Results for “vertical velocity; reflectivity; doppler velocity”

NASA NTRS2013

Evaluation of Model Microphysics within Precipitation Bands of Extratropical Cyclones

Recent studies evaluating the bulk microphysical schemes (BMPs) within cloud resolving models (CRMs) have indicated large uncertainties and errors in the amount and size distributions of snow and cloud ice aloft. The snow prediction is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33‐km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Coldseason Precipitation Experiment (GCPEx) experiment, as well as a few years (15 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku-band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. A Particle Size and Velocity (PARSIVEL) disdrometer was also used to measure the surface size distribution and fall speeds of snow at SBNY. For the 15 cases at SBNY, the WSM6, Morrison (MORR), Thompson (THOM2), and Stony Brook (SBU-YLIN) BMPs were validated. A non-spherical snow assumption (THOM2 and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU-YLIN schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM2 is approx 0.25 m/s too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM2, and MORR schemes were approx 0.25 m/s too slow, while the SBU-YLIN was 0.25 to 0.5 m/s too fast. Overall, the BMPs simulate a size distribution close to the observed for D < 4 mm in the dendritic, plates, and mixed habit periods. The model BMPs underestimate the size distribution when large aggregates were observed. For D > 6 mm in the dendrites, side planes, and mixed habit periods, the BMPs are likely not simulating enough aggregation to create a larger size distribution, although the MORR (double moment) scheme seemed to perform best. These SBNY results will be compared with some results from GCPEx for a warm frontal snow band observed at 18 February 2012.

Colle, Brian A.↗

NASA NTRS2013

Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

Recent studies evaluating the bulk microphysical schemes (BMPs) within cloud resolving models (CRMs) have indicated large uncertainties and errors in the amount and size distributions of snow and cloud ice aloft. The snow prediction is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33‐km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Coldseason Precipitation Experiment (GCPEx) experiment, as well as a few years (15 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku-band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. A Particle Size and Velocity (PARSIVEL) disdrometer was also used to measure the surface size distribution and fall speeds of snow at SBNY. For the 15 cases at SBNY, the WSM6, Morrison (MORR), Thompson (THOM2), and Stony Brook (SBU-YLIN) BMPs were validated. A non-spherical snow assumption (THOM2 and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU-YLIN schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM2 is ~0.25 meters per second too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM2, and MORR schemes were ~0.25 meters per second too slow, while the SBU-YLIN was 0.25 to 0.5 meters per second too fast. Overall, the BMPs simulate a size distribution close to the observed for D < 4 mm in the dendritic, plates, and mixed habit periods. The model BMPs underestimate the size distribution when large aggregates were observed. For D > 6 mm in the dendrites, side planes, and mixed habit periods, the BMPs are likely not simulating enough aggregation to create a larger size distribution, although the MORR (double moment) scheme seemed to perform best. These SBNY results will be compared with some results from GCPEx for a warm frontal snow band observed at 18 February 2012.

Colle, Brian A.↗

NASA NTRS2014

Evaluation of Mixed-Phase Microphysics Within Winter Storms Using Field Data and In Situ Observations

Snow prediction within models is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33-km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Cold-season Precipitation Experiment (GCPEx) experiment over southern Ontario, as well as a few years (12 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. The GCPex presentation will focus on verification using aircraft spirals through warm frontal snow band event on 18 February 2012. All the BMPs realistically simulated the structure of the band and the vertical distribution of snow/ice aloft, except the SBU-YLIN overpredicted slightly and Thompson (THOM) underpredicted somewhat. The Morrison (MORR) scheme produced the best slope size distribution for snow, while the Stony Brook (SBU) underpredicted and the THOM slightly overpredicted. Those schemes that have the slope intercept a function of temperature (SBU and WSM6) tended to perform better for that parameter than others, especially the fixed intercept in Goddard. Overall, the spread among BMPs was smaller than in other studies, likely because there was limited riming with the band. For the 15 cases at SBNY, which include moderate and heavy riming events, the non-spherical snow assumption (THOM and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM is approx. 0.25 m/s too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM, and MORR schemes were approx. 0.25 m/s too slow, while the SBU was 0.25 to 0.5 m/s too fast because of some excessive cloud water issues.

