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- Author or Editor: Sergey Y. Matrosov x
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Abstract
A comparative study of the use of X- and S-band polarimetric radars for rainfall parameter retrievals is presented. The main advantage of X-band polarimetric measurements is the availability of reliable specific differential phase shift estimates, K DP, for lighter rainfalls when phase measurements at the S band are too noisy to produce usable K DP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-Rayleigh resonant effects, K DP values at a 3.2-cm wavelength (X band) are on average a factor of 3.7 greater than at 11 cm (S band), which is a somewhat larger difference than simple frequency scaling predicts. The non-Rayleigh effects also cause X-band horizontal polarization reflectivity, Z eh, and differential reflectivity, Z DR, to be larger than those at the S band. The differences between X- and S-band reflectivities can exceed measurement uncertainties for Z eh starting approximately at Z eh > 40 dBZ, and for Z DR when the mass-weighted drop diameter, Dm , exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed that consistent K DP estimates exceeding about 0.1° km−1 began to be possible at reflectivities greater than ∼26–30 dBZ while at the S band such estimates can generally be made if Z eh > ∼35–39 dBZ. Experimental radar data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm h−1 showed availability of the K DP-based estimates of R for most of the data points at the X band while at the S band such estimates were available only for R greater than about 8–10 mm h−1. After correcting X-band differential reflectivity measurements for differential attenuation, Z DR measurements at both radar frequency bands were in good agreement with each other for Dm < 2 mm, which approximately corresponds to Z DR ≈ 1.6 dB. The Z DR-based retrievals of characteristic raindrop sizes also agreed well with in situ disdrometer measurements.
Abstract
A comparative study of the use of X- and S-band polarimetric radars for rainfall parameter retrievals is presented. The main advantage of X-band polarimetric measurements is the availability of reliable specific differential phase shift estimates, K DP, for lighter rainfalls when phase measurements at the S band are too noisy to produce usable K DP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-Rayleigh resonant effects, K DP values at a 3.2-cm wavelength (X band) are on average a factor of 3.7 greater than at 11 cm (S band), which is a somewhat larger difference than simple frequency scaling predicts. The non-Rayleigh effects also cause X-band horizontal polarization reflectivity, Z eh, and differential reflectivity, Z DR, to be larger than those at the S band. The differences between X- and S-band reflectivities can exceed measurement uncertainties for Z eh starting approximately at Z eh > 40 dBZ, and for Z DR when the mass-weighted drop diameter, Dm , exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed that consistent K DP estimates exceeding about 0.1° km−1 began to be possible at reflectivities greater than ∼26–30 dBZ while at the S band such estimates can generally be made if Z eh > ∼35–39 dBZ. Experimental radar data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm h−1 showed availability of the K DP-based estimates of R for most of the data points at the X band while at the S band such estimates were available only for R greater than about 8–10 mm h−1. After correcting X-band differential reflectivity measurements for differential attenuation, Z DR measurements at both radar frequency bands were in good agreement with each other for Dm < 2 mm, which approximately corresponds to Z DR ≈ 1.6 dB. The Z DR-based retrievals of characteristic raindrop sizes also agreed well with in situ disdrometer measurements.
Abstract
A new methodology for estimating the depolarization ratio (DR) by dual-polarization radars with simultaneous transmission/reception of orthogonally polarized waves together with traditionally measured differential reflectivity Z DR, correlation coefficient ρ hυ , and differential phase ΦDP in a single mode of operation is suggested. This depolarization ratio can serve as a proxy for circular depolarization ratio measured by radars with circular polarization. The suggested methodology implies the use of a high-power phase shifter to control the system differential phase on transmission and a special signal processing to eliminate the detrimental impact of differential phase on the estimate of DR. The feasibility of the suggested approach has been demonstrated by retrieving DR from the standard polarimetric variables and the raw in-phase I and quadrature Q components of radar signals and by implementing the scheme on a C-band radar with simultaneous transmission/reception of horizontally and vertically polarized waves. Possible practical implications of using DR include the detection of hail and the determination of its size above the melting layer, the discrimination between various habits of ice aloft, and the possible identification and quantification of riming, which is associated with the presence of supercooled cloud water. Some examples of these applications are presented.
