Browsing by Author "Snyder, Peter K."

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    A Cautionary Note on Decadal Sea Level Pressure Predictions from GCMs
    (2018-02-06) Liess, Stefan; Snyder, Peter K.; Kumar, Arjun; Kumar, Vipin
    Decadal prediction of sea level pressure (SLP) plays an important role in regional climate prediction, because it shows changes in atmospheric behavior on time scales that are relevant for policy makers. These changes consist of a combination of externally forced and internally driven climate system characteristics. A comparison of SLP trends in a subset of seven Coupled Model Intercomparison Project (CMIP) phase 5 general circulation models (GCM) during the satellite-era to their CMIP3 counterparts reveals an unrealistically strong forecast skill in CMIP3 models for trend predictions for 2001-2011 when using the 1979-2000 period to train the forecast.   Boreal-winter SLP trends over five high-, mid-, and low-latitude zones were calculated over a two-decade initialization period for each ensemble member and then ranked based on their performance relative to observations in all five zones over the same time period.  The same method is used to rank the ensemble members during the following decade. In CMIP3, 17 out of 38 ensemble members retain their rank in the 2001-2011 hindcast period and 3 retain the neighboring rank. However, these numbers are much lower in more recent CMIP5 decadal predictions over a similar period with the same number of ensembles. The conclusion to consider the forecast skill in CMIP3 predictions during the 2001-2011 as unrealistic is corroborated by comparisons to earlier periods from the 1960s to the 1980s in both CMIP3 and CMIP5 simulations. Thus, although the 2001-2011 CMIP3 predictions show statistically significant forecast skill, this skill should be treated as a spurious result that is unlikely to be reproduced by newer more accurate GCMs.
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    Is Planting Forests Bad For The Climate?
    (2011-11) Snyder, Peter K.
    Planting forests is a proven approach to mitigating global warming through sequestering atmospheric CO2. However, in the mid-latitudes this could actually have the unintended consequence of warming the planet by decreasing the surface reflectivity. Numerical modeling results are used to show where and how forests can benefit the climate.
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    MAP Inference on Million Node Graphical Models: KL-divergence based Alternating Directions Method
    (2012-02-27) Fu, Qiang; Wang, Huahua; Banerjee, Arindam; Liess, Stefan; Snyder, Peter K.
    Motivated by a problem in large scale climate data analysis, we consider the problem of maximum a posteriori (MAP) inference in graphical models with millions of nodes. While progress has been made in recent years, existing MAP inference algorithms are inherently sequential and hence do not scale well. In this paper, we present a parallel MAP inference algorithm called KL-ADM based on two ideas: tree-decomposition of a graph, and the alternating directions method (ADM). However, unlike standard ADM, we use an inexact ADM augmented with a Kullback-Leibler (KL) divergence based regularization. The unusual modification leads to an efficient iterative algorithm while avoiding double-loops. We rigorously prove global convergence of KL-ADM. We illustrate the effectiveness of KL-ADM through extensive experiments on large synthetic and real datasets. The application on real world precipitation data finds all major droughts in the last century.
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    The Unintended Climate Consequences of Carbon Sequestration in North American Forests
    (2010) Snyder, Peter K.
    Planting forests is one of few readily available and proven approaches to mitigating climate change through the sequestering of atmospheric carbon dioxide (CO2). In order to avoid a doubling in the concentration of atmospheric CO2 from preindustrial values by mid-century will require a multitude of technologies and approaches - carbon sequestration through forest planting being one of the more practical ones. However there is considerable uncertainty over whether afforestation/reforestation will actually do more harm than good. Planting a forest may decrease the surface reflectivity resulting in greater net radiation being absorbed at the surface and thus, surface warming. In some cases this warming can more than offset the climate benefit derived from carbon sequestration. Using a dynamic global vegetation model, the competing effects of fraction cover of forest, stand age, and local climate on the total benefit to the climate system is evaluated. Model results indicate that regionally there are large variations in the climate benefit of forest placement. This study offers new insight on the feasibility of large-scale forest planting as a climate mitigation strategy.