Historically, most demographic data for states and substate areas were collected from the long version of the decennial census questionnaire. A “snapshot” of the characteristics of the population on the April 1 census date was available once every 10 years. The long form of the decennial census has been replaced by the American Community Survey (ACS) that has been conducted on an ongoing basis for the entire country since 2005. Instead of a snapshot in which all of the data are gathered at one time, the ACS aggregates data collected over time, making the results more difficult to interpret. However, the ACS data are updated annually.

A practical guide to the American Community Survey (3-year estimates)

Technological advances are bringing connected and autonomous vehicles (CAVs) to the ever- evolving transportation system. Anticipating the public acceptance and adoption of these technologies is important. A recent internet-based survey was conducted polling 347 Austinites to understand their opinions on smart-car technologies and strategies. Ordered-probit and other model results indicate that respondents perceive fewer crashes to be the primary benefit of autonomous vehicles (AVs), with equipment failure being their top concern. Their average willingness to pay (WTP) for adding full (Level 4) automation ($7,253) appears to be much higher than that for adding partial (Level 3) automation ($3,300) to their current vehicles. This study estimates the impact of demographics, built-environment variables, and travel characteristics on Austinites’ WTP for adding such automations and connectivity to their current and coming vehicles. It also estimates adoption rates of shared autonomous vehicles (SAVs) under different pricing scenarios ($1, $2, and $3 per mile), choice dependence on friends’ and neighbors’ adoption rates, and home-location decisions after AVs and SAVs become a common mode of transport. Higher-income, technology-savvy males, living in urban areas, and those who have experienced more crashes have a greater interest in and higher WTP for the new technologies, with less dependence on others’ adoption rates. Such behavioral models are useful to simulate long-term adoption of CAV technologies under different vehicle pricing and demographic scenarios. These results can be used to develop smarter transportation systems for more efficient and sustainable travel.

Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective

In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.

Forest responses to increasing aridity and warmth in the southwestern United States

It has been predicted, by theory and models, that heavy precipitation will increase with climate change and this is now being seen in observations. Emergence of signals such as this will enable testing of predictions, which should increase confidence in them. Environmental phenomena are often observed first, and then explained quantitatively. The complexity of processes, the range of scales involved, and the lack of first principles make it challenging to predict conditions beyond the ones observed. Here we use the intensification of heavy precipitation as a counterexample, where seemingly complex and potentially computationally intractable processes manifest themselves to first order in simple ways: heavy precipitation intensification is now emerging in the observed record across many regions of the world, confirming both theory and model predictions made decades ago. As the anthropogenic climate signal strengthens, there will be more opportunities to test climate predictions for other variables against observations and across a hierarchy of different models and theoretical concepts.

Observed heavy precipitation increase confirms theory and early model

Since it was first described about two centuries ago and due to its adverse impacts on urban ecological environment and the overall livability of cities, the urban heat island (UHI) phenomenon has been, and still is, an important research topic across various fields of study. However, UHI studies on cities in mountain regions are still lacking. This study aims to contribute to this endeavor by monitoring and examining the formation of surface UHI (SUHI) in a tropical mountain city of Southeast Asia –Baguio City, the summer capital of the Philippines– using Landsat data (1987–2015). Based on mean surface temperature difference between impervious surface (IS) and green space (GS1), SUHI intensity (SUHII) in the study area increased from 2.7 °C in 1987 to 3.4 °C in 2015. Between an urban zone (>86% impervious) and a rural zone (

Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015)

Land surface temperature (LST) is a fundamental physical property relevant to many ecological, hydrological, and atmospheric processes. There is a strong relationship between LST and near surface air temperature ( ${\mathbf {T}_{\mathbf {air}}}$ ), although the two temperatures have different physical meaning and responses to atmospheric conditions. In complex terrain, these differences are amplified; yet it is in these environments that remotely sensed LST may be most valuable in prediction and characterization of spatial–temporal patterns of ${\text{T}_{\text{air}}}$ due to typical paucity of meteorological stations in mountainous regions. This study presents an analysis on the suitability and limitations of using LST as a proxy or an input variable for predicting ${\text{T}_{\text{air}}}$ in complex mountainous topography. Explicitly, we investigated the influence of key environmental, topographic, and instrumental factors on the relation between LST and measured ${\text{T}_{\text{air}}}$ in two mountainous ecoregions of Nevada. The relation between LST and ${\text{T}_{\text{air}}}$ was found to be strongest during late summer and fall, and weakest during winter and early spring. Increasing terrain roughness was found to diminish the relation between between LST and ${\text{T}_{\text{air}}}$ . There was a strong agreement between nighttime ${\text{T}_{\text{air}}}$ lapse rates and LST lapse rates. Given the inadequacy of several gridded ${\text{T}_{\text{air}}}$ products in capturing minimum temperature cold-air pooling and inversions, using LST as an input variable in the interpolation process would enhance capture of temperature inversions in gridded data over complex terrain. Crucially, the relationship between LST and ${\text{T}_{\text{air}}}$ did not differ significantly across the two distinct mountainous ecoregions.

