scholarly journals Seasonal Influence of Insolation on Fine-Resolved Air Temperature Variation and Snowmelt

2014 ◽  
Vol 53 (2) ◽  
pp. 323-332 ◽  
Author(s):  
Nikki Vercauteren ◽  
Steve W. Lyon ◽  
Georgia Destouni
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Eastern Coast ◽  
Seasonal Influence ◽  
Near Surface ◽  
Average Temperature ◽  
Monthly Average ◽  
Air Temperatures ◽  
Low Performance ◽  
Snow Cover Duration

AbstractThis study uses GIS-based modeling of incoming solar radiation to quantify fine-resolved spatiotemporal responses of year-round monthly average temperature within a field study area located on the eastern coast of Sweden. A network of temperature sensors measures surface and near-surface air temperatures during a year from June 2011 to June 2012. Strong relationships between solar radiation and temperature exhibited during the growing season (supporting previous work) break down in snow cover and snowmelt periods. Surface temperature measurements are here used to estimate snow cover duration, relating the timing of snowmelt to low performance of an existing linear model developed for the investigated site. This study demonstrates that linearity between insolation and temperature 1) may only be valid for solar radiation levels above a certain threshold and 2) is affected by the consumption of incoming radiation during snowmelt.

scholarly journals Fine-Resolved, Near-Coastal Spatiotemporal Variation of Temperature in Response to Insolation

2013 ◽  
Vol 52 (5) ◽  
pp. 1208-1220 ◽  
Author(s):  
Nikki Vercauteren ◽  
Georgia Destouni ◽  
Carl Johan Dahlberg ◽  
Kristoffer Hylander
Keyword(s):  
Model Development ◽  
Temperature Response ◽  
Lag Time ◽  
Spatiotemporal Variation ◽  
Eastern Coast ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Average Temperature ◽  
Monthly Average ◽  
Diurnal Temperature Variation

AbstractThis study uses GIS-based modeling of incoming solar radiation to quantify fine-resolved spatiotemporal responses of monthly average temperature, and diurnal temperature variation, at different times and locations within a field study area located on the eastern coast of Sweden. Near-surface temperatures are measured by a network of temperature sensors during the spring and summer of 2011 and then used as the basis for model development and testing. The modeling of finescale spatiotemporal variation considers topography, distance from the sea, and observed variations in atmospheric conditions, accounting for site latitude, elevation, surface orientation, daily and seasonal shifts in sun angle, and effects of shadows from surrounding topography. The authors find a lag time between insolation and subsequent temperature response that follows an exponential decay from coastal to inland locations. They further develop a linear regression model that accounts for this lag time in quantifying fine-resolved spatiotemporal temperature evolution. This model applies in the considered growing season for spatial distribution across the studied near-coastal landscape.

scholarly journals Simulations of a cold-air pool associated with elevated wintertime ozone in the Uintah Basin, Utah

2014 ◽  
Vol 14 (11) ◽  
pp. 15953-16000 ◽  
Author(s):  
E. M. Neemann ◽  
E. T. Crosman ◽  
J. D. Horel ◽  
L. Avey
Keyword(s):  
Boundary Layer ◽  
Snow Cover ◽  
Layer Structure ◽  
Inversion Layer ◽  
Cloud Microphysics ◽  
Photochemical Reactions ◽  
Near Surface ◽  
Cold Air ◽  
Air Temperatures ◽  
Uintah Basin

Abstract. Numerical simulations are used to investigate the meteorological characteristics of the 1–6 February 2013 cold-air pool in the Uintah Basin, Utah, and the resulting high ozone concentrations. Flow features affecting cold-air pools and air quality in the Uintah Basin are studied, including: penetration of clean air into the basin from across the surrounding mountains, elevated easterlies within the inversion layer, and thermally-driven slope and valley flows. The sensitivity of the boundary layer structure to cloud microphysics and snow cover variations are also examined. Ice-dominant clouds enhance cold-air pool strength compared to liquid-dominant clouds by increasing nocturnal cooling and decreasing longwave cloud forcing. Snow cover increases boundary layer stability by enhancing the surface albedo, reducing the absorbed solar insolation at the surface, and lowering near-surface air temperatures. Snow cover also increases ozone levels by enhancing solar radiation available for photochemical reactions.

scholarly journals Simulations of a cold-air pool associated with elevated wintertime ozone in the Uintah Basin, Utah

