Atmosphere

Atmospheric turbulent circulations in the vicinity of wildland fire fronts play an important role in the transfer of momentum into and out of combustion zones, which in turn can potentially affect the behavior and spread of wildland fires. The vertical turbulent transfer of momentum is accomplished via individual sweep, ejection, outward interaction, and inward interaction events, collectively known as sweep-ejection dynamics. This study examined the sweep-ejection dynamics that occurred before, during, and after the passage of a surface fire front during a prescribed fire experiment conducted in an open-canopied forest in the New Jersey Pine Barrens. High-frequency (10 Hz), tower-based, sonic anemometer measurements of horizontal and vertical wind velocity components in the vicinity of the fire front were used to assess the relative frequencies of occurrence of the different types of momentum-flux events, their contributions to the overall momentum fluxes, and their periodicity patterns. The observational results suggest that the presence of surface fire fronts in open-canopied forests can substantially change the sweep-ejection dynamics that typically occur when fires are not present. In particular, sweep events resulting in the downward transport of high horizontal momentum air from above were found to be more prominent during fire-front-passage periods. Full article

The atmosphere over the Atlantic Ocean is highly impacted by human activities on the surrounding four major continents. Globally, human activity creates significant burdens for the sustainability of key Earth systems, pressuring the planetary boundaries of environmental sustainability. Here, we propose a science-based integrated approach addressing linked science and policy challenges in the North Atlantic. There is a unique combination of ongoing anthropogenic changes occurring in the coupled atmosphere–ocean environment of the region related to climate, air and water quality, the biosphere and cryosphere. This is matched by a unique potential for the societies that surround the North Atlantic to systematically address these challenges in a dynamic and responsive manner. Three key linked science-policy challenges to be addressed as part of this proposed integrated regional approach are: (1) understanding physical and dynamic changes, (2) sustaining human and ecosystem health and (3) reducing existing knowledge gaps on the carbon budget and the Earth’s energy balance. We propose a North Atlantic multidisciplinary scientific assessment system and observation network to address these thematic challenges. We propose to build on and link with the existing research activities and observational networks and infrastructures to specifically address the key North Atlantic challenges that encompass a range of policy areas. This will strengthen the institutional response to weather, climate, environmental and ecological threats and reduce societal risk. Full article

The Indian Summer Monsoon (ISM) plays a vital role in the livelihoods and economy of those living on the Indian subcontinent, including the small, mountainous country of Bhutan. The ISM fluctuates over varying temporal scales and its variability is related to many internal and external factors including the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In 2015, a Super El Niño occurred in the tropical Pacific alongside a positive IOD in the Indian Ocean and was followed in 2016 by a simultaneous La Niña and negative IOD. These events had worldwide repercussions. However, it is unclear how the ISM was affected during this time, both at a regional scale over the whole ISM area and at a local scale over Bhutan. First, an evaluation of data products comparing ERA5 reanalysis, TRMM and GPM satellite, and GPCC precipitation products against weather station measurements from Bhutan, indicated that ERA5 reanalysis was suitable to investigate ISM change in these two years. The reanalysis datasets showed that there was disruption to the ISM during this period, with a late onset of the monsoon in 2015, a shifted monsoon flow in July 2015 and in August 2016, and a late withdrawal in 2016. However, this resulted in neither a monsoon surplus nor a deficit across both years but instead large spatial-temporal variability. It is possible to attribute some of the regional scale changes to the ENSO and IOD events, but the expected impact of a simultaneous ENSO and IOD events are not recognizable. It is likely that 2015/16 monsoon disruption was driven by a combination of factors alongside ENSO and the IOD, including varying boundary conditions, the Pacific Decadal Oscillation, the Atlantic Multi-decadal Oscillation, and more. At a local scale, the intricate topography and orographic processes ongoing within Bhutan further amplified or dampened the already altered ISM. Full article

