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Two deep-layer tropospheric temperature products, one for the lower troposphere (T 2LT) and one for the midtroposphere (T 2 , which includes some stratospheric emissions), are based on the observations of channel 2 of the microwave sounding unit on National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites. Revisions to version C of these datasets have been explicitly applied to account for the effects of orbit decay (loss of satellite altitude) and orbit drift (east-west movement). Orbit decay introduces an artificial cooling in T 2LT , while the effects of orbit drift introduce artificial warming in both T 2LT and T 2. The key issues for orbit drift are 1) accounting for the diurnal cycle and 2) the adjustment needed to correct for spurious effects related to the temperature of the instrument. In addition, new calibration coefficients for NOAA-12 have been applied. The net global effect of these revisions (version D) is small, having little impact on the year-to-year anomalies. The change in global trends from C to D for 1979-98 for T 2LT is an increase from ϩ0.03 to ϩ0.06 K decade Ϫ1 , and a decrease for T 2 from ϩ0.08 to ϩ0.04 K decade Ϫ1 .

The humidity of the free troposphere is being increasingly scrutinized in climate research due to its central role in global warming theory through positive water vapor feedback. This feedback is the primary source of global warming in general circulation models (GCMs). Because the loss of infrared energy to space increases nonlinearly with decreases in relative humidity, the vast dry zones in the Tropics are of particular interest. These dry zones are nearly devoid of radiosonde stations, and most of those stations have, until recently, ignored the low humidity information from the sondes. This results in substantial uncertainty in GCM tuning and validation based on sonde data. While satellite infrared radiometers are now beginning to reveal some information about the aridity of the tropical free troposphere, the authors show that the latest microwave humidity sounder data suggests even drier conditions than have been previously reported. This underscores the importance of understanding how these low humidity levels are controlled in order to tune and validate GCMs, and to predict the magnitude of water vapor feedback and thus the magnitude of global warming. D. Braswell + Feedback from the redistribution of water vapour remains a substantial uncertainty in climate models.. .. Much of the current debate has been addressing feedback from the tropical upper troposphere, where the feedback appears likely to be positive. However, this is not yet convincingly established; much further evaluation of climate models with regard to observed processes is needed. Climate Change 1995, IPCC Second Assessment 1. Introduction Most global warming predicted by general circulation models (GCMs) is due to positive water vapor feedback between water vapor and surface temperature

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[1] The impact of time-varying radiative forcing on the diagnosis of radiative feedback from satellite observations of the Earth is explored. Phase space plots of variations in global average temperature versus radiative flux reveal linear striations and spiral patterns in both satellite measurements and in output from coupled climate models. A simple forcingfeedback model is used to demonstrate that the linear striations represent radiative feedback upon nonradiatively forced temperature variations, while the spiral patterns are the result of time-varying radiative forcing generated internal to the climate system. Only in the idealized special case of instantaneous and then constant radiative forcing, a situation that probably never occurs either naturally or anthropogenically, can feedback be observed in the presence of unknown radiative forcing. This is true whether the unknown radiative forcing is generated internal or external to the climate system. In the general case, a mixture of both unknown radiative and nonradiative forcings can be expected, and the challenge for feedback diagnosis is to extract the signal of feedback upon nonradiatively forced temperature change in the presence of the noise generated by unknown time-varying radiative forcing. These results underscore the need for more accurate methods of diagnosing feedback from satellite data and for quantitatively relating those feedbacks to long-term climate sensitivity.