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The Extraordinary March 2022 East Antarctica “Heat” Wave. Part I: Observations and Meteorological Drivers

Abstract Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30°–40°C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of −9.4°C on 18 March at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’s meteorological drivers, impacts, and historical climate context. Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline, which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm-air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heat wave, an area of 3.3 million km 2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere. Significance Statement In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.

Wille, Jonathan D.↗

Surface Meteorological Station - Forks, WA (FKS) - Reviewed Data

A variety of instruments are used to measure various quantities related to meteorology, precipitation, and radiation near the Earth’s surface. Typically, a standard suite of instruments is deployed to monitor meteorological state variables.

17 WIND ENERGY↗

FACE-MDS Phase 2: Meteorological Data and Protocols

This dataset contains meteorological data, site parameterization data, and protocols for simulation of the five Free Air CO2 Enrichment (FACE) experiments and one Open Top Chamber (OTC) experiment that were the study sites of the FACE Model Data Synthesis (FACE-MDS) project. This dataset should contain everything necessary to simulate these six CO2 enrichment experiments -- Duke, Kennedy Space Center, NDFF, ORNL, PHACE, and Rhinelander -- following the FACE-MDS simulation protocol. Data cover 1998-2008 (1998-01-01 to 2008-12-31). File naming convention can be found in the file 'facemds-file-table-metdata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-metvars.xml'. Where possible, Assistance for the Land-surface Modelling Activities (ALMA) v3 convention for meteorological variables naming ontology was followed. Additional info can be found in the user guide, protocol documents, and readmes in this dataset. The original naming convention mentioned in the protocol was replaced with the one described in 'facemds-standard-name-table-modvars.xml' in the accompanying dataset (doi:10.15485/1480327). The dataset contains 21 data files that are available in comma-separate (*.csv), plain text (*.txt), and NetCDF (*.nc) format. Nine companion files and additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. This dataset was updated on 2026-06-02 to add a version of the data files in comma separate (.csv) format, a user guide, data dictionary files, and a file-level metadata file. No previously released data values were changed.

54 ENVIRONMENTAL SCIENCES↗

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

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↗

High-Frequency Vertical Profiling of Meteorological Parameters Using AMF1 Facility during RAWEX?GVAX at ARIES, Nainital

An extensive field study, RAWEX-GVAX, was carried out during a 10-month (June 2011-March 2012) campaign at ARIES, Nainital and observations on a wide range of parameters like physical and optical properties of aerosols, meteorological parameters and boundary layer evolution were made. This work presents results obtained from high-frequency (four launches per day), balloon-borne observations of meteorological parameters (pressure, temperature, relative humidity, wind speed and wind direction). These observations show wind speed as high as 84 m/s near the subtropical jet. It is shown that reanalysis wind speeds are in better agreement at 250 hPa (altitude of subtropical jet) than those above or below this value (100 hPa or 500 hPa). These observations also demonstrate that AIRS-derived temperature profiles are negatively biased in the lower altitude region, whereas they are positively biased near the tropopause. WRF simulated results are able to capture variations in temperature, humidity and wind speed profile reasonable well. WRF and AIRS-derived tropopause height, tropopause pressure and tropopause temperature also show agreement with radiosonde estimates.

Aerosols↗

Brookhaven National Laboratory meteorological services instrument calibration plan and procedures

This document describes the Meteorological Services (Met Services) Calibration and Maintenance Schedule and Procedures, The purpose is to establish the frequency and mechanism for the calibration and maintenance of the network of meteorological instrumentation operated by Met Services. The goal is to maintain the network in a manner that will result in accurate, precise and reliable readings from the instrumentation.

54 ENVIRONMENTAL SCIENCES↗

Meteorological services annual data report for 2012

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2012. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

Meteorological Services: Annual Data Report for 2013

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2013. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers based on the level of time and resources required. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

LANL Meteorology Program

The goal of the Meteorology Program is to provide all routine meteorology measurements for LANL operational requirements. This report discusses the program, its routine operations, and other services.

54 ENVIRONMENTAL SCIENCES↗

Partial Support for the Federal Committee for Meteorological Services and Supporting Research (Final Report)

The OFCM sponsored a session within the 16th annual George Mason University Atmospheric Transport and Diffusion Modeling Conference. The theme of the session was Identifying the Research Needs and Current/Planned Research Projects within the Operational and Research Planetary Boundary Layer Interagency Community. Subject matter experts (SME) from the NWS, U.S. Department of Energy, and the National Center for Atmospheric Research participated in the session’s panel discussion. The OFCM-sponsored special session SMEs identified the following areas as operational and research priorities/requirements: Transitioning from planetary boundary layer (PBL) schemes to large-scale eddy simulation; Separating out waves from turbulence and understanding when and how to simulate internal waves degenerating into turbulence; Treating stable boundary layers and unstable boundary layers as separate entities; Increasing the capacity to observe heterogenous boundary layers and to use these observations to improve data assimilation; Dealing with terrain (in all its variations) in a more appropriate way; Conducting a coordinated, joint field program to address the priorities/requirements listed above. The Federal Coordinator brought the results of the successful forum to the attention of the broader interagency PBL community with the goal of eliciting from that community how best to proceed in meeting the operational and research requirements articulated at the special session. On December 16, 2011, the Federal Coordinator also convened a meeting of the Interdepartmental Committee for Meteorological Services and Supporting Research (ICMSSR), a committee with members from 12 federal agencies, including DOE. One of the topics addressed at the meeting was the status of coupling ATD models and the impact across the federal meteorological community. A status report was provided to all ICMSSR members.

54 ENVIRONMENTAL SCIENCES↗

Meteorological Services Annual Data Report for 2014

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2014. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

Meteorological services annual data report for 2015

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2015. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

Meteorological services annual data report for 2016

This document presents the meteorological data collected at Brookhaven National Laboratory (BNL) by Meteorological Services (Met Services) for the calendar year 2016. The purpose is to publicize the data sets available to emergency personnel, researchers and facility operations. Met services has been collecting data at BNL since 1949. Data from 1994 to the present is available in digital format. Data is presented in monthly plots of one-minute data. This allows the reader the ability to peruse the data for trends or anomalies that may be of interest to them. Full data sets are available to BNL personnel and to a limited degree outside researchers. The full data sets allow plotting the data on expanded time scales to obtain greater details (e.g., daily solar variability, inversions, etc.).

54 ENVIRONMENTAL SCIENCES↗

LANL Meteorology Program

This report describes the primary job assignments and uses for meteorological data in the LANL meteorology program.

54 ENVIRONMENTAL SCIENCES↗

Meteorological Observations Available for the State of Utah

The National Weather Service’s Meteorological Assimilation Data Ingest System (MADIS) contains a large number of station networks of surface and upper air meteorological observations for the state of Utah. In addition to MADIS, observations from individual station networks may also be available. It has been confirmed that LLNL has access to the data sources listed below.

54 ENVIRONMENTAL SCIENCES↗