dataesr/scientific-paragraphs-categorization huggingface dataset:
g. Clark et al. , 2007)  and using a larger dataset for the Pacific would be necessary to confirm these initial findings. Differences between the Atlantic and Pacific may be due to differences in Rossby Wave breaking events and the influence of the North Atlantic Oscillation (NAO) or El Nino and Southern Oscillation (ENSO) leading to varying amounts of mixing in the Ex-UTLS over the Atlantic and Pacific  (Shuckburgh et al. , 2009). In time, IAGOS will allow climatological differences between the Atlantic and Pacific to be more fully described.
Conclusions This article described the first trans-Pacific flights of an IAGOS-equipped aircraft. Ozone, water vapour and CO are now measured regularly across the Pacific by an aircraft operated by China Airlines from Taipei to Vancouver. The results reveal air with a range of ozone mixing ratios from 18 to !500 ppbv representing origins in the marine boundary layer and the lowermost stratosphere. Concentrations of CO range from 20 to 570 ppbv, with the higher concentrations representing polluted air masses. The corresponding water vapour signature, along with FLEX-PART back-trajectories suggest that these high mixing ratios of CO originate from boreal wildfire plumes exported from Eurasia and Alaska. A statistical study of the air masses over the Pacific will be possible as more data are collected.
In addition, the IAGOS database will soon contain additional added-value products, such as recent CO contributions, thanks to the automatic application coupling IAGOS, with FLEXPART and the ECCAD (Emissions of atmospheric Compounds and Compilation of Ancillary Data) emissions inventory database. This ongoing development of the database for the provision of IAGOS data and services will enable a better understanding of the origin of the observed CO plumes. There are some notable differences between the Pacific and the Atlantic. The Pacific storm tracks export highly polluted air across the Pacific basin and CO mixing ratios are much higher than observed over the Atlantic. Mixing ratios of ozone are lower over the Pacific suggesting a more frequent export of air from the tropical marine boundary layer to mid-latitudes, and ozone mixing ratios are higher over the Atlantic, suggesting that for the same latitude, the sampled air over the Atlantic is deeper within the lowermost stratosphere.
These differences may be related to the climatological position of the tropopause and storm tracks being different over the two basins. This will be an important area for further work as more IAGOS data becomes available and seasonal climatologies of CO and O 3 can be derived over the Pacific. IAGOS is important to the scientific community in providing data in the UTLS region in regions where in situ data are often of limited temporal and spatial extent. The data will prove useful in the validation of satellite and models in this region and are available at www. iagos. org.
Acknowledgements The programmes MOZAIC and CARIBIC, and the current Research Infrastructure IAGOS, are operated with support from the European Commission, national agencies in Germany (BMBF), France (MESR) and the UK (NERC), and the IAGOS member institutions (www. iagos. org/partners). The participating airlines (Lufthansa, Air France, Austrian, China Airlines, Iberia, Cathay Pacific, Air Namibia, Sabena) supported IAGOS by carrying the measurement equipment free of charge since 1994. The data are available at www. iagos. fr. Thanks to additional support from ETHER. J. W. Kaiser was funded in the EU H2020 project MACC-III (contract no. 633080).
Contact with light was avoided throughout the whole procedure. Numerical analyses. All data were tested for normality and transformed if necessary. We used linear mixed effects models to test the effects of warming and date of sampling (fixed effects) on overall microbial biomass, and the biomass of bacteria, fungi, photosynthetic protists, cyanobacteria, ciliates, testate amoebae, rotifers and nematodes while accounting for the temporal repeated measurements in each plot on the four dates. All models were fitted including plot nested with date as a random effect on the intercept to correct for the inflation of the residual degrees of freedom that would have occurred if we were using repeated measurements as true replicates  48. The nlme package in R was used to run these models  48. We also used linear mixed effects models to test the effect of light (fixed effects) on the abundance and biomass of MTA and photosynthetic protists, microbial and Sphagnum chlorophyll content, A max, bryo , F v /F m , while accounting for the block effect (paired peat cores).
