Ugo Cortesi

Dr. Ugo Cortesi

Institute for Applied Physics “Nello Carrara” (IFAC-CNR), 50019 Sesto Fiorentino (Firenze), Italy
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Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 June 2016 in Atmospheric Measurement Techniques
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DHDaan Hubert
Daan Hubert
JLJean-Christopher Lambert
Jean-Christopher Lambert
TVTijl Verhoelst
Tijl Verhoelst
JGJosé Granville
José Granville
Arno KeppensArno Keppens
Arno Keppens
JZJoseph M. Zawodny
Joseph M. Zawodny
The ozone profile records of a large number of limb and occultation satellite instruments are widely used to address several key questions in ozone research. Further progress in some domains depends on a more detailed understanding of these data sets, especially of their long-term stability and their mutual consistency. To this end, we made a systematic assessment of 14 limb and occultation sounders that, together, provide more than three decades of global ozone profile measurements. In particular, we considered the latest operational Level-2 records by SAGE II, SAGE III, HALOE, UARS MLS, Aura MLS, POAM II, POAM III, OSIRIS, SMR, GOMOS, MIPAS, SCIAMACHY, ACE-FTS and MAESTRO. Central to our work is a consistent and robust analysis of the comparisons against the ground-based ozonesonde and stratospheric ozone lidar networks. It allowed us to investigate, from the troposphere up to the stratopause, the following main aspects of satellite data quality: long-term stability, overall bias and short-term variability, together with their dependence on geophysical parameters and profile representation. In addition, it permitted us to quantify the overall consistency between the ozone profilers. Generally, we found that between 20 and 40 km the satellite ozone measurement biases are smaller than ±5 %, the short-term variabilities are less than 5–12 % and the drifts are at most ±5 % decade−1 (or even ±3 % decade−1 for a few records). The agreement with ground-based data degrades somewhat towards the stratopause and especially towards the tropopause where natural variability and low ozone abundances impede a more precise analysis. In part of the stratosphere a few records deviate from the preceding general conclusions; we identified biases of 10 % and more (POAM II and SCIAMACHY), markedly higher single-profile variability (SMR and SCIAMACHY) and significant long-term drifts (SCIAMACHY, OSIRIS, HALOE and possibly GOMOS and SMR as well). Furthermore, we reflected on the repercussions of our findings for the construction, analysis and interpretation of merged data records. Most notably, the discrepancies between several recent ozone profile trend assessments can be mostly explained by instrumental drift. This clearly demonstrates the need for systematic comprehensive multi-instrument comparison analyses.

16 January 2009 in Atmospheric Chemistry and Physics
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EDE. Dupuy
E. Dupuy
KWK. A. Walker
K. A. Walker
JKJ. Kar
J. Kar
CBC. D. Boone
C. D. Boone
CMC. T. McElroy
C. T. McElroy
JZJ. M. Zawodny
J. M. Zawodny
This paper presents extensive {bias determination} analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45–60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (~35–55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45–55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.

