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Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement: Numerical weather prediction (NWP) is the "go-to" approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) can be used to improve performance across a wide range of Earth system prediction tasks. As with any application of AI, it is important for AI to be developed in an ethical and responsible manner to minimize bias and other effects. In this work, we extend our previous work demonstrating how AI can go wrong with weather and climate applications by presenting a categorization of bias for AI in the Earth sciences. This categorization can assist AI developers to identify potential biases that can affect their model throughout the AI development life cycle. We highlight examples from a variety of Earth system prediction tasks of each category of bias. SIGNIFICANCE STATEMENT: As artificial intelligence (AI) grows in popularity, its methods are being applied to a wide range of Earth system prediction tasks. Although AI can facilitate more accurate prediction at many tasks, it is not without potential pitfalls, especially if the developers are not as familiar with its potential drawbacks. In this paper, we provide a classification system for the types of bias that one is likely to see in applying AI to Earth sciences. Our classification system will assist current and future AI developers to recognize where their AI system or data are biased so they can take steps to alleviate this bias. [ABSTRACT FROM AUTHOR]

An unprecedented heat wave occurred over the Pacific Northwest and southwest Canada on 25–30 June 2021, resulting in all-time temperature records that greatly exceeded previous record maximum temperatures. The impacts were substantial, including several hundred deaths, thousands of hospitalizations, a major wildfire in Lytton, British Columbia, Canada, and severe damage to regional vegetation. Several factors came together to produce this extreme event: a record-breaking midtropospheric ridge over British Columbia in the optimal location, record-breaking midtropospheric temperatures, strong subsidence in the lower atmosphere, low-level easterly flow that produced downslope warming on regional terrain and the removal of cooler marine air, an approaching low-level trough that enhanced downslope flow, the occurrence at a time of maximum insolation, and drier-than-normal soil moisture. It is shown that all-time-record temperatures have not become more frequent and that annual high temperatures only increased at the rate of baseline global warming. Although anthropogenic warming may have contributed as much as 1°C to the event, there is little evidence of further amplification from increasing greenhouse gases. Weather forecasts were excellent for this event, with highly accurate predictions of the extreme temperatures. Significance Statement: This paper describes the atmospheric evolution that produced an extreme heat wave over the Pacific Northwest during June 2021 and puts this event into historical perspective. [ABSTRACT FROM AUTHOR]

Summer drought over northern Asia (NA) seriously threatens the local fragile ecological environment and social economy development. In this study, using the standardized precipitation evapotranspiration index (SPEI), we first identify the dominant modes of interannual variability in summer drought condition over NA and then explore the atmospheric patterns responsible for the formation of the modes. The results show that the first empirical orthogonal function (EOF1) mode of summer SPEI over NA exhibits a meridional dipole pattern, which is influenced primarily by the polar–Eurasian teleconnection (POL) and circumglobal teleconnection (CGT) patterns. Under the influence of negative POL and positive CGT patterns, there is an anomalous anticyclone (cyclone) over northwestern Siberia (Lake Baikal to Northeast China). Such atmospheric circulations lead to meridional dipole patterns in air temperature, moisture condition, vertical motion, and cloud cover over NA, favoring decreased (increased) precipitation and increased (decreased) potential evapotranspiration over northern (southern) NA, finally contributing to the formation of EOF1. The second EOF (EOF2) shows an approximate zonal dipole pattern, which is influenced by the British–Baikal Corridor (BBC) and Scandinavia (SCA) teleconnection patterns. The positive BBC and SCA patterns can lead to an anomalous anticyclone over the Ural Mountains and a cyclone over Lake Baikal. Such atmospheric circulations result in a zonal dipole pattern in precipitation and potential evapotranspiration over NA through changing the local moisture condition, air temperature, and radiation, consequently favoring the formation of EOF2. Fitting analysis indicates that the aforementioned atmospheric factors can explain 76% (55%) of the interannual variability of EOF1 (EOF2). [ABSTRACT FROM AUTHOR]

This article explores the challenges posed by extreme weather and climate-related events and the inadequacy of current resilience and adaptation frameworks. It discusses the "Exploring Unprecedented Extremes" workshop held in Montreal, Canada, which aimed to address the research gap in understanding and preparing for these events. The workshop emphasized the need for transformational changes in governance and the integration of diverse perspectives to effectively respond to climate extremes. It also highlighted the importance of effective communication and coproduction of knowledge in bridging the gap between scientific research and decision-making. The article provides examples of recent extreme events and emphasizes the urgency of addressing these challenges. It discusses the importance of understanding different ways of knowing and establishing trust in research collaborations, as well as exploring various modeling approaches used to study climate change and extreme weather events. The text concludes by emphasizing the need for a shift in perspective and the adoption of transdisciplinary approaches to effectively address climate extremes. The workshop served as a foundation for examining the impacts of climate change and identifying strategies for adaptation and transformation, and the text emphasizes the urgency of taking action and promoting understanding among individuals, communities, and organizations. [Extracted from the article]