Colle, Brian A.↗

DOE OSTI2025

rwpvertvel

The 915-Mhz Radar Wind Profiler (RWP) has been configured to point vertically and operate in precipitation mode so as to measure Doppler velocity in the vertical direction, tracking the motion of hydrometeors as they fall, and enabling the calculation of vertical air motion within clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

kazr2cfrpr (a1)

The Ka-band ARM Zenith Radar (KAZR) remotely probes the extent and composition of clouds at millimeter wavelengths. The KAZR is a zenith-pointing Doppler radar that operates at a frequency of approximately 35 GHz. The main purpose of this radar is to determine the first three Doppler moments (reflectivity, vertical velocity, and spectral width) at a range resolution of approximately 30 meters from near-ground to nearly 20 kilometers in altitude. The KAZR replaces the millimeter-wavelength cloud radar (MMCR) and uses a new digital receiver that provides higher spatial and temporal resolution than the MMCR. In addition, spectral artifacts in the data are significantly reduced in the KAZR, allowing researchers to study cloud dynamics much more closely than with the MMCR. KAZR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

kazr2cfrge (a1)

The Ka-band ARM Zenith Radar (KAZR) remotely probes the extent and composition of clouds at millimeter wavelengths. The KAZR is a zenith-pointing Doppler radar that operates at a frequency of approximately 35 GHz. The main purpose of this radar is to determine the first three Doppler moments (reflectivity, vertical velocity, and spectral width) at a range resolution of approximately 30 meters from near-ground to nearly 20 kilometers in altitude. The KAZR replaces the millimeter-wavelength cloud radar (MMCR) and uses a new digital receiver that provides higher spatial and temporal resolution than the MMCR. In addition, spectral artifacts in the data are significantly reduced in the KAZR, allowing researchers to study cloud dynamics much more closely than with the MMCR. KAZR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

kazr2cfrmd (a1)

The Ka-band ARM Zenith Radar (KAZR) remotely probes the extent and composition of clouds at millimeter wavelengths. The KAZR is a zenith-pointing Doppler radar that operates at a frequency of approximately 35 GHz. The main purpose of this radar is to determine the first three Doppler moments (reflectivity, vertical velocity, and spectral width) at a range resolution of approximately 30 meters from near-ground to nearly 20 kilometers in altitude. The KAZR replaces the millimeter-wavelength cloud radar (MMCR) and uses a new digital receiver that provides higher spatial and temporal resolution than the MMCR. In addition, spectral artifacts in the data are significantly reduced in the KAZR, allowing researchers to study cloud dynamics much more closely than with the MMCR. KAZR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Processing of High Resolution, Multiparametric Radar Data for the Airborne Dual-Frequency Precipitation Radar APR-2

Following the successful Precipitation Radar (PR) of the Tropical Rainfall Measuring Mission, a new airborne, 14/35 GHz rain profiling radar, known as Airborne Precipitation Radar - 2 (APR-2), has been developed as a prototype for an advanced, dual-frequency spaceborne radar for a future spaceborne precipitation measurement mission. . This airborne instrument is capable of making simultaneous measurements of rainfall parameters, including co-pol and cross-pol rain reflectivities and vertical Doppler velocities, at 14 and 35 GHz. furthermore, it also features several advanced technologies for performance improvement, including real-time data processing, low-sidelobe dual-frequency pulse compression, and dual-frequency scanning antenna. Since August 2001, APR-2 has been deployed on the NASA P3 and DC8 aircrafts in four experiments including CAMEX-4 and the Wakasa Bay Experiment. Raw radar data are first processed to obtain reflectivity, LDR (linear depolarization ratio), and Doppler velocity measurements. The dataset is then processed iteratively to accurately estimate the true aircraft navigation parameters and to classify the surface return. These intermediate products are then used to refine reflectivity and LDR calibrations (by analyzing clear air ocean surface returns), and to correct Doppler measurements for the aircraft motion. Finally, the the melting layer of precipitation is detected and its boundaries and characteristics are identifIed at the APR-2 range resolution of 30m. The resulting 3D dataset will be used for validation of other airborne and spaceborne instruments, development of multiparametric rain/snow retrieval algorithms and melting layer characterization and statistics.

airborne radar↗

NASA NTRS1999

Rain Fallspeeds and Rates Derived from Airborne Nadir-Pointing Doppler Radar Measurements

The use of vertical-incidence Doppler velocity in addition to radar reflectivity may yield information on drop size distribution and therefore result in better rainrate estimates. Doppler velocity can provide useful information on the raindrop size distribution. Doppler velocities from a zenith-pointing radar represent the sum of the mean reflectivity-weighted hydrometeor fallspeed and the vertical air motion. Dual-parameter rain estimation methods using the Doppler velocity, require that the latter can be removed, or is negligible. Atlas et al. (1972) derived relations between Doppler velocity, reflectivity, and rain rate assuming an exponential size distribution for rain. Ulbrich (1994) expanded on this work by deriving the relation between the Doppler velocity and the reflectivity assuming a Gamma size distribution. This distribution provides a more realistic representation of the small rain drops. To get accurate information on raindrop size distributions with the above method, the air motions must be removed from the observed Doppler velocities

