DOI: 10.5061/dryad.zcrjdfnrr
title: Integrated vertical profiles for 16 coastal NEXRAD weather surveillance radars from 2014 to 2023

description: This dataset quantifies offshore and adjacent terrestrial migration of
 landbirds along the western North Atlantic and Gulf of Mexico coasts from
 2014–2023. Offshore flights of migratory landbirds are common but
 difficult to quantify due to lack of offshore monitoring. Offshore wind
 development is expanding rapidly and may overlap with migration corridors.
 Understanding the timing, locations, and numbers of offshore birds can
 identify high-risk periods and areas for collision mitigation. We used 16
 coastal weather surveillance radars in the western North Atlantic and Gulf
 of Mexico to evaluate differences in passage, altitude, and timing of
 migration between adjacent terrestrial and offshore habitats for spring
 and fall from 2014 to 2023. We used machine learning methods to predict
 unobserved low altitude densities that the radar beam overshoots at
 increasing distances from the radar. Migration traffic varied
 geographically and seasonally, with offshore migration traffic being lower
 in spring than fall and lower than terrestrial migration year-round.
 Offshore migratory activity below 300m (common rotor-swept zones) showed
 shorter durations and fewer peak nights than terrestrial migration.
 Offshore flight altitudes were 8-14% lower than over land, and the
 propensity for offshore flights was higher in fall, especially near
 coastlines perpendicular to migratory directions. We identify regional
 patterns in offshore migration to inform wind energy siting decisions and
 operation. Migration of landbirds in the offshore environment at rotor
 swept zones is common, and increasing wind energy operations will likely
 increase interaction between birds and rotors. The limited number of peak
 nights and shorter migration windows offshore increases opportunities for
 dynamic conservation. Curtailment targeting high-risk regions, seasons and
 nights, will reduce operational downtime while protecting birds. Fall
 migration and areas downstream of coastlines perpendicular to migratory
 direction have a higher propensity for offshore migration, suggesting that
 spatial and temporal variation in migration intensity should be considered
 when balancing collisions risks and operational costs. 
description: This data is vertically integrated vertical profiles of 16
 coastal NEXRAD stations, which was filtered to isolate biological activity
 while filtering out precipitation and sea clutter noise. To compile this
 dataset, we analyzed bird migration data from 16 coastal WSR-88D (NEXRAD)
 radar stations along the Atlantic and Gulf coasts of the U.S. between 2014
 and 2023 between the spring (Mar 1–Jun 15) and fall (Aug 1–Nov 15)
 migration seasons. We downloaded Level II polar volume data at 30-minute
 intervals between civil sunset and sunrise for each radar from the NEXRAD
 archives (Original polar volume files are from the NEXRAD Level II archive
 data which are openly available from the Registry of Open Data on AWS Data
 Exchange (https://registry.opendata.aws/noaanexrad). <br> Using the R packages bioRad and vol2birdR, we derived vertical profiles of bird density from reflectivity data, excluding precipitation via a correlation threshold (ρHV &gt; 0.95). Each radar scan was partitioned into terrestrial and offshore profiles using custom spatial masks based on high-resolution coastline data, excluding a 10 km coastal buffer. We calculated three types of vertical profiles using 100 m bins from 0 to 5000 m a.s.l.: Standard (5–35 km range) Terrestrial (5–75 km) Offshore (5–75 km) A post hoc precipitation filter and manual review removed remaining precipitation and sea clutter, excluding 435 radar-date combinations. Because radar beams overshoot lower altitudes at greater ranges offshore, we developed an extrapolation model using xgboost to estimate densities in unsampled low-altitude bins (0-100 to 0-400 m) based on standard land-based profiles. Profiles were normalized by vertically integrated density and cube-root transformed to reduce skew. Four models were trained, each predicting an increasing number of lower bins, and performance was validated against radars with complete low-altitude coverage. We calculated height-integrated bird density and flight altitudes using bioRad’s integrate_profile(), which converts densities into migration traffic rates (birds km^-1<sup>h</sup>-1^). Temporal integration produced nightly and seasonal passage estimates. This resulted in the attached file "Integrated_radar_profiles.csv" which was used in the analysis.
description: # Integrated vertical profiles for 16 coastal NEXRAD weather surveillance
 radars from 2014 to 2023 Dataset DOI:
 [10.5061/dryad.zcrjdfnrr](10.5061/dryad.zcrjdfnrr) #### Description of the
 data and file structure #### Reproducibility Radar_analysis.Rmd is the
 attached code which reproduces the analysis from the file:
 Integrated_radar_profiles.csv, which is the only input file required to
 knit the analysis and reproduce the analysis in the manuscript. ### File
 locations & working directory The Rmd is set up to use **relative
 paths**, so you don’t have to call `setwd()`. * Place `Radar_analysis.Rmd`
 and `Integrated_radar_profiles.csv` in the **same folder** (or put the CSV
 in a `data/` subfolder) * The Rmd reads the CSV via a path constructed
 with `here::here()` ### Files and variables #### File:
 Integrated_radar_profiles.csv ##### Variables The file:
 Integrated_radar_profiles.csv contains the following columns: * radar: 4
 letter abbreviation of each radar station * datetime: POSIXct date of each
 profile in UTC * vid: Vertically Integrated Density in individuals/km^2.
 vid is a surface density, whereas dens in vp objects is a volume density.
 * vir: Vertically Integrated Reflectivity in cm^2/km^2 * mtr: Migration
 Traffic Rate in individuals/km/h * rtr: Reflectivity Traffic Rate in
 cm^2/km/h * mt: Migration Traffic in individuals/km, cumulated from the
 start of the time series up to datetime * rt: Reflectivity Traffic in
 cm^2/km, cumulated from the start of the time series up to datetime * ff:
 Horizontal ground speed in m/s * dd: Direction of the horizontal ground
 speed in degrees * u: Ground speed component west to east in m/s * v:
 Ground speed component south to north in m/s * height: Mean flight height
 (height weighted by eta) in m above sea level * Type: Over_land or
 Offshore * year: year of the data * NOY: night of year #### File:
 Radar_analysis.Rmd **Description:** This is the accompanying analysis to
 the manuscript ## Code/software (required r packages) library(dplyr) #
 data frame manipulation library(lme4) # models library(glmmTMB) # models
 library(readr) # reading in csvs library(lubridate) # date/time
 conversions library(tidyr) # data frame manipulation library(broom) # for
 tidy tibbles library(bioRad) # standardized methods for extracting and
 reporting biological signals from weather radars. ## Access information
 Other publicly accessible locations of the data: * NEXRAD Level II archive
 data, available from the Registry of Open Data on AWS Data Exchange
 ([https://registry.opendata.aws/noaa-nexrad](https://registry.opendata.aws/noaa-nexrad); Ansari et al., 2018). Data was derived from the following sources: * NEXRAD Level II archive data, available from the Registry of Open Data on AWS Data Exchange ([https://registry.opendata.aws/noaa-nexrad](https://registry.opendata.aws/noaa-nexrad); Ansari et al., 2018).