• Glove and mitten protection in extreme cold weather: an Antarctic study

      Iserson, Kenneth V.; Univ Arizona, Dept Emergency Med (CO-ACTION PUBLISHING, 2017-01-23)
      Background: Myths, misconceptions and a general lack of information surround the use of gloves and mittens in extreme cold environments. Objective. This study assessed how well an assortment of gloves and mittens performed in a very cold environment. Methods. A convenience sample of gloves and mittens were tested in Antarctica during the winter of 2016 using a calibrated thermometer (range: -148 degrees F to +158 degrees F/-1008C to +70 degrees C) three times over a 0.5-mile distance (similar to 20 minutes). A small sensor on a 10-foot-long cable was taped to the radial surface of the distal small finger on the non-dominant hand. The tested clothing was donned over the probe, the maximum temperature inside the glove/mitten was established near a building exit (ambient temperature approximately 54 degrees F/12 degrees C), and the building was exited, initiating the test. The hand was kept immobile during the test. Some non-heated gloves were tested with chemical heat warmers placed over the volar or dorsal wrist. Results. The highest starting (96 degrees F/36 degrees C) and ending (82 degrees F/28 degrees C) temperatures were with electrically heated gloves. The lowest starting temperature was with electrically heated gloves with the power off (63 degrees F/17 degrees C). Non-heated gloves with an inserted chemical hand warmer had the lowest minimum temperature (33 degrees F/1 degrees C). Maximum temperatures for gloves/mittens did not correlate well with their minimum temperature. Conclusions. Coverings that maintained finger temperatures within a comfortable and safe range (at or above 59 degrees F/15 degrees C) included the heated gloves and mittens (including some with the power off) and mittens with liners. Mittens without liners (shell) generally performed better than unheated gloves. Better results generally paralleled the item's cost. Inserting chemical heat warmers at the wrist increased heat loss, possibly through the exposed area around the warmer.
    • To what extent is your data assimilation scheme designed to find the posterior mean, the posterior mode or something else?

      Hodyss, Daniel; Bishop, Craig H.; Morzfeld, Matthias; Univ Arizona, Dept Math (CO-ACTION PUBLISHING, 2016-09-30)
      Recently there has been a surge in interest in coupling ensemble-based data assimilation methods with variational methods (commonly referred to as 4DVar). Here we discuss a number of important differences between ensemble-based and variational methods that ought to be considered when attempting to fuse these methods. We note that the Best Linear Unbiased Estimate (BLUE) of the posterior mean over a data assimilation window can only be delivered by data assimilation schemes that utilise the 4-dimensional (4D) forecast covariance of a prior distribution of non-linear forecasts across the data assimilation window. An ensemble Kalman smoother (EnKS) may be viewed as a BLUE approximating data assimilation scheme. In contrast, we use the dual form of 4DVar to show that the most likely non-linear trajectory corresponding to the posterior mode across a data assimilation window can only be delivered by data assimilation schemes that create counterparts of the 4D prior forecast covariance using a tangent linear model. Since 4DVar schemes have the required structural framework to identify posterior modes, in contrast to the EnKS, they may be viewed as mode approximating data assimilation schemes. Hence, when aspects of the EnKS and 4DVar data assimilation schemes are blended together in a hybrid, one would like to be able to understand how such changes would affect the mode-or mean-finding abilities of the data assimilation schemes. This article helps build such understanding using a series of simple examples. We argue that this understanding has important implications to both the interpretation of the hybrid state estimates and to their design.