Investigating chemical composition of the troposphere over the Russian Arctic using the "Optik" Tu-134 aircraft laboratory

The need to undertake a comprehensive investigation of the atmospheric composition over the Russian segment of the Arctic is caused by a serious lack and irregularity in obtaining observational data from this regio of the Earth. In addition, a comparison of the aircraft in-situ measurements with satellite data retrieved for the Kara Sea region in 2017 revealed large uncertainties in determining the vertical distribution of greenhouse gas concentrations using remote sensing methods. The development and improvement of the last ones needs at least their periodic verification by means of undertaking precise in-situ aircraft measurements.The general scheme of the proposed experiment is as follows (map is attached): flight from Novosibirsk to Naryan-Mar via Sabetta. From Naryan-Mar, flight to a water area of the Bering Sea (up to 1000 km). Flight from Naryan-Mar to Sabetta. From here, flight to a water area of the Kara Sea (up to 1000 km). Then, flight to Tiksi. Flight from Tiksi to a water area of the Laptev Sea (up to 1000 km). Flight to Chokurdakh or Chersky. From there, flight to a water area of the East Siberian Sea (up to 1000 km). Flight to Cape Schmidt. Flight to a water area of the Chukchi Sea (up to 1000 km). Return route: Cape Shmidt&#8211;Chersky (or Chokurdah)&#8211;Yakutsk&#8211;Bratsk&#8211;Novosibirsk. It will take about 100 hours of flying time to implement the entire aircraft campaign. Campaign period is about 2-3 weeks. It is better to undertake the campaign during summer when the ocean is open. Flights over the land surface are assumed to be undertaken from 0.5 km to 11 km above ground level while above the sea from 0.2 km to 11 km. The flight profile is variable from the maximum possible height to the minimum allowed one. Vertical profiles of gas and aerosol composition will be obtained, including black carbon and organic components, as well as basic meteorological quantities.Satellite data will be verified that do not yet provide acceptable accuracy. For the first time, unique information will be obtained over the least explored region of the Arctic, which is crucial for the whole planet in terms of climate formation and the impact of global warming.

Download Full-text

Aerosol size distributions during the Atmospheric Tomography Mission (ATom): methods, uncertainties, and data products

Atmospheric Measurement Techniques ◽

10.5194/amt-12-3081-2019 ◽

2019 ◽

Vol 12 (6) ◽

pp. 3081-3099 ◽

Cited By ~ 14

Author(s):

Charles A. Brock ◽

Christina Williamson ◽

Agnieszka Kupc ◽

Karl D. Froyd ◽

Frank Erdesz ◽

...

Keyword(s):

High Resolution ◽

Size Distribution ◽

Atmospheric Composition ◽

The Arctic ◽

Distribution Data ◽

Size Distributions ◽

Aerosol Composition ◽

Aerosol Mass ◽

Data Products

Abstract. From 2016 to 2018 a DC-8 aircraft operated by the US National Aeronautics and Space Administration (NASA) made four series of flights, profiling the atmosphere from 180 m to ∼12 km above sea level (km a.s.l.) from the Arctic to the Antarctic over both the Pacific and Atlantic oceans. This program, the Atmospheric Tomography Mission (ATom), sought to sample the troposphere in a representative manner, making measurements of atmospheric composition in each season. This paper describes the aerosol microphysical measurements and derived quantities obtained during this mission. Dry size distributions from 2.7 nm to 4.8 µm in diameter were measured in situ at 1 Hz using a battery of instruments: 10 condensation particle counters with different nucleation diameters, two ultra-high-sensitivity aerosol size spectrometers (UHSASs), one of which measured particles surviving heating to 300 ∘C, and a laser aerosol spectrometer (LAS). The dry aerosol measurements were complemented by size distribution measurements from 0.5 to 930 µm diameter at near-ambient conditions using a cloud, aerosol, and precipitation spectrometer (CAPS) mounted under the wing of the DC-8. Dry aerosol number, surface area, and volume, and optical scattering and asymmetry parameters at several wavelengths from the near-UV to the near-IR ranges were calculated from the measured dry size distributions (2.7 nm to 4.8 µm). Dry aerosol mass was estimated by combining the size distribution data with particle density estimated from independent measurements of aerosol composition with a high-resolution aerosol mass spectrometer and a single-particle soot photometer. We describe the instrumentation and fully document the aircraft inlet and flow distribution system, the derivation of uncertainties, and the calculation of data products from combined size distributions. Comparisons between the instruments and direct measurements of some aerosol properties confirm that in-flight performance was consistent with calibrations and within stated uncertainties for the two deployments analyzed. The unique ATom dataset contains accurate, precise, high-resolution in situ measurements of dry aerosol size distributions, and integral parameters, and estimates and measurements of optical properties, for particles < 4.8 µm in diameter that can be used to evaluate aerosol abundance and processes in global models.

