The RAPSODI (<ani:underline>R</ani:underline>adiosonde <ani:underline>A</ani:underline>tmospheric <ani:underline>P</ani:underline>rofiles from <ani:underline>S</ani:underline>hip and island platforms during <ani:underline>O</ani:underline>RCESTRA, collected to <ani:underline>D</ani:underline>ecipher the <ani:underline>I</ani:underline>TCZ) radiosonde dataset was collected during the ORCESTRA field campaign in August and September 2024. It is designed to investigate the mechanisms linking mesoscale tropical convection to tropical waves and to air-sea heat and moisture exchanges that regulate convection and tropical cyclone formation. The campaign began at the Instituto Nacional de Meteorologia e Geofísica (INMG) on Sal in the Cape Verde Islands, continued with ship-based observations aboard the German research vessel R/V Meteor during an Atlantic transect, and concluded at the Barbados Cloud Observatory (BCO) in the eastern Caribbean. Over the 52 d campaign, a total of 624 radiosondes were launched at high temporal frequency (typically every three hours), capturing high-resolution vertical profiles of temperature, humidity, pressure, and winds from three complementary platforms. The dataset encompasses raw, quality-controlled, and vertically gridded data, is detailed in this paper and offers a valuable resource for investigating the atmospheric structure and processes shaping tropical convection and the intertropical convergence zone (ITCZ). The datasets generated in this study include raw radiosonde measurements (Level 0), oscillating and merged radiosonde profiles (Level 1), and vertically gridded profiles (Level 2), which are publicly available via the ORCESTRA data portal and DOI-referenced archives (; https://ipfs.io/ipns/latest.orcestra-campaign.org/raw/BCO/radiosondes/,; https://ipfs.io/ipns/latest.orcestra-campaign.org/raw/INMG/radiosondes/,; https://ipfs.io/ipns/latest.orcestra-campaign.org/raw/METEOR/radiosondes/,; https://doi.org/10.82246/BAFYBEIHXRAJOJUQZYX65QSO7AMA6NGVREETKDW3HQZX3SDZFB7LCMG6VAQ,; https://doi.org/10.82246/BAFYBEIA34AUWYVBH2RQ7CN7AGUZZ7PULQ2KRDDDIEESM6KPYSI,; https://doi.org/10.82246/BAFYBEID7CNW62ZMZFGXCVC6Q6FA267A7IVK2W,).

The HALO-(AC)³ aircraft campaign was carried out in March and April 2022 over the Norwegian and Greenland seas, the Fram Strait, and the central Arctic Ocean. Three research aircraft - the High Altitude and Long Range Research Aircraft (HALO), Polar 5, and Polar 6 - performed 54 partly coordinated research flights on 23 flight days over areas of open ocean, the marginal sea ice zone (MIZ), and the central Arctic sea ice. The general objective of the research flights was to quantify the evolution of air mass properties during moist and warm-air intrusions (WAIs) and cold-air outbreaks (CAOs). To obtain a comprehensive data set, the three aircraft operated following different strategies. HALO was equipped with active and passive remote sensing instruments and dropsondes to cover the regional evolution of cloud and thermodynamic processes. Polar 5 carried a similar remote sensing payload to HALO, and Polar 6 was instrumented with in situ cloud, aerosol, and trace gas instruments focusing on the initial air mass transformation close to the MIZ. The processed, calibrated, and validated data are published in the World Data Center PANGAEA as instrument-separated data subsets and listed in aircraft-separated collections for HALO (, https://doi.org/10.1594/PANGAEA.968885), Polar 5 (, https://doi.org/10.1594/PANGAEA.968883), and Polar 6 (, https://doi.org/10.1594/PANGAEA.968884). A detailed overview of the available data sets is provided here. Furthermore, the campaign-specific instrument setup, the data processing, and quality are summarized. Based on measurements conducted during a specific CAO, it is shown that the scientific analysis of the HALO-(AC)³ data benefits from the coordinated operation of the three aircraft.

Understanding the drivers of cloud organization is crucial for accurately estimating cloud feedbacks and their contribution to climate warming. Shallow mesoscale circulations are thought to play an important role in cloud organization, but they have not been observed. Here we present observational evidence for the existence of shallow mesoscale overturning circulations using divergence measurements made during the EUREC ⁴A field campaign in the North Atlantic trades. Meteorological re-analyses reproduce the observed low-level divergence well and confirm the circulations to be mesoscale features (around 200 km across). We find that the shallow mesoscale circulations are associated with large variability in mesoscale vertical velocity and amplify moisture variance at the cloud base. Through their modulation of cloud-base moisture, the circulations influence how efficiently the subcloud layer dries, thus producing moist ascending branches and dry descending branches. The observed moisture variance differs from expectations from large-eddy simulations, which show the largest variance near the cloud top and negligible subcloud variance. The ubiquity of shallow mesoscale circulations, and their coupling to moisture and cloud fields, suggests that the strength and scale of mesoscale circulations are integral to determining how clouds respond to climate change.

