A climatology of the diurnal variations in stratospheric and mesospheric ozone over Bern, Switzerland

Abstract. In this paper, we compare the diurnal variations in middle-atmospheric water vapor as measured by two ground-based microwave radiometers in the Alpine region near Bern, Switzerland. The observational data set is also compared to data from the chemistry–climate model WACCM. Due to the small diurnal variations of usually less than 1%, averages over extended time periods are required. Therefore, two time periods of five months each, December to April and June to October, were taken for the comparison. The diurnal variations from the observational data agree well with each other in amplitude and phase. The linear correlation coefficients range from 0.8 in the upper stratosphere to 0.5 in the upper mesosphere. The observed diurnal variability is significant at all pressure levels within the sensitivity of the instruments. Comparing our observations with WACCM, we find that the agreement of the phase of the diurnal cycle between observations and model is better from December to April than from June to October. The amplitudes of the diurnal variations for both time periods increase with altitude in WACCM, but remain approximately constant at 0.05 ppm in the observations. The WACCM data are used to separate the processes that lead to diurnal variations in middle-atmospheric water vapor above Bern. The dominating processes were found to be meridional advection below 0.1 hPa, vertical advection between 0.1 and 0.02 hPa and (photo-)chemistry above 0.02 hPa. The contribution of zonal advection is small. The highest diurnal variations in water vapor as seen in the WACCM data are found in the mesopause region during the time period from June to October with diurnal amplitudes of 0.2 ppm (approximately 5% in relative units).

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Diurnal variations in middle atmospheric water vapor by ground-based microwave radiometry

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-3859-2013 ◽

2013 ◽

Vol 13 (2) ◽

pp. 3859-3880 ◽

Cited By ~ 1

Author(s):

D. Scheiben ◽

A. Schanz ◽

B. Tschanz ◽

N. Kämpfer

Keyword(s):

Water Vapor ◽

Observational Data ◽

Climate Model ◽

Correlation Coefficients ◽

Diurnal Variations ◽

Atmospheric Water Vapor ◽

Atmospheric Water ◽

Data Set ◽

Diurnal Variability ◽

Time Periods

Abstract. In this paper, we compare the diurnal variations in middle atmospheric water vapor as measured by two ground-based microwave radiometers in the Alpine region near Bern, Switzerland. The observational data set is also compared to data from the chemistry-climate model WACCM. Due to the small diurnal variations of usually less than 1%, averages over extended time periods are required. Therefore, two time periods of five months each, December to April and June to October, were taken for the comparison. The diurnal variations from the observational data agree well with each other in amplitude and phase. The linear correlation coefficients range from 0.8 in the upper stratosphere to 0.5 in the upper mesosphere. The observed diurnal variability is significant at all pressure levels within the sensitivity of the instruments. Comparing our observations with WACCM, we find that the agreement of the phase of the diurnal cycle between observations and model is better from December to April than from June to October. The amplitudes of the diurnal variations for both time periods increase with altitude in WACCM, but remain approximately constant at 0.05 parts per million in the observations. The WACCM data is used to separate the processes that lead to diurnal variations in middle atmospheric water vapor above Bern. The dominating processes were found to be meridional advection below 0.1 hPa, vertical advection between 0.1 and 0.02 hPa and (photo-)chemistry above 0.02 hPa. The contribution of zonal advection is small. The highest diurnal variations in water vapor are found in the mesopause region during the time period from June to October with diurnal amplitudes of 0.2 ppm (approximately 5% in relative units).

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Climate Impact of Polar Mesospheric and Stratospheric Ozone Losses due to Energetic Particle Precipitation

10.5194/acp-2017-507 ◽

2017 ◽

Author(s):

Katharina Meraner ◽

Hauke Schmidt

Keyword(s):

Radiative Forcing ◽

Energetic Particle ◽

Climate Model ◽

Stratospheric Ozone ◽

Energetic Particles ◽

Climate Impact ◽

Particle Precipitation ◽

Ozone Loss ◽

Mesospheric Ozone ◽

Energetic Particle Precipitation

Abstract. Energetic particles enter the polar atmosphere and enhance the production of nitrogen oxides and hydrogen oxides in the winter stratosphere and mesosphere. Both components are powerful ozone destroyers. Recently, it has been inferred from observations that the direct effect of energetic particle precipitation (EPP) causes significant long-term mesospheric ozone variability. Satellites observe a decrease in mesospheric ozone by up to 34 % between EPP maximum and EPP minimum. Here, we analyze the climate impact of polar mesospheric and polar stratospheric ozone losses due to EPP in the coupled climate model MPI-ESM. Using radiative transfer modeling, we find that the radiative forcing of a mesospheric ozone loss during polar night is small. Hence, climate effects of a mesospheric ozone loss due to energetic particles seem unlikely. A stratospheric ozone loss due to energetic particles warms the winter polar stratosphere and subsequently weakens the polar vortex. However, those changes are small, and few statistically significant changes in surface climate are found.