Improved representation of turbulent processes in numerical models of tropical cyclones (TCs) is expected to improve intensity forecasts. To this end, the authors use a large-eddy simulation (with 31-m horizontal grid spacing) of an idealized category 5 TC to understand the role of turbulent processes in the inner core of TCs and their role on the mean intensity. Azimuthally and temporally averaged budgets of the momentum fields show that TC turbulence acts to weaken the maximum tangential velocity, diminish the strength of radial inflow into the eye, and suppress the magnitude of the mean eyewall updraft. Turbulent flux divergences in both the vertical and radial directions are shown to influence the TC mean wind field, with the vertical being dominant in most of the inflowing boundary layer and the eyewall (analogous to traditional atmospheric boundary layer flows), while the radial becomes important only in the eyewall. The validity of the downgradient eddy viscosity hypothesis is largely confirmed for mean velocity fields, except in narrow regions which generally correspond to weak gradients of the mean fields, as well as a narrow region in the eye. This study also provides guidance for values of effective eddy viscosities and vertical mixing length in the most turbulent regions of intense TCs, which have rarely been measured observationally. A generalized formulation of effective eddy viscosity (including the Reynolds normal stresses) is presented. Significance Statement: This study uses a turbulence-resolving simulation of a category 5 tropical cyclone to understand the role of turbulence in intense storms. Results show that turbulence clearly modulates storm structure and intensity. This study provides guidance for the values of turbulent quantities (which are usually parameterized in comparatively coarse operational TC forecast models) in scarcely observed regions of intense storms. Furthermore, a complete formulation of the effective eddy viscosities is proposed, incorporating contributions from typically ignored Reynolds normal stress terms. [ABSTRACT FROM AUTHOR]

Evaluating the accuracy of various precipitation datasets over ungauged or even sparse-gauge areas is a challenging task. Cross-validation methods can evaluate three or more datasets based on the error independence from input data, without relying on ground observations. Here, the triple collocation (TC) method is employed to evaluate multisource precipitation datasets: China Gauge-based Daily Precipitation Analysis (CGDPA), model-based ERA5, and satellite-derived IMERG-Early, IMERG-Late, GSMaP in near–real time (GSMaP-NRT), and GSMaP moving vector with Kalman filter (GSMaP-MVK) over the Tibetan Plateau (TP). TC-based results show that ERA5 has better performances than satellite-only precipitation products over mountainous regions with complex terrains. For purely satellite-derived products, IMERG products outperform GSMaP products. Considering the potential existence of error dependencies among input datasets, caution should be exercised. Thus, it is necessary to introduce an alternative cross-validation method (generalized three-cornered hat) and explore the applicability of cross validation from the perspective of error independence. We found that cross-validation methods have high applicability in most TP regions with sparse-gauge density (accounting for about 80.1% of the total area). Additionally, we conducted simulation experiments to discuss the applicability and robustness of TC. The simulation results substantiated that cross validation can serve as a robust evaluation method over sparse-gauge regions. Although it is generally known that the cross-validation methods can be served in sparse-gauge regions, the application condition of different evaluation methods for precipitation products is identified quantitatively in TP now. Significance Statement: Cross validation is a powerful assessment method for multisource precipitation datasets. This method is widely used by hydrologists in sparse-gauge or ungauged regions, like the African continent and the Tibetan Plateau (TP). However, as an indirect assessment method, the inherent uncertainty in cross validation warrants emphasis. Here, two cross-validation methods (the triple collocation method and the generalized three-cornered hat method) are employed to evaluate multisource precipitation datasets: China Gauge-based Daily Precipitation Analysis (CGDPA), model-based ERA5, and satellite-derived IMERG-Early, IMERG-Late, GSMaP in near–real time (GSMaP-NRT), and GSMaP moving vector with Kalman filter (GSMaP-MVK) over the TP. In this study, we not only assessed the current mainstream six precipitation datasets but also analyzed their uncertainties by combining these two cross-validation methods. [ABSTRACT FROM AUTHOR]

The variability of stratospheric water vapor (SWV) plays a crucial role in stratospheric chemistry and Earth's energy budget, strongly influenced by sea surface temperature (SST). In this study, we systematically investigate the response of lower-SWV (LSWV) to regional sea surface temperature changes using idealized SST patch experiments within a climate model. The results indicate that LSWV is most sensitive to tropical sea surface temperature, with the strongest response occurring in late autumn and early winter. Warming of the tropical Indian Ocean and western Pacific (WP) leads to stratospheric drying, while warming of the tropical Atlantic (TA) and eastern Pacific results in stratospheric moistening. The drying impact on LSWV due to warming in the western Pacific Ocean exceeds the wet effect in the eastern Pacific Ocean by approximately 60%. The variations in tropical SST influence LSWV by modulating the temperature at the tropical tropopause layer, especially over the Indo-Pacific warm pool through Matsuno–Gill responses. Furthermore, the response of LSWV to tropical SST changes exhibits nonnegligible nonlinearity, which indicates the importance of nonlinearity in determining the LSWV response to global surface warming. Significance Statement: In this study, we explore how changes in the temperature of the ocean's surface can affect the amount of water vapor in the stratosphere, a layer of Earth's atmosphere. Understanding this relationship is important because water vapor in the stratosphere can influence both our climate and the chemistry of the atmosphere. Using a climate model, we found that water vapor in the lower stratosphere is especially responsive to temperature changes in tropical ocean regions. Specifically, when the Indian Ocean and the western Pacific get warmer, the stratosphere tends to get drier. On the other hand, warming in the Atlantic and eastern Pacific leads to more moisture in the stratosphere. The way these changes add up is complex and not simply a sum of individual parts, especially in tropical warm pool regions. Our findings have implications for how we understand and predict the impacts of climate change on stratospheric water vapor. [ABSTRACT FROM AUTHOR]

