Simulated Storm Intensity Research Articles

How Much Marsh Restoration Is Enough to Deliver Wave Attenuation Coastal Protection Benefits?

As coastal communities grow more vulnerable to sea-level rise and increased storminess, communities have turned to nature-based solutions to bolster coastal resilience and protection. Marshes have significant wave attenuation properties and can play an important role in coastal protection for many communities. Many restoration projects seek to maximize this ecosystem service but how much marsh restoration is enough to deliver measurable coastal protection benefits is still unknown. This question is critical to guiding assessments of cost effectiveness and for funding, implementation, and optimizing of marsh restoration for risk reduction projects. This study uses SWAN model simulations to determine empirical relationships between wave attenuation and marsh vegetation. The model runs consider several different common marsh morphologies (including systems with channels, ponds, and fringing mudflats), vegetation placement, and simulated storm intensity. Up to a 95% reduction in wave energy is seen at as low as 50% vegetation cover. Although these empirical relationships between vegetative cover and wave attenuation provide essential insight for marsh restoration, it is also important to factor in lifespan estimates of restored marshes when making overall restoration decisions. The results of this study are important for coastal practitioners and managers seeking performance goals and metrics for marsh restoration, enhancement, and creation.

A Modeling Investigation of the Potential Impacts of Pollution Aerosols on Hurricane Harvey

AbstractWe examine the potential role of aerosol pollution on the rainfall and intensity of hurricane Harvey. For this study, we use the global model, OLAM, with aerosol estimates from the global atmospheric chemistry model GEOS-Chem. Two sets of simulations of hurricane Harvey were performed. Simulations in the first set cover the intensification phase of Harvey until initial landfall in Texas and focus on the sensitivity of storm track and intensity, while simulations in the second set examine the sensitivity of storm track and precipitation during the period after initial landfall when record flooding occurred near Houston. During each period, simulations were performed with no anthropogenic sources of aerosol, with both natural and anthropogenic aerosol sources, and with both sources enhanced ten times.During the rapid intensification phase, the results indicate that aerosol amounts had very little impact on storm motion. Moreover, very little difference was found on the intensity of the simulated storm to aerosol amounts for the no-anthropogenic vs the GEOS-Chem estimated amounts with anthropogenic sources. However, when both natural and anthropogenic aerosol amounts were enhanced ten times, the simulated storm intensity was enhanced appreciably in terms of minimum sea-level pressure.During the second period of the simulation, through which Harvey remained a tropical storm, the main result was that very little sensitivity was found in precipitation or any other TC characteristic to aerosol concentrations. We cannot definitively state why the individual convective cells did not respond to high aerosol concentrations during this phase of the storm. However, the abundant precipitation in all three simulations scavenged the vast majority of aerosol as it flowed radially inward, and we speculate that this modulated the potential impact of aerosols on the inner TC and eyewallOverall, the simulated response of hurricane Harvey to aerosols was far less spectacular than what has been simulated in the past. We conclude that this is because hurricane Harvey was a strongly dynamically-driven storm system that as a result was relatively impervious to the effects of aerosols.

Dynamical Structures of Cross-Domain Forecast Error Covariance of a Simulated Tropical Cyclone in a Convection-Permitting Coupled Atmosphere–Ocean Model

AbstractUnderstanding the dynamics of the flow-dependent forecast error covariance across the air–sea interface is beneficial toward revealing the potential influences of strongly coupled data assimilation on tropical cyclone (TC) initialization in coupled models, and the fundamental dynamics associated with TC air–sea interactions. A 200-member ensemble of convection-permitting forecasts from a coupled atmosphere–ocean regional model is used to investigate the forecast error covariance across the oceanic and atmospheric domains during the rapid intensification of Hurricane Florence (2018). Forecast uncertainties in both atmospheric and oceanic domains, from an Eulerian perspective, increase with forecast lead time, mainly from TC displacement errors. In a storm-relative framework, the ensemble forecast uncertainties in both domains are predominantly caused by differences in the simulated storm intensity and structure. The largest ensemble spread in the atmospheric pressure, temperature, and wind fields can be found within the TC inner-core region. Alternatively, the largest ensemble spread in the upper-ocean currents and temperature fields are located along the cold wake behind the storm. Cross-domain ensemble correlations between simulated atmospheric (oceanic) observations and oceanic (atmospheric) state variables in the storm-relative coordinates are highly anisotropic, variable dependent, and ultimately driven by the dynamics of TC air–sea interactions. Meaningful and dynamically consistent cross-domain ensemble correlations suggest that it is possible to use atmospheric and oceanic observations to simultaneously update state variables associated with the coupled ocean–atmosphere prediction of TCs using strongly coupled data assimilation. Sensitivity experiments demonstrate that at least 60–80 ensemble members are required to represent physically consistent cross-domain correlations and minimize sampling errors.

