Simulated Storm Research Articles

Conditions of Loss Cone Filling by Scattering on the Curved Field Lines for 30 keV Protons During Geomagnetic Storm as Inferred From Numerical Trajectory Tracing

AbstractThe rate of pitch angle scattering on the curved magnetic field lines is well parameterized by the ratio of the minimum field line curvature radius to the maximum effective particle gyroradius (K = RC/rg). The critical value of this ratio (Kcr) corresponding to the loss cone filling is of special interest since it corresponds to the low altitude isotropic boundaries (IBs). The early theoretical estimates gave Kcr = 8, whereas recent estimations of the K parameter on the field lines corresponding to the observed IBs during the geomagnetic storms revealed KIB values in the range of 3–30. We numerically trace the trajectories of the 30 keV protons in the magnetic field of the global magnetohydrodynamic simulation of the intense storm in order to infer statistical distribution of Kcr. The electric field and effects of nonstationarity are neglected in this study. It is found that although the Kcr values do show some variations during the course of the storm, its range is rather narrow 4 < Kcr < 8. The result suggests that higher KIB values found in the observational studies, if not caused by the magnetosphere‐ionosphere mapping error, should be attributed to some other mechanism of pitch angle scattering. The Kcr values tend to be lower (4–6) during the main phase because the region of low K values approaches the Earth and the equatorial loss cone size becomes larger due to a larger equatorial magnetic field in the near‐earth region. The remaining variation of Kcr is explained by the presence of the guide component of the magnetic field.

NUMERICAL SIMULATION OF WAVE-DRIVEN FLOWS ON A MORPHOLOGICALLY EVOLVING BEACH

Wave-driven flows in the nearshore zone are responsible for the erosion and transport of beach sediments, causing a continuous cycle of bathymetric change that is linked with changes to wave transformation and nearshore hydrodynamics. Numerical models have been used to investigate the evolving nearshore wave field corresponding to beach morphology change in field studies (e.g., Ruiz de Alegria-Arzaburu et al., 2013). In the present study, the non-hydrostatic wave-flow SWASH model (Zijlema et al., 2011) is applied to five laboratory cases to investigate the change in wave and flow fields corresponding to evolving beach morphology during a simulated storm event.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/LZQQuuiqsPY

An Idealized Physical Model for the Severe Convective Storm Environmental Sounding

AbstractThis work develops a theoretical model for steady thermodynamic and kinematic profiles for severe convective storm environments, building off the two-layer static energy framework developed in work by Agard and Emanuel. The model is phrased in terms of static energy, and it allows for independent variation of the boundary layer and free troposphere separated by a capping inversion. An algorithm is presented to apply the model to generate a sounding for numerical simulations of severe convective storms, and the model is compared and contrasted with that of Weisman and Klemp. The model is then fit to a case-study sounding associated with the 3 May 1999 tornado outbreak, and its potential utility is demonstrated via idealized numerical simulation experiments. A long-lived supercell is successfully simulated with the historical sounding but not the analogous theoretical sounding. Two types of example experiments are then performed that do simulate a long-lived supercell: 1) a semitheoretical experiment in which a portion of the theoretical sounding is modified to match the real sounding (low-level moisture); 2) a fully theoretical experiment in which a model physical parameter is modified (free-tropospheric relative humidity). Overall, the construction of this minimal model is flexible and amenable to additional modifications as needed. The model offers a novel framework that may be useful for testing how severe convective storms depend on the vertical structure of the hydrostatic environment, as well as for linking variability in these environments to the physical processes that produce them within the climate system.

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

AbstractIn this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery.The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L−1) agreed—to within a factor of about 2—with aircraft data at flight levels (−10° to −15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations.The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

Sense-making in a Simulated Emergency Operations Centre

This study reports the results of a laboratory experiment in decision-making in an Emergency Operations Centre (EOC) during a crisis. It adapted a validated simulation of a severe winter storm in a fictional city in Canada, during which a variety of serious events caused major disruptions, including loss of life. Participants were naïve individuals, as the focus was on sense-making in unfamiliar dynamic and uncertain environments and situations requiring urgent responses (i.e., conditions that occur during crises). The objective was to assess the impacts of enactment on the retention of memory of recent experiences. The enactment was theorized as the basis for sense-making processes where taking an action is guided by learning through acting. In contrast, predictions based on a simple model, the Zeigarnik effect, indicate the depletion of memory for completed actions, thus indicating their perverse effects on the capacity to learn. This experiment showed that participants in our simulation who played the role of passive observers of EOC activities during a severe storm remembered more of the events than did participants who played the role of trainees in the EOC who had to act on requests for information and decisions. Other results pointed to the conclusion that the role played by participants in the EOC significantly affected which events they remembered, their mood, and their priorities in the EOC. These results imply that having non-acting observers present in the EOC might be a way to better preserve organizational memory.

