GI4.2

EDI
Open session on atmosphere, land and ocean monitoring

The Open Session on atmosphere, land and ocean monitoring aims at presenting highlights of recent results obtained through observations and modelling as well as relevant reviews in these fields.
We shall connect with Earth Observations programmes at ESA, EU and worldwide, using new satellites and oberving platforms, as well as new techniques for distributing, merging and analysing EO data using AI.

The session is intended as an open forum for interdisciplinary discussion between representatives of different fields. Thus, we welcome especially overarching presentations which may be interesting to a wider community.

Observations are one major link to get an overall picture of processes within the Earth environment during measurement campaigns. This includes application to derive atmospheric parameters, surface properties of vegetation, soil and minerals and dissolved or suspended matter in inland water and the ocean. Ground based systems and data sets from ships, aircraft and satellites are key information sources to complement the overall view. All of these systems have their pros and cons, but a comprehensive view of the observed system is generally best obtained by means of a combination of all of them.

The validation of operational satellite systems and applications is a topic that has come increasingly into focus with the European Copernicus program in recent years. The development of smaller state-of-the-art instruments, the combination of more and more complex sets of instruments simultaneously on one platform, with improved accuracy and high data acquisition speed together with high accuracy navigation and inertial measurements enables more complex campaign strategies even on smaller aircraft or unmanned aerial vehicles (UAV).

This session will bring together a multidisciplinary research community to present:

• Atmosphere-land-ocean (or inland water) system modelling and validation
• new instruments (Lidar, etc), platforms (UAV etc.), setups and use in multidisciplinary approaches
• Larger scale in-situ and remote sensing observation networks from various platforms (ground based, airborne, ship-borne, satellite)
• recent field campaigns and their outcomes
• (multi-) aircraft campaigns
• satellite calibration/validation campaigns
• sophisticated instrument setups and observations
• advanced instrument developments
• UAV applications

Co-organized by AS5/OS1
Convener: Bernard Foing | Co-convener: Paola FormentiECSECS
Presentations
| Fri, 27 May, 10:20–11:48 (CEST)
 
Room 0.51

Presentations: Fri, 27 May | Room 0.51

Chairpersons: Bernard Foing, Paola Formenti
10:20–10:25
10:25–10:35
|
EGU22-2203
|
ECS
|
solicited
|
Highlight
|
On-site presentation
Birgit Schlager, Thomas Goelles, Stefan Muckenhuber, Tobias Hammer, Kim Senger, Rüdiger Engel, Christian Bobrich, and Daniel Watzenig

We enable exciting and novel mapping and monitoring use cases for automotive lidar technologies in the Arctic. Originally, these lidar technologies were developed for enabling environment perception of automated vehicles with high spatial resolution and accuracy. Therefore, these lidar sensors have several advantages for mobile mapping applications in the Arctic compared to commonly used technologies like time-lapse cameras and satellite or aerial photogrammetry that suffer from lower accuracy of 3-dimensional (3D) data than the proposed automotive lidar sensors. At present, terrestrial laser scanners (TLS), like the Riegl VZ-6000, are commonly used in the Arctic. However, especially for mobile use cases, the automotive lidar provides a lot of advantages compared to TLS, for instance lower cost, more robust, smaller, and lighter and thus more portable. Therefore, automotive lidar sensors open the door for new mobile mapping and monitoring applications in the Arctic.

The data acquisition hardware consists of a sensor unit, a data logger, and batteries. The sensor unit integrates an automotive lidar, the Ouster OS1-64 Gen1, a ublox multi-band active global navigation satellite system (GNSS) antenna, and a Xsens 9-axis inertial measurement unit (IMU) with a gyroscope, an accelerometer, and a magnetometer. Furthermore, a long-term evolution (LTE) stick is integrated for retrieving real time kinematic (RTK) data. In a post-processing step, collected point clouds and IMU data can be used by a simultaneous localization and mapping (SLAM) algorithm for point cloud stitching with one big point cloud and the trajectory of the mapping sensor as a result, i.e., a map of the scanned environment. Optionally, the differential global positioning system (DGPS) data can be used additionally by the SLAM algorithm. The setup can be mounted in multiple ways to support a wide variety of new applications, e.g., on a handle, car, ship, or snowmobile.

