Category Archives: Paper Discussion

Summaries, interpretation and general discussion of journal articles.

Manabe and Wetherald (1975): The Effects of 2xCO2 on the Climate of a GCM

This is one of the early seminal atmospheric modeling papers that dealt with the effects of anthropogenic CO2. Of course, we knew about the basics of how increased CO2 would affect the atmosphere ever since John Tyndall’s work in 1861, along with many others. Manabe and Wetherald were some of the first to explore this problem with an atmospheric model. This was made possible by the availability of computing power, which was paltry compared to the computers of today. Maybe even paltry when compared to a modern smartphone!

Manabe, S. and R. T. Wetherald, 1975: The Effects of Doubling the CO2 Concentration on the climate of a General Circulation Model. J. Atmos. Sci., 32, 3–15.

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Diaz and Aiyyer (2013): Energy Dispersion in African Easterly Waves

Diaz, M., and A. Aiyyer, 2013: Energy Dispersion in African Easterly Waves. J. Atmos. Sci., 70, 130–

This study sets out to understand why African easterly waves (AEW) have a westward phase speed, but an eastward group velocity. Previous studies of AEW energetics haven’t really considered this aspect of AEWs, but this study presents a convincing case that techniques used to understand midlatitude baroclinic waves can be very useful to understand AEW dynamics. Continue reading

Boer (1993): Climate Change and the Regulation of the Surface Moisture and Energy Budgets

I see this paper cited a lot in the climate literature, because it was one of the early papers that established the idea that the response of global mean hydrologic cycle is constrained by the net radiation at the surface.

Boer, G. (1993). Climate change and the regulation of the surface moisture and energy budgets. Climate Dynamics, 8, 225–239.  Continue reading

Lappen and Schumacher (2014): The Role of Tilted Heating in the MJO

Lappen, C.-L., and C. Schumacher (2014), The role of tilted heating in the evolution of the MJO, J. Geophys. Res. Atmos., 119, 29662989.

The Madden-Julian Oscillation (MJO) has many curious features that currently have evaded a fundamental understanding. One such feature is the “westward tilt with height” that is often seen in analysis such as this lagged humidity composites from Kiladis et al. (2005), Continue reading

Chikira (2014): How can Radiative Heating Influence Atmospheric Humidity?

Chikira, M., 2014: Eastward-Propagating Intraseasonal Oscillation Represented by Chikira Sugiyama Cumulus Parameterization. Part II: Understanding Moisture Variation under Weak Temperature Gradient Balance. J. Atmos. Sci., 71, 615–639.

A recent paper by Chikira (2014) has changed the way I think about moisture mode theory and the Madden Julian Oscillation (MJO). If you’re not familiar with the MJO or moisture mode theory, then this post is gonna be over your head (sorry). But if you’ve been following the decades long search to explain what the MJO is and how it works, then I encourage you to read this paper. Continue reading

Judd et al. (2008): A Geometric Understanding of Model Error

Judd, K., C. A. Reynolds, T. E. Rosmond, and L. A. Smith, 2008: The geometry of model error. J. Atmos. Sci., 65, 1749–1772.

Recently I’ve been working on “hindcasting” weather events with a climate model. A hindcast is just a forecast, but you do it after the event has happened. Many climate models have issues in how they represent the relationship between convection and environmental moisture. It is difficult to compare the variability in a climate simulation and observations, because the long-term averages tend to be slightly different in each case in such a way that affects the variability itself. So, the idea behind these hindcasts is to compare a climate model to observations in the short period after model initialization, when they are much closer to each other.

A common problem in this type of work is that the models quickly “drift” away from the initial state. This drift is sometimes referred to as “model error”. Up till now, I’ve been thinking about model error as a problem with the model that needs to be corrected. However, this new paper by Judd et al. (2008) has changed my thinking on this issue. Continue reading