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  • 1
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    Online Resource
    Methane emissions from a Californian landfill, determined from airborne remote sensing and in situ measurements
    Copernicus GmbH ; 2017
    In:  Atmospheric Measurement Techniques Vol. 10, No. 9 ( 2017-09-20), p. 3429-3452
    Details
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 10, No. 9 ( 2017-09-20), p. 3429-3452
    Abstract: Abstract. Fugitive emissions from waste disposal sites are important anthropogenic sources of the greenhouse gas methane (CH4). As a result of the growing world population and the recognition of the need to control greenhouse gas emissions, this anthropogenic source of CH4 has received much recent attention. However, the accurate assessment of the CH4 emissions from landfills by modeling and existing measurement techniques is challenging. This is because of inaccurate knowledge of the model parameters and the extent of and limited accessibility to landfill sites. This results in a large uncertainty in our knowledge of the emissions of CH4 from landfills and waste management. In this study, we present results derived from data collected during the research campaign COMEX (CO2 and MEthane eXperiment) in late summer 2014 in the Los Angeles (LA) Basin. One objective of COMEX, which comprised aircraft observations of methane by the remote sensing Methane Airborne MAPper (MAMAP) instrument and a Picarro greenhouse gas in situ analyzer, was the quantitative investigation of CH4 emissions. Enhanced CH4 concentrations or CH4 plumes were detected downwind of landfills by remote sensing aircraft surveys. Subsequent to each remote sensing survey, the detected plume was sampled within the atmospheric boundary layer by in situ measurements of atmospheric parameters such as wind information and dry gas mixing ratios of CH4 and carbon dioxide (CO2) from the same aircraft. This was undertaken to facilitate the independent estimation of the surface fluxes for the validation of the remote sensing estimates. During the COMEX campaign, four landfills in the LA Basin were surveyed. One landfill repeatedly showed a clear emission plume. This landfill, the Olinda Alpha Landfill, was investigated on 4 days during the last week of August and first days of September 2014. Emissions were estimated for all days using a mass balance approach. The derived emissions vary between 11.6 and 17.8 kt CH4 yr−1 with related uncertainties in the range of 14 to 45 %. The comparison of the remote sensing and in situ based CH4 emission rate estimates reveals good agreement within the error bars with an average of the absolute differences of around 2.4 kt CH4 yr−1 (±2. 8 kt CH4 yr−1). The US Environmental Protection Agency (EPA) reported inventory value is 11.5 kt CH4 yr−1 for 2014, on average 2.8 kt CH4 yr−1 (±1. 6 kt CH4 yr−1) lower than our estimates acquired in the afternoon in late summer 2014. This difference may in part be explained by a possible leak located on the southwestern slope of the landfill, which we identified in the observations of the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) instrument, flown contemporaneously aboard a second aircraft on 1 day.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    URL: Article
    URL: Article
    DOI: 10.5194/amt-10-3429-2017
    DOI: 10.5194/amt-10-3429-2017-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2505596-3
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  • 2
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    Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm
    Copernicus GmbH ; 2022
    In:  Atmospheric Measurement Techniques Vol. 15, No. 11 ( 2022-06-09), p. 3401-3437
    Details
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 15, No. 11 ( 2022-06-09), p. 3401-3437
    Abstract: Abstract. We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    URL: Article
    DOI: 10.5194/amt-15-3401-2022
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2505596-3
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  • 3
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    DataSheet1.PDF
    Frontiers Media SA ; 2022
    In:  Frontiers in Remote Sensing Vol. 3 ( 2022-5-11)
    Details
    In: Frontiers in Remote Sensing, Frontiers Media SA, Vol. 3 ( 2022-5-11)
    Abstract: The European Copernicus programme plans to install a constellation of multiple polar orbiting satellites (Copernicus Anthropogenic CO 2 Monitoring Mission, CO2M mission) for observing atmospheric CO 2 content with the aim to estimate fossil fuel CO 2 emissions. We explore the impact of potential CO2M observations of column-averaged CO 2 (XCO 2 ), nitrogen dioxide (NO 2 ), and aerosols in a 200 × 200 km 2 domain around Berlin. For the quantification of anticipated XCO 2 random and systematic errors we developed and applied new error parameterisation formulae based on artificial neural networks. For the interpretation of these data, we further established a CCFFDAS modelling chain from parameters of emission models to XCO 2 and NO 2 observations to simulate the 24 h periods preceeding simulated CO2M overpasses over the study area. For one overpass in winter and one in summer, we present a number of assessments of observation impact in terms of the posterior uncertainty in fossil fuel emissions on scales ranging from 2 to 200 km. This means the assessments include temporal and spatial scales typically not covered by inventories. The assessments differentiate the fossil fuel CO 2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector.” We find that combined measurements of XCO 2 and aerosols provide a powerful constraint on emissions from larger power plants; the uncertainty in fossil fuel emissions from the largest three power plants in the domain was reduced by 60%–90% after assimilating the observations. Likewise, these measurements achieve an uncertainty reduction for the other sector that increases when aggregated to larger spatial scales. When aggregated over Berlin the uncertainty reduction for the other sector varies between 28% and 48%. Our assessments show a considerable contribution of aerosol observations onboard CO2M to the constraint of the XCO 2 measurements on emissions from all power plants and for the other sector on all spatial scales. NO 2 measurements onboard CO2M provide a powerful additional constraint on the emissions from power plants and from the other sector. We further apply a Jacobian representation of the CCFFDAS modelling chain to decompose a simulated CO 2 column in terms of spatial emission impact. This analysis reveals the complex structure of the footprint of an observed CO 2 column, which indicates the limits of simple mass balances approaches for interpretation of such observations.
