dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions Wintertime DINEOF reconstructions of the Pathfinder v5. 2 1981-2010 SST data and the combined 2002-2010 Pathfinder v5. 2 and AMSR-E SST data were validated using in situ data. Similar verification indices were deduced for both the combined and non-combined DINEOF reconstructions. This means that, when available, microwave SST images could be used as a complementary source of information when reconstructing infrared SST images, allowing a major percentage of SST images to be reconstructed. The IPC-Navidad was found to be well determined by the first mode (49 % of the variance) of a PCA analysis conducted on the reconstructed 1981-2010 Pathfinder v5. 2 SST data and the 2002-2010 combined Pathfinder v5. 2 and AMSR-E SST data, restraining the SST to shelf and shelfbreak areas in both cases.
The combined use of a missing data reconstruction technique (DINEOF) and a statistical analysis (PCA), has allowed an objective deduction of the variability of this processes during the 1981-2010 winters for the first time at a daily scale. Future directions of the work presented here should deal with three main issues. First, an effort should be made to increase the number of days included in the objective deduction of the IPC-Navidad signal by increasing the number of SST images that is reconstructed. Although limited to the last decade, the joint use of infrared and microwave SST images has been shown to be a valuable alternative in this sense. An alternative reconstruction strategy using SST and SLA data jointly, which would be valuable for the 1992-2010 period, was also proposed in the discussion.
A more general approach covering the entire period analysed could also be the use of in situ data from ICOADS and WOD datasets to try to reconstruct the images that cannot be reconstructed by means of the DINEOF technique. This procedure, if successful, could also allow us to go further back in time to the period where satellite SST retrievals are not available but in situ data exist. The second main issue that future works should deal with is the improvement of the de-tection of the IPC-Navidad signal in the reconstructed SST data, especially for most cloudy winters and those with weak IPC-Navidad events. Working lines in this topic should include a more effective removal of the seasonal signal of the IPC-Navidad from the climatology used to deduce the SST anomalies. Other alternatives to the PCA approach used here, like the joint detection of the IPC-Navidad signal in SST and SLA data using a combined PCA or CCA (Canonical Correlation Analysis) techniques proposed in the discussion, could be valuable tools.
Acknowledgements. ERA-Interim data were obtained from the  ECMWF data server  (http://data. ecmwf. int/data). Pathfinder v5. 2 data were provided by  GHRSST  and the  US National Oceanographic Data Center. AMSR-E data are produced by  Remote Sensing Systems  and sponsored by the  NASA Earth Science MEaSUREs DISCOVER Project  and the  AMSR-E Science Team. Data are available at www. remss. com. The altimeter products were produced by  Ssalto/Duacs  and distributed by Aviso, with support from  Cnes  (http://www. aviso. oceanobs. com/duacs/). ICOADS data for this study have been retrieved from the  Research Data Archive (RDA)  which is maintained by the  Computational and Information Systems Laboratory  (CISL) at the  National Center for Atmospheric Research (NCAR). Word Ocean Database data were obtained from http://www.
nodc. noaa. gov/OC5/WOD/prwod. html. DINEOF source code is freely available at http://modb. oce. ulg. ac. be/mediawiki/index. php/DINEOF. G. Esnaola is supported by a research grant ( Interacción Atmósfera-Océano  en el  Golfo de Bizkaia ) from  Fundación Centros Tecnológicos Iñaki Goenaga. Jon Sáenz  would like to thank the financial support from project  CGL2008-03321  ( Spanish National R+D+I  Programme). He also thanks funding provided by the  University of the Basque Country  ( UFI 11/55 ,  PPH12/01  and  GIU 11/01 ). The  Basque Government  ( Department of Agriculture, Fisheries and Food ) has funded the project VARIACIONES. The authors want to express their gratitude to  A. Caballero  from  AZTI-Tecnalia  for her help with the Altimetry data and to  B. Le Cann  from  UBO-CNRS-IRD-IFREMER  for his useful comments on an early draft of this document.
satellite data in the reconstruction does not have a negative impact in its quality, but it increases the number of reconstructed days from 418 to 460. The results shown in Table1correspond to the reconstructions based on quality flag 7 Pathfinder database values. 1981-2010 Pathfinder 2002-2010 Pathfinder 2002-2010 Pathfinder/AMSR-E SATELLITE DINEOF SATELLITE DINEOF SATELLITE DINEOF Days 1256 (35. 5 %) 1256 (35. 5 %) 418 (40. 9%) 418 (40. 9 %) 460 (45. 0 %) 460 (45. 0 %) N 8807 42 458 2832 16 733 2919 18 336 BIAS( • C) -0. 19 -0. 31 -0. 18 -0. 32 -0. 18 -0. 31 MAD( • C) 0. 47 0. 46 0. 24 0. 27 0. 24 0. 26 microwave.
