Explore the vast range of titles available.

Spotify provides a streaming service that has been welcomed as disrupting the world of music. Yet such disruption always comes at a price. This book contests the tired claim that digital culture thrives on disruption. Borrowing the notion of 'teardown' from reverse-engineering processes, a team of five researchers have playfully disassembled Spotify's product and the way it is commonly understood. Spotify has been hailed as the solution to illicit downloading, but it began as a partly illicit enterprise that grew out of the Swedish file-sharing community. Spotify was originally praised as an innovative digital platform but increasingly resembles a media company in need of regulation, raising questions about the ways in which such cultural content as songs, books, and films are now typically made available online. 'Spotify Teardown' combines interviews, participant observations, and other analyses of Spotify's 'front end' with experimental, covert investigations of its 'back end'. The authors engaged in a series of interventions, which include establishing a record label for research purposes, intercepting network traffic with packet sniffers, and web-scraping corporate materials. Their innovative digital methods earned them a stern letter from Spotify accusing them of violating its terms of use; the company later threatened their research funding. Thus, the book itself became an intervention into the ethics and legal frameworks of corporate behavior.

This study was conducted to quantify the errors prompted by neglecting three-dimensional (3D) effects, i.e., beam-filling and horizontal photon transport effects, at millimeter/sub-millimeter wavelengths. This paper gives an overview of the 3D effects that impact ice cloud retrievals of both current and proposed (Ice Cloud Imager) satellite instruments operating at frequencies of ≈186.3 and ≈668 GHz. The 3D synthetic scenes were generated from two-dimensional (2D) CloudSat (Cloud Satellite) observations over the tropics and mid-latitudes using a stochastic approach. By means of the Atmospheric Radiative Transfer Simulator (ARTS), three radiative transfer simulations were carried out: one 3D, one independent beam approximation (IBA), and one-dimensional (1D). The comparison between the 3D and IBA simulations revealed a small horizontal photon transport effect, with IBA simulations introducing mostly random errors and a slight overestimation (below 1 K). However, performing 1D radiative transfer simulations results in a significant beam-filling effect that increases primarily with frequency, and secondly, with footprint size. For a sensor footprint size of 15 km, the errors induced by neglecting domain heterogeneities yield root mean square errors of up to ≈4 K and ≈13 K at 186.3 GHz and 668 GHz, respectively. However, an instrument operating at the same frequencies, but with a much smaller footprint size, i.e., 6 km, is subject to smaller uncertainties, with a root mean square error of ≈2 K at 186.3 GHz and ≈7.1 K at 668 GHz. When designing future satellite instruments, this effect of footprint size on modeling uncertainties should be considered in the overall error budget. The smallest possible footprint size should be a priority for future sub-millimeter observations in light of these results.

The Baltic Sea is partly covered by sea ice in every winter season. Landfast ice (LFI) on the Baltic Sea is a place for recreational activities such as skiing and ice fishing. Over thick LFI ice roads can be established between mainland and islands to speed up transportation compared to the use of ferries. LFI also allows transportation of material to or from islands without piers for large ships. For all these activities, information on LFI extent and sea ice thickness, snow thickness and degree of ice deformation on LFI is very important. We generated new operational products for these LFI parameters based on synthetic aperture radar (SAR) imagery and existing products and prediction models on the Baltic Sea ice properties. The products are generated daily and have a 500 m pixel size. They are visualized in a web-portal titled “Baltic Sea landfast ice extent and thickness (BALFI)” which has free access. The BALFI service was started in February 2019. Before the BALFI service, information on the LFI properties in fine scale (<1 km) was not available from any single source or product. We studied the accuracy and quality of the BALFI products for the ice season 2019–2020 using ice charts and in-situ coastal ice station data. We suggest that the current products give usable information on the Baltic LFI properties for various end-users. We also identify some topics for the further development of the BALFI products.

