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On the modelling and diagnostics of s olar activity effect s i n the atmosphere Project SOLICE. Tomáš Halenka *). *) regular associate of the Abdus Salam ICTP. Solar activity forcing.
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On the modelling and diagnostics of solar activity effects in the atmosphere Project SOLICE Tomáš Halenka*) *) regular associate of the Abdus Salam ICTP
Solar activity forcing • amplitude of total solar irradiance variance causes forcing about 0.1 Wm-2 during 11-years solar cycle – comparable to trend in GHG forcing, but strongly latitudinally dependent • UV radiation (200-300nm) changes about 9% • Lyman-a (121.6nm) by a factor of 2
Project EC SOLICE (Solar Influences on Climate and the Environment) funded by the European Community 5thFP with objectives: • to extract the stratospheric solar signal in datasets of ozone, temperature, geopotential height, vorticity and circulation • to assess the impacts of solar variability in the troposphere • to investigate the response of stratospheric composition and climate to variations in solar ultra-violet radiation using general circulation models (GCMs), coupled chemistry-climate models (CCMs), chemical transport models (CTMs) and mechanistic models • to develop a more complete understanding of the mechanisms by which solar variability influences the natural variability of the stratosphere and troposphere
Project EC SOLICE (Solar Influences on Climate and the Environment) • initiated in April 2000 • completed in December 2003 • final report in March 2004 • involving eight Europeaninstitutions and two American collaborators • full results and further project details are available at http://www.imperial.ac.uk/research/spat/research/SOLICE/index.htm. This presentation of selection of results based on final report and article prepared for SPARCNews by coordinator of the project J. D. Haigh, Imperial College, London from contributions of SOLICE Partners
SOLICE Partners J.D. Haigh1, J. Austin2,3, N. Butchart2, M.-L. Chanin4, S. Crooks5, L.J. Gray6,7, T. Halenka8, J. Hampson4, L.L. Hood9, I.S.A. Isaksen10, P. Keckhut4, K. Labitzke11, U. Langematz11, K. Matthes11, M. Palmer5,6, B.Rognerud10, K. Tourpali12, C. Zerefos12,13 • Imperial College London, UK • The Met. Office, Exeter, UK • now at NOAA GFDL, Princeton, USA • Service d’Aeronomie du CNRS, France • University of Oxford, UK • Rutherford Appleton Laboratory, Didcot, UK • now at University of Reading, UK • Charles University, Prague, Czech Republic • University of Arizona, Tucson, USA • University of Oslo, Norway • Free University of Berlin, Germany • Aristotle University of Thessaloniki, Greece • now at University of Athens, Greece
Scientific achievements and main deliverables: Answers to the following questions: • What are the observed solar responses in middle atmosphere temperature and wind? • What is the observed interaction of the solar cycle and QBO in the lower stratosphere? • What are the observed solar responses in circulation patterns? • What is the response to solar variability in the troposphere? • What are the observed solar responses in ozone? • How successfully do GCM simulations with controlled irradiance and ozone variations reproduce observed solar signal? • Does inclusion of an interactive ocean improve simulations? • Does a representation of the QBO improve model simulations of the solar influence? • How well do chemistry-climate models simulate solar cycle impact on stratospheric ozone and temperature? • How well do chemistry-climate models simulate the 27-day solar cycle impact on stratospheric ozone and temperature? • What was the impact of the Maunder Minimum in solar activity on climate? • What is a possible mechanism for the solar signal to reach the lower stratosphere? • How do solar activity levels affect the solar radiative forcing of climate? • To what extent does solar variability impact surface UV? • What is the possible mechanism for the stratospheric low latitude solar signal to reach the troposphere?
What are the observed solar responses in middle atmosphere temperature and wind? Annual-mean zonal temperature response to solar activity based on SSU/MSU data from 1979 up to 1998. Annual response is presented as a function of latitude bands and pressure heights (to 100hPa up to 0.4 hPa corresponding to the tropopause level up to 55 km). The gray shaded regions indicate statistically significant signal. Examples of vertical profiles of temperature responses from the rocketsonde data (1969-early 1990) in the tropics, NH subtropics and NH mid-latitude with 1 and 2 sigma error bar (Keckhut et al. 2003). Results from the zonal wind and temperature regression using the ERA-40 analysis showing the average annual response in the stratosphere and mesosphere (Crooks and Gray, 2004). Shading denotes the 95% and 99% confidence levels.
