C-Band Scanning ARM Precipitation Radar, 2nd Generation
C-Band Scanning ARM Precipitation Radar, 2nd Generation. CF/Radial Formatted.
54 ENVIRONMENTAL SCIENCES↗
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Results for “Radar remote sensing”
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Ka-Band Scanning ARM Cloud Radar
Ka-Band Scanning ARM Cloud Radar. CF/Radial Formatted.
54 ENVIRONMENTAL SCIENCES↗
X-Band Scanning ARM Cloud Radar
X-Band Scanning ARM Cloud Radar. CF/Radial Formatted.
54 ENVIRONMENTAL SCIENCES↗
W-Band Scanning ARM Cloud Radar
W-Band Scanning ARM Cloud Radar. CF/Radial Formatted.
54 ENVIRONMENTAL SCIENCES↗
Separating Cloud and Drizzle Signals in Radar Doppler Spectra Using a Parametric Time Domain Method
The ability to separate cloud and drizzle returns in active remote sensing observations is important for understanding the microphysics of clouds and precipitation. Yet, robust separations remain challenging in radar remote sensing. Prior methods for cloud and drizzle separation for radar observations use the properties of the Doppler spectra such as skewness. However, these methods have challenges when the drizzle becomes dominant in the observation volume. This paper presents a parametric time domain method (PTDM) that separates cloud and drizzle using the Doppler spectra measurements without assuming any prior properties of cloud and drizzle. The advantage of PTDM is that it can estimate the signal properties in the time domain and can obtain the cloud and drizzle estimates simultaneously. Based on our radar signal simulations, the uncertainty in estimated power and velocity from PTDM are within 2 dB and 0.02 m s -1 , respectively. We have also evaluated the PTDM algorithm using observations from the Atmospheric Radiation Measurement (ARM) Program W-band cloud radar in the Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP-MBL) campaign at the Azores in 2009–10. Two cases corresponding to light and moderate drizzling conditions are considered for the study. The statistics of the estimates obtained show that the PTDM method performs well in separating the cloud and drizzle returns. Finally, the estimated cloud and drizzle reflectivity from PTDM were used to retrieve their corresponding microphysical properties, showing that the retrieved liquid water path agrees to 25 g m -2 with the benchmark microwave method.
Engineering↗
Multi–year analysis of rain–snow levels at Marquette, Michigan
This study uses observations from a ground-based instrument suite to investigate the rain-snow level in stratiform rainfall from January 2014 to April 2020 in the Upper Great Lakes Region. The height above the surface where ice melts to rain, the rain-snow level (RSL), influences microphysical assumptions in remote sensing precipitation retrievals and the ability of space-based radar to discriminate surface precipitation phase because of ground clutter. The instrument suite is installed at the Marquette, MI (MQT) National Weather Service station adjacent to Lake Superior. Rain events and the RSL are studied through a ground-based vertically profiling radar (Micro Rain Radar), a custom NASA-developed video disdrometer (Precipitation Imaging Package), and reanalyses products from ECMWF ERA5 and NASA MERRA-2. Further, distinct macro and micro physical characteristics are observed in precipitation events with shallow RSL ( < 1.8 km above ground level [AGL]) and intermediate RSL ( > 1.8 km AGL). Intermediate RSL correspond to rain events with relatively higher rain rates and a higher concentration of small drops in the drop size distributions (DSDs). Shallow RSL DSDs contain relatively higher concentrations of large drops with lower fall speeds suggesting that partially melted snowflakes may be reaching the surface. Reflectivity-rain-rate relationships are also impacted by microphysical differences associated with RSL regimes. Radar-detected RSL agree with reanalysis-derived melt levels- especially at wet-bulb isotherms of 0.5°C and 1°C. Seasonal differences such as shallow rain-snow levels in winter, fall, and spring have subsequent implications for satellite detectability.
54 ENVIRONMENTAL SCIENCES↗
Precipitation Trade Wind Cumuli within EUREC 4 A Field Campaign Report
The campaign Trades Cumuli Precipitation Initiation and Characterization (TCPIC) within the overarching Elucidating the Role of Clouds-Circulation Coupling in Climate EUREC 4 A campaign took place from 17 January 2020 to 20 February 2020, a total of 35 days. The campaign complemented the more extensive EUREC 4 A campaign focusing on cumulus clouds' role in the Earth's climate. TCPIC concentrated on understanding what triggers the onset and development of precipitation in trade wind cumulus clouds. The campaign requested the deployment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) roll, pitch, and heave (RPH) stabilization platform to stabilize two radars on the Maria S. Merian research vessel (RV). The advanced remote-sensing techniques from stabilized radars characterized the entire precipitation life cycle, from the formation of larger cloud drops to precipitation evaporating on its way to the surface. Retrievals of evaporation rates, to track how rain affects the trade wind boundary layer, will be based on the zenith-pointing Doppler observations collected from the stabilized micro rain radar (MRR). Figure 1 shows the instrumentation's deployment on the RV: we installed the AMF RPH stabilization platform and the radars on the uppermost deck (peil deck) of the ship. For installing the devices, we coordinated a test phase of the equipment on the Maria S. Merian RV from 25 to 29 October 2019 in Emden harbor, Germany. In this testing phase, we set up all the connections, tested how to mount the W-band and the micro rain radars firmly on the table, and experimented with guided movements of the table to test the resistance of the whole system. Figure 1 shows the final tests conducted in Emden with the stable platform and the radars mounted.