Download Full-text

Aerosol size distributions during the Atmospheric Tomography (ATom) mission: methods, uncertainties, and data products

10.5194/amt-2019-44 ◽

2019 ◽

Cited By ~ 1

Author(s):

Charles A. Brock ◽

Christina Williamson ◽

Agnieszka Kupc ◽

Karl Froyd ◽

Frank Erdesz ◽

...

Keyword(s):

High Resolution ◽

Size Distribution ◽

Atmospheric Composition ◽

The Arctic ◽

Distribution Data ◽

Size Distributions ◽

Aerosol Composition ◽

Aerosol Mass ◽

Data Products

Abstract. From 2016–2018 a DC-8 aircraft operated by the U.S. National Aeronautics and Space Administration (NASA) made four series of flights, profiling the atmosphere from 150 m to ~ 12 km above sea level from the Arctic to the Antarctic over both the Pacific and Atlantic Oceans. This program, the Atmospheric Tomography (ATom) mission, sought to sample the troposphere in a representative manner, making measurements of atmospheric composition in each season. This paper describes the aerosol microphysical measurements and derived quantities obtained during this mission. Dry size distributions from 2.7 nm to 4.8 µm in diameter were measured in-situ at 1 Hz using a battery of instruments: 10 condensation particle counters with different nucleation diameters, two ultra-high sensitivity aerosol size spectrometers (UHSAS), one of which measured particles surviving heating to 300 °C, and a laser aerosol spectrometer (LAS). The dry aerosol measurements were complemented by size distribution measurements from 0.5–930 µm diameter at near-ambient conditions using a cloud, aerosol, and precipitation spectrometer (CAPS) mounted under the wing of the DC-8. Dry aerosol number, surface area, and volume, and optical scattering and asymmetry parameter at several wavelengths from the near-UV to the near-IR were calculated from the measured dry size distributions (2.7 nm to 4.8 µm). Dry aerosol mass was estimated by combining the size distribution data with particle density estimated from independent measurements of aerosol composition with a high-resolution aerosol mass spectrometer and a single particle soot photometer. This paper briefly describes the instrumentation and fully documents the aircraft inlet and flow distribution system, the derivation of uncertainties, and the calculation of data products from combined size distributions. Comparisons between the instruments and direct measurements of some aerosol properties confirm that in-flight performance was consistent with calibrations and within stated uncertainties for the two deployments analyzed. The unique ATom dataset contains accurate, precise, high-resolution in-situ measurements of dry aerosol size distributions, and integral parameters, and estimates and measurements of optical properties, for particles

Download Full-text

Application of hyper-resolution hydrological modeling for water resources decision making

10.5194/egusphere-egu2020-2766 ◽

2020 ◽

Author(s):

Eric Wood ◽

Noemi Vergopolan ◽

Peirong Lin ◽

Ming Pan

Keyword(s):

Decision Making ◽

Water Resources ◽

Satellite Data ◽

Land Surface ◽

Hydrological Modeling ◽

Land Surface Model ◽

Management Decision ◽

Surface Model ◽

The Impact

Managing water resources and basin reclamation requires hydrological data across a set of scales.&#160; Unfortunately, in many areas the in-situ data is sparse, or not made available to water managers.&#160; With NASA, ESA and Chinese satellites, their data can potentially be merged with in-situ gauge data.&#160; Doing so results in a number of research challenges: 1. Satellite data based on microwave sensors (e.g. L-band sensors from SMAP or SMOS) results in coarse resolution (~35-50 km) making the data difficult for management; (ii) Satellite data from instruments like LandSat (~90m) suffers from cloud contamination.&#160; New satellites improve resolution but still suffer cloud contamination; (iii) Precipitation (along with radiation) falls between these two spectrums, and its fast dynamics can impact water management decision making; (iv) Topographic and soil characteristics, which govern the runoff from the land to rivers; and (v) river flows that are a water source for drought and a site for reservoirs.In this talk I will present a new land surface model (HydroBlocks) that we run at a 30m resolution at regional to continental scales.&#160; The water is transmitted to hyper-resolution streams for which we have extracted ~2,900,000 reaches.&#160; Visualization of the models will offer the listener the impact of moving to these scales; and the data needed for water resources management of river basins.

