130 research outputs found
Record-breaking ozone loss in the Arctic winter 2010/2011: comparison with 1996/1997
We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh^(−1) (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HO_x cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NO_x cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements
Stratospheric ozone climatology and variability over a southern subtropical site: Reunion Island (21° S; 55° E)
No severe ozone depletion in the tropical stratosphere in recent decades
Stratospheric ozone is an important constituent of the atmosphere. Significant changes in its concentrations have great consequences for the environment in general and for ecosystems in particular. Here, we analyse ground-based, ozonesonde and satellite ozone measurements to examine the ozone depletion and the spatiotemporal trends in ozone in the tropics during the past 5 decades (1980–2020). The amount of column ozone in the tropics is relatively small (250–270 DU) compared to high and mid-latitudes (Northern Hemisphere (NH) 275–425 DU; Southern Hemisphere (SH) 275–350 DU). In addition, the tropical total ozone trend is very small (±0–0.2 DU yr−1), as estimated for the period 1998–2022. No observational evidence is found regarding the indications or signatures of severe stratospheric ozone depletion in the tropics in contrast to a recent claim. Finally, current understanding and observational evidence do not provide any support for the possibility of an ozone hole occurring outside Antarctica today with respect to the present-day stratospheric halogen levels.</p
Coherence of long-term stratospheric ozone vertical distribution time series used for the study of ozone recovery at a northern mid-latitude station
The coherence of stratospheric ozone time series retrieved from various observational records is investigated at Haute-Provence Observatory (OHP–43.93° N, 5.71° E). The analysis is accomplished through the intercomparison of collocated ozone measurements of Light Detection and Ranging (lidar) with Solar Backscatter UltraViolet(/2) (SBUV(/2)), Stratospheric Aerosol and Gas Experiment II (SAGE~II), Halogen Occultation Experiment (HALOE), Microwave Limb Sounder (MLS) on Upper Atmosphere Research Satellite (UARS) and Aura and Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite observations as well as with in situ ozonesondes and ground-based Umkehr measurements performed at OHP. A detailed statistical study of the relative differences of ozone observations over the whole stratosphere is performed to detect any specific drift in the data. On average, all instruments show their best agreement with lidar at 20–40 km, where deviations are within ±5 %. Discrepancies are somewhat higher below 20 and above 40 km. The agreement with SAGE II data is remarkable since average differences are within ±1 % at 17–41 km. In contrast, Umkehr data underestimate systematically the lidar measurements in the whole stratosphere with a near zero bias at 16–8 hPa (~30 km). Drifts are estimated using simple linear regression for the data sets analysed in this study, from the monthly averaged difference time series. The derived values are less than ±0.5 % yr<sup>&minus;1</sup> in the 20–40 km altitude range and most drifts are not significant at the 2<i>σ</i> level. We also discuss the possibilities of extending the SAGE II and HALOE data with the GOMOS and Aura MLS data in consideration with relative offsets and drifts since the combination of such data sets are likely to be used for the study of stratospheric ozone recovery in the future
Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars
The objective of this paper and its companion (Wing et al., 2018) is to show
that ground-based lidar temperatures are a stable, accurate, and precise
data set for use in validating satellite temperatures at high vertical
resolution. Long-term lidar observations of the middle atmosphere have been
conducted at the Observatoire de Haute-Provence (OHP), located in southern
France (43.93° N, 5.71° E), since 1978. Making use of
20 years of high-quality co-located lidar measurements, we have shown that
lidar temperatures calculated using the Rayleigh technique at 532 nm are
statistically identical to lidar temperatures calculated from the
non-absorbing 355 nm channel of a differential absorption lidar (DIAL)
system. This result is of interest to members of the Network for the
Detection of Atmospheric Composition Change (NDACC) ozone lidar community
seeking to produce validated temperature products. Additionally, we have
addressed previously published concerns of lidar–satellite relative warm bias
in comparisons of upper-mesospheric and lower-thermospheric (UMLT)
temperature profiles. We detail a data treatment algorithm which minimizes
known errors due to data selection procedures, a priori choices, and