With such an extension, it is possible to export a same model as SFM system input. It is also possible to generate theoretical models from the Arpenteur 3D platform  (Drap & Grussenmeyer, 2001 ) by navigating within an already oriented model and by generating theoretical photographs using a modified screenshot module that store the rendered image but also the camera position and its intrinsic parameters. With the availability of theoretical models as input of photogrammetric systems, we can evaluate them by comparing their results with the original model. This evaluation takes into account the orientations of the photographs and the projections of the 3D points. It is so possible to quantify the difference between computed models and the reference. We illustrate the use of theoretical models for validation of photogrammetric processes from three tools: PhotoModeler©, SFM Toolkit and Agisoft© Photoscan®.
They are the common perpendicular to the left (respectively right) null-vectors of the three matrices T 1 , T 2 and T 3. So, we cannot evaluate the metric accuracy without control points in the scene, for this reason, we use several spheres with known position in space to obtain an Absolute Orientation, using these points in the final BA (see Figure  11 ). These control points will help us to compare the accuracy of the produced 3D model with Arpenteur framework and to compare it with models obtained with: Agisoft or Visual SFM. In (Lo Brutto, 2012) authors evaluate the performance of several softwares and 3D web services to analyse the accuracy of 3D models. We have to note that the only error introduced in the model is the Control Point Identification on the photograph in the Photoscan software by Agisoft.
, 2011; van Huissteden et al. , 2011; Belshe et al. , 2012). However, the smallest water bodies (< 0. 01 ha), which are most subject to thawing and transformation  (Pokrovsky et al. , 2011) , fall below the resolution threshold of these models, and these water bodies are not present on available topographic maps or detected by remote techniques. These small aquatic systems, which are not yet included in the global database, potentially make a large overall contribution to the hydrological balance  (Lehner and Doll, 2004; Downing et al. , 2006). Similar to small boreal lakes that regulate C stocks and accumulation rates in permafrost-free regions (e. g. ,  Ferland et al. , 2012 and references therein) , small thaw ponds in western Siberia represent important stocks of dissolved and colloidal organic carbon (OC) and trace elements (TE) and contribute significantly to fluxes of CO 2 and CH 4 in the atmosphere  (Shirokova et al.
The ANOVA test was carried out with a oneway analysis of variance by using the Dunn's method due to the different number of samples for each year (SigmaPlot version 11. 0/Systat Software, Inc). In this method, P < 0. 05 means the difference in the median values is important and statistically significant. On the other hand, P > 0. 05 means that the differences in the median values are not statistically significant and they may stem from random sampling variability. In addition, a Sign test adopted from Rijsbergen (1979) was used to assess global differences in all averages of lake water composition parameters measured during two different years.
Acknowledgements. We thank two anonymous reviewers for their constructive comments. Yves Auda  and  Aridane Gonzalez  are thanked for the help with statistics. This work was supported by the  Mega-grant 220 of Russian Ministry of Education and Research and Tomsk State University "BIO-GEO-CLIM " No  14. B25. 31. 0001 , ANR  " Arctic Metals", GDRI "Carbon in Wetlands of Siberia", Programs of Presidium RAS  (No  12-P-5-1021 ) and  UroRAS  (No  12-Y-5-1034 ). Edited by: P. Stoy The publication of this article is financed by  CNRS-INSU.
2007) , thus demonstrating that uncertainties possibly due to the biochronologic framework induce no noticeable bias on long-term analysis of the fossil record. However, the potential impact of these uncertainties when compar-ing the provincial communities' evolutionary patterns is discussed in detail below (see 'Biochronologic issues and broad spatiotemporal patterns' section). The data-set used in this study includes localities covering Europe from the western Iberian peninsula to Greece (including Crete), via northern Europe. The former Yugoslavia was excluded from the database because this region contains too few localities, and the western part of the former Soviet Union was excluded because more work on standardisation of taxonomies needs to be done in this region in order to allow comparisons with the rest of Europe.
