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Tobias Kukulka and Todd X. Thoman

Abstract

Dispersion processes in the ocean surface boundary layer (OSBL) determine marine material distributions such as those of plankton and pollutants. Sheared velocities drive shear dispersion, which is traditionally assumed to be due to mean horizontal currents that decrease from the surface. However, OSBL turbulence supports along-wind jets; located in near-surface convergence and downwelling regions, such turbulent jets contain strong local shear. Through wind-driven idealized and large-eddy simulation (LES) models of the OSBL, this study examines the role of turbulent along-wind jets in dispersing material. In the idealized model, turbulent jets are generated by prescribed cellular flow with surface convergence and associated downwelling regions. Numeric and analytic model solutions reveal that horizontal jets substantially contribute to along-wind dispersion for sufficiently strong cellular flows and exceed contributions due to vertical mean shear for buoyant surface-trapped material. However, surface convergence regions also accumulate surface-trapped material, reducing shear dispersion by jets. Turbulence resolving LES results of a coastal depth-limited ocean agree qualitatively with the idealized model and reveal long-lived coherent jet structures that are necessary for effective jet dispersion. These coastal results indicate substantial jet contributions to along-wind dispersion. However, jet dispersion is likely less effective in the open ocean because jets are shorter lived, less organized, and distorted due to spiraling Ekman currents.

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Chen Zhang, Hua Liao, Fang-Zhi Wang, and Ru Li

Abstract

Human behaviors are believed to be sensitive to environmental conditions. However, little is known about the role of temperature in individual daily behaviors. We examine the links between temperature and food intake using nearly one million purchasing records from China. The results show that a 1°C increase in temperature would cause a 0.11% decrease in food intake, which amounts to USD 4.2 million of daily food expenditures nationwide. Moreover, females appear to be more sensitive to the temperature in their food intake than males. In addition, we observe a U-shaped relationship between the temperature and the willingness to order a takeout online, and this observation is robust under multiple alternative estimations. Our results indicate that a higher temperature would reduce energy demand for body thermoregulation, resulting in less food intake. Both extreme high and low temperatures can cause disutility. Therefore, the consumers who still want to satisfy their needs for food intake feel compelled to alter their willingness to pay under the extreme temperature events. The quantitative analysis can provide helpful references for modeling the climate–consumer relationship in integrated assessment models. Thus, it is an interesting avenue for future research to bridge the climate and consumers to identify welfare loss and inequality due to climate change.

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Katie A. Wilson, Burkely T. Gallo, Patrick Skinner, Adam Clark, Pamela Heinselman, and Jessica J. Choate

Abstract

Convection-allowing model ensemble guidance, such as that provided by the Warn-on-Forecast System (WoFS), is designed to provide predictions of individual thunderstorm hazards within the next 0–6 h. The WoFS web viewer provides a large suite of storm and environmental attribute products, but the applicability of these products to the National Weather Service forecast process has not been objectively documented. Therefore, this study describes an experimental forecasting task designed to investigate what WoFS products forecasters accessed and how they accessed them for a total of 26 cases (comprising 13 weather events, each worked by two forecasters). Analysis of web access log data revealed that, in all 26 cases, product accesses were dominated in the reflectivity, rotation, hail, and surface wind categories. However, the number of different product types viewed and the number of transitions between products varied in each case. Therefore, the Levenshtein (edit distance) method was used to compute similarity scores across all 26 cases, which helped to identify what it meant for relatively similar versus dissimilar navigation of WoFS products. The Spearman’s rank correlation coefficient R results found that forecasters working the same weather event had higher similarity scores for events that produced more tornado reports and for events in which forecasters had higher performance scores. The findings from this study will influence subsequent efforts for further improving WoFS products and developing an efficient and effective user interface for operational applications.

