dataesr/scientific-paragraphs-categorization huggingface dataset:
A successful assessment of trends for the upcoming 2014 WMO Ozone Assessment requires addressing the problems of time series artefacts due to changes in instrumentation, homogenizing applied satellite retrievals and reduce and describing measurement uncertainties. The SPARC/IO 3 C/IGACO-O 3 /NDACC (SI 2 N) Initiative has brought together scientists dealing with ground and satellite ozone profile measurements in order to consolidate efforts documenting long-term ozone profile changes. SI 2 N has also defined the time frame to ensure that any dataset improvements are finalized to ensure inclusion in the 2014 WMO Ozone Assessment analysis. This paper provides a summary of the most important available ozone datasets, describes measurement methods, detection limits and uncertainty estimates, gives details about the vertical and temporal resolution of individual datasets and provides references to relevant published work.
The vertical resolution decreases as a function of altitude ranging from several hundred meters at lower altitudes to several kilometers above 40 km (Table  1a , b; Fig. 3a ). The systematic uncertainty ranges from a few percent below 20 km to more than 10-15 % above 45 km  (Godin-Beekmann et al. , 2003). Ozone lidar measurements are self-calibrated. However, measurement stability can be affected by instrumental artifacts such as alignment error, changes in the intensity of the lidar signals due to varying laser power, or changes in weather conditions  (Godin-Beekmann et al. , 2003). There are twelve stratospheric ozone lidar instruments operational globally at this point (see Fig. 1 ), with the longest continuous records starting in the late 1980s  (Steinbrecht et al. , 2009). Data are archived in the NDACC database (see Table  1d  for the URL).
Back Close Full as the temperature or the instrumental line-shape (if not correctly determined), should also be considered in the upper layers  (García et al. , 2012). The ozone trends in  Vigouroux et al. (2008)  were calculated with a bootstrap resampling method, applied to the daily mean partial columns of the ozone time-series. This work was extended up to 2009 in the WMO 2010 Ozone Assessment report  (WMO, 2011)  for five European stations (28 • N to 79 • N). A current update up to 2012 is ongoing, involving additional stations, including stations in the Southern Hemisphere. The spectroscopic database has been changed to HITRAN 2008  (Rothman et al. , 2009) , and an additional effort of homogenization has been made in contrast to the work described in  Vigouroux et al. (2008) ; all stations are using a priori information from the model WACCM.
The length of the FTIR ozone time-series varies by station (see Fig. 1  for the geographical distribution of the stations); the longest time-series available starts in 1995, and the shortest in 2002 (Fig. 2 ; Table  1c ). In the coming years, more recently established observatory stations (e. g. Reunion Island: long-term measurements started in 2009; Toronto: regular data containing the 1000-1005 cm -1 range started in 2010) or stations that have not yet reprocessed their retrievals using the optimized common strategy (e. g. : Eureka, Bremen) could be included in ozone trends studies. The FTIR data not yet available on NDACC database (see Table  1d  for the URL) can be acquired by direct contact with the responsible Principal Investigator. There are currently 17 active long-term NDACC FTIR sites.
, 2002 (Sugita et al. , , 2006)). These validations showed that ILAS ozone data agreed with other data sets within ±10 % with a few exceptions between 11 and 64 km Figures (Table  1a , b). ILAS-II ozone data agreed with other data sets within ±10 % at altitudes between 11 and 40 km for the Northern Hemisphere. Above 41 km, a negative bias between the NH ILAS-II ozone data and the other data increased, reaching 30 % at 61-65 km. Southern Hemisphere ILAS-II ozone data agreed with other data sets within ±10 % at altitudes between 11 and 60 km. Since the solar-occultation technique is used with both ILAS and ILAS-II, the instruments are self-calibrated by measuring 100 % and 0 % intensity of the sun each time before and after the atmospheric measurement. ILAS ozone data are archived at the ILAS and ILAS-II webpages (see Table  1d  for URLs).
Below 12 km, meteorological results from the Canadian Meteorological Centre (CMC) operational weather analysis and forecast system are used (note that in version 3. 5 of the ACE-FTS retrievals, the CMC pressure and temperature results are used below 15 km,  Boone et al. , 2013). The resulting temperature and pressure profiles are the basis for retrieving VMR profiles of ozone and over 30 trace gas species. For the ozone retrieval, spectral features between 984 and 1190 cm -1 are used. The spectroscopic parameters on which the calculations are based are derived from the HIgh-resolution TRANsmission (HITRAN) molecular absorption database 2004 line list  (Rothman et al. , 2005). The version 2. 2 ozone updated (herein v2. 2) dataset was validated extensively by  Dupuy et al. (2009). In comparisons with ozonesondes and satellite limb sounding instruments, a small positive bias of +1 to +8 % (+5 % on average) was found between 16 and 44 km.
