus on blowing snow.
• 02_notebooks/05_sublimation_event_classification/ — sublimation event classifications.
• 01_data/ — all resulting NetCDF/CSV outputs derived from raw data.
• 03_results/ — reproduce figures for the manuscript.

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Files / notebooks (execution order) — short descriptions

Below are the proposed notebook names (with suggested numbering), what they produce (files in data/outputs/), and a short dataset description. Run in the numeric order shown.

01 — Data preparation

• 01-01_clean_and_resample_SOS_data.ipynb
  Produces: sos_ds_5min_storage, sos_ds_30M_storage, sos_ds_1H_storage, sos_ds_3H_storage, sos_ds_6H_storage, sos_ds_12H_storage, sos_ds_1day_storage, sos_1H_max_wspd_ds_max_wspd_storage
  Description: core cleaning/resampling for SOS station network; produces multiple temporally aggregated storage files.

• 01-02_clean_SPLASH_laser_disdrometer.ipynb
  Produces: laser_disdrometer_gothic_*, wy22_resampled_5min_SPLASH_kp_ldis, wy23_resampled_5min_SPLASH_kp_ldis, ldquants_*
  Description: QC and resample SPLASH laser disdrometer particle spectra to standard time resolutions.

• 01-03_clean_and_correct_SPLASH_ceilometer.ipynb
  Produces: splash_kp_ceilometer
  Description: QA/QC ceilometer outputs and format for downstream precipitation/blowing-snow classification.

• 01-04_tropoe_dataset.ipynb
  Produces: windy_days_dl_winds_700m_and_kp_10m_winds (used later)
  Description: QC lidar profiles and produce daylists of windy periods for event analysis.

• 01-05_check_turbulent_flux_calcs.ipynb
  Produces: None Description: checks calculated turbulent fluxes from other data sources.

• 01-06_explore_east_river_valley_wind_events.ipynb
  Produces: sail_* (exploratory outputs)
  Description: exploratory notebook for East River valley wind events — used to seed event notebooks.

• 01-07_clean_SAIL_data.ipynb
  Produces: sail_* (exploratory outputs) Description: downloads and saves SAIL data used later in the analysis.

02 — Precipitation & ceilometer classification

• 02-01_all_things_precipitation.ipynb (04_all_things_precipitation)
  Produces: w22_all_precip_30min, w23_all_precip_30min, pluvio2_2021*, pluvio2_2022*, merged precipitation product sets.
  Description: merges disdrometer, pluvio, and gts precipitation into consolidated 30-min products.

• 02-02_ceilometer_blowing_snow_classification.ipynb (07_ceilometer_blowing_snow)
  Produces: ceilometer_precipitation_classification_w22, ceilometer_precipitation_classification_w23, ceilometer_precipitation_classification_splash_w22, ceilometer_precipitation_classification_splash_w23
  Description: classify ceilometer returns to label precipitation vs blowing snow at 1H/30min scales.

• 02-03_wind_precip_blowing_snow.ipynb (08_wind_precipitation_blowing_snow)
  Produces: precipitation_rate_gts_w22/w23, corrected_ldis_precipitation_rate_kps_w22/w23, sail_ld_gothic_2022_precip_binary, sail_ld_gothic_2023_precip_binary, and other precip masks.
  Description: correct/distribute precipitation rates across instruments and produce binary precipitation masks.

03 — Event-level analysis (winter events & SPLASH/SOIL)

• 03-01_kp_winter_22_23_wind_events.ipynb (02a)
  Produces: sos_daily_h2o_flux_cleaned, event-level KP wind summaries.
  Description: detect and summarize KP wind events in winter 2022–23.

• 03-02_SAIL_wind_events_21_23.ipynb (02b)
  Produces: sail_ds_1H_met_2022, sail_ds_1H_met_2023, laser_disdrometer_* seasonal slices, tropoe_20221201_20230401, met_20211001_20220930, met_20221001_20230930
  Description: identify SAIL campaign wind events & generate event-specific datasets.

• 03-03_SPLASH_sublimation_21_23.ipynb (02c)
  Produces: splash_ASFS_KP_all_storage, splash_ASFS_AP_all_storage, w22_*/w23_*_qc_* files (1H & 30min)
  Description: process SPLASH datasets to quantify sublimation-relevant fluxes.

