Xuanyu Chen

Trade-wind shallow convection, a major source of uncertainty in cloud-feedback estimates, exhibits pronounced meso-scale (O(10-100 km)) variability, with organization patterns that depart strongly from the canonical “popcorn” cumuli and has thus gained the attention of many investigations in the past decade. We review these advances and present them in a unifying framework which highlights how mesoscale heterogeneities emerge from interactions between internal processes and external forcings. The internal processes include meso-scale circulations, cold-pools and convection-scale elements such as thermals, whereas external forcings are conventional large-scale cloud controlling factors (CCFs) such as sea-surface temperature gradients, wind speed and shear, the stability and humidity at inversion levels, etc. The interactions between these internal processes and external forcings result in a ubiquitous presence of mesoscale organized systems of shallow cumuli which crucially regulate cloud fraction, radiative effects and precipitation. The process-studies over the years allows provides diagnostic means to validate the representation of these processes in models. From literature, we thus also collate diagnostics to be used as a benchmark dataset on meso-scale processes and their large-scale imprint as reference for the validation of simulations, development of new parameterizations and establishment of new constrains. The benchmark dataset is based on high-resolution simulations and observations and contains products and software code to facilitate the inter-comparison with additional sources.

Several different time periods of the Atlantic Tradewind Ocean‐Atmosphere Mesoscale Interaction Campaign (ATOMIC) are isolated for examining how the depiction of tradewind marine shallow cumuli in single‐column models (SCMs) is affected by choices about model physics. The periods of interest are times when the NOAA Research Vessel Ronald H. Brown and research aircraft WP‐3D Orion were collocated, enabling verification of initial conditions and large‐scale forcing (advective) tendencies constructed using gridded data from the fifth generation ECMWF atmospheric reanalysis (ERA5). To demonstrate how this new ATOMIC test case can be used to guide model development, three parameterization suites of the NOAA Unified Forecast System are evaluated within the Common Community Physics Package Single Column Model (CCPP SCM). Calculations are also performed using a large‐eddy simulation (LES) to further bridge the gap between observations and SCM output, all of which are separated into regimes of either relatively active (“cloudy”) or inactive (“clear”) marine shallow cumuli. In both regimes tested, the parameterization suites tend to: (a) generate an unrealistic skewed or bimodal distribution of cloud fraction, (b) overestimate light to moderate rain rates, (c) produce an erroneously cold and dry boundary layer, and (d) produce higher‐than‐observed cloud tops. Results show that modifying the treatment of cloud fraction as well as increasing spatial and temporal resolution help bring the SCM more in line with observations. In addition, evidence is found to suggest that some of the remaining model biases may stem from intrinsic differences in the spatio‐temporal sampling properties of the observations versus SCM output.

This study investigates the local impact of weak sea surface temperature (SST) warm anomalies on trade cumulus cloudiness in an idealized and ensemble framework with large‐eddy simulations. The control experiment uses a spatially uniform, time‐invariant SST and mean large‐scale conditions and atmospheric forcings derived from the Atlantic Tradewind Ocean‐Atmosphere Mesoscale Interaction Campaign. The perturbed experiment adds a Gaussian warm SST anomaly (SSTA) with a 12.5 km radius and 0.5 K magnitude. The ensemble‐averaged differences between perturbation and control experiments show that cloud fraction is enhanced over the downwind half of the prescribed warm SSTA, with the enhancement peaking slightly above the environmental lifting condensation level (LCL) and then decaying with height. Compared to the upper‐level (1.5 km) cloud response, the low‐level cloud response (1 km) to the warm SSTA is stronger and occurs more systematically across different ensemble members. This near‐LCL cloud response is driven by enhanced surface buoyancy flux and buoyancy‐driven turbulence over the warm SSTA as opposed to SSTA‐induced anomalous surface convergence and mesoscale ascent. Process denial experiments indicate that the locally enhanced surface sensible and latent heat fluxes contribute almost equally to increase the near‐LCL cloudiness, even though the locally enhanced surface sensible heat flux plays a dominant role in enhancing surface buoyancy flux. These results corroborate recent satellite composite results (Chen et al., 2023, https://doi.org/10.1175/jas‐d‐23‐0075.1 ), suggesting that the observed increase of daily cloud fraction above warm SSTAs is due to more frequent turbulence‐driven formation of shallow cumuli near the cloud base.