Parameterizations for internal gravity waves in atmospheric models are traditionally subject to a number of simplifications. Most notably, they rely on both neglecting wave propagation and advection in the horizontal direction (single-column assumption) and an instantaneous balance in the vertical direction (steady-state assumption). While these simplifications are well justified to cover some essential dynamic effects and keep the computational effort small, it has been shown that both mechanisms are potentially significant. In particular, the recently introduced Multiscale Gravity Wave Model (MS-GWaM) successfully applied ray-tracing methods in a novel type of transient but columnar internal gravity wave parameterization (MS-GWaM-1D). We extend this concept to a three-dimensional version of the parameterization (MS-GWaM-3D) to simulate subgrid-scale nonorographic internal gravity waves. The resulting global wave model—implemented into the weather forecast and climate code Icosahedral Nonhydrostatic (ICON)—contains three-dimensional transient propagation with accurate flux calculations, a latitude-dependent background source, and convectively generated waves. MS-GWaM-3D helps reproduce expected temperature and wind patterns in the mesopause region in the climatological zonal mean state and thus proves a viable internal gravity wave (IGW) parameterization. Analyzing the global wave action budget, we find that horizontal wave propagation is as important as vertical wave propagation. The corresponding wave refraction includes previously missing but well-known effects such as wave refraction into the polar jet streams. On a global scale, three-dimensional wave refraction leads to a horizontal flow-dependent redistribution of waves such that the structures of the zonal mean wave drag and consequently the zonal mean winds are modified. [ABSTRACT FROM AUTHOR]

Tropical cyclones are known to expand to an equilibrium size on the f plane, but the expansion process is not understood. In this study, an analytical model for tropical cyclone outer-size expansion on the f plane is proposed. Conceptually, the storm expands because the imbalance between latent heating and radiative cooling drives a lateral inflow that imports absolute vorticity. Volume-integrated latent heating increases more slowly with size than radiative cooling, and hence, the storm expands toward an equilibrium size. The predicted expansion rate is given by the ratio of the difference in size from its equilibrium value rt,eq to an environmentally determined time scale τrt of 10–15 days. The model is fully predictive if given a constant rt,eq, which can also be estimated environmentally. The model successfully captures the first-order size evolution across a range of numerical simulation experiments in which the potential intensity and f are varied. The model predictions of the dependencies of lateral inflow velocity and expansion rate on latent heating rate are also compared well with numerical simulations. This model provides a useful foundation for understanding storm size dynamics in nature. [ABSTRACT FROM AUTHOR]

Although many people believe their pain fluctuates with weather conditions, both weather and pain may be associated with time spent outside. For example, pleasant weather may mean that people spend more time outside doing physical activity and are exposed to the weather, leading to more (or less) pain, and poor weather or severe pain may keep people inside, sedentary, and not exposed to the weather. We conducted a smartphone study where participants with chronic pain reported daily pain severity, as well as time spent outside. We address the relationship between four weather variables (temperature, dewpoint temperature, pressure, and wind speed) and pain by proposing a three-step approach to untangle their effects: (i) propose a set of plausible directed acyclic graphs (DAGs) that account for potential roles of time spent outside (e.g., collider, effect modifier, mediator); (ii) analyze the compatibility of the observed data with the assumed model; and (iii) identify the most plausible model by combining evidence from the observed data and domain-specific knowledge. We found that the data do not support time spent outside as a collider or mediator of the relationship between weather variables and pain. On the other hand, time spent outside modifies the effect between temperature and pain, as well as wind speed and pain, with the effect being absent on days that participants spent inside and present if they spent some or all of the day outside. Our results show the utility of using directed acyclic graphs for studying causal inference. Significance Statement: Three-quarters of people living with chronic pain believe that weather influences their pain. However, people staying inside would not be exposed to the weather outside, and good weather may mean that people are more active outside, leading to more or less pain. To obtain data to calculate how the amount of time spent outside affects the weather–pain relationship, we conducted a 15-month smartphone study collecting daily pain reports and nearby weather for nearly 5000 participants in the United Kingdom. We found that time spent outside modifies the relationship between temperature/wind speed and pain, showing the importance of accounting for other factors when investigating the association between weather and chronic pain, which could guide future research into pain mitigation and management. [ABSTRACT FROM AUTHOR]

