PNA Winter correlated with globally gridded temperatures (Jan-Feb-Mar (JFM) averages ) (Monthly means)
x Calculated T-value In this example the T value is conform with the null hypothesis that there is no correlation. We accept H 0 at the chosen two sided significance test-level of p (for example 0.05).
x Calculated T-value In this example the T value is unusually far in the tails of the theoretical T-distribution for a zero correlation. We reject H 0 at the chosen two sided significance test-level of p (for example 0.05) and say: there is a significant correlation at the (two-sided) 5-% significance level
PNA Winter correlated with globally gridded temperatures (Jan-Feb-Mar (JFM) averages ) (Monthly means) Masked out non-significant correlations (two-sided t-test at 5% level)
ENSO Index: Tropical Pacific Sea Surface Temperatures Seasonal forcast outlook: El Nino is coming!
Source: (retrieved ) 7 days
Source: (retrieved ) 12 months 1 week
Source: (retrieved ) 60 years 1 year
Source: (retrieved ) 300 years 60 years
Source: (retrieved ) 800 ?
Source: (retrieved ) 800,000 years 300 years Reconstructions from air bubbles trapped in Antarctic Ice Cores
Atmospheric Environmental sciences study processes on a wide range of time scales! from tenth of seconds in turbulence (or even less, e.g. lightning processes ) Weather (hours to weeks) Seasonal variability (weeks to months) Climate variability (years-decades) Ice age cycles (10-100,000 years) Geological processes (plate tectonics) > 10,000,000yrs
Atmospheric Environmental sciences study processes on a wide range of time scales! The sampling rate at which we observe these processes must match the typical time-scales of the variations
scripts: rmean.R timeseries_noise1.R timeseries_record1.R timeseries_pna_daily.R timeseries_co2_ R timeseries_insolation_ R data: norm.daily.pna.index.b current.ascii csv timeseries_co2_ asc timeseries_insolation_JJA_ asc sound_staple1.csv sound_plasticbag1.csv sound_noisy_tone1.csv sound_water_fountain_sample.csv