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Victoria A. Johnson, Kimberly E. Klockow-McClain, Randy A. Peppler, and Angela M. Person

Abstract

Residents of the Oklahoma City metropolitan area are frequently threatened by tornadoes. Previous research indicates that perceptions of tornado threat affect behavioral choices when severe weather threatens and, as such, are important to study. In this paper, we examine the potential influence of tornado climatology on risk perception. Residents across central Oklahoma were surveyed about their perceptions of tornado proneness for their home location, and this was compared with the local tornado climatology. Mapping and programming tools were then used to identify relationships between respondents’ perceptions and actual tornado events. Research found that some dimensions of the climatology, such as tornado frequency, nearness, and intensity, have complex effects on risk perception. In particular, tornadoes that were intense, close, and recent had the strongest positive influence on risk perception, but weaker tornadoes appeared to produce an “inoculating” effect. Additional factors were influential, including sharp spatial discontinuities between neighboring places that were not tied to any obvious physical feature or the tornado climatology. Respondents holding lower perceptions of risk also reported lower rates of intention to prepare during tornado watches. By studying place-based perceptions, this research aims to provide a scientific basis for improved communication efforts before and during tornado events and for identifying vulnerable populations.

Open access
Minghao Yang, Chongyin Li, Xiong Chen, Yanke Tan, Xin Li, Chao Zhang, and Guiwan Chen

Abstract

The reproducibility of climatology and the midwinter suppression of the cold-season North Pacific storm track (NPST) in historical runs of 18 CMIP6 models is evaluated against the NCEP reanalysis data. The results show that the position of the climatological peak area of 850-hPa meridional eddy heat flux (υT850) is well captured by these models. The spatial patterns of climatological υT850 are basically consistent with the NCEP reanalysis. Generally, NorESM2-LM and CESM2-WACCM present a relatively strong capability to reproduce the climatological amplitude of υT850 with lower RMSE than the other models. Compared with CMIP5 models, the intermodel spread of υT850 climatology among the CMIP6 models is smaller, and their multimodel ensemble is closer to the NCEP reanalysis. The geographical distribution in more than half of the selected models is farther south and east. For the subseasonal variability of υT850, nearly half of the models exhibit a double-peak structure. In contrast, the apparent midwinter suppression in the NPST represented by the 250-hPa filtered meridional wind variance (υυ250) is reproduced by all the selected models. In addition, the present study investigates the possible reasons for simulation biases regarding climatological NPST amplitude. It is found that a higher model horizontal resolution significantly intensifies the climatological υυ250. There is a significant in-phase relationship between climatological υυ250 and the intensity of the East Asian winter monsoon (EAWM). However, the climatological υT850 is not sensitive to the model grid spacing. Additionally, the climatological low-tropospheric atmospheric baroclinicity is uncorrelated with climatological υυ250. The stronger climatological baroclinic energy conversion is associated with the stronger climatological υT850.

Open access
Mengmeng Lu, Song Yang, Junbin Wang, Yuting Wu, and Xiaolong Jia

Abstract

The thermal effect of the entire Tibetan Plateau (TP) tends to strengthen the South Asian summer monsoon (SASM); however, how does this monsoon component respond to the thermal conditions of different TP domains? How do the thermal conditions of the entire TP influence other monsoons, including the East Asian summer monsoon (EASM) and the Southeast Asian summer monsoon (SEASM)? These questions are addressed by conducting an experiment with the CESM, which is forced by reducing the surface albedo over the plateau by half, from a TP-averaged 0.20 to 0.10, from May to September, and similar experiments for different TP domains. Both observational and model results show that the entire TP heating intensifies the large-scale Asian monsoon, the SASM, and the EASM but surprisingly weakens the SEASM. It is also surprising that the TP heating exerts a stronger effect on the EASM than on the SASM. The southern TP (south of 35°N) does not show the strongest impact on the SASM in comparison with other TP domains, and it exerts the weakest impact on the EASM, which is most strongly influenced by the thermal effect of the eastern (east of 90°E) and northern TP. The western TP weakens the SEASM (as do the other domains), and it strengthens other monsoon components. The thermal conditions of the southern and eastern TP are accompanied by signals of tropical atmospheric response at relatively broader spatial scales, whereas those of the northern TP more apparently lead to a significant wave train extending eastward from the TP to western Eurasia over the higher latitudes.