2015 ◽  
Vol 15 (1) ◽  
pp. 135-151 ◽  
Author(s):  
E. M. Neemann ◽  
E. T. Crosman ◽  
J. D. Horel ◽  
L. Avey
Keyword(s):  
Boundary Layer ◽  
Snow Cover ◽  
Layer Structure ◽  
Inversion Layer ◽  
Cloud Microphysics ◽  
Photochemical Reactions ◽  
Near Surface ◽  
Cold Air ◽  
Air Temperatures ◽  
Uintah Basin

Abstract. Numerical simulations are used to investigate the meteorological characteristics of the 31 January–6 February 2013 cold-air pool in the Uintah Basin, Utah, and the resulting high ozone concentrations. Flow features affecting cold-air pools and air quality in the Uintah Basin are studied, including the following: penetration of clean air into the basin from across the surrounding mountains, elevated easterlies within the inversion layer, and thermally driven slope and valley flows. The sensitivity of the boundary layer structure to snow cover variations and cloud microphysics are also examined. Snow cover increases boundary layer stability by enhancing the surface albedo, reducing the absorbed solar insolation at the surface, and lowering near-surface air temperatures. Snow cover also increases ozone levels by enhancing solar radiation available for photochemical reactions. Ice-dominant clouds enhance cold-air pool strength compared to liquid-dominant clouds by increasing nocturnal cooling and decreasing longwave cloud forcing.

Relationship between meteorological conditions and respiratory syncytial virus in a tropical country

2015 ◽  
Vol 143 (12) ◽  
pp. 2679-2686 ◽  
Author(s):  
C. E. RODRIGUEZ-MARTINEZ ◽  
M. P. SOSSA-BRICEÑO ◽  
R. ACUÑA-CORDERO
Keyword(s):  
Respiratory Syncytial Virus ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Latin American ◽  
Meteorological Conditions ◽  
Acute Lower Respiratory Infection ◽  
Average Temperature ◽  
Monthly Average ◽  
Syncytial Virus

SUMMARYThis study aimed to determine which meteorological conditions are associated with respiratory syncytial virus (RSV) isolates in a population of children hospitalized with acute lower respiratory infection (ALRI) in Bogota, Colombia. In an analytical cross-sectional study, links were examined between the number of monthly RSV infections and monthly average climatic variation (temperature, relative humidity, rainfall, wind speed, solar radiation) between 1 January 2010 and 30 April 2011 in a population of hospitalized children aged <3 years with ALRI caused by RSV. Out of a total of 1548 children included in the study (mean age 9·2 ± 8·5 months), 1194 (77·1%) presented RSV infection during the 3-month period from March to May. In the multivariate analysis, after controlling for wind speed, relative humidity, and solar radiation, monthly average temperature [incident rate ratio (IRR) 3·14, 95% confidence interval (CI) 1·56–6·30,P= 0·001] and rainfall (IRR 1·008, 95% CI 1·00–1·01,P= 0·048) were independently associated with the monthly number of RSV infections. In conclusion, in Bogota, a tropical Latin American city, average temperature and rainfall are the meteorological variables most strongly associated with RSV isolation in children hospitalized with ALRI in the city.

scholarly journals Snow cover duration trends observed at sites and predicted by multiple models

2020 ◽  
Author(s):  
Richard Essery ◽  
Hyungjun Kim ◽  
Libo Wang ◽  
Paul Bartlett ◽  
Aaron Boone ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Strongly Correlated ◽  
Seasonal Snow ◽  
Physically Based ◽  
Physically Based Models ◽  
The Common ◽  
Snow Cover Duration ◽  
Two Parameters ◽  
Seasonal Snow Cover

Abstract. Thirty-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.

A Decade of Ground–Air Temperature Tracking at Emigrant Pass Observatory, Utah

2006 ◽  
Vol 19 (15) ◽  
pp. 3722-3731 ◽  
Author(s):  
Marshall G. Bartlett ◽  
David S. Chapman ◽  
Robert N. Harris
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Incident Solar Radiation ◽  
Ground Temperatures ◽  
Temperature Tracking ◽  
Air Temperatures ◽  
Winter Snow ◽  
A Minor

