Teleconnectivity in Upper Tropospheric Clouds and Water Vapour from the EOS Microwave Limb Sounder and their implication for the Pacific Ocean-Atmosphere Coupling System

Upper tropospheric clouds and water vapour have a large affect on the Earth's radiation budget. The NASA Earth Observing System (EOS) comprises of a series of polar orbiting satellites of which a subset is known as the A- train constellation. Close comparisons of clouds and the radiation budget may be made from A-train instruments in both space and time, with excellent precision and spatial coverage. The presence of high ice clouds (both thick cirrus and cumulonimbus) and water vapour are detected well by the GHz radiometers of the passive Microwave Limb Sounding (MLS) instrument on the EOS Aura satellite. Fluctuations in these upper tropospheric (UT) components are examined in conjunction with longwave, shortwave and albedo measurements from the Clouds and Radiant Energy System (CERES) instrument. The El Nino Southern Oscillation (ENSO) plays a key role in the natural variability of the climate system, and has strong links to A-train observations. Analysis of MLS cloud ice at UT levels is a novel and accurate measure of deep convective cores associated with the ascending branch of the Walker cell. As such, MLS retrieved clouds above 177hPa and water vapour above 316hPa were found to exhibit a significant teleconnectivity between Darwin and Tahiti. Variability in radiation budget was also detected by the CERES instrument on the Aqua and Terra satellites, not only over the Pacific, but over the entire tropical belt. Spatially gridded MLS measurements are examined using Principal Components Analysis to accurately replicate the traditional Multivariant ENSO Index. This methodology enables perturbations in the Pacific radiation budget to be estimated from cloud and water vapour variability over the ENSO cycle and a potential for back-dating upper tropospheric MLS measurements. This has implications for climate prediction, by reducing uncertainty in the climate sensitivity parameter. It also highlights strong links between the upper troposphere and surface, climate- ocean feedbacks and may enable better prediction of natural climate variability over a seasonal timescale.