Found 820 publications. Showing page 28 of 35:
The tropospheric NO2 column from Sentinel-5P/TROPOMI (2018–2020) and Aura/OMI (2010–2020) over Poland, notably for 7 major Polish cities, was used to assess the annual variability and the COVID-19 lockdown effect. On a national scale, during lockdown (March–June 2020), strong sources of pollution were found in Katowice and Warszawa, as well as at the power plant in Bełchatów. A gradual drop in OMI NO2 values between March and June was found for all cities and the entire domain of Poland, this being a part of the annual NO2 cycle derived for every year from 2010 to 2020. In fact, the gradual drop of NO2 in the lockdown year was within the typical monthly and annual variability. In March 2020, Kraków showed the highest NO2 reduction rate. A reduction of NO2 was observed in Gdańsk, Wrocław, and Warszawa during every month of the lock-down period. Several factors, including wind speed and direction, temperature, and increased emission sources, can limit the dispersion and removal of NO2. Although meteorological conditions have a significant impact on the annual cycle of NO2 in Poland, it is important to note that anthropogenic emissions remain the primary driver of NO2 concentrations. Therefore, the study concludes that the effect of COVID-19 restrictions on NO2 pollution was negligible and clarifies the current understanding of the COVID-19 effect over Poland, with an emphasis on hotspots in the major Polish cities and their vicinity. This is consistent with our understanding that the reduction of NO2 pollution is seen in cities due to reduced traffic (domestic, municipal, and airborne).
2023
Polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), organochlorine pesticides (OCPs) and organophosphate esters (OPEs) were assessed in blood plasma and feathers of 19 adult black-legged kittiwakes (Rissa tridactyla) breeding in two colonies (Blomstrandhalvøya and Krykkjefjellet) at the Arctic archipelago, Svalbard. Potential associations with body condition index (BCI) and thyroid hormones were investigated. All compound classes were detected in both blood plasma and feathers, but due to low sample size and volumes, OPEs could only be quantified in four individuals, warranting larger follow-up studies. Kittiwakes breeding at Blomstrandhalvøya had significantly higher concentrations of organic pollutants in blood plasma than kittiwakes breeding at Krykkjefjellet (p < 0.001). Concentrations in blood plasma and feathers did not significantly correlate for any of the investigated compounds, and feather concentrations did not differ significantly between the colonies. This suggests that pollutant levels in adult kittiwake feathers do not reflect local contamination at breeding sites and are as such not useful to monitor local contamination at Svalbard. Significant negative associations between BCI and most pollutants were found in both populations, whereas significant correlations between the BCI, the ratio of total triiodothyronine to free triiodothyronine (TT3:fT3), and several pollutants were only found for kittiwakes from Blomstrandhalvøya (all r ≥ −0.60 and p ≤ 0.05). This indicates that higher levels of circulating pollutants during the breeding period covary with the TT3: fT3 ratio, and may act as an additional stressor during this period.
2018
Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and presents a general framework to evaluate them, based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those where it is expected that the techniques will perform well, and those for which some complexity about the site may provide a more severe test. Overall all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small/large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as Optimal Estimation the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potential mixed land/water surfaces, or aerosol optical properties outside of the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for refinement of these techniques.
2020
Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.
2022
Signals from the south; humpback whales carry messages of Antarctic sea‐ice ecosystem variability
Southern hemisphere humpback whales (Megaptera novaeangliae) rely on summer prey abundance of Antarctic krill (Euphausia superba) to fuel one of the longest‐known mammalian migrations on the planet. It is hypothesized that this species, already adapted to endure metabolic extremes, will be one of the first Antarctic consumers to show measurable physiological change in response to fluctuating prey availability in a changing climate; and as such, a powerful sentinel candidate for the Antarctic sea‐ice ecosystem. Here, we targeted the sentinel parameters of humpback whale adiposity and diet, using novel, as well as established, chemical and biochemical markers, and assembled a time trend spanning 8 years. We show the synchronous, inter‐annual oscillation of two measures of humpback whale adiposity with Southern Ocean environmental variables and climate indices. Furthermore, bulk stable isotope signatures provide clear indication of dietary compensation strategies, or a lower trophic level isotopic change, following years indicated as leaner years for the whales. The observed synchronicity of humpback whale adiposity and dietary markers, with climate patterns in the Southern Ocean, lends strength to the role of humpback whales as powerful Antarctic sea‐ice ecosystem sentinels. The work carries significant potential to reform current ecosystem surveillance in the Antarctic region.