initialization parameters inherent in the lidar retrieval. Our algorithm
results in a median cooling of the lidar-calculated absolute temperature
profile by 20 K at 90 km altitude with respect to the standard OHP
NDACC lidar temperature algorithm. The confidence engendered by the long-term
cross-validation of two independent lidars and the improved lidar temperature
data set is exploited in Wing et al. (2018) for use in multi-year satellite
validations.</p
Drift Corrected Trends and Periodic Variations in MIPAS IMK/IAA Ozone Measurements
Drifts, trends and periodic variations were calculated from monthly zonally averaged ozone profiles. The ozone profiles were derived from level-1b data of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) by means of the scientific level-2 processor run by the Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK). All trend and drift analyses were performed using a multilinear parametric trend model which includes a linear term, several harmonics with period lengths from 3 to 24 months and the quasi-biennial oscillation (QBO). Drifts at 2-sigma significance level were mainly negative for ozone relative to Aura MLS and Odin OSIRIS and negative or near zero for most of the comparisons to lidar measurements. Lidar stations used here include those at Hohenpeissenberg (47.8° N, 11.0 ° E), Lauder (45.0 ° S, 169.7 ° E), Mauna Loa (19.5 ° N, 155.6 ° W), Observatoire Haute Provence (43.9 ° N, 5.7 ° E) and Table Mountain (34.4 ° N, 117.7 ° W). Drifts against the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) were found to be mostly insignificant. The assessed MIPAS ozone trends cover the time period of July 2002 to April 2012 and range from -0.56 ppmv decade-1 to +0.48 ppmv decade-1 (-0.52 ppmv decade-1 to +0.47 ppmv decade-1 when displayed on pressure coordinates) depending on altitude/ pressure and latitude. From the empirical drift analyses we conclude that the real ozone trends might be slightly more positive/ less negative than those calculated from the MIPAS data, by conceding the possibility of MIPAS having a very small (approximately within -0.3 ppmv decade-1 negative drift for ozone. This leads to drift-corrected trends of -0.41 ppmv decade-1 to +0.55 ppmv decade-1 (-0.38 ppmv decade-1 to +0.53 ppmv decade-1 when displayed on pressure coordinates) for the time period covered by MIPAS Envisat measurements, with very few negative and large areas of positive trends at mid-latitudes for both hemispheres around and above 30 km (similar to 10 hPa). Negative trends are found in the tropics around 25 and 35 km (similar to 25 and 5 hPa), while an area of positive trends is located right above the tropical tropopause. These findings are in good agreement with the recent literature. Differences of the trends compared with the recent literature could be explained by a possible shift of the subtropical mixing barriers. Results for the altitude-latitude distribution of amplitudes of the quasi-biennial, annual and the semi-annual oscillation are overall in very good agreement with recent findings
Stratospheric aerosols from the Sarychev volcano eruption in the 2009 Arctic summer
Aerosols from the Sarychev volcano eruption (Kuril Islands, northeast of Japan) were observed in the Arctic lower stratosphere a few days after the strongest SO2 injection which occurred on 15 and 16 June 2009. From the observations provided by the Infrared Atmospheric Sounding Interferometer (IASI) an estimated 0.9 Tg of sulphur dioxide was injected into the upper troposphere and lower stratosphere (UTLS). The resultant stratospheric sulphate aerosols were detected from satellites by the Optical Spectrograph and Infrared Imaging System (OSIRIS) limb sounder and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and from the surface by the Network for the Detection of Atmospheric Composition Changes (NDACC) lidar deployed at OHP (Observatoire de Haute-Provence, France). By the first week of July the aerosol plume had spread out over the entire Arctic region. The Sarychev-induced stratospheric aerosol over the Kiruna region (north of Sweden) was measured by the Stratospheric and Tropospheric Aerosol Counter (STAC) during eight balloon flights planned in August and September 2009. During this balloon campaign the Micro Radiomètre Ballon (MicroRADIBAL) and the Spectroscopie d'Absorption Lunaire pour l'Observation des Minoritaires Ozone et NOx (SALOMON) remote-sensing instruments also observed these aerosols. Aerosol concentrations returned to near-background levels by spring 2010. The effective radius, the surface area density (SAD), the aerosol extinction, and the total sulphur mass from STAC in situ measurements are enhanced with mean values in the range 0.15-0.21 μm, 5.5-14.7 μm2 cm-3, 5.5-29.5 × 10-4 km-1, and 4.9-12.6 × 10-10 kg[S] kg-1[air], respectively, between 