EUREC⁴A observations from the SAFIRE ATR42 aircraft

As part of the EUREC4A (Elucidating the role of cloud-circulation coupling in climate) field campaign, which took place in January and February 2020 over the western tropical Atlantic near Barbados, the French SAFIRE ATR42 research aircraft conducted 19 flights in the lower troposphere. Each flight followed a common flight pattern that sampled the atmosphere around the cloud-base level, at different heights of the subcloud layer, near the sea surface and in the lower free troposphere. The aircraft's payload included a backscatter lidar and a Doppler cloud radar that were both horizontally oriented, a Doppler cloud radar looking upward, microphysical probes, a cavity ring-down spectrometer for water isotopes, a multiwavelength radiometer, a visible camera and multiple meteorological sensors, including fast rate sensors for turbulence measurements. With this instrumentation, the ATR characterized the macrophysical and microphysical properties of trade-wind clouds together with their thermodynamical, turbulent and radiative environment. This paper presents the airborne operations, the flight segmentation, the instrumentation, the data processing and the EUREC4A datasets produced from the ATR measurements. It shows that the ATR measurements of humidity, wind and cloud-base cloud fraction measured with different techniques and samplings are internally consistent, that meteorological measurements are consistent with estimates from dropsondes launched from an overflying aircraft (HALO), and that water isotopic measurements are well correlated with data from the Barbados Cloud Observatory. This consistency demonstrates the robustness of the ATR measurements of humidity, wind, cloud-base cloud fraction and water isotopic composition during EUREC4A. It also confirms that through their repeated flight patterns, the ATR and HALO measurements provided a statistically consistent sampling of trade-wind clouds and of their environment. The ATR datasets are freely available at the locations specified in Table 11.

Advanced open-source tools for detecting and analyzing peaks in cloud radar Doppler spectra

<p>Cloud radar Doppler spectra contain vertically highly resolved valuable information about the hydrometeors present in the cloud. A mixture of different hydrometeor types can lead to several peaks in the Doppler spectrum due to their different fall speeds, giving a hint about the size/ density/ number of the respective particles. Tools to separate and interpret peaks in cloud radar Doppler spectra have been developed in the past, but their application is often limited to certain radar settings, or the code not freely available to other users.</p> <p>We here present the effort of joining two methods, which have been developed and published (Radenz et al., 2019; Kalesse et al., 2019) with the aim to make them insensitive to instrument type and settings, and available on GitHub, and applicable to all cloud radars which are part of the ACTRIS CloudNet network.</p> <p>A supervised machine learning peak detection algorithm (PEAKO, Kalesse et al., 2019) is used to derive the optimal parameters to detect peaks in cloud radar Doppler spectra for each set of instrument settings. In the next step, these parameters are used by peakTree (Radenz et al., 2019), which is a tool for converting multi-peaked (cloud) radar Doppler spectra into a binary tree structure. PeakTree yields the (polarimetric) radar moments of each detected peak and can thus be used to classify the hydrometeor types. This allows us to analyze Doppler spectra of different cloud radars with respect to, e.g. the occurrence of supercooled liquid water or ice needles/columns with high linear depolarisation ratio (LDR).</p>

Arctic low-level clouds and their importance for radiative transfer simulations

<p>The observation of low-level stratocumulus cloud decks in the Arctic poses challenges to ground-based remote sensing. These clouds frequently occur during summer below the lowest range gate of common zenith-pointing cloud radar instruments, like the KAZR and the Mira-35. In addition, the optical thickness of these low-level clouds often do cause a complete attenuation of the lidar beam. For remote-sensing instrument synergy retrievals, as Cloudnet (Illingworth, 2007) or ARSCL (Active Remote Sensing of Clouds, Shupe, 2007), liquid-water detection in clouds is usually based on lidar backscatter. Thus, a complete attenuation can cause misclassification of mixed-phase clouds as pure-ice clouds. Moreover, the missing cloud radar information makes it difficult to derive the cloud microphysical properties, as most common retrievals are based on cloud radar reflectivity.</p> <p>A new low-level stratus detection mask (Griesche, 2020) was used to detect these clouds. The liquid-water cloud microphysical properties were derived by a simple but effective analysis of the liquid-water path. This approach was applied to remote-sensing data from a shipborne expedition performed in the Arctic summer 2017. The values calculated by applying the adjusted method improve the results of radiative transfer simulations yielding the determination of radiative closure.</p> <p> </p> <p> </p> <p>Illingworth et al. (2007). “Cloudnet”. BAMS.</p> <p>Shupe (2007). “A ground-based multisensor cloud phase classifier”. GRL.</p> <p>Griesche et al. (2020). “Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106”. AMT.</p>

