scholarly journals Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

2020 ◽  
Vol 20 (11) ◽  
pp. 6991-7019
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Solar Minimum ◽  
Climate Model ◽  
Solar Maximum ◽  
Sunspot Cycle ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Reference Spectrum ◽  
Heating Rates ◽  
Data Set

Abstract. Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. The SSI values for the solar maximum of each SSI data set are created by adding the SSI differences between November 1994 and November 1989 to a common SSI reference spectrum for near-solar-minimum conditions based on ATLAS-3 (Atmospheric Laboratory of Applications and Science-3). The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar response in shortwave heating rates in the upper mesosphere and in the upper stratosphere–lower mesosphere. The strongest influence on the variability of the solar response in ozone and temperature is identified in the upper stratosphere–lower mesosphere. However, in the region of the largest ozone mixing ratio, in the stratosphere from 50 to 10 hPa, the SSI data sets do not contribute much to the variability of the solar response when the Spectral And Total Irradiance REconstructions-T (SATIRE-T) SSI data set is omitted. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid-latitudes, where the model dynamics modulate the solar responses. Apart from the upper mesosphere, there are also regions where the largest fraction of the variability of the solar response is explained by randomness, especially for the solar response in temperature.

scholarly journals Quantifying uncertainties of climate signals related to the 11–year solar cycle. Part I: Annual mean response in heating rates,temperature and ozone

2020 ◽  
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Model ◽  
Sunspot Cycle ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Mixing Ratios ◽  
Solar Signal ◽  
The Tropics

Abstract. Variations of the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry-climate model (CCM) formulation. In this study CCM simulations with the ECHAM MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1) – Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature and ozone. The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar signal in shortwave heating rates in the upper mesosphere and in the upper stratosphere/lower mesosphere. The strongest influence on the variability of the solar signal in ozone and temperature is identified in the upper stratosphere/lower mesosphere. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid latitudes, where the model dynamics modulate the solar responses.

scholarly journals Evaluation of CLaMS, KASIMA and ECHAM5/MESSy1 simulations in the lower stratosphere using observations of Odin/SMR and ILAS/ILAS-II

2009 ◽  
Vol 9 (1) ◽  
pp. 1977-2020
Author(s):  
F. Khosrawi ◽  
R. Müller ◽  
M. H. Proffitt ◽  
R. Ruhnke ◽  
O. Kirner ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Circulation Model ◽  
Lagrangian Model ◽  
Data Sets ◽  
Data Set ◽  
The Impact

Abstract. 1-year data sets of monthly averaged nitrous oxide (N2O) and ozone (O3) derived from satellite measurements were used as a tool for the evaluation of atmospheric photochemical models. Two 1-year data sets, one derived from the Improved Limb Atmospheric Spectrometer (ILAS and ILAS-II) and one from the Odin Sub-Millimetre Radiometer (Odin/SMR) were employed. Here, these data sets are used for the evaluation of two Chemical Transport Models (CTMs), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the Chemical Lagrangian Model of the Stratosphere (CLaMS) as well as for one Chemistry-Climate Model (CCM), the atmospheric chemistry general circulation model ECHAM5/MESSy1 (E5M1) in the lower stratosphere with focus on the Northern Hemisphere. Since the Odin/SMR measurements cover the entire hemisphere, the evaluation is performed for the entire hemisphere as well as for the low latitudes, midlatitudes and high latitudes using the Odin/SMR 1-year data set as reference. To assess the impact of using different data sets for such an evaluation study we repeat the evaluation for the polar lower stratosphere using the ILAS/ILAS-II data set. Only small differences were found using ILAS/ILAS-II instead of Odin/SMR as a reference, thus, showing that the results are not influenced by the particular satellite data set used for the evaluation. The evaluation of CLaMS, KASIMA and E5M1 shows that all models are in good agreement with Odin/SMR and ILAS/ILAS-II. Differences are generally in the range of ±20%. Larger differences (up to −40%) are found in all models at 500±25 K for N2O mixing ratios greater than 200 ppb. Generally, the largest differences were found for the tropics and the lowest for the polar regions. However, an underestimation of polar winter ozone loss was found both in KASIMA and E5M1 both in the Northern and Southern Hemisphere.

