Regional Nested Model Simulations of Present Day and 2 × CO2 Climate over the Central Plains of the U.S.

A nested regional climate model is used to generate a scenario of climate change over the MINK region (Missouri, Iowa, Nebraska, Kansas) due to doubling of carbon dioxide concentration (2 × CO₂) for use in agricultural impact assessment studies. Five-year long present day (control) and 2 × CO₂ simulations are completed at a horizontal grid point spacing of 50 km. Monthly and seasonal precipitation and surface air temperature over the MINK region are reproduced well by the model in the control run, except for an underestimation of both variables during the spring months. The performance of the nested model in the control run is greatly improved compared to a similar experiment performed with a previous version of the nested modeling system by Giorgi et al. (1994). The nested model generally improves the simulation of spatial precipitation patterns compared to the driving general circulation model (GCM), especially during the summer. Seasonal surface warming of 4 to 6 K and seasonal precipitation increases of 6 to 24% are simulated in 2 × CO₂ conditions. The control run temperature biases are smaller than the simulated changes in all seasons, while the precipitation biases are of the same order of magnitude as the simulated changes. Although the large scale patterns of change in the driving GCM and nested RegCM model are similar, significant differences between the models, and substantial spatial variability, occur within the MINK region.     

Experimental and petrological constraints on lunar differentiation from the Apollo 15 green picritic glasses

Abstract— Phase equilibrium experiments on the most magnesian Apollo 15C green picritic glass composition indicate a multiple saturation point with olivine and orthopyroxene at 1520°C and 1.3 GPa (about 260 km depth in the moon). This composition has the highest Mg# of any lunar picritic glass and the shallowest multiple saturation point. Experiments on an Apollo 15A composition indicate a multiple saturation point with olivine and orthopyroxene at 1520°C and 2.2 GPa (about 440 km depth in the moon). The importance of the distinctive compositional trends of the Apollo 15 groups A, B, and C picritic glasses merits the reanalysis of NASA slide 15426,72 with modern electron microprobe techniques. We confirm the compositional trends reported by Delano (1979, 1986) in the major element oxides SiO₂, TiO₂, Al₂O₃, Cr₂O₃, FeO, MnO, MgO, and CaO, and we also obtained data for the trace elements P₂O₅, K₂O, Na₂O, NiO, S, Cu, Cl, Zn, and F. Petrogenetic modeling demonstrates that the Apollo 15 A‐B‐C glass trends could not have been formed by fractional crystallization or any continuous assimilation/fractional crystallization (AFC) process. The B and C glass compositional trends could not have been formed by batch or incremental melting of an olivine + orthopyroxene source or any other homogeneous source, though the A glasses may have been formed by congruent melting over a small pressure range at depth. The B compositional trend is well modeled by starting with an intermediate A composition and assimilating a shallower, melted cumulate, and the C compositional trend is well modeled by a second assimilation event. The assimilation process envisioned is one in which heat and mass transfer were separated in space and time. In an initial intrusive event, a picritic magma crystallized and provided heat to melt magma ocean cumulates. In a later replenishment event, the picritic magma incrementally mixed with the melted cumulate (creating the compositional trends in the green glass data set), ascended to the lunar surface, and erupted as a fire fountain. A barometer created from multiple saturation points provides a depth estimate of other glasses in the A‐B‐C trend and of the depths of assimilation. This barometer demonstrates that the Apollo 15 A‐B‐C trend originated over a depth range of ?460 km to ?260 km within the moon.     

Staying cool in a changing climate: Reaching vulnerable populations during heat events