This study investigates the spatiotemporal variations of the summer frequency of daytime–nighttime compound extreme high-temperature events (FCEHEs) in the mid–high latitudes of Asia (MHA) from 1979 to 2014. Results show that FCEHE has shown an upward trend with fluctuations, especially in Mongolia–Baikal. The descending anomaly caused by the anomalous high pressure over Mongolia–Baikal results in reduced cloud cover, which increases solar radiation reaching the ground, favoring the higher FCEHE. This process is consistent during the daytime and nighttime periods, with relatively limited nighttime solar radiation, potentially compensated by the increased downward longwave radiation to sustain the extreme high temperatures. This benefit process is closely connected with two main factors: the increased sea ice in the Barents Sea during spring and the anomalously warm sea surface temperature (SST) in the Northwest Pacific during summer. The increased sea ice can affect the Eurasia (EU) teleconnection, while the warm SST affects the Pacific-Japan/East Asia–Pacific pattern (PJ/EAP). Subsequently, these factors further modulate the circulation anomalies and then FCEHE. Significance Statement: This study provides valuable insights into the spatiotemporal variations and the possible underlying mechanisms for change in the frequency of daytime–nighttime compound extreme high-temperature events (FCEHEs) in the mid–high latitudes of Asia. The spring sea ice anomalies over the Barents Sea and summer sea surface temperature anomalies in the Northwest Pacific affect the local anticyclonic circulation in Mongolia–Baikal through Eurasia (EU) and Pacific-Japan/East Asia–Pacific (PJ/EAP) patterns, respectively. The resulting descending anomaly and reduced cloud cover contribute to interannual variations of FCEHE, which is highly similar during the daytime and nighttime periods. During the nighttime, when the solar radiation is relatively limited, the increased downward longwave radiation may compensate to sustain extreme high temperatures. [ABSTRACT FROM AUTHOR]

The Madden–Julian oscillation (MJO) propagates eastward as a disturbance of mostly zonal wind and precipitation along the equator. The initial diagnosis of the MJO spectral peak at 40–50-day periods suggests a reduction in amplitude associated with slower MJO events that occur at lower frequencies. If events on the low-frequency side of the spectral peak continued to grow in amplitude with reduced phase speed, the spectrum would just be red. Wavelet regression analysis of slow and fast eastward-propagating MJO signals during northern winter assesses how associated moisture and wind patterns could explain why slow MJO events achieve lower amplitude in tracers of moist convection. Results suggest that slow MJO events favor a ridge anomaly over Europe, which drives cool dry air equatorward over Africa and Arabia as the active convection develops over the Indian Ocean. We hypothesize that dry air tracing back to this source, together with a longer duration of the events, leads to associated convection diminishing along the equator and instead concentrating in the Rossby gyres off the equator. Significance Statement: The Madden–Julian oscillation (MJO) dominates the subseasonal variability of the tropical atmosphere. This work suggests that it favors maximum convective activity in the 40–50-day period range because lower-frequency MJO signals tend to import more cool dry air from the extratropics and along the equator, thereby weakening the slower events. [ABSTRACT FROM AUTHOR]

Accurately modeling the interactions between inland water bodies and the atmosphere in meteorological and climate models is crucial, given the marked differences with surrounding landmasses. Modeling surface heat fluxes remains a challenge because direct observations available for validation are rare, especially at high latitudes. This study presents a detailed evaluation of the Canadian Small Lake Model (CSLM), a one-dimensional mixed-layer dynamic lake model, in reproducing the surface energy budget and the thermal stratification of a subarctic reservoir in eastern Canada. The analysis is supported by multiyear direct observations of turbulent heat fluxes collected on and around the 85-km2 Romaine-2 hydropower reservoir (50.7°N, 63.2°W) by two flux towers: one operating year-round on the shore and one on a raft during ice-free conditions. The CSLM, which simulates the thermal regime of the water body including ice formation and snow physics, is run in offline mode and forced by local weather observations from 25 June 2018 to 8 June 2021. Comparisons between observations and simulations confirm that CSLM can reasonably reproduce the turbulent heat fluxes and the temperature behavior of the reservoir, despite the one-dimensional nature of the model that cannot account for energy inputs and outputs associated with reservoir operations. The best performance is achieved during the first few months after the ice break-up (mean error = −0.3 and −2.7 W m−2 for latent and sensible heat fluxes, respectively). The model overreacts to strong wind events, leading to subsequent poor estimates of water temperature and eventually to an early freeze-up. The model overestimated the measured annual evaporation corrected for the lack of energy balance closure by 5% and 16% in 2019 and 2020. Significance Statement: Freshwater bodies impact the regional climate through energy and water exchanges with the atmosphere. It is challenging to model surface energy fluxes over a northern lake due to the succession of stratification and mixing periods over a year. This study focuses on the interactions between the atmosphere of an irregular shaped northern hydropower reservoir. Direct measurements of turbulent fluxes using an eddy covariance system allowed the model assessment. Turbulent fluxes were successfully predicted during the open water period. Comparison between observed and modeled time series showed a good agreement; however, the model overreacted to high wind episodes. Biases mostly occur during freeze-up and breakup, stressing the importance of a good representation of the ice cover processes. [ABSTRACT FROM AUTHOR]

Extreme weather events (EWEs) linked to climate change are expected to increase in frequency in the coming years, putting the entire world in danger. Parents exert a significant influence on the lives of their children and the overall function of the family unit. However, natural disasters have a significant impact on daily life and pose an immediate danger, resulting in loss of life, injuries, and property damage. In addition, disasters can also have an impact on the responsibilities that parents play in their house. This study examines the evolving dynamics of parental roles in the context of EWEs, examining the shifting expectations and actual realities of fatherhood and motherhood. The study examines the various effects of EWEs on family structures, gender roles, and parental obligations by conducting a comprehensive review of 30 relevant articles. Our findings indicate that in severe weather conditions, men tend to adopt the position of "father" and are perceived as heroic figures, rescuers, and guardians/protectors who prioritize the well-being of their children and families, as well as take on financial obligations. On the other hand, women are often viewed as caregivers/rescuers/victims during such conditions. Moreover, in many countries, women are expected to care for other family members, including younger children and the elderly, which may limit their mobility during severe weather. Extreme weather conditions affect men and women differently, and there may also be significant differences in gender-related expectations and dimensions within a country. It is therefore essential to thoroughly study how these roles change in response to extreme weather events. We recommend conducting additional rigorous studies, both quantitative and qualitative, to comprehensively examine this relationship. This study will aid in designing initiatives aimed at fostering parenting attributes, particularly in regions susceptible to disasters. [ABSTRACT FROM AUTHOR]