Open access
Helene Asbjørnsen, Helen L. Johnson, and Marius Årthun

Abstract

The inflow across the Iceland–Scotland Ridge determines the amount of heat supplied to the Nordic seas from the subpolar North Atlantic (SPNA). Consequently, variable inflow properties and volume transport at the ridge influence marine ecosystems and sea ice extent farther north. Here, we identify the upstream pathways of the Nordic seas inflow and assess the mechanisms responsible for interannual inflow variability. Using an eddy-permitting ocean model hindcast and a Lagrangian analysis tool, numerical particles are released at the ridge during 1986–2015 and tracked backward in time. We find an inflow that is well mixed in terms of its properties, where 64% comes from the subtropics and 26% has a subpolar or Arctic origin. The local instantaneous response to the NAO is important for the overall transport of both subtropical and Arctic-origin waters at the ridge. In the years before reaching the ridge, the subtropical particles are influenced by atmospheric circulation anomalies in the gyre boundary region and over the SPNA, forcing shifts in the North Atlantic Current (NAC) and the Subpolar Front. An equatorward-shifted NAC and westward-shifted Subpolar Front correspond to a warmer, more saline inflow. Atmospheric circulation anomalies over the SPNA also affect the amount of Arctic-origin water rerouted from the Labrador Current toward the Nordic seas. A high transport of Arctic-origin water is associated with a colder, fresher inflow across the Iceland–Scotland Ridge. The results thus demonstrate the importance of gyre dynamics and wind forcing in affecting the Nordic seas inflow properties and volume transport.

Open access
Nergui Nanding, Huan Wu, Jing Tao, Viviana Maggioni, Hylke E. Beck, Naijun Zhou, Maoyi Huang, and Zhijun Huang

Abstract

This study characterizes precipitation error propagation through a distributed hydrological model based on the river basins across the contiguous United States (CONUS), to better understand the relationship between errors in precipitation inputs and simulated discharge (i.e., PQ error relationship). The NLDAS-2 precipitation and its simulated discharge are used as the reference to compare with TMPA-3B42 V7, TMPA-3B42RT V7, Stage IV, CPC-U, MERRA-2, and MSWEP V2.2 for 1548 well-gauged river basins. The relative errors in multiple conventional precipitation products and their corresponding discharges are analyzed for the period of 2002–13. The results reveal positive linear PQ error relationships at annual and monthly time scales, and the stronger linearity for larger temporal accumulations. Precipitation errors can be doubled in simulated annual accumulated discharge. Moreover, precipitation errors are strongly dampened in basins characterized by temperate and continental climate regimes, particularly for peak discharges, showing highly nonlinear relationships. Radar-based precipitation product consistently shows dampening effects on error propagation through discharge simulations at different accumulation time scales compared to the other precipitation products. Although basin size and topography also influence the PQ error relationship and propagation of precipitation errors, their roles depend largely on precipitation products, seasons, and climate regimes.

Open access
Xiuhua Zhu

Abstract

This work proposes a framework to examine interactions of climate modes that are identified as leading EOF modes; their coupling structure is unveiled through correlation analysis and helps in constructing a regression model, whose performance is compared across GCMs, thereby providing a quantitative overview of model performances in simulating mode interaction. As a demonstration surface temperature is analyzed for five CMIP5 preindustrial control (PiControl) simulations. Along with the seasonal land and ocean modes, four interannual modes are identified: the tropical mode (TM) associated with the Hadley circulation, the tropical Pacific mode (TPM) characterizing a zonal temperature contrast between the eastern tropical Pacific and the Atlantic/Indian Oceans, and two annular modes, the Arctic mode (AM) and Antarctic mode (AAM). All GCMs converge on the following points: 1) TM strongly couples with seasonal signals of the previous year; 2) TPM leads TM by 1 year, and thus a weaker zonal temperature contrast in the tropics contributes to warming in the entire tropical band 1 year later; and 3) AM weakly couples to TM at a 1-yr lead, suggesting that a colder North Pole may contribute to colder tropics. In addition, all GCMs do not support a linear coupling between AAM and TM. The above-learned coupling structure is incorporated to construct an optimum regression model that demonstrates considerable predictive power. The proposed approach may both serve as a useful tool for dynamical analysis and lend insight into GCM differences. Its merit is demonstrated by the finding that different representations of the mean seasonal cycle in GCMs may account for the GCM dependence of relative contributions of seasonal and interannual modes to TM variability.

