Changing Arctic. Firm scientific evidence versus public interest in the issue.

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The global integrated world ocean assessment: linking observations to science and policy across multiple scales

In 2004, the United Nations (UN) General Assembly approved a Regular Process to report on the environmental, economic and social aspects of the world's ocean. The Regular Process for Global Reporting and Assessment of the State of the Marine Environment, including Socioeconomic Aspects produced the first global integrated assessment of the marine environment in December 2016 (known as the first World Ocean Assessment). The second assessment, to be delivered in December 2020, will build on the baselines included in the first assessment, with a focus on establishing trends in the marine environment with relevance to global reporting needs such as those associated with the UN Sustainable Development Goals. Central to the assessment process and its outputs are two components. First, is the utilization of ocean observation and monitoring outputs and research to temporally assess physical, chemical, biological, social, economic and cultural components of coastal and marine environments to establish their current state, impacts currently affecting coastal and marine environments, responses to those impacts and associated ongoing trends. Second, is the knowledge brokering of ocean observations and associated research to provide key information that can be utilized and applied to address management and policy needs at local, regional and global scales. Through identifying both knowledge gaps and capacity needs, the assessment process also provides direction to policy makers for the future development and deployment of sustained observation systems that are required for enhancing knowledge and supporting national aspirations associated with the sustainable development of coastal and marine ecosystems. Input from the ocean observation community, managers and policy makers is critical for ensuring that the vital information required for supporting the science policy interface objectives of the Regular Process is included in the assessment. This community white paper discusses developments in linking ocean observations and science with policy achieved as part of the assessment process, and those required for providing strategic linkages into the future.Agência financiadora - United Nations Division for Ocean Affairs and the Law of the Seainfo:eu-repo/semantics/publishedVersio

Comparison of atmospheric aerosol optical depths measured with different sun photometers in three regions of Spitsbergen Archipelago

Results of multiyear (2011-2017) aerosol monitoring were used to compare the spectral aerosol optical depths (AOD) of the atmosphere, measured with different sun photometers at three Arctic stations on Spitsbergen Archipelago: Hornsund, Barentsburg, Ny-Ålesund. In addition to agreement of data in three regions, we also found that AOD in Barentsburg slightly (comparable to error) exceeds those from other stations located 110-120 km away. The AOD discrepancy is more pronounced in the shortwave part of the spectrum, indicating more abundant fine-mode aerosol in Barentsburg

Study of chemical and optical properties of biomass burning aerosols during long-range transport events toward the arctic in Summer 2017

Producción CientíficaBiomass burning related aerosol episodes are becoming a serious threat to the radiative balance of the Arctic region. Since early July 2017 intense wildfires were recorded between August and September in Canada and Greenland, covering an area up to 4674 km2 in size. This paper describes the impact of these biomass burning (BB) events measured over Svalbard, using an ensemble of ground-based, columnar, and vertically-resolved techniques. BB influenced the aerosol chemistry via nitrates and oxalates, which exhibited an increase in their concentrations in all of size fractions, indicating the BB origin of particles. The absorption coefficient data (530 nm) at ground reached values up to 0.6 Mm–1, highlighting the impact of these BB events when compared to average Arctic background values, which do not exceed 0.05 Mm–1. The absorption behavior is fundamental as implies a subsequent atmospheric heating. At the same time, the AERONET Aerosol Optical Depth (AOD) data showed high values at stations located close to or in Canada (AOD over 2.0). Similarly, increased values of AODs were then observed in Svalbard, e.g., in Hornsund (daily average AODs exceeded 0.14 and reached hourly values up to 0.5). Elevated values of AODs were then registered in Sodankylä and Andenes (daily average AODs exceeding 0.150) a few days after the Svalbard observation of the event highlighting the BB columnar magnitude, which is crucial for the radiative impact. All the reported data suggest to rank the summer 2017 plume of aerosols as one of the biggest atmosphere related environmental problems over Svalbard region in last 10 years

An Overview of Ocean Climate Change Indicators: Sea Surface Temperature, Ocean Heat Content, Ocean pH, Dissolved Oxygen Concentration, Arctic Sea Ice Extent, Thickness and Volume, Sea Level and Strength of the AMOC (Atlantic Meridional Overturning Circulation)