2018
2018
European pollen reanalysis, 1980–2022, for alder, birch, and olive
The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980–2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications.
2024
2020
Seasonal Variation of Wet Deposition of Black Carbon at Ny-Ålesund, Svalbard
Black carbon (BC) aerosol deposited in and onto Arctic snow increases the snow's absorption of solar radiation and accelerates snowmelt. Concentrations of BC in the Arctic atmosphere and snow are controlled by wet deposition; however, details of this process are poorly understood owing to the scarcity of time-resolved measurements of BC in hydrometeors. We measured mass concentrations of BC in hydrometeors (CMBC) and in air (MBC) with 16% and 15% accuracies, respectively, at Ny-Ålesund, Svalbard during 2012–2019. Median monthly MBC and CMBC values showed similar seasonal variations, being high in winter-spring and low in summer. Median monthly BC wet deposition mass flux (FMBC) was highest in winter and lowest in summer, associated with seasonal patterns of CMBC and precipitation. Seasonally averaged BC size distributions in hydrometeors were similar except for summer. Measurements of MBC and CMBC in spring 2017 showed a size-independent removal efficiency, indicating that BC-containing particles were efficiently activated into cloud droplets. These observations at Ny-Ålesund were compared with observations at Barrow, Alaska, during 2013–2017. The near-surface MBC at Ny-Ålesund and Barrow had similar seasonal patterns; however, the two sites differed in CMBC and FMBC. In summer, CMBC was low at Ny-Ålesund but moderate at Barrow, likely reflecting differences in MBC in the lower troposphere. Seasonally averaged BC size distributions in hydrometeors were similar at both sites, suggesting that average BC size distributions are similar in the Arctic lower troposphere. The efficiency of BC removal tends to be size-independent during transport, leading to the observed similarity.
2021
Arctic sea-ice loss intensifies aerosol transport to the Tibetan Plateau
The Tibetan Plateau (TP) has recently been polluted by anthropogenic emissions transported from South Asia, but the mechanisms conducive to this aerosol delivery are poorly understood. Here we show that winter loss of Arctic sea ice over the subpolar North Atlantic boosts aerosol transport toward the TP in April, when the aerosol loading is at its climatological maximum and preceding the Indian summer monsoon onset. Low sea ice in February weakens the polar jet, causing decreased Ural snowpack via reduced transport of warm, moist oceanic air into the high-latitude Eurasian interior. This diminished snowpack persists through April, reinforcing the Ural pressure ridge and East Asian trough, segments of a quasi-stationary Rossby wave train extending across Eurasia. These conditions facilitate an enhanced subtropical westerly jet at the southern edge of the TP, invigorating upslope winds that combine with mesoscale updrafts to waft emissions over the Himalayas onto the TP.
2020
The fingerprint of the summer 2018 drought in Europe on ground-based atmospheric CO2 measurements
During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO2) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO2 cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO2 due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO2 transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO2 uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO2 anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO2 anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018.