Heliotropes are passive solar hot-air balloons that are capable of achieving nearly level flight within the lower stratosphere for several hours. These inexpensive flight platforms enable stratospheric sensing with high cadence enabled by the low cost to manufacture, but their performance has not yet been assessed systematically. During July–September of 2021, 29 heliotropes were successfully launched from Oklahoma and achieved float altitude as part of the Balloon-based Acoustic Seismology Study (BASS). All of the heliotrope envelopes were nearly identical with only minor variations to the flight line throughout the campaign. Flight data collected during this campaign comprise a large sample to characterize the typical heliotrope flight behavior during launch, ascent, float, and descent. Each flight stage is characterized, dependence on various parameters is quantified, and a discussion of nominal and anomalous flights is provided. [ABSTRACT FROM AUTHOR]

The vertical velocity distribution in the atmosphere is asymmetric with stronger upward than downward motion. This asymmetry is important for the distribution of precipitation and its extremes and for an effective static stability that has been used to represent the effects of latent heating on extratropical eddies. Idealized GCM simulations show that the asymmetry increases as the climate warms, but current moist dynamical theories based around small-amplitude modes greatly overestimate the increase in asymmetry with warming found in the simulations. Here, we first analyze the changes in asymmetry with warming using numerical inversions of a moist quasigeostrophic omega equation applied to output from the idealized GCM. The inversions show that increases in the asymmetry with warming in the GCM simulations are primarily related to decreases in moist static stability on the left-hand side of the moist omega equation, whereas the dynamical forcing on the right-hand side of the omega equation is unskewed and contributes little to the asymmetry of the vertical velocity distribution. By contrast, increases in asymmetry with warming for small-amplitude modes are related to changes in both moist static stability and dynamical forcing leading to enhanced asymmetry in warm climates. We distill these insights into a toy model of the moist omega equation that is solved for a given moist static stability and wavenumber of the dynamical forcing. In comparison to modal theory, the toy model better reproduces the slow increase of the asymmetry with climate warming in the idealized GCM simulations and over the seasonal cycle from winter to summer in reanalysis. Significance Statement: Upward velocities are stronger than downward velocities in the atmosphere, and this asymmetry is important for the distribution of precipitation because precipitation is linked to upward motion. An important and open question is what sets this asymmetry and how much it increases as the climate warms. Past work has shown that current theories greatly overestimate the increase in asymmetry with warming in idealized simulations. In this work, we develop a more complete theory and show that it is able to better reproduce the slow increase of the asymmetry with warming that is found over the seasonal cycle from winter to summer and in idealized simulations of warming climates. [ABSTRACT FROM AUTHOR]

The long-range transport of bioaerosols by dust events significantly impacts ecological and meteorological networks of the atmosphere, biosphere, and anthroposphere. Bioaerosols not only cause significant public health risks, but also act as efficient ice nuclei for inducing cloud formation and precipitation in the hydrological cycle. To establish risk management for bioaerosol impacts on the Earth system, a large-scale investigation of bioaerosols must be performed under different environmental conditions. For this purpose, a Dust–Bioaerosol (DuBi) field campaign was conducted to investigate the distribution of bioaerosols by collecting ∼950 samples at 39 sites across East Asia from 2016 to 2021. Concentrations and community structures of bioaerosols were further analyzed using fluorescence microscopic observations and high-throughput DNA sequencing, and these factors were compared to environmental factors, such as PM10 and aridity. The results indicated that microbial concentrations at dryland sites were statistically higher than those at humid sites, while the microbe-to-total-particle ratio was statistically lower in drylands than in humid regions. Microbial cells per microgram of PM10 decreased when PM10 increased. The proportion of airborne particles at each site did not vary substantially with season. The richness and diversity of airborne bacteria were significantly higher in drylands than in semiarid regions, while the community structures were stable among all sampling sites. The DuBi field campaign improves our understanding of bioaerosol characteristic variations along the dust transport pathway in East Asia and the changes of bioaerosols under the trend of climate warming, supporting the efforts to reduce public health risks. SIGNIFICANCE STATEMENT: We first conducted large-scale Dust–Bioaerosol (DuBi) field observations in East Asia from 2016 to 2021. We used unified sampling and analysis methods to collect 950 samples at 39 sites and analyzed bioaerosols' concentration and community structure. This study aims to find the relationship between bioaerosols with atmospheric particles and aridity, which fills gaps in the field. These results improve our understanding of bioaerosols' impacts on ecological and meteorological networks of the atmosphere, biosphere, and anthroposphere. The comprehensive observations will promote prediction of bioaerosol change under the trend of climate warming, supporting the efforts to reduce global climate, ecological security, and public health risks in the future. [ABSTRACT FROM AUTHOR]

