1,721,048 research outputs found
Econometric estimates of Earth's transient climate sensitivity
Full text linkHow sensitive is Earth’s climate to a given increase in atmospheric greenhouse gas (GHG) concentrations? This long-standing question in climate science was recently analyzed by dynamic panel data methods using extensive spatio-temporal data of global surface temperatures, solar radiation, and GHG concentrations over the last half century to 2010 (Storelvmo et al, 2016). Those methods revealed that atmospheric aerosol effects masked approximately one-third of the continental warming due to increasing GHG concentrations over this period, thereby implying greater climate sensitivity to GHGs than previously thought. The present study provides regularity conditions and asymptotic theory justifying the use of time series cointegration-based methods of estimation when there are both stochastic process and deterministic trends in the global forcing variables, such as GHGs, and station-level trend effects from such sources as local aerosol pollutants. The asymptotics validate estimation and confidence interval construction for econometric measures of Earth’s transient climate sensitivity (TCS). The methods are applied to observational data and to data generated from several groups of global climate models (GCMs) that are sampled spatio-temporally and aggregated in the same way as the empirical observations for the time period 1964–2005. The findings indicate that 7 out of 9 of the GCM reported TCS values lie within the 95% empirical confidence interval computed econometrically from the GCM output. The analysis shows the potential of econometric methods to provide empirical estimates and confidence limits for TCS, to calibrate GCM simulation output against observational data in terms of the implied TCS estimates obtained via the econometric model, and to reveal the respective sensitivity parameters (GHG and non-GHG related) governing GCM temperature trends
Lidar measurements taken at the ALOMAR mountain observatory at Andenes, Norway during March 2021
No full textDuring a 2-week measurement campaign from 15-31 March 2021 (ISLAS2021), we collected a comprehensive dataset characterizing the atmospheric water vapour and precipitation stable isotope and aerosol composition at a coastal station in the European sub-Arctic. Located at the northeastern coast of the Nordic Seas, stable water isotope measurements with cavity ring-down spectrometers (CRDS) were collected at Andenes, Norway close to sea level and at the nearby ALOMAR mountain top observatory at 370 m a.s.l. Paired water vapour isotope and precipitation measurements at sub-event time resolution were collected at both station locations. These were supplemented with water vapour isotope measurements at the cities of Tromsø, Norway and Bergen, Norway. Surface precipitation samples were collected on a per-event basis along a transect towards the south to assess spatial representativeness. Measurements of ice nucleating particle concentrations were taken at sea level during precipitation events, supplemented by continuous size-resolved aerosol measurements. These detailed measurements were complemented by additional instrumentation to characterize the atmospheric conditions, including ground-based vertical-pointing rain radars, disdrometer, frequent radiosonde ascents and a ceilometer. All stable water isotope measurements have been calibrated onto the VSMOW-SLAP scale. During the campaign, weather conditions were alternating rapidly between warm mid-latitude air masses and marine cold-air outbreak conditions. The data from the ISLAS2021 measurement campaign therefore provide insight into a variety of mixed-phase precipitation processes, atmospheric long-range transport, and the dynamics of high-latitude weather system with the combined perspective of stable water isotopes and aerosol measurements.
This dataset contains attenuated backscatter at 355nm, 532nm and 1064nm as well as the volume depolarization ratio at 532nm. The temporal resolution is 30s and the vertical resolution is 7.5m. The dataset consists of four observation periods. One observation period contains 1-3 measurements. In between the individual measurements, neutral density filter changes were applied to the 355nm and/or 1064nm channels, i.e. filters were removed to increase the signal or filters were added to protect the detection hardware from a too-high signal. The time periods for the individual filter configurations are included under filter_configs in this metadata. For the signals at 532nm (both polarization directions) and 355nm, there are two detection channels each, one analogue detection channel suitable for the near range (nr) and one photon-counting channel suitable for the far range (fr). They are in this dataset not glued, but the attenuated backscatter is given for each channel individually. The volume depolarization ratio at 532nm is also calculated from the analogue and photon-counting signals individually. At 1064nm, there is only one detection channel which is an analogue channel. The data processing of the data from the raw files to the published file uses the python packages atmospheric-lidar and lidar_molecular developed by Ioannis Binietoglou (https://pypi.org/project/atmospheric-lidar/, https://gitlab.com/ioannis_binietoglou/lidar_molecular). Range correction and background subtraction are applied to all channels, in addition deadtime-correction is applied to the photon-counting channels. This procedure is the same as applied by Schäfer et al., (2022). Where signals were too high in the lowest part of the atmosphere to apply deadtime-correction in the photon-counting channel, these lowest layers were removed. The number of removed layers varies between the different measurements. The calibration factors for the depolarization ratio have already been applied, but are given in the dataset together with the standard deviation of the calibration filter for uncertainty estimates using error propagation
Improving Climate Projections by Understanding How Cloud Phase affects Radiation
No full textWhether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Reply to Levermann et al.: Linear scaling for monsoons based on well-verified balance between adiabatic cooling and latent heat release
Full text linkReply to Levermann et al.: Linear scaling for monsoons based on well-verified balance between adiabatic cooling and latent heat release
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