The frequency and intensity of hot weather events are expected to increase globally, threatening human health, especially among the elderly, poor, and chronically ill. Current literature indicates that emergency preparedness plans, heat health warning systems, and related interventions may not be reaching or supporting behavior change among those most vulnerable in heat events. Using a qualitative multiple case study design, we comprehensively examined practices of these populations to stay cool during hot weather (“cooling behaviors”) in four U.S. cities with documented racial/ethnic and socio-economic disparities and diverse heat preparedness strategies: Phoenix, Arizona; Detroit, Michigan; New York City, New York; and Philadelphia, Pennsylvania. Based on semi-structured in-depth interviews we conducted with 173 community members and organizational leaders during 2009–2010, we assessed why vulnerable populations do or do not participate in health-promoting behaviors at home or in their community during heat events, inquiring about perceptions of heat-related threats and vulnerability and the role of social support. While vulnerable populations often recognize heat's potential health threats, many overlook or disassociate from risk factors or rely on experiences living in or visiting warmer climates as a protective factor. Many adopt basic cooling behaviors, but unknowingly harmful behaviors such as improper use of fans and heating and cooling systems are also adopted. Decision-making related to commonly promoted behaviors such as air conditioner use and cooling center attendance is complex, and these resources are often inaccessible financially, physically, or culturally. Interviewees expressed how interpersonal, intergenerational relationships are generally but not always protective, where peer relationships are a valuable mechanism for facilitating cooling behaviors among the elderly during heat events. To prevent disparities in heat morbidity and mortality in an increasingly changing climate, we note the implications of local context, and we broadly inform heat preparedness plans, interventions, and messages by sharing the perspectives and words of community members representing vulnerable populations and leaders who work most closely with them.     

Mapping beach morphodynamics remotely: A novel application tested on South African sandy shores

Sandy beaches have been identified as threatened ecosystems but despite the need to conserve them, they have been generally overlooked. Systematic conservation planning (SCP) has emerged as an efficient method of selecting areas for conservation priority. However, SCP analyses require digital shapefiles of habitat and species diversity. Mapping these attributes for beaches from field data can take years and requires exhaustive resources. This study thus sought to derive a methodology to classify and map beach morphodynamic types from satellite imagery. Since beach morphodynamics is a strong predictor of macrofauna diversity, they could be considered a good surrogate for mapping beach biodiversity. A dataset was generated for 45 microtidal beaches (of known morphodynamic type) by measuring or coding for several physical characteristics from imagery acquired from Google Earth. Conditional inference trees revealed beach width to be the only factor that significantly predicted beach morphodynamic type, giving four categories: dissipative, dissipative-intermediate, intermediate and reflective. The derived model was tested by using it to predict the morphodynamic type of 28 other beaches of known classification. Model performance was good (75% prediction accuracy) but misclassifications occurred at the three breaks between the four categories. For beaches around these breaks, consideration of surf zone characteristics in addition to beach width ameliorated the misclassifications. The final methodology yielded a 93% prediction accuracy of beach morphodynamic type. Overlaying other considerations on this classification scheme could provide additional value to the layer, such that it also describes species’ spatial patterns. These could include: biogeographic regions, estuarine versus sandy beaches and short versus long beaches. The classification scheme was applied to the South African shoreline as a case study. The distribution of the beach morphodynamic types was partly influenced by geography. Most of the long, dissipative beaches are found along the west coast of the country, the south coast beaches are mostly dissipative-intermediate, and the east coast beaches range from short, estuarine pocket and embayed beaches in the former Transkei (south east), to longer intermediate and reflective beaches in KwaZulu-Natal (in the north east). Once combined with the three biogeographic regions, and distinguishing between estuarine and sandy shores, the South African coast comprised 24 different beach types. Representing shorelines in this form opens up potential for numerous spatial analyses that can not only further our understanding of sandy beach ecology at large spatial scales but also aid in deriving conservation strategies for this threatened ecosystem.     

Response of Soybean and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States

This study examines how uncertainty associated with the spatial scale of climate change scenarios influences estimates of soybean and sorghum yield response in the southeastern United States. We investigated response using coarse (300-km, CSIRO) and fine (50-km, RCM) scale climate change scenarios and considering climate changes alone, climate changes with CO₂ fertilization, and climate changes with CO₂ fertilization and adaptation. Relative to yields simulatedunder a current, control climate scenario, domain-wide soybean yield decreased by 49% with the coarse-scale climate change scenario alone, and by26% with consideration for CO₂ fertilization. By contrast, thefine-scale climate change scenario generally exhibited higher temperatures and lower precipitation in the summer months resulting in greater yield decreases (69% for climate change alone and 54% with CO₂fertilization). Changing planting date and shifting cultivars mitigated impacts, but yield still decreased by 8% and 18% respectively for the coarse andfine climate change scenarios. The results were similar for sorghum. Yield decreased by 51%, 42%, and 15% in response to fine-scaleclimate change alone, CO₂ fertilization, and adaptation cases, respectively– significantly worse than with the coarse-scale (CSIRO) scenarios. Adaptation strategies tempered the impacts of moisture and temperature stress during pod-fill and grain-fill periods and also differed with respect to the scale of the climate change scenario.     

