2.25.2013

Projections of labor capacity loss under climate change


Reductions in labour capacity from heat stress under climate warming
John P. Dunne,  Ronald J. Stouffer , Jasmin G. John
Abstract: A fundamental aspect of greenhouse-gas-induced warming is a global-scale increase in absolute humidity. Under continued warming, this response has been shown to pose increasingly severe limitations on human activity in tropical and mid-latitudes during peak months of heat stress. One heat-stress metric with broad occupational health applications is wet-bulb globe temperature. We combine wet-bulb globe temperatures from global climate historical reanalysis and Earth System Model (ESM2M) projections with industrial and military guidelines for an acclimated individual’s occupational capacity to safely perform sustained labour under environmental heat stress (labour capacity)—here defined as a global population-weighted metric temporally fixed at the 2010 distribution. We estimate that environmental heat stress has reduced labour capacity to 90% in peak months over the past few decades. ESM2M projects labour capacity reduction to 80% in peak months by 2050. Under the highest scenario considered (Representative Concentration Pathway 8.5), ESM2M projects labour capacity reduction to less than 40% by 2200 in peak months, with most tropical and mid-latitudes experiencing extreme climatological heat stress. Uncertainties and caveats associated with these projections include climate sensitivity, climate warming patterns, CO2 emissions, future population distributions, and technological and societal change.
Not a major surprise to regular readers of FE, but still important. For more serious stuff on this topic, see here, here and here. For more entertaining experiments, see here and here. If you're still reading and want more, click here.

2.20.2013

"Climate Extremes: Recent Trends with Implications for National Security"


Last year, I participated in a few workshops where we thought through some of the "worst case scenarios" as well as potential mechanisms through which climatic changes could influence US national security interests in the next decade or so. The report (which I did not write) is now out (here, article here). The authors are trained geoscientists, so the text is focused on the physics side of the problem.
CLIMATE EXTREMES AND NATIONAL SECURITY – THE BOTTOM LINE
Climate change has entered the mainstream as a potential threat to U.S. national security. The 2010 Quadrennial Defense Review, and the 2010 National Security Strategy all identify climate change as likely to trigger outcomes that will threaten U.S. security. These assessments have had to rely on projections of climate change tuned to identify impacts over roughly a one-century time frame. This time frame is driven by the nature of the questions that dominated the initial literature (e.g., what impacts can  be expected from a doubling of pre-industrial carbon dioxide) and the fact that global climate models are generally able to resolve expected impacts only over large scales and the long term.Having arrived at a condition where climate change has been identified as a likely threat to U.S. national security interests, but with little ability to clarify the nature of expected climate impacts over a timeframe that is relevant to security decision-makers, the authors decided to focus on the near-term impacts from climate change (over the next decade). In short, the analysis finds that, absent unknown or unpredictable forces, the increase in extreme events observed in the past decade is likely to continue in the near term as accelerated warming and natural variability combine to produce changing weather conditions around the world. This will impact Water Security, Energy Security, Food Security, and Critical Infrastructure, and brings into focus the need to consider the accelerating nature of climate stress, in concert with the more traditional political, economic, and social indicators.
Some people may think the headlines from the report sound alarmist (I'm just guessing), but I think the text is quite pragmatic:
What was once a 1 in 100 year anomaly is likely to become a 1 in 10 or 1 in 30 year anomaly or even more frequent in the near future. Our infrastructure and agriculture is not designed to accommodate  the increasing frequency and prevalence of such extremes. Human security and the interests of most nations are at stake as a result of such increasing  climate stress. The national security context will change. The potential for profound impacts upon water, food and energy security, critical infrastructure, and ecosystem resources will  influence the individual and collective responses of nations coping with climate changes. U.S. national security interests have always been influenced by extreme weather patterns. Now the risks will become larger and more apparent. The study renders the judgment that the increasingly disruptive influences of climate extremes necessitate their careful consideration in threat analysis, mitigation, and response. It is in the best interest of the U.S. to be vigilant about extreme weather patterns, the behavior of nations in their attempts to mitigate or adapt to the effects of changing extremes, and impacts on social, economic, and political well-being.
h/t Center for Climate and Security

2.18.2013

Plotting restricted cubic splines in Stata [with controls]

Michael Roberts has been trying to convince me to us restricted cubic splines to plot highly nonlinear functions, in part because they are extremely flexible and they have nice properties near their edges.  Unlike polynomials, information at one end of the support only weakly influences fitted values at the other end of the support. Unlike the binned non-parametric methods I posted a few weeks ago, RC-splines are differentiable (smooth). Unlike other smooth non-parametric methods, RC-splines are fast to compute and easily account for control variables (like fixed effects) because they are summarized by just a few variables in an OLS regression. They can also be used with spatially robust standard errors or clustering, so they are great for nonlinear modeling of spatially correlated processes. 

In short: they have lots of advantages. The only disadvantage is that it takes a bit of effort to plot them since there's no standard Stata command to do it.

Here's my function plot_rcspline.ado, which generates the spline variables for the independent variable, fits a spline while accounting for control variables, and plots the partial effect of the specified independent variables (adjusting for the control vars) with confidence intervals (computed via delta method). It's as easy as

plot_rcspline y x

and you get something like


where the "knots" are plotted as the vertical lines (optional).

Help file below the fold.  Enjoy!

