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CROCUS Forward Scatter Disdrometer Data at Argonne National Laboratory Prairie Site

The Vaisala FD70 is a multi-parameter present weather and visibility sensor designed to measure precipitation type, intensity, and visibility with high accuracy in diverse environmental conditions. It uses a combination of forward-scatter measurement and optical disdrometer technologies to detect drop size, fall speeds, and optical properties, enabling the classification of various precipitation types such as rain, snow, sleet, and freezing rain along is visibility estimates. The FD70 provides quantitative estimates of liquid-equivalent precipitation rate and meteorological optical range (MOR), supporting applications in meteorological research, aviation, and road weather monitoring. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20 acre prairie site at Argonne National Lab, located in Lemont, IL. Data is available in netcdf format. Each file contains one second interval data, for approximately 24 hrs each day. File naming convention includes the project (CROCUS), location (ATMOS), instrument name, data level (raw, a1), and date (year, month, day).

54 ENVIRONMENTAL SCIENCES↗

CROCUS Low Cost All-in-One Weather Station AMB-004 Data Argonne National Laboratory Prairie Site

The Ambient Weather WS-2902D (AMB) is a low cost weather station that has become very useful for filling data gaps in harder to deploy locations. These low cost weather stations collect 13 second data, which is averaged to a five minute data output available to users through an Application Programming Interface (API) key. The data files contain measurements for precipitation, temperature, wind chill/heat index, relative humidity, dew point, UV index, solar radiation, wind speed, wind direction, wind gust, and with an external particulate matter 2.5 (PM 2.5) sensor. Having all of these measurements in one condense system allows for fast deploying and dense network capabilities. Three of the AMB weather stations were deployed at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The instruments are denoted by their three digit identifier (CMS-AMB-xxx) format. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (CMS-AMB-004), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or ACT-DOE.

EARTH SCIENCE > ATMOSPHERE > AEROSOLS > PARTICULAT↗

CROCUS Low Cost All-in-One Weather Station AMB-001 Data Argonne National Laboratory Prairie Site

The Ambient Weather WS-2902D (AMB) is a low cost weather station that has become very useful for filling data gaps in harder to deploy locations. These low cost weather stations collect 13 second data, which is averaged to a five minute data output available to users through an API key. The data files contain measurements for precipitation, temperature, wind chill/heat index, relative humidity, dew point, UV index, solar radiation, wind speed, wind direction, wind gust, and with an external particulate matter 2.5 (PM 2.5) sensor. Having all of these measurements in one condense system allows for fast deploying and dense network capabilities. Three of the AMB weather stations were deployed at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The instruments are denoted by their three digit identifier (CMS-AMB-xxx) format. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (CMS-AMB-001), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or ACT-DOE.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Optical All Precipitation Gauge Data at Argonne National Laboratory Prairie Site

The APG (Optical Scientific Inc. All-Precipitation Gauge 815-DS) dataset contains one-minute measurements of precipitation rate, precipitation accumulation, air temperature, and present weather detection, both in 4680 format and decoded. Data were collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (apg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

54 ENVIRONMENTAL SCIENCES↗

NGEE Arctic Rainfall Simulator Validation Data from Los Alamos National Laboratory, New Mexico, Summer 2022

Experiments evaluating the uniformity and intensity of rainfall produced by the NGEE Arctic Rainfall Simulator (NARS) were conducted at Los Alamos National Laboratory, New Mexico, over summer 2022. Petri dishes were placed in a grid within the NARS plot. Simulated rainfall was collected in each petri dish and the intensity and uniformity of the simulator was subsequently calculated. This data package contains two .csv files, one that summarizes the rainfall intensity and uniformity for each experiment, the other that contains individual petri dish water volume and intensity for each plot location and experiment. The Python scripts to control NARS are also included. The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Rain intensity control and data collection are automated using a Raspberry Pi microcomputer. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Environmental monitoring data from the 2022-2023 field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains sensor data from programmed loggers as well as handheld moisture probes, including weather data, air and soil temperature, and soil volumetric water content. Data files and data dictionary(ies) are uploaded as .csv files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought. This environmental data was collected to provide context for the fungal community data and Pinus ponderosa physiological data.

54 ENVIRONMENTAL SCIENCES↗

Micro Rain Radar Pro Data at the Argonne Testbed for Multiscale Observational Science obtained during the CROCUS Urban Integrated Field Laboratory

The Micro Rain Radar Pro (MRR-PRO) is a vertically pointing Ka-band Doppler radar designed to capture the fine-scale structure and evolution of precipitation. By recording the full Doppler spectrum at high temporal and spatial resolution, the MRR-PRO provides insight into both hydrometeor fall velocities and precipitation microphysics. From these spectra, key moments—reflectivity, mean Doppler velocity, spectral width, and rainfall rate—are derived and stored alongside the raw spectral data in CF/Radial 1.4-compliant files. Deployed at the Argonne Testbed for Multiscale Observational Studies (ATMOS) since November 2024, the MRR-PRO delivers vertical profiles at 70 m range resolution extending up to 4.5 km above ground level. These observations enable detailed analyses of precipitation type, intensity, and vertical structure, supporting process-level studies of cloud and precipitation dynamics in diverse weather regimes.