We used the introduced setup for several applications and successfully mapped glacier caves and surrounding glacier surfaces on Longyearbreen and Larsbreen in Svalbard as one example of a novel Arctic use case. Furthermore, we showed that the setup is working on a ship scanning a harbor in Croatia. In this measurement campaign, we used a multi-beam sonar from Furuno in addition to our mapping setup which made it possible to map the coast above and below the water surface.

Therefore, we suggest several new applications of automotive lidar sensors in the Arctic, e.g., monitoring coastal erosions due to permafrost thawing and mapping glacier fronts. In this way, accurate outlines and structures of coasts and calving glacier fronts can be generated. Such data will be relevant for future development of glacier calving models. Furthermore, the setup can be used for monitoring glacier fronts over a period of several years. Further research may also include merging the gained 3D map with photogrammetry data to generate highly accurate 3D models of a glacier front with textural details. Another novel Arctic use case could be time-lapse scans of infrastructure, e.g., runway, roads, or cultural heritage, that is affected by the thawing permafrost to track its changes and movements cost-effectively.

How to cite: Schlager, B., Goelles, T., Muckenhuber, S., Hammer, T., Senger, K., Engel, R., Bobrich, C., and Watzenig, D.: Automotive lidar in the Arctic: 3D monitoring and mapping, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2203, https://doi.org/10.5194/egusphere-egu22-2203, 2022.

10:35–10:42
|
EGU22-2948
|
On-site presentation
Assessing ExxonMobil’s global warming projections
(withdrawn)
Geoffrey Supran, Naomi Oreskes, and Stefan Rahmstorf
10:42–10:49
|
EGU22-7738
|
Virtual presentation
Gabriela Schaepman-Strub, Heidemarie Kassens, Samuel L. Jaccard, and Mikhail Makhotin and the Arctic Century science team

The region of the Kara and Laptev Seas in the Russian Arctic has been experiencing one of the highest warming rates globally during past decades. From 5 August – 6 September 2021, the Arctic Century science team gathered unique data during a research expedition, along marine transects and on seven high Arctic islands that are very rarely accessible. The aim of the expedition is to contribute to the understanding of the dynamics and interactions between the ocean, cryosphere, land and atmosphere in the face of global change. Here we provide an overview of the main research topics and investigations performed, including: dynamics of Atlantic water masses; biodiversity and ecosystem productivity in the ocean and on high Arctic islands, at the margin of life; dynamics of the atmosphere and interactions with the ocean and land; past climate change and sea level history reconstruction based on sediment and ice cores; and amount and flow of macro- and microplastic in the ocean and along the shoreline. First analyses of samples and data are currently being performed by the expedition consortium. After an initial moratorium, the data will be made openly accessible to the wider science community.

How to cite: Schaepman-Strub, G., Kassens, H., Jaccard, S. L., and Makhotin, M. and the Arctic Century science team: Arctic Century 2021 – an interdisciplinary expedition to the Kara and Laptev Seas to study ocean, atmosphere and land processes in the changing Arctic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7738, https://doi.org/10.5194/egusphere-egu22-7738, 2022.

10:49–10:56
|
EGU22-10629
|
On-site presentation
Andrew Barna, Stephen Diggs, and Susan Becker

In this presentation, we will discuss the procedures and utilities employed that produced the final core data (CTDO, nutrients, salinity, and oxygen). These datasets were published within 4 weeks of the conclusion of the cruise, much quicker than the program's 6-week requirement for preliminary data, and significantly faster than the 6-month final data requirement.

The Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP) “provides approximately decadal resolution of the changes in inventories of heat, freshwater, carbon, oxygen, nutrients, and transient tracers, covering the ocean basins from coast to coast and full depth (top to bottom), with global measurements of the highest required accuracy to detect these changes.”

The Oceanographic Data Facility at Scripps Institution of Oceanography has been making the CTDO, salinity, oxygen, and nutrient measurements since the program's inception for some of the US lead GO-SHIP expeditions. This group internally shares personnel with the corresponding data repository (CCHDO). This collaboration allows the technicians to proactively develop tools and data formats that are both compliant for data submission as well as easy to utilize at sea. Mature versions of these utilities and procedures were promoted in both 1-on-1 conversations and interactive demonstrations.

