Trends And Inter-Annual Variability Of Outgoing Spectrally Resolved Infrared Emission In High, Middle, And Tropical Latitude Zones: Use Of Recent AIRS And IASI Data Sets For CLARREO Mission Formulation

A CLARREO proxy dataset created from near nadir observations from the NASA AIRS high-resolution infrared sounder on the Aqua platform was used to measure the natural variability of the ALL SKY infrared brightness temperature spectrum on monthly to multi-annual time scales and on global, zonal, and regional spatial scales After binning the spectral data on 5x5 degree grid cells and performing area weighting, the annual means were computed. A five year time period January 2003 to December 2007 was used in this study. We will illustrate the AIRS proxy monthly time series for the global mean spectrum as a deviation from the five year mean. Note that stratospheric and tropospheric channels are out of phase with each other. This natural variability on the global average can be used in the estimation of time to detect trends in brightness temperature since many months are required to average down the short term “weather noise” contained in the climate record. Since we believe trends in the atmosphere will depend on latitude, e.g. polar regions may have faster rates of change than the tropics, we also compute the zonal monthly brightness temperature anomaly for five latitude zones defined to as follows; Arctic (66.5 N - 85 N), Northern Hemisphere Mid-Latitude (23.5 N - 66.5 N), Tropical (23.5 S - 23.5 N), Southern Hemisphere Mid-Latitude (66.5 S - 23.5 S), Antarctic (85 S - 66.5 S). For each AIRS spectral channel we compute the observed five-year trend, the monthly standard deviation, and the one-month lag autocorrelation. The trends in the Arctic in particular are relatively large in the time period under observation whereas the trend for the global average is much smaller. From the standard deviation and autocorrelation we can compute a 95 percent confidence level for the significance of the observed trends using the Weatherhead et al (1998) formulation. In this formulation, a non-zero temporal autocorrelation in the time series leads to a longer time to detect the significance of a trend. The five year AIRS observation record shows some spectral channel have trends that are already statistically significant according to the Weatherhead formulation (e.g. the longwave all-sky window region in the Arctic) but the trends over the period 2003-2007 should not be considered representative of the longer climate record. For trends in the longer climate record we should make use of global climate model output which has been used to calculate trends in nadir brightness temperature, e.g. by Yi Huang (Harvard) and collaborators. However, the natural variability contained in the CLARREO proxy observations is believed to have greater realism than the variability of the climate models which do not contain all the relevant short term weather “noise”. For this reason we recommend that the observed variability and autocorrelation be used in the CLARREO mission formulation for the estimation of time to detect trends predicted by global climate models.