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Jordis S. Tradowsky, Chris P. Burrows, Sean B. Healy, and John R. Eyre

Abstract

A new method to estimate radiosonde temperature biases using radio occultation measurements as a reference has been developed. The bias is estimated as the difference between mean radio occultation and mean radiosonde departures from collocated profiles extracted from the Met Office global numerical weather prediction (NWP) system. Using NWP background profiles reduces the impact of spatial and temporal collocation errors. The use of NWP output also permits determination of the lowest level at which the atmosphere is sufficiently dry to analyze radio occultation dry temperature retrievals. The authors demonstrate the advantages of using a new tangent linear version of the dry temperature retrieval algorithm to propagate bending angle departures to dry temperature departures. This reduces the influence of a priori assumptions compared to a nonlinear retrieval. Radiosonde temperature biases, which depend on altitude and the solar elevation angle, are presented for five carefully chosen upper-air sites and show strong intersite differences, with biases exceeding 2 K at one of the sites. If implemented in NWP models to correct radiosonde temperature biases prior to assimilation, this method could aid the need for consistent anchor measurements in the assimilation system. The method presented here is therefore relevant to NWP centers, and the results will be of interest to the radiosonde community by providing site-specific temperature bias profiles. The new tangent linear version of the linear Abel transform and the hydrostatic integration are described in the interests of the radio occultation community.

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Sebastian Mieruch, Stefan Noël, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Marc Schröder, and Jörg Schulz

Abstract

Global total column water vapor trends have been derived from both the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite data and from globally distributed radiosonde measurements, archived and quality controlled by the Deutscher Wetterdienst (DWD).

The control of atmospheric water vapor amount by the hydrological cycle plays an important role in determining surface temperature and its response to the increase in man-made greenhouse effect. As a result of its strong infrared absorption, water vapor is the most important naturally occurring greenhouse gas. Without water vapor, the earth surface temperature would be about 20 K lower, making the evolution of life, as we know it, impossible. The monitoring of water vapor and its evolution in time is therefore of utmost importance for our understanding of global climate change. Comparisons of trends derived from independent water vapor measurements from satellite and radiosondes facilitate the assessment of the significance of the observed changes in water vapor.

In this manuscript, the authors have compared observed water vapor change and trends, derived from independent instruments, and assessed the statistical significance of their differences. This study deals with an example of the Behrens–Fisher problem, namely, the comparison of samples with different means and different standard deviations, applied to trends from time series.

Initially the Behrens–Fisher problem for the derivation of the consolidated change and trends is solved using standard (frequentist) hypothesis testing by performing the Welch test. Second, a Bayesian model selection is applied to solve the Behrens–Fisher problem by integrating the posterior probabilities numerically by using the algorithm Differential Evolution Markov Chain (DEMC). Additionally, an analytical approximative solution of the Bayesian posterior probabilities is derived by means of a quadratic Taylor series expansion applied in a computationally efficient manner to large datasets. The two statistical methods used in the study yield similar results for the comparison of the water vapor changes and trends from the different measurements, yielding a consolidated and consistent behavior.

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Andreas Richter, Folkard Wittrock, Mark Weber, Steffen Beirle, Sven Kühl, Ulrich Platt, Thomas Wagner, Walburga Wilms-Grabe, and John P. Burrows

Abstract

Measurements from the Global Ozone Monitoring Experiment (GOME) are used to study the chemical evolution of the stratosphere during the unusual 2002 winter in the Southern Hemisphere. The results show that chlorine activation as indicated by OClO columns was similar to previous years in the vortex until the major warming on 26 September 2002 after which it decreased rapidly. Similarly, NO2 columns were only slightly larger than in previous years before the warming, indicating strong denoxification and probably also denitrification. After the warming, very large NO2 columns were observed for a few days, which then decreased again as the vortex reestablished itself until the final warming. Ozone columns were much larger than in any previous year from September onward, mainly as a result of the unusual dynamical situation. Analysis of the global long-term time series of GOME measurements since 1996 provides a unique opportunity to set the austral winter 2002 into perspective. The GOME data reveal the large difference in variability of chlorine activation between the two hemispheres, whereas denoxification shows surprisingly little variation from year to year in both hemispheres. However, NO2 depletion in the Southern Hemisphere is usually sustained for about one month longer in the Antarctic stratosphere as a result of the stable vortex. Compared to the observations in the Northern Hemisphere, the austral winter 2002 was still stable and cold and had a high potential for chemical ozone destruction.

