Found 2696 publications. Showing page 50 of 270:
This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.
2021
Information Requirements under the Essential-Use Concept: PFAS Case Studies
Per- and polyfluoroalkyl substances (PFAS) are a class of substances for which there are widespread concerns about their extreme persistence in combination with toxic effects. It has been argued that PFAS should only be employed in those uses that are necessary for health or safety or are critical for the functioning of society and where no alternatives are available (“essential-use concept”). Implementing the essential-use concept requires a sufficient understanding of the current uses of PFAS and of the availability, suitability, and hazardous properties of alternatives. To illustrate the information requirements under the essential-use concept, we investigate seven different PFAS uses, three in consumer products and four industrial applications. We investigate how much information is available on the types and functions of PFAS in these uses, how much information is available on alternatives, their performance and hazardous properties and, finally, whether this information is sufficient as a basis for deciding on the essentiality of a PFAS use. The results show (i) the uses of PFAS are highly diverse and information on alternatives is often limited or lacking; (ii) PFAS in consumer products often are relatively easy to replace; (iii) PFAS uses in industrial processes can be highly complex and a thorough evaluation of the technical function of each PFAS and of the suitability of alternatives is needed; (iv) more coordination among PFAS manufacturers, manufacturers of alternatives to PFAS, users of these materials, government authorities, and other stakeholders is needed to make the process of phasing out PFAS more transparent and coherent.
2021
2021
Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.
2021
As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data are questioning the causality of this relationship.
Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow–NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west-to-east snow depth gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.
2021
Svalbard Integrated Arctic Earth Observing System (SIOS) is an international partnership of research institutions studying the environment and climate in and around Svalbard. SIOS is developing an efficient observing system, where researchers share technology, experience, and data, work together to close knowledge gaps, and decrease the environmental footprint of science. SIOS maintains and facilitates various scientific activities such as the State of the Environmental Science in Svalbard (SESS) report, international access to research infrastructure in Svalbard, Earth observation and remote sensing services, training courses for the Arctic science community, and open access to data. This perspective paper highlights the activities of SIOS Knowledge Centre, the central hub of SIOS, and the SIOS Remote Sensing Working Group (RSWG) in response to the unprecedented situation imposed by the global pandemic coronavirus (SARS-CoV-2) disease 2019 (COVID-19). The pandemic has affected Svalbard research in several ways. When Norway declared a nationwide lockdown to decrease the rate of spread of the COVID-19 in the community, even more strict measures were taken to protect the Svalbard community from the potential spread of the disease. Due to the lockdown, travel restrictions, and quarantine regulations declared by many nations, most physical meetings, training courses, conferences, and workshops worldwide were cancelled by the first week of March 2020. The resumption of physical scientific meetings is still uncertain in the foreseeable future. Additionally, field campaigns to polar regions, including Svalbard, were and remain severely affected. In response to this changing situation, SIOS initiated several operational activities suitable to mitigate the new challenges resulting from the pandemic. This article provides an extensive overview of SIOS’s Earth observation (EO), remote sensing (RS) and other operational activities strengthened and developed in response to COVID-19 to support the Svalbard scientific community in times of cancelled/postponed field campaigns in Svalbard. These include (1) an initiative to patch up field data (in situ) with RS observations, (2) a logistics sharing notice board for effective coordinating field activities in the pandemic times, (3) a monthly webinar series and panel discussion on EO talks, (4) an online conference on EO and RS, (5) the SIOS’s special issue in the Remote Sensing (MDPI) journal, (6) the conversion of a terrestrial remote sensing training course into an online edition, and (7) the announcement of opportunity (AO) in airborne remote sensing for filling the data gaps using aerial imagery and hyperspectral data. As SIOS is a consortium of 24 research institutions from 9 nations, this paper also presents an extensive overview of the activities from a few research institutes in pandemic times and highlights our upcoming activities for the next year 2021. Finally, we provide a critical perspective on our overall response, possible broader impacts, relevance to other observing systems, and future directions. We hope that our practical services, experiences, and activities implemented in these difficult times will motivate other similar monitoring programs and observing systems when responding to future challenging situations. With a broad scientific audience in mind, we present our perspective paper on activities in Svalbard as a case study.
Earth observation; Remote sensing; COVID-19; Svalbard; Earth System Science; SIOS
2021
Microfibers (MF) are one of the major classes of microplastic found in the marine environment on a global scale. Very little is known about how they move and distribute from point sources such as wastewater effluents into the ocean. We chose Adventfjorden near the settlement of Longyearbyen on the Arctic Svalbard archipelago as a case study to investigate how microfibers emitted with untreated wastewater will distribute in the fjord, both on a spatial and temporal scale. Fiber abundance in the effluent was estimated from wastewater samples taken during two one-week periods in June and September 2017. Large emissions of MFs were detected, similar in scale to a modern WWTP serving 1.3 million people and providing evidence of the importance of untreated wastewater from small settlements as major local sources for MF emissions in the Arctic. Fiber movement and distribution in the fjord mapped using an online-coupled hydrodynamic-drift model (FVCOM-FABM). For parameterizing a wider spectrum of fibers from synthetic to wool, four different density classes of MFs, i.e., buoyant, neutral, sinking, and fast sinking fibers are introduced to the modeling framework. The results clearly show that fiber class has a large impact on the fiber distributions. Light fibers remained in the surface layers and left the fjord quickly with outgoing currents, while heavy fibers mostly sank to the bottom and deposited in the inner parts of the fjord and along the northern shore. A number of accumulation sites were identified within the fjord. The southern shore, in contrast, was much less affected, with low fiber concentrations throughout the modeling period. Fiber distributions were then compared with published pelagic and benthic fauna distributions in different seasons at selected stations around the fjord. The ratios of fibers to organisms showed a very wide range, indicating hot spots of encounter risk for pelagic and benthic biota. This approach, in combination with in-situ ground-truthing, can be instrumental in understanding microplastic pathways and fate in fjord systems and coastal areas and help authorities develop monitoring and mitigation strategies for microfiber and microplastic pollution in their local waters.