Abstract Observations of air and ground temperatures collected between 1993 and 2004 from Emigrant Pass Geothermal Climate Observatory in northwestern Utah are analyzed to understand the relationship between these two quantities. The influence of surface air temperature (SAT), incident solar radiation, and snow cover on surface ground temperature (SGT) variations are explored. SAT variations explain 94% of the variance in SGT. Incident solar radiation is the primary variable governing the remaining variance misfit and is significantly more important during summer months than winter months. A linear relationship between the ground–air temperature difference (ΔTsgt-sat) and solar radiation exists with a trend of 1.21 K/(100 W m−2); solar radiation accounts for 1.3% of the variance in SGT. The effects of incident solar radiation also account for the 2.47-K average offset in ΔTsgt-sat. During the winter, snow cover plays a role in governing SGT variability, but exerts only a minor influence on the annual tracking of ground and air temperatures at the site, accounting for 0.5% of the variance in SGT. These observations of the tracking of SGT and SAT confirm that borehole temperature changes mimic changes in SAT at frequencies appropriate for climatic reconstructions.

scholarly journals Snow cover duration trends observed at sites and predicted by multiple models

2020 ◽  
Vol 14 (12) ◽  
pp. 4687-4698
Author(s):  
Richard Essery ◽  
Hyungjun Kim ◽  
Libo Wang ◽  
Paul Bartlett ◽  
Aaron Boone ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Strongly Correlated ◽  
Seasonal Snow ◽  
Physically Based ◽  
Physically Based Models ◽  
The Common ◽  
Snow Cover Duration ◽  
Two Parameters ◽  
Seasonal Snow Cover

Abstract. The 30-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models, but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.

scholarly journals DEVELOPMENT OF THE MONTHLY AVERAGE DAILY SOLAR RADIATION MAP USING A-CBR, FEM, AND KRIGING METHOD

2017 ◽  
Vol 24 (2) ◽  
pp. 489-512 ◽  
Author(s):  
Choongwan KOO ◽  
Taehoon HONG ◽  
Kwangbok JEONG ◽  
Jimin KIM
Keyword(s):  
Solar Radiation ◽  
Decision Makers ◽  
Estimation Accuracy ◽  
Case Based Reasoning ◽  
Final Decision ◽  
Kriging Method ◽  
Pv System ◽  
Fem Model ◽  
Remote Sensors ◽  
Monthly Average

Photovoltaic (PV) system could be implemented to mitigate global warming and lack of energy. To maximize its effectiveness, the monthly average daily solar radiation (MADSR) should be accurately estimated, and then an accurate MADSR map could be developed for final decision-makers. However, there is a limitation in improving the accuracy of the MADSR map due to the lack of weather stations. This is because it is too expensive to measure the actual MADSR data using the remote sensors in all the sites where the PV system would be installed. Thus, this study aimed to develop the MADSR map with improved estimation accuracy using the advanced case-based reasoning (A-CBR), finite element method (FEM), and kriging method. This study was conducted in four steps: (i) data collection; (ii) estimation of the MADSR data in the 54 unmeasured locations using the A-CBR model; (iii) estimation of the MADSR data in the 89 unmeasured locations using the FEM model; and (iv) development of the MADSR map using the kriging method. Compared to the previous MADSR map, the proposed MADSR map was determined to be improved in terms of its estimation accuracy and classification level.

scholarly journals Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland

2021 ◽  
Vol 13 (11) ◽  
pp. 2045
Author(s):  
Anaí Caparó Bellido ◽  
Bradley C. Rundquist
Keyword(s):  
Snow Cover ◽  
Near Infrared ◽  
Accuracy Assessment ◽  
Important Variable ◽  
Field Station ◽  
Near Surface ◽  
Fractional Snow Cover ◽  
Rgb Images ◽  
Phenological Metrics

Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor vegetation phenology. This research explores the utility of the PhenoCam Network cameras to estimate Fractional Snow Cover (FSC) in grassland. The goal is to operationalize FSC estimates from PhenoCams to inform and improve the satellite-based determination of phenological metrics. The study site is the Oakville Prairie Biological Field Station, located near Grand Forks, North Dakota. We developed a semi-automated process to estimate FSC from PhenoCam images through Python coding. Compared with previous research employing RGB images only, our use of the monochrome RGB + NIR (near-infrared) reduced pixel misclassification and increased accuracy. The results had an average RMSE of less than 8% FSC compared to visual estimates. Our pixel-based accuracy assessment showed that the overall accuracy of the images selected for validation was 92%. This is a promising outcome, although not every PhenoCam Network system has NIR capability.

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