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Makenzie J. Krocak, Jinan N. Allan, Joseph T. Ripberger, Carol L. Silva, and Hank C. Jenkins-Smith

Abstract

Nocturnal tornadoes are challenging to forecast and even more challenging to communicate. Numerous studies have evaluated the forecasting challenges, but fewer have investigated when and where these events pose the greatest communication challenges. This study seeks to evaluate variation in confidence among U.S. residents in receiving and responding to tornado warnings by hour of day. Survey experiment data come from the Severe Weather and Society Survey, an annual survey of U.S. adults. Results indicate that respondents are less confident about receiving warnings overnight, specifically in the early morning hours [from 12:00 AM to 4:00 AM local time (0000–0400 LT)]. We then use the survey results to inform an analysis of hourly tornado climatology data. We evaluate where nocturnal tornadoes are most likely to occur during the time frame when residents are least confident in their ability to receive tornado warnings. Results show that the Southeast experiences the highest number of nocturnal tornadoes during the time period of lowest confidence, as well as the largest proportion of tornadoes in that time frame. Finally, we estimate and assess two multiple linear regression models to identify individual characteristics that may influence a respondent’s confidence in receiving a tornado between 12:00 AM and 4:00 AM. These results indicate that age, race, weather awareness, weather sources, and the proportion of nocturnal tornadoes in the local area relate to warning reception confidence. The results of this study should help inform policymakers and practitioners about the populations at greatest risk for challenges associated with nocturnal tornadoes. Discussion focuses on developing more effective communication strategies, particularly for diverse and vulnerable populations.

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Ren-Jie Wu, Min-Hui Lo, and Bridget R. Scanlon

Abstract

The terrestrial water storage anomaly (TWSA) is a critical component of the global water cycle where improved spatiotemporal dynamics would enhance exploration of weather- and climate-linked processes. Thus, correctly simulating TWSA is essential not only for water-resource management but also for assessing feedbacks to climate through land–atmosphere interactions. Here we evaluate simulated TWSA from 25 climate models (from phase 6 of the Climate Model Intercomparison Project) through comparison with TWSA from GRACE satellite data (2003–14) in 14 river basins globally and assess causes of discrepancies by examining precipitation (P), evapotranspiration (ET), and runoff (R off) fluxes during recharge (increasing TWS) and discharge (decreasing TWS) cycles. Most models show consistent biases in seasonal amplitudes of TWS anomalies relative to GRACE output: higher modeled amplitudes in river basins in high northern latitudes and the Parana and Congo basins, and lower amplitudes in most midlatitude basins and other tropical basins. This TWSA systematic bias also exists in the previous CMIP5 simulations. Models overestimate P compared to observed P datasets in 7 out of 14 basins, which increases (decreases) seasonal storage amplitude relative to GRACE in the recharge (discharge) cycle. Overestimation (underestimation) of runoff is another common contributing factor in the discharge phase that increases (decreases) TWSA amplitudes relative to GRACE in five river basins. The results provide a comprehensive assessment of the reliability of the simulated annual range in TWSA through comparison with GRACE data that can be used to guide future model development.

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Zeke Baker

Abstract

A major implication of climate change is the declining capacity for communities to anticipate future conditions and scenarios. In the Bering Sea region of western Alaska, this situation is acute and holds manifold consequences, particularly for the region’s primarily Indigenous residents. Based upon interviews and fieldwork in two Bering Sea communities and among regional weather forecasters, this paper explores the intertwined temporalities of weather, climate, and social life. I demonstrate that anticipatory culture, which otherwise structures anticipatory practices with regard to climate, local weather, and social life, is beset by temporal dissonance across three time scales. First, dramatic climatic and ecosystem shifts reshape how Indigenous Peoples envision themselves as culturally inhabiting a long-range history and future. Second, changes in weather patterns, ecological cycles, and sea ice dynamics upset evaluations of seasonality, leading to a pervasive sense of unpredictability. Third, on the everyday time scale, social and technological change complicates mariners’ evaluations of risk and economic (commercial and subsistence) decision-making. I conclude by connecting these three socioenvironmental temporalities to the temporal frames that primarily characterize weather and climate services, with an emphasis on the U.S. National Weather Service. The paper discusses how such services may further orient toward engaging socially embedded practices of anticipation in addition to formal prediction. Such an orientation can help to shape an anticipatory culture that more closely aligns meteorological and social patterns.