Download Full-text

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

Proceedings of International Conference "Managinag risks to coastal regions and communities in a changinag world" (EMECS'11 - SeaCoasts XXVI) ◽

10.31519/conferencearticle_5b1b93852689d4.28131112 ◽

2017 ◽

Author(s):

Alexander Myasoedov ◽

Sergey Azarov ◽

Ekaterina Balashova ◽

...

Keyword(s):

Satellite Data ◽

Wind Wave ◽

Arctic Region ◽

Web Gis ◽

The Arctic ◽

Flexible Tool ◽

In Situ Data ◽

Current State ◽

Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

Download Full-text

Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling

Surveys in Geophysics ◽

10.1007/s10712-021-09637-5 ◽

2021 ◽

Author(s):

Gary Sutlieff ◽

Lucy Berthoud ◽

Mark Stinchcombe

Keyword(s):

Satellite Data ◽

Meteorological Data ◽

Atmospheric Composition ◽

Chemical Detection ◽

List Type ◽

Data Types ◽

Wide Range ◽

Future Technologies ◽

The Impact ◽

Near Future

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field

Download Full-text

Thirty-Nine-Year Wave Hindcast, Storm Activity, and Probability Analysis of Storm Waves in the Kara Sea, Russia

Water ◽

10.3390/w13050648 ◽

2021 ◽

Vol 13 (5) ◽

pp. 648

Author(s):

Stanislav Myslenkov ◽

Vladimir Platonov ◽

Alexander Kislov ◽

Ksenia Silvestrova ◽

Igor Medvedev

Keyword(s):

Climate Change ◽

Pareto Distribution ◽

Linear Trend ◽

Wind Waves ◽

Kara Sea ◽

The Arctic ◽

Storm Events ◽

Storm Activity ◽

Significant Linear Trend ◽

The Impact

The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

Download Full-text

Plot-scale retrieval of land surface temperature and emissivity estimation

10.5194/egusphere-egu21-3962 ◽

2021 ◽

Author(s):

Gitanjali Thakur ◽

Stan Schymanski ◽

Kaniska Mallick ◽

Ivonne Trebs

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Satellite Data ◽

Land Surface ◽

Longwave Radiation ◽

Landscape Scale ◽

The Earth ◽

Downwelling Longwave Radiation

The surface energy balance (SEB) is defined as the balance between incoming energy from the sun and outgoing energy from the Earth&#8217;s surface. All components of the SEB depend on land surface temperature (LST). Therefore, LST is an important state variable that controls the energy and water exchange between the Earth&#8217;s surface and the atmosphere. LST can be estimated radiometrically, based on the infrared radiance emanating from the surface. At the landscape scale, LST is derived from thermal radiation measured using&#160; satellites.&#160; At the plot scale, eddy covariance flux towers commonly record downwelling and upwelling longwave radiation, which can be inverted to retrieve LST&#160; using the grey body equation : &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Rlup = &#949;&#963; Ts4 + (1 &#8722; &#949;) R ldw&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; (1) where Rlup is the upwelling longwave radiation, Rldw is the downwelling longwave radiation, &#949; is the surface emissivity, Ts&#160; is the surface temperature and &#963;&#160; is the Stefan-Boltzmann constant. The first term is the temperature-dependent part, while the second represents reflected longwave radiation. Since in the past downwelling longwave radiation was not measured routinely using flux towers, it is an established practice to only use upwelling longwave radiation for the retrieval of plot-scale LST, essentially neglecting the reflected part and shortening Eq. 1 to: &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Rlup = &#949;&#963; Ts4 &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160;&#160; (2) Despite&#160; widespread availability of downwelling longwave radiation measurements, it is still common to use the short equation (Eq. 2) for in-situ LST retrieval. This prompts the question if ignoring the downwelling longwave radiation introduces a bias in LST estimations from tower measurements. Another associated question is how to obtain the correct &#949; needed for in-situ LST retrievals using tower-based measurements. The current work addresses these two important science questions using observed fluxes at eddy covariance towers for different land cover types. Additionally, uncertainty in retrieved LST and emissivity due to uncertainty in input fluxes was quantified using SOBOL-based uncertainty analysis (SALib). Using landscape-scale emissivity obtained from satellite data (MODIS), we found that the LST&#160; obtained using the complete equation (Eq. 1) is 0.5 to 1.5 K lower than the short equation (Eq. 2). Also, plot-scale emissivity was estimated using observed sensible heat flux and surface-air temperature differences. Plot-scale emissivity obtained using the complete equation was generally between 0.8 to 0.98 while the short equation gave values between 0.9 to 0.98, for all land cover types. Despite additional input data for the complete equation, the uncertainty in plot-scale LST was not greater than if the short equation was used. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) were strongly correlated with our plot-scale estimates, but on average higher by 0.5 to 9 K, regardless of the equation used. However, for most sites, the correspondence between MODIS TERRA LST and retrieved plot-scale LST estimates increased significantly if plot-scale emissivity was used instead of the landscape-scale emissivity obtained from satellite data.