21 September 2007 in Atmospheric Chemistry and Physics
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Ugo CortesiUgo Cortesi
Ugo Cortesi
JLJ. C. Lambert
J. C. Lambert
CCC. De Clercq
C. De Clercq
GBGiovanni Bianchini
Giovanni Bianchini
TBT. Blumenstock
T. Blumenstock
SWS. Wood
S. Wood
The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), on-board the European ENVIronmental SATellite (ENVISAT) launched on 1 March 2002, is a middle infrared Fourier Transform spectrometer measuring the atmospheric emission spectrum in limb sounding geometry. The instrument is capable to retrieve the vertical distribution of temperature and trace gases, aiming at the study of climate and atmospheric chemistry and dynamics, and at applications to data assimilation and weather forecasting. MIPAS operated in its standard observation mode for approximately two years, from July 2002 to March 2004, with scans performed at nominal spectral resolution of 0.025 cm−1 and covering the altitude range from the mesosphere to the upper troposphere with relatively high vertical resolution (about 3 km in the stratosphere). Only reduced spectral resolution measurements have been performed subsequently. MIPAS data were re-processed by ESA using updated versions of the Instrument Processing Facility (IPF v4.61 and v4.62) and provided a complete set of level-2 operational products (geo-located vertical profiles of temperature and volume mixing ratio of H2O, O3, HNO3, CH4, N2O and NO2) with quasi continuous and global coverage in the period of MIPAS full spectral resolution mission. In this paper, we report a detailed description of the validation of MIPAS-ENVISAT operational ozone data, that was based on the comparison between MIPAS v4.61 (and, to a lesser extent, v4.62) O3 VMR profiles and a comprehensive set of correlative data, including observations from ozone sondes, ground-based lidar, FTIR and microwave radiometers, remote-sensing and in situ instruments on-board stratospheric aircraft and balloons, concurrent satellite sensors and ozone fields assimilated by the European Center for Medium-range Weather Forecasting. A coordinated effort was carried out, using common criteria for the selection of individual validation data sets, and similar methods for the comparisons. This enabled merging the individual results from a variety of independent reference measurements of proven quality (i.e. well characterized error budget) into an overall evaluation of MIPAS O3 data quality, having both statistical strength and the widest spatial and temporal coverage. Collocated measurements from ozone sondes and ground-based lidar and microwave radiometers of the Network for the Detection Atmospheric Composition Change (NDACC) were selected to carry out comparisons with time series of MIPAS O3 partial columns and to identify groups of stations and time periods with a uniform pattern of ozone differences, that were subsequently used for a vertically resolved statistical analysis. The results of the comparison are classified according to synoptic and regional systems and to altitude intervals, showing a generally good agreement within the comparison error bars in the upper and middle stratosphere. Significant differences emerge in the lower stratosphere and are only partly explained by the larger contributions of horizontal and vertical smoothing differences and of collocation errors to the total uncertainty. Further results obtained from a purely statistical analysis of the same data set from NDACC ground-based lidar stations, as well as from additional ozone soundings at middle latitudes and from NDACC ground-based FTIR measurements, confirm the validity of MIPAS O3 profiles down to the lower stratosphere, with evidence of larger discrepancies at the lowest altitudes. The validation against O3 VMR profiles using collocated observations performed by other satellite sensors (SAGE II, POAM III, ODIN-SMR, ACE-FTS, HALOE, GOME) and ECMWF assimilated ozone fields leads to consistent results, that are to a great extent compatible with those obtained from the comparison with ground-based measurements. Excellent agreement in the full vertical range of the comparison is shown with respect to collocated ozone data from stratospheric aircraft and balloon instruments, that was mostly obtained in very good spatial and temporal coincidence with MIPAS scans. This might suggest that the larger differences observed in the upper troposphere and lowermost stratosphere with respect to collocated ground-based and satellite O3 data are only partly due to a degradation of MIPAS data quality. They should be rather largely ascribed to the natural variability of these altitude regions and to other components of the comparison errors. By combining the results of this large number of validation data sets we derived a general assessment of MIPAS v4.61 and v4.62 ozone data quality. A clear indication of the validity of MIPAS O3 vertical profiles is obtained for most of the stratosphere, where the mean relative difference with the individual correlative data sets is always lower than ±10%. Furthermore, these differences always fall within the combined systematic error (from 1 hPa to 50 hPa) and the standard deviation is fully consistent with the random error of the comparison (from 1 hPa to ~30–40 hPa). A degradation in the quality of the agreement is generally observed in the lower stratosphere and upper troposphere, with biases up to 25% at 100 hPa and standard deviation of the global mean differences up to three times larger than the combined random error in the range 50–100 hPa. The larger differences observed at the bottom end of MIPAS retrieved profiles can be associated, as already noticed, to the effects of stronger atmospheric gradients in the UTLS that are perceived differently by the various measurement techniques. However, further components that may degrade the results of the comparison at lower altitudes can be identified as potentially including cloud contamination, which is likely not to have been fully filtered using the current settings of the MIPAS cloud detection algorithm, and in the linear approximation of the forward model that was used for the a priori estimate of systematic error components. The latter, when affecting systematic contributions with a random variability over the spatial and temporal scales of global averages, might result in an underestimation of the random error of the comparison and add up to other error sources, such as the possible underestimates of the p and T error propagation based on the assumption of a 1 K and 2% uncertainties, respectively, on MIPAS temperature and pressure retrievals. At pressure lower than 1 hPa, only a small fraction of the selected validation data set provides correlative ozone data of adequate quality and it is difficult to derive quantitative conclusions about the performance of MIPAS O3 retrieval for the topmost layers.