Acknowledgements The authors would like to thank  T. Sime-Ngando ,  J. Colombet  and  Karine Greiner  for their help with the flow cytometry, and  M-L Toussaint  and  G. Bernard  for field assistance. This research is part of the  ANR   PEATWARM  project (Effect of moderate warming on the functioning of Sphagnum peatlands and their function as carbon sink). PEATWARM is supported by the  French National Agency for Research  under the " Vulnerability: Environment-Climate"   Program  ( ANR-07-VUL-010 ). VEJJ, AB and EADM were additionally supported by the  Polish Ministry of Science and Higher Education  (grant  NN305077936 ), through the  Swiss Contribution  to the enlarged  European Union  ( Climpeat project ;  PSPB-013/2010 ). RJP was supported by the  Russian Scientific Fund  (Grant  14-14-00891 ).
g. , calcium, magnesium, sodium, and potassium). For these analyses, water samples from Lake La Preciosa, Lake Atexcac, and Lake Quechulac were diluted 200, 150, and 20 times, respectively, with nitric acid at 2%. The uncertainty on alkalinity measurements was better than 1%. Concerning the measurements of dissolved silica, anions, and cations, the uncertainty of the measurements was better than 5%. Activities of main anions, cations and dissolved silica as well as saturation indices of the surface water solutions of Lake La Preciosa, Lake Quechulac, and Lake Atexcac were calculated using the Visual MINTEQ software. Table  1  summarizes precipitation equilibrium reactions and solubility constants of the mineral phases included in our calculations, e. g. , Ca-and/or Mg-carbonates, sepiolite, "amorphous sepiolite" (as coined by  Wollast et al.
X-ray Diffraction The bulk mineralogical composition of microbialites was determined by XRD. About 1 g of each microbialite was crushed in an agate mortar and the powder was deposited on an aluminum sample holder. XRD measurements were performed using a Panalytical X'Pert diffractometer equipped with a cobalt anode (Co-Kα). Data were recorded at 45 kV and 35 mA in the continuous-scan mode between 4 and 120 • (2θ) with a step of 0. 0084 • and a total counting time of around 4 h. XRD data were analyzed using the PANalytical X'Pert Highscore software for background subtraction, peak finding, and matching with XRD patterns of reference compounds from the International Crystal Structure Database (ICSD, Fachinformationszentrum Karlsruhe, Germany; US Institute of Standards and Technology, USA). For additional XRD characterization of the silicate phase, treatments with ethylene glycol were performed.
Scanning Electron Microscopy Scanning electron microscopy (SEM) analyses were performed using a Zeiss ultra 55 field emission gun (FEG) SEM. Backscattered electron (BSE) images were acquired using an angle selective backscattered (AsB) detector at an accelerating voltage of 15 kV and a working distance of ∼7. 5 mm. The elemental composition of mineral phases was determined by energy dispersive X-ray spectrometry (EDXS) using an EDS QUANTAX detector. EDXS data were analyzed using the ESPRIT software package (Bruker).
Scanning Transmission X-ray Microscopy The six FIB foils extracted from the Atexcac microbialite sample were analyzed by STXM at the carbon K-edge (C Kedge), the iron L 2,3 -edges (Fe L 2,3 -edges), and the magnesium K-edge (Mg K-edge). Analyses were performed on beamline 11. 0. 2. 2 at the Advanced Light Source (Berkeley, USA), using a 25 nm zone plate. Energy calibration was achieved using the well-resolved 3p Rydberg peak of gaseous CO 2 at 294. 96 eV. Data included images and image stacks, from which X-ray absorption near edge structure (XANES) spectra and maps were retrieved. The aXis2000 software  (Hitchcock, 2012)  was used for data processing. STXM has been used before for the study of biomineralization and fossilization of microbes in ancient and modern microbialites  (Benzerara et al.
Indeed, mineral phases in the microbialites may have formed continuously or discretely over a certain period of time, whereas the chemical composition of the lake was measured during sample collection only. Several earlier studies have monitored the chemical composition of surface water in Lakes of Atexcac, La Preciosa, and Quechulac at different periods during the year  (Vilaclara et al. , 1993; Armienta et al. , 2008; Kaźmierczak et al. , 2011). Comparison with present data suggests that the solution chemistry of these lakes has not varied significantly over time and that these lakes have been supersaturated with respect to kerolite at least since 2001  (Armienta et al. , 2008 ). Yet, the chemical composition of the Mexican lakes may vary temporarily depending on seasons because of the mixing of the water column once per year and/or high influxes during rain events of fine volcanic material that dissolves easily in high pH water and raise temporarily Mg and SiO 2 activities.