The most recent set of measurements made by the US GO-SHIP program was in the Atlantic ocean last year (March-May 2021). Taking advantage of existing close collaborations within the shipboard environment, we were able to ensure measurements were documented while the expedition was still in progress, ensuring that data formats were consistent and conforming to the program's required formats. A full metadata package for the global/cross-cruise database, in addition to mature preliminary files, was ready at the conclusion of the expedition. The close relationship between the seagoing team and the data managers in the repository has allowed for the accelerated publication of finalized measurements through sharing of software, metadata databases, and expertise.

How to cite: Barna, A., Diggs, S., and Becker, S.: FAIR Data Teams: Rapid access to climate measurements by rethinking workflows, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10629, https://doi.org/10.5194/egusphere-egu22-10629, 2022.

10:56–11:03
|
EGU22-11656
|
ECS
|
On-site presentation
Eldho Elias, Dhanyalekshmi Pillai, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig

Studies have shown that the uncertainty of methane emission estimates over India is as high as 40-60%, largely due to the lack of observations. In India, measurements are limited to a few locations, with the majority of them being flask measurement stations. The observational constraint of the measurements could be greatly improved with the development of a network of continuous measurement stations at well-chosen locations. For this study, we have designed an atmospheric methane measurement network for India using transport modeling techniques and a scaling-factor-based inversion approach. A network optimization algorithm selects the combination of observation locations that gives the most uncertainty reduction in the estimates of posterior methane emission fluxes over India. The backbone of this study is a simple analytical inversion setup that utilizes the STILT (Stochastic Time Inverted Lagrangian Transport) model, a sectorial emission model based on EDGAR, as well as fluxes from wetlands and biomass burning. The state space of the inversion consists of monthly emissions, separated by sector, aggregated spatially to the level of political states.

The challenge in network design is to formulate an appropriate target quantity, which the network will be optimized to constrain. Using the annual total emissions as the single target results in a network that will optimally constrain the largest sources, irrespective of their spatial location or the seasonality of the source. Thus, we also included other targets, such as political-state-level emissions, sectoral emissions, and seasonality. For the study, we used a base network of existing stations (“base”) and added further stations from a candidate set (“extended”) on the basis of the incremental uncertainty reduction they provide. We found that more measurement stations along the Indo-Gangetic Plains and North-Eastern India are required. An optimized network was also designed from scratch using the same strategy and it was found to yield similar uncertainty reduction compared to the “base” + “extended” network despite having fewer stations. The effectiveness of the optimal network and the base network in reducing the uncertainties of the different emission categories is assessed and discussed.

How to cite: Elias, E., Pillai, D., Marshall, J., Totsche, K. U., and Gerbig, C.: Network Design for a Cost-Effective Atmospheric Methane Measurement Network over India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11656, https://doi.org/10.5194/egusphere-egu22-11656, 2022.

11:03–11:10
|
EGU22-744
|
Virtual presentation
Ho Seuk Bae, Su-Uk Son, Hyoung Rok Kim, Woo-Shik Kim, and Joung Soo Park

In the seawater environment, interactions of the rotation of ship propellers with the wind tend to produce masses of localized bubbles. These bubble clouds cause acoustical interference in the acquisition of sonar data during marine surveys and marine exploration. For example, pronounced bubble-attenuation of pressure levels results in acoustic signals received by sonar equipment being below predicted values. In addition, a strong backscattering signal may be detected due to the impedance difference between liquid water and intra-bubble air. These effects distort underwater sonar measurement data. If the acoustic characteristics of a bubble cloud in the seawater environment can be known in advance, more precise measurement data could be obtained through data processing. Thus, the aim of this study was to assess the acoustic characteristics of experimenter-produced bubbles. Acoustic tomography techniques were used to obtain data descriptive of the acoustic characteristics and distribution of bubble clouds. We developed six sets of buoy systems equipped with multiple projectors and hydrophones for acoustic tomography. The buoy systems were installed in a hexagonal arrangement in seawater. A transmitter emitted sequential sound signals into the water in response to radiofrequency-transmitted commands from a control device located on land. Each acoustic signal was recorded by multiple hydrophones. Applying repetitive optimization techniques to the tomography data, it was possible to analyze acoustic characteristics such as transmission loss of signals transmitted through bubble clouds, magnitude of backscattering associated with bubble clouds, and bubble distributions. The acoustic effects and distribution characteristics of bubbles documented in this experiment will be used as foundational data for subsequent research.