04 — Blowing-snow / sublimation event analysis

• 04-01_blowing_snow_kettle_ponds.ipynb (09_blowing_snow_and_sublimation_kettle_ponds)
  Produces: sos_1H_max_wspd_ds_max_wspd_storage, sublimation_met_timeseries_30T, and event lists.
  Description: event-level blowing-snow analysis for kettle pond eddy covariance sites.

• 04-02_S3_precip_sublimation_direction.ipynb (10_S3_precip_sublimation_direction)
  Produces: directional precipitation/sublimation summaries used for S3 analyses.
  Description: assess precipitation vs sublimation directionality for event classification.

• 04-03_surface_and_upper_air_obs.ipynb (12_surface_and_upper_air_obs)
  Produces: radiosonde and surface merged products e.g., wy22_SAIL_gts_radiosonde, wy23_SAIL_gts_radiosonde, sail_ds_1H_met_kp_*
  Description: create surface & upper-air collocations for event characterization.

• 04-04_sublimation_frequencies.ipynb (14_sublimation_frequencies)
  Produces: event-frequency outputs and inputs for modeling.
  Description: compute how often certain sublimation-type events occur by season/site.

05 — Characteristic events, long/small event classification, and modeling

• 05-01_characteristic_event_meteorology.ipynb (15_characteristic_event_meteorology)
  Produces: CSVs summarizing event-level meteorology (peak winds, precipitation totals, fluxes).
  Description: extract event-level attributes for modeling.

• 05-02_all_things_sublimation.ipynb (16_all_things_sublimation)
  Produces: w22_winter_sublimation, w23_winter_sublimation, w22_long_evts, w23_long_evts, w22_spiky_evts, w23_spiky_evts, latent-heat flux summaries, precipitation masks.
  Description: computes season-scale sublimation budgets and event partitions.

• 05-03_large_sublimation_event_profiles.ipynb (17_large_sublimation_event_profiles)
  Produces: gucdlprofwstats4newsM1.*, radsys_ckp_dataset, and other large-event profiles.
  Description: collates vertical profile statistics for large sublimation events.

• 05-04_doppler_lidar_vertical_velocity.ipynb (18_doppler_lidar_vertical_velocity)
  Produces: lidar vertical velocity summaries for long/spiky events.
  Description: derive valley-scale vertical velocity fields for event types.

• 05-05_sublimation_event_modeling.ipynb (19_sublimation_event_modeling)
  Produces: model outputs that combine reanalysis + local observations, e.g., event-based sublimation estimates.
  Description: run models (or scripts) to turn observed event attributes into sublimation mass-loss estimates.

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Data outputs (high-level descriptions)

In 01_data/ you should expect:

• SOS network storage files (sos_ds_*_storage) — cleaned SOS station data aggregated at multiple temporal resolutions (5min, 30min, 1H, 3H, 6H, 12H, daily).
• SPLASH disdrometer files (laser_disdrometer*, wy*_resampled_5min_*, ldquants_*) — particle spectra and derived rain/snow metrics at 5min resolution.
• Precipitation merges (w22_all_precip_30min, w23_all_precip_30min, pluvio2_*) — merged multi-instrument precipitation products.
• Ceilometer classifications (ceilometer_precipitation_classification_*) — labels for precipitation vs blowing-snow.
• Event lists and summaries (e.g., w22_long_evts, w23_spiky_evts, etc.) — lists of event start/stop times and event metrics.
• Sublimation budgets (w22_winter_sublimation, w23_winter_sublimation) — seasonal sublimation total estimates.
• Model outputs — derived model predictions / scenario outputs used by 19_sublimation_event_modeling.

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Notes & recommendations

• Use the new numeric prefix when renaming; it makes mandatory execution order obvious.
• Keep all produced .nc/.csv in data/outputs/. If disk space becomes an issue, consider data/outputs/processed/ vs data/outputs/final/.
• If a notebook both produces and uses datasets locally, keep it in the stage where the primary function is (e.g., cleaning vs analysis).

License

This repository is open-source and available under the MIT License. Please review the license for terms and conditions of use.

Contact

If you have any questions or need further information, feel free to contact me at dlhogan@uw.edu.