Atmospheric Wind Research Articles

Persistence or Transition of the North Atlantic Oscillation Across Boreal Winter: Role of the North Atlantic Air‐Sea Coupling

AbstractClimate anomalies over North America and Europe are closely related to the North Atlantic Oscillation (NAO). The persistence, decay or switch of the NAO phase across the boreal winter determines whether the NAO‐related climate anomalies are sustained, weakened or reversed during the boreal winter. This study compares the spatiotemporal evolution of atmospheric wind and sea surface temperature (SST) anomalies over the North Atlantic corresponding to persistence and switch of the NAO phase across the boreal winter. It is revealed that the persistence of the NAO from early to late winter is associated with a strong coupling between the NAO and the North Atlantic tripole SST anomalies. The formation of the tripole SST anomalies is attributed to the wind‐related surface latent heat flux changes. The tripole SST anomalies feedback on the NAO through eddy‐mean flow interaction. In contrast, during the winters with the switch of the NAO phase, the North Atlantic SST anomalies follow the wind changes, but do not have obvious feedback on the NAO. Our analysis identifies a prominent change of the winter NAO evolution in the early 1990s. The NAO switches its phase from early to late winter during 1970s through the early 1990s, but tends to maintain its phase during the boreal winter after the early 1990s. This interdecadal change appears to be related to the mean SST change. The SST increase in both the tropical and mid‐latitude North Atlantic Ocean in the early 1990s enhances the feedback of the NAO‐induced tripole SST anomalies on the NAO.

Wave disturbances of the atmosphere in a spatially inhomogeneous flow

Analysis of measurements by the Dynamics Explorer 2 satellite indicates a close connection between atmospheric wave disturbances and wind circulation in the polar thermosphere. According to satellite observations, large-amplitude acoustic-gravity waves are systematically observed in the regions of formation of powerful wind systems. At the same time, the azimuths of AGW propagation are spatially consistent with the directions of wind circulation. Waves propagate mainly against the wind, and their amplitude is approximately proportional to the wind speed. In order to explain the experimental data, the paper theoretically investigated the changes in the amplitudes of AGW in a horizontally inhomogeneous wind flow. The dispersion equation of the AGW in the reference frame of the medium, which moves with a non-uniform speed, was obtained. When obtaining it, inertial forces were taken into account, as well as the change in the background density of the atmosphere in an inhomogeneous flow. It is shown that under the slow change in wind speed, the real part of this equation coincides with the dispersion equation of AGW for a stationary medium. An expression for the change in the amplitude of waves in a moving medium was obtained, according to which, in an oncoming inhomogeneous wind, the amplitude of the wave increases approximately according to a linear law, which is consistent with the data of satellite observations.

Modeling and correction of fringe patterns in Doppler asymmetric spatial heterodyne interferometry.

Doppler asymmetric spatial heterodyne (DASH) interferometry is a novel concept for observing atmospheric winds. This paper discusses a numerical model for the simulation of fringe patterns and a methodology to correct fringe images for extracting Doppler information from ground-based DASH measurements. Based on the propagation of optical waves, the fringe pattern was modeled considering different angular deviations and optical aberrations. A dislocation between two gratings can introduce an additional spatial modulation associated with the diffraction order, which was seen in laboratory measurements. A phase correction is proposed to remove phase differences between different row interferograms, which is the premise for calculating the average interferogram to improve the signal-to-noise ratio. Laboratory tests, simulation results, and Doppler velocity measurements indicate that a matrix determined in the laboratory can be applied to correct interferograms obtained from ground-based DASH measurements.

