Browse

You are looking at 101 - 110 of 118,391 items for :

  • All content x
Clear All
Sonia Lasher-Trapp, Enoch Jo, Luke R. Allen, Bryan N. Engelsen, and Robert J. Trapp

Abstract

The current study identifies and quantifies various mechanisms of entrainment, and their diluting effects, in the developing and mature stages of a simulated supercell thunderstorm. The two stages, differentiated by the lack or presence of a rotating updraft, are shown to entrain air by different, but related mechanisms that result from the strong vertical wind shear of the environment. The greatest entrainment rates in the developing stage result from the asymmetric overturning of large eddies near cloud top on the down-shear side. These rates are greater than those published in the literature for cumuli developing in environments lacking strong shear. Although the entrainment rate increases exponentially in time throughout the developing stage, successive cloud turrets help to replenish some of the lost buoyancy and condensate, allowing the nascent storm to develop further. During the mature stage, the greatest entrainment rates occur via “ribbons” of horizontal vorticity wrapping around the rotating updraft that ascend in time. The smaller width of the ribbons in comparison to the wider storm core limits their dilutive effects. Passive tracers placed in the low-level air ingested by the mature storm indicate that on average 20% of the core contains some undiluted air ingested from below the storm base, unaffected by any entrainment mechanism.

Restricted access
Ping Chen, Bo Sun, Huijun Wang, and Baoyan Zhu

Abstract

This study investigates the relationship and underlying mechanisms between the Indian Ocean Dipole (IOD) and Arctic sea ice. The results reveal that the preceding December sea ice over the Laptev Sea plays an important role in the formation of positive IOD conditions during April–June (AMJ). In years with positive December Laptev sea ice anomalies, the zonal wavenumber-1 (ZWN1) planetary wave component is stimulated at middle and high latitudes. The high-latitude ZWN1 propagates upward to the stratosphere and downward to the troposphere in December, affects the atmospheric circulation over the North Atlantic, and further leads to a warm sea surface temperature anomaly (SSTA) that persists until the following February. The mid-latitude ZWN1 propagates upward to the stratosphere in January and downward to the troposphere in February, contributing to the positive 200-hPa geopotential height anomaly (GPHA) in the subtropical Atlantic. The ascending anomaly induced by the warm SSTA and the positive 200-hPa GPHA in the subtropical Atlantic in February are favorable for effective Rossby wave source formation and stimulate an atmospheric wave train that forms an anomalous cyclone over the northern Arabian Sea, which contributes to enhanced convection over North India, stimulating an anomalous anticyclone over East India and leading to reduced convection over the northeastern Indian Ocean in March. The reduced convection over the northeastern Indian Ocean may lead to strengthened equatorial easterly winds and further contribute to positive IOD conditions in AMJ. These findings indicate that December Laptev sea ice may contribute to AMJ IOD conditions.

Restricted access
Sydney Sroka and Kerry Emanuel

Abstract

The intensity of tropical cyclones is sensitive to the air-sea fluxes of enthalpy and momentum. Sea spray plays a critical role in mediating enthalpy and momentum fluxes over the ocean’s surface at high wind speeds, and parameterizing the influence of sea spray is a crucial component of any air-sea interaction scheme used for the high wind regime where sea spray is ubiquitous. Many studies have proposed parameterizations of air-sea flux that incorporate the microphysics of sea spray evaporation and the mechanics of sea spray stress. Unfortunately, there is not yet a consensus on which parameterization best represents air-sea exchange in tropical cyclones, and the different proposed parameterizations can yield substantially different tropical cyclone intensities. This paper seeks to review the developments in parameterizations of the sea spray-mediated enthalpy and momentum fluxes for the high wind speed regime and to synthesize key findings that are common across many investigations.

Restricted access
David Huntsman, Hao-Che Wu, and Alex Greer

Abstract

Scholars have produced several theories and models to explain why individuals adjust to hazards. While findings from these studies are informative, studies have not considered how threat and coping appraisals may have differential effects on varying types of hazard adjustments, or how these findings may generalize to vulnerable populations. This study expands on the Protection Motivation Theory to explore the factors that shape hazard adjustment intentions among college students, a population traditionally defined as vulnerable, in response to tornado risk. An online survey was administered to college students (n=377) at Oklahoma State University, situated in a region that experiences considerable tornado risk. While the correlations between threat appraisal and tornado hazard adjustment intentions are smaller than the correlations between coping appraisal and tornado hazard adjustment intentions, findings suggest that threat appraisals become more important for influencing college students’ adjustment intentions when adjustment activities are complex (e.g., tornado shelter, home insurance), rather than basic (e.g., flashlight, first aid kid). This suggests that while both threat appraisals and coping appraisals are important for complex hazard adjustment intentions, basic hazard adjustment intentions are almost exclusively determined by coping appraisals. These findings have several practical implications for emergency management and provide new avenues for future hazard adjustment studies.

