Browse

Edward D. Zaron
and
Shane Elipot

Abstract

Internal waves generated by the interaction of the surface tides with topography are known to propagate long distances and lead to observable effects such as sea level variability, ocean currents, and mixing. In an effort to describe and predict these waves, the present work is concerned with using geographically-distributed data from satellite altimeters and drifting buoys to estimate and map the baroclinic sea level associated with the M2, S2, N2, K1, and O1 tides. A new mapping methodology is developed, based on a mixed L 1/L 2-norm optimization, and compared with previously-developed methods for tidal estimation from altimeter data. The altimeter and drifter data are considered separately in their roles for estimating tides and for cross-validating estimates obtained with independent data. Estimates obtained from altimetry and drifter data are found to agree remarkably well in regions where the drifter trajectories are spatially dense; however, heterogeneity of the drifter trajectories is a disadvantage when they are considered alone for tidal estimation. When the different data types are combined by using geodetic-mission altimetry to cross-validate estimates obtained with either exact-repeat altimetry or drifter data, and subsequently averaging the latter estimates, the estimates significantly improve on the previously-published HRET8.1 model, as measured by their utility for predicting sea level and surface currents in the open ocean. The methodology has been applied to estimate the annual modulations of M2, which are found to have much smaller amplitudes compared to those reported in HRET8.1, and suggest that the latter estimates of these tides were not reliable.

Restricted access
P. W. Miller
,
C. Li
,
K. Xu
,
S. Caparotta
, and
R.V. Rohli

Abstract

On 13 April 2021, a mesoscale convective system (MCS) swept across the southeastern Louisiana coast, capsizing the 39-m Seacor Power roughly 7 km from shore and leaving 13 mariners drowned or missing. In addition to the severe straight-line winds that sank the vessel, sustained surface winds >20 m s−1 behind the leading convection persisted well after the main convective band, inhibiting search and rescue efforts. Though complete historical fatality statistics are unavailable, the 13 deaths associated with this event likely represent one of the deadliest severe convective weather events in modern U.S. maritime history. This analysis integrates in-situ, remotely sensed, and reanalysis datasets to reconstruct the 2021 Seacor Power accident as well as ascertain its depiction in day-of operational convection-allowing model (CAM) guidance. Results suggest that the MCS formed along an unanalyzed coastal boundary and developed a strong meso-high to the east of the wreck as it moved offshore. The resulting zonally oriented pressure gradient directed stiff easterly winds over the wreck for several hours, even as the squall line had propagated well away from the coast. This multi-hour period of severe weather along the Louisiana coast was relatively well resolved by morning-of CAM guidance, providing optimism that future such events may be anticipated with the lead times required by vulnerable sea craft to reach safe harbor. Future severe convective weather watches containing marine zones might include a “marine” section detailing the potential sea conditions, analogous to the “aviation” section in current severe weather watches.

Restricted access
Audrey Casper
,
Emma S. Nuss
,
Christine M. Baker
,
Melissa Moulton
, and
Gregory Dusek

Abstract

Rip currents, fast offshore-directed flows, are the leading cause of death and rescues on surf beaches worldwide. The National Oceanic and Atmospheric Administration (NOAA) seeks to minimize this threat by providing rip-current hazard likelihood forecasts based on environmental conditions from the Nearshore Wave Prediction System. Rip currents come in several types, including bathymetric rip currents that form when waves break on sandbars interspersed with channels and transient rip currents that form when there are breaking waves coming from multiple directions. The NOAA model was developed and tested in an area where bathymetric rip currents may be the most prevalent type of rip current. Therefore, model performance in regions where other types of rip currents (e.g., transient rip currents) may be more ubiquitous remains unknown. To investigate the efficacy of the NOAA model guidance in the context of different rip-current types, we compared modeled rip-current probabilities with physical-based parameterizations of bathymetric and transient rip-current speeds. We also compared these probabilities to lifeguard observations of bathymetric and transient rip currents from Salt Creek Beach, California, in summer and fall 2021. We found that the NOAA model skillfully predicts a wide range of hazardous parameterized bathymetric speeds but generally underpredicts hazardous transient rip-current speeds and the hazardous rip currents observed at Salt Creek Beach. Our results demonstrate how wave parameters, including directional spread, may serve as environmental indicators of rip-current hazard. By evaluating factors that influence the skill of modeled rip-current predictions, we strive toward improved rip-current hazard forecasting.