Interannual changes of the summer circulation and hydrology in the East China Sea: A modeling study from 1981 to 2015

This study investigated long-term interannual changes in summer circulation and hydrology in the East China Sea (ECS) by performing 35-year high-resolution ocean model simulation from 1981 to 2015. The sea surface temperature (SST) warming trend was considerably weaker in summer than in winter. To the east of the Yangtze Estuary, the interannual variation of SST in summer was mainly dominated by horizontal advection associated with variations in the Taiwan warm current and heat flux in the offshore region north of the Yangtze Estuary. Baroclinic circulation during summer played a crucial role in subsurface mixing. Near the surface, the significant atmospheric wind mode (EOF1) and Kuroshio mode (EOF2) dominate interannual variations in ocean circulation. In the subsurface, local wind around the Tsushima Strait dominated the interannual ocean variation. Anomalous northeasterly winds induced a southwestward pressure gradient due to topographical confinement. These anomalies propagated to the south along the continental shelf through topographic Rossby waves. This study identified two types of anomalous features based on combinations of surface and subsurface EOFs. The combination represents an in-phase contribution between wind and Kuroshio forcings and between the surface and subsurface circulation that enhances the hydrological variability in the ECS. The implication on the relevant biogeochemical and ecological studies in the East China Sea is also very crucial at the interannual time scale.

Development of the Turbulent Diffusion Model of Fine Suspended Substances in the Lower Atmosphere Layer

A promising direction for solving the problem of air pollution by fine substances is the use of numerical modeling in the development of mathematical models of the transport of pollutants in the atmosphere. An urgent problem in applying mathematical models with numerical algorithms and software is constructing a qualitative model that would meet both the physical parameters and fulfill all the optimal conditions of numerical analysis. The main objective of this study was to develop an algorithm of a mathematical model based on the equation of distribution of impurities in a turbulent medium. That allows considering the simultaneous influence of wind speed, turbulence of atmospheric air, pollution parameters, direction, and wind force on the size of scattering zones. The unique feature of the study is the use of the coordinate splitting equation of impurities distribution in a turbulent environment with subsequent normalization and parameterization of conditions. Finding integrands functions in the calculation algorithm allows obtaining a stable computational algorithm of the proposed propagation model of fine suspended particles. The solution of the function implemented in the Mathcad Prime 7 software. Distributions of concentrations and their levels for various values of turbulence of atmospheric air and dangerous wind speed are received. The most significant number of fine particles is at a distance of up to 4 km from the emission source. Still, there is also the transfer of contaminants at more than 5 km (up to 57 % of the initial emission concentration). The model has convenient software and algorithmic software, the time of calculation of graphic visualizations up to 20 minutes on medium-power computers. The obtained mathematical model can use in systems of forecasting man-caused load on the environment for the prompt solution of environmental problems.

A field study on the aerodynamics of freight trains with different stacking configurations

A full-scale 48-foot shipping container was instrumented with surface pressure taps and loaded onto a number of single- and double-stacked container freight trains. Surface pressure data enabled the container pressure drag coefficient to be evaluated for a range of different train loading configurations, container positions along the train, and atmospheric wind conditions. Field-based measurements show that for low and high crosswind conditions surface pressure distributions measured on the front face of the instrumented container are in good agreement with those reported in past studies. However, the magnitude of the pressure drag coefficient was found to be typically 50% lower for all loading cases analysed compared with previous seemingly analogous wind-tunnel and numerical investigations. For high crosswind conditions, the drag coefficient was found to increase and correlated well with the level of asymmetry observed in the measured pressure distributions. This was true for all cases regardless of the position along the length of the train. In the absence of direct information of the incident free-stream wind conditions, the level of asymmetry in the pressure distributions was found to provide a viable indirect method for assessing the impact that crosswinds have on the aerodynamic drag of freight trains.

Impacts of Gravity Waves in the Martian Thermosphere: The Mars Global Ionosphere‐Thermosphere Model Coupled With a Whole Atmosphere Gravity Wave Scheme