This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
2020
Understanding nanomaterial (NM)–protein interactions is a key issue in defining the bioreactivity of NMs with great impact for nanosafety. In the present work, the complex phenomena occurring at the bio/nano interface were evaluated in a simple case study focusing on NM–protein binding thermodynamics and protein stability for three representative metal oxide NMs, namely, zinc oxide (ZnO; NM-110), titanium dioxide (TiO2; NM-101), and silica (SiO2; NM-203). The thermodynamic signature associated with the NM interaction with an abundant protein occurring in most cell culture media, bovine serum albumin (BSA), has been investigated by isothermal titration and differential scanning calorimetry. Circular dichroism spectroscopy offers additional information concerning adsorption-induced protein conformational changes. The BSA adsorption onto NMs is enthalpy-controlled, with the enthalpic character (favorable interaction) decreasing as follows: ZnO (NM-110) > SiO2 (NM-203) > TiO2 (NM-101). The binding of BSA is spontaneous, as revealed by the negative free energy, ΔG, for all systems. The structural stability of the protein decreased as follows: TiO2 (NM-101) > SiO2 (NM-203) > ZnO (NM-110). As protein binding may alter NM reactivity and thus the toxicity, we furthermore assessed its putative influence on DNA damage, as well as on the expression of target genes for cell death (RIPK1, FAS) and oxidative stress (SOD1, SOD2, CAT, GSTK1) in the A549 human alveolar basal epithelial cell line. The enthalpic component of the BSA–NM interaction, corroborated with BSA structural stability, matched the ranking for the biological alterations, i.e., DNA strand breaks, oxidized DNA lesions, cell-death, and antioxidant gene expression in A549 cells. The relative and total content of BSA in the protein corona was determined using mass-spectrometry-based proteomics. For the present case study, the thermodynamic parameters at bio/nano interface emerge as key descriptors for the dominant contributions determining the adsorption processes and NMs toxicological effect.
2020
The response of the atmosphere to solar irradiance and geomagnetic activity is analyzed in experiments with the Whole Atmosphere Community Climate Model (WACCM) under idealized forcings. Four experiments are carried out combining high (H) and low (L) solar radiative forcing with high (7) and low (3) geomagnetic activity: H7 (with high radiative forcing and high geomagnetic activity), H3, (high/low), L7 (low/high), and L3 (low/low). The comparison between these experiment is used to assess the effects of solar radiative forcing and geomagnetic activity mainly on the stratosphere. A two-step Monte Carlo-based statistical test, which defines an impact score, is used to assess statistically significant impacts on regional scales, on pressure levels, for a few key model variables, like NOx, ozone, and temperature.
Under low solar forcing (L7/L3), a statistically significant relationship between geomagnetic activity and NOx is found in both hemispheres and for all seasons. An equally strong relationship is lacking for ozone and temperature when analyzing these fields on isobaric levels. A statistically significant impact on stratospheric ozone is only seen in austral winter and spring. However, vertical cross sections show statistically significant impact on temperature and ozone mainly in the southern hemisphere (SH) during austral winter and the following spring.
Significant and persistent signals in both SH NOx and ozone concentrations are only produced when the effect of high solar forcing is added to high geomagnetic activity (H7). In this case, statistically significant differences are also found for mesospheric temperatures, ozone and NOx. This latter result appears also under low geomagnetic activity as a result of solar forcing alone, suggesting that solar irradiance significantly affects NOx, ozone and stratospheric temperatures and, in some seasons, even tropospheric temperature.
In summary, geomagnetic activity primarily affects NOx and ozone concentrations in the SH. Solar maximum conditions can reduce the amount of NOx in the stratosphere because of higher ozone production. Thus, we conclude that correlations between changes in solar irradiance and geomagnetic activity are important with respect to their effects on the atmosphere. In particular, geomagnetic activity can modulate atmospheric ozone concentrations and other associated stratospheric and tropospheric variables under conditions of high solar activity.
2020
2025
2019
During an exceptionally warm September of 2016, the unique, stable weather conditions over Poland allowed for an extensive testing of the new algorithm developed to improve the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) aerosol optical depth (AOD) retrieval. The development was conducted in the frame of the ESA-ESRIN SAMIRA project. The new AOD algorithm aims at providing the aerosol optical depth maps over the territory of Poland with a high temporal resolution of 15 minutes. It was tested on the data set obtained between 11-16 September 2016, during which a day of relatively clean atmospheric background related to an Arctic airmass inflow was surrounded by a few days with well increased aerosol load of different origin. On the clean reference day, for estimating surface reflectance the AOD forecast available on-line via the Copernicus Atmosphere Monitoring Service (CAMS) was used. The obtained AOD maps were validated against AODs available within the Poland-AOD and AERONET networks, and with AOD values obtained from the PollyXT-UW lidar. of the University of Warsaw (UW).