The tornadoes of 30–31 May 2019 in south-Central Chile: Sensitivity to topography and SST

Tornadoes were reported in south-central Chile on 30 and 31 May 2019. To better understand the mechanisms that supported the organization and severity of the storms that generated them, a series of high-resolution sensitivity simulations were conducted using the Weather Research and Forecast (WRF) model. In addition to a control simulation, three simulations were run that successively reduced the topography to 50%, 25%, and 0% of original height; three more simulations were run that increased SST by 2 K everywhere, decreased it by 2 K everywhere, and set all SSTs greater than 16 °C to exactly 16 °C; finally, two more simulations were run to explore the combined effects of SST changes and lower topography.Results indicate that as topography was lowered, a strong northerly low-level jet along the upslope of the Andes weakened and broadened in both vertical and horizontal extent. Values of 0–6-km bulk shear and 0–3-km storm-relative helicity (SRH) over the regions where the tornadoes occurred diminished with successive reduction of the topography. As a result, simulated brightness temperatures were warmer, and swaths of updraft helicity were fewer and shorter. These results indicate that on 30–31 May 2019, flow blocking by the Andes topography generated mesoscale wind shear conditions that favored tornadoes. When SSTs were increased, instability (quantified by convective available potential energy, CAPE) also increased, although primarily offshore, and updraft helicity swath length increased, indicating a positive impact on simulated storm intensity. When SSTs were decreased, CAPE also decreased along with a decline in magnitude of updraft helicity. These results suggest that SSTs also impact storm severity via an influence on atmospheric instability. When the two factors were combined, warmer SSTs were not able to overcome a reduction in wind shear associated with a decrease in the topography. This suggests that in south-central Chile, wind shear is more important than CAPE for tornadic thunderstorms, as has been found for other regions around the world).

A long‐lived supercell over mountainous terrain

The life cycle of a convective storm forming over highly complex topography on the northern side of the Alps is studied. Moist convection began ahead of a cold front in the late morning of 2 August 2007 in eastern Switzerland. It developed into a supercell storm that moved along the Alpine main crest for more than 8 h, passed over several 2000 m high ridges and ultimately dissipated over eastern Austria. This study analyzes the impact of topography on the pre‐storm environment and on the storm development using several simulations with the Weather Research and Forecasting (WRF) model at a minimum horizontal grid spacing of 833 m. A hindcast simulation of the event features a convective system evolving in good agreement with observations. Variations in the simulated storm intensity appear to be related to the topography below the storm. Two idealized simulations help understand how the Alpine topography affected storm initiation and development. North of the Alps, relatively strong shear between southwesterly synoptic flow aloft and thermally induced plain‐to‐mountain flow near the ground created favourable conditions for supercell development. Small‐scale terrain features supported the upward transport of moisture via slope circulations, locally reducing CIN and increasing CAPE, and ultimately enhancing the storm longevity.

Effects of surface flux parameterization on the numerically simulated intensity and structure of Typhoon Morakot (2009)

The effects of surface flux parameterizations on tropical cyclone (TC) intensity and structure are investigated using the Advanced Research Weather Research and Forecasting (WRF-ARW) modeling system with high-resolution simulations of Typhoon Morakot (2009). Numerical experiments are designed to simulate Typhoon Morakot (2009) with different formulations of surface exchange coefficients for enthalpy (CK) and momentum (CD) transfers, including those from recent observational studies based on in situ aircraft data collected in Atlantic hurricanes. The results show that the simulated intensity and structure are sensitive to CK and CD, but the simulated track is not. Consistent with previous studies, the simulated storm intensity is found to be more sensitive to the ratio of CK/CD than to CK or CD alone. The pressure–wind relationship is also found to be influenced by the exchange coefficients, consistent with recent numerical studies. This paper emphasizes the importance of CD and CK on TC structure simulations. The results suggest that CD and CK have a large impact on surface wind and flux distributions, boundary layer heights, the warm core, and precipitation. Compared to available observations, the experiment with observed CD and CK generally simulated better intensity and structure than the other experiments, especially over the ocean. The reasons for the structural differences among the experiments with different CD and CK setups are discussed in the context of TC dynamics and thermodynamics.