Trade-wind cumuli play a key role in the earth’s radiative budget and are at the heart of the longstanding uncertainty in climate sensitivity estimates. Understanding the mesoscale spatial organization (20 to 2000 km) of trade cumuli is at the forefront of addressing this uncertainty. Recent observations have shown that trade cumulus cloudiness is locally modulated by the weak yet ubiquitous sea surface temperature anomalies (SSTAs) over O(10-100) km in the Northwest Tropical Atlantic trade wind region. Specifically, the daily cloud fraction is increased above daily warm SSTAs. We hypothesize that the associated condensation heating anomalies can trigger convective aggregation downwind of warm SSTAs through an inherent convective instability for nonprecipitating shallow cumulus shown in Janssens et al. 2023. To test this hypothesis, we employ a Lagrangian framework where trade cumulus trajectories are estimated using ERA5 wind fields at 925 hPa. These Lagrangian cloud trajectories are initiated over the daily centroids of warm and cold mesoscale SST anomalies identified from the NOAA GOES-POES blended SST analysis at different local times. Cloud properties and cloud organization metrics are obtained and computed from the NASA SatCORPS CERES GEO Edition 4 GOES-16 Northern Hemisphere V1.2 product. Our preliminary composite analysis on ~400 Lagrangian trajectories passing warm and cold SSTAs, respectively, in the EUREC4A/ATOMIC region suggests that there is likely a downstream response in trade cumulus cloud fraction within 6 hours (~170 km) after an air parcel passes through a warm or cold SSTA. For trajectories initiated over the daily centers of SSTAs at 1:30am LT, we found that cloud fraction reduces after experiencing warm SSTAs and increases after experiencing cold SSTAs, similar to stratocumulus cloud responses to large-scale SST perturbations. The outcome of this study will help clarify the role of mesoscale air-sea interaction in trade cumulus cloud organization.

This study investigates the impact of weak sea surface temperature (SST) warm anomalies on trade cumulus cloudiness in an idealized and ensemble framework with large-eddy simulations. The control experiment uses a spatially uniform, time-invariant SST and mean large-scale conditions and atmospheric forcings derived from the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). The perturbed experiment adds a Gaussian warm SST anomaly (SSTA) with a 12.5 km radius and 0.5 K magnitude. The ensemble-averaged differences between perturbation and control experiments show that cloud fraction is enhanced over the downwind half of the prescribed warm SSTA, with the enhancement peaking slightly above the environmental lifting condensation level (LCL) and then decaying with height. Furthermore, the low-level cloud response (<1 km) to the warm SSTA is stronger and occurs more systematically across different ensemble members. This near-LCL cloud response is driven by enhanced surface buoyancy flux and turbulence over the warm SSTA as opposed to SSTA-induced anomalous surface convergence and mesoscale upward motions. Process denial experiments indicate that the locally enhanced surface sensible and latent heat fluxes contribute almost equally to increase the near-LCL cloudiness, even though the locally enhanced surface sensible heat flux plays a dominant role in enhancing surface buoyancy flux. These results corroborate recent satellite composite results (Chen et al., 2023), suggesting that the observed increase of daily cloud fraction above warm SSTAs is due to more frequent turbulence-driven formation of shallow cumuli near the cloud base.

The impact of weak submeso- to mesoscale SST anomalies on daily averaged trade cumulus cloudiness is investigated using satellite observations that have been validated against shipboard measurements from the Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (ATOMIC). Daily spatial SST anomalies are identified from GOES–POES Blended SST analysis within a 10° × 10° region during January and February 2020. Daily averaged cloud fraction and 10-m neutral wind from satellite observations and reanalysis are composited over the identified SST features, using a common coordinate system based on the near-surface background wind directions. Composites of satellite cloud fraction show a statistically significant increase of cloudiness over the SST warm core with a reduction of cloudiness away from it. These responses are largely the same but with opposite signs over SST cold anomalies, suggesting that spatial heterogeneity in SST can locally imprint on daily cloud fraction. Composites of daily 10-m wind speed and wind convergence anomalies from both satellite and reanalysis show that surface wind speed is increased over SST warm anomalies, implying enhanced turbulence over warmer SSTs. Correspondingly, the surface convergence anomalies in these composites are located around the maximum downwind SST gradient, offset downwind from the cloudiness anomalies. These results indicate that the response of daily cloudiness to these SST anomalies is more likely generated by spatial variability of surface-driven turbulence and surface fluxes rather than that of surface or boundary layer convergence.

UAV equipped with tilt photogrammetry platform can obtain multiple angles images and establish 3D model of tilt photogrammetry, which has unique advantages in 3D intelligent construction. The purpose of this paper is to take the playground and library of the Department of Informatics of Wuhan University as the research area, obtain regional UAV images, and evaluate the residual in the spatial direction of the model by using the measured control points and model points collected in the field, so as to evaluate and analyze the accuracy of the 3D model. By analyzing the data, the root mean square error and maximum error of plane coordinates are 0.31 cm and 0.34 cm respectively, the root mean square error and maximum error of elevation are 0.07 cm and 0.11 cm respectively, and the field measured control point coordinates. Through the accuracy evaluation and analysis of the constructed three-dimensional model, it is concluded that the maximum error in X direction is 1.26 cm, the maximum error in Y direction is 1.39 cm, and the maximum error in Z direction is 1.60 cm. The results show that the accuracy of the three-dimensional model in the study area reaches centimeter-level and meets the requirements of relevant production specifications. It can provide reliable data support for construction and urban planning industries.

