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

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 Representing Extremes in a Daily Gridded Precipitation Analysis over the United States: Impacts of Station Density, Resolution, and Gridding Methods

2014 ◽  
Vol 27 (14) ◽  
pp. 5201-5218 ◽  
Author(s):  
Melissa Gervais ◽  
L. Bruno Tremblay ◽  
John R. Gyakum ◽  
Eyad Atallah
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
The United States ◽  
Low Resolution ◽  
Spatial Homogeneity ◽  
Precipitation Analysis ◽  
Precipitation Station ◽  
Density Resolution ◽  
Analysis Point ◽  
Station Density

Abstract This study focuses on errors in extreme precipitation in gridded station products incurred during the upscaling of station measurements to a grid, referred to as representativeness errors. Gridded precipitation station analyses are valuable observational data sources with a wide variety of applications, including model validation. The representativeness errors associated with two gridding methods are presented, consistent with either a point or areal average interpretation of model output, and it is shown that they differ significantly (up to 30%). An experiment is conducted to determine the errors associated with station density, through repeated gridding of station data within the United States using subsequently fewer stations. Two distinct error responses to reduced station density are found, which are attributed to differences in the spatial homogeneity of precipitation distributions. The error responses characterize the eastern and western United States, which are respectively more and less homogeneous. As the station density decreases, the influence of stations farther from the analysis point increases, and therefore, if the distributions are inhomogeneous in space, the analysis point is influenced by stations with very different precipitation distributions. Finally, ranges of potential percent representativeness errors of the median and extreme precipitation across the United States are created for high-resolution (0.25°) and low-resolution areal averaged (0.9° lat × 1.25° lon) precipitation fields. For example, the range of the representativeness errors is estimated, for annual extreme precipitation, to be from +16% to −12% in the low-resolution data, when station density is 5 stations per 0.9° lat × 1.25° lon grid box.

scholarly journals Simulation of Daily Extreme Precipitation over the United States in the CMIP5 30-Yr Decadal Prediction Experiment

2019 ◽  
Vol 58 (4) ◽  
pp. 875-886 ◽  
Author(s):  
Steve T. Stegall ◽  
Kenneth E. Kunkel
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The United States ◽  
Natural Variability ◽  
Return Level ◽  
Historical Period ◽  
Regional Variability ◽  
Anthropogenic Forcing ◽  
Near Term

AbstractThe CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.

scholarly journals Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

2016 ◽  
Vol 17 (2) ◽  
pp. 693-711 ◽  
Author(s):  
Hamed Ashouri ◽  
Soroosh Sorooshian ◽  
Kuo-Lin Hsu ◽  
Michael G. Bosilovich ◽  
Jaechoul Lee ◽  
...  
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Gulf Coast ◽  
The United States ◽  
Value Theory ◽  
Extreme Value ◽  
Precipitation Extremes ◽  
Precipitation Product ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

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.

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

2021 ◽  
Author(s):  
Kevin Lanza ◽  
Melody Alcazar ◽  
Deanna M. Hoelscher ◽  
III 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 Refining Ornamental Heat Zone Categories with Evapotranspiration

HortScience ◽  
2004 ◽  
Vol 39 (4) ◽  
pp. 884A-884
Author(s):  
Albert Sutherland* ◽  
Mike Schnelle ◽  
Derek Arndt
Keyword(s):  
United States ◽  
Relative Humidity ◽  
Great Plains ◽  
Air Temperature ◽  
Cold Hardiness ◽  
Reference Evapotranspiration ◽  
The United States ◽  
Ornamental Plant ◽  
Heat Zone ◽  
Oklahoma Mesonet

The American Horticulture Society (AHS) Heat Zone categories have been developed to categorize ornamental plant adaptability to different air temperature climates. These zones, like the Plant Hardiness map showing plant cold hardiness zones within the United States, are primarily north to south zones. Within the Great Plains region of the United States, the AHS Heat Zone categories provide a basic level of plant adaptability to air temperature, but do not account for plant reaction to variations in wind, relative humidity or sunlight. Daily reference evapotranspiration provides a single number that responds to variations in air temperature, wind, relative humidity and sunlight. In Oklahoma, the Oklahoma Mesonet provides a uniform statewide network of weather monitor towers that can be used to accurately calculate both short and tall American Society of Civil Engineers (ASCE) reference evapotranspiration (ref ET) across the entire state. Accumulated daily ref ET values can be used to provide further refinement in categorizing ornamental plant adaptability.

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

2020 ◽  
Author(s):  
Kevin Lanza ◽  
Melody Alcazar ◽  
Deanna M. Hoelscher ◽  
III 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.

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