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.

Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High‐Resolution Model

AbstractGravity wave (GW) activity in the lower and middle atmosphere of Mars during the global dust storm of 2018 has been studied for the first time using a high‐resolution (GW‐resolving) general circulation model. Dust storm simulations were compared with those utilizing the climatological distribution of dust in the absence of storms. Both scenarios are based on observations of the dust optical depth by the Mars Climate Sounder instrument on board the Mars Reconnaissance Orbiter. The modeling reveals a reduction of the wave activity by a factor of 2 or more in the lower atmosphere, which qualitatively agrees with recent observations. It is associated with a decline of GW generation due to baroclinic and convective stabilization of the Martian troposphere induced by the increased amount of airborne aerosols during the storm. Contrary to the decrease of GW activity in the lower atmosphere, wave energy and momentum fluxes in the middle atmosphere increase by approximately the same factor. This enhancement of GW activity is caused by the changes in the large‐scale circulation, most importantly in the mean zonal wind, which facilitate vertical wave propagation by allowing for a greater portion of GW harmonics originated in the lower atmosphere to avoid filtering on their way to upper layers.

Performance of MPAS-A and WRF in predicting and simulating western North Pacific tropical cyclone tracks and intensities

Performances of the Model for Prediction Across Scales-Atmosphere (MPAS-A) in predicting and the Weather Research and Forecasting (WRF) model in simulating western North Pacific (WNP) tropical cyclone (TC) tracks and intensities have been compared. Parallel simulations of the same historical storms that made landfall over southern China, namely, TCs Hope (1979), Gordon (1989), Koryn (1993), Imbudo (2003), Dujuan (2003), Molave (2009), Hato (2017) and Mangkhut (2018), were carried out using WRF and MPAS-A, with initial conditions (and, for WRF, lateral boundary conditions as well) taken from ERA-interim. For MPAS-A, the model was integrated using a standard 60-to-3-km variable-resolution global grid mesh and also on 160-to-2-km grids customized to cover the TC tracks with the highest resolution mesh. The WRF model was integrated using a 15-km/3-km nested domain. No TC bogus scheme was applied when initializing the MPAS-A and WRF simulations. It was found that while TC tracks were reasonably captured by the two models configured variously, the storm intensities were underestimated in general. Given MPAS-A runs were initial value predictions whereas WRF runs were dynamically downscaled from ERA-interim, the finding that MPAS-A has comparable (or slightly better) performance as (than) WRF is noteworthy. To further examine the sensitivity of the MPAS-A TC forecasts to the initial data, additional experiments were carried out for TCs Molave and Hope using ERA5 reanalysis as initial conditions. The ERA5 initialized runs showed significant (slight) improvement in intensity (track) evolution, suggesting that the underestimated TC intensity is likely related to inferior representation of storms in the ERA-interim initial fields. Furthermore, additional runs using another customized 60-to-2-km mesh showed a reasonable improvement in capturing the TC tracks, suggesting that the track forecast accuracy of MPAS-A in TC can be sensitive to the grid resolution in the coarsest part of the variable-resolution mesh used.

A Review and Evaluation of Planetary Boundary Layer Parameterizations in Hurricane Weather Research and Forecasting Model Using Idealized Simulations and Observations

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (Km) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent Km. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of Km. The smaller the Km in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent Km and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades.

