Detection and Attribution

Synthetic Microwave Sounding Unit (MSU) temperatures


Exceptional Stratospheric Contribution to Human Fingerprints on Atmospheric Temperature

Santer, B. D., S. Po-Chedley, L. Zhang, C.-Z. Zou, Q. Fu, S. Solomon, D. W. J. Thompson, C. Mears, and K. E. Taylor, 2023: Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.2300758120 (Download Data – 117MB)


Natural variability contributes to model-satellite differences in tropical tropospheric warming

Po-Chedley, S., B. D. Santer, S. Fueglistaler, M. D. Zelinka, P. J. Cameron-Smith, J. F. Painter, Q. Fu, 2021: Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.2020962118


Quantifying stochastic uncertainty in detection time of human-caused climate signals

Benjamin D. Santer, John C. Fyfe, Susan Solomon, Jeffrey F. Painter, Céline Bonfils, Giuliana Pallotta, Mark D. Zelinka Proceedings of the National Academy of Sciences Sep 2019, 201904586; DOI: 10.1073/pnas.1904586116


Human influence on the seasonal cycle of tropospheric temperature


Causes of differences in model in satellite tropospheric warming rates

Tropospheric Warming Over the Past Two Decades


New Synthetic MSU Data

We now employ a new method to calculate synthetic Microwave Sounding Unit (MSU) atmospheric temperatures from climate model simulation output. This method was developed by Dr. Carl Mears at Remote Sensing Systems (RSS) in Santa Rosa, California. The method relies on local weighting functions, whose values are dependent on the surface pressure and surface type at each model grid-point. The method is fully described in:

Mears, C.A., B.D. Santer, C.S. Doutriaux, and F.J. Wentz, 2011: Calculating synthetic microwave sounder brightness temperatures from discrete-level data. Journal of Atmospheric and Oceanic Technology (in review).

This new method has been applied to simulation output from phase 3 of the Coupled Model Intercomparison Project (CMIP-3). The synthetic MSU lower tropospheric temperatures calculated from CMIP-3 output are analyzed in:

Santer, B.D., C. Mears, C. Doutriaux, P. Caldwell, P.J. Gleckler, T.M.L. Wigley, S. Solomon, N.P. Gillett, D. Ivanova, T.R. Karl, J.R. Lanzante, G.A. Meehl, P.A. Stott, K.E. Taylor, P.W. Thorne, M.F. Wehner, and F.J. Wentz, 2011: Separating signal and noise in atmospheric temperature changes: The importance of timescale. Journal of Geophysical Research (Atmospheres), 116 (D22) doi:10.1029/2011JD016263

To download the synthetic MSU temperature data used in Santer et al. (2011), and to see more information regarding the calculation of these temperatures, go to New Synthetic MSU Data 2011


Raw Synthetic MSU Data

Synthetic MSU temperatures from 49 simulations of 20th century climate change were calculated as described in:

Santer, B.D., et al., 2008: Consistency of modeled and observed temperature trends in the tropical troposphere. International Journal of Climatology, 28, 1703-1722, doi:10.1002/joc.1756.

To download the data used in the above article and read about the details on the derivation see Synthetic MSU Data