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders. Full article

As the main source of dust in Asia, China often suffers from dust events. The temporal and spatial characteristics of dust events change with the variations of geography, climate and human activities. Based on the criteria of selecting dust events proposed recently by the China Environmental Monitoring Station, the hourly concentration of PM₁₀ and PM_2.5 of 336 cities in China from 2015 to 2020 were used to study the temporal and spatial characteristics of dust events more accurately and objectively. The results showed that all of the dust events in China clearly decreased, but the strong dust events did not decrease. There were 334 cities that had dust events except Shenzhen and Dongguan, 299 cities were seriously polluted due to dust events, 134 cities encountered dust level III and 56 cities encountered dust level IV. The high frequencies of dust events were mainly distributed in Northern China, especially in Northwest China. The dust contribution of PM₁₀ to the cities in Northwest China was more than 10% and about 5–10% for PM_2.5. The most likely month for dust was May. The starting time of dust was bimodally distributed, and the most common starting time was 10:00–11:00 BJT, followed by 22:00–23:00 BJT. According to the PSCF (Potential Source Contribution Function) results, the dust potential source contribution of different cities mainly came from the northwest, and was mainly affected by Mongolia in addition to the local dust in China. In addition, Beijing was obviously affected by dust recirculation. This study is of great significance to the improvement of the forecast of dust weather and the warning of heavy pollution caused by dust events. Full article

The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO${}_2$ emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame. Full article

Sea breezes have been observed to move inland over 100 km. These airmasses can be markedly different from regional airmasses, creating a shallow layer with differences in humidity, wind, temperature and aerosol characteristics. To understand their influence on boundary layer and cloud development on subsequent days, we identify their frequency and characteristics. We visually identified sea breeze fronts on radar passing over the Savannah River Site (SRS) between March and October during 2015–2019. The SRS is ~150 km from the nearest coastal location; therefore, our detection suggests further inland penetration. We also identified periods when sea breeze fronts may have passed but were not visually observed on radar due to the shallow sea breeze airmass remaining below the radar beam elevation that ranges between approximately 1–8 km depending on the beam angle and radar source (Columbia, SC or Charleston, SC). Near-surface atmospheric measurements indicate that the dew point temperature increases, the air temperature decreases, the variation in wind direction decreases and the aerosol size increases after sea breeze frontal passage. A synoptic classification procedure also identified that inland moving sea breezes are more commonly observed when the synoptic conditions include weak to moderate offshore winds with an average of 35 inland sea breezes occurring each year, focused primarily in the months of April, May and June. Full article

We discuss the measurements of black carbon concentrations in the composition of atmospheric aerosol over the seas of the North Atlantic and European sector of the Arctic Ocean (21 expeditions in 2007–2020). The black carbon concentrations were measured by an aethalometer and filter method. The comparison of the two variants of the measurements of the black carbon concentrations showed that the data acceptably agreed and can be used jointly. It is noted that the spatial distribution of black carbon over the ocean is formed under the influence of outflows of air masses from the direction of continents, where the main sources of emission of absorbing aerosol are concentrated. We analyzed the statistical characteristics of black carbon concentrations in five marine regions, differing by the outflows of continental aerosol. The largest black carbon content is a salient feature of the atmosphere of the North and Baltic Seas, surrounded by land: average values of concentrations are 210 ng/m³, and modal values are 75 ng/m³. In other regions (except in the south of the Barents Sea), the average black carbon concentrations are 37–44 ng/m³ (modal concentrations are 18–26 ng/m³). We discuss the specific features of the spatial (latitude-longitude) distributions of black carbon concentrations, relying on ship-based measurements and model calculations (MERRA-2 reanalysis data). A common regularity of the experimental and model spatial distributions of black carbon is that the concentrations decrease in the northern direction and with the growing distance from the continent: from several hundred ng/m³ in the southern part of the North Sea to values below 50 ng/m³ in polar regions of the ocean. Full article

The main goal of this study is to present a recently developed classification method for weather types based on the vorticity and the location of the synoptic centers relative to the Adriatic region. The basis of the present objective classification, applied to the Adriatic region, is the subjective classification developed by Poje. Our algorithm considered daily mean sea-level pressure and 500 hPa geopotential height to define one out of 17 possible weather types. We applied the algorithm to identify which weather type was relevant in the generation of the two typical near-surface winds over the Adriatic region, namely Bora and Sirocco. Two high-resolution (0.11°) EURO-CORDEX regional climate models were used, SMHI-RCA4 and DHMZ-RegCM4, forced by several CMIP5 global climate models and analyzed for two 30-year periods: near-present day and mid-21st century climate conditions under the high-end Representative Concentration Pathway (RCP8.5) scenario. Bora and Sirocco days were extracted for each weather type and a distribution over the 30-year period was presented. Our results suggest that in the winter season, climate model projections indicate a reduction in the main cyclonic types relevant in the formation of Bora over the entire Adriatic region and an increase in the number of anticyclonic types relevant in Sirocco events. In contrast, for the summer season, an increase in the main anticyclonic Bora-related weather types is found in the ensemble over the northern Adriatic region. Full article