    Type of Medium: Online Resource
    ISSN: 2673-6187
    URL: Article
    URL: Article
    DOI: 10.3389/frsen.2022.887456
    DOI: 10.3389/frsen.2022.887456.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 3091289-1
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  • 4
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    XCO〈sub〉2〈/sub〉 retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm
    Copernicus GmbH ; 2021
    In:  Atmospheric Measurement Techniques Vol. 14, No. 5 ( 2021-05-26), p. 3837-3869
    Details
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 14, No. 5 ( 2021-05-26), p. 3837-3869
    Abstract: Abstract. Since 2009, the Greenhouse gases Observing SATellite (GOSAT) has performed radiance measurements in the near-infrared (NIR) and shortwave infrared (SWIR) spectral region. From February 2019 onward, data from GOSAT-2 have also been available. We present the first results from the application of the Fast atmOspheric traCe gAs retrievaL (FOCAL) algorithm to derive column-averaged dry-air mole fractions of carbon dioxide (XCO2) from GOSAT and GOSAT-2 radiances and their validation. FOCAL was initially developed for OCO-2 XCO2 retrievals and allows simultaneous retrievals of several gases over both land and ocean. Because FOCAL is accurate and numerically very fast, it is currently being considered as a candidate algorithm for the forthcoming European anthropogenic CO2 Monitoring (CO2M) mission to be launched in 2025. We present the adaptation of FOCAL to GOSAT and discuss the changes made and GOSAT specific additions. This particularly includes modifications in pre-processing (e.g. cloud detection) and post-processing (bias correction and filtering). A feature of the new application of FOCAL to GOSAT and GOSAT-2 is the independent use of both S- and P-polarisation spectra in the retrieval. This is not possible for OCO-2, which measures only one polarisation direction. Additionally, we make use of GOSAT's wider spectral coverage compared to OCO-2 and derive not only XCO2, water vapour (H2O), and solar-induced fluorescence (SIF) but also methane (XCH4), with the potential for further atmospheric constituents and parameters like semi-heavy water vapour (HDO). In the case of GOSAT-2, the retrieval of nitrous oxide (XN2O) and carbon monoxide (CO) may also be possible. Here, we concentrate on the new FOCAL XCO2 data products. We describe the generation of the products as well as applied filtering and bias correction procedures. GOSAT-FOCAL XCO2 data have been produced for the time interval 2009 to 2019. Comparisons with other independent GOSAT data sets reveal agreement of long-term temporal variations within about 1 ppm over 1 decade; differences in seasonal variations of about 0.5 ppm are observed. Furthermore, we obtain a station-to-station bias of the new GOSAT-FOCAL product to the ground-based Total Carbon Column Observing Network (TCCON) of 0.56 ppm with a mean scatter of 1.89 ppm. The GOSAT-2-FOCAL XCO2 product is generated in a similar way as the GOSAT-FOCAL product, but with adapted settings. All GOSAT-2 data until the end of 2019 have been processed. Because of this limited time interval, the GOSAT-2 results are considered to be preliminary only, but first comparisons show that these data compare well with the GOSAT-FOCAL results and also TCCON.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    URL: Article
    DOI: 10.5194/amt-14-3837-2021
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2505596-3
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  • 5
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    Assimilation of atmospheric CO 2 observations from space can support national CO 2 emission inventories
    IOP Publishing ; 2022
    In:  Environmental Research Letters Vol. 17, No. 1 ( 2022-01-01), p. 014015-
    Details
    In: Environmental Research Letters, IOP Publishing, Vol. 17, No. 1 ( 2022-01-01), p. 014015-
    Abstract: The Paris Agreement establishes a transparency framework for anthropogenic carbon dioxide (CO 2 ) emissions. It’s core component are inventory-based national greenhouse gas emission reports, which are complemented by independent estimates derived from atmospheric CO 2 measurements combined with inverse modelling. It is, however, not known whether such a Monitoring and Verification Support (MVS) capacity is capable of constraining estimates of fossil-fuel emissions to an extent that is sufficient to provide valuable additional information. The CO 2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO 2 concentration (XCO 2 ), is expected to become a key component of such an MVS capacity. Here we provide a novel assessment of the potential of a comprehensive data assimilation system using simulated XCO 2 and other observations to constrain fossil fuel CO 2 emission estimates for an exemplary 1-week period in 2008. We find that CO2M enables useful weekly estimates of country-scale fossil fuel emissions independent of national inventories. When extrapolated from the weekly to the annual scale, uncertainties in emissions are comparable to uncertainties in inventories, so that estimates from inventories and from the MVS capacity can be used for mutual verification. We further demonstrate an alternative, synergistic mode of operation, with the purpose of delivering a best fossil fuel emission estimate. In this mode, the assimilation system uses not only XCO 2 and the other data streams of the previous (verification) mode, but also the inventory information. Finally, we identify further steps towards an operational MVS capacity.