Shallow cumulus clouds in the trade-wind regions cool the planet by reflecting solar radiation. The response of trade cumulus clouds to climate change is a key uncertainty in climate projections ^1–4. Trade cumulus feedbacks in climate models are governed by changes in cloud fraction near cloud base ^5,6, with high-climate-sensitivity models suggesting a strong decrease in cloud-base cloudiness owing to increased lower-tropospheric mixing ^5–7. Here we show that new observations from the EUREC ⁴A (Elucidating the role of cloud-circulation coupling in climate) field campaign ^8,9 refute this mixing-desiccation hypothesis. We find the dynamical increase of cloudiness through mixing to overwhelm the thermodynamic control through humidity. Because mesoscale motions and the entrainment rate contribute equally to variability in mixing but have opposing effects on humidity, mixing does not desiccate clouds. The magnitude, variability and coupling of mixing and cloudiness differ markedly among climate models and with the EUREC ⁴A observations. Models with large trade cumulus feedbacks tend to exaggerate the dependence of cloudiness on relative humidity as opposed to mixing and also exaggerate variability in cloudiness. Our observational analyses render models with large positive feedbacks implausible and both support and explain at the process scale a weak trade cumulus feedback. Our findings thus refute an important line of evidence for a high climate sensitivity ^10,11.

As part of the EUREC4A field campaign which took place over the tropical North Atlantic during January-February 2020, 1215 dropsondes from the HALO and WP-3D aircraft were deployed through 26 flights to characterize the thermodynamic and dynamic environment of clouds in the trade-wind regions. We present JOANNE (Joint dropsonde Observations of the Atmosphere in tropical North atlaNtic meso-scale Environments), the dataset that contains these dropsonde measurements and the products derived from them. Along with the raw measurement profiles and basic post-processing of pressure, temperature, relative humidity and horizontal winds, the dataset also includes a homogenized and gridded dataset with 10 m vertical spacing. The gridded data are used as a basis for deriving diagnostics of the area-averaged mesoscale circulation properties such as divergence, vorticity, vertical velocity and gradient terms, making use of sondes dropped at regular intervals along a circular flight path. A total of 85 such circles, 1/4 222 km in diameter, were flown during EUREC4A. We describe the sampling strategy for dropsonde measurements during EUREC4A, the quality control for the data, the methods of estimation of additional products from the measurements and the different post-processed levels of the dataset. The dataset is publicly available (10.25326/246, ) as is the software used to create it (10.5281/zenodo.4746312, ).

We use estimates of mesoscale vertical velocity and collocated cloud measurements from the second Next-Generation Aircraft Remote Sensing for Validation campaign (NARVAL2) in the tropical North Atlantic to show the observed impact of mesoscale vertical motion on tropical clouds. Our results not only confirm previously untested hypotheses about the role of dynamics being nonnegligible in determining cloudiness, but go further to show that at the mesoscale, the dynamics has a more dominant control on cloudiness variability than thermodynamics. A simple mass-flux estimate reveals that mesoscale vertical velocity at the subcloud-layer top explains much of the variations in peak shallow cumulus cloud fraction. In contrast, we find that thermodynamic cloud-controlling factors, such as humidity and stability, are unable to explain the variations in cloudiness at the mesoscale. Thus, capturing the observed variability of cloudiness may require not only a consideration of thermodynamic factors, but also dynamic ones such as the mesoscale vertical velocity. SIGNIFICANCE STATEMENT: Knowing how low clouds link to atmospheric circulation over a few hundred kilometers will reduce current uncertainties in the sensitivity of Earth's climate to warming. Such investigations have previously been limited by lack of circulation measurements at the mesoscale. However, using measurements now available from a recent field campaign over the tropical North Atlantic along with cloud measurements, we demonstrate how atmospheric vertical motion especially in the lower layers can influence the extent and structure of clouds. We find that the kinematics have a more dominant control on low-level cloudiness than conventionally studied thermodynamics. Our results show why it is important to focus attention to the circulation to improve our understanding of the variability in cloudiness.