Significance Statement

The purpose of this study is to evaluate how well the NOAA rip-current hazard model predicts different rip-current types. Accurate forecasting of rip currents is important because rip currents are the leading cause of death and rescues at surf beaches worldwide. By comparing the performance of the NOAA model to parameterized rip-current speed and lifeguard observations of rip-current strength, we highlighted the model’s decreased ability to predict hazardous transient rip currents compared to hazardous bathymetric rip currents. Because bathymetric and transient rip currents are driven by different environmental conditions, an improved hazard model must be sensitive to these different conditions to predict a greater range of hazardous rip currents.

Restricted access
Wojciech W. Grabowski
,
Yongjoon Kim
, and
Seong Soo Yum

Abstract

Numerical simulations of turbulent moist Rayleigh–Bénard convection driving CCN activation and droplet growth in the laboratory Pi chamber are discussed. Supersaturation fluctuations come from isobaric mixing of warm and humid air rising from the lower boundary with colder air featuring lower water vapor concentrations descending from the upper boundary. Lagrangian particle–based microphysics is used to represent the growth of haze CCN and cloud droplets with kinetic, solute, and surface tension effects included. Dry CCN spectra in the range between 2- and 200-nm radii from field observations are considered. Increasing the total CCN concentration from pristine to polluted conditions results in an increase in the droplet concentration and reduction in the mean droplet radius and spectral width. These are in agreement with Pi chamber observations and numerical simulations, as well as with numerous past studies of CCN cloud-base activation in natural clouds. The key result is that a relatively small fraction of the available CCN is activated in the Pi chamber fluctuating supersaturations, from about a half in the pristine case to only a 10th in the polluted case. The activation fraction as a function of the dry CCN radius is similar in all simulations, close to zero at the CCN small end, increasing to a maximum at CCN radius around 50 nm, and decreasing to close to zero at the large CCN end. This is explained as too small supersaturations to activate small CCN as in natural clouds and insufficient time to allow large CCN reaching the critical radius.

Significance Statement

Impact of turbulence on the formation and growth of cloud droplets is an important cloud physics problem. Laboratory experiments in the Michigan Technological University cloud chamber provide key insights into this problem. Numerical simulations of cloud chamber processes discussed in this paper complement laboratory experiments by providing insights difficult or impossible to obtain in the laboratory. The study contrasts the formation and growth of cloud droplets in the laboratory cloud chamber with processes taking place in natural clouds. The differences documented in this paper pose questions concerning the impact of turbulence on the formation and growth of cloud droplets as a result of interactions of clouds with their environment.

Restricted access
Manon von Kaenel
and
Steven A. Margulis

Abstract

Quantifying spatio-temporal variability in snow water resources is a challenge especially relevant in regions that rely on snowmelt for water supply. Model accuracy is often limited by uncertainties in meteorological forcings and/or suboptimal physics representation. In this study, we evaluate the performance and sensitivity of Noah-MP snow simulations from ten model configurations across 199 sites in the Western US. Nine experiments are constrained by observed meteorology to test snow-related physics options, and the tenth tests an alternative source of meteorological forcings. We find that the base case, which aligns with the National Water Model configuration and uses observations-based forcings, overestimates observed accumulated SWE at 90% of stations by a median of 9.6%. The model performs better in the accumulation season at colder, drier sites and in the melt season at wetter, warmer sites. Accumulation metrics are sensitive to model configuration in two experiments, and melt metrics in six. Alterations to model physics cause changes to median accumulation metrics from −13% to 2.3% with the greatest change due to precipitation partitioning; and to melt metrics from −10% to 3% with the greatest change due to surface resistance configuration. The experiment with alternative forcings causes even greater and wider-ranging changes (medians ranging −29% to 6%). Not all stations share the same best-performing model configuration. At most stations, the base case is outperformed by four alternative physics options which also significantly impact snow simulation. This research provides insights into the performance and sensitivity of snow predictions across site conditions and model configurations.

