Stephen Leroy's Publications

Smith, J. B., D. M. Wilmouth, K. M. Bedka, K. P. Bowman, C. R. Homeyer, J. A. Dykema, M. R. Sargent, C. Clapp, S. S. Leroy, D. S. Sayres, J. M. Dean-Day, T. P. Bui, and J. G. Anderson (2017), A case-study of convectively sourced water vapor observed in the overworld stratosphere over the United States, J. Geophys. Res. Atmos. 122, doi:10.1002/2017JD026831.

On 27 August 2013, during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys field mission, NASA's ER‐2 research aircraft encountered a region of enhanced water vapor, extending over a depth of approximately 2 km and a minimum areal extent of 20,000 km2 in the stratosphere (375 K to 415 K potential temperature), south of...

Huang, Y., S. Leroy, P.J. Gero, J. Dykema, and J.G. Anderson (2010), Separation of Longwave Climate Feedbacks from Spectral Observations, J. Geophys. Res., 115, D07104, doi:10.1029/2009JD012766, 2010.

We conduct a theoretical investigation into whether changes in the outgoing longwave radiation (OLR) spectrum can be used to constrain longwave greenhouse-gas forcing and climate feedbacks, with a focus on isolating and quantifying their contributions to the total OLR change in all-sky conditions. First, we numerically compute the spectral signals of CO2 forcing and feedbacks of temperature,...

Leroy, S.S., and J.G. Anderson, Optical Detection of Regional Trends Using Global Data, J. Climate, 23, Issue 16 (August 2010), pp. 4438-4446, doi: http://dx.doi.org/10.1175/2010JCLI3550.1.

A complete accounting of model uncertainty in the optimal detection of climate signals requires normalization of the signals produced by climate models; however, there is not yet a well-defined rule for the normalization. This study seeks to discover such a rule. The authors find that, to arrive at the equations of optimal detection from a general application of Bayesian statistics to the problem...

Huang, Yi, Stephen S. Leroy, James G. Anderson , 2010: Determining Longwave Forcing and Feedback Using Infrared Spectra and GNSS Radio Occulation, J. Climate, 23, 6027–6035. doi: http://dx.doi.org/10.1175/2010JCLI3588.1 

The authors investigate whether combining a data type derived from radio occultation (RO) with the infrared spectral data in an optimal detection method improves the quantification of longwave radiative forcing and feedback. Signals derived from a doubled-CO2 experiment in a theoretical study are used. When the uncertainties in both data types are conservatively estimated, jointly detecting the...

Leroy, S.S., Y. Huang, and J.G. Anderson, Radio Occulation Data: Its Utility in NWP and Climate Fingerprinting, Proceedings of ECMWF Seminar on Diagnosis of Forecasting and Data  Assimilation Systems, 7-10, September 2009.

Radio occultation data: Its utility in NWP and climate fingerprinting. Presentation at ECMWY 2009 Annual Seminar — Seminar on Diagnosis of Forecasting and Data Assimilation Systems, 7 - 10 September 2009.(http://www.ecmwf.int/newsevents/meetings/annual_seminar/2009/presentations.html)

Leroy, Stephen, James Anderson, John Dykema, Richard Goody, 2008: Testing Climate Models Using Thermal Infrared Spectra. J. Climate, 21, 1863–1875. doi: http://dx.doi.org/10.1175/2007JCLI2061.1 

An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to...

Leroy, S.S., J.A. Dykema, and J.G. Anderson, “Scalar prediction in climate using data and model,” Submitted to J. Climate (2008).

Scalar detection in climate change research, having taken the form of optimal detection/linear multi-pattern regression, has been used in the recent past to detect multiple climate signals in the presence of natural inter- annual variability and associate those signals with specific causes. It has been applied to many climate observables to show high probabilities of human influence on climatic...

Leroy, S., J. G. Anderson, J. Dykema, and R. Goody (2008), Testing climate models with thermal infrared spectra, J. Clim., 21, 1863–1875.

An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to...

Leroy, S. S., J. G. Anderson, and G. Ohring (2008), Climate signal detection times and constraints on climate benchmark accuracy requirements,J. Clim., 21, 841 – 846, doi:10.1175/2007JCLI1946.1.

Long term trends in the climate system are always partly obscured by naturally occurring interannual variability.All else being equal, the larger the natural variability is, the less precisely one can estimate a trend in a timeseriesof data. Measurement uncertainty, though, also obscures long term trends. We derive how measurement uncertaintyand natural interannual variability interact in...

Leroy, S. S., and J. G. Anderson (2007), Estimating Eliassen-Palm flux using COSMIC radio occultationGeophys. Res. Lett.,34, L10810, doi:10.1029/2006GL028263.

We present a methodology for analyzing the Eliassen-Palm (E-P) flux in the troposphere and stratosphere using GPS radio occultation data from the COSMIC project. In this methodology, geopotential height and temperature are mapped on constant pressure surfaces using a Bayesian interpolation scheme with a spherical harmonic basis, and the components of the E-P flux are evaluated using geostrophic...

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