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John P. Burrows, Mark Weber, Michael Buchwitz, Vladimir Rozanov, Annette Ladstätter-Weißenmayer, Andreas Richter, Rüdiger DeBeek, Ricarda Hoogen, Klaus Bramstedt, Kai-Uwe Eichmann, Michael Eisinger, and Dieter Perner

Abstract

The Global Ozone Monitoring Experiment (GOME) is a new instrument aboard the European Space Agency’s (ESA) Second European Remote Sensing Satellite (ERS-2), which was launched in April 1995. The main scientific objective of the GOME mission is to determine the global distribution of ozone and several other trace gases, which play an important role in the ozone chemistry of the earth’s stratosphere and troposphere. GOME measures the sunlight scattered from the earth’s atmosphere and/or reflected by the surface in nadir viewing mode in the spectral region 240–790 nm at a moderate spectral resolution of between 0.2 and 0.4 nm. Using the maximum 960-km across-track swath width, the spatial resolution of a GOME ground pixel is 40 × 320 km2 for the majority of the orbit and global coverage is achieved in three days after 43 orbits.

Operational data products of GOME as generated by DLR-DFD, the German Data Processing and Archiving Facility (D-PAF) for GOME, comprise absolute radiometrically calibrated earthshine radiance and solar irradiance spectra (level 1 products) and global distributions of total column amounts of ozone and NO2 (level 2 products), which are derived using the DOAS approach (Differential Optical Absorption Spectroscopy). (Under certain conditions and some restrictions, the operational data products are publically available from the European Space Agency via the ERS Helpdesk.)

In addition to the operational data products, GOME has delivered important information about other minor trace gases such as OClO, volcanic SO2, H2CO from biomass burning, and tropospheric BrO. Using an iterative optimal estimation retrieval scheme, ozone vertical profiles can be derived from the inversion of the UV/VIS spectra. This paper reports on the GOME instrument, its operation mode, and the retrieval techniques, the latter with particular emphasis on DOAS (total column retrieval) and advanced optimal estimation (ozone profile retrieval).

Observation of ozone depletion in the recent polar spring seasons in both hemispheres are presented. OClO observed by GOME under twilight conditions provides valuable information on the chlorine activation inside the polar vortex, which is believed to be responsible for the rapid catalytic destruction of ozone. Episodes of enhanced BrO in the Arctic, most likely contained in the marine boundary layer, were observed in early and late spring. Excess tropospheric nitrogen dioxide and ozone have been observed during the recent Indonesian fire in fall 1997. Formaldehyde could also clearly be identified by GOME and is known to be a by-product resulting from biomass burning.

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Mark P. Baldwin, Thomas Birner, Guy Brasseur, John Burrows, Neal Butchart, Rolando Garcia, Marvin Geller, Lesley Gray, Kevin Hamilton, Nili Harnik, Michaela I. Hegglin, Ulrike Langematz, Alan Robock, Kaoru Sato, and Adam A. Scaife

Abstract

The stratosphere contains ~17% of Earth’s atmospheric mass, but its existence was unknown until 1902. In the following decades our knowledge grew gradually as more observations of the stratosphere were made. In 1913 the ozone layer, which protects life from harmful ultraviolet radiation, was discovered. From ozone and water vapor observations, a first basic idea of a stratospheric general circulation was put forward. Since the 1950s our knowledge of the stratosphere and mesosphere has expanded rapidly, and the importance of this region in the climate system has become clear. With more observations, several new stratospheric phenomena have been discovered: the quasi-biennial oscillation, sudden stratospheric warmings, the Southern Hemisphere ozone hole, and surface weather impacts of stratospheric variability. None of these phenomena were anticipated by theory. Advances in theory have more often than not been prompted by unexplained phenomena seen in new stratospheric observations. From the 1960s onward, the importance of dynamical processes and the coupled stratosphere–troposphere circulation was realized. Since approximately 2000, better representations of the stratosphere—and even the mesosphere—have been included in climate and weather forecasting models. We now know that in order to produce accurate seasonal weather forecasts, and to predict long-term changes in climate and the future evolution of the ozone layer, models with a well-resolved stratosphere with realistic dynamics and chemistry are necessary.

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Jack Fishman, Kevin W. Bowman, John P. Burrows, Andreas Richter, Kelly V. Chance, David P. Edwards, Randall V. Martin, Gary A. Morris, R. Bradley Pierce, Jerald R. Ziemke, Jassim A. Al-Saadi, John K. Creilson, Todd K. Schaack, and Anne M. Thompson

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Research Council. Tropospheric measurements show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of carbon monoxide and nitrogen dioxide in the winter and spring. In the summer, when photochemistry is most intense, photochemically generated ozone is found in large concentrations over and downwind from where anthropogenic sources are largest, such as the eastern United States and eastern China. In the tropics and the subtropics, where photon flux is strong throughout the year, trace gas concentrations are driven by the abundance of the emissions. The largest single tropical source of pollution is biomass burning, as can be seen readily in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at the spatial and temporal scales required by policy makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

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