Multifrequency radar observations of clouds and precipitation including the G-band

Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research, something that until now was only discussed in theory. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the Ka–G pairing can generate differential reflectivity signal several decibels larger than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes. The observations also showed that G-band signals experience non-Rayleigh scattering in regions where Ka- and W-band signal do not, thus demonstrating the potential of G-band radars for sizing sub-millimeter ice crystals and droplets. Observed peculiar radar reflectivity patterns also suggest that G-band radars could be used to gain insight into the melting behavior of small ice crystals. G-band signal interpretation is challenging, because attenuation and non-Rayleigh effects are typically intertwined. An ideal liquid-free period allowed us to use triple-frequency Ka–W–G observations to test existing ice scattering libraries, and the results raise questions on their comprehensiveness. Overall, this work reinforces the importance of deploying radars (1) with sensitivity sufficient enough to detect small Rayleigh scatters at cloud top in order to derive estimates of path-integrated hydrometeor attenuation, a key constraint for microphysical retrievals; (2) with sensitivity sufficient enough to overcome liquid attenuation, to reveal the larger differential signals generated from using the G-band as part of a multifrequency deployment; and (3) capable of monitoring atmospheric gases to reduce related uncertainty

Data relevant to Going mobile to address emerging climate equity needs in the heterogeneous urban environment

During its first few deployments, the mobile observatory has captured unique observations. Among them are vertical air motion measurements along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY which are shown to hold information critical to improving our understanding of the role of buildings in the ventilation of heat, pollution, and contaminants in urban street channels. Also, air temperature measurements collected during travel along a transect between Suffolk County and Manhattan, NY offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the urban dome across different communities

Observations of shallow trade-wind cumulus cloudiness and mass flux variability and their relationship to boundary layer structure

Oceanic cumuli are ubiquitous in the subtropics and help regulate the thermodynamic structure of the lower troposphere and the large-scale tropical circulation. Yet, observations of the vertical structure of marine cumulus cloudiness and mass flux remain sparse. Fortunately, modern island-based remote sensors more specifically, the Barbados zenith cloud radar posses the sensitivity to study hydrometers which, when small enough, can also be used as tracers of air motion.Over the 2-years analyzed, the daily cloud fraction profile of cumulus non-precipitating (peak 4.5 % at 710 m), precipitating without (peak 2.3 % at 809 m) and with attached stratiform layers (peak 1 % at 1679 m) oscillate slightly (~ 3 %). Precipitating cumuli with stratiform outflows are deeper and contain more abrupt vertical variations in reflectivity and Doppler velocity than other precipitating cumuli. Non-precipitating cumuli exhibit an elevated reflectivity core and an ascendant center surrounded by a subsiding shell. Bulk (3 h) statistics reveal that these cloud are active and organized. They contain 79 % updrafts with 86 % of them being organized in large coherent structures contributing to a maximum updraft mass flux of 0.008- 0.036 kgm-2s-1 just above cloud base. Alternatively, downdrafts contribute insignificant mass flux and show little vertical and temporal variability (0.000-0.007 kgm-2s-1). Together with complementary Raman lidar information, normalized updraft mass flux profiles suggest that updraft mass flux profile slope is inversely related to environmental relative humidity. Similarly, the presence of stratiform detrained layers coincides with moistening under the inversion layer. Altogether, the analysis presented here is useful for evaluating and constraining the representation of cloudiness and mass flux schemes in numerical models.Les cumulus océaniques sont omniprésents dans les régions subtropicales et aident à réguler la structure thermodynamique de la basse troposphère ainsi que la circulation tropicale à grande. Pourtant, une pénurie d'observations de la distribution verticale des cumulus océaniques et de leur flux de persiste. Par chance, les capteurs à distance modernes basés sur des iles, plus précisément le radar de nuage vertical de la Barbade possède la sensibilité pour étudier les hydrométéores qui, quand ils sont assez petits, peuvent aussi être utilisés pour retracer le mouvement de l'air.Au cours des 2 ans analysés, le profile de fraction nuageuse des cumulus sans précipitation (maximum 4.5 % à 710 m), avec précipitation sans (maximum 2.3 % à 809 m) et avec segments stratiformes attachés (maximum 1 % à 1679 m) oscille légèrement (~ 3 %). Les cumulus avec précipitation et couche stratiforme detraînée sont plus épais et contiennent des variations de réflectivité et de vitesse Doppler plus abruptes que les autres cumulus pluvieux. Les cumulus sans précipitation possèdent un noyau de réflectivité surélevé et un centre ascendant entouré par une coquille descendante. Des statistiques globale (3 h) montrent que ces nuages sont actifs et organisés. Ils contiennent 79 % de courants ascendants et 86 % d'entre eux sont organisés en de larges structures cohérentes qui contribuent au flux de masse maximum de 0.008-0.036 kgm-2s-1 juste au dessus de la base des nuages. D'un autre côté, les courants descendants contribuent un flux de masse négligeable and montrent peu de variations verticales et temporelles (0.000-0.007 kgm-2s-1). Complémenter d'information du lidar Raman, les profiles de flux de masse ascendant normalisés suggèrent que l'inclinaison du profile de flux de masse ascendant est inversement proportionnel à l'humidité environnementale. De façon similaire, la présence de couches stratiformes detraînées coïncide avec l'humidification de l'environnent sous la couche d'inversion. Considérant ceci, l'analyse présentée ici est utile pour évaluer et restreindre la représentation des nuages et les parametrisations de flux de masse dans les modèles numériques