At altitudes above 45 km, larger differences of up to +40 % (+20 % on average) are found for the v2. 2 ozone profiles. The current version of the ACE-FTS dataset is version 3. 5  (Boone et al. , 2013). Waymark and colleagues (personal communication) have evaluated the differences between the well-validated v2. 2 and new v3. 5 profiles and found that there is a reduction of ≈ 5 % at altitudes above 35 km in v3. 5 compared to v2. 2. There is no error budget available for the ACE-FTS ozone product at present. However, there is an associated fitting uncertainty provided for each measurement. Introduction.
However, careful evaluation of possible drifts is needed since the signal to noise ratio is low with dim stars and the increasing amount of dark charge is known to cause problems despite the self-calibrating measurement principle. These problems are minimized by careful screening of the data for dim and cool stars. In addition to the nighttime occultation measurements discussed above, GOMOS has daytime occultation measurements (Table  1c ). Presently GOMOS daytime occultations are of poor quality (e. g. van Gijsel et al. , 2010). Daytime ozone profiles can, however, be derived from GOMOS measurements of scattered solar light  (Tukiainen et al. , 2011). These data are processed by the Finnish Meteorological Institute (FMI) and ozone profiles are available from the ESA SPIN project. All occultation measurements are available via the ESA EARTHNET webpage (see Table  1d.
LIMS The Limb Infrared Monitor of the Stratosphere (LIMS), an infrared, limb-emission instrument, operated on Nimbus 7 following its launch in late October 1978 through late May 1979, at which time its solid cryogen coolant was depleted (Fig. 2 ). The quality of the original LIMS Version 5 dataset is described in  Gille and Russell (1984)  and references therein. The LIMS retrieval algorithm uses a top-down onion-peeling approach and iterates to achieve a match of the calculated and measured limb radiances for its wide and narrow CO2 radiometer channels in the 15-micrometer region. A constant CO 2 volume mixing ratio profile of 325 ppmv is assumed for the radiance calculations in the upper stratosphere, where the forward models for the wide and narrow CO 2 channels are aligned and iterated.
Radiance profiles for the LIMS species channels are registered against the pressure profiles that are obtained in this manner. In order for the LIMS dataset to be more compatible with those from instruments of the UARS, Envisat, and the EOS satellite programs of more recent decades, LIMS profiles were retrieved anew using updated spectral line parameters for CO 2 and other species, including ozone, from the 1992 or 1996 HITRAN line lists  (Remsberg et al. , 2004). LIMS ozone profiles were obtained from infrared limb radiance measurements at 9 to 10 micrometers. The resultant LIMS Version 6 Level 2 profiles of temperature, species and height are tabulated at 18 levels per decade of pressure or at a spacing of 0. 88 km (Table  1a ). They have an effective vertical resolution of 3. 7 km, in order to account properly for the effects of the instrument on the observed radiances and of the retrieved temperatures on the retrieved ozone profiles (Table  1b ).
The Version 6 dataset was processed in 2002 and the Level 2 and 3 products are archived at NASA Goddard (GES DISC; see Table  1d  for URL). A more detailed description of the LIMS V6 ozone and its quality is provided in  Remsberg et al. (2007). Overall uncertainties for LIMS ozone range from 20-30 % in the lower stratosphere, to approximately 12 % in the mid-to upper stratosphere. Each measured, up/down horizon radiance scan pair included a view of its warm, internal blackbody, followed by a calibration measurement of cold space. Characteristics of the blackbody remained stable throughout the 7. 25 months of the LIMS mission. Most recently,  Remsberg et al. (2012)  reported on the assimilation of the LIMS V6 ozone into the GEOS-5 model of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) system.
UARS MLS The Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS) was one of ten instruments on the NASA UARS platform, launched on 12 September 1991  (Reber et al. , 1993, Fig. 2 ). UARS-MLS (a predecessor to Aura MLS) pioneered microwave limb sounding of the Earth's stratosphere and mesosphere from space (see  Barath et al. , 1993; Waters, 1993). UARS-MLS measured microwave emission near 205 GHz for its primary stratospheric ozone retrievals. The UARS orbit was inclined at 57 • and MLS data coverage was from 34 • on one side of the equator to 80 • on the other side, switching sides after each satellite yaw maneuver (which occurred roughly every 36 days). The measurements thus cover all local solar times during each "yaw period". Profiles were spaced ≈ 3-4 • along the orbit track and the average daily sampling in longitude is ≈ 12 • ; there are about 1350 profiles per day (Table  1c ).