AbstractGravity waves are a key mechanism that facilitates coupling between the lower and upper atmosphere of Mars. In order to better understand the mean, large‐scale impacts of gravity waves on the thermosphere, a modern whole atmosphere, nonlinear, non‐orographic gravity wave parameterization scheme has been incorporated into a three‐dimensional ground‐to‐exosphere Mars general circulation model, the Mars Global Ionosphere‐Thermosphere Model (M‐GITM). M‐GITM simulations utilizing the gravity wave parameterization indicate that significant gravity wave momentum is deposited in the thermosphere, especially within the altitude range of 90–170 km. This impacts the winds in the thermosphere; in particular, M‐GITM simulations show a decrease in speed of the wind maximum in the summer hemisphere by over a factor of two. Gravity wave effects also impact the temperatures above 120 km in the model, producing a cooler simulated thermosphere at most latitudes. M‐GITM results were also compared to upper atmospheric temperature and wind data sets from the MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft. Some aspects of wind data‐model comparisons improved once the gravity wave scheme was added to M‐GITM; furthermore, a cooler temperature profile produced by these new M‐GITM simulations for the MAVEN Deep Dip 2 observational campaign resulted in a closer data‐model comparison, particularly above 180 km. Overall, these modeling results show that gravity waves play an important role for the energy and momentum budget of the Martian thermosphere.

Accurate and efficient forecasted wind energy using selected temporal metrological variables and wind direction

The aim of this work is to find the most efficient and suitable input features to be selected for forecasting monthly wind energy accurately. Machine learning is employed for a modular pipelined neural network, composed of time-delayed and feedforward networks with features of metrological variables such as atmospheric temperature, humidity, wind direction, and wind speed frequency distribution parameters. Logged data over a year’s period at a UAE site are analyzed on daily and monthly bases depending on their variation characteristics, in which standard Weibull probability distribution function is used for the feedforward neural network together with wind direction data, while daily average ambient temperature and humidity are attempted for the composite time delay networks. Different network abstractions of input features are compared, and it is found that wind direction data offer a better wind speed forecast. Wind energy is calculated based on monthly forecasting. A detailed adaptive probabilistic analysis is conducted to predict thresholds in variations of the forecast analysis. Error estimation tools are performed for adopting this method

The GAPS Programme at TNG

Aims. We present a novel method for studying the thermal emission of exoplanets as a function of orbital phase at very high spectral resolution, and use it to investigate the climate of the ultra-hot Jupiter KELT-9b. Methods. We combine three nights of HARPS-N and two nights of CARMENES optical spectra, covering orbital phases between quadratures (0.25 < φ < 0.75), when the planet shows its day-side hemisphere with different geometries. We co-add the signal of thousands of Fe I lines through cross-correlation, which we map to a likelihood function. We investigate the phase-dependence of two separate observable quantities, namely (i) the line depths of Fe I and (ii) their Doppler shifts, introducing a new method that exploits the very high spectral resolution of our observations. Results. We confirm a previous detection of Fe I emission, and demonstrate a precision of 0.5 km s−1 on the orbital properties of KELT-9b when combining all nights of observations. By studying the phase-resolved Doppler shift of Fe I lines, we detect an anomaly in the planet's orbital radial velocity well-fitted with a slightly eccentric orbital solution (e = 0.016 ± 0.003, ω = 150−11+13°, 5σ preference). However, we argue that this anomaly is caused by atmospheric circulation patterns, and can be explained if neutral iron gas is advected by day-to-night atmospheric wind flows of the order of a few km s−1. We additionally show that the Fe I emission line depths are symmetric around the substellar point within 10° (2σ), possibly indicating the lack of a large hot-spot offset at the altitude probed by neutral iron emission lines. Finally, we do not obtain a significant preference for models with a strong phase-dependence of the Fe I emission line strength. We show that these results are qualitatively compatible with predictions from general circulation models (GCMs) for ultra-hot Jupiter planets. Conclusions. Very high-resolution spectroscopy phase curves are of sufficient sensitivity to reveal a phase dependence in both the line depths and their Doppler shifts throughout the orbit. They constitute an under-exploited treasure trove of information that is highly complementary to space-based phase curves obtained with HST and JWST, and open a new window onto the still poorly understood climate and atmospheric structure of the hottest planets known to date.

