dataesr/scientific-paragraphs-categorization huggingface dataset:
To construct a long temperature time-series from satellite measurements, compiling and averaging data from several instruments is necessary. For this, adjustments and bias corrections between the different instruments are required  [13, 14]. Other biases are also related to the diversity in instrument characteristics and temperature retrieval algorithms that are based on different assumptions. When these datasets are used in climate and Numerical Weather Prediction (NWP) models, the error due to this homogenization of different data records becomes difficult to assess. This emphasizes the importance of using a single instrument with a global spatial coverage and long time series that is homogeneous and consistent for the assessment of climate variables. Since 2006, the Infrared Atmospheric Sounding Interferometers (IASIs) have been used for numerical weather prediction  [15]  and to monitor the atmospheric composition  [16, 17].
IASI is also used as a reference for the inter-calibration of infrared sensors by the Global Space-Based Inter-Calibration System  [18]. Inter-comparison of the three instruments has shown excellent agreement between them  [19, 20]. IASI radiance and temperature values, called Level 1C data (L1C) and Level 2 data (L2), respectively, are processed and delivered to numerous users by the Eumetcast delivery system. Since 2007, the EUropean organisation for the exploitation of METeorological SATellites (EUMETSAT) has carried out several updates of the processing algorithms for both L1C and L2 datasets and, as a result, the radiance and temperature time series are not homogeneous. Trace gas concentration retrievals that are based on IASI L1C and L2 are impacted by this non-homogeneity  [21, 22] , making the computation of trends for temperature and atmospheric composition difficult.
Recently, EUMETSAT has reprocessed the 2007-2017 IASI Metop-A L1C data  [23]  with the most recent version of the algorithm and there is now a homogeneous L1C dataset available (data after 2017 are assumed to be homogeneous with the new dataset). EUMETSAT is now in the process of releasing a first homogeneous L2 temperature data record, but this is not yet available. This study thus aims to investigate the changes of L1C due to algorithm updates by comparing the operational IASI-A L1C data (non-homogeneous) with the reprocessed IASI-A L1C product (homogeneous). The inhomogeneity in the L2 records due to successive updates of the L2 algorithm is then evaluated by comparing the IASI temperatures at different altitudes with those from the European Centre for Medium-Range Weather Forecasts' (ECMWF) latest available reanalysis data-ERA5  [24].
IASI L1C Radiances The radiance values are written as an integer N multiplied by a scale factor (N × 10 -scalefactor ). EUMETSAT has divided the IASI spectrum into five spectral regions and each region has a scale factor that is approximately proportional to the value of the radiance values in the region. Figure  1  shows the precision of the radiance values as a function of the wavenumber. We can clearly see that the decimal precision of the radiance values depends on the wavenumber and varies between 10 -9 and 10 -7. To compare the reprocessed IASI-A radiance values and the operational ones (before reprocessing), we looked for one coincident observation per day in each dataset. Slight differences (of the order of 10 -2 degrees) were found when comparing the latitudes and longitudes of coincident observations.
For a proper comparison, the selected observations were the ones minimizing (latoperlatreproc) 2 + (lonoper -lonreproc) 2. By minimizing the difference between the operational and reprocessed latitudes and longitudes, we made sure that the observations selected in the operational and reprocessed datasets were the same. The differences between the reprocessed and operational radiances were computed at four distinct wavenumbers (700, 1200, 1700, and 2200 cm -1 ). Those wavenumbers were chosen because they are relevant in the study of atmospheric temperatures and humidity. The 700 and 2200 cm -1 spectral channels were used to retrieve temperature profiles from the CO2 bands. The 1200 cm -1 channel is sensitive to the skin temperature and the 1700 cm -1 band falls in the middle of the water vapor continuum  [16, 25].
Slight differences (of the order of 10 -2 degrees) were found when comparing the latitudes and longitudes of coincident observations. For a proper comparison, the selected observations were the ones minimizing (lat operlat reproc ) 2 + (lon operlon reproc ) 2. By minimizing the difference between the operational and reprocessed latitudes and longitudes, we made sure that the observations selected in the operational and reprocessed datasets were the same. The differences between the reprocessed and operational radiances were computed at four distinct wavenumbers (700, 1200, 1700, and 2200 cm -1 ). Those wavenumbers were chosen because they are relevant in the study of atmospheric temperatures and humidity. The 700 and 2200 cm -1 spectral channels were used to retrieve temperature profiles from the CO 2 bands.