Download Full-text

SMOS Neural Network Soil Moisture Data Assimilation in a Land Surface Model and Atmospheric Impact

10.20944/preprints201904.0216.v1 ◽

2019 ◽

Author(s):

Nemesio Rodriguez-Fernandez ◽

Patricia de Rosnay ◽

Clement Albergel ◽

Philippe Richaume ◽

Filipe Aires ◽

...

Keyword(s):

Neural Network ◽

Soil Moisture ◽

Data Assimilation ◽

Land Surface ◽

Positive Impact ◽

Land Surface Model ◽

Surface Model ◽

Northern Asia ◽

The Impact

The assimilation of Soil Moisture and Ocean Salinity (SMOS) data into the ECMWF (European Centre for Medium Range Weather Forecasts) H-TESSEL (Hydrology revised - Tiled ECMWF Scheme for Surface Exchanges over Land) model is presented. SMOS soil moisture (SM) estimates have been produced specifically by training a neural network with SMOS brightness temperatures as input and H-TESSEL model SM simulations as reference. This can help the assimilation of SMOS information in several ways: (1) the neural network soil moisture (NNSM) data have a similar climatology to the model, (2) no global bias is present with respect to the model even if regional differences can exist. Experiments performing joint data assimilation (DA) of NNSM, 2 metre air temperature and relative humidity or NNSM-only DA are discussed. The resulting SM was evaluated against a large number of in situ measurements of SM obtaining similar results to those of the model with no assimilation, even if significant differences were found from site to site. In addition, atmospheric forecasts initialized with H-TESSEL runs (without DA) or with the analysed SM were compared to measure of the impact of the satellite information. Although, NNSM DA has an overall neutral impact in the forecast in the Tropics, a significant positive impact was found in other areas and periods, especially in regions with limited in situ information. The joint NNSM, T2m and RH2m DA improves the forecast for all the seasons in the Southern Hemisphere. The impact is mostly due to T2m and RH2m, but SMOS NN DA alone also improves the forecast in July- September. In the Northern Hemisphere, the joint NNSM, T2m and RH2m DA improves the forecast in April-September, while NNSM alone has a significant positive effect in July-September. Furthermore, forecasting skill maps show that SMOS NNSM improves the forecast in North America and in Northern Asia for up to 72 hours lead time.

Download Full-text

The prevalence of meteoric-sulphuric particles within the stratospheric aerosol layer

10.5194/egusphere-egu21-15390 ◽

2021 ◽

Author(s):

Graham Mann ◽

James Brooke ◽

Kamalika Sengupta ◽

Lauren Marshall ◽

Sandip Dhomse ◽

...