Data-set A compilation of 657 localities that yielded rodents was undertaken and recently updated. Synonymies were corrected to make sure that any given species or lineage had the same name throughout the database. This work of systematic standardisation was made using published systematic revisions of small mammals  (Mein and Freudenthal 1971; Freudenthal et al. 1992; Daams and de Bruijn 1995; Ro ¨ssner and Heissig 1999). When no such revision was available, the point of view of the original author(s) was followed. Then all of the localities from the same region (or sedimentary unit) and biochronological unit were grouped into a regional synthetic set. Following the work of standardisation and compilation, it was necessary to select the regional data-sets in order to avoid biases such as insufficient sampling effort.
Temporal analysis Because the fossil record is not continuous, neighbouring regions presenting similar faunal assemblages have been grouped into provinces. Temporal evolution can then be compared across communities based on the familial species richness percentages for the five provinces presenting the longest fossil record. In order to describe and follow changes in their composition, biochronological units have been clustered based on the species richness per categories, using the program PAST  (Hammer et al. 2001). This was done using an unweighted pair-group algorithm based on the average correlation between the proportions of any two given assemblages, used as a similarity measure between each pair of biochronological units. The clustering has been constrained by the chronological order of the biochronological units (allowing only adjacent units to be joined during the agglomerative clustering procedure).
15. 0 Ma), even though they seem less important than the previous ones based on the number of species involved  (Fortelius et al. 1996). The next major change occurs during the early Late Miocene, between MN9 and MN10 (ca. 9. 7 Ma). It is, however, not significant based on the results of the Mantel test for the Peri-Carpathian province. The main migration event occurring at the beginning of the Late Miocene is the arrival of the first true murines (MN9, ca. 11. 1-9. 7 Ma). Interestingly, this event does not significantly affect all the assemblages (only four MN9 localities in our database yielded murine specimens: Priay B, Castelnou 1B, Pedregueras 2C and Can Llobateres 1). Instead, the next break in their composition occurs later, between MN9 and MN10 (ca. 9. 7 Ma). This is roughly coeval with the socalled Vallesian Crisis, showing the replacement of forestdominated environments by more open landscapes in western Europe  (Agustı ´and Moya-Sola1990 ).
Acknowledgements The results stem in part from the PhD thesis of O. M which was supported by the  French Ministry of Education and Research. O. M. 's present research is currently supported by a  Lise Meitner fellowship  from the  Austrian Science Fund  ( FWF-M1375-B17 ). The authors are also grateful to  G. Escarguel  and  M. Hugueney  who contributed to this work through most instructive discussions and comments on earlier drafts of this paper. C. Sullivan  and  D. Hone  also kindly helped to improve the English text. The comments of several anonymous reviewers also contributed to improving this study.
Secondary and back-scattered electron detector mode scanning electron microscopy images, as well as Energy Dispersive X-ray analysis were performed using a Quanta 200 scanning electron microscope with a voltage of 25 Kv. Raman spectra were obtained with a confocal microspectrometer SENTERRA (Bruker Optics, Ettlingen, Germany) equipped with a 532 nm exciting line (spectra acquired with 2 mW laser power, 20 coadditions of 10 s excitation with a 50x1000 µm slit) and automatically compared with the Rruff database  [99].
Research at Fumane is coordinated by the  Ferrara University  in the framework of a project supported by the  Italian Ministry of Culture -Veneto Archaeological Superintendence , public institutions ( Lessinia Mountain Community -Regional Natural Park, Fumane Municipality, Veneto Region -Department for Cultural Heritage, Max Planck Institute for Evolutionary Anthropology ), and private associations and companies ( National Geographic Society -CRE  Grant  9022-11 ,  Cariverona Foundation ,  Banca di Credito Cooperativo della Valpolicella ,  Roberto Gardina  & C. , Albino Armani Vinegrowers since 1607 and others). Microscopic study of the shell and elemental and mineralogical analysis of the pigment were funded by the  European Research Council (ERC)  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013/ERC  grant agreement no.