Heymsfield, Gerald M.↗

DOE OSTI2025

A radar view of ice microphysics and turbulence in Arctic cloud systems

Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

MICRE W-band radar reflectivity and Doppler velocity

Daily files containing radar reflectivity and mean Doppler velocity collected from vertically pointing W-band radar during the Macquarie Island Cloud & Radiation Experiment (MICRE): April 2016 to March 2017.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1986

Observations of mesoscale vertical velocities around frontal zones

Vertical velocity and reflectivity data obtained with a VHF Doppler radar over a 15-day period in October and November of 1981 are analyzed. Standard radiosonde data and surface observations were used to locate two occluded fronts, two warm fronts, and a cold front that passed the radar site. These fronts are also evident in the radar reflectivity data. Most studies of the vertical circulation patterns associated with mososcale systems have used precipitation and cloud formations as tracers. Unlike other observational techniques, the VHF radar permits the continuous measurement of the three-dimensional air velocity vector in time and height from a fixed location. With the beam in a vertically pointing position, signals are scattered from turbulent variations in the refractive index with half the scale of the radar wavelength and by regions with sudden changes in the refractive index associated with horizontally stratified layers. Generally, the strongest echoes occur at the maximum in the vertical gradient of refractivity, usually at the base of a temperature inversion, such as the tropopause. VHF radars can also be used to locate atmospheric fronts, which are characterized by static stability, large horizontal temperature gradients, large vorticities, and vertical wind shears. These radars can provide the velocity field data needed to study wave motions associated with fronts and compare the actual vertical circulation to theoretical predictions.

Dennis, T. S.↗

NASA NTRS1993

Microphysical properties of the November 26 cirrus cloud retrieved by Doppler radar/IR radiometer technique

Gaining information about cirrus cloud microphysics requires development of remote sensing techniques. In an earlier paper. Matrosov et al. (1992) proposed a method to estimate ice water path (IWP) (i.e., vertically integrated ice mass content IMC) and characteristic particle size averaged through the cloud from combined groundbased measurements of radar reflectivities and IR brightness temperatures of the downwelling thermal radiation in the transparency region of 10-12 mu m. For some applications, the vertically averaged characteristic particle sizes and IWP could be the appropriate information to use. However, vertical profiles of cloud microphysical parameters can provide a better understanding of cloud structure and development. Here we describe a further development of the previous method by Matrosov et al. (1992) for retrieving vertical profiles of cirrus particle sizes and IMC rather than their vertically averaged values. In addition to measurements of radar reflectivities, the measurements of Doppler velocities are used in the new method. This provides us with two vertical profiles of measurements to infer two vertical profiles of unknowns, i.e., particle characteristic sizes and IMC. Simultaneous measurements of the IR brightness temperatures are still needed to resolve an ambiguity in particle size-fall velocity relationships.

Matrosov, Sergey Y.↗

NASA NTRS1982

The life cycle of thunderstorm gust fronts as viewed with Doppler radar and rawinsonde data

This paper presents the time-dependent analysis of the thunderstorm gust front with the use of Project NIMROD data. RHI cross sections of reflectivity and Doppler velocity are constructed to determine the entire vertical structure. The life cycle of the gust front is divided into four stages: (1) the formative stage; (2) the early mature stage; (3) the late mature stage; and (4) the dissipation stage. A new finding is a horizontal roll detected in the reflectivity pattern resulting from airflow that is deflected upward by the ground, while carrying some of the smaller precipitation ahead of the main echo core of the squall line. This feature is called a 'precipitation roll'. As determined from rawinsonde data, the cold air behind the gust front accounts for the observed surface pressure rise. Calculations confirm that the collision of two fluids produce a nonhydrostatic pressure at the leading edge of the outflow. The equation governing the propagation speed of a density current accurately predicts the movement of the gust front.

Wakimoto, R. M.↗

DOE OSTI2022

Ka-Band Scanning ARM Cloud Radar (KASACR), 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross Mode (a1-level)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Ka-Band Scanning ARM Cloud Radar (KASACR), 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross-Polarization Mode (a1-level)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

kasacrcfrspcxpol (a1)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

kasacrcfrspccross (a1)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