The Infrared Atmospheric Sounding Interferometer (IASI) forms the main infrared sounding component of the European Organisation for the Exploitation of Meteorological Satellites's (EUMETSAT's) Meteorological Operation (MetOp)-A satellite (Klaes et al. 2007), which was launched in October 2006. This article presents the results of the first 4 yr of the operational IASI mission. The performance of the instrument is shown to be exceptional in terms of calibration and stability. The quality of the data has allowed the rapid use of the observations in operational numerical weather prediction (NWP) and the development of new products for atmospheric chemistry and climate studies, some of which were unexpected before launch. The assimilation of IASI observations in NWP models provides a significant forecast impact; in most cases the impact has been shown to be at least as large as for any previous instrument. In atmospheric chemistry, global distributions of gases, such as ozone and carbon monoxide, can be produced in near–real time, and short-lived species, such as ammonia or methanol, can be mapped, allowing the identification of new sources. The data have also shown the ability to track the location and chemistry of gaseous plumes and particles associated with volcanic eruptions and fires, providing valuable data for air quality monitoring and aircraft safety. IASI also contributes to the establishment of robust long-term data records of several essential climate variables. The suite of products being developed from IASI continues to expand as the data are investigated, and further impacts are expected from increased use of the data in NWP and climate studies in the coming years. The instrument has set a high standard for future operational hyperspectral infrared sounders and has demonstrated that such instruments have a vital role in the global observing system.

Crowdsourcing is traditionally defined as obtaining data or information by enlisting the services of a (potentially large) number of people. However, due to recent innovations, this definition can now be expanded to include ‘and/or from a range of public sensors, typically connected via the Internet.’ A large and increasing amount of data is now being obtained from a huge variety of non‐traditional sources – from smart phone sensors to amateur weather stations to canvassing members of the public. Some disciplines (e.g. astrophysics, ecology) are already utilizing crowdsourcing techniques (e.g. citizen science initiatives, web 2.0 technology, low‐cost sensors), and while its value within the climate and atmospheric science disciplines is still relatively unexplored, it is beginning to show promise. However, important questions remain; this paper introduces and explores the wide‐range of current and prospective methods to crowdsource atmospheric data, investigates the quality of such data and examines its potential applications in the context of weather, climate and society. It is clear that crowdsourcing is already a valuable tool for engaging the public, and if appropriate validation and quality control procedures are adopted and implemented, it has much potential to provide a valuable source of high temporal and spatial resolution, real‐time data, especially in regions where few observations currently exist, thereby adding value to science, technology and society.

This paper describes the development of a new sampling and measurement method to infer methane flux using proxy measurements of CO2 concentration and wind data recorded by Unmanned Aerial Systems (UAS). The flux method described and trialed here is appropriate to the spatial scale of landfill sites and analogous greenhouse gas emission hotspots, making it an important new method for low-cost and rapid case study quantification of fluxes from currently uncertain (but highly important) greenhouse gas sources. We present a case study using these UAS-based measurements to derive instantaneous methane fluxes from a test landfill site in the north of England using a mass balance model tailored for UAS sampling and co-emitted CO2 concentration as a methane-emission proxy. Methane flux (and flux uncertainty) during two trials on 27 November 2014 and 5 March 2015, were found to be 0.140 kg s-1 (±61% at 1σ), and 0.050 kg s-1 (±54% at 1σ), respectively. Uncertainty contributing to the flux was dominated by ambient variability in the background (inflow) concentration (>40%) and wind speed (>10%); with instrumental error contributing only ∼1-2%. The approach described represents an important advance concerning the challenging problem of greenhouse gas hotspot flux calculation, and offers transferability to a wide range of analogous environments. This new measurement solution could add to a toolkit of approaches to better validate source-specific greenhouse emissions inventories - an important new requirement of the UNFCCC COP21 (Paris) climate change agreement.

Airborne and ground-based measurements of methane (CH₄), carbon dioxide (CO₂) and boundary layer thermodynamics were recorded over the Fennoscandian landscape (67–69.5° N, 20–28° E) in July 2012 as part of the MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) field campaign. Employing these airborne measurements and a simple boundary layer box model, net regional-scale (~ 100 km) fluxes were calculated to be 1.2 ± 0.5 mg CH₄ h⁻¹ m⁻² and −350 ± 143 mg CO₂ h⁻¹ m⁻². These airborne fluxes were found to be relatively consistent with seasonally averaged surface chamber (1.3 ± 1.0 mg CH₄ h⁻¹ m⁻²) and eddy covariance (1.3 ± 0.3 mg CH₄ h⁻¹ m⁻² and −309 ± 306 mg CO₂ h⁻¹ m⁻²) flux measurements in the local area. The internal consistency of the aircraft-derived fluxes across a wide swath of Fennoscandia coupled with an excellent statistical comparison with local seasonally averaged ground-based measurements demonstrates the potential scalability of such localised measurements to regional-scale representativeness. Comparisons were also made to longer-term regional CH₄ climatologies from the JULES (Joint UK Land Environment Simulator) and HYBRID8 land surface models within the area of the MAMM campaign. The average hourly emission flux output for the summer period (July–August) for the year 2012 was 0.084 mg CH₄ h⁻¹ m⁻² (minimum 0.0 and maximum 0.21 mg CH₄ h⁻¹ m⁻²) for the JULES model and 0.088 mg CH₄ h⁻¹ m⁻² (minimum 0.0008 and maximum 1.53 mg CH₄ h⁻¹ m⁻²) for HYBRID8. Based on these observations both models were found to significantly underestimate the CH₄ emission flux in this region, which was linked to the under-prediction of the wetland extents generated by the models.