Abstract

An error budget analysis is performed for retrieval of along-track winds based on the design of a spaceborne Doppler radar using polarization diversity. The analysis is conducted within the framework of a case study of an Atlantic hurricane. The proposed concept consists of either a Ka-band or W-band stereoradar mounted on an LEO satellite equipped with both nadir- and forward-viewing beams and with an optional cross-scanning capability. Such a radar design is intended for observing the microphysical and dynamical structures of cloud systems, including disturbed mesoscale convective systems. Because of the high winds involved in such weather phenomena and because of the Doppler fading introduced by platform motion, polarization diversity is adopted. The simulation framework enables a breakdown of the Doppler velocity measurement error budget into its most important components, that is, nonuniform beamfilling, multiple scattering, and inherent signal noise. The impact of each of these error terms on the total error depends on the adopted integration length, the number of scanned tracks, and the specifics of the radar. This allows for optimally selecting an integration length suitable for minimizing the total rms velocity error. The analysis shows that the use of a large antenna could achieve impressive measurement accuracy of the along-line-of-sight wind velocities. Notably, this would be the case for integration lengths longer than 3 km, even when carrying out cross-track scanning for up to 17 separate tracks. Examples of retrieved along-track wind fields also reveal that the large antenna configurations are capable of identifying and quantifying the foremost dynamic features (e.g., vertical wind shear and convergence/divergence regions).

Abstract

The turbulent-scale vertical velocity structure in a continental stratocumulus cloud is studied using a 3-mm wavelength Doppler radar operating in a vertically pointing mode. The radar observations provided 30-m sampling in the vertical with 2-s averages of 10 000 samples. Vertical velocity measurements were made continuously for an 8-h period and were further supported by measurements of cloud-base height from a laser ceilometer and liquid water path from a microwave radiometer. During the beginning of the observational period, the cloud layer extended between 200 and 800 m. The vertical velocity variance profiles evolved systematically over the period from a well-defined peak in the upper part of the cloud layer of ∼0.7 m² s⁻² to a peak in the lower part of the cloud layer of 0.2 m² s⁻² as the layer became decoupled later in the observing period. The vertical velocity skewness during the well-coupled conditions was negative through most of the cloud, consistent with the presence of relatively narrow downdrafts. A positive skewness in the top 100 m of the cloud is consistent with relatively narrow penetrating updrafts at this level.

The radar vertical velocities are used to compare the directly observed updraft fractional coverage and mass flux with those obtained from the bulk statistics. These comparisons are consistent with similar comparisons made using a large eddy simulation model. The fractional coverage and the mass flux associated with coherent updraft structures are obtained for a range of criteria used to define the updrafts. A more detailed analysis of the vertical velocities in the cloud confirms the existence of well-defined downdrafts extending through the entire cloud depth. These downdrafts are estimated to have horizontal dimensions of about 200 m and appear to originate on the downshear side of updrafts. The reduction of radar reflectivity at cloud top in the downdrafts is consistent with the entrainment of drier air. This study further illustrates the utility of millimeter-wavelength radars for studying turbulence in boundary layer clouds and particularly in defining the vertical structure of coherent eddies.

Abstract

Fair-weather cumuli are fundamental in regulating the vertical structure of water vapor and entropy in the lowest 2–3 km of the earth’s atmosphere over vast areas of the oceans. In this study, a long record of profiling cloud radar observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) at Nauru Island is used to investigate cloud vertical air motion statistics over an 8-yr observing period. Appropriate processing of the observed low radar reflectivities provides radar volume samples that contain only small cloud droplets; thus, the Doppler velocities are used as air motion tracers. The technique is applied to shallow boundary layer clouds (less than 1000 m thick) during the 1999–2007 period when radar data are available. Using the boundary layer winds from the soundings obtained at the Nauru ACRF, the fair-weather cumuli fields are classified in easterly and westerly boundary layer wind regimes. This distinction is necessary to separate marine-forced (westerlies) from land-forced (easterlies) shallow clouds because of a well-studied island effect at the Nauru ACRF. The two regimes exhibit large diurnal differences in cloud fraction and cloud dynamics as manifested by the analysis of the hourly averaged vertical air motion statistics. The fair-weather cumuli fields associated with easterlies exhibit a strong diurnal cycle in cloud fraction and updraft strength and fraction, indicating a strong influence of land-forced clouds. In contrast over the fair-weather cumuli with oceanic origin, land-forced clouds are characterized by uniform diurnal cloudiness and persistent updrafts at the cloud-base level. This study provides a unique observational dataset appropriate for testing fair-weather cumulus mass flux and turbulence parameterizations in numerical models.