A Case Study of Cloud-top Kelvin–Helmholtz Instability Waves near the Dendritic Growth Zone

Kelvin-Helmholtz instability (KH) waves have been broadly shown to affect the growth of hydrometeors within a region of falling precipitation, but formation and growth from KH waves at cloud top needs further attention. Here, we present detailed observations of cloud-top KH waves that produced a snow plume that extended to the surface. Airborne transects of cloud radar aligned with range height indicator scans from ground-based precipitation radar track the progression and intensity of the KH wave kinetics and precipitation. In-situ cloud probes and surface disdrometer measurements are used to quantify the impact of the snow plume on the composition of an underlying supercooled liquid water (SLW) cloud and the snowfall observed at the surface. KH wavelengths of 1.5 km consisted of ~750-m-wide up- and downdrafts. A distinct fluctus region appeared as a wave-breaking cloud top where the fastest updraft was observed to exceed 5 m s−1. Relatively weaker updrafts of 0.5-1.5 m s−1 beneath the fluctus and partially overlapping the dendritic growth zone were associated with steep gradients in reflectivity of −5 to 20 dBZe in as little as 500 m depths due to rapid growth of pristine planar ice crystals. The falling snow removed ~80% of the SLW content from the underlying cloud and led to a twofold increase in surface liquid equivalent snowfall rate from 0.6 to 1.3 mm hr−1. This paper presents the first known study of cloud-top KH waves producing snowfall with observations of increased snowfall rates at the surface.

Retrieval and Evaluation of Ice Water Content from the Airborne Wyoming Cloud Radar in Orographic Wintertime Clouds during SNOWNIE

The ice water content (IWC) in ice and mixed-phase clouds is retrieved from airborne Wyoming Cloud Radar (WCR) measurements aboard the University of Wyoming King Air (UWKA), which has a suite of integrated in situ IWC, optical array probes (OAP) and remote sensing measurements and provides a unique dataset for this algorithm development and evaluation. A sensitivity study with different idealized ice particle habits shows that the retrieved IWC with aggregate ice particle habit agrees the best with the in situ measurement, especially in ice or ice-dominated mixed-phase clouds with a correlation coefficient (rr) of 0.91 and close-to-zero bias. For mixed-phase clouds with ice fraction ratio less than 0.8, the variances of IWC estimates increase (rr = 0.76) and the retrieved mean IWC is larger than in situ IWC by a factor of 2. This is found to be related to the uncertainty of in situ measurements, the large cloud inhomogeneity, and the retrieval assumption uncertainty. The simulated reflectivity (Ze) and IWC relationships assuming three idealized ice particle habits and measured particle size distributions show that hexagonal columns with the same Ze have a lower IWC than aggregates, whose Ze-IWC relation is more consistent with the observed WCR Ze and in-situ IWC relation in those clouds. The 2DS images also indicate that ice particle habit transition occurs in orographic mixed-phase clouds, hence the retrieved IWC assuming modified Gamma PSD of aggregate particles tends to be biased larger in this kind of clouds.

A Dual-Frequency Cloud Radar for Observations of Precipitation and Cloud in Tibet: Description and Preliminary Measurements