Numerical Modeling of the Influence of the Atmospheric Wind Field Structure on the Macro- and Microstructure Characteristics of Convective Clouds

Numerical Modeling of the Influence of the Atmospheric Wind Field Structure on the Macro- and Microstructure Characteristics of Convective Clouds

FastICA Algorithm Applied on Black Sea Water-Level Ultrasound Measurements

The parameters influencing the sea level measured with ultrasonic devices that are analyzed in this paper are the air temperature, atmospheric pressure and wind speed. As these variations are independent to each other and to the sea level, they can be removed from the measured sea level by applying a filtering algorithm based on independent component analysis (FastICA), adapted and improved for this application. The sound speed increases with temperature, so an internal temperature sensor is required to compensate for the sound-speed variation. Though this may improve the measurement accuracy, it is not enough to achieve the best results because there is a discrepancy between the internal sensor and the actual environment temperature. For high accuracy measurements, an external temperature sensor is required. In our case, we imported temperature datasets from a weather station, along with other datasets regarding atmospheric pressure and wind speed. The use of these external datasets, along with an algorithm based on principal component analysis (PCA) for error removal and the filtering algorithm based on FastICA for environmental phenomena extraction, allows us to achieve more accurate values for the Black Sea level in Constanta (2017–2020), independent of external influences.

A novel mechanism - smart morphing façade system - to mitigate wind-induced vibration of tall buildings

Wind-induced vibration plays a significant role in the design of tall buildings, primarily due to serviceability requirements for occupant comfort and structural safety. As a result, several approaches have been developed to address this concern. This paper describes a novel control mechanism, a smart-morphing-façade (Smorphacade) system, using the concept of an aerodynamically modified building façade to mitigate wind-induced vibration of tall buildings. Compared to a fixed-façade system, since a Smorphacade can be dynamically modified in real time based on rapidly-changing wind speed and wind direction during a windstorm, it can be further developed into an active control system. The Smorphacade is comprised of a set of circular ducts embedded in a flat plate and arranged in a matrix formation that is fixed on the original façade but with a gap between the two facades. Each circular-shaped duct is comprised of two parts, a fixed base with alternate open and closed surfaces shaped like a fan-blade and a rotating part similar in shape like the fixed one but placed inside the fixed one and capable of rotation by a protruding fin. By rotating the fin, the porosity of the duct and the fin inclination angle can be simultaneously changed, enabling flow control through the duct. The performance of a Smorphacade system in different configurations was studied using the CAARC standard tall-building model under atmospheric boundary layer wind; its effectiveness in reducing building response was examined by comparing the results of a building with a Smorphacade system to those from one without it. It was found that the effectiveness of the Smorphacade system in reducing the average combined vibration among all three directions (2 transverse and 1 torsional) varied between 16.7 and 18.6%, with a maximum reduction of 32% and 59.7% in across-wind direction and torsional direction, respectively, depending on factors such as Smorphacade configuration, wind speed, and angle of attack.

The simulation of mineral dust in the United Kingdom Earth System Model UKESM1

Abstract. Mineral dust plays an important role in Earth system models and is linked to many components, including atmospheric wind speed, precipitation and radiation, surface vegetation cover and soil properties and oceanic biogeochemical systems. In this paper, the dust scheme in the first configuration of the United Kingdom Earth System Model UKESM1 is described, and simulations of dust and its radiative effects are presented and compared with results from the parallel coupled atmosphere–ocean general circulation model (GCM) HadGEM3-GC3.1. Not only changes in the driving model fields but also changes in the dust size distribution are shown to lead to considerable differences to the present-day dust simulations and to projected future changes. UKESM1 simulations produce a present-day, top-of-the-atmosphere (ToA) dust direct radiative effect (DRE – defined as the change in downward net flux directly due to the presence of dust) of 0.086 W m−2 from a dust load of 19.5 Tg. Under climate change pathways these values decrease considerably. In the 2081–2100 mean of the Shared Socioeconomic Pathway SSP5–8.45 ToA DRE reaches 0.048 W m−2 from a load of 15.1 Tg. In contrast, in HadGEM3-GC3.1 the present-day values of −0.296 W m−2 and 15.0 Tg are almost unchanged at −0.289 W m−2 and 14.5 Tg in the 2081–2100 mean. The primary mechanism causing the differences in future dust projections is shown to be the vegetation response, which dominates over the direct effects of warming in our models. Though there are considerable uncertainties associated with any such estimates, the results presented demonstrate both the importance of the size distribution for dust modelling and also the necessity of including Earth system processes such as interactive vegetation in dust simulations for climate change studies.