Stony Brook Radar Observatory radar and lidar data for February 25, 2020

Observations collected during the 25-February-2020 deployment of the Vapor In-Cloud Profiling Radar at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka, W-and G-band radar, revealed that the differential reflectivity from Ka-G-band pair provides larger signals than the traditional Ka-W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes. The data include: 1) Vapor In-Cloud Profiling Radar (VIPR) collected on 24-26 February 2020 2) W-band profiling radar (ROGER) collected on 25 February 2020 3) Ka-band Scanning Polarimetric Radar (KASPR) vertically-pointing measurements on 25 February 2020 4) SBU Phased Array Radar (SKYLER) vertically-pointing measurements on 25 February 2020 5) Lufft CHM lidar collected on 25 February 202

Data for Paper Agile adaptive radar sampling of fast-evolving atmospheric phenomena guided by satellite imagery and surface cameras

The data include: Stony Brook University phased array radar (SKYLER) data collected on August 21, 2019 and September 2, 2019. Stony Brook University Ka-band scanning polarimetric cloud radar (KASPR) data collected on August 21, 2019, August 25, 2019, and September 2, 2019. Those data were used in the paper Agile adaptive radar sampling of fast-evolving atmospheric phenomena guided by satellite imagery and surface cameras submitted to Geophysical Research Letters

Mind the gap - Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars

Ground-based radar observations show that, over the eastern North Atlantic, 50 % of warm marine boundary layer (WMBL) hydrometeors occur below 1.2 km and have reflectivities of < −17 dBZ, thus making their detection from space susceptible to the extent of surface clutter and radar sensitivity. Surface clutter limits the ability of the CloudSat cloud profiling radar (CPR) to observe the true cloud base in ∼52 % of the cloudy columns it detects and true virga base in ∼80 %, meaning the CloudSat CPR often provides an incomplete view of even the clouds it does detect. Using forward simulations, we determine that a 250 m resolution radar would most accurately capture the boundaries of WMBL clouds and precipitation; that being said, because of sensitivity limitations, such a radar would suffer from cloud cover biases similar to those of the CloudSat CPR. Observations and forward simulations indicate that the CloudSat CPR fails to detect 29 %–43 % of the cloudy columns detected by ground-based sensors. Out of all configurations tested, the 7 dB more sensitive EarthCARE CPR performs best (only missing 9.0 % of cloudy columns) indicating that improving radar sensitivity is more important than decreasing the vertical extent of surface clutter for measuring cloud cover. However, because 50 % of WMBL systems are thinner than 400 m, they tend to be artificially stretched by long sensitive radar pulses, hence the EarthCARE CPR overestimation of cloud top height and hydrometeor fraction. Thus, it is recommended that the next generation of space-borne radars targeting WMBL science should operate interlaced pulse modes including both a highly sensitive long-pulse mode and a less sensitive but clutter-limiting short-pulse mode