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SCIAMACHY CO over land and oceans: 2003–2007 interannual variability

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-3799-2009 ◽

2009 ◽

Vol 9 (11) ◽

pp. 3799-3813 ◽

Cited By ~ 40

Author(s):

A. M. S. Gloudemans ◽

A. T. J. de Laat ◽

H. Schrijver ◽

I. Aben ◽

J. F. Meirink ◽

...

Keyword(s):

Interannual Variability ◽

Biomass Burning ◽

Accurate Determination ◽

Likelihood Method ◽

Retrieval Algorithm ◽

Data Set ◽

Noise Error ◽

A Minor ◽

Iterative Maximum Likelihood ◽

Good Agreement

Abstract. We present a new method to obtain accurate SCIAMACHY CO columns over clouded ocean scenes. Based on an improved version of the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm, we now have retrieved five years of data over both land and clouded ocean scenes between 2003 and 2007. The ocean-cloud method uses the CH4 columns retrieved simultaneously with the CO columns to determine the cloud top height. The CH4 cloud top height is in good agreement with the FRESCO+ cloud top height determined from UV-VIS oxygen-A band measurements, providing confidence that the CH4 cloud top height is a good diagnostic of the cloud top height over (partially) clouded ocean scenes. The CO measurements over clouded ocean scenes have been compared with collocated modeled CO columns over the same clouds and agree well. Using clouded ocean scenes quadruples the number of useful CO measurements compared to land-only measurements. The five-year CO data set over land and clouded ocean scenes presented here is based on an improved version of the IMLM algorithm which includes a more accurate determination of the random instrument-noise error for CO. This leads to a smaller spread in the differences between single CO measurements and the corresponding model values. The new version, IMLM version 7.4, also uses updated spectroscopic parameters for H2O and CH4 but this has only a minor impact on the retrieved CO columns. The five-year data set shows significant interannual variability over land and over clouded ocean scenes. Three examples are highlighted: the Asian outflow of pollution over the northern Pacific, the biomass-burning outflow over the Indian Ocean originating from Indonesia, and biomass burning in Brazil. In general there is good agreement between observed and modeled seasonal cycles and interannual variability.

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Diurnal variations of stratospheric ozone measured by ground-based microwave remote sensing at the Mauna Loa NDACC site: measurement validation and GEOSCCM model comparison

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-31855-2013 ◽

2013 ◽

Vol 13 (12) ◽

pp. 31855-31890 ◽

Cited By ~ 8

Author(s):

A. Parrish ◽

I. S. Boyd ◽

G. E. Nedoluha ◽

P. K. Bhartia ◽

S. M. Frith ◽

...

Keyword(s):

Remote Sensing ◽

Model Comparison ◽

Climate Model ◽

Stratospheric Ozone ◽

Microwave Remote Sensing ◽

Diurnal Variations ◽

Atmospheric Composition ◽

Mauna Loa ◽

Remote Sensing Technique ◽

Measurement Validation

Abstract. There is presently renewed interest in diurnal variations of stratospheric and mesospheric ozone for the purpose of supporting homogenization of records of various ozone measurements that are limited by the technique employed to being made at certain times of day. We have made such measurements for 18 yr using a passive microwave remote sensing technique at the Mauna Loa Observatory in Hawaii, which is a primary station in the Network for Detection of Atmospheric Composition Change (NDACC). We have recently reprocessed these data with hourly time resolution to study diurnal variations. We inspected differences between pairs of the ozone spectra (e.g. day and night) from which the ozone profiles are derived to determine the extent to which they may be contaminated by diurnally varying systematic instrumental or measurement effects. These are small, and we have reduced them further by selecting data that meet certain criteria that we established. We have calculated differences between profiles measured at different times: morning–night, afternoon–night, and morning–afternoon and have intercompared these with like profiles derived from Aura-MLS, UARS-MLS, SMILES, and SBUV/2 measurements. Differences between averages of coincident profiles are typically <1.5% of typical nightime values over most of the covered altitude range with some exceptions. We calculated averages of ozone values for each hour from the Mauna Loa microwave data, and normalized these to the average for the first hour after midnight for comparison with corresponding values calculated with the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). We found that the measurements and model output mostly agree to better than 1.5% of the midnight value, with one noteworthy exception: the measured morning–night values are significantly (2–3%) higher than the modeled ones from 3.2 to 1.8 hPa (~39–43 km), and there is evidence that the measured values are increasing compared to the modeled values before sunrise in this region.