Abstract
A new methodology for estimating the depolarization ratio (DR) by dual-polarization radars with simultaneous transmission/reception of orthogonally polarized waves together with traditionally measured differential reflectivity Z DR, correlation coefficient ρ hυ , and differential phase ΦDP in a single mode of operation is suggested. This depolarization ratio can serve as a proxy for circular depolarization ratio measured by radars with circular polarization. The suggested methodology implies the use of a high-power phase shifter to control the system differential phase on transmission and a special signal processing to eliminate the detrimental impact of differential phase on the estimate of DR. The feasibility of the suggested approach has been demonstrated by retrieving DR from the standard polarimetric variables and the raw in-phase I and quadrature Q components of radar signals and by implementing the scheme on a C-band radar with simultaneous transmission/reception of horizontally and vertically polarized waves. Possible practical implications of using DR include the detection of hail and the determination of its size above the melting layer, the discrimination between various habits of ice aloft, and the possible identification and quantification of riming, which is associated with the presence of supercooled cloud water. Some examples of these applications are presented.
Abstract
Nonspherical atmospheric ice particles can enhance radar backscattering and attenuation above that expected from spheres of the same mass. An analysis of scanning 95-GHz radar data collected during the Storm Peak Laboratory Cloud Property Validation Experiment (StormVEx) shows that at a least a small amount of enhanced backscattering was present in most radar scans, with a median enhancement of 2.4 dB at zenith. This enhancement will cause an error (bias) in ice water content (IWC) retrievals that neglect particle orientation, with a value of 2.4 dB being roughly equivalent to a relative error in IWC of 43%. Of the radar scans examined, 25% had a zenith-enhanced backscattering exceeding 3.5 dB (equivalent to a relative error in IWC in excess of 67%) and 10% of the scans had a zenith-enhanced backscattering exceeding 6.4 dB (equivalent to a relative error in IWC in excess of 150%). Cloud particle images indicate that large enhancement typically occurred when planar crystals (e.g., plates and dendrites) were present, with the largest enhancement occurring when large planar crystals were falling out of a supercooled liquid-water layer. More modest enhancement was sometimes due to planar crystals, but it was also sometimes likely a result of horizontally oriented nonspherical irregularly shaped particles. The analysis also shows there is a strong correlation (about −0.79) between the change in slant 45° depolarization ratio with radar scan elevation angle and the magnitude of the zenith-enhanced backscattering, suggesting that measurements of the slant depolarization ratio can be used to improve radar-based cloud microphysical property retrievals.
Abstract
Nonspherical atmospheric ice particles can enhance radar backscattering and attenuation above that expected from spheres of the same mass. An analysis of scanning 95-GHz radar data collected during the Storm Peak Laboratory Cloud Property Validation Experiment (StormVEx) shows that at a least a small amount of enhanced backscattering was present in most radar scans, with a median enhancement of 2.4 dB at zenith. This enhancement will cause an error (bias) in ice water content (IWC) retrievals that neglect particle orientation, with a value of 2.4 dB being roughly equivalent to a relative error in IWC of 43%. Of the radar scans examined, 25% had a zenith-enhanced backscattering exceeding 3.5 dB (equivalent to a relative error in IWC in excess of 67%) and 10% of the scans had a zenith-enhanced backscattering exceeding 6.4 dB (equivalent to a relative error in IWC in excess of 150%). Cloud particle images indicate that large enhancement typically occurred when planar crystals (e.g., plates and dendrites) were present, with the largest enhancement occurring when large planar crystals were falling out of a supercooled liquid-water layer. More modest enhancement was sometimes due to planar crystals, but it was also sometimes likely a result of horizontally oriented nonspherical irregularly shaped particles. The analysis also shows there is a strong correlation (about −0.79) between the change in slant 45° depolarization ratio with radar scan elevation angle and the magnitude of the zenith-enhanced backscattering, suggesting that measurements of the slant depolarization ratio can be used to improve radar-based cloud microphysical property retrievals.
