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Solar Activity, Cosmic Rays, and Global Warming Alexis Wagener and Greg Edwards.

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Presentation on theme: "Solar Activity, Cosmic Rays, and Global Warming Alexis Wagener and Greg Edwards."— Presentation transcript:

1 Solar Activity, Cosmic Rays, and Global Warming Alexis Wagener and Greg Edwards

2 Cosmic Rays Very high energy particles Protons and light nuclei Origins are unclear, evidence suggests they are emitted from supernovae and galactic nuclei Image (right) shows cosmic ray collision, resulting in “atmospheric cascade”

3 Heliosphere: region maintained by solar wind whose magnetic properties maintain a “bubble” against outside pressure of interstellar medium Magnetosphere: area near astronomical unit where charged particles are controlled by objects magnetic field Heliosphere and Magnetosphere

4 The Atmospheric Effects Ionization is the process by which an atom or molecule gains or loses an electron, becoming charged and more reactive Cosmic Rays cause ionization in the atmosphere, creating aerosols in the troposphere (the lowest 10km) which then act as Cloud Condensation Nuclei (CCN)

5 Coronal Mass Ejections Massive burst of solar wind and magnetic fields being released into space Magnetic field generated creates a temporary shield against cosmic rays The image (right) depicts solar wind disrupting the Earth’s magnetosphere

6 Forbush Decreases Reductions of galactic cosmic rays for periods of hours or days Occurs from a disruption in the Earth’s magnetosphere in a geomagnetic storm as solar winds reach the earth, repulsing charged particles from the Earth’s atmosphere Cosmic Ray Variation vs. Time Red: Oulu, Finland Green: Magadan, Russia Blue: Inuvik, Canada

7 Solar Activity Cycle Occur over 11 years, resulting in modulation of sunspots Cycle is marked by variation of short-wave solar irradiance, and frequency of coronal mass ejections and solar flares Observed Number of Sunspots vs. Time

8 Sunspots Temporary phenomena on the photosphere: observed as visibly dark spots Caused by intense magnetic activity Images (above) of our Sun taken in December 2006. Note the two sunspots in close proximity, each having opposite magnetic orientation Used to measure intensity of solar cycle since coronal mass ejections occur in magnetically active region surrounding sunspots

9 Special Sensor Microwave/Imager Measures brightness temperatures at four frequencies (85, 37, 22, and 19 GHz) Information within measurements allow for calculation of near-surface wind speed, columnar water vapor, columnar cloud liquid water, and precipitation Digital Rendering of SSM/I scan geometry

10 Moderate Resolution Imaging Spectroradiometer Launched into orbit by Nasa in 1999 on board Terra Satellite and 2002 on board Aqua Satellite Instruments image entire Earth every 1-2 days using varying resolutions Designed to provide measurement in large-scale global dynamics including cloud cover and radiation budget Digital rendering of MODIS in orbit

11 Aerosol Robotic Network (AERONET) Network of ground based photometers used to measure atmospheric aerosol properties Measures radiances at fixed wavelengths to determine an average of the total aerosol column within the atmosphere CIMEL Sunphotometer

12 Neutron Monitors Ground based detector used to measure high- energy particles striking the atmosphere Measures by-products reaching the surface (such as neutrons) of atmospheric cascade caused by primary cosmic ray collision Neutron Monitor in the Antarctic

13 Ion Chambers Gas filled radiation detector used to measure ionization of atmosphere Specifically designed lead shielded ion chambers are used to measure muon intensity Depiction (right) of ion chamber measuring induced current from ionization of gaseous field

14 Observed Solar Activity Trend Blue: Beryllium-10 concentration Red: Annual observed sunspots The trend of increased solar activity correlates to increased atmospheric ionization Beryllium-10 is formed in the atmosphere by cosmic ray collision Correlation between trends suggests solar activity is responsible for reduction in cosmic ray flux

15 Global Temperature and Cosmic Ray Flux Global Temperature Anomaly vs. Time Cosmic Ray Intensity Decrease vs. Time Red: percentage over Solar Activity Cycles Blue: mean percentage Similar trend after 1980 suggests correlation between global temperature and cosmic rays

16 Supporting the theory - Svensmark et al. Hypothesis: Forbush Decreases in Galactic Cosmic Rays lead to less liquid water in low-altitude clouds, causing global warming. Coronal Mass Ejections (releasing magnetic plasma clouds) lead to Forbush decreases in Cosmic Ray intensity in the Earth’s Atmosphere

17 26 Solar Events, 1987-2007 Forbush Decrease dates ranked by depression of ionization Dates in bold denote dates for which AERONET data is available There is observed to be a direct correlation between Forbush Decreases (of cosmic rays) and decreased ionization in the lower atmosphere

18 Response to Forbush Decreases Aerosol particles Cloud Water content Liquid water cloud fraction IR-detected low cloud Red Curves show % change in cosmic ray neutron counts Cloud water content responds to the cosmic ray minimum 4 days later than the aerosol count, supporting the hypothesized mechanism

19 Comparison of Forbush Decrease effects Negative slopes suggest that minima in clouds and aerosols deepen with the strength of Forbush Decrease events Points represent individual Forbush Decrease events Blue: weighted lines of best fit

20 Discussion and Conclusion ●Large error bars may have masked Forbush Decrease effects ●Other studies used more Forbush Decreases, however they included weaker ones, with greater relative uncertainties ●Timescales: Evidence suggests aerosol growth occurs over a few hours, however some models suggest growth in the order of several days This study claims to show evidence of a strong influence on aerosol levels and cloudiness from solar variability on a global scale.