14 km and 18 km. The observed and modelled e-folding time of sulphate aerosols from the Sarychev eruption is around 70-80 days, a value much shorter than the 12-14 months calculated for aerosols from the 1991 eruption of Mt Pinatubo. The OSIRIS stratospheric aerosol optical depth (AOD) at 750 nm is enhanced by a factor of 6, with a value of 0.02 in late July compared to 0.0035 before the eruption. The HadGEM2 and MIMOSA model outputs indicate that aerosol layers in polar region up to 14-15 km are largely modulated by stratosphere-troposphere exchange processes. The spatial extent of the Sarychev plume is well represented in the HadGEM2 model with lower altitudes of the plume being controlled by upper tropospheric troughs which displace the plume downward and upper altitudes around 18-20 km, in agreement with lidar observations. Good consistency is found between the HadGEM2 sulphur mass density and the value inferred from the STAC observations, with a maximum located about 1 km above the tropopause ranging from 1 to 2 × 10 -9 kg[S] kg-1[air], which is one order of magnitude higher than the background level. © Author(s) 2013.The authors thank the CNES balloon
launching team for successful operations and the Swedish Space
Corporation at Esrange. The ETHER database (CNES-INSUCNRS)
and the CNES “sous-direction Ballon” are partners of the
project. The StraPolEt ´ e project has been funded by the French ´
“Agence Nationale de la Recherche” (ANR-BLAN08-1-31627),
the “Centre National d’Etudes Spatiales” (CNES), and the “Institut ´
Polaire Paul-Emile Victor” (IPEV). The AEROWAVE (Aerosols,
Water Vapor and Electricity) and the HALOHA (HALOgen in
High Altitudes) projects have been funded by the recently created
French CNES-INSU Balloon Committee (so-called CSTB). We are
grateful to Slimane Bekki and David Cugniet for their constructive
comments about the AER-UPMC 2-D model, to Marc-Antoine
Drouin for his help about the MIMOSA model, and to the LPC2E
technical team for this successful campaign. Jim Haywood and
Andy Jones were supported by the Joint DECC/Defra Met Office
Hadley Centre Climate Programme (GA01101). IASI was developed
and built under the responsibility of the Centre National
d’Etudes Spatiales (CNES, France). It is flown on board the Metop ´
satellites as part of the EUMETSAT Polar System. The IASI L1
data are received through the EUMETCast near-real-time data
distribution service. L. Clarisse is a postdoctoral researcher with
FRS-FNRS. We acknowledge the CALIOP team for acquiring
and processing data as well as the ICARE team for providing and
maintaining the computational facilities to store them. Odin is a
Swedish-led satellite project funded jointly by Sweden (SNSB),
Canada (CSA), France (CNES), and Finland (Tekes). This study
was supported by the French VOLTAIRE Labex (Laboratoire
d’Excellence ANR-10-LABX-100-01) managed by the University
of Orleans
Stratospheric AOD after the 2011 eruption of Nabro volcano measured by lidars over the Northern Hemisphere
International audienceNabro volcano (13.37°N, 41.70°E) in Eritrea erupted on 13 June 2011 generating a layer of sulfate aerosols that persisted in the stratosphere for months. For the first time we report on ground-based lidar observations of the same event from every continent in the Northern Hemisphere, taking advantage of the synergy between global lidar networks such as EARLINET, MPLNET and NDACC with independent lidar groups and satellite CALIPSO to track the evolution of the stratospheric aerosol layer in various parts of the globe. The globally averaged aerosol optical depth (AOD) due to the stratospheric volcanic aerosol layers was of the order of 0.018 ± 0.009 at 532 nm, ranging from 0.003 to 0.04. Compared to the total column AOD from the available collocated AERONET stations, the stratospheric contribution varied from 2% to 23% at 532 nm
Chapter 4: The LOTUS regression model
One of the primary motivations of the LOTUS effort is to attempt to reconcile the discrepancies in ozone trend results from the wealth of literature on the subject. Doing so requires investigating the various methodologies employed to derive long-term trends in ozone as well as to examine the large array of possible variables that feed into those methodologies and analyse their impacts on potential trend results. Given the limited amount of time, the LOTUS group focused on the most common methodology of multiple linear regression and performed a number of sensitivity tests with the goal of trying to establish best practices and come to a consensus on a single regression model to use for this study. This chapter discusses the details and results of the sensitivity tests before describing the components of the final single model that was chosen and the reasons for that choice
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