Ocean surface waves have been known to affect the wind stress, or air-sea momentum flux, in the open ocean under tropical cyclones. As a tropical cyclone (TC) makes landfall, the surface waves shoal as they enter the shallower coastal waters (< 30~50 m). The impacts of these shoaling surface waves on the wind stress have not yet been thoroughly investigated, but they have been postulated to be important for storm surge prediction. In this study, the WAVEWATCH III (WW3) model is used to simulate the depth modifications on the surface wave fields and the wind stress. Two wave-spectrum based wind stress estimation modules in the WW3 model are used to quantify the impact of wave shoaling on wind stress and drag coefficient under steady uniform wind and tropical cyclone conditions. The consequence of using the shoaling wave modified wind stress for modeling storm surge is investigated using the Advanced Circulation (ADCIRC) model. For the shoaling wave simulations, an accurate wave field generated by tropical cyclones in the open ocean needs to be established first. The sensitivity of tropical cyclone wave simulations in the open ocean to different spatial resolutions (1/3 °, 1/6 °, 1/12 ° and 1/24 °) is evaluated using two wave models, WW3 and Simulating WAves Nearshore. Results from both models show that the coarsest resolution (1/3 °) introduces significant errors in both the significant wave height (Hs) and the mean wavelength. Moreover, results reveal that sensitivity to spatial resolution strongly depends on storm characteristics. Waves simulated under the small and fast moving TC show the largest sensitivity to the coarse spatial resolutions. With the 1/3 ° resolution, maximum Hs can be underestimated by as much as 6% in WW3 and 16% in SWAN compared to those with the 1/24 ° resolution. The impacts of shoaling ocean surface waves on the wind stress and drag coefficient (Cd) in coastal waters are investigated with the WW3 under steady, uniform onshore wind and tropical cyclones. Our results show that under uniform onshore winds, as water depth decreases, the drag coefficient increases gradually to a peak value and then rapidly reduces compared to the deep-water value. The maximum Cd occurs roughly where depth-induced wave breaking starts. The magnitude of Cd enhancement is more significant on a steeper slope and can reach 40%, which is mainly due to the steepening of waves and reduction of the wave phase speed during the shoaling.

This study investigates the impact of shoaling wind waves on the drag coefficient in coastal waters. The shoaling wave spectrum is simulated using the WAVEWATCH III (WW3) model with shallow water physics. The high‐frequency part (spectral tail), which is unresolved in the wave model, is empirically parameterized as a function of wind speed. The full wave spectrum is then used to estimate the sea‐state‐dependent wind stress and drag coefficient. Shoaling wind waves are simulated on a sloped bottom under the idealized steady uniform wind. Experimental wind speed spans from 10 to 65 m/s, and the bottom slope is varied from 1:100 to 1:2,000. Our results show that as water depth decreases, the drag coefficient increases gradually to a peak value and then rapidly reduces compared to the deep water value. The maximum C_d value occurs roughly where depth‐induced wave breaking starts. The magnitude of C_d enhancement is more significant on a steeper slope and can reach 40%. This C_d enhancement is mainly due to steepening of waves and reduction of the wave phase speed during the shoaling. Our results also suggest significantly larger variability of C_d at a given wind speed in finite‐depth waters than in deep water.

This study investigates the impacts of shoaling waves on the wind stress and drag coefficient (C_d) in coastal waters during tropical cyclone (TC) landfall. Numerical experiments are conducted using idealized TCs with two intensities, Category 1 and 5, and two translation speeds, 5 and 10 m/s, propagating toward and normal to the shoreline over two bottom slopes, 1:200 and 1:2000. The wave spectra are simulated using the WAVEWATCH III wave model. The unresolved high‐frequency spectral tail is parameterized as a function of wind speed, and the full wave spectrum is used to calculate the wind stress and drag coefficient. Our results show that the sea state dependence of wind stress magnitude (or C_d) is significantly increased in shallow water at a given wind speed. Compared to its deep‐water value, C_d is enhanced in the right (due to shoaling fetch‐dependent waves) and in the left (due to shoaling opposing‐wind swells) TC quadrants. However, C_d is reduced in the front/rear quadrants due to weaker wind seas. The misalignment between the wind stress and wind speed directions is enhanced in shallow water. In general, the shoaling wave effects on the wind stress and C_d are much stronger on steeper bottom slopes and in faster moving storms.