How to cite: Bae, H. S., Son, S.-U., Kim, H. R., Kim, W.-S., and Park, J. S.: Acoustic tomography assessment of the acoustic characteristics of bubble clouds, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-744, https://doi.org/10.5194/egusphere-egu22-744, 2022.

11:10–11:17
|
EGU22-4615
|
On-site presentation
Morten Hundt, Maria Timofeeva, and Oleg Aseev

Air pollutants and greenhouse gases (GHG) can be attributed to a variety of sources, such as transportation vehicles and buildings, waste management and agricultural production, natural events such as forest fires and many others. Simultaneous monitoring of air pollutants and GHG with high selectivity and sensitivity enables to detect and evaluate their sources and sinks. Air pollution modelling and validation of emission inventories or satellite observations require measurements at various spatial and temporal scales. 

Infrared laser (IR) absorption spectroscopy offers an efficient way to determine fingerprints of various gas species in monitored air with high precision and reliability. In the past, this technology was commonly used in “one-species-one-instrument” solutions due to limited coverage of used mid-IR distributed feedback quantum cascade lasers (DFB-QCLs). We provide a new compact laser absorption spectrometer that combines several mid-IR lasers. Our solution allows simultaneous high precision measurements of the greenhouse gases CO2, N2O, H2O and CH4, and the pollutants CO, NO, NO2, O3, SO2 and NH3 within a single instrument.

In our contribution we will demonstrate examples of our instruments’ applications for mobile monitoring of 10 GHG and air pollutants in urban areas, airborne measurements with airships and measurements at low pollution background stations. Furthermore, we will present the results of parallel monitoring with our instrument and standard conventional gas analysers used for GHG and air pollutant measurements. It demonstrates the ability of our instrument to serve as all-in-one solution and to replace up to 7 standard gas analysers opening a wide range of new mobile multi-compound gas monitoring applications for example in (small) airplanes or cars.

How to cite: Hundt, M., Timofeeva, M., and Aseev, O.: Simultaneous monitoring of greenhouse gases and air pollutants in a single instrument, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4615, https://doi.org/10.5194/egusphere-egu22-4615, 2022.

11:17–11:24
|
EGU22-10605
|
ECS
|
Virtual presentation
Mikhail Borisov and Mikhail Krinitskiy

The sun is the closest natural source of radiation, both shortwave and longwave. The state of the atmosphere, and in particular the Total Cloud Cover (TCC) and the Lower Cloud Cover (LCC), most strongly affects the transfer of incoming solar radiation to the surface. At the moment, the amount and types of clouds are assessed primarily by an expert using visual observation, and such an assessment is considered reliable according to WMO observations guide. However, it is known that the estimates of an observer are subject to errors due to the subjectivity of perception of the visual cloudy scene. Uncertainty in observer estimates may lead to significant inaccuracies in operational weather forecast systems as well as in reanalyses and climatic time series. In addition, the lack of knowledge about the observation error limits one in assessing the corresponding uncertainty of the climatic trends of cloudiness characteristics. In this study, we investigated the uncertainty in the estimates of the TCC, LCC.

To carry out such a study, we conducted an experiment involving the simultaneous observation of the same cloudy situation by several observers. The experiment was carried out on board the Akademik Ioffe research vessel during the AI-58 research cruise from August 18 till September 6 of 2021 in Kara, Baltic and White Seas. The experiment involved 19 volulntary participants. There were 78 observation moments. The number of observers varied from 5 to 19 due to their own duties onboard. On average, the cloud characteristics were assessed by 12 participants.

Thus, in the present study, the uncertainties of cloud characteristics estimated by one forgetful independent observer several times in equivalent conditions were simulated with a large number of experts participating in synchronous observations. We demonstrate that the disparity of opinions is small for simple cloudy situations in which the sky is almost clear or mostly covered by clouds. We also show that the uncertainty in the conditions of moderate cloudiness can reach 1.5 oktas in terms of standard deviation.

This study may help clarifying existing and future models for assessing meteorological characteristics, as well as models used to calculate incoming solar radiation. We plan to assess the uncertainty of cloud types observed by human experts. We will also repeat our experiment in other regions of the World Ocean in order to expand the variety of observed cloud situations, in which a wider range of expert opinions can be expected, as well as to form a dataset balanced w.r.t. synoptic conditions.