ACKNOWLEDGMENTS The research leading to these results has received funding from the  European Research Council  under the European Union's  Seven Framework Program :  ERC grants Calcyan  (PI:  K. Benzerara , Grant Agreement no. 307110 ) and ProtistWorld (P. I. P. López-García , Grant Agreement no. 322669 ). Advanced Light Source (ALS) Molecular Environmental Science beamline 11. 0. 2 is supported by the  Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences , and  Biosciences and Materials Sciences Division, U. S. Department of Energy , at the  Lawrence Berkeley National Laboratory. The  TEM  facility at IMPMC was purchased owing to a support by  Region Ile-de-France  grant  SESAME 2000 E 1435. The SEM and FIB facilities at IMPMC were purchased owing to a support by  Région Ile de France  grant  SESAME 2006 I-07-593/R.
Acknowledgements. This study was funded by the  Agence Nationale pour la Recherche (ANR)  through the  SUMER, Blanc SIMI   6-2012. All the computations presented in this paper were performed using the CIMENT infrastructure (https://ciment. ujf-grenoble. fr), which is supported by the  Rhône-Alpes region  (GRANT CPER07_13 CIRA: http://www. ci-ra. org). We also thank the  CSC-IT Center for Science Ltd (Finland)  for their support in Elmer/Ice development. We also thank  Andreas Vieli ,  Joe Todd  and  Martin Truffer , whose comments and advice greatly improved the quality of the paper. Edited by:  A. Vieli.
AIRS-LMD cloud properties The spatial resolution of the AIRS measurements is 13. 5 km at nadir. Nine AIRS measurements (3 × 3), called a "golf ball" (see grey circles in Fig. 1 ), correspond to one footprint of the Advanced Microwave Sounding Unit (AMSU). NASA AIRS L2 standard products include atmospheric temperature and water vapour profiles as well as surface skin temperature and ice/snow flag  (Susskind et al. , 2003 (Susskind et al. , , 2006;; Chahine et al. , 2006)  at the spatial resolution of an AMSU footprint. The AIRS-LMD (AIRS clouds retrieved at the Laboratory of Dynamic Meteorology) cloud retrieval makes use of these products as ancillary data and has been described in  (Stubenrauch et al. , 2010). Briefly, the retrieval methodology is based on a weighted χ 2 method using radiances measured along the wing of the 15 µm CO 2 absorption band.
CALIPSO cloud data at 5 km spatial resolution CALIOP (Cloud-Aerosol Lidar with Orthoganal Polarization), a two-wavelength polarization-sensitive nadir viewing lidar, provides high-resolution vertical profiles of aerosols and clouds. It uses three receiver channels: one measuring the 1064 nm backscatter intensity and two channels measuring orthogonally polarized components of the 532 nm backscattered signal. Cloud and aerosol layers are detected by comparing the measured 532 nm signal return with the return expected from a molecular atmosphere. The method utilizes an adaptive threshold test  (Vaughan et al. , 2009)  and retrieved the height of the physical top height, rather than the effective radiative height. The method is capable of detecting the clouds with visible extinction as small as ∼ 0.
01 km -1 though the detection efficiency decreases in this domain and, as  Davis et al. (2010)  have shown, the CALIPSO misses a certain fraction of sub-visible cirrus clouds. The retrieval algorithm is the same for the daytime and nighttime portions of the orbit, except that different detection thresholds are used for day and night. Analysis of the parallel and perpendicular polarization of 532 nm backscatter signals provides vertically resolved identification of cloud water phase according to the algorithm of  Hu et al. (2007). For this analysis, we utilize z top and z base from version 3 of the CALIPSO L2 cloud data averaged to 5 km along the track (release v. 3. 01).
Colocation of the data sets Figure  1  illustrates a typical single-day coverage of AIRS and CALIPSO-CloudSat at a specific observation time (13:30 at the equator crossing time). Whereas the AIRS swaths cover areas about 1000 km, the active instruments only cover a 90 m-1. 4 km wide track near the middle of the AIRS swaths. Since the instruments share the same orbit, one can impose strict overlapping criteria to get a high-quality data set. Our colocation starts with the AIRS data and searches the other data sets for the observations closest to the centres of individual AIRS footprints (usually, three per each golf ball). A blown-up part in the upper-right corner of Fig. 1 Table  2. Colocation statistics corresponding to the data illustrated in Fig. 1.
