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Aiguo Dai and Jiechun Deng

Abstract

Arctic amplification (AA) reduces meridional temperature gradients (dT/dy) over the northern mid-high latitudes, which may weaken westerly winds. It is suggested that this may lead to wavier and more extreme weather in the midlatitudes. However, temperature variability is shown to decrease over the northern mid-high latitudes under increasing greenhouse gases due to reduced dT/dy. Here, through analyses of coupled model simulations and ERA5 reanalysis, it is shown that consistent with previous studies, cold-season surface and lower-mid troposphere temperature (T) variability decreases over northern mid-high latitudes even in simulations with suppressed AA and sea ice loss under increasing CO2; however, AA and sea ice loss further reduce the T variability greatly, leading to a narrower probability distribution and weaker cold or warm extreme events relative to future mean climate. Increased CO2 strengthens meridional wind (υ) with a wavenumber-4 pattern but weakens meridional thermal advection [−υ(dT/dy)] over most northern mid-high latitudes, and AA weakens the climatological υ and −υ(dT/dy). The weakened thermal advection and its decreased variance are the primary causes of the T variability decrease, which is enlarged by a positive feedback between the variability of T and −υ(dT/dy). AA not only reduces dT/dy, but also its variance, which further decreases T variability through −υ(dT/dy). While the mean snow and ice cover decreases, its variability increases over many northern latitudes, and these changes do not weaken the T variability. Thus, AA’s influence on midlatitude temperature variability comes mainly from its impact on thermal advection, rather than on winds as previously thought.

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Stephen M. Strader, Alex M. Haberlie, and Alexandra G. Loitz

Abstract

This study investigates the interrelationships between National Weather Service (NWS) county warning area (CWA) tornado risk, exposure, and societal vulnerability. CWA climatological tornado risk is determined using historical tornado event data, and exposure and vulnerability are assessed by employing present-day population, housing, socioeconomic, and demographic metrics. In addition, tornado watches, warnings, warning lead times, false alarm warnings, and unwarned tornado reports are examined in relation to CWA risk, exposure, and vulnerability. Results indicate that southeastern U.S. CWAs are more susceptible to tornado impacts because of their greater tornado frequencies and larger damage footprints intersecting more vulnerable populations (e.g., poverty and manufactured homes). Midwest CWAs experience fewer tornadoes relative to Southeast and southern plains CWAs but encompass faster tornado translational speeds and greater population densities where higher concentrations of vulnerable individuals often reside. Northern plains CWAs contain longer-tracked tornadoes on average and larger percentages of vulnerable elderly and rural persons. Southern plains CWAs experience the highest tornado frequencies in general and contain larger percentages of minority Latinx populations. Many of the most socially vulnerable CWAs have shorter warning lead times and greater percentages of false alarm warnings and unwarned tornadoes. Study findings provide NWS forecasters with an improved understanding of the relationships between tornado risk, exposure, vulnerability, and warning outcomes within their respective CWAs. Findings may also assist NWS Weather Forecast Offices and the Warning Decision Training Division with developing training materials aimed at increasing NWS forecaster knowledge of how tornado risk, exposure, and vulnerability factors influence local tornado disaster potential.

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Vikram S. Negi, Shinny Thakur, Rupesh Dhyani, Indra D. Bhatt, and Ranbeer S. Rawal

Abstract

Mountains are important global sites for monitoring biological and socioecological responses to climate change, and the Himalaya has some of the world’s most rapid and visible signs of climate change. The increased frequency and severity of climate anomalies in the region are expected to significantly affect livelihoods of indigenous communities in the region. This study documents the perceptions of indigenous communities of climate change in the western Himalaya of India. The study highlights the power of knowledge and understanding available to indigenous people as they observe and respond to climate change impacts. We conducted a field-based study in 14 villages that represent diverse socioecological features along an altitudinal range of 1000–3800 m MSL in the western Himalaya. Among the sampled population, most of the respondents (>95%) agreed that climate is changing. However, people residing at low- and high-altitude villages differ significantly in their perception, with more people at high altitudes believing in an overall warming trend. Instrumental temperature and rainfall from nearby meteorological stations also supported the perception of local inhabitants. The climate change perceptions in the region were largely determined by sociodemographic variables such as age, gender, and income as well as altitude. A logistic regression, which exhibited significant association of sociodemographic characteristics with climate change perceptions, further supported these findings. The study concluded that the climate change observations of local communities can be usefully utilized to develop adaptation strategies and mitigation planning in the Himalayan region.