Abstract

Ice cloud properties are influenced by cloud-scale vertical air motion. Dynamical properties of ice clouds can be determined via Doppler measurements from ground-based, profiling cloud radars. Here, the decomposition of the Doppler velocities into reflectivity-weighted particle velocity V_t and vertical air motion w is described. The methodology is applied to high clouds observations from 35-GHz profiling millimeter wavelength radars at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) climate research facility in Oklahoma (January 1997–December 2010) and the ARM Tropical Western Pacific (TWP) site in Manus (July 1999–December 2010). The Doppler velocity measurements are used to detect gravity waves (GW), whose correlation with high cloud macrophysical properties is investigated. Cloud turbulence is studied in the absence and presence of GW. High clouds are less turbulent when GW are observed. Probability density functions of V_t , w, and high cloud macrophysical properties for the two cloud subsets (with and without GW) are presented. Air-density-corrected V_t for high clouds for which GW (no GW) were detected amounted to hourly means and standard deviations of 0.89 ± 0.52 m s⁻¹ (0.8 ± 0.48 m s⁻¹) and 1.03 ± 0.41 m s⁻¹ (0.86 ± 0.49 m s⁻¹) at SGP and Manus, respectively. The error of w at one standard deviation was estimated as 0.15 m s⁻¹. Hourly means of w averaged around 0 m s⁻¹ with standard deviations of ±0.27 (SGP) and ±0.29 m s⁻¹ (Manus) for high clouds without GW and ±0.22 m s⁻¹ (both sites) for high clouds with GW. The midlatitude site showed stronger seasonality in detected high cloud properties.

Abstract

The Amazon plays an important role in the global energy and hydrological budgets. The precipitation during the dry season (June–September) plays a critical role in maintaining the extent of the rain forest. The deployment of the first Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF-1) in the context of the Green Ocean Amazon (GOAmazon) field campaign at Manacapuru, Brazil, provided comprehensive measurements of surface, cloud, precipitation, radiation, and thermodynamic properties for two complete dry seasons (2014 and 2015). The precipitation events occurring during the nighttime were associated with propagating storm systems (nonlocal effects), while the daytime precipitation events were primarily a result of local land–atmosphere interactions. During the two dry seasons, precipitation was recorded at the surface on 106 days (43%) from 158 rain events with 82 daytime precipitation events occurring on 64 days (60.37%). Detailed comparisons between the diurnal cycles of surface and profile properties between days with and without daytime precipitation suggested the increased moisture at low and midlevels to be responsible for lowering the lifting condensation level, reducing convective inhibition and entrainment, and thus triggering the transition from shallow to deep convection. Although the monthly accumulated rainfall decreased during the progression of the dry season, the contribution of daytime precipitation to it increased, suggesting the decrease to be mainly due to reduction in propagating squall lines. The control of daytime precipitation during the dry season on large-scale moisture advection above the boundary layer and the total rainfall on propagating squall lines suggests that coarse-resolution models should be able to accurately simulate the dry season precipitation over the Amazon basin.

Abstract

Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large-drop formation (weather radar “first echo”). These measurements also complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2D) along-wind range–height indicator observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning Atmospheric Radiation Measurement Program (ARM) cloud radar (SACR) at the U.S. Department of Energy (DOE)–ARM Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger-scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous small nonprecipitating cloud elements. A new cloud identification and tracking algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2D observations (30 s) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud-element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived nonprecipitating clouds having an apparent life cycle shorter than 15 min. The advantages and disadvantages of cloud tracking using an SACR are discussed.