Selecting high-level ice clouds Figure  2  illustrates the information available in the collocated data set, for typical examples of high-level ice clouds, with IWP (ice water path) increasing from 9. 0 to 303 g m -2. In this figure, we supplement the IWC vertical profiles with AIRS z cld (horizontal red lines), CALIPSO z top and z base (blue lines), and GEOPROF z top and z base (green lines). It is interesting to trace the behaviour of these values with changing IWP: whereas CALIPSO and GEOPROF z top match on all four panels, CALIPSO and GEOPROF z base match at IWP < 100 g m -2 , while the CALIPSO lidar cannot probe the lower boundary of thicker clouds; AIRS z cld corresponds to the radiative height close to the maximum backscatter signal from CALIPSO  (Stubenrauch et al. , 2010) ; for high-level ice clouds it lies generally 1 to 2 km below cloud top, depending on the vertical accumulation of optical depth  (Liao et al.
Relating IWC profile shapes to cloud and atmospheric parameters We have analyzed 3 years  (2007) (2008) (2009)  of collocated data by searching for the best fit within the four primitive IWC(z) shapes: rectangular, isosceles trapezoid, lower triangle, and upper triangle. Then we have studied their relative occurrence with respect to IWP, cloud layering (single or multi), cloud vertical extent, vertical wind, latitude and underlying surface (land or ocean). As a first step, we have studied the probability of occurrence of these specific IWC profile shapes as a function of IWP. Table  5  presents the statistics separately for single-layer and multi-layer cloud scenes, respectively. As the median values of Table  3  have already indicated, about 75 % of all high ice clouds lie within the range of IWP < 100 g m -2.
0 W m -2 for direct and 2. 0 W m -2 for diffuse irradiances  (Oreopoulos et al. , 2012). Scattering calculations are performed using the DISORT (Discrete Ordinates Radiative Transfer Program) package  (Stamnes et al. , 1988). For each spectral band, the optical properties of water and ice clouds are calculated using the  Hu and Stamnes (1993)  and  Fu (1996)  parameterizations, respectively. With the help of the RRTM code, we have performed a series of radiative transfer calculations, varying the atmospheric scenario, De(z) (10 values), IWC(z) profile shape, IWP (seven intervals), cloud vertical extent ( z cld , seven values), and cloud top height (five values). In addition, we doubled the number of simulations by adding an underlying optically thick water cloud to estimate the IWC profile effects when the terrestrial radiance is "blocked".
Absolute differences of IWC-profile-shape-weighted SW and LW fluxes Even though some of the panels in Figs. 8  and 9  show noticeable changes in TOA and SRF fluxes, this knowledge alone is not enough to estimate the energetic effects of using the rectangular type IWC(z) in all the cases instead of using real (or more realistic) profiles. To do that, we have used a precalculated set of 98 000 fluxes as a big lookup table (LUT) (see Sect. 4. 2. 1) and applied it to each of the events in the collocated data set. For clear-sky cases, we used a corresponding clear-sky profile to obtain realistic cloud-amountweighted fluxes (we used cloud amount from AIRS). For cloudy cases, we used the fluxes corresponding to the best fit IWC model profile (if the best fit returned the rectangular profile it was included to keep the statistics unbiased).
Conclusion Since IR sounders only determine bulk cirrus microphysical properties, we added the data from active instruments to get a deeper insight into vertical profiles of IWC and De. The primary object of this analysis was to find out if the IWC profiles can be classified according to simple shapes, ideally as a function of parameters determined by IR sounders alone, and to determine the effect on the radiative properties of the cloud. Below we list the most important findings of our analyses. 1. A minimal and sufficient set of primitive shapes representing the IWC profiles in high ice clouds consists of four elements: rectangular, isosceles trapezoid, upper triangle, and lower triangle. The statistical analysis shows that rectangular and trapezoid IWC shapes together make up more than 70 % of all the cases with trapezoid-like IWC profiles dominating both single-and multi-layer scenes.
Acknowledgements. This research was supported by the  European Space Agency  through the  Cloud_cci  project and by  CNRS. The authors are grateful to the  "Atmospheric and Environmental Research" company and  to its RT model development team in particular for providing and supporting the RRTM radiative transfer code. The calculations have been performed at the ClimServ IPSL centre. The CALIPSO and GEOPROF data has been retrieved from the  ICARE Data and Service Center at the University of Lille , and the authors thank the personnel of both centres for a continuous support of the work. Edited by:  M. Krämer.