Abstract
Scanning polarimetric W-band radar data were evaluated for the purpose of identifying predominant ice hydrometeor habits. Radar and accompanying cloud microphysical measurements were conducted during the Storm Peak Laboratory Cloud Property Validation Experiment held in Steamboat Springs, Colorado, during the winter season of 2010/11. The observed ice hydrometeor habits ranged from pristine and rimed dendrites/stellars to aggregates, irregulars, graupel, columns, plates, and particle mixtures. The slant 45° linear depolarization ratio (SLDR) trends as a function of the radar elevation angle are indicative of the predominant hydrometeor habit/shape. For planar particles, SLDR values increase from values close to the radar polarization cross coupling of about −21.8 dB at zenith viewing to maximum values at slant viewing. These maximum values depend on predominant aspect ratio and bulk density of hydrometeors and also show some sensitivity to particle characteristic size. The highest observed SLDRs were around −8 dB for pristine dendrites. Unlike planar-type hydrometeors, columnar-type particles did not exhibit pronounced depolarization trends as a function of viewing direction. A difference in measured SLDR values between zenith and slant viewing can be used to infer predominant aspect ratios of planar hydrometeors if an assumption about their bulk density is made. For columnar hydrometeors, SLDR offsets from the cross-coupling value are indicative of aspect ratios. Experimental data were analyzed for a number of events with prevalence of planar-type hydrometeors and also for observations when columnar particles were the dominant species. A relatively simple spheroidal model and accompanying T-matrix calculations were able to approximate most radar depolarization changes with viewing angle observed for different hydrometeor types.
Abstract
Scanning polarimetric W-band radar data were evaluated for the purpose of identifying predominant ice hydrometeor habits. Radar and accompanying cloud microphysical measurements were conducted during the Storm Peak Laboratory Cloud Property Validation Experiment held in Steamboat Springs, Colorado, during the winter season of 2010/11. The observed ice hydrometeor habits ranged from pristine and rimed dendrites/stellars to aggregates, irregulars, graupel, columns, plates, and particle mixtures. The slant 45° linear depolarization ratio (SLDR) trends as a function of the radar elevation angle are indicative of the predominant hydrometeor habit/shape. For planar particles, SLDR values increase from values close to the radar polarization cross coupling of about −21.8 dB at zenith viewing to maximum values at slant viewing. These maximum values depend on predominant aspect ratio and bulk density of hydrometeors and also show some sensitivity to particle characteristic size. The highest observed SLDRs were around −8 dB for pristine dendrites. Unlike planar-type hydrometeors, columnar-type particles did not exhibit pronounced depolarization trends as a function of viewing direction. A difference in measured SLDR values between zenith and slant viewing can be used to infer predominant aspect ratios of planar hydrometeors if an assumption about their bulk density is made. For columnar hydrometeors, SLDR offsets from the cross-coupling value are indicative of aspect ratios. Experimental data were analyzed for a number of events with prevalence of planar-type hydrometeors and also for observations when columnar particles were the dominant species. A relatively simple spheroidal model and accompanying T-matrix calculations were able to approximate most radar depolarization changes with viewing angle observed for different hydrometeor types.
Abstract
Dual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s−1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m−2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly <4 kg m−2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak-echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).
Abstract
Dual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s−1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m−2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly <4 kg m−2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak-echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).
The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.
Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.
The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.
Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.
Abstract
This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals.
significance statement
Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.
Abstract
This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals.
significance statement
Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.
Abstract
Thorough understanding of aerosols, clouds, boundary layer structure, and radiation is required to improve the representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly forming sea ice. Over the last three years, the U.S. Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems [UASs, also known as unmanned aerial vehicles (UAVs) and drones] and tethered balloon systems (TBSs) at Oliktok Point, Alaska. These activities have featured in situ measurements of the thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics, and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deployed by the DOE Atmospheric Radiation Measurement (ARM) program through the third ARM Mobile Facility (AMF-3), these flight activities demonstrate the ability of such platforms to provide critically needed information. In addition to providing new and unique datasets, lessons learned during initial campaigns have assisted in the development of an exciting new community resource.
Abstract
Thorough understanding of aerosols, clouds, boundary layer structure, and radiation is required to improve the representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly forming sea ice. Over the last three years, the U.S. Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems [UASs, also known as unmanned aerial vehicles (UAVs) and drones] and tethered balloon systems (TBSs) at Oliktok Point, Alaska. These activities have featured in situ measurements of the thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics, and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deployed by the DOE Atmospheric Radiation Measurement (ARM) program through the third ARM Mobile Facility (AMF-3), these flight activities demonstrate the ability of such platforms to provide critically needed information. In addition to providing new and unique datasets, lessons learned during initial campaigns have assisted in the development of an exciting new community resource.