Current coupled climate models contain large biases in simulating tropical cyclogenesis, reducing the confidence in tropical cyclone (TC) projection. In this study, we investigated the influence of sea surface temperature (SST) biases on TC genesis in the Coupled Model Intercomparison Project phase 6 simulations from 1979 to 2014. Positive TC genesis biases were found over the tropical central North Pacific (CNP) in most of climate models, including the high-resolution models. Compared to coupled models, TC genesis density (TCGD) simulations over CNP in uncoupled models forced by observational SST improved obviously. A warm SST bias over the tropical CNP in the coupled models is the main cause of TC genesis biases. The SST bias–induced diabatic heating leads to an anomalous Gill-type atmospheric circulation response, which contributes to a series of favorable environmental conditions for TC formation over the CNP. Numerical experiments were also performed with HiRAM to demonstrate the influence of SST biases on the TCGD simulation, further confirming our conclusion. The current results highlight the importance of improving TC simulation in state-of-the-art climate models by reducing SST simulation bias. [ABSTRACT FROM AUTHOR]

Monsoon systems transport water and energy across the globe, making them a central component of the global circulation system. Changes in different forcing parameters have the potential to fundamentally change the monsoon characteristics as indicated in various paleoclimatic records. Here, we use the Atmosphere Model developed at the Geophysical Fluid Dynamics Laboratory (GFDL-AM2) and couple it with a slab ocean in order to analyze the monsoon's sensitivity to changes in different parameters on a planet with idealized topography (varying land position, slab depth, atmospheric CO2 concentration, solar radiation, sulfate aerosol concentration, and surface albedo). This Monsoon Planet concept of an aquaplanet with a broad zonal land stripe allows us to reduce the influence of topography and to access the relevant meridional monsoon dynamics. In simulations with monsoon dynamics, a bimodal rainfall distribution develops during the monsoon months with one maximum over the tropical ocean and the other one over land. The intensity and extent of the monsoon depend on the relative height of a local maximum in the surface pressure field that is acting as a barrier and is determining the coastward moisture transport. Changes in the barrier height occur during the course of one year but can also be induced when varying different parameters in the sensitivity analysis (e.g., the increase of atmospheric CO2 reduces the barrier height, resulting in an increase of rainfall, while aerosols have the opposing effect). This bimodal rainfall structure separated by a pressure barrier is also present in reanalysis data of the West African monsoon. Significance Statement: Monsoon rainfall directly impacts the livelihood of millions of individuals in the tropics. Because monsoons transport energy and water around the globe, their influence reaches far beyond the tropics, and changes in their dynamics affect the climate both locally and globally. The individual monsoon systems are subject to various forcing factors that determine the monsoon characteristics in partly opposing ways. Here, we implement a model setup of the Monsoon Planet to study the monsoon's sensitivity to various forcings in a simplified design, allowing us to gain new insights into monsoon dynamics. We find that a local maximum in the pressure field is acting as a barrier for moisture transport and thus determines the monsoon characteristics over land. [ABSTRACT FROM AUTHOR]

The symmetries of the governing equations of atmospheric flows constrain the solutions. The present study applies those symmetries identified from the governing equations to the atmospheric boundary layers under relatively weak stratifications (stable and unstable). More specifically, the invariant solutions are analyzed, which conserve their forms under possible symmetry transformations of a governing equation system. The key question is whether those invariant solutions can rederive the known vertical profiles of both vertical fluxes and the means for the horizontal wind and the potential temperature. The mean profiles for the wind and the potential temperature in the surface layer predicted from the Monin–Obukhov theory can be recovered as invariant solutions. However, the consistent vertical fluxes both for the momentum and heat no longer remain constant with height, as assumed in the Monin–Obukhov theory, but linearly and parabolically change with height over the dynamic sublayer and the above, respectively, in stable conditions. The present study suggests that a deviation from the constancy, though observationally known to be weak, is a crucial part of the surface-layer dynamics to maintain its symmetry consistency. Significance Statement: The atmospheric flows are governed by a differential equation system, which is often difficult to solve in any satisfactory manner, either analytically or numerically. However, without solving them explicitly, many insights can be obtained by examining the "symmetries" of the governing equations. The study suggests that basic vertical profiles of the mean state of the atmospheric boundary layer is more strongly constrained by the symmetry consistency than suggested by standard similarity theories. [ABSTRACT FROM AUTHOR]