Restricted access
Penghui Zhang
,
Shaokun Deng
,
Peng-Fei Tuo
, and
Shengli Chen

Abstract

With the rising global demand for renewable energy sources, a great number of offshore wind farms are being built worldwide, as well as in the northern South China Sea. There is, however, limited research on the impact of offshore wind farms on the atmospheric and marine environment, particularly tropical cyclones, which frequently occur in summertime in the South China Sea. In this paper, we employ the Weather Research and Forecasting (WRF) model to investigate the impacts of large-scale offshore wind farms on tropical cyclones, using the case of Typhoon Hato, which caused severe damage in 2017. Model results reveal that maximum wind speeds in coastal areas decrease by 3–5 m/s and can reach a maximum of 8 m/s. Furthermore, the wind farms change low-level moisture convergence, causing a shift of the precipitation center towards the wind farm area and causing a significant overall reduction (up to 16%) in precipitation. Model sensitivity experiments on the area and layout of the wind farm have been carried out. Results show that larger wind farm areas and denser turbine layouts cause a more substantial decrease in the wind speed over the coast and accumulated precipitation reduction, further corroborating our findings.

Restricted access
Reese Mishler
,
Guifu Zhang
, and
Vivek N. Mahale

Abstract

Polarimetric variables such as differential phase ΦDP and its range derivative, specific differential phase K DP, contain useful information for improving quantitative precipitation estimation (QPE) and microphysics retrieval. However, the usefulness of the current operationally utilized estimation method of K DP is limited by measurement error and artifacts resulting from the differential backscattering phase δ. The contribution of δ can significantly influence the ΦDP measurements and therefore negatively affect the K DP estimates. Neglecting the presence of δ within non-Rayleigh scattering regimes has also led to the adoption of incorrect terminology regarding signatures seen within current operational K DP estimates implying associated regions of unrealistic liquid water content. A new processing method is proposed and developed to estimate both K DP and δ using classification and linear programming (LP) to reduce bias in K DP estimates caused by the δ component. It is shown that by applying the LP technique specifically to the rain regions of Rayleigh scattering along a radial profile, accurate estimates of differential propagation phase, specific differential phase, and differential backscattering phase can be retrieved within regions of both Rayleigh and non-Rayleigh scattering. This new estimation method is applied to cases of reported hail and tornado debris, and the LP results are compared to the operationally utilized least squares fit (LSF) estimates. The results show the potential use of the differential backscattering phase signature in the detection of hail and tornado debris.

Free access
Nicolas G. Alonso-De-Linaje
,
Andrea N. Hahmann
,
Ioanna Karagali
,
Krystallia Dimitriadou
, and
Merete Badger

Abstract

The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-derived wind observations into mesoscale models. We utilized the Weather Research and Forecasting (WRF) Model and applied observational nudging by integrating ASCAT data over offshore areas to achieve this. We then evaluated the accuracy of the nudged WRF Model simulations by comparing them with data from ocean oil platforms, tall masts, and a wind lidar mounted on a commercial ferry crossing the southern Baltic Sea. Our findings indicate that including satellite-derived ASCAT wind speeds through nudging enhances the correlation and reduces the error of the mesoscale simulations across all validation platforms. Moreover, it consistently outperforms the control and previously published WRF-based wind atlases. Using satellite-derived winds directly in the model simulations also solves the issue of lifting near-surface winds to wind turbine heights, which has been challenging in estimating wind resources at such heights. The comparison of the 1-yr-long simulations with and without nudging reveals intriguing differences in the sign and magnitude between the Baltic and North Seas, which vary seasonally. The pattern highlights a distinct regional pattern attributed to regional dynamics, sea surface temperature, atmospheric stability, and the number of available ASCAT samples.

