The mosquito Aedes (Stegomyia) aegypti (L.), which occurs widely in the subtropics and tropics, is the primary urban vector of dengue and yellow fever viruses, and an important vector of chikungunya virus. There is substantial interest in how climate change may impact the bionomics and pathogen transmission potential of this mosquito. This Forum article focuses specifically on the effects of temperature on the bionomics of Ae. aegypti, with special emphasis on the cool geographic range margins where future rising temperatures could facilitate population growth. Key aims are to: 1) broadly define intra-annual (seasonal) patterns of occurrence and abundance of Ae. aegypti, and their relation to climate conditions; 2) synthesize the existing quantitative knowledge of how temperature impacts the bionomics of different life stages of Ae. aegypti; 3) better define the temperature ranges for which existing population dynamics models for Ae. aegypti are likely to produce robust predictions; 4) explore potential impacts of climate warming on human risk for exposure to Ae. aegypti at its cool range margins; and 5) identify knowledge or data gaps that hinder our ability to predict risk of human exposure to Ae. aegypti at the cool margins of its geographic range now and in the future. We first outline basic scenarios for intra-annual occurrence and abundance patterns for Ae. aegypti, and then show that these scenarios segregate with regard to climate conditions in selected cities where they occur. We then review how near-constant and intentionally fluctuating temperatures impact development times and survival of eggs and immatures. A subset of data, generated in controlled experimental studies, from the published literature is used to plot development rates and survival of eggs, larvae, and pupae in relation to water temperature. The general shape of the relationship between water temperature and development rate is similar for eggs, larvae, and pupae. Once the lower developmental zero temperature (10-14 degrees C) is exceeded, there is a near-linear relationship up to 30 degrees C. Above this temperature, the development rate is relatively stable or even decreases slightly before falling dramatically near the upper developmental zero temperature, which occurs at -38-42 degrees C. Based on life stage-specific linear relationships between water temperature and development rate in the 15-28 degrees C range, the lower developmental zero temperature is estimated to be 14.0 degrees C for eggs, 11.8 degrees C for larvae, and 10.3 degrees C for pupae. We further conclude that available population dynamics models for Ae. aegypti, such as CIMSiM and Skeeter Buster, likely produce robust predictions based on water temperatures in the 16-35 degrees C range, which includes the geographic areas where Ae. aegypti and its associated pathogens present the greatest threat to human health, but that they may be less reliable in cool range margins where water temperatures regularly fall below 15 degrees C. Finally, we identify knowledge or data...

As new observation systems are developed and deployed, new and presumably more precise information is becoming available for weather forecasting and climate monitoring. To take advantage of these new observations, it is desirable to have schemes to accurately retrieve the information before statistical analyses are performed so that statistical computation can be more effectively used where it is needed most. The authors propose a sequential variational approach that possesses advantages of both a standard statistical analysis [such as with a three-dimensional variational data assimilation (3DVAR) or Kalman filter] and a traditional objective analysis (such as the Barnes analysis). The sequential variational analysis is multiscale, inhomogeneous, anisotropic, and temporally consistent, as shown by an idealized test case and observational datasets in this study. The real data cases include applications in two-dimensional and three-dimensional space and time for storm outflow boundary detection (surface application) and hurricane data assimilation (three-dimensional space application). Implemented using a multigrid technique, this sequential variational approach is a very efficient data assimilation method.

The installation of the network of NEXRAD (Next Generation Weather Radar) WSR-88D (Weather Surveillance Radar-1988 Doppler) radars has been an ongoing process for more than three years. An assessment is made on how these radars and related changes at National Weather Service Offices have impacted the warning of tornadoes. Tornado warning statistics were employed to evaluate the improvements in warning lead times and detection after the installation of the WSR-88D. In an effort to remove a bias from the warning dataset, the statistics based on the first tornado event of each day were also considered. This early evaluation of the warning capability of these radars indicates an improvement at selected sites over the previous five years.

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