Related non-linear plotting functions previously posted on FE:
  1. Boxplot regression
  2. Visually-weighted regression
  3. Watercolor regression
  4. Non-parametric three-dimensional regression
  5. Binned non-parametric regression
  6. Polynomial regression of any degree

2.15.2013

Human socio-economics predict elephant population better than elephant habitat


Understanding spatial differences in African elephant densities and occurrence, a continent-wide analysis
Willem F. de Boer, Frank van Langevelde, Herbert H.T. Prins, Peter C. de Ruiter, Julian Blanc, Marc J.P. Vis, Kevin J. Gaston, Iain Douglas Hamilton
The densities and survival of many wild animals are presently at risk. Crucial for improving conservation actions is an understanding on a large scale of the relative importance of human and ecological factors in determining the distribution and densities of species. However, even for such charismatic species as the African elephant (Loxodonta africana), spatially explicit, large-scale analyses are lacking, although various local-scale studies are available. Here we show through continent-scale analysis that ecological factors, such as food availability, are correlated with the presence of elephants, but human factors are better pre- dictors of elephant population densities where elephants are present. These densities strongly correlate with conservation policy, literacy rate, corruption and economic welfare, and associate less with the availability of food or water for these animals. Our results suggest that conservation strategies should be organized in a socioeconomic context. The successful conservation of large animal species could depend more on good human education, greater literacy, good governance, and less corruption, than merely setting aside areas for conservation.
h/t Nitin


2.14.2013

Temporal and spatial dynamics of subnational climate shocks and human conflict

There are many groups trying to use gridded subnational data to understand how climatic shocks generate social conflict and to verify larger-scale analyses.  However up to now, it hasn't felt like anyone had done a particularly strong analysis where the local-level data provided new insight beyond validating earlier large-scale studies at a smaller scale.  This new working paper is the best high-resolution analysis that I've seen so far.

2.13.2013

Building Back Worse

It's sometimes hypothesized that after a natural disaster, populations "Build Back Better," meaning that the reconstruction of damaged infrastructure leaves the population better off after the disaster than they were before it struck.  There is some economic logic to this hypothesis, since we know that populations don't always update expensive capital investments when they should.  If capital is outdated, then an exogenous shock that motivates the population to replace the old capital with new capital might end up increasing the economy's output in the long-run.  Many of us are familiar with the example of a cell phone that is old and frustrating, but we don't feel like its worth replacing until we drop it in the pool by mistake -- and then find that upgrading to the latest smartphone makes us much more productive.

Politicians in the US, it seems, are required to tell the local population that they will "build back better" after a disaster strikes.  After Hurricane Sandy, we heard a lot of leaders talking about how the tri-state area will be stronger and better than it ever was, probably in part because nobody wants to hear otherwise and in part because this kind of logic is important for obtaining reconstruction funding.  Healy and Malhotra have a nice article (here) demonstrating that obtaining this kind of funding for reconstruction is important for an incumbent's re-election (recall: Hurricane Sandy -> Federal relief funding -> NJ Governor Christie's endorsement -> Obama earns votes in reelection).  And just before the Superbowl, I saw this video about the Superdome's post-Katrina reconstruction, which is not shy about endorsing the BBB hypothesis.

Importantly, though, the BBB hypothesis still remains a hypothesis, and there is no robust empirical evidence that populations actually do build back better, in aggregate, after catastrophic events. To remind that we shouldn't take the anecdotes and political rhetoric above too seriously, Amir Jina points us to an interesting IRIN report that suggests populations affected by Typhoon Bopha are building back worse:

2.06.2013

Temperature and Jewish persecution

"Recommendations" on Google scholar is getting very good. Here's a new working paper out that it flagged for me, and it hit remarkably close to home  -- it's the most recent working paper since this one that I emailed to my parents. (We've posted on climate shocks on and human conflict many previous times.)

2.04.2013

Simulations of direct interference in the large-scale water and energy balances of the atmosphere by humans


A recent NCC and a recent GRL article both use simulations to look at how large scale irrigation and energy consumption might alter large scale circulation patterns of the atmosphere.

If I were a grad student with some statistical skills, I would go out into the world and try to detect these effects with data.

Energy consumption and the unexplained winter warming over northern Asia and North America
Guang J. Zhang, Ming Cai & Aixue Hu
Abstract: The worldwide energy consumption in 2006 was close to 498 exajoules. This is equivalent to an energy convergence of 15.8 TW into the populated regions, where energy is consumed and dissipated into the atmosphere as heat. Although energy consumption is sparsely distributed over the vast Earth surface and is only about 0.3% of the total energy transport to the extratropics by atmospheric and oceanic circulations, this anthropogenic heating could disrupt the normal atmospheric circulation pattern and produce a far-reaching effect on surface air temperature. We identify the plausible climate impacts of energy consumption using a global climate model. The results show that the inclusion of energy use at 86 model grid points where it exceeds 0.4 W m−2 can lead to remote surface temperature changes by as much as 1 K in mid- and high latitudes in winter and autumn over North America and Eurasia. These regions correspond well to areas with large differences in surface temperature trends between observations and global warming simulations forced by all natural and anthropogenic forcings1. We conclude that energy consumption is probably a missing forcing for the additional winter warming trends in observations.

Irrigation in California's Central Valley strengthens the southwestern U.S. water cycle
Min-Hui Lo, James S. Famiglietti
Abstract: Characterizing climatological and hydrological responses to agricultural irrigation continues to be an important challenge to understanding the full impact of water management on the Earth's environment and hydrological cycle. In this study, we use a global climate model, combined with realistic estimates of regional agricultural water use, to simulate the local and remote impacts of irrigation in California's Central Valley. We demonstrate a clear mechanism that the resulting increase in evapotranspiration and water vapor export significantly impacts the atmospheric circulation in the southwestern United States, including strengthening the regional hydrological cycle. We also identify that irrigation in the Central Valley initiates a previously unknown, anthropogenic loop in the regional hydrological cycle, in which summer precipitation is increased by 15%, causing a corresponding increase in Colorado River streamflow of ~30%. Ultimately, some of this additional streamflow is returned to California via managed diversions through the Colorado River aqueduct and the All-American Canal.