19 January 2009 in Atmospheric Chemistry and Physics
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SPSébastien Payan
Sébastien Payan
CCC. Camy-Peyret
C. Camy-Peyret
HOH. Oelhaf
H. Oelhaf
GWG. Wetzel
G. Wetzel
GMG. Maucher
G. Maucher
ABA. Butz
A. Butz
The ENVISAT validation programme for the atmospheric instruments MIPAS, SCIAMACHY and GOMOS is based on a number of balloon-borne, aircraft, satellite and ground-based correlative measurements. In particular the activities of validation scientists were coordinated by ESA within the ENVISAT Stratospheric Aircraft and Balloon Campaign or ESABC. As part of a series of similar papers on other species [this issue] and in parallel to the contribution of the individual validation teams, the present paper provides a synthesis of comparisons performed between MIPAS CH4 and N2O profiles produced by the current ESA operational software (Instrument Processing Facility version 4.61 or IPF v4.61, full resolution MIPAS data covering the period 9 July 2002 to 26 March 2004) and correlative measurements obtained from balloon and aircraft experiments as well as from satellite sensors or from ground-based instruments. In the middle stratosphere, no significant bias is observed between MIPAS and correlative measurements, and MIPAS is providing a very consistent and global picture of the distribution of CH4 and N2O in this region. In average, the MIPAS CH4 values show a small positive bias in the lower stratosphere of about 5%. A similar situation is observed for N2O with a positive bias of 4%. In the lower stratosphere/upper troposphere (UT/LS) the individual used MIPAS data version 4.61 still exhibits some unphysical oscillations in individual CH4 and N2O profiles caused by the processing algorithm (with almost no regularization). Taking these problems into account, the MIPAS CH4 and N2O profiles are behaving as expected from the internal error estimation of IPF v4.61 and the estimated errors of the correlative measurements.

21 September 2007 in Atmospheric Chemistry and Physics
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Dingyi  WangDingyi Wang
Dingyi Wang
MHMichael Hoepfner
Michael Hoepfner
CBC. E. Blom
C. E. Blom
WWW. E. Ward
W. E. Ward
HFH. Fischer
H. Fischer
CPC. Piccolo
C. Piccolo
Nitric acid (HNO3) is one of the key products that are operationally retrieved by the European Space Agency (ESA) from the emission spectra measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard ENVISAT. The product version 4.61/4.62 for the observation period between July 2002 and March 2004 is validated by comparisons with a number of independent observations from ground-based stations, aircraft/balloon campaigns, and satellites. Individual HNO3 profiles of the ESA MIPAS level-2 product show good agreement with those of MIPAS-B and MIPAS-STR (the balloon and aircraft version of MIPAS, respectively), and the balloon-borne infrared spectrometers MkIV and SPIRALE, mostly matching the reference data within the combined instrument error bars. In most cases differences between the correlative measurement pairs are less than 1 ppbv (5–10%) throughout the entire altitude range up to about 38 km (~6 hPa), and below 0.5 ppbv (15–20% or more) above 30 km (~17 hPa). However, differences up to 4 ppbv compared to MkIV have been found at high latitudes in December 2002 in the presence of polar stratospheric clouds. The degree of consistency is further largely affected by the temporal and spatial coincidence, and differences of 2 ppbv may be observed between 22 and 26 km (~50 and 30 hPa) at high latitudes near the vortex boundary, due to large horizontal inhomogeneity of HNO3. Similar features are also observed in the mean differences of the MIPAS ESA HNO3 VMRs with respect to the ground-based FTIR measurements at five stations, aircraft-based SAFIRE-A and ASUR, and the balloon campaign IBEX. The mean relative differences between the MIPAS and FTIR HNO3 partial columns are within ±2%, comparable to the MIPAS systematic error of ~2%. For the vertical profiles, the biases between the MIPAS and FTIR data are generally below 10% in the altitudes of 10 to 30 km. The MIPAS and SAFIRE HNO3 data generally match within their total error bars for the mid and high latitude flights, despite the larger atmospheric inhomogeneities that characterize the measurement scenario at higher latitudes. The MIPAS and ASUR comparison reveals generally good agreements better than 10–13% at 20–34 km. The MIPAS and IBEX measurements agree reasonably well (mean relative differences within ±15%) between 17 and 32 km. Statistical comparisons of the MIPAS profiles correlated with those of Odin/SMR, ILAS-II, and ACE-FTS generally show good consistency. The mean differences averaged over individual latitude bands or all bands are within the combined instrument errors, and generally within 1, 0.5, and 0.3 ppbv between 10 and 40 km (~260 and 4.5 hPa) for Odin/SMR, ILAS-II, and ACE-FTS, respectively. The standard deviations of the differences are between 1 to 2 ppbv. The standard deviations for the satellite comparisons and for almost all other comparisons are generally larger than the estimated measurement uncertainty. This is associated with the temporal and spatial coincidence error and the horizontal smoothing error which are not taken into account in our error budget. Both errors become large when the spatial variability of the target molecule is high.

20 February 2018 in Atmospheric Measurement Techniques
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SCSimone Ceccherini
Simone Ceccherini
BCBruno Carli
Bruno Carli
CTCecilia Tirelli
Cecilia Tirelli
NZNicola Zoppetti
Nicola Zoppetti
SBSamuele Del Bianco
Samuele Del Bianco
RDRossana Dragani
Rossana Dragani
The complete data fusion (CDF) method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.