There is a well-documented association between ambient fine particulate matter air pollution (PM_2.5) and cardiovascular disease (CVD) morbidity and mortality. Exposure to PM_2.5 can cause premature death and harmful and chronic health effects such as heart attack, diabetes, and stroke. The Environmental Protection Agency sets annual PM_2.5 standards to reduce these negative health effects. Currently above an annual average level of 12.0 µg/m is considered unhealthy. Methods. We examined the association of long-term exposure to PM_2.5 and CVD in a cohort of 44,610 individuals who resided in 12 states recruited into the Southern Community Cohort Study (SCCS). The SCCS was designed to recruit Black and White participants who received care from Federally Qualified Health Centers; hence, they represent vulnerable individuals from low-income families across this vast region. This study tests whether SCCS participants who lived in locations exposed to elevated ambient levels of PM_2.5 concentrations were more likely to report a history of CVD at enrollment (2002–2009). Remotely sensed satellite data integrated with ground monitoring data provide an assessment of the average annual PM_2.5 in urban and rural locations where the SCCS participants resided. We used multilevel logistic regression to estimate the associations between self-reported CVD and exposure to elevated ambient levels of PM_2.5. Results. We found a 13.4 percent increase in the odds of reported CVD with exposure to unhealthy levels of PM_2.5 exposure at enrollment. The SCCS participants with medical histories of hypertension, hypercholesterolemia, and smoking had, overall, 385 percent higher odds of reported CVD than those without these clinical risk factors. Additionally, Black participants were more likely to live in locations with higher ambient PM_2.5 concentrations and report high levels of clinical risk factors, thus, they may be at a greater future risk of CVD. Conclusions: In the SCCS participants, we found a strong relation between exposures to high ambient levels of PM_2.5 and self-reported CVD at enrollment. Full article

China was the first country to undergo large-scale lockdowns in response to the pandemic in early 2020 and a progressive return to normalization after April 2020. Spaceborne observations of atmospheric nitrogen dioxide (NO₂) and oxygenated volatile organic compounds (OVOCs), including formaldehyde (HCHO), glyoxal (CHOCHO), and peroxyacetyl nitrate (PAN), reveal important changes over China in 2020, relative to 2019, in response to the pandemic-induced shutdown and the subsequent drop in pollutant emissions. In February, at the peak of the shutdown, the observed declines in OVOC levels were generally weaker (less than 20%) compared to the observed NO₂ reductions (−40%). In May 2020, the observations reveal moderate decreases in NO₂ (−15%) and PAN (−21%), small changes in CHOCHO (−3%) and HCHO (6%). Model simulations using the regional model MAGRITTEv1.1 with anthropogenic emissions accounting for the reductions due to the pandemic explain to a large extent the observed changes in lockdown-affected regions. The model results suggest that meteorological variability accounts for a minor but non-negligible part (~−5%) of the observed changes for NO₂, whereas it is negligible for CHOCHO but plays a more substantial role for HCHO and PAN, especially in May. The interannual variability of biogenic and biomass burning emissions also contribute to the observed variations, explaining e.g., the important column increases of NO₂ and OVOCs in February 2020, relative to 2019. These changes are well captured by the model simulations. Full article