MIPAS The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a limb emission, Fourier transform spectrometer  (Fischer et al. , 2008). Looking horizontally through the atmosphere at various elevation angles, it measured high-resolution, infrared emission spectra of atmospheric constituents, thus providing altitude-resolved information on these constituents. MIPAS was one of the atmospheric chemistry instruments on ESA's Envisat research satellite, which was launched into its sunsynchronous polar orbit on 1 March 2002. In March 2004, problems with the interferometer slide occurred and operation was interrupted, however on 27 January 2005 operation in the nominal mode was resumed with reduced spectral but improved spatial resolution (optimized resolution measurements). MIPAS provided data until 8 April 2012 when contact to the satellite was lost (Fig.
To this purpose, it uses the regularizing Levenberg Marquardt regularization inside the iterations and an a posteriori Tikhonov regularization with a self-adapting constraint that ensure that minimum constraints are used and the best vertical resolution obtainable from the measurements is achieved in all atmospheric conditions. ESA spectral resolution ozone data  (2002) (2003) (2004)  were validated by  Cortesi et al. (2007). A third MIPAS retrieval algorithm was developed at Oxford University (Moore and Remedios, 2010) and is based on the Optimal Estimation approach  (Rodgers, 2000). A fourth retrieval algorithm, GMTR, has been developed as a joint effort of the University of Bologna and ISAC-CNR  (Carlotti et al. , 2006). The algorithm performs simultaneous retrievals of pressure, temperature, water and ozone analyzing all the measurements acquired during a full Envisat orbit using a two dimensional approach.
The GMTR algorithm has been used to analyze the full MIPAS mission and the results are stored into the MIPAS2D database  (Dinelli et al. , 2010 (Dinelli et al. , , 2012)). All these algorithms use the same level-1b data, which is provided by ESA, but differ in some assumptions for the forward model and for the spectral intervals used in the analysis  (Laeng et al. , 2013). Recently the full validation of the ozone products of the four cited algorithms  (Laeng et al. , 2013) , an assessment of the long-term stability, and an assessment of the 10 yr trend of the IMK/IAA data product  (Eckert et al. , 2013)  have been completed. Overall uncertainties on the ozone profiles range from 35-40 % at 10 km to 8-11 % at around 30 km). Vertical resolution for optimized resolution phase (years 2005-2012) ranges from 2-2.
4 km at 10 km and 3. 2-3. 6 km at 30 km, to 5 km at 70 km. Vertical resolution for full resolution phase  (years 2002-2004)  ranges from 4 km around 10 km to 5 km around 30 km, to 8 km at 70 km (Table  1b ). In order to avoid artifacts in trend estimation from two data subsets of different characteristics resulting from the different measurement modes before and after 2004, a dedicated scheme has been developed that is immune to biases between data subsets  (von Clarmann et al. , 2010). The IMK/IAA MIPAS data are accessible at the IMK webpage (see Table  1d  for URL). The ESA MI-PAS data are accessible at the ESA webpage (see Table  1d  for URL). The MIPAS2D database is undergoing a validation process  (Casadio et al. , 2013) , but the data is accessible through the ISAC-CNR web site (see Table  1d  for URL).
e. every 0. 85 s). This leads to an excellent long-term stability of the measurements. There are no known signs of instrument degradation so far. Individual ozone profiles of the 501. 8 GHz band are quite noisy since they are derived from a relatively weak line, but averages agree reasonably well with correlative measurements  (Jones et al. , 2009). Other SMR ozone products such as from the strong ozone line in the 544. 6 GHz band (version -2. 0) are less noisy but have larger (known) biases. Data are available from the Odin-SMR webpage (see Table  1d.