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Temple R. Lee, Michael Buban, and Tilden P. Meyers

Abstract

Monin–Obukhov similarity theory (MOST) has long been used to represent surface–atmosphere exchange in numerical weather prediction (NWP) models. However, recent work has shown that bulk Richardson (Rib) parameterizations, rather than traditional MOST formulations, better represent near-surface wind, temperature, and moisture gradients. So far, this work has only been applied to unstable atmospheric regimes. In this study, we extended Rib parameterizations to stable regimes and developed parameterizations for the friction velocity (u *), sensible heat flux (H), and latent heat flux (E) using datasets from the Land-Atmosphere Feedback Experiment (LAFE). We tested our new Rib parameterizations using datasets from the Verification of the Origins of Rotation in Tornadoes Experiment-Southeast (VORTEX-SE) and compared the new Rib parameterizations with traditional MOST parameterizations and MOST parameterizations obtained using the LAFE datasets. We found that fitting coefficients in the MOST parameterizations developed from LAFE datasets differed from the fitting coefficients in classical MOST parameterizations which we attributed to the land surface heterogeneity present in the LAFE domain. Regardless, the new Rib parameterizations performed just as well as, and in some instances better than, the classical MOST parameterizations and the MOST parameterizations developed from the LAFE datasets. The improvement was most evident for H, particularly for H under unstable conditions, which was based on a better 1:1 relationship between the parameterized and observed values. These findings provide motivation to transition away from MOST and to implement bulk Richardson parameterizations into NWP models to represent surface–atmosphere exchange.

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Shasha Shang, Gaofeng Zhu, Jianhui Wei, Yan Li, Kun Zhang, Ruolin Li, Joël Arnault, Zhenyu Zhang, Patrick Laux, Qianya Yang, Ningpeng Dong, Lu Gao, and Harald Kunstmann

Abstract

Precipitation in the Three-River Headwater (TRH) region has undergone significant changes as a result of global warming, which can affect water resources in downstream regions of Asia. However, the underlying mechanisms of the precipitation variability during the cold season (October–April) are still not fully understood. In this study, the daily China gridded precipitation product CN05.1 as well as the NCEP–NCAR reanalysis are used to investigate the characteristics of the cold season precipitation variability over the TRH region and associated atmospheric mechanisms. The cold season precipitation shows an increasing trend (5.5 mm decade−1) from 1961 to 2014, with a dry-to-wet shift in around the late 1980s. The results indicate that the increased precipitation is associated with the enhanced easterly anomalies over the Tibetan Plateau (TP) and enhanced southeasterly water vapor transport. The enhanced Walker circulations, caused by the gradients of sea surface temperature between the equatorial central-eastern Pacific and Indo–western Pacific in tropical oceans, resulted in strengthened easterly anomalies over the TP and the westward expansion of the anticyclone in the western North Pacific. Meanwhile, the changed Walker circulation is accompanied by a strengthened local Hadley circulation, which leads to enhanced meridional water vapor transport from tropical oceans and the South China Sea toward the TRH region. Furthermore, the strengthened East Asia subtropical westerly jet may contribute to the enhanced divergence at upper levels and anomalous ascending motion above the TRH region, leading to more precipitation.

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Randal D. Koster, Anthony M. DeAngelis, Siegfried D. Schubert, and Andrea M. Molod

Abstract

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

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Kosuke Ono

Abstract

This study extends Bayesian model averaging (BMA) to a form suitable for time series forecasts. BMA is applied to a three-member ensemble for temperature forecasts with a 1-h interval time series at specific stations. The results of such an application typically have problematic characteristics. BMA weights assigned to ensemble members fluctuate widely within a few hours because BMA optimizations are independent at each lead time, which is incompatible with the spatiotemporal continuity of meteorological phenomena. To ameliorate this issue, a degree of correlation among different lead times is introduced by the extension of latent variables to lead times adjacent to the target lead time for the calculation of BMA weights and variances. This extension approach stabilizes the BMA weights, improving the performance of deterministic and probabilistic forecasts. Also, an investigation of the effects of this extension technique on the shapes of forecasted probability density functions showed that the extension approach offers advantages in bimodal cases. This extension technique may show promise in other applications to improve the performance of forecasts by BMA.

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