Marine heatwaves in shallow coastal ecosystems are coupled with the atmosphere: Insights from half a century of daily in situ temperature records

Marine heatwaves (MHWs) are extreme ocean temperature events that can have wide-ranging and pervasive effects on marine species and ecosystems. However, studies of MHW characteristics and drivers primarily focus on open-ocean environments, rather than the nearshore coastal ocean (<10 km from coast, <50 m depth). This is despite coastal waters sustaining significant commercial, recreational, and customary fisheries and aquaculture activities that are highly susceptible to the impacts of MHWs. The two longest (>50 year) daily in situ ocean temperature records in the Southern Hemisphere are used to investigate the variability, drivers, and trends of MHWs in shallow water marine ecosystems (SWMEs). Located at the northern and southern limits of New Zealand, both locations experience an average of two to three MHWs annually, with MHWs at the exposed coastline site generally being of longer duration but less intense than those observed within the semi-enclosed harbor site. Observed MHWs have timescales similar to synoptic weather systems (9–13 days) and are most intense during Austral summer with little seasonality in frequency or duration. An investigation of MHWs co-occurring in nearshore coastal and offshore waters suggests that MHWs in semi-enclosed waters (e.g., harbors, estuaries) are more closely coupled with local atmospheric conditions and less likely to have a co-occurring offshore MHW than those occurring on exposed coastlines. Composite analysis using a reanalysis product elucidates specific atmospheric drivers and suggests that atmospheric pressure systems, wind speed and latent heat fluxes are important contributing factors to the generation and decline of MHWs in SWMEs. Investigation of long-term trends in MHW properties revealed an increase in MHW duration and annual MHW days at the southern site and decrease in maximum intensity at the northern site. This is consistent with broad-scale warming trends previously documented at these coastal stations, with differences related to changes in large-scale circulation patterns around New Zealand. Our results highlight the importance of in situ data for the analysis of MHW events in the nearshore coastal ocean, and the role of local atmospheric forcing in modulating the occurrence of MHWs in SWMEs, which can cause decoupling of temperature dynamics with the surrounding shelf sea.

Physical Characterization of Long‐Lasting Hybrid Eruptions: The 2021 Tajogaite Eruption of Cumbre Vieja (La Palma, Canary Islands)

AbstractLong‐lasting, hybrid eruptions can be of complex description and classification, especially when associated with multiple eruptive styles and multiple products. The 2021 Tajogaite eruption of La Palma, Canary Islands, was associated with a magma‐gas decoupled system that resulted in the simultaneous emission of lava flows and tephra plumes from various vents. Even though the tephra blanket (∼2 × 107 m3) represents only 7%–16% of the total erupted volume, it provides fundamental insights into the overall eruptive dynamics. Tephra was mostly dispersed NE‐SW due to a complex regional and local wind patterns and was subdivided into 3 units and 11 layers that well correlate at different distances from the vent and with both tremor data and lava emission rate. While plume height varied at the temporal scale of a few hours, the average mass eruption rate associated with the tephra blanket of the different units remained relatively constant (∼3–4 × 103 kg s−1). In contrast, the emission rate of lava largely increased after the first week and remained higher than the overall emission of tephra throughout the whole eruption (average value of ∼6 × 104 kg s−1). Based on a detailed characterization of the tephra blanket in combination with atmospheric wind, tremor, and lava emission trend, we demonstrate the need of (a) multidisciplinary strategies for the description of hybrid eruptions that account for both the duration of individual phases and the quantification of the mass of multiple products, and of (b) dedicated ash dispersal forecasting strategies that account for the frequent variations of eruptive and atmospheric conditions.