Significance Statement

We aim to showcase a method for improving the precision of hub-height estimation of wind resources offshore. This involves integrating wind observations obtained from near-surface satellites into the model simulations. To assess the accuracy of the simulations, we compare the simulated winds to data gathered from multiple offshore sources, including oil platforms, tall masts, and a wind lidar installed on a commercial ferry.

Free access
Dylan W. Reif
,
Howard B. Bluestein
, and
David B. Parsons

Abstract

This study creates a composite sounding for nocturnal convection initiation (CI) events under weakly forced conditions and utilizes an idealized numerical simulation to assess the impact of atmospheric bores on these environments. Thirteen soundings were used to create this composite sounding. Common conditions associated with these weakly forced environments include a nocturnal low-level jet and a Brunt–Väisälä frequency of 0.011 s−1 above 900 hPa. The median lift needed for parcels to realize any convective instability is 490 m, the median convective available potential energy of these convectively unstable parcels is 992 J kg−1, and the median initial pressure of these parcels is 800 hPa. An idealized numerical simulation was utilized to examine the potential influence of bores on CI in an environment based on composite sounding. The characteristics of the simulated bore were representative of observed bores. The vertical velocities associated with this simulated bore were between 1 and 2 m s−1, and the net upward displacement of parcels was between 400 and 650 m. The vertical displacement of air parcels has two notable phases: lift by the bore itself and smaller-scale lift that occurs 100–150 km ahead of the bore passage. The prebore lift is between 50 and 200 m and appears to be related to low-frequency waves ahead of the bores. The lift with these waves was maximized in the low to midtroposphere between 1 and 4 km AGL, and this lift may play a role in assisting CI in these otherwise weakly forced environments.

Restricted access
Milind Sharma
,
Robin L. Tanamachi
, and
Eric C. Bruning

Abstract

The dual-polarization radar characteristics of severe storms are commonly used as indicators to estimate the size and intensity of deep convective updrafts. In this study, we track rapid fluctuations in updraft intensity and size by objectively identifying polarimetric fingerprints such as Z DR and K DP columns, which serve as proxies for mixed-phase updraft strength. We quantify the volume of Z DR and K DP columns to evaluate their utility in diagnosing temporal variability in lightning flash characteristics. Specifically, we analyze three severe storms that developed in environments with low-to-moderate instability and strong 0–6-km wind shear in northern Alabama during the 2016–17 VORTEX-Southeast field campaign. In these three cases (a tornadic supercell embedded in stratiform precipitation, a nontornadic supercell, and a supercell embedded within a quasi-linear convective system), we find that the volume of the K DP columns exhibits a stronger correlation with the total flash rate. The higher covariability of the K DP column volume with the total flash rate suggests that the overall electrification and precipitation microphysics were dominated by cold cloud processes. The lower covariability with the Z DR column volume indicates the presence of nonsteady updrafts or a less prominent role of warm rain processes in graupel growth and subsequent electrification. Furthermore, we observe that the majority of cloud-to-ground (CG) lightning strikes a carried negative charge to the ground. In contrast to findings from a tornadic supercell over the Great Plains, lightning flash initiations in the Alabama storms primarily occurred outside the footprint of the Z DR and K DP column objects.

Significance Statement

This study quantifies the correlation between mixed-phase updraft intensity and total lightning flash rate in three severe storms in northern Alabama. In the absence of direct updraft velocity measurements, we use polarimetric signatures, such as Z DR and K DP columns, as proxies for updraft strength. Our analysis of polarimetric radar and lightning mapping array data reveals that the lightning flash rate is more highly correlated with the K DP column volume than with the Z DR column volume in all three storms examined. This contrasts with previous findings in storms over the central Great Plains, where the Z DR column volume showed higher covariability with flash rate. Interestingly, lightning initiation in the Alabama storms mainly occurred outside the Z DR and K DP column areas, contrary to previous findings.

Open access