    Type of Medium: Online Resource
    ISSN: 1748-9326
    URL: Article
    DOI: 10.1088/1748-9326/ac3cea
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2255379-4
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  • 6
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    Ability of the 4-D-Var analysis of the GOSAT BESD XCO〈sub〉2〈/sub〉 retrievals to characterize atmospheric CO〈sub〉2〈/sub〉 at large and synoptic scales
    Copernicus GmbH ; 2016
    In:  Atmospheric Chemistry and Physics Vol. 16, No. 3 ( 2016-02-12), p. 1653-1671
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 16, No. 3 ( 2016-02-12), p. 1653-1671
    Abstract: Abstract. This study presents results from the European Centre for Medium-Range Weather Forecasts (ECMWF) carbon dioxide (CO2) analysis system where the atmospheric CO2 is controlled through the assimilation of column-averaged dry-air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing Satellite (GOSAT). The analysis is compared to a free-run simulation (without assimilation of XCO2), and they are both evaluated against XCO2 data from the Total Carbon Column Observing Network (TCCON). We show that the assimilation of the GOSAT XCO2 product from the Bremen Optimal Estimation Differential Optical Absorption Spectroscopy (BESD) algorithm during the year 2013 provides XCO2 fields with an improved mean absolute error of 0.6 parts per million (ppm) and an improved station-to-station bias deviation of 0.7  ppm compared to the free run (1.1 and 1.4  ppm, respectively) and an improved estimated precision of 1  ppm compared to the GOSAT BESD data (3.3  ppm). We also show that the analysis has skill for synoptic situations in the vicinity of frontal systems, where the GOSAT retrievals are sparse due to cloud contamination. We finally computed the 10-day forecast from each analysis at 00:00  UTC, and we demonstrate that the CO2 forecast shows synoptic skill for the largest-scale weather patterns (of the order of 1000  km) even up to day 5 compared to its own analysis.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-16-1653-2016
    DOI: 10.5194/acp-16-1653-2016-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 7
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    Can a regional-scale reduction of atmospheric CO〈sub〉2〈/sub〉 during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO〈sub〉2〈/sub〉 retrievals
    Copernicus GmbH ; 2021
    In:  Atmospheric Measurement Techniques Vol. 14, No. 3 ( 2021-03-18), p. 2141-2166
    Details
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 14, No. 3 ( 2021-03-18), p. 2141-2166
    Abstract: Abstract. The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. To investigate whether a regional-scale reduction of anthropogenic CO2 emissions during the COVID-19 pandemic can be detected using space-based observations of atmospheric CO2, we have analysed a small ensemble of OCO-2 and GOSAT satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2. We focus on East China and use a simple data-driven analysis method. We present estimates of the relative change of East China monthly emissions in 2020 relative to previous periods, limiting the analysis to October-to-May periods to minimize the impact of biogenic CO2 fluxes. The ensemble mean indicates an emission reduction by approximately 10 % ± 10 % in March and April 2020. However, our results show considerable month-to-month variability and significant differences across the ensemble of satellite data products analysed. For example, OCO-2 suggests a much smaller reduction (∼ 1 %–2 % ± 2 %). This indicates that it is challenging to reliably detect and to accurately quantify the emission reduction with current satellite data sets. There are several reasons for this, including the sparseness of the satellite data but also the weak signal; the expected regional XCO2 reduction is only on the order of 0.1–0.2 ppm. Inferring COVID-19-related information on regional-scale CO2 emissions using current satellite XCO2 retrievals likely requires, if at all possible, a more sophisticated analysis method including detailed transport modelling and considering a priori information on anthropogenic and natural CO2 surface fluxes.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    URL: Article
    DOI: 10.5194/amt-14-2141-2021
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2505596-3
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  • 8
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    The Global Ozone Monitoring Experiment (GOME): Mission Concept and First Scientific Results
    American Meteorological Society ; 1999
    In:  Journal of the Atmospheric Sciences Vol. 56, No. 2 ( 1999-01), p. 151-175
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 56, No. 2 ( 1999-01), p. 151-175
    Type of Medium: Online Resource
    ISSN: 0022-4928 , 1520-0469
    URL: Article
    DOI: 10.1175/1520-0469(1999)056〈0151:TGOMEG〉2.0.CO;2
    RVK:
    UA 4800
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 1999
