• Energy Research

Existing descriptions of bi-directional ammonia (NH 3 ) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH 3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH 3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH 3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH 3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH 3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100.

Atmospheric ozone is an Essential Climate Variable (ECV) monitored in the framework of the Global Climate Observing System (GCOS), among others due to its impact on the radiation budget of the Earth, its chemical influence on other radiatively active species, and its role in atmospheric dynamics and climate. Its corresponding importance in the context of climate change has led ECMWF to set up a dedicated procurement of state-of-the-art ozone Climate Data Records (CDRs) to the Climate Data Store of the Copernicus Climate Change Service (C3S), mainly in the form of level-3/4 gridded data products. In support, ESA ensures further improvements of the underlying level-2 ozone data products and the development of new ozone CDRs and valued added data through its Climate Change Initiative on ozone (Ozone_cci+ project). In order to confirm the fitness-for-purpose of the datasets available to the public through the Copernicus CDS, a process has been established to monitor the data health, check compliance with GCOS requirements, and regularly report key performance indicators. This presentation summarizes the ground-based quality assessment and geophysical validation of the C3S ozone CDRs procured to the CDS in 2021. These CDRs consist of ozone column and vertical profile data at level-3 (monthly gridded) and level-4 (assimilated), from several nadir and limb/occultation satellite sounders, retrieval systems, and merging schemes (see details on C3S Climate Data Store at https://cds.climate.copernicus.eu/). The validation of these climate-oriented data records is based on multi-decade time series of correlative measurements collected from monitoring networks contributing to WMO’s Global Atmosphere Watch, such as GO3OS, NDACC, and SHADOZ. The correlative measurements are quality controlled, harmonized, and compared to the various satellite CDRs using BIRA-IASB’s Multi-TASTE versatile validation system, following the latest state-of-the-art protocols and tools. Validation studies focus in particular on the long-term stability of the satellite data series, which may exhibit cyclic errors, drifts, and other long-term patterns reflecting, e.g., instrumental drift and degradation, residual biases between different instruments, and changes in sampling of atmospheric variability and patterns. Comparison results document the achieved quality of the CDRs, in particular in terms of temporal stability: The total ozone column products, covering up to four decades, are found to be stable with respect to the reference measurements at the 0.1 % per decade level. Similarly, most nadir and limb profile CDRs achieve a level of stability that is consistent with what is expected from instrument specifications. Compliance is verified with respect to user requirements identified for GCOS, from WMO rolling review of requirements (RRR), and from the climate research community through the CCI Climate Modelling User Group, whose requirements can be more stringent and more specific.

Tropical cyclone (TC) detection is essential to mitigate natural disasters, as TCs can cause significant damage to life, infrastructure and economy. In this study, we applied the deep learning object detection model YOLOv3 to detect TCs in the North Atlantic Basin, using data from the Thermal InfraRed (TIR) Atmospheric Sounding Interferometer (IASI) onboard the Metop satellites. IASI measures the outgoing TIR radiation of the Earth-Atmosphere. For the first time, we provide a proof of concept of the possibility of constructing images required by YOLOv3 from a TIR remote sensor that is not an imager. We constructed a dataset by selecting 50 IASI radiance channels and using them to create images, which we labeled by constructing bounding boxes around TCs using the hurricane database HURDAT2. We trained the YOLOv3 on two settings, first with three “best” selected channels, then using an autoencoder to exploit all 50 channels. We assessed its performance with the Average Precision (AP) metric at two different intersection over union (IoU) thresholds (0.1 and 0.5). The model achieved promising results with AP at IoU threshold 0.1 of 78.31%. Lower performance was achieved with IoU threshold 0.5 (31.05%), showing the model lacks precision regarding the size and position of the predicted boxes. Despite that, we show YOLOv3 demonstrates great potential for TC detection using TIR instruments data.

AbstractArctic sea ice has decreased dramatically in the past few decades and the Arctic is increasingly open to transit shipping and natural resource extraction. However, large knowledge gaps exist regarding composition and impacts of emissions associated with these activities. Arctic hydrocarbon extraction is currently under development owing to the large oil and gas reserves in the region. Transit shipping through the Arctic as an alternative to the traditional shipping routes is currently underway. These activities are expected to increase emissions of air pollutants and climate forcers (e.g., aerosols, ozone) in the Arctic troposphere significantly in the future. The authors present the first measurements of these activities off the coast of Norway taken in summer 2012 as part of the European Arctic Climate Change, Economy, and Society (ACCESS) project. The objectives include quantifying the impact that anthropogenic activities will have on regional air pollution and understanding the connections to Arctic climate. Trace gas and aerosol concentrations in pollution plumes were measured, including emissions from different ship types and several offshore extraction facilities. Emissions originating from industrial activities (smelting) on the Kola Peninsula were also sampled. In addition, pollution plumes originating from Siberian biomass burning were probed in order to put the emerging local pollution within a broader context. In the near future these measurements will be combined with model simulations to quantify the influence of local anthropogenic activities on Arctic composition. Here the authors present the scientific objectives of the ACCESS aircraft experiment and the the meteorological conditions during the campaign, and they highlight first scientific results from the experiment.

AbstractTwo major droughts in the past decade had large impacts on carbon exchange in the Amazon. Recent analysis of vertical profile measurements of atmospheric CO2 and CO by Gatti et al. (2014) suggests that the 2010 drought turned the normally close‐to‐neutral annual Amazon carbon balance into a substantial source of nearly 0.5 PgC/yr, revealing a strong drought response. In this study, we revisit this hypothesis and interpret not only the same CO2/CO vertical profile measurements but also additional constraints on carbon exchange such as satellite observations of CO, burned area, and fire hot spots. The results from our CarbonTracker South America data assimilation system suggest that carbon uptake by vegetation was indeed reduced in 2010 but that the magnitude of the decrease strongly depends on the estimated 2010 and 2011 biomass burning emissions. We have used fire products based on burned area (Global Fire Emissions Database version 4), satellite‐observed CO columns (Infrared Atmospheric Sounding Interferometer), fire radiative power (Global Fire Assimilation System version 1), and fire hot spots (Fire Inventory from NCAR version 1), and found an increase in biomass burning emissions in 2010 compared to 2011 of 0.16 to 0.24 PgC/yr. We derived a decrease of biospheric uptake ranging from 0.08 to 0.26 PgC/yr, with the range determined from a set of alternative inversions using different biomass burning estimates. Our numerical analysis of the 2010 Amazon drought results in a total reduction of carbon uptake of 0.24 to 0.50 PgC/yr and turns the balance from carbon sink to source. Our findings support the suggestion that the hydrological cycle will be an important driver of future changes in Amazonian carbon exchange.