2 ). The instruments are flown in sun synchronous polar orbits to obtain global coverage. Since the measurements rely on backscattered sunlight, data are taken only on the day lit side of each orbit and no data are taken during polar winter. The NOAA polar orbiting satellites were not exactly sun-synchronous and consequently drifted from near-noon orbits with NOAAs 9-14 drifting the most. NOAA-11 for example, drifted from an initial 1. 30 p. m. equator crossing time to a 5. 00 p. m. orbit in six years, returning as a morning orbit for the later part of the data record. Starting with NOAA-16 the orbital drift was partially mitigated, providing ≈ 5 yr of data before significant drift began. As the orbit drifts the solar zenith angle at which the measurements are made increases and latitude coverage decreases, which can be a problem for trend determination (Table  1c ).
The calibration of NOAA-17 SBUV/2 is used as the standard for NOAA-14, NOAA-16, and NOAA-18, while the NOAA-11 base calibration is used as the reference for the Nimbus-7 and NOAA 9 absolute calibrations. No instrument overlaps Nimbus-4 BUV; its absolute calibration is based on comparisons with ground-based instruments and has not changed in Version 8. 6. The primary data product for time series analysis is the monthly zonal-mean data, available at the NASA Goddard DISC webpage (see Table  1d  for URL). Validation of SBUV monthly zonal mean profiles  (Kramarova et al. , 2013b)  shows that the mean Figures biases and standard deviations are mostly within 5 % in the stratosphere between 25 and 1 hPa. The SBUV vertical resolution decreases in the lower stratosphere and troposphere, and as a result the SBUV smoothing error, defined as the component of vertical ozone variability that the observation system cannot measure, increases from < 1 % in the middle stratosphere up to 10-15 % in the lower stratosphere and troposphere.
Combining layers in the troposphere/lower stratosphere and above 1 hPa is recommended to limit smoothing errors, as described in  Kramarova et al. (2013a). In order to make the SBUV measurements accessible for trend analysis, it is necessary to combine the data from the different NOAA satellites. Two versions of a "merged" data set are available (NASA  Goddard, S. Frith, personal communication, 2013; NOAA CPC, J. Wild, personal communication, 2013). Both are described in more detail in the second and third SI 2 N overview papers  (Lambert et al. , 2013; Harris et al. , 2013).
SMILES The Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) was developed and operated under the cooperation of the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT)  (Kikuchi et al. , 2010). SMILES conducted its atmospheric observation from 12 October 2009 to 21 April 2010 (Fig. 2 ) on the Japanese Experiment Module (JEM) aboard the International Space Station (ISS). SMILES used three observation bands in the frequency regions of 624. 32-626. 32 GHz and 649. 12-650. 32 GHz. This instrument measured about 1600 profiles per day (both daytime and nighttime) within the latitude range of 38 • S -65 • N. Owing to the non-sun-synchronous orbit of the ISS, measured the atmosphere at different local times. This dataset provides unprecedented opportunities to study diurnal ozone variations throughout the stratosphere  (Imai et al.
Summary This paper describes long-term ozone profile data derived from five of the most common ground-based systems and 19 satellite-based instruments. The physical principles of measurements, specifics of data retrievals and uncertainties of measurements have been described in more detail in various publications and reports with relevant references given in this paper. Therefore, the goal of this paper is to provide an overview of well-established ozone records, while also offering updated information on recently reprocessed and newly available data sources. The summary includes links to data archives, lists uncertainties of measurements and retrievals, provides spatial and temporal characteristics of the datasets described above and indicates the latest released data version (see Table  1d , the numbers given are indicative or typical values).
gsfc. nasa. gov/shadoz/Dobson/Brewer Described in: Petropavlovskikh et al. (2005) WOUDC, Toronto, Canada: http://www. woudc. org/data_e. htmlLidar Depends on each lidar system. NDACC website: Nair et al. (2013) http://www. ndacc. orgFTIR Described in: Vigouroux et al. (2008) NDACC website: (not available at this point) http://www. ndacc. orgMicrowave Version 6. See Boyd et al. (2013) NDACC website: Boyd et al. (2013) http://www. ndacc. orgSpecial Lauder and  Mauna Loa  hourly processed datasets available on request from PI. Satellite-based measurement systems  SAGE Version 7 Atmospheric Science Data Center, NASA Langley. Damadeo et al. (2013) http://eosweb. larc. nasa. gov/project/sage2/sage2_v7_tableHALOE Version 19 ozone is described briefly in Randall et al. (2003). NASA Goddard Earth Sciences Data & Information Services Center (GES DISC ): http://daac.
