Work Description

Date: 13 May 2025
Dataset Title: Dataset for "Lidar-based observations of pollen above a mixed hardwood forest in the United States"

Dataset Contact: Allison Steiner ([email protected])

Dataset Creators:
Name: Allison Steiner
Email: [email protected]
Institution: University of Michigan Department of Climate and Space Sciences and Engineering
ORCID: https://orcid.org/0000-0002-3823-1512

Name: Matthew Wozniak
Email: [email protected]
Institution: University of Michigan Department of Climate and Space Sciences and Engineering
ORCID: https://orcid.org/0000-0003-4434-2064

Name: Eric Kort
Email: [email protected]
Institution: University of Michigan Department of Climate and Space Sciences and Engineering
ORCID: https://orcid.org/0000-0003-4940-7541

Name: Phil DeCola
Email: [email protected]
ORCID: https://orcid.org/0000-0003-0355-4917

Funding: NSF Grant No. AGS-0952650

Key Points:
- Dataset includes 74 days in 2015 of time-resolved MiniMPL lidar data at the UMBS Prophet Tower site during the spring to summer pollination season.

Research Overview:
Airborne pollen can impact human health by causing seasonal allergies and contribute to the total amount of particulate matter in the atmosphere. Current observations of pollen are limited in both space and time, making it is difficult to accurately forecast how pollen is released into the environment. Lidar is a ground-based remote sensing technique that can identify particles in the atmosphere, and depolarized light can identify irregularly shaped particles like pollen. We deployed a ground-based lidar with depolarization at a forested site in northern Michigan during the spring tree pollination season to understand the timing and contribution of pollen to the total amount of particulate matter in the atmosphere. We identify nine pollen events at the forested site that lead to high particulate matter in the atmosphere and find that light-scattering by pollen can account for 25-97% of the aerosol optical depth, or the reduction in light reaching the surface of the Earth. These observations can improve our understanding of how and when pollen is emitted to the atmosphere and its impact on human health and climate.

Instrument and/or Software specifications:
The MiniMPL is a smaller and lower power version of the MicroPulse Lidar MPL that are deployed in NASA’s MPLNet (https://mplnet.gsfc.nasa.gov/). The MiniMPL uses a Nd:YAG laser at 532 nm, pulsing at 2500 Hz with 3.5-4 microJ energy. The vertical range can be as high as 15 km depending on atmospheric scattering, with 10 km range more typical and vertical resolution options of 15, 30 or 75 meters. Co- and cross-polarized measurements provide information on the scattering behavior of observed atmospheric aerosol.

Files contained here:
Data for the field campaign are included with files labeled by day (e.g., UMBS_MINIMPL_2016mmdd.nc) with "mm" representing the month and "dd" representing the day. All output are in netcdf format, which includes metadata describing all information in the daily files. 74 days were captured during the campaign, including three contiguous periods from April 16 – May 14, May 26 – July 1, and July 5 – July 12.
Processed lidar data using the MiniMPL raw event count, which is calibrated and normalized to calculate the normalized relative backscatter (NRB) as a function of height (Ware et al., 2016).

Related publication(s):
Steiner, A.L., et al. Lidar-based observations of pollen above a mixed hardwood forest in the United States. Submitted to JGR-Atmospheres, May 2025.

Use and Access:
This data set is made available under a Creative Commons Public Domain license (CC0 1.0).

To Cite Data:
Steiner, Allison L., Matthew Wozniak, Eric Kort, and Phil DeCola (2025). Dataset for Lidar-based observations of pollen above a mixed hardwood forest in the United States. University of Michigan - Deep Blue.