Incorporation of sea level rise in storm surge surrogate modeling

In order to accommodate the computational burden of high-fidelity storm surge numerical models, surrogate modeling (metamodeling) techniques have gained significant popularity over the past decade. Utilizing an existing database of synthetic storm simulations, these models provide a fast-to-compute mathematical approximation to the input/output relationship of the numerical model that was used to establish this database. Thus, they offer fast predictions and, when properly calibrated, can maintain the accuracy of the high-fidelity numerical model that generated the original database. This study extends the previous work of the authors and investigates different computational aspects for incorporating Sea Level Rise (SLR) explicitly as an input within such a surrogate modeling framework. Kriging, also referenced as Gaussian process regression, is specifically chosen as the surrogate modeling technique for this study. The storms utilized correspond to a database of 300 synthetic tropical cyclones recently developed by the US Army Corps of Engineers Coastal Hazards System for the Puerto Rico and US Virgin Islands region, which considers three different SLR scenarios. The development of separate surrogate models for each of the three SLR scenarios and of a single surrogate model that predicts across all SLR scenarios are compared, addressing several relevant issues like (1) the proper definition of validation metrics (2) the correct implementation of cross-validation techniques, and (3) the need for adjustment of the surrogate model hyper-parameter calibration. It is shown that proper attention is needed when the same storms have been considered across all the different SLR scenarios in the database; otherwise, the calibration of the surrogate model may be ineffective, and the validation of its accuracy will provide erroneous confidence. The proper normalization of the storm surge output to improve the surrogate model accuracy is also discussed. Finally, the proper selection of storm simulations for establishing the database for the surrogate model development is examined, emphasizing how this selection should be performed efficiently across the different SLR scenarios. It is demonstrated that high surrogate model accuracy can be accommodated with a small number of strategically chosen storm simulations. Leveraging this investigation, recommendations are offered on how to efficiently create future high-fidelity databases to support the development of surrogate models that predict across different SLR scenarios.

Simulated Changes in Storm Morphology Associated with a Sea-Breeze Air Mass

AbstractThe central east coast of Australia is frequently impacted by large hail and damaging winds associated with severe convective storms, with individual events recording damages exceeding AUD 1 billion. These storms present a significant challenge for forecasting because of their development in seemingly marginal environments. They often have been observed to intensify upon approaching the coast, with case studies and climatological analyses indicating that interactions with the sea breeze are key to this process. The relative importance of the additional lifting and vorticity along the sea-breeze front in comparison with the change to a cooler, moister air mass with stronger low-level shear behind the front has yet to be investigated. Here, the role of the sea-breeze air mass is isolated using idealized numerical simulations of storms developing in a horizontally homogeneous environment. The base-state substitution (BSS) modeling technique is utilized to introduce the sea-breeze air mass following initial storm development. Relative to a simulation without BSS, the storm is longer lived and more intense, ultimately developing supercell characteristics including increased updraft rotation, deviant motion to the left of the mean wind vector, and a strong reflectivity gradient on the inflow edge. Separately simulating the changes in the thermodynamic and wind fields reveals that the enhanced storm longevity and intensity are primarily due to the latter. The change in the low-level environmental winds slows gust-front propagation, allowing the storm to continue to ingest warm, potentially buoyant environmental air. At the same time, increased low-level shear promotes the development of persistent updraft rotation that causes the storm to make a transition from a multicell to a supercell.

Impacts of Latent Energy and Snow Fall Speed on a Wintertime Midlatitude Cyclone

AbstractThis study aimed to understand the impacts of latent energy as well as snow fall speeds on precipitation properties and synoptic‐scale storm characteristics of a wintertime midlatitude cyclone. Simulations of a potent winter storm that impacted the Rocky Mountains and northern Great Plains of the United States in February 2017 were performed using the Weather Research and Forecasting model with latent heating or cooling from individual microphysical processes systematically turned off and fall speeds adjusted by ±50%. Results indicated substantial impacts on the microphysical characteristics of the simulated storm to fall speed, cooling from sublimation, and warming from deposition. The impacts of cooling and warming were manifested as differences in accumulated snowfall. Increased (decreased) fall speeds led to smaller (larger) ice crystals and total mass, resulting in offsetting effects on the precipitation flux, and thus minimal impacts on snowfall and large‐scale characteristics of the storm. Warming and cooling associated with deposition and sublimation, respectively, impacted the synoptic‐scale dynamics, whereby removing warming from deposition resulted in an increased meridional temperature gradient near the jet stream, thus increasing the jet strength and causing it to be more westerly with less curvature aloft. This in turn limited upper‐level divergence, creating a weaker surface low and shifting the precipitation shield southward. The opposite occurred with the removal of latent cooling due to sublimation. This study highlights the potential importance of latent energy associated with ice sublimation and deposition and fall speeds in the larger‐scale characteristics of winter storms.