Restricted 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., P-Q error relationship). The NLDAS-2 precipitation and its simulated discharge are used as the reference to compare with TMPA-3B42 V7, TMPA-3B42RT V7, StageIV, CPC-U, MERRA-2, and MSWEP-2.2 for 1,548 well gauged river basins. The relative errors in multiple conventional precipitation products and their corresponding discharges are analysed for the period of 2002-2013. The results reveal positive linear P-Q error relationships at annual and monthly timescales, 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 timescales compared to the other precipitation products. Although basin size and topography also influence the P-Q error relationship and propagation of precipitation errors, their roles depend largely on precipitation products, seasons and climate regimes.

Open access
Hung Ming Cheung, Chang-Hoi Ho, Minhee Chang, Dasol Kim, Jinwon Kim, and Woosuk Choi

Abstract

Despite tremendous advancements in dynamical models for weather forecasting, statistical models continue to offer various possibilities for tropical cyclone (TC) track forecasting. Herein, a track-pattern-based approach was developed to predict a TC track for a lead time of 6–8 days over the western North Pacific (WNP), utilizing historical tracks in conjunction with dynamical forecasts. It is composed of four main steps: (1) clustering historical tracks similar to that of an operational five-day forecast in their early phase into track patterns, and calculating the daily mean environmental fields (500-hPa geopotential height and steering flow) associated with each track; (2) deriving the two environmental variables forecasted by dynamical models; (3) evaluating pattern correlation coefficients between the two environmental fields from step (1) and those from dynamical model for a lead times of 6–8 days; and (4) producing the final track forecast based on relative frequency maps obtained from the historical tracks in step (1) and the pattern correlation coefficients obtained from step (3). TCs that formed in the WNP and lasted for at least seven days, during the 9-year period 2011–2019 were selected to verify the resulting track-pattern-based forecasts. In addition to the performance comparable to dynamical models under certain conditions, the track-pattern-based model is inexpensive, and can consistently produce forecasts over large latitudinal or longitudinal ranges. Machine learning techniques can be implemented to incorporate non-linearity in the present model for improving medium-range track forecasts.

Restricted access
Maria Pyrina, Marcel Nonnenmacher, Sebastian Wagner, and Eduardo Zorita

Abstract

Statistical climate prediction has sometimes demonstrated higher accuracy than coupled dynamical forecast systems. This study tests the applicability of springtime soil moisture (SM) over Europe and sea surface temperatures (SSTs) of three North Atlantic (NA) regions as statistical predictors of European mean summer temperature (t2m). We set up two statistical-learning (SL) frameworks, based on methods commonly applied in climate research. The SL models are trained with gridded products derived from station, reanalysis, and satellite data (ERA-20C, ERA-Land, CERA, COBE2, CRU, and ESA-CCI). The predictive potential of SM anomalies in statistical forecasting had so far remained elusive. Our statistical models trained with SM achieve high summer t2m prediction skill in terms of Pearson correlation coefficient (r), with r≥0.5 over Central and Eastern Europe. Moreover, we find that the reanalysis and satellite SM data contain similar information that can be extracted by our methods and used in fitting the forecast models.

Furthermore, the predictive potential of SSTs within different areas in the NA basin was tested. The predictive power of SSTs might increase, as in our case, when specific areas are selected. Forecasts based on extratropical SSTs achieve high prediction skill over South Europe. The combined prediction, using SM and SST predictor data, results in r≥0.5 over all European regions south of 50°N and east of 5°W. This is a better skill than the one achieved by other prediction schemes based on dynamical models. Our analysis highlights specific NA mid-latitude regions that are more strongly connected to summer mean European temperature.