54 ENVIRONMENTAL SCIENCES↗
North Slope of Alaska XSAPR b1 Data Processing Report: April 2024-April 2025
The North Slope of Alaska (NSA) atmospheric observatory, operated by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) User Facility, is a measurement site in the Arctic that has been collecting crucial atmospheric data for more than 25 years. The central facility located in Utqiaġvik, Alaska (formerly known as Barrow) hosts a suite of instruments that are used to better understand arctic processes, which are often not well represented in earth system models. The NSA site sits only a few kilometers from the Arctic Ocean, which also makes it a prime location to study complex ocean-atmosphere-ice interactions. Arctic cloud and precipitation processes are also of scientific interest, and remote-sensing instruments including radars are a key component of the NSA instrument suite. One of the radars at NSA is the X-band Scanning ARM Precipitation Radar (XSAPR). This report evaluates one year of recent XSAPR data from April 2024 through April 2025 and details the process of generating b1-level data. This analysis marks the first effort by ARM staff to quality-control NSA XSAPR data with the goal of routinely producing b1-level data in the future depending on radar operations.
54 ENVIRONMENTAL SCIENCES↗
Fixed-Site KAZR b1 Data Processing: Corrections, Calibrations, and Processing Report
The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) User Facility operates three fixed-site observatories: Eastern North Atlantic (ENA), North Slope of Alaska (NSA), and Southern Great Plains (SGP). Each fixed site has a wide variety of atmospheric instrumentation that has been collecting data for at least 10 years (NSA and SGP over 25 years). Each site is unique because it represents a different climate state. The environment at ENA is characterized by marine stratocumulus clouds and one of the key scientific areas of focus is the interaction of these clouds with aerosols. At NSA the focus is on arctic climate and cloud and radiative processes in a high-latitude environment. SGP represents a mid-latitude, mid-continent climate that experiences environmental cycles on diurnal and seasonal time scales. The ARM observatories are all meant to improve understanding of atmospheric processes that can then be better incorporated into weather and climate models. Another common thread between the fixed sites is the focus on cloud processes. Each site is equipped with at least one radar that provides continuous remote-sensing observations of clouds and precipitation. This report details the analysis of a1-level radar data at the fixed sites and the process for generating b1-level data. While b1-level data have been produced for ARM campaigns at the mobile facilities, this is the first analysis led by ARM radar mentors to correct data at the fixed sites. In particular, we focus on calibrations and corrections of the Ka-band ARM Zenith Radars (KAZRs) at ENA, NSA, and SGP. Ongoing and future work will involve corrections applied to other fixed-site radars.
54 ENVIRONMENTAL SCIENCES↗
Exploring the potential of using L-Band InSAR for the mapping of flooded vegetation in tropical wetlands
Wetlands play a critical role in global water and carbon cycles, yet monitoring their water extent remains difficult, particularly beneath dense vegetation. SAR-based techniques such as backscatter thresholding are limited by complex scattering mechanisms, while fully polarimetric SAR (PolSAR) data capable of detecting doublebounce scattering remain scarce. To address these challenges, this study evaluates the potential of Interferometric SAR (InSAR) for mapping water surfaces beneath vegetation, termed flooded vegetation, using the Atrato floodplain in Colombia as a case study. We develop an automated workflow combining InSAR fringe detection with local phase homogeneity analysis and random sampling of processing parameters to generate probabilistic flooded vegetation maps. Applied to ALOS PALSAR-1 L-band image pairs from 2007–2011, the workflow captures seasonal fluctuations in flooded extent ranging from 500 to 1,500 km2. Compared to other L-band SAR inundation products, the InSAR-based maps identify broader flooded areas, with ~70% agreement in pairwise comparisons. Around 84% of detections align with existing wetland inventories and seasonal changes correspond with regional hydrological indicators, including terrestrial water storage anomalies and water gauge measurements. PolSAR analysis shows that InSAR complements backscatter-based methods by detecting inundation in areas with weak double-bounce signals. These findings suggest that combining InSAR with backscatter-based methods can improve detection of flooded vegetation, which is especially relevant for the upcoming NISAR mission that will offer frequent global L-band observations.
Coastal inundation↗
Droplet Number Concentration Value-Added Product
The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloud layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.