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Alvaro Avila-Diaz, David H. Bromwich, Aaron B. Wilson, Flavio Justino, and Sheng-Hung Wang

ABSTRACT

Atmospheric reanalyses are a valuable climate-related resource where in situ data are sparse. However, few studies have investigated the skill of reanalyses to represent extreme climate indices over the North American Arctic, where changes have been rapid and indigenous responses to change are critical. This study investigates temperature and precipitation extremes as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over a 17-yr period (2000–16) for regional and global reanalyses, namely the Arctic System Reanalysis, version 2 (ASRv2); North American Regional Reanalysis (NARR); European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis; Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2); and Global Meteorological Forcing Dataset for Land Surface Modeling (GMFD). Results indicate that the best performances are demonstrated by ASRv2 and ERA5. Relative to observations, reanalyses show the weakest performance over far northern basins (e.g., the Arctic and Hudson basins) where observing networks are less dense. Observations and reanalyses show consistent warming with decreased frequency and intensity of cold extremes. Cold days, cold nights, frost days, and ice days have decreased dramatically over the last two decades. Warming can be linked to a simultaneous increase in daily precipitation intensity over several basins in the domain. Moreover, the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) distinctly influence extreme climate indices. Thus, these findings detail the complexity of how the climate of the Arctic is changing, not just in an average sense, but in extreme events that have significant impacts on people and places.

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Carol R. Ember, Ian Skoggard, Benjamin Felzer, Emily Pitek, and Mingkai Jiang

Abstract

All societies have religious beliefs, but societies vary widely in the number and type of gods in which they believe as well as their ideas about what the gods do. In many societies, a god is thought to be responsible for weather events. In some of those societies, a god is thought to cause harm with weather and/or can choose to help, such as by bringing needed rain. In other societies, gods are not thought to be involved with weather. Using a worldwide, largely nonindustrial sample of 46 societies with high gods, this research explores whether certain climate patterns predict the belief that high gods are involved with weather. Our major expectation, largely supported, was that such beliefs would most likely be found in drier climates. Cold extremes and hot extremes have little or no relationship to the beliefs that gods are associated with weather. Since previous research by Skoggard et al. showed that greater resource stress predicted the association of high gods with weather, we also tested mediation path models to help us evaluate whether resource stress might be the mediator explaining the significant associations between drier climates and high god beliefs. The climate variables, particularly those pertaining to dryness, continue to have robust relationships to god beliefs when controlling on resource stress; at best, resource stress has only a partial mediating effect. We speculate that drought causes humans more anxiety than floods, which may result in the greater need to believe supernatural beings are not only responsible for weather but can help humans in times of need.

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Xiaofang Feng and Liguang Wu

Abstract

The tropospheric warming in the Northern Hemisphere (NH) midlatitudes has been an important factor in regulating weather and climate since the twentieth century. Apart from anthropogenic forcing leading to the midlatitude warming, this study investigates the possible contribution of internal variability to Asian midlatitude warming and its role in East Asian circulation changes in boreal summer, using four reanalysis datasets in the past century and a set of 1800-yr preindustrial control simulations of the Community Earth System Model version 1 large ensemble (CESM-LE). The surface and tropospheric warming in the Asian midlatitudes is associated with a strong upper-level geopotential height rise north of the Tibetan Plateau (TP). Linear trends of 200-hPa geopotential height (Z200) confirm a dipole of an anomalous high north of the TP and an anomalous low over the Iranian Plateau in 1958–2017. The leading internal circulation mode bears a striking resemblance to the Z200 trend in the past 60 and 111 years, indicating that the long-term trend may be partially of internal origin. The Asian midlatitude warming is also found in preindustrial simulations of CESM-LE, further suggesting that internal variability explains at least part of the temperature change in the Asian midlatitudes, which is in a chain of wave trains along the NH midlatitudes. The Asian warming decreases the meridional gradient of geopotential height, resulting in the weakening of westerly winds over the TP and the TP thermal forcing. Thus, it is essential to consider the role of internal variability in shaping East Asian surface temperature and East Asian summer monsoon changes in the past decades.