Observations and analysis Data presented here are from a high altitude balloon flight of the Jet Propulsion Laboratory (JPL) Submillimeterwave Limb Sounder (SLS) instrument from the Columbia Scientific Balloon Facility site at Ft. Sumner, New Mexico, USA (34 • N, 104 • W). On-board the gondola, in addition to the SLS, were the JPL MkIV solar occultation Fourier transform infrared spectrometer  (Toon, 1991)  and in situ O 3 sensor  (Proffitt and McLaughlin, 1983). The balloon was launched on 22 September 2011, reached float altitude of approximately 39 km at 13:30 local time and remained above 37 km through the flight until flight termination the next day. Spectra covering the BrO band were collected upon reaching float altitude on 22 September until 04:00 on 23 September. The Submillimeter Limb Sounder is a heterodyne radiometer that measures molecular rotational thermal emission spectra from a limb observing geometry.
In Fig. 7 , we compare the MLS BrO zonal (25 • N to 35 • N) bi-monthly mean (blue line) of day-night retrieved profiles using the new algorithm described in  Millán et al. (2012). The date range of MLS data is centered on the balloon flight date, 22 September 2011. The MLS retrieval profile precision bound for the bi-monthly mean is shown as blue-dashed lines. In Fig. 7 , we also show the MLS BrO profile for September 2005 from  Kovalenko et al. (2007)  which was derived using a slightly different retrieval procedure. For both MLS retrieval cases, the pressure range over which the data are useful is 10 hPa to 4. 6 hPa (approximately 30 km to 37 km) which is indicated on the plot by closed circles, and open circles outside this range. Agreement between both MLS and SLS profiles is generally good and within the MLS precision bounds at all altitudes.
Organics Br y  (Wamsley,1998)  Fig. 9. Comparison of Br y mixing ratio scaled from SLS measured BrO (black) using the UC Irvine photochemical box model against Br y inferred from MLS BrO for 2005  (Millán et al. , 2012). The range of scientifically useful MLS measurements (10 to 4. 6 hPa) is indicated by solid circles. Uncertainties in Br y are indicated by dashed black and dashed red lines for SLS and MLS, respectively. Br y from long-lived organic gases from  Wamsley et al. (1998)  scaled to 16 ppt for an age-of-air of 5 yr (  2006 ) is also plotted (cyan curve). Closest available JEM-SMILES BrO data, matching season and local time of the SLS balloon flight, are from October 2009. Data presented here are from the JEM/SMILES operational products version 2. 3  (Takahashi et al. , 2011; Mitsuda et al.
, 2011). Figure  10  compares SLS results with daily averaged SMILES BrO profiles (blue lines) for October 12 (49 profiles), 13 (40 profiles), 14 (55 profiles) and 15 (61 profiles) in 2009 with local time between 11:00 and 16:00 and with latitude between 25 • N and 40 • N. These data are bias-corrected by subtraction of the mean night-time BrO profile for 12 to 23 October. Local solar times for the selected SMILES overpasses were sufficiently close to the SLS measurement time to make the diurnal correction negligible compared to the combined measurement uncertainty. The RMS variation in the daily averaged SMILES BrO profiles is shown as bluedashed lines in Fig. 10. We find excellent agreement between SMILES and SLS profiles above 20 km and at other altitudes agreement agreement is well-within the combined uncertanity bounds.
Acknowledgements. Research at the  Jet Propulsion Laboratory, California Institute of Technology , is performed under contract with  NASA. We thank and acknowledge the  NASA Earth Science Mission Directorate  for support of this research. We acknowledge and thank the  NASA Columbia Scientific Balloon Facility ,  Palestine Tx , for balloon launch, telemetry and payload recovery support. We thank the  MLS instrument team , the JEM/SMILES instrument and L2 data processing teams for providing the satellite datasets. JEM/SMILES mission is a joint project of  Japan Aerospace Exploration Agency (JAXA)  and  National Institute of Information and Communications Technology (NICT). Edited by:  M. Van Roozendael.
However, the complementarity of constraints among different observables can be exploited to reduce considerably the parameter space. In this respect, the inclusion of the isospin asymmetry of B → K * γ, together with the forward-backward asymmetry A FB and the longitudinal polarization fraction F L in B → K * + -integrated over the dilepton invariant mass q 2 between 1 and 6 GeV 2 already impose additional nontrivial constraints on the C 7 -C 7 plane, as well as on C ( )  9  and C ( ) 10  [6, 7]. This complementarity can be exploited further by considering the q 2 -dependence of angular B → K * + -observables. Indeed, increasingly precise measurements of these observables integrated in smaller bins are being presented, due in part to the important statistics obtained from the large data sets collected at the LHCb experiment.