How to cite: Borisov, M. and Krinitskiy, M.: Assessing the uncertainty of expert observations of cloud characteristics based on data from a field campaign in the Arctic ocean in August-September 2021, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10605, https://doi.org/10.5194/egusphere-egu22-10605, 2022.

11:24–11:31
|
EGU22-11921
|
Highlight
|
On-site presentation
Cesar Gonzalez-Pola, Francisco Sánchez, Luis Rodriguez Cobo, Rocío Graña, Juan Manuel Rodriguez, Jose Valdiande-Gutierrez, Daniel Hernandez-Urbieta, and Eneko Aierbe

Landers are modular structures equipped with miscellaneous sensors and monitoring equipment which are positioned directly on the seabed to operate autonomously for a defined timeframe. A drawback of landers intended to operate for prolonged periods in the deep ocean is the high cost of recovery systems, typically depending on buoyancy modules plus expendable ballast, or requiring ROVs assistance. LanderPick concept consists of the design of a specific trawled vehicle to deploy and recover lightweight oceanographic landers not provided with recovery elements, but having a capture mesh that facilitates their hitching. The LanderPick vehicle is technically a ROTV (Remote Operated Trawled Vehicle) controlled through a standard coaxial electromechanical cable that allows real-time control from the vessel. Navigation is enabled by a low-light high-definition camera, aided by spotlights and laser pointers. Small propellers aid in the final precision approach maneuvers. A mechanical release allows the precise placement at the sea bottom of landers carried as a payload, as well as their recovery by means of a triple hook. First sea missions of the system were carried out successfully in 2021 in southern Biscay. A 4-month deployment of a lander array equipped with current-meters along an energetic canyon axis provided unprecedented detail in the progression of the internal tidal bore. Short (48-hours) deployments of a fully-instrumented lander, including lapse-time image and baits in a deep seamount summit within a marine protected area, provided insights on the biodiversity of a unique ecosystem. The LanderPick novel approach to cost-effectively and precisely deploy and recover lightweight oceanographic landers allows to conceive (i) monitoring systems based on the deployment of arrays or fleets of low-cost landers and (ii) experiments associated with deep habitats such as coral reefs in which it is necessary to locate landers with great precision.

How to cite: Gonzalez-Pola, C., Sánchez, F., Rodriguez Cobo, L., Graña, R., Rodriguez, J. M., Valdiande-Gutierrez, J., Hernandez-Urbieta, D., and Aierbe, E.: LanderPick, a Remote Operated Trawled Vehicle to cost-effectively deploy and recover lightweight oceanographic landers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11921, https://doi.org/10.5194/egusphere-egu22-11921, 2022.

11:31–11:38
|
EGU22-12931
|
ECS
|
Presentation form not yet defined
Jing Zhao, Guoqing Li, and Zefeng Li

Since initiated by the Chinese Academy of Sciences (CAS) and the National Earth Observation Data Center (NODA) of China, Cooperation on Reanalysis of Carbon Satellite Data (CASA) had already advanced to the second stage. China aims to hit peak emissions before 2030 and for carbon neutrality by 2060.Carbon neutrality research involves Terrestrial-Marine-Atmospheric multiple fields, which inevitably require the support of scientific big data and Scientific Data e-Infrastructure (SDI). Open space-borne carbon data interconnectivity and interoperability across the massive carbon data (GOSAT, GOSAT-2, OCO-2/3, TanSat, Sentinel-5P, FY-3D, GF-5 and the second generation carbon satellites) and related auxiliary data resources integrated into the CASA platform is a key enabler to become more data-driven, to broader data value, and to meet the major demand of global and regional monitoring of anthropogenic carbon emissions. This study explores the technological barriers for carbon satellite data interconnectivity, discusses the concepts of carbon data interoperability and integration, management and governance in more detail, highlight some useful tools, and demonstrate examples in urban air pollution and CO2 emissions that can help researchers in their application studies upon estimation of anthropogenic carbon emissions based on “top-down” methods. We linked carbon data connection and interoperability both to carbon data collection and use within programmatic cycles and reflected interoperability both in organizational practices and data management plans that cover the full breadth of the data value chain. This will extend carbon data information service and provide better ways to utilizing carbon data across domains where innovation and integration are now necessarily needed.

How to cite: Zhao, J., Li, G., and Li, Z.: A carbon data integrating system supporting Carbon neutrality, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12931, https://doi.org/10.5194/egusphere-egu22-12931, 2022.

11:38–11:48