Atmospheric Contributions to Global Ocean Tides for Satellite Gravimetry

AbstractTo mitigate temporal aliasing effects in monthly mean global gravity fields from the GRACE and GRACE‐FO satellite tandem missions, both tidal and non‐tidal background models describing high‐frequency mass variability in atmosphere and oceans are needed. To quantify tides in the atmosphere, we exploit the higher spatial (31 km) and temporal (1 hr) resolution provided by the latest atmospheric ECMWF reanalysis, ERA5. The oceanic response to atmospheric tides is subsequently modeled with the general ocean circulation model MPIOM (in a recently revised TP10L40 configuration that includes the feedback of self‐attraction and loading to the momentum equations and has an improved bathymetry around Antarctica) as well as the shallow water model TiME (employing a much higher spatial resolution and more elaborate tidal dissipation than MPIOM). Both ocean models consider jointly the effects of atmospheric pressure variations and surface wind stress. We present the characteristics of 16 waves beating at frequencies in the 1–6 cpd band and find that TiME typically outperforms the corresponding results from MPIOM and also FES2014b as measured from comparisons with tide gauge data. Moreover, we note improvements in GRACE‐FO laser ranging interferometer range‐acceleration pre‐fit residuals when employing the ocean tide solutions from TiME, in particular, for the S1 spectral line with most notable improvements around Australia, India, and the northern part of South America.

A Bivariate Nonstationary Extreme Values Analysis of Skew Surge and Significant Wave Height in the English Channel

Coastal flooding compound events can be caused by climate-driven extremes of storm surges and waves. To assess the risk associated with these events in the context of climate variability, the bivariate extremes of skew surge (S) and significant wave height (HS) are modeled in a nonstationary framework using physical atmospheric/oceanic parameters as covariates (atmospheric pressure, wind speed and sea surface temperature). This bivariate nonstationary distribution is modeled using a threshold-based approach for the margins of S and HS and a dynamic copula for their dependence structure. Among the covariates considered, atmospheric pressure and related wind speed are primary forcings for the margins of S and HS, but temperature is the main positive forcing of their dependence. This latter relation implies an increasing risk of compound events of S and HS for the studied site in the context of increasing global temperature.

Comparison of horizontal wind observed by wind profiler radars with ERA5 reanalysis data in Anhui, China

The wind profiler radar (WPR) network in Anhui Province in China completed the construction in 2019 to improve the warning capacity for meteorological disasters. To verify its proper performance, vertical profiles of horizontal winds were compared with ERA5 reanalysis data from January to December 2021. The results show that the WPRs demonstrate good capability in measuring atmospheric wind due to their high data collection rate (> 80%). Overall, the data availability of the WPRs decreases with increasing altitude, exceeding 90% below 3 km during the daytime without precipitation. In terms of seasonal variability, the annual mean effective detection height reaches a maximum value at 4–6 km in summer and a minimum value at approximately 2 km in winter. Comparison analyses show that the wind measurements by the WPRs show excellent agreement with the ERA5 zonal (correlation coefficient > 0.89 and standard deviation < 2.57 m/s) and meridional winds (correlation coefficient > 0.76 and standard deviation < 3.26 m/s) over most WPR stations in Anhui, China. Additionally, the biases of winds between WPR and ERA5 generally follow a Gaussian distribution pattern, most of which are all close to zero. In particular, the differences in horizontal wind between WPR and ERA5 increase with altitude, with a much lower bias present in the lower layer. In addition, due to the difference in atmospheric turbulence between day and night, statistical parameters of comparison during daytime behave better than those at night. These findings indicate that the WPR network in Anhui is capable of providing good quality wind data, laying a solid data foundation for the improvement and development of the boundary layer scheme in the future.