(GO)(2)-SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO) 2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise. Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar-radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water-for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40 %. So, while hydrometeor-phase maps determined in forward space are very different from model reality they capture the information sensors can provide and thereby enable objective model evaluation

Mind the gap - Part 2: Improving quantitative estimates of cloud and rain water path in oceanic warm rain using spaceborne radars

The intrinsic small spatial scales and low reflectivity structure of oceanic warm precipitating clouds suggest that millimeter spaceborne radars are best suited to providing quantitative estimates of cloud and rain liquid water paths (LWPs). This assertion is based on their smaller horizontal footprint; high sensitivities; and a wide dynamic range of path-integrated attenuations associated with warmrain cells across the millimeter wavelength spectrum, with diverse spectral responses to rain and cloud partitioning. State-of-the-art single-frequency radar profiling algorithms of warm rain seem to be inadequate because of their dependence on uncertain assumptions about the rain-cloud partitioning and because of the rain microphysics. Here, high-resolution cloud-resolving model simulations for the Rain in Cumulus over the Ocean field study and a spaceborne forward radar simulator are exploited to assess the potential of existing and future spaceborne radar systems for quantitative warm-rain microphysical retrievals. Specifically, the detrimental effects of nonuniform beam filling on estimates of path-integrated attenuation (PIA), the added value of brightness temperature (TB) derived adopting radiometric radar modes, and the performances of multifrequency PIA and/or TB combinations when retrieving liquid water paths partitioned into cloud (c-LWPs) and rain (r-LWPs) are assessed. Results show that (1) Ka-and W-band TB values add useful constraints and are effective at lower LWPs than the same-frequency PIAs; (2) matched-beam combined TB values and PIAs from single-frequency or multifrequency radars can significantly narrow down uncertainties in retrieved cloud and rain liquid water paths; and (3) the configuration including PIAs, TB values and near-surface reflectivities for the Ka-band-W-band pairs in our synthetic retrieval can achieve an RMSE of better than 30 % for c-LWPs and r-LWPs exceeding 100 g m-2

Mind the gap - Part 2: Improving quantitative estimates of cloud and rain water path in oceanic warm rain using spaceborne radars

The intrinsic small spatial scales and low reflectivity structure of oceanic warm precipitating clouds suggest that millimeter spaceborne radars are best suited to providing quantitative estimates of cloud and rain liquid water paths (LWPs). This assertion is based on their smaller horizontal footprint; high sensitivities; and a wide dynamic range of path-integrated attenuations associated with warmrain cells across the millimeter wavelength spectrum, with diverse spectral responses to rain and cloud partitioning. State-of-the-art single-frequency radar profiling algorithms of warm rain seem to be inadequate because of their dependence on uncertain assumptions about the rain-cloud partitioning and because of the rain microphysics. Here, high-resolution cloud-resolving model simulations for the Rain in Cumulus over the Ocean field study and a spaceborne forward radar simulator are exploited to assess the potential of existing and future spaceborne radar systems for quantitative warm-rain microphysical retrievals. Specifically, the detrimental effects of nonuniform beam filling on estimates of path-integrated attenuation (PIA), the added value of brightness temperature (TB) derived adopting radiometric radar modes, and the performances of multifrequency PIA and/or TB combinations when retrieving liquid water paths partitioned into cloud (c-LWPs) and rain (r-LWPs) are assessed. Results show that (1) Ka-and W-band TB values add useful constraints and are effective at lower LWPs than the same-frequency PIAs; (2) matched-beam combined TB values and PIAs from single-frequency or multifrequency radars can significantly narrow down uncertainties in retrieved cloud and rain liquid water paths; and (3) the configuration including PIAs, TB values and near-surface reflectivities for the Ka-band-W-band pairs in our synthetic retrieval can achieve an RMSE of better than 30 % for c-LWPs and r-LWPs exceeding 100 g m-2