54 ENVIRONMENTAL SCIENCES↗

Duke Forest FACE (FACTS-I): Meteorological and Soil Data

This dataset, collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment, includes variables describing the meteorological conditions above canopy, within canopy, and soil depending on the variable. The Duke FACE experiment was located in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. The CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plot 1-6 with a common protocol of N-fertilization in 2005. N-fertilization continued until 2012. The data range varied by sensor availability. A summary of information about variable name and data range can be found in the ‘FileDescription_[variable_name].txt’ files.

54 ENVIRONMENTAL SCIENCES↗

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Meteorological, reference evapotranspiration and estimated transpiration data, July 2020-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Tipping Bucket Rain Gauge Data at Argonne National Laboratory Prairie Site

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from both the Nova-Lynx 12 inch TBRG and the Met One 8-inch TBRG. The dataset contains one minute measurements for precipitation accumulation measured in that timeframe from both instruments. Each TBRG was equipped with heaters for all-season measurements. These data are helpful for identifying periods of drought, potential flooding, and general input for water budgets. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS project. Data were collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-min Precipitation Accumulation↗

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗

Scripts and raw/processed precipitation NRCS network data, Upper Colorado, 2008-2017

This data package consists of scripts and data that were used to generate all the results and figures for Mital et al., 2020 (https://doi.org/10.3389/frwa.2020.00020). The purpose of the study was to develop a new algorithm to impute (or gap-fill) missing daily precipitation data. Study area was the Upper Colorado Water Resources Region (UCWRR), over a time period of 2008-2017. In terms of data, the package consists of raw precipitation measurements from Natural Resources Conservation Service (NRCS) network. These raw measurements are compiled into a single csv file (NRCS_dates_2008_2017.csv). The corresponding metadata are compiled in Metadata_processed.csv. The package also consists of outputs generated during Baseline and Sequential imputation runs as documented in Mital et al., 2020. Scripts used to generate all the results and figures for Mital et al., 2020 are also uploaded. A readme file documenting the layout of the data archive is also uploaded, and a KML file shows the geographic range for the data.

54 ENVIRONMENTAL SCIENCES↗

Downscaled precipitation and mean air temperature datasets; East-Taylor subbasin; 2008-2019; daily temporal resolution; 400 m spatial resolution

This dataset provides gridded meteorological forcing data (specifically, daily precipitation and daily mean air temperature). The dataset has been generated by downscaling the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset from a spatial resolution of 800 m to 400 m. The time period is 2008-2019, and the mapped area is East Taylor subbasin in Upper Colorado. The data are in the form of NetCDF files, arranged by year. Compared to the PRISM dataset, the dates of the downscaled dataset are shifted backwards by one (e.g., downscaled data for May 25 corresponds to PRISM data for May 26). This temporal shifting makes the meteorological forcing correspond more closely to the prescribed date. The NetCDF format is a standard raster format that can be read using any Geographic Information System (GIS) software; plenty of modules exist in popular scripting languages (such as Python, R and Matlab) that can also be used to read NetCDF files.East_Taylor_Tavg_PRISM400 corresponds to mean air temperature.East_Taylor_Precip_PRISM400.zip corresponds to precipitation.The proprietary PRISM data (800 m resolution) were purchased with funding from the Watershed Function Scientific Focus Area supported by U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award no. DE-AC02-05CH11231.Dataset update on March 9, 2022:Uploaded new data files that are identical to the earlier files but are now in the NetCDF format, arranged by year. Earlier, the files were in the GeoTiff format, arranged by date.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Weather Data at Argonne National Laboratory Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a prairie field site at Argonne National Laboratory in Lemont, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (atmos), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗

CROCUS Weather Data at University of Illinois - Chicago Tower

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the University of Illinois in Chicago, Illinois, on the meteorological tower near the greenhouse on campus. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. File naming convention includes the project (CROCUS), location (UIC), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at Argonne National Laboratory During Urban Flooding Campaign

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Argonne Testbed for Multiscale Observational Science (ATMOS) site. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at ATMOS, a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-atmos), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-min Precipitation Accumulation↗

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at NEIU Carruthers Center for Inner City Studies (CCICS)

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Northeastern Illinois University (NEIU) Carruthers Center for Inner City Studies (CCICS) campus. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at the CCICS building parking lot, located in the south side of Chicago, IL. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-ccics), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-minute Precipitation Accumulation↗