scholarly journals Evaluation of CLaMS, KASIMA and ECHAM5/MESSy1 simulations in the lower stratosphere using observations of Odin/SMR and ILAS/ILAS-II

2009 ◽  
Vol 9 (15) ◽  
pp. 5759-5783 ◽  
Author(s):  
F. Khosrawi ◽  
R. Müller ◽  
M. H. Proffitt ◽  
R. Ruhnke ◽  
O. Kirner ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Circulation Model ◽  
Lagrangian Model ◽  
Data Sets ◽  
Data Set ◽  
The Impact

Abstract. 1-year data sets of monthly averaged nitrous oxide (N2O) and ozone (O3) derived from satellite measurements were used as a tool for the evaluation of atmospheric photochemical models. Two 1-year data sets, one solar occultation data set derived from the Improved Limb Atmospheric Spectrometer (ILAS and ILAS-II) and one limb sounding data set derived from the Odin Sub-Millimetre Radiometer (Odin/SMR) were employed. Here, these data sets are used for the evaluation of two Chemical Transport Models (CTMs), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the Chemical Lagrangian Model of the Stratosphere (CLaMS) as well as for one Chemistry-Climate Model (CCM), the atmospheric chemistry general circulation model ECHAM5/MESSy1 (E5M1) in the lower stratosphere with focus on the Northern Hemisphere. Since the Odin/SMR measurements cover the entire hemisphere, the evaluation is performed for the entire hemisphere as well as for the low latitudes, midlatitudes and high latitudes using the Odin/SMR 1-year data set as reference. To assess the impact of using different data sets for such an evaluation study we repeat the evaluation for the polar lower stratosphere using the ILAS/ILAS-II data set. Only small differences were found using ILAS/ILAS-II instead of Odin/SMR as a reference, thus, showing that the results are not influenced by the particular satellite data set used for the evaluation. The evaluation of CLaMS, KASIMA and E5M1 shows that all models are in agreement with Odin/SMR and ILAS/ILAS-II. Differences are generally in the range of ±20%. Larger differences (up to −40%) are found in all models at 500±25 K for N2O mixing ratios greater than 200 ppbv, thus in air masses of tropical character. Generally, the largest differences were found for the tropics and the lowest for the polar regions. However, an underestimation of polar winter ozone loss was found both in KASIMA and E5M1 both in the Northern and Southern Hemisphere.

scholarly journals Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

2015 ◽  
Vol 15 (2) ◽  
pp. 829-843 ◽  
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Seasonal Variations ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Aerosol ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Latitude Range ◽  
Solar Occultation ◽  
Vertical Winds

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD, i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment–Fourier transform spectrometer (ACE–FTS). The SSD was negative at altitudes of 20–30 km (−0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

scholarly journals Validation of the HIRHAM-Simulated Indian Summer Monsoon Circulation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Stefan Polanski ◽  
Annette Rinke ◽  
Klaus Dethloff
Keyword(s):  
Summer Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Monsoon Circulation ◽  
Data Sets ◽  
Data Set ◽  
Topographic Features ◽  
Temperature And Precipitation ◽  
Simulated Precipitation

The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

scholarly journals Modeling the stratospheric warming following the Mt. Pinatubo eruption: uncertainties in aerosol extinctions

2013 ◽  
Vol 13 (22) ◽  
pp. 11221-11234 ◽  
Author(s):  
F. Arfeuille ◽  
B. P. Luo ◽  
P. Heckendorn ◽  
D. Weisenstein ◽  
J. X. Sheng ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Temperature Record ◽  
Data Sets ◽  
Stratospheric Warming ◽  
Data Set ◽  
Tropical Tropopause ◽  
Pinatubo Eruption ◽  
Tropopause Region

Abstract. In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.

scholarly journals Implications of potential future grand solar minimum for ozone layer and climate

2017 ◽  
Author(s):  
Pavle Arsenovic ◽  
Eugene Rozanov ◽  
Julien Anet ◽  
Andrea Stenke ◽  
Thomas Peter
Keyword(s):  
Solar Activity ◽  
Greenhouse Gas ◽  
21St Century ◽  
Atmospheric Chemistry ◽  
Solar Minimum ◽  
Climate Model ◽  
Ghg Emissions ◽  
Ozone Production ◽  
22Nd Century ◽  
The Impact