The 1200 cm -1 channel is sensitive to the skin temperature and the 1700 cm -1 band falls in the middle of the water vapor continuum  [16, 25]. Table  1  lists the main updates of the L1C algorithm. The updates are due to an update of a parameter used as an input in the L1 Product Processing Facility (PPF) (noted as "param") or by algorithm evolution inside the L1 PPF processor ("algo"). The IASI L1 PPF software version indicated in the table below is the version used for the operational IASI-A products (before reprocessing), and it is given for information, but is not linked to the change of parameters. The first reprocessed release consists of one data record generated by version 8. 0 of the EUMETSAT operational IASI processing chain and the most recent updated auxiliary files provided by the Centre National d'Etudes Spatiales (CNES), using the full orbit level 0 products retrieved from the EUMETSAT archive.
Both are computed from a statistically large matchup (IASI observations and retrievals, ECMWF analysis) dataset. The basic principle of the first statistical retrieval is a linear regression between IASI observations and the atmospheric state vector, computed from a large and representative training set. Version 6 implements a higher level of sophistication: The linear relationship between IASI observations and geophysical parameters is searched in parts, in different observation classes resulting from k-mean unsupervised clustering. It also exploits adjacent pixels to take advantage of geophysical horizontal correlations. This forms the Piece-Wise Linear Regression-cube (PWLR 3 ) algorithm, whose purpose is to ensure that a linear relationship is a good approximation of the actual relationship between the predictors (IASI radiance values in PCs) and the predictands (e.
g. , atmospheric profiles in PCs)  [31]. The temperature profiles used in this study are a combination of retrievals obtained with the statistical method and the optimal estimation method (OEM), which uses the statistical method as a first guess. The OEM is only applicable in cloud-free scenes and the dataset is hence completed by statistical retrievals in cloudy pixels. The record is still heterogeneous at this stage, as a systematic reprocessing of the IASI L2 products has not yet been released. It is therefore composed of successive operational versions of the IASI L2 processor, including incremental algorithm improvements. The exploitation of microwave radiance values in synergy with IASI started at the end of September 2014, with the version 6 IASI L2 processor, which significantly improved the product yield and quality.
Conclusions In this study, we first compared IASI's reprocessed radiance values with the operational ones, and showed that there are differences of 0. 02% in the reprocessed radiance values at 700 and 1200 cm -1 , 0. 2% at 1700 cm -1 , and 0. 5% at 2200 cm -1. In terms of the brightness temperature, these differences correspond to 0. 02, 0. 04, and 0. 1 K, respectively. In all of the regions studied, these differences are found to decrease after two updates from EUMETSAT: At 700 and 2200 cm -1 , the 2013 change of IPSF has the most impact on the evolution of the differences. At 1200 and 1700 cm -1 , most of the decrease is due to the 2010 improvement of the spectral calibration. After February 2017, we identified differences at 700 and 1200 cm -1 between the operational and the reprocessed dataset that originated in a reprocessing configuration error.
Until the reprocessed record is consolidated through 2017, L1C users of IASI-A are recommended to use the reprocessed radiance values from October 2007 to January 2017 and then the operational radiance values from February 2017 onwards. We then compared the currently available temperature record from the operational EUMETSAT release for IASI-A and B with that of ERA5. We showed that two algorithm updates in December 2010 (changes in the cloud processing) and September 2014 (new IASI L2 processor) have had the largest impact on the temperatures. After 2014, the differences between IASI and ERA5 temperatures were small. All of the lessons learned during the lifetime of the IASI mission will also help researchers to better prepare and exploit its successor-IASI-NG  [39, 40] -which will be launched on the Metop-SG program after 2023.
Funding: This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 and innovation programme  (grant agreement No  742909 ,  IASI-FT advanced ERC grant ). The authors acknowledge the Aeris data infrastructure (https://www. aeris-data. fr/)for providing access to the IASI Level 1C data and Level 2 temperature data used in this study.