2018
Stochastic and deterministic processes in Asymmetric Tsetlin Machine
This paper introduces a new approach to enhance the decision-making capabilities of the Tsetlin Machine (TM) through the Stochastic Point Location (SPL) algorithm and the Asymmetric Steps technique. We incorporate stochasticity and asymmetry into the TM's process, along with a decaying normal distribution function that improves adaptability as it converges toward zero over time. We present two methods: the Asymmetric Probabilistic Tsetlin (APT) Machine, influenced by random events, and the Asymmetric Tsetlin (AT) Machine, which transitions from probabilistic to deterministic states. We evaluate these methods against traditional machine learning algorithms and classical Tsetlin (CT) machines across various benchmark datasets. Both AT and APT demonstrate competitive performance, with the AT model notably excelling, especially in complex datasets.
2025
Simulating CH4 and CO2 over South and East Asia using the zoomed chemistry transport model LMDz-INCA
The increasing availability of atmospheric measurements of greenhouse gases (GHGs) from surface stations can improve the retrieval of their fluxes at higher spatial and temporal resolutions by inversions, provided that transport models are able to properly represent the variability of concentrations observed at different stations. South and East Asia (SEA; the study area in this paper including the regions of South Asia and East Asia) is a region with large and very uncertain emissions of carbon dioxide (CO2) and methane (CH4), the most potent anthropogenic GHGs. Monitoring networks have expanded greatly during the past decade in this region, which should contribute to reducing uncertainties in estimates of regional GHG budgets. In this study, we simulate concentrations of CH4 and CO2 using zoomed versions (abbreviated as "ZAs") of the global chemistry transport model LMDz-INCA, which have fine horizontal resolutions of ∼ 0.66° in longitude and ∼ 0.51° in latitude over SEA and coarser resolutions elsewhere. The concentrations of CH4 and CO2 simulated from ZAs are compared to those from the same model but with standard model grids of 2.50° in longitude and 1.27° in latitude (abbreviated as "STs"), both prescribed with the same natural and anthropogenic fluxes. Model performance is evaluated for each model version at multi-annual, seasonal, synoptic and diurnal scales, against a unique observation dataset including 39 global and regional stations over SEA and around the world. Results show that ZAs improve the overall representation of CH4 annual gradients between stations in SEA, with reduction of RMSE by 16–20% compared to STs. The model improvement mainly results from reduction in representation error at finer horizontal resolutions and thus better characterization of the CH4 concentration gradients related to scattered distributed emission sources. However, the performance of ZAs at a specific station as compared to STs is more sensitive to errors in meteorological forcings and surface fluxes, especially when short-term variabilities or stations close to source regions are examined. This highlights the importance of accurate a priori CH4 surface fluxes in high-resolution transport modeling and inverse studies, particularly regarding locations and magnitudes of emission hotspots. Model performance for CO2 suggests that the CO2 surface fluxes have not been prescribed with sufficient accuracy and resolution, especially the spatiotemporally varying carbon exchange between land surface and atmosphere. In addition, the representation of the CH4 and CO2 short-term variabilities is also limited by model's ability to simulate boundary layer mixing and mesoscale transport in complex terrains, emphasizing the need to improve sub-grid physical parameterizations in addition to refinement of model resolutions.