Wet-bulb globe temperature (WBGT) is used to assess environmental heat stress and accounts for the influences of air temperature, humidity, wind speed, and radiation on heat stress. Measurements of WBGT are highly sensitive to slight changes in environmental conditions and can vary several degrees Celsius across small distances (tens to hundreds of meters). Relative to observations with an International Organization for Standardization (ISO)-compliant WBGT meter, this work assesses the accuracy of WBGT measurements made with a popular handheld meter (the Kestrel 5400 Heat Stress Tracker) and WBGT estimates. Measurements were made during the summers of 2019–21 in a variety of suburban and urban environments in North Carolina, including three high school campuses. WBGT can be estimated from standard weather station variables, and many of these stations report cloud cover in lieu of solar radiation. Therefore, this work also evaluates the accuracy of clear-sky radiation estimates and adjustments to those estimates based on cloud cover. WBGT estimated with the method from Liljegren et al. from a weather station were on average 0.2°C warmer than Observed WBGT, while the Kestrel 5400 WBGT was 0.7°C warmer. Large variations in WBGT were observed across surfaces and shade conditions, with differences of 0.9°C (0.3°–1.4°C) between a tennis court and a neighboring grass field. The method for estimating clear-sky radiation in Ryan and Stolzenbach was most accurate and the clear-sky radiation modified by percentage cloud cover was found to be within 75 W m−2of observations on average. Significance Statement: Wet-bulb globe temperature (WBGT) is a heat stress index that accounts for the effects of air temperature, humidity, wind, and radiation on humans. However, WBGT is not routinely measured at weather stations. This work demonstrated the accuracy of estimating WBGT with methods from Liljegren et al. (2008), finding it to be more accurate than measurements from a popular handheld meter, the Kestrel 5400 Heat Stress Tracker. Variations in WBGT that result in different danger levels were found between measurements over a tennis court and a neighboring grass field, and between sun and shade conditions. Understanding the magnitude of these differences and the biases with WBGT estimates and measurements can inform the planning of outdoor activity to robustly safeguard health. [ABSTRACT FROM AUTHOR]

In simulations of Arctic mixed-phase clouds, cloud persistence and the liquid water path (LWP) are sensitive to ice particle number concentrations. Here, we explore sensitivities of cloud microphysical properties to the dominant ice particle shape (dendrites, plates, columns, or spheres) using the SCALE-AMPS large-eddy simulation model. AMPS is a bin microphysics scheme that predicts particle shapes based on the inherent growth ratio (IGR) of spheroids, which determines vapor depositional growth rates along the a and c axes, and the rimed and aggregate mass fractions. We examine the impacts of various IGR values on simulations of clouds observed during the M-PACE and SHEBA experiments. Under M-PACE (SHEBA) conditions, LWP varies between 49 (1.1) and 230 (6.7) g m−2, and the ice water path (IWP) varies between 3 (0.03) and 40 (0.12) g m−2, depending on the ice shape. The lowest LWP and the highest IWP are obtained when columnar particles dominate because their low terminal velocities and large capacitance and collisional area result in large vapor deposition and riming rates, whereas the highest LWP and lowest IWP are obtained when spherical particles dominate because their vapor deposition and riming rates are low. Because ice particle shape significantly influences simulated Arctic mixed-phase clouds, reliable simulations require accurately estimated IGR values under various atmospheric conditions. Finally, comparisons between the simulation results and observations show that the size distribution larger than 2000 μm is better reproduced when the increase in rimed mass that causes ice particles to become spherical is suppressed. Significance Statement: Atmospheric models have difficulties in reproducing Arctic mixed-phase clouds because of uncertainties in the parameterization of microphysical processes. This is the first study to use a large-eddy simulation model implemented with a habit-predicting bin microphysics scheme to demonstrate the important role of ice particle shape on the microphysical properties of both heavy-riming and no-riming mixed-phase clouds. We found the vapor deposition and riming rates to be greatly influenced by ice particle shape. By comparing the ice particle size distribution, mass–diameter relationship, and area ratio between simulation results and observations, we show that a hexagonal ice shape model and a riming model that simply converts ice crystals to graupel may not accurately reproduce actual heavy-riming clouds. [ABSTRACT FROM AUTHOR]

Superrefraction at the top of the atmospheric boundary layer introduces problems for assimilation of radio occultation data in weather models. A method of detection of superrefraction by spectral analysis of deep radio occultation signals introduced earlier has been tested using 2 years of COSMIC-2/FORMOSAT-7 radio occultation data. Our analysis shows a significant dependence of the probability of detection of superrefraction on the signal-to-noise ratio, which results in a certain sampling nonuniformity. Despite this nonuniformity, the results are consistent with the known global distribution of superrefraction (mainly over the subtropical oceans) and show some additional features and seasonal variations. Comparisons to the European Centre for Medium-Range Weather Forecasts analyses and limited set of radiosondes show reasonable agreement. Being an independent measurement, detection of superrefraction from deep radio occultation signals is complementary to its prediction by atmospheric models and thus should be useful for assimilation of radio occultation data in the atmospheric boundary layer. [ABSTRACT FROM AUTHOR]

As the global research enterprise grapples with the challenge of a low-carbon future, a key challenge is the future of international conferences. An emerging initiative that combines elements of the traditional in-person conference and a virtual conference is a multi-hub approach. Here we report on a real-world trial of a multi-hub approach, the World Climate Research Programme/Stratosphere-Troposphere Processes and their Role in Climate (WCRP/SPARC) General Assembly held in Qingdao-Reading-Boulder during the last week of October 2022 with more than 400 participants. While there are other examples of conferences run in dual-hub or hybrid online and in-person formats, we are not aware of other large atmospheric science conferences held in this format. Based on travel surveys of participants, we estimate that the multi-hub approach reduced the carbon footprint from travel by between a factor of 2.3 and 4.1 times the footprint when hosting the conference in a single location. This resulted in a saving of at least 288 tonnes of carbon dioxide equivalent (tCO2eq) and perhaps as much as 683 tCO2eq, compared to having the conference in one location only. Feedback from participants, collected immediately after the conference, showed that the majority would again attend another conference in a similar format. There are many ways that the format of the SPARC General Assembly could have been improved, but this proof of concept provides an inspiration to other groups to give the multi-hub format a try. [ABSTRACT FROM AUTHOR]