This paper reconciled the soil ecology benefits of forages and ruminants with reducing GHG emissions from beef. A scenario analysis compared four integrated systems for beef, pork and broilers. Slaughter cattle diets were either business as usual (BAU) or grass fed (GF), and the combined red meat consumption could not exceed the recommendation for human health. The four consumption scenarios included (PS1) equal beef and pork with BAU beef, (PS2) equal beef and pork with GF beef, (PS3) more pork and less beef with GF beef and (PS4) more pork and less beef with BAU beef. Broiler consumption was increased to force all four scenarios to provide the same amount of protein. All four scenarios required similar feed grain areas (2.5 to 3 Mha). At 2.3, 4.4, 2.2 and 1.2 Mha for PS1, PS2, PS3 and PS4, respectively, the areas in harvestable forage showed much greater variation. From high to low GHG emissions, the ranking of scenarios was PS2, PS1, PS3 and PS4. Although allowing for avoidance of soil organic matter loss changed this ranking, the carbon footprint of beef production was still double or more that of pork in all four PS. To reconcile the agro-ecological benefits of beef with reducing GHG emissions, PS3 may be better than PS4. Along with eating more pork and broilers, and less red meat overall, consumers can choose GF beef as an occasional alternative. Full article

In this study, a Land Data Assimilation System (LDAS) is applied over the Carpathian Basin at the Hungarian Meteorological Service to monitor the above-ground biomass, surface fluxes (carbon and water), and the associated root-zone soil moisture at the regional scale (spatial resolution of 8 km × 8 km) in quasi-real-time. In this system the SURFEX model is used, which applies the vegetation growth version of the Interactions between Soil, Biosphere and Atmosphere (ISBA-A-gs) photosynthesis scheme to describe the evolution of vegetation. SURFEX is forced using the outputs of the ALADIN numerical weather prediction model run operationally at the Hungarian Meteorological Service. First, SURFEX is run in an open-loop (i.e., no assimilation) mode for the period 2008–2015. Secondly, the Extended Kalman Filter (EKF) method is used to assimilate Leaf Area Index (LAI) Spot/Vegetation (until May 2014) and PROBA-V (from June 2014) and Soil Water Index (SWI) ASCAT/Metop satellite measurements. The benefit of LDAS is proved over the whole country and to a selected site in West Hungary (Hegyhátsál). It is demonstrated that the EKF can provide useful information both in wet and dry seasons as well. It is shown that the data assimilation is efficient to describe the inter-annual variability of biomass and soil moisture values. The vegetation development and the water and carbon fluxes vary from season to season and LDAS is a capable tool to monitor the variability of these parameters. Full article

Around 1997, when JCAP (the Japan Clean Air Program) began, Japan’s atmospheric environment did not meet the environmental standards for NO₂ and suspended particle matters (SPM), and strict reduction requirements for automobile exhaust gas were required. To achieve environmental standards, further cooperation between the automobile technology and fuel technology sectors was needed. In Europe and the United States, Auto-Oil programs were being implemented to reduce automobile exhaust gas, and JCAP was established as an Auto-Oil program in Japan. The Air Quality Model Study was one of the research themes and research activities continued for a total of 21 years, including JCAP I/II and JATOP I/II/III (the Japan AuTo Oil Program). JATOP was the successor program of JCAP. This paper describes the outline and main results of the JCAP/JATOP Air Quality Model Study. Full article

Six-hourly three-dimensional ensemble variational (3DEnVar) (6H-3DEnVar) data assimilation (DA) assumes constant background error covariance (BEC) during a six-hour DA window and is, therefore, unable to account for temporal evolution of the BEC. This study evaluates the one-hourly 3DEnVar (1H-3DEnVar) and six-hourly 4DEnVar (6H-4DEnVar) DA methods for the analyses and forecasts of hurricanes with rapidly evolving BEC. Both methods account for evolving BEC in a hybrid EnVar DA system. In order to compare these methods, experiments are conducted by assimilating inner core Tail Doppler Radar (TDR) wind for Hurricane Edouard (2014) and by running the Hurricane Weather Research and Forecasting (HWRF) model. In most metrics, 1H-3DEnVar and 6H-4DEnVar analyses and forecasts verify better than 6H-3DEnVar. 6H-4DEnVar produces better thermodynamic analyses than 1H-3DEnVar. Radar reflectivity shows that 1H-3DEnVar produces better structure forecasts. For the first 24–48 h of the intensity forecast, 6H-4DEnVar forecast performs better than 1H-3DEnVar verified against the best track. Degraded 1H-3DEnVar forecasts are found to be associated with background storm center location error as a result of underdispersive ensemble storm center spread. Removing location error in the background improves intensity forecasts of 1H-3DEnVar. Full article