2018
While observed mesospheric polar nitric acid enhancements have been attributed to energetic particle precipitation through ion cluster chemistry in the past, this phenomenon is not reproduced in current whole‐atmosphere chemistry‐climate models. We investigate such nitric acid enhancements resulting from energetic electron precipitation events using a recently developed variant of the Whole Atmosphere Community Climate Model (WACCM) that includes a sophisticated ion chemistry tailored for the D‐layer of the ionosphere (50–90 km), namely, WACCM‐D. Using the specified dynamics mode, that is, nudging dynamics in the troposphere and stratosphere to meteorological reanalyses, we perform a 1‐year‐long simulation (July 2009–June 2010) and contrast WACCM‐D with the standard WACCM. Both WACCM and WACCM‐D simulations are performed with and without forcing from medium‐to‐high energy electron precipitation, allowing a better representation of the energetic electrons penetrating into the mesosphere. We demonstrate the effects of the strong particle precipitation events which occurred during April and May 2010 on nitric acid and on key ion cluster species, as well as other relevant species of the nitrogen family. The 1‐year‐long simulation allows the event‐related changes in neutral and ionic species to be placed in the context of their annual cycle. We especially highlight the role played by medium‐to‐high energy electrons in triggering ion cluster chemistry and ion‐ion recombinations in the mesosphere and lower thermosphere during the precipitation event, leading to enhanced production of nitric acid and raising its abundance by 2 orders of magnitude from 10−4 to a few 10−2 ppb.
2018
While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios.
In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs.
Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.
2022
Eastward-propagating planetary waves prior to the January 2009 sudden stratospheric warming
Eastward-propagating planetary waves (EPWs) were investigated prior to the boreal January 2009 major sudden stratospheric warming (SSW) event simulated by the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model with specified dynamics. About 22 days before SSW onset, a background flow with jet maxima around the upper polar stratosphere and subtropical mesosphere developed due to the net forcing by gravity and planetary waves. The mesospheric wind structure was largely unstable and supported a wave geometry conducive to overreflection. With a zonal phase speed of ∼10 m s−1, EPWs appeared near their turning and critical layers as wavenumber-2 perturbations in the stratosphere and mesosphere. Accompanied by upward EPW activity from the lower stratosphere, EPW growth exhibited characteristics of wave instability and overreflection.
2021
2019
Using the Super Dual Auroral Radar Network observations (clustered around 60°N) and NCAR CESM2.0 extended Whole Atmosphere Community Climate Model nudged with reanalyzes, we examine the climatology of semidiurnal tides in meridional wind associated with the migrating component (SW2) and non‐migrating components of wavenumbers 1 (SW1) and 3 (SW3). We then illustrate their composite response to major sudden stratospheric warmings (SSWs). Peaking in late summer and winter, the climatological SW2 amplitude exceeds SW1 and SW3 except around late Fall and Spring. The winter climatological peak is absent in the model perhaps due to the zonal wind bias at the observed altitudes. The observed SW2 amplitude declines after SSW onset before enhancing ∼10 days later, along with SW1 and SW3. Within the observed region, the simulated SW2 only amplifies after SSW onset, with minimal SW1 and SW3 responses. The model reveals a stronger SW2 response above the observed location, with diminished amplitude before and enhancement after SSW globally. This enhancement appears related to increased equatorial ozone heating and background wind symmetry. The strongest SW1 and SW3 growth occurs in the Southern Hemisphere before SSW. SW2 and quasi‐stationary planetary wave activities are temporally collocated during SSW suggesting that their interactions excite SW1 and SW3. After SSW, the model also reveals (1) semidiurnal‐tide‐like perturbations generated possibly by the interactions between SW2 and westward‐traveling disturbances and (2) the enhancement of migrating semidiurnal lunar tide in the Northern Hemisphere that exceeds non‐migrating tidal and semidiurnal‐tide‐like responses. The simulated eastward‐propagating semidiurnal tides are briefly examined.
2021
The hydroxyl radical (OH) largely determines the atmosphere's oxidative capacity and, thus, the lifetimes of numerous trace gases, including methane (CH4). Hitherto, observation-based approaches for estimating the atmospheric oxidative capacity have primarily relied on using methyl chloroform (MCF), but as the atmospheric abundance of MCF has declined, the uncertainties associated with this method have increased. In this study, we examine the use of five hydrofluorocarbons (HFCs) (HFC-134a, HFC-152a, HFC-365mfc, HFC-245fa, and HFC-32) in multi-species inversions, which assimilate three HFCs simultaneously, as an alternative method to estimate atmospheric OH. We find robust estimates of OH regardless of which combination of the three HFCs are used in the inversions. Our results show that OH has remained fairly stable during our study period from 2004 to 2021, with variations of
2024