21 Ahluwalia - Cosmic Ray Intensity Variation Using data from multiple high-latitude ion chambers measuring muon intensity with similar voltage cutoffs, one data segment is generated for cosmic ray variation from 1937-1994 Measured ionization and cosmic ray intensity is juxtaposed with observed solar activity on same time- scale Additional hypothesis for climate affect: Peak in solar activity leads low conductivity in atmosphere and build- up of electric field, resulting in higher frequency of thunderstorms and greater cloud cover

22 Ahluwalia Raw Data Black lines: annual mean hourly values of muon intensity (.01% change) vs. Time Top line: Ionization Chamber at Cheltenham/Fredericksburg (1937-72) BottomLine: Ionization Chamber at Yakutsk (1953- 54) Similar trend in the overlapping years allowed data to be combined to one segment

23 Normalization Issues Yakutsk 1965 data point is ~1.6% above 1954 data point, inconsistent with Fredericksburg and global neutron monitor data Cosmic Ray modulation from 1957-65 is 1.11% greater for Yakutsk than Fredericksburg Cosmic Ray Decrease (.01%) vs. Time Data “filtering” begins to show new overall trend emerging

24 Normalized Data 1.11% is added to Yakutsk data points from 1953-63 Points are plotted to a common scale with normalization 100% in 1965 New data segment suggests trend in Cosmic Ray Decrease consistent with global temperature anomaly Normalized Mean Decrease (.01%) vs. Time; Solar Activity max. and min. denoted by M and m, respectively

25 Correlation between Solar Activity Cycles and Cosmic Ray Intensity Solar Activity Cycle juxtaposed with corresponding cosmic ray intensity Solar Activity (Sunspots) vs. Cosmic Ray Intensity (% Decrease) No significant correlation between amplitude of solar activity and amplitude of cosmic ray modulation

26 Damon and Laut - Statistical Errors Based on non-filtered results, observers created curves to show strong correlation between solar activity cycles and global temperatures Recent data points were found to be arithmetic errors, creating a discrepancy with the physical statistics These errors in the data and subsequent analysis were not recognized widely in the literature and should not be used to draw conclusions between solar activity and global climate

27 Suggested Correlation Between Solar Cycle Length and Temperature Change Original figures released in 1991 Blue line: filtered, partially filtered, and non-filtered data for solar cycle length (years) vs. Time Red line: Northern Hemisphere surface temperature anomaly (degrees Celsius) vs. Time Given range of cycle length and temperature anomaly suggests 95% correlation between trends

28 Adjusted Figures for Solar Cycle Length Blue line: Solar Cycle Length (years) vs. Time New figures released in 2000, suggesting same general curve Points 3, 4 are the result of trivial arithmetic error Though enough data is available for filtering of entire curve, final points are still not representation of the physical data

29 Correct Filtered Solar Cycle Length Blue line: Solar Cycle Length (years) vs. Time Points 0-4 have undergone correct filtering with data available through 2004 Recent trend shows relatively no change in solar cycle length and small correlation with temperature change

30 Solar Cycle and Temperature Change on Larger Timescale Orange: Sunspot Cycle Length (years) Red: Smoothing of SCL (years) Green: Surface Temperature Anomaly (Mann et al., 1998) Blue: Surface Temperature Anomaly (Jones and Moberg, 2003) Larger timescale shows discrepancy between temperature and solar cycle length trends

31 Criticism on Svensmark 1997: Svensmark and Friis-Christensen suggest a relationship between galactic cosmic rays and global cloud cover using data not representative of global values 1998: Svensmark releases update with correct data, contradicting the original hypothesis 2000: Marsh and Svensmark release new hypothesis suggesting relationship is between galactic cosmic rays and “low cloud cover,” not total cloud cover

32 RealClimate - Skepticism on Cosmic Ray and Low Cloud Relationship Rejects Svensmark’s hypothesis on cosmic ray affecting low cloud cover, citing selective use of data and inconclusive results Takes issue with inconsistency in findings aerosols and cloud water content reach minima ~5 and ~7 days after forbush decrease, respectively, but cloud water content also reaches minimum ~4 days after aerosol minimum Cloud lifetime is in the order of hours: observational effects on clouds days after the event is not sensible

33 Statistical Criticism of Svensmark Svensmark et al. take measurements from only 26 Forbush Decreases, signifying only 5 as strong events Forbush Decreases were measured with.06 GV cutoff neutron monitor, also measuring low-energy particles Gaussian smooth with width of 2 and maximum of 10 days may result in omission of significant results, since hypothesis suggests results are in the order of several days


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