What is the observed interaction of the solar cycle and QBO in the lower stratosphere? Left: Vertical meridional sections of the correlations between the 10.7cm solar flux and the de-trended zonal mean temperatures in July; shaded for emphasis where correlations are above 0.5. Right: The respective temperature differences (K) between solar maxima and minima, shaded where the correlations are above 0.5. Upper panels: all years; middle panels: only years in the east phase of the QBO; lower panels: only years in the west phase of the QBO. (NCEP/NCAR re-analyses, 1968-2002) (Labitzke 2003) Left: Correlations between the 10.7cm solar flux and the detrended 30-hPa temperatures in July; shaded for emphasis where correlations are above 0.5. Right: The respective temperature differences (K) between solar maxima and minima; shaded where the differences are above 1 K. Upper panels: all years; middle panels: only years in the east phase of the QBO; lower panels: only years in the west phase of the QBO. (NCEP/NCAR re-analyses, 1968-2002) (Labitzke, 2003)
What is the observed interaction of the solar cycle and QBO in the lower stratosphere? Correlations between the 10.7cm solar flux and the detrended 30-hPa geopotential heights in July; shaded for emphasis where correlations are above 0.5. Right: The respective geopotential heights differences (m) between solar maxima and minima; shaded where the differences are above 60 gpm. Upper panels: all years; middle panels: only years in the east phase of the QBO; lower panels: only years in the west phase of the QBO. (NCEP/NCAR re-analyses, 1968-2002) (Labitzke, 2003) Scatter diagrams (de-trended 30-hPa temperatures (C) against the 10.7cm solar flux) at two grid points. Upper panels: 25N/90W; lower panels:20S/60W. Left: years in the east phase of the QBO (n=16); right: years in the west phase (n=19). The numbers indicate the respective years; r=correlation coefficient, ΔT= temperature difference (K) between solar maxima and minima. Period: 1968-2002. (Labitzke 2003)
What are the observed solar responses in circulation patterns? Ratio from composites for solar max and min [2*(max-min)/(max+min)], for lower wavenumbers of potential vorticity expansion
What are the observed solar responses in circulation patterns? Moving window Fourier spectral analysis (width 256 month) for spherical harmonic coefficient 4-5. On y-axis time series wavenumber k (period[month] = 256/wavenumber). 4th mode of PCA analysis of geopotential field in 50 hPa level (left panel) together with the cross correlation analysis of running average of its component with solar flux (right panel).
What is the response to solar variability in the troposphere? Amplitudes of the components of variability in zonal mean temperature due to: (a) trend (b) solar, (c) QBO, (d) ENSO, (e) volcanoes, (f) NAO. The units are K/decade for the trend, otherwise maximum variation (K) over the data period. Shaded areas are not statistically significant at the 95% level using a Student’s t test.
What is the response to solar variability in the troposphere? Top left: annual mean zonal mean zonal wind. Other panels: amplitudes of the components of variability in zonal mean zonal wind due to Below mean panel downwards : trend, ENSO, NAO. Top right downwards: solar, volcanoes. The units are ms-1/decade for the trend, otherwise maximum variation (ms-1) over the data period.
How successfully do GCM simulations with controlled irradiance and ozone variations reproduce observed solar signal? Mean zonal mean wind differences between the solar maximum and solar minimum experiments in metres per second for the NH (20°-80°N) winter (November to February, top to bottom), contour interval: 2 m/s. From left to right: observations (NMC data from 1980-1997, update of Kodera (1995)), GISS model, MRI-G experiment, MRI-I experiment, FUB model, and IC model. (Figure 5 from Matthes et al. (2003)).
Does a representation of the QBO improve model simulations of the solar influence? Left: 10-hPa (32~km) long-term daily mean NP temperature for solar min (top) and max (bottom) experiments. QBOw: black line with shaded 2sigma standard deviation, QBOe: white line with unfilled 2sigma standard deviation. Vertical line in January to separate early and late winter. Figure 10 from Matthes et al. (2004). Right: same as left but for the UM model. Left: FUB-CMAM results, long-term mean wind differences between solar maxima and minima for the QBO east (left) and the QBOw experiment (right) for the NH from October to May and the surface to 80 km (1000 to 0.01 hPa), contour intervals: 2 m/s. Light (heavy) shading indicates the 95% (99%) significance level (Student t-test). Similar to figure 12a,b from Matthes et al. (2004); Right: same as left, but for the UM model from October until March.
How well do chemistry-climate models simulate solar cycle impact on stratospheric ozone and temperature? Impact of the 11-year solar cycle on annually averaged ozone in UMETRAC as a function of pressure and latitude. The shading in (a) denotes the regions of statistically significant change using a two-tailed t-test for the significance levels of 80%, 95% and 99%. Impact of the 11-year solar cycle on annually averaged temperature in UMETRAC as a function of pressure and latitude. The shading in (a) denotes the regions of statistically significant change using a two-tailed t-test for the significance levels of 80%, 95% and 99%.
How do solar activity levels affect the solar radiative forcing of climate?
Conclusions • The multiple regression analysis, which was developed within this contract to analyse the different dataset, has helped defining the conditions that a dataset should fulfil to be used for such detection: length of the data series, continuity, noise-level. This analysis has shown to be a powerful tool to identify the contribution of the different forcings (anthropogenic and natural). (question 1). • Our knowledge of the signature of solar response in both the troposphere and the stratosphere has been improved by using longer, improved datasets and improved techniques (questions 1, 2, 3, 4, 5). • The comparison of the solar signature observed from the whole datasets and their coherence with the output of the different models help supporting the hypothesis of a forcing mechanism involving the absorption of solar UV Flux by stratospheric ozone. • From this study, it appears clearly that only 3D models can represent the observations, because of the need to reproduce the 3D dynamical forcing (questions 6, 9, 10, 11). • Progress has been made in identifying the possible mechanisms that enable the solar response to extend deep into the lower stratosphere and troposphere (questions 12, 15). • The importance of including an interactive ocean and the quasi biennial oscillation in model simulations has been investigated (questions 7, 8) • The impact of changes in solar forcing have been investigated (questions 13, 14).
Conclusions The purpose of the project on a longer term would be to define what representation of the stratosphere, and mostly of the UV absorption by stratospheric ozone, is to be used in full climate GCMs to correctly reproduce the solar climate forcing, without being prohibitive in term of added complexity.