Discounting Under Severe Weather Threat

The human and economic costs of severe weather damage can be mitigated by appropriate preparation. Despite the benefits, researchers have only begun to examine if known decision-making frameworks apply to severe-weather-related decisions. Using experiments, we found that a hyperbolic discounting function accurately described participant decisions to prepare for, and respond to, severe weather, although only delays of 1 month or longer significantly changed decisions to evacuate, suggesting that severe weather that is not imminent does not affect evacuation decisions. In contrast, the probability that a storm would impact the participant influenced evacuation and resource allocation decisions. To influence people’s evacuation decisions, weather forecasters and community planers should focus on disseminating probabilistic information when focusing on short-term weather threats (e.g., hurricanes); delay information appears to affect people’s evacuation decision only for longer-term threats, which may hold promise for climate-change warnings.

Incorporation and Use of Earth Remote Sensing Imagery within the NOAA/NWS Damage Assessment Toolkit

Severe weather events including tornadoes, damaging winds, hail, and their combination produce changes in land surface vegetation and urban settings that are frequently observed through remote sensing. Capabilities continue to improve through a growing constellation of governmental and commercial assets, increasing the spatial resolution of visible, near to shortwave infrared, and thermal infrared remote sensing. Here, we highlight cases where visual interpretation of imagery benefitted severe weather damage assessments made within the NOAA/NWS Damage Assessment Toolkit. Examples demonstrate utility of imagery in assessing tracks and changes in remote areas where staffing limitations or access prevent a ground-based assessment.

Weathering The Storm: Developing a Climate Change Adaptation Policy for the Washington Metropolitan Area Transit Authority

For many Americans the impacts of climate change are either hypothetical futures or far-off problems. However, climate change is already impacting millions of Americans as they commute to work each day. In the Nation’s capital the Washington Metropolitan Area Transit Authority has already suffered as heat waves and severe weather damage equipment and reduce service. The transportation authority must take a comprehensive look at its infrastructure and adapt policies to mitigate the current and future risks to transportation services.

Wool weathering damage as measured by Methylene Blue absorption is linked to suint content

Weather damage of wool in grazing sheep has long been recognised by the wool industry as a problem, resulting in fibre damage, fibre loss and poor dyeing performance. Merino wool from 3538 ewe and ram hoggets was used to estimate the heritability of Methylene Blue absorption. Methylene Blue absorption has a high heritability of 0.44 ± 0.04 and was strongly genetically correlated with suint index (0.88 ± 0.02) and wool moisture index (0.92 ± 0.03). Methylene Blue absorption was moderately genetically, negatively correlated with measures of clean wool colour and yield and positively with dust penetration. There was no significant correlation between Methylene Blue absorption and dust content or economically important measures of fleece value such as fibre diameter, curvature and staple strength. The strong genetic relationship between Methylene Blue absorption and suint index indicates that Methylene Blue absorption is a very good indirect measure of greasy wool suint content but may not be a satisfactory indicator trait to select for low weather damage.

Prediction of weather damage of mungbean seed in tropical Australia. II. Model application

To demonstrate a model to simulate the risk of weather damage of mungbean, application studies were undertaken using 27 years of climatic data collected at Katherine, Northern Territory, Australia. In terms of the risk of weather damage, the transition from high risk to low risk occurred after mid-February but before 20 March. High quality seed could be expected in 70% of seasons for a crop that matured after 20 March. For planting dates prior to 25 January, the chance of producing premium quality seed was enhanced to 40–70% of seasons by sowing a cultivar that matured 2 weeks later and by harvesting promptly (4 days after maturity). There was no benefit from later maturity or harvest promptness where sowing was made after 25 January, because maturity occurred after the wet season was complete. In contrast, yield was optimised at early January sowing dates. Calculating gross margins by combining yield and weather damage simulations identified an optimum sowing date between the optimum for yield and seed quality. It was shown that later maturity combined with photoperiod sensitivity increased the sowing window from 10 to 29 days compared with a short duration variety that was insensitive to photoperiod. The relative merits of modelling and field experimentation in assessing the cropping potential for mungbean in a new region are discussed. The need to be able to simulate the yield of the second flush of flowers was acknowledged as a future research requirement.