97 MATHEMATICS AND COMPUTING↗
An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans
Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher-frequency radars as well as range–height indicator (RHI) scans. The calibration of weather radars represents one of the most dominant sources of error for their use in a variety of fields including quantitative precipitation estimation and model comparisons. While most weather radars are routinely calibrated, the frequency of calibration is often less than required, resulting in miscalibrated time periods. While full absolute calibration techniques often require the radar to be taken offline for a period of time, there have been online calibration techniques discussed in the literature. The relative calibration adjustment (RCA) technique uses the statistics of the ground clutter surrounding the radar as a monitoring source for the stability of calibration but has only been demonstrated to work at S- and C-band for plan-position indicator (PPI) scans at a constant elevation. In this work the RCA technique is modified to work with higher-frequency radars, including Ka-band cloud radars. At higher frequencies the properties of clutter can be much more variable. This work introduces an extended clutter selection procedure that incorporates the temporal stability of clutter and helps to improve the operational stability of RCA for relatively higher-frequency radars. The technique is also extended to utilize range–height scans from radars where the elevation is varied rather than the azimuth. These types of scans are often utilized with research radars to examine the vertical structure of clouds. The newly extended technique (eRCA) is applied to four Department of Energy Atmospheric Radiation Measurement (DOE ARM) weather radars ranging in frequency from C- to Ka-band. Cross comparisons of three co-located radars with frequencies C, X, and Ka at the ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) site show that the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic (ENA) site, we show how the technique can be modified to be more resilient to clutter fields that show increased variability, in this case due to sea clutter. The results show that this technique is promising for a posteriori data calibration and monitoring.
47 OTHER INSTRUMENTATION↗
Autonomous Radiation Mapping and Quantification using an Unmanned Ground Vehicle. Part I - Environment Mapping
When characterizing facilities, advanced autonomous systems are safe, efficient, and cost-effective tools, which can safely deploy state-of-the-art instrumentation without exposing workers to radiation risks. One main focus of the research is the visual mapping of the environment.This paper presents a framework for the mapping aspect that utilizes lidar and SLAM technologies coupled with a monocular camera to create a point cloud of the environment. Upon completion, the present research work aims to provide an autonomous mobile robot the capability to localize itself and aid the user with visualizing the radiation data. Challenges: C++ node needs to properly synchronize image and point cloud data. 3D lidar has resolution of ± 3 cm. Proper camera calibration needed. Transforms need to be precise for proper alignment of image and point-cloud. Results: Voxelated point clouds. Accurate colors from calibrated cameras including details smaller than lidar resolution. Developed Robotics Operating System (ROS) package for ease of transfer to other robot platforms.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Doppler Lidar (DL) Instrument Handbook
The Doppler lidar (DL) is an active remote sensing instrument that provides range- and time-resolved measurements of radial velocity and attenuated backscatter. The principle of operation is similar to radar in that pulses of energy are transmitted into the atmosphere; the energy scattered back to the transceiver is collected and measured as a time-resolved signal. From the time delay between each outgoing transmitted pulse and the backscattered signal, the distance to the scatterer is inferred. The radial or line-of-sight velocity of the scatterers is determined from the Doppler frequency shift of the backscattered radiation. The DL uses a heterodyne detection technique in which the return signal is mixed with a reference laser beam (i.e., local oscillator) of known frequency. An onboard signal processing computer then determines the Doppler frequency shift from the spectra of the heterodyne signal. The energy content of the Doppler spectra can also be used to determine attenuated backscatter.
99 GENERAL AND MISCELLANEOUS↗
Detecting forest response to droughts with global observations of vegetation water content
Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analogue of the pressure-volume curve, the non-linear relationship between 44 average leaf or branch water potential and water content commonly used in plant hydraulics. The 45 sources of variability in these ecosystem-scale pressure-volume curves and their relationship to 46 forest response to water stress are discussed. We further show to what extent diel, seasonal, and 47 decadal dynamics of VWC reflect variations in different processes relating the tree response to 48 water stress. VWC can also be used for inferring belowground conditions – which are difficult to 49 impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne 50 observational system for VWC, when combined with existing datasets, can capture diel and 51 seasonal water dynamics to advance the science and applications of global forest vulnerability to 52 future droughts.
54 ENVIRONMENTAL SCIENCES↗
THz Radar Observations of Hydrometeors in a Spray Chamber
Abstract A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere.
54 ENVIRONMENTAL SCIENCES↗
Sizing ice hydrometeor populations using the dual-wavelength radar ratio
Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, D v , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of D v retrievals using DWR are around 0.6 mm when D v is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as D v , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.
54 ENVIRONMENTAL SCIENCES↗
New insights into ice multiplication using remote-sensing observations of slightly supercooled mixed-phase clouds in the Arctic
Significance During secondary ice events, ice particle number concentrations in mixed-phase clouds can increase by orders of magnitude with profound implications for the cloud evolution. However, characterization of secondary ice events in the natural environment has been a challenge for the community for decades. We show the long-term frequency of secondary ice events in Arctic supercooled clouds for temperatures warmer than − 10 ○ C, made possible by applying a remote-sensing technique to 6 y of data. Secondary ice events are found to occur preferentially in the presence of drizzle droplets, compared with the better-known rime-splintering process, causing up to a 1,000-fold enhancement in ice number concentration. These results provide critical insights for model parameterizations and future laboratory experiments.
54 ENVIRONMENTAL SCIENCES↗