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Diurnal variations of stratospheric ozone measured by ground-based microwave remote sensing at the Mauna Loa NDACC site: measurement validation and GEOSCCM model comparison

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-7255-2014 ◽

2014 ◽

Vol 14 (14) ◽

pp. 7255-7272 ◽

Cited By ~ 28

Author(s):

A. Parrish ◽

I. S. Boyd ◽

G. E. Nedoluha ◽

P. K. Bhartia ◽

S. M. Frith ◽

...

Keyword(s):

Remote Sensing ◽

Model Comparison ◽

Climate Model ◽

Stratospheric Ozone ◽

Microwave Remote Sensing ◽

Diurnal Variations ◽

Atmospheric Composition ◽

Mauna Loa ◽

Remote Sensing Technique ◽

Measurement Validation

Abstract. There is presently renewed interest in diurnal variations of stratospheric and mesospheric ozone for the purpose of supporting homogenization of records of various ozone measurements that are limited by the technique employed to being made at certain times of day. We have made such measurements for 19 years using a passive microwave remote sensing technique at the Mauna Loa Observatory (MLO) in Hawaii, which is a primary station in the Network for Detection of Atmospheric Composition Change (NDACC). We have recently reprocessed these data with hourly time resolution to study diurnal variations. We inspected differences between pairs of the ozone spectra (e.g., day and night) from which the ozone profiles are derived to determine the extent to which they may be contaminated by diurnally varying systematic instrumental or measurement effects. These are small, and we have reduced them further by selecting data that meet certain criteria that we established. We have calculated differences between profiles measured at different times: morning–night, afternoon–night, and morning–afternoon and have intercompared these with like profiles derived from the Aura Microwave Limb Sounder (Aura-MLS), the Upper Atmosphere Research Satellite Microwave Limb Sounder (UARS-MLS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES), and Solar Backscatter Ultraviolet version 2 (SBUV/2) measurements. Differences between averages of coincident profiles are typically < 1.5% of typical nighttime values over most of the covered altitude range with some exceptions. We calculated averages of ozone values for each hour from the Mauna Loa microwave data, and normalized these to the average for the first hour after midnight for comparison with corresponding values calculated with the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). We found that the measurements and model output mostly agree to better than 1.5% of the midnight value, with one noteworthy exception: The measured morning–night values are significantly (2–3 %) higher than the modeled ones from 3.2 to 1.8 hPa (~39–43 km), and there is evidence that the measured values are increasing compared to the modeled values before sunrise in this region.

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A climatology of the diurnal variations of stratospheric and mesospheric ozone over Bern, Switzerland

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-22445-2013 ◽

2013 ◽

Vol 13 (8) ◽

pp. 22445-22485 ◽

Cited By ~ 2

Author(s):

S. Studer ◽

K. Hocke ◽

A. Schanz ◽

H. Schmidt ◽

N. Kämpfer

Keyword(s):

Diurnal Cycle ◽

Climate Model ◽

Seasonal Pattern ◽

Stratospheric Ozone ◽

Diurnal Variations ◽

Data Sets ◽

Seasonal Behavior ◽

Mean Values ◽

Spatio Temporal ◽

Ozone Variations

Abstract. The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

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Radiative and dynamical contributions to past and future Arctic stratospheric temperature trends

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-1679-2014 ◽

2014 ◽

Vol 14 (3) ◽

pp. 1679-1688 ◽

Cited By ~ 16

Author(s):

P. Bohlinger ◽

B.-M. Sinnhuber ◽

R. Ruhnke ◽

O. Kirner

Keyword(s):