Land Surface Temperature and Surface Air Temperature in Complex Terrain

Studies in mountainous terrain related to ecology and hydrology often use interpolated climate products because of a lack of local observations One dataset frequently used to develop plot-to-watershed-scale climatologies is PRISM (Parameter-elevation Regression on Independent Slopes Model) temperature Benefits of this approach include geographically-weighted station observations and topographic positioning modifiers, which become important factors for predicting temperature in complex topography Because of the paucity of long-term climate records in mountain environments, validation of PRISM algorithms across diverse regions remains challenging, with end users instead relying on atmospheric relationships derived in sometimes distant geographic settings Presented here are results from testing observations of daily temperature maximum (TMAX) and minimum (TMIN) on 16 sites in the Walker Basin, California-Nevada, located on open woodland slopes ranging from 1967 to 3111 m in elevation Individual site mean absolute error varied from 11 to 37 °C with better performance observed during summertime as opposed to winter We observed a consistent cool bias in TMIN for all seasons across all sites, with cool bias in TMAX varying with season Model error for TMIN was associated with elevation, whereas model error for TMAX was associated with topographic radiative indices (solar exposure and heat loading) These results demonstrate that temperature conditions across mountain woodland slopes are more heterogeneous than interpolated models (such as PRISM) predict, that drivers of these differences are complex and localized in nature, and that scientific application of atmospheric/climate models in mountains requires additional attention to model assumptions and source data

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2016JD025920

Testing the daily PRISM air temperature model on semiarid mountain slopes

The ability to evaluate accurately the response of the environment to climate change ideally involves long-term continuous in situ measurements of climate and landscape processes. This is the goal of the Nevada Climate-Ecohydrology Assessment Network (NevCAN), a novel system of permanent monitoring stations located across elevational and latitudinal gradients within the Great Basin hydrographic region (Figure 1). NevCAN was designed, first, to quantify the daily, seasonal, and interannual variability in climate that occurs from basin valleys to mountain tops of the Great Basin in the arid southwest of the United States; second, to relate the temporal patterns of ecohydrologic response to climate occurring within each of the major ecosystems that compose the Great Basin; and, last, to monitor changes in climate that modulate water availability, sequestration of carbon, and conservation of biological diversity.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2013EO110001

A Network for Observing Great Basin Climate Change

In the Great Basin region of western North America, records of past climate and wildfire variability are needed not only for fire use, but also for understanding the mechanisms behind the century-long expansion of pinon-juniper woodlands. The Mt. Irish area (Lincoln County, south-eastern Nevada) is a remote mountain ecosystem on the hydrographic boundary between the Great Basin and the Colorado River Basin. Non-scarred ponderosa pines (Pinus ponderosa C. Lawson var. scopulorum Engelm.) and single-needle pinyons (Pinus monophylla Torr. & Frem.) were used to develop a tree-ring reconstruction of drought (mean PDSI for May–July from NV Climate Division 3) from 1396 to 2003. A hypothetical fire regime was obtained from the PDSI reconstruction and from explicitly assumed relationships between climate and wildfire occurrence. A census of fire-scarred trees was then sampled at the study area, and crossdated fire-scar records were used to generate the fire history, independently of the pre-existing pyroclimatic m...

Dendroecological testing of the pyroclimatic hypothesis in the central Great Basin, Nevada, USA

In the Great Basin of North America, big sagebrush (Artemisia tridentata Nutt.) growth rings can be used to reconstruct environmental changes with annual resolution in areas where there is otherwise little such information available. We tested the annual nature of big sagebrush wood layers using accelerator mass spectrometry (AMS) radiocarbon dating. Four cross-sections from 3 sagebrush plants were collected near Ely, Nevada, USA, and analyzed using dendrochronological methods. Ten 14C measurements were then used to trace the location of the 1963-64 "bomb spike." Although the number of rings on each section did not exceed 60, crossdating was possible within a section and between sections. Years assigned to individual wood layers by means of crossdating aligned with their expected 14C values, matching the location of the 14C peak. This result confirmed the annual nature of growth rings formed by big sagebrush, and will facilitate the development of spa- tially explicit, well-replicated proxy records of environmental change, such as wildfire regimes, in Great Basin valleys.

/pdf/radiocarbon-analysis-confirms-the-annual-nature-of-sagebrush-13msmu7b4j.pdf

Scotty Strachan

Papers

Land Surface Temperature and Surface Air Temperature in Complex Terrain

Testing the daily PRISM air temperature model on semiarid mountain slopes

A Network for Observing Great Basin Climate Change

Dendroecological testing of the pyroclimatic hypothesis in the central Great Basin, Nevada, USA

Radiocarbon Analysis Confirms the Annual Nature of Sagebrush Growth Rings