Abstract

The retrieval of cloud, drizzle, and turbulence parameters using radar Doppler spectra is challenged by the convolution of microphysical and dynamical influences and the overall uncertainty introduced by turbulence. A new technique that utilizes recorded radar Doppler spectra from profiling cloud radars is presented here. The technique applies to areas in clouds where drizzle is initially produced by the autoconversion process and is detected by a positive skewness in the radar Doppler spectrum. Using the Gaussian-shape property of cloud Doppler spectra, the cloud-only radar Doppler spectrum is estimated and used to separate the cloud and drizzle contributions. Once separated, the cloud spectral peak can be used to retrieve vertical air motion and eddy dissipation rates, while the drizzle peak can be used to estimate the three radar moments of the drizzle particle size distribution. The technique works for nearly 50% of spectra found near cloud top, with efficacy diminishing to roughly 15% of spectra near cloud base. The approach has been tested on a large dataset collected in the Azores during the Atmospheric Radiation Measurement Program (ARM) Mobile Facility deployment on Graciosa Island from May 2009 through December 2010. Validation of the proposed technique is achieved using the cloud base as a natural boundary between radar Doppler spectra with and without cloud droplets. The retrieval algorithm has the potential to characterize the dynamical and microphysical conditions at cloud scale during the transition from cloud to precipitation. This has significant implications for improving the understanding of drizzle onset in liquid clouds and for improving model parameterization schemes of autoconversion of cloud water into drizzle.

Abstract

Spaceborne Doppler radars have the potential to provide key missing observations of convective vertical air motions especially over the tropical oceans. Such measurements can improve understanding of the role of tropical convection in vertical energy transport and its interaction with the environment. Several millimeter wavelength Doppler radar concepts have been proposed since the 1990s. The Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) Cloud Profiling Radar (CPR) will be the first Dopplerized atmospheric radar in space but has not been optimized for Doppler measurements in deep convective clouds.

The key challenge that constrains the CPR performance in convective clouds is the range–Doppler dilemma. Polarization diversity (PD) offers a solution to this constraint by decoupling the coherency (Doppler) requirement from the unambiguous range requirement. Careful modeling of the radar signal depolarization and its impact on radar receiver channel cross talk is needed to accurately assess the performance of the PD approach.

The end-to-end simulator presented in this work allows reproduction of the signal sensed by a Doppler radar equipped with polarization diversity when overpassing realistic three-dimensional convective cells, with all relevant cross-talk sources accounted for. The notional study highlights that multiple scattering is the primary source of cross talk, highly detrimental for millimeter Doppler velocity accuracy. The ambitious scientific requirement of 1 m s⁻¹ accuracy at 500-m integration for reflectivities above −15 dBZ are within reach for a W-band radar with a 2.5-m antenna with optimal values of the pulse-pair interval between 20 and 30 μs but only once multiple scattering and ghost-contaminated regions are screened out. The identification of such areas is key for Doppler accuracies and can be achieved by employing an interlaced pulse-pair mode that measures the cross and the copolar reflectivities. To mitigate the impact of attenuation and multiple scattering, the Ka band has been considered as either alternative or additional to the W band. However, a Ka system produces worse Doppler performances than a W-band system with the same 2.5-m antenna size. Furthermore, in deep convection it results in similar levels of multiple scattering and therefore it does not increase significantly the depth of penetration. In addition, the larger footprint causes stronger nonuniform beam-filling effects. One advantage of the Ka-band option is the larger Nyquist velocity that tends to reduce the Doppler accuracies. More significant benefits are derived from the Ka band when observing precipitation not as intense as the deep convection is considered here.

This study demonstrates that polarization diversity indeed represents a very promising methodology capable of significantly reducing aliasing and Doppler moment estimate errors, two main error sources for Doppler velocity estimates in deep convective systems and a key step to achieving typical mission requirements for convection-oriented millimeter radar-based spaceborne missions.

Abstract

Unprecedented high-resolution observations of mammatus from a profiling 94-GHz Doppler radar during the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL–FACE) are presented. Because of its high sensitivity and temporal and spatial resolution, the cloud radar used was able to resolve the fine structure of individual mammatus clouds and record significant vertical Doppler velocity perturbations (−6 to +1 m s⁻¹). Strong perturbations of the Doppler velocity within the mammatus as it extends below the main cirrus cloud base are captured by the radar observations. Upward motions in the periphery of descending mammatus cores are documented. Areas of intense, small-scale turbulent mixing near the cirrus cloud base are identified using the Doppler spectrum width. Power spectra analysis of the mean Doppler velocity field supports the presence of gravity waves and the development of higher-frequency structures near the cirrus anvil base, where the mammatus clouds are observed. The observations provide strong evidence for dynamical forcing from coherent vertical motions 500 m above the cloud base contributing to the mammatus formation. The results are discussed in the context of suggested theories for mamma formation and morphology.

Abstract

Light shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.