Restricted access
Dhruv Balwada, Qiyu Xiao, Shafer Smith, Ryan Abernathey, and Alison R. Gray

Abstract

It has been hypothesized that submesoscale flows play an important role in the vertical transport of climatically important tracers, due to their strong associated vertical velocities. However, the multi-scale, non-linear, and Lagrangian nature of transport makes it challenging to attribute proportions of the tracer fluxes to certain processes, scales, regions, or features. Here we show that criteria based on the surface vorticity and strain joint probability distribution function (JPDF) effectively decomposes the surface velocity field into distinguishable flow regions, and different flow features, like fronts or eddies, are contained in different flow regions. The JPDF has a distinct shape and approximately parses the flow into different scales, as stronger velocity gradients are usually associated with smaller scales. Conditioning the vertical tracer transport on the vorticity-strain JPDF can therefore help to attribute the transport to different types of flows and scales. Applied to a set of idealized Antarctic Circumpolar Current simulations that vary only in horizontal resolution, this diagnostic approach demonstrates that small-scale strain dominated regions that are generally associated with submesoscale fronts, despite their minuscule spatial footprint, play an outsized role in exchanging tracers across the mixed layer base and are an important contributor to the large-scale tracer budgets. Resolving these flows not only adds extra flux at the small scales, but also enhances the flux due to the larger-scale flows.

Restricted access
Zongsheng Zheng, Chenyu Hu, Zhaorong Liu, Jianbo Hao, Qian Hou, and Xiaoyi Jiang

Abstract

Tropical cyclone, also known as typhoon, is one of the most destructive weather phenomena. Its intense cyclonic eddy circulations often cause serious damages to coastal areas. Accurate classification or prediction for typhoon intensity is crucial to the disaster warning and mitigation management. But typhoon intensity-related feature extraction is a challenging task as it requires significant pre-processing and human intervention for analysis, and its recognition rate is poor due to various physical factors such as tropical disturbance. In this study, we built a Typhoon-CNNs framework, an automatic classifier for typhoon intensity based on convolutional neural network (CNN). Typhoon-CNNs framework utilized a cyclical convolution strategy supplemented with dropout zero-set, which extracted sensitive features of existing spiral cloud band (SCB) more effectively and reduces over-fitting phenomenon. To further optimize the performance of Typhoon-CNNs, we also proposed the improved activation function (T-ReLU) and the loss function (CE-FMCE). The improved Typhoon-CNNs was trained and validated using more than 10,000 multiple sensor satellite cloud images of National Institute of Informatics. The classification accuracy reached to 88.74%. Compared with other deep learning methods, the accuracy of our improved Typhoon-CNNs was 7.43% higher than ResNet50, 10.27% higher than InceptionV3 and 14.71% higher than VGG16. Finally, by visualizing hierarchic feature maps derived from Typhoon-CNNs, we can easily identify the sensitive characteristics such as typhoon eyes, dense-shadowing cloud areas and SCBs, which facilitates classify and forecast typhoon intensity.

Restricted access
Jian Rao, Chaim I. Garfinkel, and Ian P. White

Abstract

Using the Model of an Idealized Moist Atmosphere (MiMA) capable of spontaneously generating a Quasi-Biennial Oscillation (QBO), the gradual establishment of the extratropical response to the QBO is explored. The period and magnitude of the QBO and the magnitude of the polar Holton-Tan (HT) relationship is simulated in a free-running configuration of MiMA, comparable to that in state-of-the-art climate models. In order to isolate mechanisms whereby the QBO influences variability outside of the tropical atmosphere, a series of branch experiments are performed with nudged QBO winds. When easterly QBO winds maximized around 30 hPa are relaxed, an Eliassen-Palm (E-P) flux divergence dipole quickly forms in the extratropical middle stratosphere as a direct response to the tropical meridional circulation, in contrast to the HT mechanism which is associated with wave propagation near the zero wind line. This meridional circulation response to the relaxed QBO winds develops within the first 10 days in seasonally-varying and fixed-seasonal experiments. No detectable changes in upward propagation of waves in the midlatitude lowermost stratosphere are evident for at least 20 days after branching, with the first changes only evident after 20 days in perpetual midwinter and season-varying runs, but after 40 days in perpetual November runs. The polar vortex begins to respond around the 20th day, and subsequently a near-surface response in the Atlantic sector forms in mid-to-late winter runs. These results suggest that the maximum near-surface response observed in mid-to-late winter is not simply due to a random seasonal synchronization of the QBO phase, but also due to the long (short) lag of the surface response to a QBO relaxation in early (mid-to-late) winter.

Restricted access