Abstract. Continued anthropogenic greenhouse gas (GHG) emissions are expected to cause further global warming throughout the 21st century. Understanding potential interferences with natural forcings is thus of great interest. Here we investigate the impact of a recently proposed 21st century grand solar minimum on atmospheric chemistry and climate using the SOCOL3-MPIOM chemistry-climate model with interactive ocean. We examine several model simulations for the period 2000–2199, following the greenhouse gas scenario RCP4.5, but with different solar forcings: the reference simulation is forced by perpetual repetition of solar cycle 23 until the year 2199, whereas the grand solar minimum simulations assume strong declines in solar activity of 3.5 and 6.5 W m−2 with different durations. Decreased solar activity is found to yield up to a doubling of the GHG induced stratospheric and mesospheric cooling. Under the grand solar minimum scenario tropospheric temperatures are also projected to decrease. On the global scale the reduced solar forcing compensates at most 15 % of the expected greenhouse warming at the end of 21st and around 25 % at the end of 22nd century. The regional effects are predicted to be stronger, in particular in northern high latitude winter. In the stratosphere, the reduced incoming ultraviolet radiation leads to less ozone production by up to 8 %, which overcompensates the anticipated ozone increase due to reduced stratospheric temperatures and an acceleration of the Brewer-Dobson circulation. This, in turn, leads to a delay in total ozone column recovery from anthropogenic chlorine-induced depletion, with a global ozone recovery to the pre-ozone hole values happening only upon completion of the grand solar minimum in the 22nd century or later.

scholarly journals High resolution atmospheric reconstruction for Europe 1948–2012: coastDat2

2013 ◽  
Vol 6 (2) ◽  
pp. 779-809 ◽  
Author(s):  
B. Geyer
Keyword(s):  
Climate Model ◽  
Numerical Models ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Data Sets ◽  
Data Set ◽  
Horizontal Grid ◽  
Global Reanalysis ◽  
Marine Climate

Abstract. The coastDat data sets were produced to give a consistent and homogeneous database mainly for assessing weather statistics and long-term changes for Europe, especially in data sparse regions. A sequence of numerical models was employed to reconstruct all aspects of marine climate (such as storms, waves, surges etc.) over many decades. Here, we describe the atmospheric part of coastDat2 (Geyer and Rockel, 2013, doi:10.1594/WDCC/coastDat-2_COSMO-CLM). It consists of a regional climate reconstruction for entire Europe, including Baltic and North Sea and parts of the Atlantic. The simulation was done for 1948 to 2012 with a regional climate model and a horizontal grid size of 0.22° in rotated coordinates. Global reanalysis data were used as forcing and spectral nudging was applied. To meet the demands on the coastDat data set about 70 variables are stored hourly.

scholarly journals A reassessment of the discrepancies in the annual variation of <i>δ</i>D-H<sub>2</sub>O in the tropical lower stratosphere between the MIPAS and ACE-FTS satellite data sets

2020 ◽  
Vol 13 (1) ◽  
pp. 287-308
Author(s):  
Stefan Lossow ◽  
Charlotta Högberg ◽  
Farahnaz Khosrawi ◽  
Gabriele P. Stiller ◽  
Ralf Bauer ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Annual Variation ◽  
Lower Stratosphere ◽  
Michelson Interferometer ◽  
Tape Recorder ◽  
Data Sets ◽  
Altitude Effect ◽  
Data Set ◽  
Tropical Tropopause ◽  
Tropopause Region