Drought is one of the most complex climate-related phenomena and is expected to progressively affect our lives by causing very serious environmental and socioeconomic damage by the end of the 21st century. In this study, we have extracted a dataset of exceptional meteorological drought events between 1975 and 2019 at the country and subregional scales. Each drought event was described by its start and end date, intensity, severity, duration, areal extent, peak month and peak area. To define such drought events and their characteristics, separate analyses based on three drought indices were performed at 12-month timescale: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). A multivariate combined drought index (DXI) was developed by merging the previous three indices for more understanding of droughts’ features at the country and subregional levels. Principal component analysis (PCA) was used to identify five different drought subregions based on DXI-12 values for 312 Mediterranean stations and a new special score was defined to classify the multi-subregional exceptional drought events across the Mediterranean Basin (MED). The results indicated that extensive drought events occurred more frequently since the late 1990s, showing several drought hotspots in the last decades in the southeastern Mediterranean and northwest Africa. In addition, the results showed that the most severe events were more detected when more than single drought index was used. The highest percentage area under drought was also observed through combining the variations of three drought indices. Furthermore, the drought area in both dry and humid areas in the MED has also experienced a remarkable increase since the late 1990s. Based on a comparison of the drought events during the two periods—1975–1996 and 1997–2019—we find that the current dry conditions in the MED are more severe, intense, and frequent than the earlier period; moreover, the strongest dry conditions occurred in last two decades. The SPEI-12 and RDI-12 have a higher capacity in providing a more comprehensive description of the dry conditions because of the inclusion of temperature or atmospheric evaporative demand in their scheme. A complex range of atmospheric circulation patterns, particularly the Western Mediterranean Oscillation (WeMO) and East Atlantic/West Russia (EATL/WRUS), appear to play an important role in severe, intense and region-wide droughts, including the two most severe droughts, 1999–2001 and 2007–2012, with lesser influence of the NAO, ULMO and SCAND. Full article

In the last decades, thermal infrared ground-based cameras have become effective tools to detect significant spatio-temporal anomalies in the hydrothermal/volcanic environment, possibly linked to impending eruptions. In this paper, we analyzed the temperature time-series recorded by the ground-based Thermal Infrared Radiometer permanent network of INGV-OV, installed inside the Solfatara-Pisciarelli area, the most active fluid emission zones of the Campi Flegrei caldera (Italy). We investigated the temperatures’ behavior in the interval 25 June 2016–29 May 2020, with the aim of tracking possible endogenous hydrothermal/volcanic sources. We performed the Independent Component Analysis, the time evolution estimation of the spectral power, the cross-correlation and the Changing Points’ detection. We compared the obtained patterns with the behavior of atmospheric temperature and pressure, of the time-series recorded by the thermal camera of Mt. Vesuvius, of the local seismicity moment rate and of the CO₂ emission flux. We found an overall influence of exogenous, large scale atmospheric effect, which dominated in 2016–2017. Starting from 2018, a clear endogenous forcing overcame the atmospheric factor, and dominated strongly soil temperature variations until the end of the observations. This paper highlights the importance of monitoring and investigating the soil temperature in volcanic environments, as well as the atmospheric parameters. Full article

This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p < 0.05 to be statistically significant. We observed significant (p < 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (T_min) in Punjab. We also noted a significant (p < 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan. Full article

The multiscale dynamics associated with turbulent convection present in physical systems governed by very high Rayleigh numbers still remains a vividly disputed topic in the community of astrophysicists, and in general, among physicists dealing with heat transport by convection. The Sun is a very close star for which detailed observations and estimations of physical properties on the surface, connected to the processes of the underlying convection zone, are possible. This makes the Sun a unique natural laboratory in which to investigate turbulent convection in the hard turbulence regime, a regime typical of systems characterized by high values of the Rayleigh number. In particular, it is possible to study the geometry of convection using the photospheric magnetic voids (or simply voids), the quasi-polygonal quiet regions nearly devoid of magnetic elements, which cover the whole solar surface and which form the solar magnetic network. This work presents the most extensive statistics, both in the spatial scales studied (1–80 Mm) and in the temporal duration (SC 23 and SC 24), to investigate the multiscale nature of solar magnetic patterns associated with the turbulent convection of our star. We show that the size distribution of the voids, in the 1–80 Mm range, for the 317,870 voids found in the 692 analyzed magnetograms, is basically described by an exponential function. Full article