EUREC&amp;lt;sup&amp;gt;4&amp;lt;/sup&amp;gt;A's &amp;lt;i&amp;gt;HALO&amp;lt;/i&amp;gt;

Konow, Heike; Ewald, Florian; George, Geet; Jacob, Marek; Klingebiel, Marcus; Kölling, Tobias; Luebke, Anna; Mieslinger, Theresa; Pörtge, Veronika; Radtke, Jule; Schäfer, Michael; Schulz, Hauke; Vogel, Raphaëla; Wirth, Martin; Bony, Sandrine; Crewell, Susanne; Ehrlich, André; Forster, Linda; Giez, Andreas; Gödde, Felix; Groß, Silke; Gutleben, Manuel; Hagen, Martin; Hirsch, Lutz; Jansen, Friedhelm; Lang, Theresa; Mayer, Bernhard; Mech, Mario; Prange, Marc; Schnitt, Sabrina; Vial, Jessica; Walbröl, Andreas; Wendisch, Manfred; Wolf, Kevin; Zinner, Tobias; Zöger, Martin; Ament, Felix; Stevens, Björn

doi:10.5194/essd-13-5545-2021

Cited by 31 publications

(19 citation statements)

References 20 publications

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“…More details about the circles flown by HALO and P3 are provided by Konow et al . (2021) and Pincus et al . (2021), respectively, whereas the description of the circle products from the JOANNE dataset is found in George et al .…”

Section: Eurec4$$ {}^4 $$A/atomic Datamentioning

confidence: 95%

“…We also explored dropsonde measurements from the 15 circles flown by the P3 aircraft, which provide the advantage of night-time sampling, but, as the P3 flew only two subsequent circles each day, important information about time evolution is missing. More details about the circles flown by HALO and P3 are provided by Konow et al (2021) and Pincus et al (2021), respectively, whereas the description of the circle products from the JOANNE dataset is found in George et al (2021b). The circle products include area-averaged quantities of parameter gradients, divergence, and vertical velocity.…”

Section: Joanne Dropsondesmentioning

confidence: 99%

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The frictional layer in the observed momentum budget of the trades

Nuijens

Savazzi

Boer

et al. 2022

Quart J Royal Meteoro Soc

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Profiles of eddy momentum flux divergence are calculated as the residual in the momentum budget constructed from airborne circular dropsonde arrays (∼ 220 km) for thirteen days during the EUREC 4 A/ATOMIC field study. The observed dynamical forcing averaged over all flights agrees broadly with ECMWF IFS forecasts. In the direction of the flow, a mean flux divergence (friction) exists over a 1.5 km deep Ekman layer, and a mean flux convergence (acceleration) is present near cloud tops. The friction is counter-gradient between 1 -1.5 km, where vertical wind shear exceeds the observed thermal wind. From the frictional profile, a 10 m momentum flux of ∼ 0.1 Nm −2 is derived, in line with Saildrone turbulence measurements. A momentum flux divergence in the cross-wind direction is pronounced near the surface and acts to veer the wind, opposing the friction-induced cross-isobaric wind turning. Weaker friction and upper level acceleration of easterly flow is observed when stronger winds and more vigorous convection prevail. Turbulence measurements on board the SAFIRE ATR-42 (ATR) aircraft and the UAS CU RAAVEN reveal pronounced spatial variability of momentum fluxes, with a non-negligible contribution of meso-scales (5 -60 km). The findings highlight the non-trivial impact of turbulence, convection and mesoscale flows in the presence of diverse cloud fields on the depth and strength of the frictional layer.

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Section: Eurec4$$ {}^4 $$A/atomic Datamentioning

confidence: 95%

Section: Joanne Dropsondesmentioning

confidence: 99%

The frictional layer in the observed momentum budget of the trades

Nuijens

Savazzi

Boer

et al. 2022

Quart J Royal Meteoro Soc

Self Cite

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“…An additional description of the HALO flight and technical characteristics of the instruments can be found in Konow et al . (2021). Combining as many HALO measurements as possible, together with the satellite measurements described hereafter, leverages each instrument's strengths and weaknesses and provides a spread in the estimates of the investigated parameters.…”

Section: Case Study High‐resolution Observations and Modelmentioning

confidence: 99%

“…During EUREC

{}^4

A, HALO was deployed east of Barbados (Konow et al ., 2021; Stevens et al ., 2021). Each flight was planned with a circle track designed to capture the mesoscale variability of the atmosphere and to measure the mesoscale vertical velocity (Bony and Stevens, 2019).…”