RESULTS YAMAT-seq captures mature, full-length tRNAs from the majority of A. thaliana tRNA reference genes tRNAs were sequenced with a combination of two complementary methods, YAMAT-seq  (Shigematsu et al. 2017 ) and AlkB treatment  (Cozen et al. 2015; Zheng et al. 2015)  to generate full-length, mature tRNA reads from A. thaliana leaf total-cellular RNA. The demethylating enzyme AlkB was used in conjunction with YAMAT-seq's Y-shaped adapters that are complementary to the CCA motif found at the 3¢ end of mature tRNAs to generate Illumina libraries composed almost entirely of tRNA sequences, with representatives from most genes in the reference A. thaliana database (all sequences in the database can be found in supp. Table  1  with the corresponding tRNA gene identifiers). Greater than 99% of the reads mapped to a tRNA sequence when BLASTed to an A.
thaliana tRNA database (e-value cutoff of 1e-6) (supp. Table  2 ). The remaining reads were largely derived from cytosolic/plastid rRNAs and adapter artifacts (supp. Table  3 ). Over 98% of the reads had a 3¢-terminal CCA sequence. Although the proportion of reads that matched the reference sequence length varied among isoacceptor families (Figure  1 ), the vast majority of the reads were 74-95 nt after adapter trimming (representing the expected range of mature tRNA sequence lengths in A. thaliana), indicating that our library size selection successfully targeted full-length tRNAs. A small fraction of the reads, even those with a CCA tail, were truncated. These fragments (defined as having less than 70% hit coverage to a reference tRNA) appear to be largely generated from a subset of tRNAs, particularly certain nuclear tRNA-Thr and tRNA-Ala genes.
03 and adjusted R 2 = 0. 91; Figure  5 ). These data suggest that adapter ligation bias is not the primary determinant of tRNA-seq coverage skew as cDNA copy number in ddPCR is reflective of the number of final tRNA-seq Illumina reads. An additional source of sequencing bias could result from preferential RT of tRNAs with fewer modifications or less inhibitory secondary structures. In order to quantify tRNA abundance in totalcellular RNA without the intermediate step of RT, northern blot analysis was performed by probing for four A. thaliana tRNAs representing a range of CPM values from the tRNA-seq data. All four labeled probes were hybridized to three RNA replicates as well as a dilution series of a complementary oligonucleotide in order to quantify the tRNA signal (supp. Table  8 ). The tRNA-Pro gene with the highest CPM showed the weakest hybridization signal, and the highly expressed plastid tRNA-GlyGCC did not have the strongest intensity of the two plastid tRNAs probed (Figure  6 ).
Sequencing and read processing The nine original A. thaliana tRNA-seq libraries (three AlkB+, three AlkB-, and three entirely untreated) were single-indexed and sequenced on an Illumina MiSeq with single-end, 150 bp reads. Libraries from M. truncatula, O. sativa, S. tuberosum, and the A. thaliana D135S AlkB mutant and wild type AlkB libraries were dual-indexed and sequenced on an Illumina NovaSeq 6000 with paired-end, 150-base pair reads. Sequencing reads are available via the NCBI Sequence Read Archive under BioProject PRJNA562543. Adapters were trimmed using Cutadapt version 1. 16  (Martin 2011 ) with a quality-cutoff parameter of 10 for the 3¢ end of each read. A minimum length filter of 5 bp was applied to reads from the MiSeq sequencing platform. Read length filters of a minimum of 50 bp and a maximum of 95 bp were applied to reads produced from the NovaSeq 6000, as a much larger percentage of the reads from those libraries were <20 bp after adapter trimming.
For paired-end data, BBMerge from the BBTools software package was used to merge R1 and R2 read pairs into a consensus sequence  (Bushnell et al. 2017). Identical reads were summed and collapsed into read families using the FASTQ/A Collapser tool from the FASTX-Toolkit version 0. 0. 13 (http://hannonlab. cshl. edu/fastx_toolkit/index. html).
Sequence alignments and mapping Mapping for all processed and collapsed reads was performed with a custom Perl script using reference tRNA databases from the PlantRNA website (http://seve. ibmp. unistra. fr/plantrna/). Each collapsed read family was BLASTed (blastn, 1e-6) against a complete set of (non-identical) nuclear, mitochondrial and plastid reference tRNA sequences from the corresponding species, and the best match was assigned to each read family. The read count of all assigned read families was then summed for each reference sequence. When a read family was an equally good match to multiple references, the read count was divided by the total number of tied references. Multiple BLAST statistics were recorded for each read family/reference hit pair including e-value, hit score, hit length, and percent identity.