Atmospheric Chemistry ◽

Planetary Wave ◽

Climate Model ◽

Stratospheric Ozone ◽

Wave Activity ◽

The Arctic ◽

Radiosonde Data ◽

Data Set ◽

The Past ◽

Stratospheric Temperature

Abstract. Arctic stratospheric ozone depletion is closely linked to the occurrence of low stratospheric temperatures. There are indications that cold winters in the Arctic stratosphere have been getting colder, raising the question if and to what extent a cooling of the Arctic stratosphere may continue into the future. We use meteorological reanalyses from the European Centre for Medium Range Weather Forecasts (ECMWF) ERA-Interim and NASA's Modern-Era Retrospective-Analysis for Research and Applications (MERRA) for the past 32 yr together with calculations of the chemistry-climate model (CCM) ECHAM/MESSy Atmospheric Chemistry (EMAC) and models from the Chemistry-Climate Model Validation (CCMVal) project to infer radiative and dynamical contributions to long-term Arctic stratospheric temperature changes. For the past three decades the reanalyses show a warming trend in winter and cooling trend in spring and summer, which agree well with trends from the Radiosonde Innovation Composite Homogenization (RICH) adjusted radiosonde data set. Changes in winter and spring are caused by a corresponding change of planetary wave activity with increases in winter and decreases in spring. During winter the increase of planetary wave activity is counteracted by a residual radiatively induced cooling. Stratospheric radiatively induced cooling is detected throughout all seasons, being highly significant in spring and summer. This means that for a given dynamical situation, according to ERA-Interim the annual mean temperature of the Arctic lower stratosphere has been cooling by −0.41 ± 0.11 K decade−1 at 50 hPa over the past 32 yr. Calculations with state-of-the-art models from CCMVal and the EMAC model qualitatively reproduce the radiatively induced cooling for the past decades, but underestimate the amount of radiatively induced cooling deduced from reanalyses. There are indications that this discrepancy could be partly related to a possible underestimation of past Arctic ozone trends in the models. The models project a continued cooling of the Arctic stratosphere over the coming decades (2001–2049) that is for the annual mean about 40% less than the modeled cooling for the past, due to the reduction of ozone depleting substances and the resulting ozone recovery. This projected cooling in turn could offset between 15 and 40% of the Arctic ozone recovery.

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Objective assessment of ozone in chemistry-climate model simulations

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-19351-2009 ◽

2009 ◽

Vol 9 (5) ◽

pp. 19351-19385

Author(s):

A. Yu. Karpechko ◽

N. P. Gillett ◽

B. Hassler ◽

K. H. Rosenlof ◽

E. Rozanov

Keyword(s):

Climate Models ◽

Climate Model ◽

Stratospheric Ozone ◽

Objective Assessment ◽

Model Performance ◽

Atmospheric Temperature ◽

Model Verification ◽

Data Set ◽

Model Average ◽

Observational Uncertainty

Abstract. Stratospheric ozone recovery is expected to drive pronounced trends in atmospheric temperature and circulation from the stratosphere to the troposphere in the 21st century, but coupled chemistry-climate models (CCMs) vary widely in their predictions of future ozone evolution. In order to assess which models might be expected to better simulate future ozone evaluation, we assess the ability of twelve CCMs to simulate observed ozone climatology and trends and rank the models according to their errors averaged across the individual diagnostics chosen. According to our analysis no one model performs better than the others in all the diagnostics; however, combining errors in individual diagnostics into one metric of model performance allows us to objectively rank the models. The multi-model average shows better overall agreement with the observations than any individual model. Based on this analysis we conclude that the multi-model average ozone projection presents the best estimate of future ozone evolution. Our results also demonstrate a sensitivity of the analysis to the choice of reference data set for vertical ozone distribution over the Antarctic, highlighting the constraints that large observational uncertainty imposes on such model verification.

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Quantitative assessment of Southern Hemisphere ozone in chemistry-climate model simulations

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-1385-2010 ◽

2010 ◽

Vol 10 (3) ◽

pp. 1385-1400 ◽

Cited By ~ 12

Author(s):

A. Yu. Karpechko ◽

N. P. Gillett ◽

B. Hassler ◽

K. H. Rosenlof ◽

E. Rozanov

Keyword(s):

Boundary Conditions ◽

Southern Hemisphere ◽

Climate Model ◽

Stratospheric Ozone ◽

Model Verification ◽

Future Climate ◽

Data Set ◽

Model Average ◽

Climate Simulations ◽

Observational Uncertainty

Abstract. Stratospheric ozone recovery in the Southern Hemisphere is expected to drive pronounced trends in atmospheric temperature and circulation from the stratosphere to the troposphere in the 21st century; therefore ozone changes need to be accounted for in future climate simulations. Many climate models do not have interactive ozone chemistry and rely on prescribed ozone fields, which may be obtained from coupled chemistry-climate model (CCM) simulations. However CCMs vary widely in their predictions of ozone evolution, complicating the selection of ozone boundary conditions for future climate simulations. In order to assess which models might be expected to better simulate future ozone evolution, and thus provide more realistic ozone boundary conditions, we assess the ability of twelve CCMs to simulate observed ozone climatology and trends and rank the models according to their errors averaged across the individual diagnostics chosen. According to our analysis no one model performs better than the others in all the diagnostics; however, combining errors in individual diagnostics into one metric of model performance allows us to objectively rank the models. The multi-model average shows better overall agreement with the observations than any individual model. Based on this analysis we conclude that the multi-model average ozone projection presents the best estimate of future ozone evolution and recommend it for use as a boundary condition in future climate simulations. Our results also demonstrate a sensitivity of the analysis to the choice of reference data set for vertical ozone distribution over the Antarctic, highlighting the constraints that large observational uncertainty imposes on such model verification.

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