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).

Evaluation of Rainfall Forecasts by Three Mesoscale Models during the Mei-yu Season of 2008 in Taiwan. Part II: Development of an Object-Oriented Method

This study describes a recently developed object-oriented method suitable for Taiwan for the purpose to verify quantitative precipitation forecasts (QPFs) produced by mesoscale models as a complement to the traditional approaches in existence. Using blended data from the rain-gauge network in Taiwan and the Tropical Rainfall Measuring Mission (TRMM) as the observation, the method developed herein is applied to twice-daily 0–48 h QPFs produced by the Cloud-Resolving Storm Simulator (CReSS) during the South-West Monsoon Experiment (SoWMEX) in May–June 2008. In this method, rainfall objects are identified through a procedure that includes smoothing and thresholding. Various attribute parameters and the characteristics of observed and forecast rain-area objects are then compared and discussed. Both the observed and the QPF frequency distributions of rain-area objects with respect to total water production, object size, and rainfall are similar to chi-distribution, with highest frequency at smaller values and decreased frequencies toward greater values. The model tends to produce heavier rainfall than observation, while the latter exhibits a higher percentage of larger objects with weaker rainfall intensity. The distributions of shape-related attributes are similar between QPF and observed rainfall objects, with more northeast–southwest oriented and fewer northwest–southeast oriented objects. Both observed and modeled object centroid locations have relative maxima over the terrain of Taiwan, indicating reasonable response to the topography. The above results are consistent with previous studies.

Spatial Footprints of Storm Surges Along the Global Coastlines

AbstractWe perform the first global analysis of the spatial footprints of storm surges, using observed and simulated storm surge data. Three different techniques are applied to quantify the spatial footprints: clustering analysis, percentage of co‐occurrence, and joint probability analysis. The capability of the simulated data to represent the observed storm surge footprints is demonstrated. Results lead to the identification of coastline stretches prone to be impacted simultaneously by the same storm surge events. The spatial footprint sizes differ around the globe, partially conditioned by the geography of the coastline, that is, more irregular coastlines consist of a larger number of different storm surge clusters with varying footprint sizes. For the northwestern Atlantic, spatial footprints of storm surges vary when specifically accounting for tropical cyclones, using storm track information in the storm surge simulations. Our results provide important new insights into the spatial footprints of storm surges at the global scale and will help to facilitate improvements in how coastal flood risk is identified, assessed, and managed, by taking these spatial features into account.

The Role of Hiss, Chorus, and EMIC Waves in the Modeling of the Dynamics of the Multi‐MeV Radiation Belt Electrons

AbstractIn this study, we performed a series of long‐term and individual storm simulations with and without hiss, chorus, and electromagnetic ion cyclotron (EMIC) waves. We compared simulation results incorporating different wave modes with Van Allen Probes flux observations to illustrate how hiss and chorus waves aid EMIC waves in depleting multi‐MeV electrons. We found that EMIC, hiss, and chorus waves are required to reproduce satellite measurements in our simulations. Our results indicate that hiss waves play a dominant role in scattering near‐equatorial mirroring electrons, and they assist EMIC waves, which scatter only small pitch angle electrons. The best agreement between the observations and the simulations (long‐term and 17 January 2013 storm) is achieved when hiss, chorus, and EMIC waves are included.

Base-Hurricane: A new extension for the Landis-II forest landscape model

Hurricanes in the southeast United States are infrequent disturbances that affect large areas and have a large effect on forest succession. In order to understand and quantify this effect, we added a new module to the LANDIS-II landscape change model. Focusing on the southeast coast of the United States, we simulated stochastic hurricanes for 50 years. For each simulated storm, the new model extension generates the maximum sustained wind speed over the region and uses the resulting parameter surface to compute maximum sustained wind speed for each cohort cell in a raster grid. Mortality is estimated for each species and age cohort in each cell based on the maximum sustained wind speed, altering forest succession. Results indicate that hurricanes reduce average aboveground biomass by > 20% over 50 years on a landscape in Fort Bragg, North Carolina (USA) compared to a scenario without hurricanes and increased uncertainty of projected succession.