Generation of modification index In order to capture all possible misincorporations and indels including those that could have occurred at the end of the reads, a custom Perl script and the alignment software MAFFT version 7. 407  (Katoh et al. 2017 ) was used to produce full-length alignments of reads to their top BLAST reference tRNA hit and identify all base substitutions and indels in the resulting alignment. Only reads that BLASTed to their reference sequence with an e-value of 1e-10 or less and had 90% hit coverage to the reference were retained for modification index calling. Only positions that were covered by greater than five reads were used for modification index calling, and a position was considered confidently modified if ³30% of the mapped reads at that position differed from the reference nucleotide by either a substation or deletion.
Statistics and figure generation Differential expression analysis between the AlkB treated and untreated libraries in the original analysis as well as the wild type and D135S mutant AlkB libraries was done with the R package EdgeR version 3. 24. 3 (Robinson et al. 2010) , using a dataset with only reads that had 100% hit coverage to a reference sequence. A linear regression was performed in R with the lm function to test the relationship between tRNA-seq CPM values and ddPCR copy-number estimates per ng of input RNA. Fig. 1|  The proportion of tRNA-seq reads at different lengths based on isoacceptor family. Black dots represent the proportion of isoacceptor reference sequences at indicated length (e. g. 100% of the Ala-tRNA reference genes are 76 nt in length). Three biological replicates are plotted for each treatment (AlkB+, AlkB-and untreated).
Note that the dominant peak for read length often corresponds to the length of the reference sequence(s). Adjusted R 2 values for separate linear regressions on biological replicates 1, 2, and 3 were 0. 79, 0. 85, and 0. 96, respectively. When data points were averaged across biological replicates, linear regression yielded an adjusted R 2 of 0. 91 and a p-value of 0. 03. Fig. 6|  Northern blot analysis does not show the same expression dominance of nuclear tRNA-Pro and plastid tRNA-GlyGCC that was observed with tRNA-seq. Four different A. thaliana tRNA genes were probed from total cellular RNA and quantified. Each tRNA target membrane had three replicates of total A. thaliana RNA, which was quantified using a dilution series of a synthesized 38-nt oligonucleotide complementary to the corresponding probe.
ACKNOWLEDGEMENTS We thank  Deyu Li  for providing valuable guidance in optimizing the AlkB reaction and all of the research personnel at the  Institute of Molecular Biology of Plants  for graciously hosting J. M. W. We would also like to thank  Dr. Carol Wilusz  and  Adam Heck  for test RNA samples and valuable discussions, and  Dr. John Hunt  and  Dr. Victor Wong  at  Columbia University  for sending samples of AlkB for initial testing. This work was supported by a  Chateaubriand Fellowship  from the  Embassy of France  in the  United States , an  NSF   GAUSSI graduate research fellowship  ( DGE-1450032 ),  NSF  award  IOS-1829176 , and start-up funds from  Colorado State University.
Acknowledgements. We thank  Esmail Taghizadeh  and  Thomas Keller  ( University of Zurich ) for support with analyses and technical assistance. We also thank  Rahel Wanner  ( Zurich University of Applied Sciences ) for CHN-O analyses. Financial support. This research has been supported by the  Swiss National Science Foundation  (grant no. 200021_178768 ). Review statement. This paper was edited by  Jens-Arne Subke  and reviewed by two anonymous referees.
Data availability. The data related to this article are available at https://doi. org/10. 5281/zenodo. 4268490 (Schiedung and Abiven, 2020). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/bg-17-6457-2020-supplement. Author contributions. MS and SA designed the experiment. MS conducted the experiment, analyzed the data and wrote the manuscript. SA, SLB, GS and KK provided input to the data discussion and the manuscript. Biogeosciences, 17, 6457-6474, 2020 https://doi. org/10. 5194/bg-17-6457-2020.
Results Data coverage. The regional distribution of our new MBES bathymetry and backscatter data at 30 m grid resolution is shown in Fig. 2. All but the very shallowest seafloor is covered within a radius of ~45 km around the archipelago. Further afield, near-complete coverage was also achieved at the intersection of the TTFZ with the MAR. More scattered data were collected along regional tracks between seismological and electromagnetic ocean-bottom stations and on transits to the area  35, 36. We describe features of the seafloor in threespecific areas (see Figs. 2 3 4 5 6 7 8 ). Central area. On the main island's submarine flanks, the contour at 2000 meters below sea level (mbsl) is almost circular with a diameter of ~20km (Fig. 3a ). At this depth, a saddle to the southwest of the island connects the edifice to a plateau bearing the neighboring islands.