A new dual-frequency Doppler polarimetric cloud radar (DDCR), working at 35-GHz (Ka-band radar, wavelength: 8.6 mm) and 94-GHz (W-band radar, wavelength: 3.2 mm) frequencies, has been in operation at Yangbajing Observatory on the Tibetan Plateau (China) for more than a year at the time of writing. Calculations and field observations show that the DDCR has a high detection sensitivity of −39.2 dBZ at 10 km and −33 dBZ at 10 km for the 94-GHz radar and 35-GHz radar, respectively. The radar reflectivity measured by the two radars illustrates different characteristics for different types of cloud: for precipitation, the attenuation caused by liquid cloud droplets is obviously more serious for the 94-GHz radar than the 35-GHz radar (the difference reaches 40 dB in some cases), and the 94-GHz radar lost signals due to serious attenuation by heavy rainfall; while for clouds dominated by ice crystals where the attenuation significantly weakens, the 94-GHz radar shows better detection ability than the 35-GHz radar. Observations in the Tibetan region show that the 35-GHz radar is prone to missing cloud near the edge, such as the cloud-top portion, resulting in underestimation of the cloud-top height (CTH). Statistical analysis based on one year of observations shows that the mean CTH measured by the 94-GHz radar in the Tibetan region is approximately 600 m higher than that measured by the 35-GHz radar. The analysis in this paper shows that the DDCR, with its dual-frequency design, provides more valuable information than simpler configurations, and will therefore play an important role in improving our understanding of clouds and precipitation in the Tibetan region.

Vertical Structure of a Snowfall Event Based on Observations From the Aircraft and Mountain Station in Beijing

An aircraft platform, ground-based disdrometer, cloud radar, radiometer, and automatic station were combined to study a snowfall case (16:30–21:00 observed by ground cloud radar) on the Yangqing Mountains in Beijing. Comparing the variation of ice habit and number concentration at aircraft altitude (2.9–3.2 km) and ground, we discussed the ice growth mechanisms in the Beijing Mountains. Results indicated that the snowfall was steady but not strong with reflectivity less than 20dBZ, and cloud top altitude less than 4.5 km. The number concentrations for both liquid and ice crystals at aircraft altitude and ground were very similar, both dominated by small particles at diameters of 0.1–1.2 mm, and the proportion of mean number concentrations at small diameters both in the aircraft and on the ground was large, peaking at 44 L−1 mm−1 and 8826 L−1 mm−1 respectively, and decreased rapidly as the diameter increased. There was no mixed phase in clouds with little liquid water. Particles were relatively regular, and were transparent with dendritic and disk-hexagonal shapes. The ice crystals and snowflakes were mainly grown by the deposition and aggregation, rarely by the riming process, and no secondary ice formation was observed.

Vertical Structure of Ice Clouds and Vertical Air Motion from Vertically Pointing Cloud Radar Measurements

The vertical structure of ice clouds and vertical air motion (Vair) were investigated using vertically pointing Ka-band cloud radar. The distributions of reflectivity (Z), Doppler velocity (VD), and spectrum width (SW) were analyzed for three ice cloud types, namely, cirrus, anvil, and stratiform clouds. The radar parameters of the cirrus clouds showed narrower distributions than those of the stratiform and anvil clouds. In the vertical structures, the rapid growth of Z and VD occurred in the layer between 8 and 12 km (roughly a layer of −40 °C to −20 °C) for all ice clouds. The prominent feature in the stratiform clouds was an elongated “S” shape in the VD near 7–7.5 km (at approximately −16 °C to −13 °C) due to a significant decrease in an absolute value of VD. The mean terminal fall velocity (Vt) and Vair in the ice clouds were estimated using pre-determined Vt–Z relationships (Vt = aZb) and the observed VD. Although the cirrus clouds demonstrated wide distributions in coefficients a and exponents b depending on cloud heights, they showed a smaller change in Z and Vt values compared to that of the other cloud types. The anvil clouds had a larger exponent than that of the stratiform clouds, indicating that the ice particle density of anvil clouds increases at a faster rate compared with the density of stratiform clouds for the same Z increment. The significant positive Vair appeared at the top of all ice clouds in range up to 0.5 m s−1, and the anvil clouds showed the deepest layer of upward motion. The stratiform and anvil clouds showed a dramatic increase in vertical air motion in the layer of 6–8 km as shown by the rapid decrease of VD. This likely caused increase of supersaturation above. A periodic positive Vair linked with a significant reduction in VD appeared at the height of 7–8 km (approximately −15 °C) dominantly in the stratiform clouds. This layer exhibited a bi-modal power spectrum produced by pre-existing larger ice particles and newly formed numerous smaller ice particles. This result raised a question on the origins of smaller ice particles such as new nucleation due to increased supersaturation by upward motion below or the seeder-feeder effect. In addition, the retrieved Vair with high-resolution data well represented a Kelvin-Helmholtz wave development.