The accurate simulation of microwave observations of clouds and precipitation are computationally challenging. A common simplification is the assumption of totally random orientation (TRO); however, studies have revealed that TRO occurs relatively infrequently in reality. A more appropriate assumption is that of azimuthally random orientation (ARO), but so far it has been a computationally expensive task. Recently a fast approximate approach was introduced that incorporates hydrometeor orientation into the assimilation of data from microwave conically scanning instruments. The approach scales the extinction in vertical (V) and horizontal (H) polarised channels to approximate ARO. In this study, the application of the approach was extended to a more basic radiative transfer perspective using the Atmospheric Radiative Transfer Simulator and the high-frequency channels of the Global Precipitation Measurement Microwave Imager (GMI). The comparison of forward simulations and GMI observations showed that with a random selection of scaling factors from a uniform distribution between 1 and 1.4–1.5, it is possible to mimic the full distribution of observed polarisation differences at 166 GHz over land and water. The applicability of this model at 660 GHz was also successfully demonstrated by means of existing airborne data. As a complement, a statistical model for polarised snow emissivity between 160 and 190 GHz was also developed. Combining the two models made it possible to reproduce the polarisation signals that were observed over all surface types, including snow and sea ice. Further, we also investigated the impact of orientation on the ice water path (IWP) retrievals. It has been shown that ignoring hydrometeor orientation has a significant negative impact (∼20% in the tropics) on retrieval accuracy. The retrieval with GMI observations produced highly realistic IWP distributions. A significant highlight was the retrieval over snow covered regions, which have been neglected in previous retrieval studies. These results provide increased confidence in the performance of passive microwave observation simulations and mark an essential step towards developing the retrievals of ice hydrometeor properties based on data from GMI, the Ice Cloud Imager (ICI) and other conically scanning instruments.

The second generation of the EUMETSAT Polar System (EPS-SG) will include the Ice Cloud Imager (ICI), the first operational sensor covering sub-millimetre wavelengths. Three copies of ICI will be launched that together will give a measurement time series exceeding 20 years. Due to the novelty of ICI, preparing the data processing is especially important and challenging. This paper focuses on activities related to the operational product planned, but also presents basic technical characteristics of the instrument. A retrieval algorithm based on Bayesian Monte Carlo integration has been developed. The main retrieval quantities are ice water path (IWP), mean mass height (Zm) and mean mass diameter (Dm). A novel part of the algorithm is that it fully presents the inversion as a description of the posterior probability distribution. This is preferred for ICI as its retrieval errors do not always follow Gaussian statistics. A state-of-the-art retrieval database is used to test the algorithm and to give an updated estimate of the retrieval performance. The degrees of freedom in measured radiances, and consequently the retrieval precision, vary with cloud situation. According to present simulations, IWP, Zm and Dm can be determined with 90 % confidence at best inside 50 %, 700 m and 50 µm, respectively. The retrieval requires that the data from the 13 channels of ICI are remapped to a common footprint. First estimates of the errors introduced by this remapping are also presented.

A neural-network-based retrieval method to determine the snow ice water path (SIWP), liquid water path (LWP), and integrated water vapor (IWV) from millimeter and submillimeter brightness temperatures, measured by using airborne radiometers (ISMAR and MARSS), is presented. The neural networks were trained by using atmospheric profiles from the ICON numerical weather prediction (NWP) model and by radiative transfer simulations using the Atmospheric Radiative Transfer Simulator (ARTS). The basic performance of the retrieval method was analyzed in terms of offset (bias) and the median fractional error (MFE), and the benefit of using submillimeter channels was studied in comparison to pure microwave retrievals. The retrieval is offset-free for SIWP  > 0.01 kg m−2, LWP  > 0.1 kg m−2, and IWV  > 3 kg m−2. The MFE of SIWP decreases from 100 % at SIWP  =  0.01 kg m−2 to 20 % at SIWP  =  1 kg m−2 and the MFE of LWP from 100 % at LWP  = 0.05 kg m−2 to 30 % at LWP  =  1 kg m−2. The MFE of IWV for IWV  > 3 kg m−2 is 5 to 8 %. The SIWP retrieval strongly benefits from submillimeter channels, which reduce the MFE by a factor of 2, compared to pure microwave retrievals. The IWV and the LWP retrievals also benefit from submillimeter channels, albeit to a lesser degree. The retrieval was applied to ISMAR and MARSS brightness temperatures from FAAM flight B897 on 18 March 2015 of a precipitating frontal system west of the coast of Iceland. Considering the given uncertainties, the retrieval is in reasonable agreement with the SIWP, LWP, and IWV values simulated by the ICON NWP model for that flight. A comparison of the retrieved IWV with IWV from 12 dropsonde measurements shows an offset of 0.5 kg m−2 and an RMS difference of 0.8 kg m−2, showing that the retrieval of IWV is highly effective even under cloudy conditions.