The edifice of Nightingale Island (Fig. 3 ; 37°26ʹS 12°29ʹW, ~2. 6 km 2 ) has a basal diameter of ~17km, encompassing steep slopes with angles at >15° very similar to those of TdC and Inaccessible Island. The new datasets reveal previously unknown features, including two submarine volcanoes to the southwest and southeast/east of Nightingale Island, named Rockhopper and Isolde Seamounts (Fig. 3 ). Rockhopper Seamount (37°34ʹS 12°45ʹW) has a basal diameter of about 20-22 km and rises to a depth of 470 mbsl at its summit, almost 2500 m above the adjacent seafloor (Fig. 4a, b ). The summit forms an NNW-SSE elongated ridge that is almost parallel to the region's abyssal hill fabric. A second, less prominent WSW-ENE striking ridge runs almost parallel to the TTFZ (Fig. 5 ). With >20°, the seamounts' slopes are considerably steeper than the slopes of the islands, but still within the range of oceanic shield volcanoes  16.
A sedimentary fan, characterized by low backscatter values (<-30dB), is imaged to the southeast of Rockhopper Seamount (Fig. 3 ). Isolde Seamount (37°26ʹS 12°20ʹW) has a basal diameter of 10 km and rises with slopes of ~18° to a depth of ~300 mbsl, about 1200 m above the seafloor in the saddle between it and Nightingale Island (Fig. 4c, d ). The summit lies on a ridge that is elongated ENE, almost parallel to the TTFZ. The data reveal the presence of a ~500 m-wide depression whose floor lies at ~550 mbsl, which we interpret as a summit crater. A more detailed survey would be necessary to test this interpretation. In addition to the new named seamounts, a small eroded plateau (4 × 4 km, with a basal diameter of 6 km) is mapped in water depths of 200-220 mbsl to the north of Nightingale Island and east of Inaccessible Island (37° 19ʹS 12°30ʹW) (Fig.
Northwest of Inaccessible Island, areas A and B in Fig. 5  show evidence for volcanic activity in the form of monogenetic volcanic cones, knolls, and lava flows. Whereas area B is characterized by the abundance of cones, area A is dominantly covered by lava flows, which are identifiable from higher backscatter intensities (Fig. 3b ) and from the sub-bottom profile P2 (see below). Further west, between 14°20ʹW and 13°20ʹW, the seafloor is marked by scattered small volcanic cones. Only a very few of these cones show summit crater structures. Some of the cones appear to have coalesced to form ridges. Our data reveal no evidence for the presence of major fault zones other than the TTFZ, which runs ENE-WSW across the deep seafloor south of the archipelago. There is little evidence for intraplate volcanic activity within the TTFZ itself, or further south of it.
Area of the westernmost volcanic cones. Figure  6  details the area of the TTFZ halfway between TdC and the MAR. This area is not yet fully covered by shipboard bathymetry, but the existing data allow some preliminary observations. The bathymetric data (Fig. 6a ) show undisturbed abyssal hill fabric away from the fracture zone, consisting of NNW-SSE orientated hills and ridges formed along the MAR over the past 5-20 Myrs  21, 22. The BTM clearly illustrates this pre-existing normal fabric (Fig. 6b ). Scat-tered small volcanic cones and W-E oriented ridges are visible along and near to the TTFZ, with decreasing number and frequency westward. Evidence for volcanic activity seems to extend out to 250 km westwards of the TdC island group (as far as ~14° 48ʹW), where we mapped a small volcanic cone on top of the abyssal hills of ~10 Myr-old oceanic crust  21, 22  just 130 km east of the MAR.
8a ). However, in the median valley of the MAR rift valley and the valleys marking the transform fault and fracture zone water depths are typically between 3000 and 4000 m, but reach more than 4800m in the nodal basin. Southeast of the eastern ridge-transform intersection at 38°25ʹS, 16°20ʹW, a newly discovered domal high rises to <2000 mbsl (Fig. 8a ). The dome surface displays several ENE-WSW orientated, spreadingparallel striations (Fig. 8b ), which are also well-imaged in the backscatter data (Fig. 8c ). The striations reach lengths of up to 17 km and are closely spaced, giving the surface a corrugated appearance. Corrugated surfaces like this were first interpreted by Cann et al. 41  as detachment faults bounded by active mid-ocean ridge and transform faults (at the socalled inside-corners of ridge-transform intersections), and termed oceanic core complexes (OCC).