Coupled models still display major SST biases in the equatorial Atlantic, inducing a systematic southward shift of the monsoon. Because of these strong biases, the monsoon is further evaluated in SST-imposed simulations along the 108W-108E African Monsoon Multidisciplinary Analysis (AMMA) transect, across a range of time scales ranging from seasonal to intraseasonal and diurnal fluctuations. The comprehensive set of observational data now available allows an in-depth evaluation of the monsoon across those scales, especially through the use of high-frequency outputs provided by some CMIP5 models at selected sites along the AMMA transect. Most models capture many features of the African monsoon with varying degrees of accuracy. In particular, the simulation of the top-of-atmosphere and surface energy balances, in relation with the cloud cover, and the intermittence and diurnal cycle of precipitation demand further work to achieve a reasonable realism.
2011 ). Among these sites, 11 were defined in coordination with the AMMA community along the AMMA transect, 3 of them corresponding to the supersites mentioned above. In addition, the availability of new spaceborne measurements from active sensors as part of the afternoon satellite constellation (A-Train) opens the path for the establishment of global climatologies of the three-dimensional distribution of clouds (e. g. ,  Bouniol et al. 2012). The availability of these new datasets and new outputs at selected sites from CMIP5, as well as the better understanding of some key processes at work in the WAM system, provides a unique opportunity to evaluate more in depth the WAM representation by climate models. In the present work, we seek to capitalize on this AMMA legacy, and to provide a process-oriented analysis of CMIP5 simulations.
The paper is organized as follows: Section 2 describes the datasets used for the CMIP5 model evaluation. In section 3, the long-term variability of the WAM is assessed from CMIP3 to CMIP5 models. Section 4 evaluates the representation of the WAM mean state and seasonal evolution in both coupled and SST-forced simulations. Section 5 addresses a more physical evaluation of monsoon processes, with an emphasis on the intraseasonal and diurnal scales of the water cycle. Finally, conclusions are given in section 6.
A full description of the CMIP3 framework and a comprehensive assessment of the models can be found in  Meehl et al. (2007b). Integrations of 18 CMIP3 models are used here. They were made available to the community by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) through their website (wwwpcmdi. llnl. gov/ipcc/model_documentation/ipcc_model_ documentation. php), where a detailed description of the models can be found. (All model names referred to in this paper are expanded in full in the appendix. ) The simulations performed as part of CMIP5 and used in the present study are listed in Table  1. They were made available on the Earth System Grid (ESG; http:// cmip-pcmdi. llnl. gov/cmip5/index. html) data archive. The different types of integrations of the CMIP5 framework are described in  Taylor et al.
b. Decadal and interannual rainfall variability over the Sahel The Sahelian rainfall exhibits a large variability at decadal and interannual time scales. To address these scales, the time series of the Sahel precipitation P was decomposed into a decadal component P 9 and an interannual fluctuation dP, such that P 5 P 9 1 dP. The quantity P 9 is defined as the 9-yr running mean of the raw series. Figure  3a  illustrates the observed raw and filtered time series of precipitation averaged over (108-188N, 08-108E) for both the Climatic Research Unit (CRU) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) datasets (see Table  3 ). The Sahelian drought is clearly identified after 1973, with a partial recovery in the recent years. Although this recovery is not homogeneous over the entire Sahelian belt,  Lebel and Ali (2009)  show a clear signal over this central Sahel domain.
larc. nasa. gov). d The National Aeronautics and Space Administration (NASA)-Global Energy and Water Cycle Experiment (GEWEX) surface radiation budget (SRB) consists of top-of-atmosphere and surface radiative fluxes. Two sets of surface radiative flux estimations are available, based on different algorithms, known as primary (SRB3pr) and Langley parameterized algorithms (SRB3qc). More information on these two datasets is available at http://gewex-srb. larc. nasa. gov/index. php. e Bamba (17. 18N, 1. 48E, 2004-07) ,  Agoufou (15. 348N, 1. 488E, 2002 -08), Wankama (13. 678N, 2. 658E, 2005-06)  dots). The relative change between these two periods ranges between 10% in the CRU dataset and 24% in the CMAP dataset. Despite a large dispersion, one-half of the models capture the tendency to rainfall recovery.