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Jing Ma, Shang-Ping Xie, Haiming Xu, Jiuwei Zhao, and Leying Zhang

Abstract

Using the ensemble hindcasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) coupled model for the period of 1980–2005, spatiotemporal evolution in the covariability of sea surface temperature (SST) and low-level winds in the ensemble mean and spread over the tropical Atlantic is investigated with the month-reliant singular value decomposition (SVD) method, which treats the variables in a given monthly sequence as one time step. The leading mode of the ensemble mean represents a coevolution of SST and winds over the tropical Atlantic associated with a phase transition of El Niño from the peak to decay phase, while the second mode is related to a phase transition from El Niño to La Niña, indicating a precursory role of the north tropical Atlantic (NTA) SST warming in La Niña development. The leading mode of ensemble spread in SST and winds further illustrates that an NTA SST anomaly acts as a precursor for El Niño–Southern Oscillation (ENSO). A north-tropical pathway for the delayed effect of the NTA SST anomaly on the subsequent ENSO event is identified; the NTA SST warming induces the subtropical northeast Pacific SST cooling through the modulation of a zonal–vertical circulation, setting off a North Pacific meridional mode (NPMM). The coupled SST–wind anomalies migrate southwestward to the central equatorial Pacific and eventually amplify into a La Niña event in the following months due to the equatorial Bjerknes feedback. Ensemble spread greatly increases the sample size and affords insights into the interbasin interactions between the tropical Atlantic and Pacific, as demonstrated here in the NTA SST impact on ENSO.

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Chenli Wang, Kun Zhao, Anning Huang, Xingchao Chen, and Xiaona Rao

Abstract

The South China coast suffers frequent heavy rainfall every warm season. Based on the objective classification method of principal components analysis, the key role of the synoptic pattern in determining the heavy rainfall processes that occurred over the South China coast in the warm season during 2008–18 is examined in this study. We found that heavy rainfall occurs most frequently under three typical synoptic patterns (P1–P3 hereafter) characterized by strong low-level onshore winds. P1 and P3 feature a prevailing southwesterly monsoonal flow in the lower troposphere, with heavy rainfall frequently occurring over the inland windward region in the afternoon associated with the orographic lifting and solar heating. The onshore wind of P3 is stronger than P1 as the western Pacific subtropical high extends more westward to 122°E, which induces stronger low-level convergence along the coastline than P1 when the ageostrophic wind veers from the offshore to onshore direction in the early morning. Hence, a secondary early morning rainfall peak can be found along the coastline. P2 is characterized by a low-level vortex located over the southwest portion of south China. Heavy rainfall under P2 usually initiates over the western part of the coastal region in the morning and then propagates inland in the afternoon. Overall, the synoptic patterns strongly determine the spatial distribution and diurnal cycle of heavy rainfall over the South China coast. This heavy rainfall is closely related to the diurnally varying low-level onshore winds rather than the low-level jets, as well as the different interactions between the low-level onshore winds and the local orography, coastline, and land–sea breeze circulations under different synoptic patterns.

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Zhe Feng, Fengfei Song, Koichi Sakaguchi, and L. Ruby Leung

Abstract

A process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the United States. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation features at 12-, 25-, and 50-km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency, and intensity are found to be consistently underestimated in the central United States, particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while the MCS precipitation area is too large and its intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during the daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

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Yu-Hsuan Lin, Hen-I Lin, Fang-I Wen, and Sheng-Jang Sheu

Abstract

A better understanding of farmers’ investment strategies associated with climate and weather is crucial to protecting farming and other climate-exposed sectors from extreme hydrometeorological events. Accordingly, this study employed a field experiment to investigate the investment decisions under risk and uncertainty by 213 farmers from four regions of Taiwan. Each was asked 30 questions that paired “no investment,” “investment with crop insurance,” “investment with subsidized crop insurance,” and “investment” as possible responses. By providing imperfect information and various probabilities of certain states occurring, the experimental scenarios mimicked various types of weather-forecasting services. As well as their socioeconomic characteristics, the background information we collected about the participants included their experiences of natural disasters and what actions they take to protect their crops from weather damage. The sampled farmers became more conservative in their decision-making as the weather forecasts they received became more precise, except when increases in risk were associated with high returns. The provision of insurance subsidies also had a conservatizing effect. However, considerable variation in investment preferences was observed according to the farmers’ crop types. For those seeking to create comprehensive policies aimed at helping the agricultural sector deal with the costs of damage from extreme events, this study has important implications. This approach could be extended to research on the perceptions of decision-makers in other climate-exposed sectors such as the construction industry.

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