PM2.5 Pollution in Six Major Chinese Urban Agglomerations: Spatiotemporal Variations, Health Impacts, and the Relationships with Meteorological Conditions

To investigate the spatiotemporal patterns of fine particulate matter (PM2.5) under years of control measures in China, a comprehensive analysis including statistical analysis, geographical analysis, and health impact assessment was conducted on millions of hourly PM2.5 concentrations data during the period of 2017–2020 in six typical major urban agglomerations. During the period of 2017–2020, PM2.5 concentrations in the Beijing–Tianjin–Hebei urban agglomeration (BTH-UA), Central Plains urban agglomeration (CP-UA), Yangtze River Delta urban agglomeration (YRD-UA), Triangle of Central China urban agglomeration (TC-UA), Chengdu–Chongqing urban agglomeration (CY-UA), and Pearl River Delta urban agglomeration (PRD-UA) decreased at a rate of 6.69, 5.57, 5.45, 3.85, 4.66, and 4.1 µg/m3/year, respectively. PM2.5 concentration in BTH-UA decreased by 30.5% over four years, with an annual average of 44.6 µg/m3 in 2020. CP-UA showed the lowest reduction ratio (22.1%) among the six regions, making it the most polluted urban agglomeration. In southern BTH-UA, northeastern CP-UA, and northwestern TC-UA, PM2.5 concentrations with high levels formed a high–high agglomeration, indicating pollution caused by source emission in these areas was high and hard to control. Atmospheric temperature, pressure, and wind speed have important influences on PM2.5 concentrations. RH has a positive correlation with PM2.5 concentration in north China but a negative correlation in south China. We estimated that meteorological conditions can explain 16.7–63.9% of the PM2.5 changes in 129 cities, with an average of 33.4%, indicating other factors including anthropogenic emissions dominated the PM2.5 changes. Among the six urban agglomerations, PM2.5 concentrations in the CP-UA were most influenced by the meteorological change. Benefiting from the reduction in PM2.5 concentration, the total respiratory premature mortalities in six regions decreased by 73.1%, from 2017 to 2020. The CP-UA had the highest respiratory premature mortality in six urban agglomerations. We suggested that the CP-UA needs more attention and stricter pollution control measures.

Nudging Observed Winds in the Arctic to Quantify Associated Sea Ice Loss from 1979 to 2020

Abstract Over the past decades, Arctic climate has exhibited significant changes characterized by strong pan-Arctic warming and a large-scale wind shift trending toward an anticyclonic anomaly centered over Greenland and the Arctic Ocean. Recent work has suggested that this wind change is able to warm the Arctic atmosphere and melt sea ice through dynamically driven warming, moistening, and ice drift effects. However, previous examination of this linkage lacks a capability to fully consider the complex nature of the sea ice response to the wind change. In this study, we perform a more rigorous test of this idea by using a coupled high-resolution modeling framework with observed winds nudged over the Arctic that allows for a comparison of these wind-induced effects with observations and simulated effects forced by anthropogenic forcing. Our nudging simulation can well capture observed variability of atmospheric temperature, sea ice, and the radiation balance during the Arctic summer and appears to simulate around 30% of Arctic warming and sea ice melting over the whole period (1979–2020) and more than 50% over the period 2000–12, which is the fastest Arctic warming decade in the satellite era. In particular, in the summer of 2020, a similar wind pattern reemerged to induce the second-lowest sea ice extent since 1979, suggesting that large-scale wind changes in the Arctic are essential in shaping Arctic climate on interannual and interdecadal time scales and may be critical to determine Arctic climate variability in the coming decades. Significance Statement This work conducts a set of new CESM1 nudging simulations to quantify the impact of the observed evolution of large-scale high-latitude atmospheric winds on Arctic climate variability over the past four decades. Variations in climate parameters, including sea ice, radiation, and atmospheric temperatures are well replicated in the model when observed winds are imposed in the Arctic. By investigating simulated sea ice melting processes in the simulation, we illustrate and estimate how large-scale winds in the Arctic help melt sea ice in summer. The nudging method has the potential to make Arctic climate attribution more tangible and to unravel the important physical processes underlying recent abrupt climate change in the Arctic.