17 Matching Annotations
  1. Feb 2019
  2. Dec 2018
  3. Feb 2018
  4. Feb 2017
  5. Nov 2016
    1. We hypothesize that precipitation levels during the preceding wet season and during the onset of the dry season in forests of Southern Hemisphere South America act as a key regulator of drought intensity during the subsequent dry season.

      The hypothesized causal pathway through precipitation is not directly on the precip during the peak fire period, but through factors that are influenced on longer time-scales.

      This is advantageous for forecasting because it means that the strongest signals for forecasting occur several months in advance of the desired forecast. If the strongest response was more proximate it would make the advanced forecasts weaker as they would be relying on the earlier month SST values as estimates of the closer in values that could in concept produce stronger forecasts.

    2. We defined our empirical predictive model as a linear combination of the two climate indices sampled during these months of maximum correlation:FSSpredicted(x,t)=a(x)×ONI[t,m(x)−τONI(x)]+b(x)×AMO[t,m(x)−τAMO(x)]+c(x)

      If I'm reading this and the supplemental material correctly this is a two step modeling approach applied independently to each region.

      1. For each region identify the month of ONI and AMO that are most tightly correlated with FSS.
      2. Use the values of ONI and AMO for the selected months to build a two-variable multiple regression.

      If this is right it seems like the model could be improved further by incorporating lagging methods like https://doi.org/10.1111/ele.12399 and by making the model spatially explicit so that neighboring regions can borrow strength from one another. However the ability to to perform these kinds of approaches may be necessarily limited by the small size of the available training set.

    3. we used 2001–2009 fire counts detected by the Moderate Resolution Imaging Spectroradiometer (MODIS)

      The success of this model with only small amounts of training data is encouraging for other areas of ecology and environmental science where the available time-series may be short.

    4. Fire season severity, here defined as the sum of satellite-based active fire counts in a 9-month period centered at the peak fire month, depends on multiple parameters that influence fuel moisture levels and fire activity in addition to precipitation, including vapor pressure deficits, wind speeds, ignition sources, land use decisions, and the duration of the dry season. As a result, the relationship between FSS and SSTs may be more complex than the relationships between precipitation and SSTs described above.

      This recognition of additional factors that could influence fire, and the fact it more complex models using the same data may be able to indirectly use some of these influences is really valuable. It is, in effect, positing that latent variables associated with some of these causes may be associated with measurable aspects of SST.

    5. This is a nice example of chaining together separate pieces of knowledge to understand what form of forecasting model might be successful. Large scale climate phenomena -> variation in precipitation -> variation in fire season severity.

    1. To predict FSS at or before the beginning of the fire season, we established a cutoff (minimum) lead time of 3 month

      It would be interesting to know how certainty in the results continued to improve as the last few months of data became available. If the improvements where substantial it could justify consideration of shifting policy to more last minute shifts in resources.

  6. Oct 2016
    1. A rat crept softly through the vegetation

      This line stands out because it seems that it doesn't fit. The book is filled with images of fire and bones. All of a sudden there is life in the rat and the vegetation.

    2. Burning burning burning burning

      This book is called The Fire Sermon, but is only here at the end that we get fire. This book, like much of the poem, has a motif of water. In this book specifically, we have the Thames, damp ground, the sailor home from sea, fisherman, the river, barges, and more. There is little to do with heat or flames. In a piece with so little to do with fire, it makes us ask the question: why is this section called The Fire Sermon? It is followed by a reference to the Lord. Is the poem referencing Hell?

    3. Burning burning burning burning

      This is the only line that might have related to the "fire" within his sermon title. As well as the images that surfaced prior to this "book."

    4. From satin

      The beginning of this line correlates with the constant image of "flames," "smoke," "fiery," "firelight," etc. "From satin" appears to be a reference towards Lucifer himself in relation to this woman that is sitting in her chair, "like a burnished throne."

    5. Dead
  7. Dec 2015
    1. The blurring of boundaries between the body and the city raises complexities in relationto our understanding of the human subject and the changing characteristics of humanagency.

      Maybe this is to say we shouldn't be blurring the lines of the boundaries so much then? Sounds a bit like playing with fire..

  8. Mar 2015