, 2013). Its role in aerosol formation  (Hertel et al. , 2012)  makes it an important component in air quality and climate issues  (Pope et al. , 2009; Erisman et al. , 2011). In addition to being directly toxic to plants at high concentrations  (Krupa, 2003) , NH 3 and its derivatives are also quickly deposited in the ecosystems, increasing their eutrophication and reducing biodiversity  (Erisman et al. , 2007; EEA-European Environment Agency, 2014). All these impacts are magnified as the nitrogen atom included in NH 3 enters the "nitrogen cascade"  (Galloway et al. , 2003b). Human activities have caused a large increase of NH 3 : manure management and agricultural soils are responsible for more than 82 % of the 49. 3 Tg of NH 3 emitted globally in 2008 (EDGAR-Emission Database for Global Atmospheric  Research, 2011).
Satellite observations NH 3 was first detected in IASI spectra inside fire plumes above Greece in 2007  (Coheur et al. , 2009). Subsequently, the development of a simplified retrieval method allowed the first global map of NH 3 from IASI observations to be produced  (Clarisse et al. , 2009). In  Clarisse et al. (2010) , a sensitivity study was performed, showing the abilities of infrared sensors to probe the lower troposphere, depending on atmospheric parameters such as the thermal contrast (see below). Recently, an improved IASI-NH 3 data set has been generated, combining better sensitivity and error characterization. The algorithm used to retrieve NH 3 columns from the radiance spectra is described in detail and compared to previous algorithms by  Van Damme et al. (2014a). In short, the improved retrieval scheme exploits the hyperspectral characteristic of IASI and a broad spectral range between 800 and 1200 cm -1.
sedoo. fr) The EMEP network has been running since the 1980s, with data provided by the countries as part of the Convention on Long-Range Transboundary Air Pollution. These data are made available after national and EMEP quality assessments have been conducted  (EMEP, 2014). For this analysis data from 27 sites were used, which have been generated from various national networks contributing to EMEP, so that instrumentation differs from one site to another (EBAS, 2014). The AMoN network was established in 2010 in the USA to monitor NH 3 with Radiello passive diffusion-type samplers (with a time resolution of 2 weeks) (NADP-National  Atmospheric Deposition Program, 2012). From this network, we use the 28 sites which have started to provide measurements no later than 1 March 2011. The NEU data set was generated using DELTA (DEnuder for Long-Term Atmospheric sampling) systems, detailed in  Sutton et al.
Looking at interannual variability, for example in 2013, the fertilization peaks of March, July and October are clearly observed  (Shen et al. , 2011). It is interesting to note that the highest January surface concentration (5. 1 µg m -3 ) and satellite total column (7. 8 ×10 15 molec cm -2 ) are measured during the severe winter pollution episode of 2013 (see  Boynard et al. , 2014; Wang et al. , 2014). The correlation analysis for the monthly values of the 43 NNDMN sites gives a Pearson's r equal to 0. 39 (considering the IASI data with a monthly relative retrieval error below 100 %) and a slope of the regression equal to 0. 21 (n = 1149). The Pearson's r is globally higher than for Europe probably due to the higher concentrations in China. This is also observed in the monthly retrieval error which are overall lower.
The latter may therefore be better monitored by IASI. The right bottom plot (Fig. 3 ) compares the surface VMR for Africa in ppbv. There is no correlation when the data of all the sites are grouped. This could be explained by the sparsity of the IDAF data set combined with the difficulties of the satellite to catch specific high emission events. The only station showing a positive significant Pearson's r is Lamto (Ivory Coast, 0. 39), which is not surprisingly a wet savanna site. The comparison for each station individually is provided in Table  A3. In general, the regression intercept is relatively high, while the slope is relatively low. For all three regions the largest measured concentrations are underestimated in the IASI surface-derived data. This smaller range of concentrations could be a consequence of using a fixed vertical profile shape in the retrieval procedure for IASI spectra.
Hourly resolved data set The LML data set offers long-term hourly resolved NH 3 measurements allowing the investigation of individual IASI observations and testing the effect of averaging different time scales. However, it is worth noting that this network provides measurements in an area (the Netherlands) that is not particularly favorable for infrared remote sensing of surface pollution (low thermal contrast and relatively high cloud coverage). Table  2  summarizes the results from the comparison of the IASI concentrations (columns converted to surface concentrations as above) to those measured from the ground. The upper part presents the comparison from the linear regression for each individual site (slope (a) and intercept (b) of the linear regression, Pearson's r (underlined when significant) and the number of observations (n)).