1) PRECIPITATION Figure  6  shows JAS precipitation averaged from 1979 to 2008 between 108W and 108E for each model and observational dataset introduced in section 2. Even though the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) datasets do not cover the same period, they provide similar results along this transect, the sensitivity to the exact chosen period being much smaller than the typical model biases (not shown). Following the previous section and Fig. 5 , models have been separated into  FIG. 4. (Continued)  two subsets according to their mean temperature over the Sahara: the warm (Fig. 6a ) and the cold (Fig. 6b ) models. Overall, models capture the large-scale precipitation maximum over the continent near 108-118N. About one-third of the models (BCC-CSM1.
g. ,  Fink and Reiner 2003; Kiladis et al. 2006; Thorncroft and Rowell 1998). In particular,  Ruti and Dell'Aquila (2010)  showed that models characterized by a weak meridional temperature gradient are unable to feed these synoptic disturbances. A strong gradient, however, is not a necessary condition for arising waves. Over the Sahara, the near-surface temperature in CMIP5 models exhibits a large spread, which reaches almost 7 K near 258N (Fig. 7 ). This spread starts to develop in the southern Sahel, around 108N, and extends up to the northern coast of Africa at 358N. Unfortunately the dispersion is as large as in observational datasets and reanalyses. This reflects the sparse coverage of in situ observations over the Sahara, and precludes detailed model evaluation there. The surface energy budget over the Sahara discussed at the end of this section provides further insight into the origin of this spread within the CMIP5 ensemble.
Up to 158N, observations and reanalyses are in better agreement and the spread among models is weaker, although about one-third of CMIP5 models are still too cold by 2-3 K [BNU-ESM, CCSM4, CESM1(CAM5), CNRM-CM5, EC-EARTH, GFDL-HIRAM-C180 and -C360, MRI-AGCM3. 2S, and NorESM1-M], and one is too warm by 2-3 K (MRI-CGCM3). 3) CLOUDS AND THEIR RADIATIVE EFFECT  Bouniol et al. (2012)  analyzed the cloud cover mean properties over the Sahel with the AMF data of Niamey. They identified four cloud categories: clouds associated with convective systems and low-, mid-, and high-level clouds, in agreement with  Slingo (1980). Using CloudSat.
2012). The representation of aerosols may also explain a large part of the spread. Meridional fluctuations of the longwave incoming radiation at the surface are weaker. It increases from the more humid and cloudier Gulf of Guinea to the drier Sahara at 208N by 10-20 W m 22. Note, however, that the atmosphere warms and loads with aerosols along this direction. Several models simulate this weak gradient, ). The black square with error bars is the mean obtained from observational datasets (i. e. , SRB3pr, SRB3qc, and CERES-EBAF for radiative fluxes, and ERAI, MERRA, and CFSR for the 2-m temperature). The warmer (colder) models are indicated with dots (filled square). with departures less than 20 W m 22. Farther north, biases in the longwave incoming surface radiation increase significantly and reach the same order of magnitude as in the shortwave, especially in the colder models (Fig.
c. The annual cycle of the WAM At the seasonal time scale, the West African monsoon is characterized by a northward migration of the ITCZ with an abrupt climatological shift in early summer  (Sultan and Janicot 2000, 2003) , culminating in August, and by a smoother southward withdrawal of the rainfall band in September and October. The monsoon onset time is consistent in the two observational datasets (Figs. 12a, b ). It is well marked by a transition between a maximum of precipitation along the Guinean coast in May-June and a second one centered near 128N in August. In between, a minimum of rainfall occurs over the whole region as the ITCZ moves northward. Presumably because the monsoon is primarily forced by the annual excursion of the sun, most models capture the ITCZ summer migration, although with varying degrees of accuracy.
The annual cycle of temperature over West Africa is also characterized by a northward migration of the temperature maximum during spring and summer and a southward retreat at the end of August  (Ramel et al. 2006). Two annual maxima can be identified (Fig. 13a ). The first one occurs over the Sahel during May-June, prior to the monsoon rainfall onset, when the soil is still very dry, and typically at the time of the establishment of a humid low-level monsoon flow in the Sahel  (Slingo et al. 2009; Guichard et al. 2009). Then, the summer rainfall over the Sahel leads to enhanced surface evapotranspiration  (Timouk et al. 2009 ) and to an overall cooling at the surface. The second maximum occurs over the Sahara, near 278-288N at the end of July, one month after the insolation maximum. The annual cycle depicted by the CRU, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim), and Modern-Era Retrospective Analysis for Research and Applications (MERRA; not shown) datasets is very consistent.