Holocene climate of New England

Stratigraphic studies of pollen and macrofossils from six sites at different elevations in the White Mountains of New Hampshire demonstrate changes in the distributions of four coniferous tree species during the Holocene. Two species presently confined to low elevations extended farther up the mountain slopes during the early Holocene: white pine grew 350 m above its present limit beginning 9000 yr B.P., while hemlock grew 300–400 m above its present limit soon after the species immigrated to the region 7000 yr. B.P. Hemlock disappeared from the highest sites about 5000 yr B.P., but both species persisted at sites 50–350 m above their present limits until the Little Ice Age began a few centuries ago. The history of the two main high-elevation conifers is more difficult to interpret. Spruce and fir first occur near their present upper limits 9000 or 10,000 yr B.P. Fir persisted in abundance at elevations similar to those where it occurs today throughout the Holocene, while spruce became infrequent at all elevations from the beginning of the Holocene until 2000 yr B.P. These facts suggest a more complex series of changes than a mere upward shift of the modern environmental gradient. Nevertheless, we conclude that the minimum climatic change which would explain the upward extensions of hemlock and white pine is a rise in temperature, perhaps as much as 2°C. The interval of maximum warmth started 9000 yr B.P. and lasted at least until 5000 yr B.P., correlative with the Prairie Period in Minnesota.     

Analysis of post-disaster damage and disruptive impacts on the operating status of small businesses after Hurricane Katrina

When small businesses are impacted by natural hazard events, hazard and sociological researchers may have access to collect data from a sample of open businesses, in hopes of distilling lessons that might help reduce vulnerability to future disasters. Lessons from demised businesses might be more useful in reducing business closure for increasing business sustainability to disasters. Using interviews from a random sample of 371 open and 126 closed businesses’ experiences with Hurricane Katrina, discrete choice methods examine the relationship between the impact of post-disaster damage, loss of lifelines, types of delays in reopening, and cascading damages on business continuity. This unique sample offers the opportunity to determine whether damage to operating businesses was different than that of demised businesses. Respondents provided pre-Katrina data up through the last interviews in 2013. Results demonstrate that damage may have a short-term effect on operating status; it was associated with immediate demise but had much less effect on longer-term recovery. Additionally, it is evident that there is one path to failure. Businesses that did reopen, but later closed, may have been impacted by a cascade of both exogenous and endogenous shocks.     

The estimation of spectra from time‐frequency transforms for use in attenuation studies

We introduce the signal dependent time–frequency distribution, which is a time–frequency distribution that allows the user to optimize the tradeoff between joint time–frequency resolution and suppression of transform artefacts. The signal‐dependent time–frequency distribution, as well as the short‐time Fourier transform, Stockwell transform, and the Fourier transform are analysed for their ability to estimate the spectrum of a known wavelet used in a tuning wedge model. Next, the signal‐dependent time–frequency distribution, and fixed‐ and variable‐window transforms are used to estimate spectra from a zero‐offset synthetic seismogram. Attenuation is estimated from the associated spectral ratio curves, and the accuracy of the results is compared. The synthetic consisted of six pairs of strong reflections, based on real well‐log data, with a modeled intrinsic attenuation value of 1000/Q = 20. The signal‐dependent time–frequency distribution was the only time–frequency transform found to produce spectra that estimated consistent attenuation values, with an average of 1000/Q = 26±2; results from the fixed‐ and variable‐window transforms were 24±17 and 39±10, respectively. Finally, all three time–frequency transforms were used in a pre‐stack attenuation estimation method (the pre‐stack Q inversion algorithm) applied to a gather from a North Sea seismic dataset, to estimate attenuation between nine different strong reflections. In this case, the signal‐dependent time‐frequency distribution produced spectra more consistent with the constant‐Q model of attenuation assumed in the pre‐stack attenuation estimation algorithm: the average L1 residuals of the spectral ratio surfaces from the theoretical constant‐Q expectation for the signal‐dependent time‐frequency distribution, short‐time Fourier transform, and Stockwell transform were 0.12, 0.21, and 0.33, respectively. Based on the results shown, the signal‐dependent time‐frequency distribution is a time–frequency distribution that can provide more accurate and precise estimations of the amplitude spectrum of a reflection, due to a higher attainable time–frequency resolution.