2021
The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project
The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project aims at monitoring global-scale nitrous oxide (N2O) sources by retrieving N2O surface fluxes from the inversion of space-borne N2O measurements that are sensitive to the lowermost atmospheric layers under favorable conditions. MIN2OS will provide emission estimates of N2O at a horizontal resolution of 1° × 1° on the global scale and 10 × 10 km2 on the regional scale on a weekly to monthly basis depending on the application (e.g., agriculture, national inventories, policy, scientific research). Our novel approach is based on the development of: 1) a space-borne instrument operating in the Thermal InfraRed domain providing, in clear sky conditions, N2O mixing ratio in the lowermost atmosphere (900 hPa) under favorable conditions (summer daytime) over land and under favorable and unfavorable (winter nighttime) conditions over the ocean and 2) an atmospheric inversion framework to estimate N2O surface fluxes from the atmospheric satellite observations. After studying three N2O spectral bands (B1 at 1240–1350 cm−1, B2 at 2150–2260 cm−1 and B3 at 2400–2600 cm−1), a new TIR instrument will be developed, centered at 1250–1330 cm−1, with a resolution of 0.125 cm−1, a Full Width at Half Maximum of 0.25 cm−1 and a swath of 300 km. To optimally constrain the retrieval of N2O vertical profiles, the instrument will be on-board a platform at ~830 km altitude in a sun-synchronous orbit crossing the Equator in descending node at 09:30 local time in synergy with two other platforms (Metop-SG and Sentinel-2 NG) expected to fly in 2031–32 aiming at detecting surface properties, agricultural information on the field scale and vertical profiles of atmospheric constituents and temperature. The lifetime of the MIN2OS project would be 4–5 years to study the interannual variability of N2O surface fluxes. The spectral noise can be decreased by at least a factor of 5 compared to the lowest noise accessible to date with the Infrared Atmospheric Sounding Interferometer-New Generation (IASI-NG) mission. The N2O total error is expected to be less than ~1% (~3 ppbv) along the vertical. The preliminary design of the MIN2OS project results in a small instrument (payload of 90 kg, volume of 1200 × 600 × 300 mm3) with, in addition to the spectrometer, a wide field and 1-km resolution imager for cloud detection. The instruments could be hosted on a small platform, the whole satellite being largely compatible with a dual launch on VEGA-C. The MIN2OS project has been submitted to the European Space Agency Earth Explorer 11 mission ideas.
2021
Dimethyl Sulfide-Induced Increase in Cloud Condensation Nuclei in the Arctic Atmosphere
Oceanic dimethyl sulfide (DMS) emissions have been recognized as a biological regulator of climate by contributing to cloud formation. Despite decades of research, the climatic role of DMS remains ambiguous largely because of limited observational evidence for DMS-induced cloud condensation nuclei (CCN) enhancement. Here, we report concurrent measurement of DMS, physiochemical properties of aerosol particles, and CCN in the Arctic atmosphere during the phytoplankton bloom period of 2010. We encountered multiple episodes of new particle formation (NPF) and particle growth when DMS mixing ratios were both low and high. The growth of particles to sizes at which they can act as CCN accelerated in response to an increase in atmospheric DMS. Explicitly, the sequential increase in all relevant parameters (including the source rate of condensable vapor, the growth rate of particles, Aitken mode particles, hygroscopicity, and CCN) was pronounced at the DMS-derived NPF and particle growth events. This field study unequivocally demonstrates the previously unconfirmed roles of DMS in the growth of particles into climate-relevant size and eventual CCN activation.
2021
Integrated water vapor during rain and rain-free conditions above the Swiss Plateau
Water vapor column density, or vertically-integrated water vapor (IWV), is monitored by ground-based microwave radiometers (MWR) and ground-based receivers of the Global Navigation Satellite System (GNSS). For rain periods, the retrieval of IWV from GNSS Zenith Wet Delay (ZWD) neglects the atmospheric propagation delay of the GNSS signal by rain droplets. Similarly, it is difficult for ground-based dual-frequency single-polarisation microwave radiometers to separate the microwave emission of water vapor and cloud droplets from the rather strong microwave emission of rain. For ground-based microwave radiometry at Bern (Switzerland), we take the approach that IWV during rain is derived from linearly interpolated opacities before and after the rain period. The intermittent rain periods often appear as spikes in the time series of integrated liquid water (ILW) and are indicated by ILW ≥ 0.4 mm. In the present study, we assume that IWV measurements from radiosondes are not affected by rain. We intercompare the climatologies of IWV(rain), IWV(no rain), and IWV(all) obtained by radiosonde, ground-based GNSS atmosphere sounding, ground-based MWR, and ECMWF reanalysis (ERA5) at Payerne and Bern in Switzerland. In all seasons, IWV(rain) is 3.75 to 5.94 mm greater than IWV(no rain). The mean IWV differences between GNSS and radiosonde at Payerne are less than 0.26 mm. The datasets at Payerne show a better agreement than the datasets at Bern. However, the MWR at Bern agrees with the radiosonde at Payerne within 0.41 mm for IWV(rain) and 0.02 mm for IWV(no rain). Using the GNSS and rain gauge measurements at Payerne, we find that IWV(rain) increases with increase of the precipitation rate during summer as well as during winter. IWV(rain) above the Swiss Plateau is quite well estimated by GNSS and MWR though the standard retrievals are limited or hampered during rain periods.
2021