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 9
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    Space-based Earth observation in support of the UNFCCC Paris Agreement
    Frontiers Media SA ; 2022
    In:  Frontiers in Environmental Science Vol. 10 ( 2022-10-5)
    Details
    In: Frontiers in Environmental Science, Frontiers Media SA, Vol. 10 ( 2022-10-5)
    Abstract: Space-based Earth observation (EO), in the form of long-term climate data records, has been crucial in the monitoring and quantification of slow changes in the climate system—from accumulating greenhouse gases (GHGs) in the atmosphere, increasing surface temperatures, and melting sea-ice, glaciers and ice sheets, to rising sea-level. In addition to documenting a changing climate, EO is needed for effective policy making, implementation and monitoring, and ultimately to measure progress and achievements towards the overarching goals of the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement to combat climate change. The best approach for translating EO into actionable information for policymakers and other stakeholders is, however, far from clear. For example, climate change is now self-evident through increasingly intense and frequent extreme events—heatwaves, droughts, wildfires, and flooding—costing human lives and significant economic damage, even though single events do not constitute “climate”. EO can capture and visualize the impacts of such events in single images, and thus help quantify and ultimately manage them within the framework of the UNFCCC Paris Agreement, both at the national level (via the Enhanced Transparency Framework) and global level (via the Global Stocktake). We present a transdisciplinary perspective, across policy and science, and also theory and practice, that sheds light on the potential of EO to inform mitigation, including sinks and reservoirs of greenhouse gases, and adaptation, including loss and damage. Yet to be successful with this new mandate, EO science must undergo a radical overhaul: it must become more user-oriented, collaborative, and transdisciplinary; span the range from fiducial to contextual data; and embrace new technologies for data analysis (e.g., artificial intelligence). Only this will allow the creation of the knowledge base and actionable climate information needed to guide the UNFCCC Paris Agreement to a just and equitable success.
    Type of Medium: Online Resource
    ISSN: 2296-665X
    URL: Article
    DOI: 10.3389/fenvs.2022.941490
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2741535-1
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  • 10
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    Consistency of Satellite Climate Data Records for Earth System Monitoring
    American Meteorological Society ; 2020
    In:  Bulletin of the American Meteorological Society Vol. 101, No. 11 ( 2020-11-01), p. E1948-E1971
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 101, No. 11 ( 2020-11-01), p. E1948-E1971
    Abstract: Climate data records (CDRs) of essential climate variables (ECVs) as defined by the Global Climate Observing System (GCOS) derived from satellite instruments help to characterize the main components of the Earth system, to identify the state and evolution of its processes, and to constrain the budgets of key cycles of water, carbon, and energy. The Climate Change Initiative (CCI) of the European Space Agency (ESA) coordinates the derivation of CDRs for 21 GCOS ECVs. The combined use of multiple ECVs for Earth system science applications requires consistency between and across their respective CDRs. As a comprehensive definition for multi-ECV consistency is missing so far, this study proposes defining consistency on three levels: 1) consistency in format and metadata to facilitate their synergetic use (technical level); 2) consistency in assumptions and auxiliary datasets to minimize incompatibilities among datasets (retrieval level); and 3) consistency between combined or multiple CDRs within their estimated uncertainties or physical constraints (scientific level). Analyzing consistency between CDRs of multiple quantities is a challenging task and requires coordination between different observational communities, which is facilitated by the CCI program. The interdependencies of the satellite-based CDRs derived within the CCI program are analyzed to identify where consistency considerations are most important. The study also summarizes measures taken in CCI to ensure consistency on the technical level, and develops a concept for assessing consistency on the retrieval and scientific levels in the light of underlying physical knowledge. Finally, this study presents the current status of consistency between the CCI CDRs and future efforts needed to further improve it.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-19-0127.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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