Open access
Wenwei Xu, Karthik Balaguru, Andrew August, Nicholas Lalo, Nathan Hodas, Mark DeMaria, and David Judi

Abstract

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

Open access
Xiaodong Wu, Falk Feddersen, and Sarah N. Giddings

Abstract

Rip currents are generated by surfzone wave breaking and are ejected offshore, inducing inner-shelf flow spatial variability (eddies). However, surfzone effects on the inner-shelf flow spatial variability have not been studied in realistic models that include both shelf and surfzone processes. Here, these effects are diagnosed with two nearly identical twin realistic simulations of the San Diego Bight over summer to fall, where one simulation includes surface gravity waves (WW) and the other does not (NW). The simulations include tides, weak to moderate winds, internal waves, and submesoscale processes and have surfzone width L sz of 96 (±41) m (≈1 m significant wave height). Flow spatial variability metrics, alongshore root-mean-square vorticity, divergence, and eddy cross-shore velocity are analyzed in an L sz normalized cross-shore coordinate. At the surface, the metrics are consistently (>70%) elevated in the WW run relative to NW out to 5L sz offshore. At 4L sz offshore, WW metrics are enhanced over the entire water column. In a fixed coordinate appropriate for eddy transport, the eddy cross-shore velocity squared correlation between WW and NW runs is <0.5 out to 1.2 km offshore or 12 time-averaged L sz. The results indicate that the eddy tracer (e.g., larvae) transport and dispersion across the inner shelf will be significantly different in the WW and NW runs. The WW model neglects specific surfzone vorticity generation mechanisms. Thus, these inner-shelf impacts are likely underestimated. In other regions with larger waves, impacts will extend farther offshore.

Open access
K. Gustavsson, M. Z. Sheikh, A. Naso, A. Pumir, and B. Mehlig

Abstract

Small nonspherical particles settling in a quiescent fluid tend to orient so that their broad side faces down because this is a stable fixed point of their angular dynamics at small particle Reynolds number. Turbulence randomizes the orientations to some extent, and this affects the reflection patterns of polarized light from turbulent clouds containing ice crystals. An overdamped theory predicts that turbulence-induced fluctuations of the orientation are very small when the settling number Sv (a dimensionless measure of the settling speed) is large. At small Sv, by contrast, the overdamped theory predicts that turbulence randomizes the orientations. This overdamped theory neglects the effect of particle inertia. Therefore, we consider here how particle inertia affects the orientation of small crystals settling in turbulent air. We find that it can significantly increase the orientation variance, even when the Stokes number St (a dimensionless measure of particle inertia) is quite small. We identify different asymptotic parameter regimes where the tilt-angle variance is proportional to different inverse powers of Sv. We estimate parameter values for ice crystals in turbulent clouds and show that they cover several of the identified regimes. The theory predicts how the degree of alignment depends on particle size, shape, and turbulence intensity, and that the strong horizontal alignment of small crystals is only possible when the turbulent energy dissipation is weak, on the order of 1 cm2 s−3 or less.

Open access
Akira Yamazaki, Takemasa Miyoshi, Jun Inoue, Takeshi Enomoto, and Nobumasa Komori

Abstract

An ensemble-based forecast sensitivity to observations (EFSO) diagnosis has been implemented in an atmospheric general circulation model–ensemble Kalman filter data assimilation system to estimate the impacts of specific observations from the quasi-operational global observing system on weekly short-range forecasts. It was examined whether EFSO reasonably approximates the impacts of a subset of observations from specific geographical locations for 6-h forecasts, and how long the 6-h observation impacts can be retained during the 7-day forecast period. The reference for these forecasts was obtained from 12 data-denial experiments in each of which a subset of three radiosonde observations launched from a geographical location was excluded. The 12 locations were selected from three latitudinal bands comprising (i) four Arctic regions, (ii) four midlatitude regions in the Northern Hemisphere, and (iii) four tropical regions during the Northern Hemisphere winter of 2015/16. The estimated winter-averaged EFSO-derived observation impacts well corresponded to the 6-h observation impacts obtained by the data denials and EFSO could reasonably estimate the observation impacts by the data denials on short-range (from 6 h to 2 day) forecasts. Furthermore, during the medium-range (4–7 day) forecasts, it was found that the Arctic observations tend to seed the broadest impacts and their short-range observation impacts could be projected to beneficial impacts in Arctic and midlatitude North American areas. The midlatitude area was located just downstream of dynamical propagation from the Arctic toward the midlatitudes. Results obtained by repeated Arctic data-denial experiments were found to be generally common to those from the non-repeated experiments.

Open access