A Hail Growth Trajectory Model for Exploring the Environmental Controls on Hail Size: Model Physics and Idealized Tests

AbstractA detailed microphysical model of hail growth is developed and applied to idealized numerical simulations of deep convective storms. Hailstone embryos of various sizes and densities may be initialized in and around the simulated convective storm updraft, and then are tracked as they are advected and grow through various microphysical processes. Application to an idealized squall line and supercell storm results in a plausibly realistic distribution of maximum hailstone sizes for each. Simulated hail growth trajectories through idealized supercell storms exhibit many consistencies with previous hail trajectory work that used observed storms. Systematic tests of uncertain model parameters and parameterizations are performed, with results highlighting the sensitivity of hail size distributions to these changes. A set of idealized simulations is performed for supercells in environments with varying vertical wind shear to extend and clarify our prior work. The trajectory calculations reveal that, with increased zonal deep-layer shear, broader updrafts lead to increased residence time and thus larger maximum hail sizes. For cases with increased meridional low-level shear, updraft width is also increased, but hailstone sizes are smaller. This is a result of decreased residence time in the updraft, owing to faster northward flow within the updraft that advects hailstones through the growth region more rapidly. The results suggest that environments leading to weakened horizontal flow within supercell updrafts may lead to larger maximum hailstone sizes.

High Rates of Exposure to Simulated Winter Storm Cues Negatively Affect White-Throated Sparrow (Zonotrichia albicollis) Energy Reserves

Climate change is causing changes in weather patterns and more frequent extreme weather events. Although birds are often able to cope with and respond to inclement weather with physiological and behavioral responses, as weather events become more severe or frequent the adaptive coping responses of many species may be pushed beyond their limits. We investigated the effects of experimental recurrent inclement winter weather cues on body composition, glucocorticoid hormones, and behavior of white-throated sparrows (Zonotrichia albicollis). We used a hypobaric climatic wind tunnel to simulate storms by transiently decreasing barometric pressure and temperature, and measured behavioral responses, body composition, and baseline corticosterone levels in birds exposed, or not exposed (control), to different frequencies of simulated storms. In study 1, experimental birds were exposed to one storm per week over 9 weeks. In study 2, experimental birds were exposed to two storms per week over 12 weeks. Birds exposed to one simulated storm per week had higher fat and lean masses than control birds, with no differences in the amount of time groups spent feeding. This change in body composition suggests that birds were coping by increasing energy stores. In contrast, birds exposed to two simulated storms per week had lower fat masses compared to control birds, even though they spent more time feeding. Experimental birds in study 2 also had lower baseline corticosterone levels than controls. These changes suggest that the coping response observed in study 1 was overcome in study 2. These findings provide novel experimental evidence that birds detect and respond to changes in temperature and barometric pressure independent of other storm-related cues. One simulated storm per week resulted in potentially adaptive responses of increase mass. However, increasing the frequency of storm exposure to twice per week may exceed a physiological threshold for tolerance to which these songbirds are able to cope. These results also experimentally demonstrate that repeated exposure to inclement weather cues can directly affects birds’ energy reserves, with strong implications for survival as severe weather events continue to become more prevalent.

What is the Intrinsic Predictability of Tornadic Supercell Thunderstorms?

AbstractA 25-member ensemble of relatively high-resolution (75-m horizontal grid spacing) numerical simulations of tornadic supercell storms is used to obtain insight on their intrinsic predictability. The storm environments contain large and directionally varying wind shear, particularly in the boundary layer, large convective available potential energy, and a low lifting condensation level. Thus, the environments are extremely favorable for tornadic supercells. Small random temperature perturbations present in the initial conditions trigger turbulence within the boundary layers. The turbulent boundary layers are given 12 h to evolve to a quasi–steady state before storms are initiated via the introduction of a warm bubble. The spatially averaged environments are identical within the ensemble; only the random number seed and/or warm bubble location is varied. All of the simulated storms are long-lived supercells with intense updrafts and strong mesocyclones extending to the lowest model level. Even the storms with the weakest near-surface rotation probably can be regarded as weakly tornadic. However, despite the statistically identical environments, there is considerable divergence in the finescale details of the simulated storms. The intensities of the tornado-like vortices that develop in the simulations range from EF0 to EF3, with large differences in formation time and duration also being exhibited. The simulation differences only can be explained by differences in how the initial warm bubbles and/or storms interact with turbulent boundary layer structures. The results suggest very limited intrinsic predictability with respect to predicting the formation time, duration, and intensity of tornadoes.