William D. Braswell

Error Estimates of Version 5.0 of MSU-AMSU Bulk Atmospheric Temperatures

Abstract Deep-layer temperatures derived from satellite-borne microwave sensors since 1979 are revised (version 5.0) to account for 1) a change from microwave sounding units (MSUs) to the advanced MSUs (AMSUs) and 2) an improved diurnal drift adjustment for tropospheric products. AMSU data, beginning in 1998, show characteristics indistinguishable from the earlier MSU products. MSU–AMSU error estimates are calculated through comparisons with radiosonde-simulated bulk temperatures for the low–middle troposphere (TLT), midtroposphere (TMT), and lower stratosphere (TLS.) Monthly (annual) standard errors for global mean anomalies of TLT satellite temperatures are estimated at 0.10°C (0.07°C). The TLT (TMT) trend for January 1979 to April 2002 is estimated as +0.06° (+0.02°) ±0.05°C decade–1 (95% confidence interval). Error estimates for TLS temperatures are less well characterized due to significant heterogeneities in the radiosonde data at high altitudes, though evidence is presented to suggest that since 19...

MSU Tropospheric Temperatures: Dataset Construction and Radiosonde Comparisons

Abstract Two deep-layer tropospheric temperature products, one for the lower troposphere (T2LT) and one for the midtroposphere (T2, 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 T2LT, while the effects of orbit drift introduce artificial warming in both T2LT and T2. 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. T...

How dry is the tropical free troposphere? : Implications for global warming theory

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.

On the Misdiagnosis of Surface Temperature Feedbacks from Variations in Earth’s Radiant Energy Balance

The sensitivity of the climate system to an imposed radiative imbalance remains the largest source of uncertainty in projections of future anthropogenic climate change. Here we present further evidence that this uncertainty from an observational perspective is largely due to the masking of the radiative feedback signal by internal radiative forcing, probably due to natural cloud variations. That these internal radiative forcings exist and likely corrupt feedback diagnosis is demonstrated with lag regression analysis of satellite and coupled climate model data, interpreted with a simple forcing-feedback model. While the satellite-based metrics for the period 2000–2010 depart substantially in the direction of lower climate sensitivity from those similarly computed from coupled climate models, we find that, with traditional methods, it is not possible to accurately quantify this discrepancy in terms of the feedbacks which determine climate sensitivity. It is concluded that atmospheric feedback diagnosis of the climate system remains an unsolved problem, due primarily to the inability to distinguish between radiative forcing and radiative feedback in satellite radiative budget observations.

Cloud and radiation budget changes associated with tropical intraseasonal oscillations

[1] We explore the daily evolution of tropical intraseasonal oscillations in satellite-observed tropospheric temperature, precipitation, radiative fluxes, and cloud properties. The warm/rainy phase of a composited average of fifteen oscillations is accompanied by a net reduction in radiative input into the ocean-atmosphere system, with longwave heating anomalies transitioning to longwave cooling during the rainy phase. The increase in longwave cooling is traced to decreasing coverage by ice clouds, potentially supporting Lindzen’s ‘‘infrared iris’’ hypothesis of climate stabilization. These observations should be considered in the testing of cloud parameterizations in climate models, which remain sources of substantial uncertainty in global warming prediction. Citation: Spencer, R. W., W. D. Braswell, J. R. Christy, and J. Hnilo (2007), Cloud and radiation budget changes associated with tropical intraseasonal oscillations, Geophys. Res. Lett., 34, L15707, doi:10.1029/2007GL029698.

Potential Biases in Feedback Diagnosis from Observational Data: A Simple Model Demonstration

Abstract Feedbacks are widely considered to be the largest source of uncertainty in determining the sensitivity of the climate system to increasing anthropogenic greenhouse gas concentrations, yet the ability to diagnose them from observations has remained controversial. Here a simple model is used to demonstrate that any nonfeedback source of top-of-atmosphere radiative flux variations can cause temperature variability, which then results in a positive bias in diagnosed feedbacks. This effect is demonstrated with daily random flux variations, as might be caused by stochastic fluctuations in low cloud cover. The daily noise in radiative flux then causes interannual and decadal temperature variations in the model’s 50-m-deep swamp ocean. The amount of bias in the feedbacks diagnosed from time-averaged model output depends upon the size of the nonfeedback flux variability relative to the surface temperature variability, as well as the sign and magnitude of the specified (true) feedback. For model runs produ...

How accurate are satellite ‘thermometers’?

We believe that lower-tropospheric temperatures measured directly by satellites have excellent long-term accuracy, as seen by comparisons with independent atmospheric measurements from weather balloons. Our results contradict indirect measurements by Hurrell and Trenberth who claimed that the satellite data have significant discontinuities.

Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds

Abstract The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A’s higher spatial and radiometric resolutions provide more useful information on the strength of the middle- and upper-tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. The gradient wind equation is recast to include AMSU-A-derived variables. Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (Vmax). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1–10 Tb data (δrTb), the squares of these gradients, a channel-15-based scattering index (SI89), and area-averaged Tb. Calculations of Tb and δrTb from mesoscale model simulations o...

The role of ENSO in global ocean temperature changes during 1955–2011 simulated with a 1D climate model

Global average ocean temperature variations to 2,000 m depth during 1955–2011 are simulated with a 40 layer 1D forcing-feedback-mixing model for three forcing cases. The first case uses standard anthropogenic and volcanic external radiative forcings. The second adds non-radiative internal forcing (ocean mixing changes initiated in the top 200 m) proportional to the Multivariate ENSO Index (MEI) to represent an internal mode of natural variability. The third case further adds ENSO-related radiative forcing proportional to MEI as a possible natural cloud forcing mechanism associated with atmospheric circulation changes. The model adjustable parameters are net radiative feedback, effective diffusivities, and internal radiative (e.g., cloud) and non-radiative (ocean mixing) forcing coefficients at adjustable time lags. Model output is compared to Levitus ocean temperature changes in 50 m layers during 1955–2011 to 700 m depth, and to lag regression coefficients between satellite radiative flux variations and sea surface temperature between 2000 and 2010. A net feedback parameter of 1.7Wm−2 K−1 with only anthropogenic and volcanic forcings increases to 2.8Wm−2 K−1 when all ENSO forcings (which are one-third radiative) are included, along with better agreement between model and observations. The results suggest ENSO can influence multi-decadal temperature trends, and that internal radiative forcing of the climate system affects the diagnosis of feedbacks. Also, the relatively small differences in model ocean warming associated with the three cases suggests that the observed levels of ocean warming since the 1950s is not a very strong constraint on our estimates of climate sensitivity.

Estimation of Tropospheric Temperature Trends from MSU Channels 2 and 4

Abstract The problems inherent in the estimation of global tropospheric temperature trends from a combination of near-nadir Microwave Sounding Unit (MSU) channel-2 and -4 data are described. The authors show that insufficient overlap between those two channels’ weighting functions prevents a physical removal of the stratospheric influence on tropospheric channel 2 from the stratospheric channel 4. Instead, correlations between stratospheric and tropospheric temperature fluctuations based upon ancillary (e.g., radiosonde) information can be used to statistically estimate a correction for the stratospheric influence on MSU 2 from MSU 4. Fu et al. developed such a regression relationship from radiosonde data using the 850–300-hPa layer as the target predictand. There are large errors in the resulting fit of the two MSU channels to the tropospheric target layer, so the correlations from the ancillary data must be relied upon to provide a statistical minimization of the resulting errors. Such relationships dep...