Keyword(s):

High Latitude ◽

Climate Model ◽

Polar Vortex ◽

Stratospheric Aerosol ◽

Light Extinction ◽

The Arctic ◽

Aerosol Layer ◽

Aerosol Composition ◽

Particle Layer

The widespread presence of meteoric smoke particles (MSPs) within a distinct class of stratospheric aerosol particles has become clear from in-situ measurements in the Arctic, Antarctic and at mid-latitudes. &#160; We apply an adapted version of the interactive stratosphere aerosol configuration of the composition-climate model UM-UKCA, to predict the global distribution of meteoric-sulphuric particles nucleated heterogeneously on MSP cores. We compare the UM-UKCA results to new MSP-sulphuric simulations with the European stratosphere-troposphere chemistry-aerosol modelling system IFS-CB05-BASCOE-GLOMAP. The simulations show a strong seasonal cycle in meteoric-sulphuric particle abundance results from the winter-time source of MSPs transported down into the stratosphere in the polar vortex. Coagulation during downward transport sees high latitude MSP concentrations reduce from ~500 per cm3 at 40km to ~20 per cm3 at 25km, the uppermost extent of the stratospheric aerosol particle layer (the Junge layer). &#160; Once within the Junge layer's supersaturated environment, meteoric-sulphuric particles form readily on the MSP cores, growing to 50-70nm dry-diameter (Dp) at 20-25km. Further inter-particle coagulation between these non-volatile particles reduces their number to 1-5 per cc at 15-20km, particle sizes there larger, at Dp ~100nm. The model predicts meteoric-sulphurics in high-latitude winter comprise >90% of Dp>10nm particles above 25km, reducing to ~40% at 20km, and ~10% at 15km. &#160; These non-volatile particle fractions are slightly less than measured from high-altitude aircraft in the lowermost Arctic stratosphere (Curtius et al., 2005; Weigel et al., 2014), and consistent with mid-latitude aircraft measurements of lower stratospheric aerosol composition (Murphy et al., 1998), total particle concentrations &#160;also matching in-situ balloon measurements from Wyoming (Campbell and Deshler, 2014). &#160; The MSP-sulphuric interactions also improve agreement with SAGE-II observed stratospheric aerosol extinction in the quiescent 1998-2002 period.&#160; &#160; Simulations with a factor-8-elevated MSP input form more Dp>10nm meteoric-sulphurics, but the increased number sees fewer growing to Dp ~100nm, the increased MSPs reducing the stratospheric aerosol layer&#8217;s light extinction.

Download Full-text

Source identification of aerosol chemical composition in the Atlas region of North Africa.

10.5194/dach2022-259 ◽

2021 ◽

Author(s):

Nabil Deabji ◽

Khanneh Wadinga Fomba ◽

Eduardo José dos Santos Souza ◽

Hartmut Herrmann

Keyword(s):

High Altitude ◽

Complex Mixture ◽

Saharan Dust ◽

Atmospheric Composition ◽

Urban Site ◽

Chemical Components ◽

Research Station ◽

African Region ◽

Aerosol Composition ◽

The Impact

Aerosol particles are important constituents of the atmosphere due to their role in controlling climate-related processes. In addition, their impacts on air quality and human health make it essential to study. However, the characterization and the identification of natural and anthropogenic atmospheric particles can be challenging due to the complex mixture occurring during atmospheric transport. Background locations such as high-altitude sites provide valuable infrastructure for obtaining representative data for understanding various pathways for aerosol interactions useful in assessing atmospheric composition. However, information about aerosol characteristics at high-altitude in the African regions and their relation to urban aerosol composition is still not well understood. In the present study, PM10 and PM2.5 particulate matter was characterized at two different sites in the North African region of Morocco. A background site located at the newly established AM5 research station in the Middle Atlas region at an altitude of 2100 m and an urban site situated in a polluted city, Fez. The goal was to determine chemical components, evaluate Saharan dust&#8217;s role on the PM10 concentrations between the sites, and assess the impact of urban pollution on background aerosol composition. The results indicate that the background aerosol composition is influenced by both regional and trans-regional transport. Despite the site's proximity to the Sahara Desert, the deserts influence on the atmospheric composition was observed for only 22% of the time and this was mainly seasonal. Marine air masses were more dominant with a mixture of sea salt and polluted aerosol from the coastal regions especially during wintertime. Furthermore, high concentrations of mineral dust were observed during the daytime due to the resuspension of road dust. At the same time, an increase of PAHs and anthropogenic metals such as Pb, Ni, and Cu were found during the nighttime because of the boundary layer variation. The Fez's urban site is characterized by a high contribution of elemental carbon (6%) and organic biomass tracers (3%) such as Levoglucosane and 4-nitrophenol.

Download Full-text