In this study, we assess the potential of X-band Interferometric Synthetic Aperture Radar imagery for automated classification of sea ice over the Baltic Sea. A bistatic SAR scene acquired by the TanDEM-X mission over the Bothnian Bay in March of 2012 was used in the analysis. Backscatter intensity, interferometric coherence magnitude, and interferometric phase have been used as informative features in several classification experiments. Various combinations of classification features were evaluated using Maximum likelihood (ML), Random Forests (RF) and Support Vector Machine (SVM) classifiers to achieve the best possible discrimination between open water and several sea ice types (undeformed ice, ridged ice, moderately deformed ice, brash ice, thick level ice, and new ice). Adding interferometric phase and coherence-magnitude to backscatter-intensity resulted in improved overall classification performance compared to using only backscatter-intensity. The RF algorithm appeared to be slightly superior to SVM and ML due to higher overall accuracies, however, at the expense of somewhat longer processing time. The best overall accuracy (OA) for three methodologies were achieved using combination of all tested features were 71.56, 72.93, and 72.91% for ML, RF and SVM classifiers, respectively. Compared to OAs of 62.28, 66.51, and 63.05% using only backscatter intensity, this indicates strong benefit of SAR interferometry in discriminating different types of sea ice. In contrast to several earlier studies, we were particularly able to successfully discriminate open water and new ice classes.

Microwave remote sensing is important for observing the mass of ice hydrometeors. One of the main error sources of microwave ice mass retrievals is that approximations around the shape of the particles are unavoidable. One common approach to represent particles of irregular shape is the soft particle approximation (SPA). We show that it is possible to define a SPA that mimics mean optical particles of available reference data over narrow frequency ranges, considering a single observation technique at the time, but that SPA does not work in a broader context. Most critically, the required air fraction varies with frequency and application, as well as with particle size. In addition, the air fraction matching established density parameterisations results in far too soft particles, at least for frequencies above 90 GHz. That is, alternatives to SPA must be found. One alternative was recently presented by Geer and Baordo (2014). They used a subset of the same reference data and simply selected as \"shape model\" the particle type giving the best overall agreement with observations. We present a way to perform the same selection of a representative particle shape but without involving assumptions on particle size distribution and actual ice mass contents. Only an assumption on the occurrence frequency of different particle shapes is still required. Our analysis leads to the same selection of representative shape as found by Geer and Baordo (2014). In addition, we show that the selected particle shape has the desired properties at higher frequencies as well as for radar applications. Finally, we demonstrate that in this context the assumption on particle shape is likely less critical when using mass equivalent diameter to characterise particle size compared to using maximum dimension, but a better understanding of the variability of size distributions is required to fully characterise the advantage. Further advancements on these subjects are presently difficult to achieve due to a lack of reference data. One main problem is that most available databases of precalculated optical properties assume completely random particle orientation, while for certain conditions a horizontal alignment is expected. In addition, the only database covering frequencies above 340 GHz has a poor representation of absorption as it is based on outdated refractive index data as well as only covering particles having a maximum dimension below 2 mm and a single temperature.

The article describes a new practical model for the infrared absorption of chlorofluorocarbons and other gases with dense spectra, based on high-resolution transmission molecular absorption database (HITRAN) absorption cross-sections. The model is very simple, consisting of frequency-dependent polynomial coefficients describing the pressure and temperature dependence of absorption. Currently it is implemented for the halocarbon species required by the Radiative Forcing Model Intercomparison Project. In cases where cross-section data is available at a range of different temperatures and pressures, this approach offers practical advantages compared to previously available options, and is traceable, since the polynomial coefficients follow directly from the laboratory spectra. The new model is freely available and has several important applications, notably in remote sensing and in developing advanced radiation schemes for global circulation models that include halocarbon absorption. For demonstration, the model is applied to the problem of computing instantaneous clear-sky halocarbon radiative efficiencies and present day radiative forcing. Results are in reasonable agreement with earlier assessments that were carried out with the less explicit Pinnock method, and thus broadly validate that method.

The Finnish Ice Service is part of the Finnish Meteorological Institute (FMI). Based on the mandate in the Finnish legislation, it provides information on the ice conditions in the Baltic Sea. This paper introduces the methods used by the Finnish Ice Service, data sources, products, services, datasets, and supporting Baltic Sea ice remote sensing and geophysics research conducted at FMI. The predecessor of the Finnish Ice Service started its operational ice charting in 1915 to provide ice information for the winter navigation. To this day, the main users still are the winter navigation authorities, including the icebreaker fleet and management, as well as the shipping community, scientists and general public. The focus area is the Baltic Sea. Typically, the service operates from mid-October to the end of May, providing up-to-date sea-ice information in several products and formats. The prevailing ice situation is described in ice charts, ice reports and ice codes, which are based on a range of different observation sources like satellite images, predominantly from synthetic aperture radars, and surface observations from both icebreakers and coastal observers. The Finnish Ice Service has long sea ice observation timeseries and archives of manually analysed ice charts. To help users and customers optimize their operations in ice infested waters, the Finnish Ice Service provides numerical and manual sea ice forecasts with various forecast lengths. The Finnish Ice Service processes and disseminates satellite data and also provides advisory and consultant services to users. As FMI is committed to the open data policy, the main ice service products are provided free of charge. A number of products are also available through the Copernicus Marine Service (CMS).