A 2000-yr reconstruction of air temperature in the Great Basin of the United States with specific reference to the Medieval Climatic Anomaly

2014 ◽  
Vol 82 (2) ◽  
pp. 309-317 ◽  
Author(s):  
Scott A. Reinemann ◽  
David F. Porinchu ◽  
Glen M. MacDonald ◽  
Bryan G. Mark ◽  
James Q. DeGrand
Keyword(s):  
United States ◽  
Great Basin ◽  
Air Temperature ◽  
Temperature Reconstruction ◽  
The United States ◽  
Organic Content ◽  
Ice Age ◽  
Specific Reference ◽  
Medieval Climatic Anomaly ◽  
Snake Range

AbstractA sediment core representing the past two millennia was recovered from Stella Lake in the Snake Range of the central Great Basin in Nevada. The core was analyzed for sub-fossil chironomids and sediment organic content. A quantitative reconstruction of mean July air temperature (MJAT) was developed using a regional training set and a chironomid-based WA-PLS inference model (r2jack = 0.55, RMSEP = 0.9°C). The chironomid-based MJAT reconstruction suggests that the interval between AD 900 and AD 1300, corresponding to the Medieval Climate Anomaly (MCA), was characterized by MJAT elevated 1.0°C above the subsequent Little Ice Age (LIA), but likely not as warm as recent conditions. Comparison of the Stella Lake temperature reconstruction to previously published paleoclimate records from this region indicates that the temperature fluctuations inferred to have occurred at Stella Lake between AD 900 and AD 1300 correspond to regional records documenting hydroclimate variability during the MCA interval. The Stella Lake record provides evidence that elevated summer temperature contributed to the increased aridity that characterized the western United States during the MCA.

scholarly journals Effects of trees, gardens, and nature trails on heat index and child health: design and methods of the Green Schoolyards Project

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kevin Lanza ◽  
Melody Alcazar ◽  
Deanna M. Hoelscher ◽  
Harold W. Kohl
Keyword(s):  
Physical Activity ◽  
United States ◽  
Relative Humidity ◽  
Air Temperature ◽  
The United States ◽  
Heat Index ◽  
Activity Levels ◽  
Natural Setting ◽  
Physical Activity Levels ◽  
Nature Trails

Abstract Background Latinx children in the United States are at high risk for nature-deficit disorder, heat-related illness, and physical inactivity. We developed the Green Schoolyards Project to investigate how green features—trees, gardens, and nature trails—in school parks impact heat index (i.e., air temperature and relative humidity) within parks, and physical activity levels and socioemotional well-being of these children. Herein, we present novel methods for a) observing children’s interaction with green features and b) measuring heat index and children’s behaviors in a natural setting, and a selection of baseline results. Methods During two September weeks (high temperature) and one November week (moderate temperature) in 2019, we examined three joint-use elementary school parks in Central Texas, United States, serving predominantly low-income Latinx families. To develop thermal profiles for each park, we installed 10 air temperature/relative humidity sensors per park, selecting sites based on land cover, land use, and even spatial coverage. We measured green features within a geographic information system. In a cross-sectional study, we used an adapted version of System for Observing Play and Recreation in Communities (SOPARC) to assess children’s physical activity levels and interactions with green features. In a cohort study, we equipped 30 3rd and 30 4th grade students per school during recess with accelerometers and Global Positioning System devices, and surveyed these students regarding their connection to nature. Baseline analyses included inverse distance weighting for thermal profiles and summing observed counts of children interacting with trees. Results In September 2019, average daily heat index ranged 2.0 °F among park sites, and maximum daily heat index ranged from 103.4 °F (air temperature = 33.8 °C; relative humidity = 55.2%) under tree canopy to 114.1 °F (air temperature = 37.9 °C; relative humidity = 45.2%) on an unshaded playground. 10.8% more girls and 25.4% more boys interacted with trees in September than in November. Conclusions We found extreme heat conditions at select sites within parks, and children positioning themselves under trees during periods of high heat index. These methods can be used by public health researchers and practitioners to inform the redesign of greenspaces in the face of climate change and health inequities.

scholarly journals OVERALL AND SEX-SPECIFIC REFERENCE RANGES FOR HIGH-SENSITIVITY TROPONIN T GEN 5 STAT IN THE UNITED STATES

2018 ◽  
Vol 71 (11) ◽  
pp. A233 ◽  
Author(s):  
Robert Fitzgerald ◽  
Christopher deFilippi ◽  
Judd Hollander ◽  
W. Frank Peacock ◽  
Alexander T. Limkakeng ◽  
...  
Keyword(s):  
United States ◽  
Troponin T ◽  
High Sensitivity ◽  
The United States ◽  
Specific Reference ◽  
Reference Ranges ◽  
High Sensitivity Troponin ◽  
High Sensitivity Troponin T

scholarly journals Relationship between hourly extreme precipitation and local air temperature in the United States

2012 ◽  
Vol 39 (16) ◽  
pp. n/a-n/a ◽  
Author(s):  
Vimal Mishra ◽  
John M. Wallace ◽  
Dennis P. Lettenmaier
Keyword(s):  
United States ◽  
Air Temperature ◽  
Extreme Precipitation ◽  
The United States

An Evaluation of NDFD Weather Forecasts for Wildland Fire Behavior Prediction

2018 ◽  
Vol 33 (1) ◽  
pp. 301-315 ◽  
Author(s):  
Wesley G. Page ◽  
Natalie S. Wagenbrenner ◽  
Bret W. Butler ◽  
Jason M. Forthofer ◽  
Chris Gibson
Keyword(s):  
United States ◽  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Wildland Fire ◽  
Fire Behavior ◽  
The United States ◽  
Mean Bias Error ◽  
Bias Error ◽  
Behavior Prediction

Abstract Wildland fire managers in the United States currently utilize the gridded forecasts from the National Digital Forecast Database (NDFD) to make fire behavior predictions across complex landscapes during large wildfires. However, little is known about the NDFDs performance in remote locations with complex topography for weather variables important for fire behavior prediction, including air temperature, relative humidity, and wind speed. In this study NDFD forecasts for calendar year 2015 were evaluated in fire-prone locations across the conterminous United States during periods with the potential for active fire spread using the model performance statistics of root-mean-square error (RMSE), mean fractional bias (MFB), and mean bias error (MBE). Results indicated that NDFD forecasts of air temperature and relative humidity performed well with RMSEs of about 2°C and 10%–11%, respectively. However, wind speed was increasingly underpredicted when observed wind speeds exceeded about 4 m s−1, with MFB and MBE values of approximately −15% and −0.5 m s−1, respectively. The importance of accurate wind speed forecasts in terms of fire behavior prediction was confirmed, and the forecast accuracies needed to achieve “good” surface head fire rate-of-spread predictions were estimated as ±20%–30% of the observed wind speed. Weather station location, the specific forecast office, and terrain complexity had the largest impacts on wind speed forecast error, although the relatively low variance explained by the model (~37%) suggests that other variables are likely to be important. Based on these results it is suggested that wildland fire managers should use caution when utilizing the NDFD wind speed forecasts if high wind speed events are anticipated.

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