Global ocean physical and chemical trends are reviewed and updated using seven key ocean climate change indicators: (i) Sea Surface Temperature, (ii) Ocean Heat Content, (iii) Ocean pH, (iv) Dissolved Oxygen concentration (v) Arctic Sea Ice extent, thickness, and volume (vi) Sea Level and (vii) the strength of the Atlantic Meridional Overturning Circulation (AMOC). The globally averaged ocean surface temperature shows a mean warming trend of 0.062 ± 0.013 ºC per decade over the last 120 years (1900–2019). During the last decade (2010–2019) the rate of ocean surface warming has accelerated to 0.280 ± 0.068 ºC per decade, 4.5 times higher than the long term mean. Ocean Heat Content in the upper 2,000 m shows a linear warming rate of 0.35 ± 0.08 Wm-2 in the period 1955–2019 (65 years). The warming rate during the last decade (2010–2019) is twice (0.70 ± 0.07 Wm-2) the warming rate of the long term record. Each of the last six decades have been warmer than the previous one. Global surface ocean pH has declined on average by approximately 0.1 pH units (from 8.2 to 8.1) since the industrial revolution (1770). By the end of this century (2100) ocean pH is projected to decline additionally by 0.1-0.4 pH units depending on the RCP (Representative Concentration Pathway) and SSP (Shared Socioeconomic Pathways) future scenario. The time of emergence of the pH climate change signal varies from 8 to 15 years for open ocean sites, and 16-41 years for coastal sites. Global dissolved oxygen levels have decreased by 4.8 petamoles or 2% in the last 5 decades, with profound impacts on local and basin scale habitats. Regional trends are varying due to multiple processes impacting dissolved oxygen: solubility change, respiration changes, ocean circulation changes and multidecadal variability. Arctic sea ice extent has been declining by -13.1% per decade in summer (September) and by -2.6% per decade in winter (March) during the last 4 decades (1979–2020). The combined trends of sea ice extent and sea ice thickness indicate that the volume of non-seasonal Arctic Sea Ice has decreased by 75% since 1979. Global mean sea level has increased in the period 1993–2019 (the altimetry era) at a mean rate of 3.15 0.3 mm year-1 and is experiencing an acceleration of ~ 0.084 (0.06–0.10) mm year-2. During the last century (1900–2015; 115y) global mean sea level (GMSL) has rised 19 cm, and near 40% of that GMSL rise has taken place since 1993 (22y). Independent proxies of the evolution of the Atlantic Meridional Overturning Circulation (AMOC) indicate that AMOC is at its weakest for several hundreds of years and has been slowing down during the last century. A final visual summary of key ocean climate change indicators during the recent decades is provided.Versión del edito

Lidar-based Studies of Aerosol Optical Properties Over Coastal Areas

Aerosol size distribution and concentration strongly depend on wind speed,direction, and measuring point location in the marine boundary layer over coastal areas.The marine aerosol particles which are found over the sea waves in high wind conditionsaffect visible and near infrared propagation for paths that pass very close to the surface aswell as the remote sensing measurements of the sea surface. These particles are producedby various air sea interactions. This paper presents the results of measurements taken atnumerous coastal stations between 1992 and 2006 using an FLS-12 lidar system togetherwith other supporting instrumentation. The investigations demonstrated that near-waterlayers in coastal areas differ significantly from those over open seas both in terms ofstructure and physical properties. Taking into consideration the above mentioned factors,aerosol concentrations and optical properties were determined in the marine boundary layeras a function of offshore distance and altitude at various coastal sites in two seasons. Thelidar results show that the remote sensing algorithms used currently in coastal areas needverification and are not fully reliable

Lidar-based Studies of Aerosol Optical Properties Over Coastal Areas

Abstract: Aerosol size distribution and concentration strongly depend on wind speed, direction, and measuring point location in the marine boundary layer over coastal areas. The marine aerosol particles which are found over the sea waves in high wind conditions affect visible and near infrared propagation for paths that pass very close to the surface as well as the remote sensing measurements of the sea surface. These particles are produced by various air sea interactions. This paper presents the results of measurements taken at numerous coastal stations between 1992 and 2006 using an FLS-12 lidar system together with other supporting instrumentation. The investigations demonstrated that near-water layers in coastal areas differ significantly from those over open seas both in terms of structure and physical properties. Taking into consideration the above mentioned factors, aerosol concentrations and optical properties were determined in the marine boundary layer as a function of offshore distance and altitude at various coastal sites in two seasons. The lidar results show that the remote sensing algorithms used currently in coastal areas need verification and are not fully reliable

Aerosol optical properties over Svalbard: a comparison between Ny-Ålesund and Hornsund

This paper presents the CAMS model based aerosol optical properties calculated for two Spitsbergen fjords, Kongsfjorden (Ny-Ålesund) and Hornsund (Polish Polar Station in Hornsund) measured between 2010 and 2015. A small decrease in Aerosol Optical Depth (AOD) is shown throughout the study period leading to an alteration of the state of the polar atmosphere. However, the potential differences observed between the stations were not statistically significant. While during the studied period no significant differences in chemical composition between the stations were observed, increasing mean values of Black Carbon (BC) were found to be associated with an increasing number of wild forest fires in remote areas producing smoke plumes, which are further transported over vast distances and reach Spitsbergen

Deep Neural Networks for Aerosol Optical Depth Retrieval

Aerosol Optical Depth (AOD) is a measure of the extinction of solar radiation by aerosols in the atmosphere. Understanding the variations of global AOD is necessary for precisely determining the role of aerosols. Arctic warming is partially caused by aerosols transported from vast distances, including those released during biomass burning events (BBEs). However, measuring AODs is challenging, typically requiring active LIDAR systems or passive sun photometers. Both are limited to cloud-free conditions; sun photometers provide only point measurements, thus requiring more spatial coverage. A more viable method to obtain accurate AOD may be found through machine learning. This study uses DNNs to estimate Svalbard’s AODs using a minimal set of meteorological parameters (temperature, air mass, water vapor, wind speed, latitude, longitude, and time of year). The mean absolute error (MAE) between predicted and true data was 0.00401 for the entire set and 0.0079 for the validation set. It was then shown that the inclusion of BBE data improves predictions by 42.167%. It was demonstrated that AODs may be accurately estimated without the use of expensive instrumentation, using machine learning and minimal data. Similar models may be developed for other regions, allowing immediate improvement of current meteorological models