Abstract. The annual variation of δD in the tropical lower stratosphere is a critical indicator for the relative importance of different processes contributing to the transport of water vapour through the cold tropical tropopause region into the stratosphere. Distinct observational discrepancies of the δD annual variation were visible in the works of Steinwagner et al. (2010) and Randel et al. (2012). Steinwagner et al. (2010) analysed MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observations retrieved with the IMK/IAA (Institut für Meteorologie und Klimaforschung in Karlsruhe, Germany, in collaboration with the Instituto de Astrofísica de Andalucía in Granada, Spain) processor, while Randel et al. (2012) focused on ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Here we reassess the discrepancies based on newer MIPAS (IMK/IAA) and ACE-FTS data sets, also showing for completeness results from SMR (Sub-Millimetre Radiometer) observations and a ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg and Modular Earth Submodel System) Atmospheric Chemistry (EMAC) simulation (Eichinger et al., 2015b). Similar to the old analyses, the MIPAS data set yields a pronounced annual variation (maximum about 75 ‰), while that derived from the ACE-FTS data set is rather weak (maximum about 25 ‰). While all data sets exhibit the phase progression typical for the tape recorder, the annual maximum in the ACE-FTS data set precedes that in the MIPAS data set by 2 to 3 months. We critically consider several possible reasons for the observed discrepancies, focusing primarily on the MIPAS data set. We show that the δD annual variation in the MIPAS data up to an altitude of 40 hPa is substantially impacted by a “start altitude effect”, i.e. dependency between the lowermost altitude where MIPAS retrievals are possible and retrieved data at higher altitudes. In itself this effect does not explain the differences with the ACE-FTS data. In addition, there is a mismatch in the vertical resolution of the MIPAS HDO and H2O data (being consistently better for HDO), which actually results in an artificial tape-recorder-like signal in δD. Considering these MIPAS characteristics largely removes any discrepancies between the MIPAS and ACE-FTS data sets and shows that the MIPAS data are consistent with a δD tape recorder signal with an amplitude of about 25 ‰ in the lowermost stratosphere.

scholarly journals The SPARC water vapour assessment II: Profile-to-profile and climatological comparisons of stratospheric <i>δ</i>D(H<sub>2</sub>O) observations from satellite

2018 ◽  
Author(s):  
Charlotta Högberg ◽  
Stefan Lossow ◽  
Ralf Bauer ◽  
Kaley A. Walker ◽  
Patrick Eriksson ◽  
...  
Keyword(s):  
Water Vapour ◽  
Atmospheric Chemistry ◽  
Lower Stratosphere ◽  
Isotopic Ratio ◽  
Michelson Interferometer ◽  
Data Sets ◽  
Data Set ◽  
Spectroscopic Database ◽  
Temporal And Spatial ◽  
Chemistry Experiment

Abstract. Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), we have evaluated five data sets of δD(H2O) obtained from observations of Odin/SMR (Sub-Millimetre Radiometer), Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding) and SCISAT/ACE-FTS (Science Satellite/Atmospheric Chemistry Experiment-Fourier Transform Spectrometer) using profile-to-profile and climatological comparisons. Our focus is on stratospheric altitudes, but results from the upper troposphere to the lower mesosphere are provided. There are clear quantitative differences in the measurements of the isotopic ratio, which primarily concerns the comparisons to the SMR data set. In the lower stratosphere, this data set shows a higher depletion than the MIPAS and ACE-FTS data sets. The differences maximise close to 50 hPa and exceed 200 per mille. With increasing altitude, the biases typically decrease. Above 4 hPa, the SMR data set shows a lower depletion than the MIPAS data sets, on occasion exceeding 100 per mille. Overall, the δD biases of the SMR data set are driven by HDO biases in the lower stratosphere and by H2O biases in the upper stratosphere and lower mesosphere. In between, in the middle stratosphere, the biases in δD are a combination of deviations in both HDO and H2O. These biases are attributed to issues with the calibration, in particular in terms of the sideband filtering for H2O, and uncertainties in spectroscopic parameters. The MIPAS and ACE-FTS data sets agree rather well between about 100 hPa and 10 hPa. The MIPAS data sets show less depletion below about 15 hPa (up to about 30 per mille), due to differences in both HDO and H2O. Higher up the picture is reversed, and towards the upper stratosphere the biases typically increase. This is driven by increasing biases in H2O and on occasion the differences in δD exceed 80 per mille. Below 100 hPa, the differences between the MIPAS and ACE-FTS data sets are even larger. In the climatological comparisons, the MIPAS data sets continue to show less depletion than the ACE-FTS data sets below 15 hPa during all seasons, with some variations in magnitude. The differences between the MIPAS and ACE-FTS data come from different aspects, such as differences in the temporal and spatial sampling (except for the profile-to-profile comparisons), cloud influence, vertical resolution, and the microwindows and spectroscopic database chosen. Differences between data sets from the same instrument are typically small in the stratosphere.

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