The Advanced Study Program (ASP) at the National Center for Atmospheric Research has supported the career development of postdoctoral fellows for over 60 years. This study of ASP alumni helps better understand their career paths and provides a window into the geoscience community. It examines career aspirations and job satisfaction, as well as experiences with mentoring and attitudes about diversity and inclusion in the workplace. While about half of ASP alumni today work in academia, job changes and pursuit of careers outside of academia are increasing. Former ASP participants are actively engaged in mentoring and are supportive of efforts in diversity, equity, and inclusion (DEI). Alumni who identify as women reported feeling less supported by their employers in their career growth and in their service activities such as mentoring than alumni who identify as men. The study also found that women engage in a broader range of DEI activities and mentor more often out of altruistic reasons rather than as an expectation of their position. In addition to mastering research and teaching skills, future postdocs will need training in leadership, grant writing, DEI, and project management to succeed in today's geoscience workforce. [ABSTRACT FROM AUTHOR]

Densely observed remote sensing data such as radars and satellites generally contain significant spatial error correlations. In data assimilation, the observation error covariance matrix is usually assumed to be diagonal, and the dense data are thinned or spatially averaged to compensate for neglecting the spatial observation error correlation. However, in theory, including the spatial observation error correlation in data assimilation can make better use of the dense data. This study performs perfect model observing system simulation experiments (OSSEs) using the nonhydrostatic icosahedral atmospheric model (NICAM) and the local ensemble transform Kalman filter (LETKF) to assess the impact of assimilating horizontally dense and error-correlated observations. The condition number of the observation error covariance matrix, defined as the ratio of the largest to smallest eigenvalues, is important for the numerical stability of the LETKF computation. A large condition number makes it difficult to compute the ensemble transform matrix correctly. Reducing the condition number by reconditioning is found effective for stable computation. The results show that including the horizontal observation error correlation with reconditioning makes the analysis more accurate but requires 6 times more computations than the case with the diagonal observation error covariance matrix. Significance Statement: It is important to effectively utilize observations in data assimilation for more accurate weather prediction. Spatially dense observations are known to have an error correlation that is ignored in the data assimilation. This study explores assimilating dense observations by explicitly including observation error correlations with an idealized experiment. The results shows that the analysis is improved by including the observation error correlations. Also, the condition number of the observation error covariance matrix is essential for stable computations. [ABSTRACT FROM AUTHOR]

This study investigates the performance of the latter NCEP Unified Forecast System (UFS) Coupled Model prototype simulations (P5–P8) during boreal summer 2011–17 in regard to coupled land–atmosphere processes and their effect on model bias. Major land physics updates were implemented during the course of model development. Namely, the Noah land surface model was replaced with Noah-MP and the global vegetation dataset was updated starting with P7. These changes occurred along with many other UFS improvements. This study investigates UFS's ability to simulate observed surface conditions in 35-day predictions based on the fidelity of model land surface processes. Several land surface states and fluxes are evaluated against flux tower observations across the globe, and segmented coupling processes are also diagnosed using process-based multivariate metrics. Near-surface meteorological variables generally improve, especially surface air temperature, and the land–atmosphere coupling metrics better represent the observed covariance between surface soil moisture and surface fluxes of moisture and radiation. Moreover, this study finds that temperature biases over the contiguous United States are connected to the model's ability to simulate the different balances of coupled processes between water-limited and energy-limited regions. Sensitivity to land initial conditions is also implicated as a source of forecast error. Above all, this study presents a blueprint for the validation of coupled land–atmosphere behavior in forecast models, which is a crucial model development task to assure forecast fidelity from day one through subseasonal time scales. [ABSTRACT FROM AUTHOR]

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution. [ABSTRACT FROM AUTHOR]

The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments ("implicit" schemes) or prognostic melt-pond parameterizations ("explicit" schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere. Significance Statement: This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change. [ABSTRACT FROM AUTHOR]

A unique storm identification and tracking method is analyzed in varying storm environments within the United States spanning 273 hours in 2018. The methodology uses a quantity calculated through fusion of radar-based vertically integrated liquid (VIL) and satellite-based GLM flash rate density (FRD) called VILFRD to identify storms in space and time. This research analyzes GLM data use within VILFRD for the first time (method original: O), assesses four modifications to VILFRD implementation to find a more stable storm size with time (method new: N), larger storms (method original dilated: OD), or both (method new dilated: ND), and compares VILFRD methods with storm tracking using the 35-dBZ isosurface at −10°C (method non-VILFRD: NV). A case study analysis from 2019 is included to assess methods on a smaller scale and introduce a "lightning only" (LO) version of VILFRD. Large study results highlight that VILFRD-based storm identification produces smaller storms with more lightning than the NV method, and the NV method produces larger storms with a more stable size over time. Methods N and ND create smaller storm size fluctuations, but size changes more often. Dilation (OD, ND) creates larger storms and almost double the number of storms identified relative to nondilated methods (O, N, NV). The case study results closely resemble the large sample results and show that the LO method identifies storms with more lightning and shorter durations. Overall, these findings can aid in choice of storm tracking method based on desired user application and promote further testing of a lightning-only version of VILFRD. [ABSTRACT FROM AUTHOR]