Section: Case Study High‐resolution Observations and Modelmentioning

confidence: 99%

Flower trade‐wind clouds are shallow mesoscale convective systems

Dauhut

Couvreux

Bouniol

et al. 2022

Quart J Royal Meteoro Soc

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Flower clouds are trade‐wind shallow cumuli, with tops reaching 3 km altitude, organised into 100‐km wide clusters. They are widespread over the subtropics and associated with the strongest cloud radiative effect among trade‐wind cumuli mesoscale organisations. In the context of large uncertainty in climate projections due to the representation of shallow clouds, major knowledge gaps remain about the global impact of mesoscale organisations and the local processes driving them. Here, the processes governing the flower organisation are investigated based on the case study of February 2, 2020 from the Elucidate the Couplings Between Clouds, Convection, and Circulation (EUREC4$$ {}^4 $$A) campaign, east of Barbados. One flower cloud is simulated with a large‐eddy simulation (LES), using the Meso‐NH model at 100‐m horizontal grid spacing, and validated extensively with high‐resolution observations from the High Altitude and Long‐range Research Aircraft (HALO), dropsondes, and satellite measurements. The cloud‐top altitudes exhibit a trimodal distribution. The processes shaping flower clouds are wide cold pools and cloudy updrafts organised in one large arc at the western edge. These updrafts are responsible for the highest cloud tops and drive most of the vertical turbulent fluxes of sensible heat, humidity, and momentum. A mesoscale circulation takes place at the scale of the flower clouds and makes them very similar to deep mesoscale convective systems.

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“…to measurements of meso-scale vertical pressure velocities ω obtained from dropsonde measurements of the EUREC 4 A field campaign. During EUREC 4 A, the HALO aircraft flew 69 circles of about 200 km diameter launching 12 dropsondes per circle (Konow et al, 2021;George et al, 2021). Using the method of Bony and Stevens (2019), circle-integrated profiles of divergence allow for a deduction of ω, some first EUREC 4 A averaged results of which are presented by .…”

Section: Clear-skymentioning

confidence: 99%

How adequately are elevated moist layers represented in reanalysis and satellite observations?

Prange

Buehler

Brath

2022

Preprint

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Abstract. We assess the representation of Elevated Moist Layers (EMLs) in ERA5 reanalysis, the IASI L2 retrieval Climate Data Record (CDR) and the AIRS-based CLIMCAPS-Aqua L2 retrieval. EMLs are free tropospheric moisture anomalies that typically occur in the vicinity of deep convection in the tropics. EMLs significantly effect the spatial structure of radiative heating, which is considered a key driver for meso-scale dynamics, in particular convective aggregation. To our knowledge, the representation of EMLs in the mentioned data products have not been explicitly studied, a gap we address in this work. We assess the different datasets' capability of capturing EMLs by collocating them with 2146 radiosondes launched from Manus Island within the Western Pacific warmpool, a region where EMLs occur particularly often. We identify and characterise moisture anomalies in the collocated datasets in terms of moisture anomaly strength, vertical thickness and altitude. By comparing the distributions of these characteristics, we deduce what specific EML characteristics the datasets are capturing well and what they are missing. Distributions of ERA5 moisture anomaly characteristics match those of the radiosonde dataset quite well and remaining biases can be removed by applying a 1 km moving average to the radiosonde profiles. We conclude that ERA5 is a suitable reference dataset for investigating EMLs. We find that the IASI L2 CDR is subject to stronger smoothing than ERA5 with moisture anomalies being on average 13 % weaker and 28 % thicker than collocated ERA5 anomalies. The CLIMCAPS L2 product shows significant biases in its mean vertical humidity structure compared to the three other investigated datasets. These biases manifest as an underestimation of mean moist layer height of about 1.3 km compared to the three other datasets, a general mid-tropospheric moist bias and an upper tropospheric dry bias. Biases found in the all-sky scenes do not change significantly when limiting the analysis to clear-sky scenes. We calculate radiatively driven vertical velocities derived from longwave heating rates to estimate the dynamical effect of the moist layers. Moist-layer-associated vertical velocity values derived from GRUAN soundings range between 2 to 3 hPa hour-1 while mean meso-scale pressure velocities from the EUREC4A field campaign range between 1 to 2 hPa hour-1, highlighting the dynamical significance of EMLs. Subtle differences in the representation of moisture and temperature structures in ERA5 and the satellite datasets create large relative errors in ωrad on the order of 40–80 % with reference to GRUAN, indicating limited usefulness of these datasets to assess the dynamical impact of EMLs.

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EUREC<sup>4</sup>A's <i>HALO</i>

Cited by 31 publications

References 20 publications

The frictional layer in the observed momentum budget of the trades

The frictional layer in the observed momentum budget of the trades

Flower trade‐wind clouds are shallow mesoscale convective systems

How adequately are elevated moist layers represented in reanalysis and satellite observations?

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