scholarly journals Numerical Simulation of Near-Surface Atmospheric Conditions during a Radiation Fog over the Complex Terrain

2020 ◽  
Vol 555 ◽  
pp. 012093
Author(s):  
Feimin Zhang ◽  
Bohang Ren ◽  
Chunlei Dou ◽  
Chenghai Wang
Keyword(s):  
Numerical Simulation ◽  
Complex Terrain ◽  
Atmospheric Conditions ◽  
Radiation Fog ◽  
Near Surface

Examination of Errors in Near-Surface Temperature and Wind from WRF Numerical Simulations in Regions of Complex Terrain

2013 ◽  
Vol 28 (3) ◽  
pp. 893-914 ◽  
Author(s):  
Hailing Zhang ◽  
Zhaoxia Pu ◽  
Xuebo Zhang
Keyword(s):  
Complex Terrain ◽  
Forecast Error ◽  
Wrf Model ◽  
Atmospheric Temperature ◽  
Lower Atmosphere ◽  
Forecast Errors ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
System A ◽  
Synoptic Forcing

Abstract The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that the WRF model is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the lower-atmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in near-surface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flow-dependent errors are clearly shown.

The Compliance Method for Measurement of Near Surface Residual Stresses—Analytical Background

1994 ◽  
Vol 116 (4) ◽  
pp. 550-555 ◽  
Author(s):  
M. Gremaud ◽  
W. Cheng ◽  
I. Finnie ◽  
M. B. Prime
Keyword(s):  
Numerical Simulation ◽  
Residual Stresses ◽  
Random Errors ◽  
Residual Stress Field ◽  
Near Surface ◽  
Surface Residual Stresses ◽  
Zero Shift ◽  
Stress States ◽  
The Stability ◽  
Piecewise Functions

Introducing a thin cut from the surface of a part containing residual stresses produces a change in strain on the surface. When the strains are measured as a function of the depth of the cut, residual stresses near the surface can be estimated using the compliance method. In previous work, the unknown residual stress field was represented by a series of continuous polynomials. The present paper shows that for stress states with steep gradients, superior predictions are obtained by using “overlapping piecewise functions” to represent the stresses. The stability of the method under the influence of random errors and a zero shift is demonstrated by numerical simulation.

Experiments on wind-driven heat exchange processes over melting snow

2021 ◽  
Author(s):  
Michael Haugeneder ◽  
Tobias Jonas ◽  
Dylan Reynolds ◽  
Michael Lehning ◽  
Rebecca Mott
Keyword(s):  
Snow Cover ◽  
Surface Wind ◽  
Infrared Camera ◽  
Snow Accumulation ◽  
Internal Boundary ◽  
Small Scale ◽  
Snow Melt ◽  
Two Dimensional ◽  
Atmospheric Conditions ◽  
Near Surface

<p>Snowmelt runoff predictions in alpine catchments are challenging because of the high spatial variability of t<span>he snow cover driven by </span>various snow accumulation and ablation processes. In spring, the coexistence of bare and snow-covered ground engages a number of processes such as the enhanced lateral advection of heat over partial snow cover, the development of internal boundary layers, and atmospheric decoupling effects due to increasing stability at the snow cover. The interdependency of atmospheric conditions, topographic settings and snow coverage remains a challenge to accurately account for these processes in snow melt models.<br>In this experimental study, we used an Infrared Camera (VarioCam) pointing at thin synthetic projection screens with negligible heat capacity. Using the surface temperature of the screen as a proxy for the air temperature, we obtained a two-dimensional instantaneous measurement. Screens were installed across the transition between snow-free and snow-covered areas. With IR-measurements taken at 10Hz, we capture<span> the dynamics of turbulent temperature fluctuations</span><span> </span>over the patchy snow cover at high spatial and temporal resolution. From this data we were able to obtain high-frequency, two-dimensional windfield estimations adjacent to the surface.</p><p>Preliminary results show the formation of a stable internal boundary layer (SIBL), which was temporally highly variable. Our data suggest that the SIBL height is very shallow and strongly sensitive to the mean near-surface wind speed. Only strong gusts were capable of penetrating through this SIBL leading to an enhanced energy input to the snow surface.</p><p>With these type of results from our experiments and further measurements this spring we aim to better understand small scale energy transfer processes over patch snow cover and it’s dependency on the atmospheric conditions, enabling to improve parameterizations of these processes in coarser-resolution snow melt models.</p>

scholarly journals Global source attribution of sulfate concentration and direct and indirect radiative forcing

2017 ◽  
Vol 17 (14) ◽  
pp. 8903-8922 ◽  
Author(s):  
Yang Yang ◽  
Hailong Wang ◽  
Steven J. Smith ◽  
Richard Easter ◽  
Po-Lun Ma ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Radiative Forcing ◽  
Dimethyl Sulfide ◽  
Sulfur Source ◽  
Atmospheric Conditions ◽  
So2 Emissions ◽  
Near Surface ◽  
Indirect Radiative Forcing ◽  
Global Source

Abstract. The global source–receptor relationships of sulfate concentrations, and direct and indirect radiative forcing (DRF and IRF) from 16 regions/sectors for years 2010–2014 are examined in this study through utilizing a sulfur source-tagging capability implemented in the Community Earth System Model (CESM) with winds nudged to reanalysis data. Sulfate concentrations are mostly contributed by local emissions in regions with high emissions, while over regions with relatively low SO2 emissions, the near-surface sulfate concentrations are primarily attributed to non-local sources from long-range transport. Regional source efficiencies of sulfate concentrations are higher over regions with dry atmospheric conditions and less export, suggesting that lifetime of aerosols, together with regional export, is important in determining regional air quality. The simulated global total sulfate DRF is −0.42 W m−2, with −0.31 W m−2 contributed by anthropogenic sulfate and −0.11 W m−2 contributed by natural sulfate, relative to a state with no sulfur emissions. In the Southern Hemisphere tropics, dimethyl sulfide (DMS) contributes 17–84 % to the total DRF. East Asia has the largest contribution of 20–30 % over the Northern Hemisphere mid- and high latitudes. A 20 % perturbation of sulfate and its precursor emissions gives a sulfate incremental IRF of −0.44 W m−2. DMS has the largest contribution, explaining −0.23 W m−2 of the global sulfate incremental IRF. Incremental IRF over regions in the Southern Hemisphere with low background aerosols is more sensitive to emission perturbation than that over the polluted Northern Hemisphere.

scholarly journals The effect of atmospheric turbulence and chamber deployment period on autochamber CO<sub>2</sub> and CH<sub>4</sub> flux measurements in an ombrotrophic peatland

2012 ◽  
Vol 9 (2) ◽  
pp. 1439-1482 ◽  
Author(s):  
D. Y. F. Lai ◽  
N. T. Roulet ◽  
E. R. Humphreys ◽  
T. R. Moore ◽  
M. Dalva
Keyword(s):  
Atmospheric Turbulence ◽  
Concentration Gradient ◽  
Co2 Concentration ◽  
Time Of Day ◽  
Reliable Estimate ◽  
Organic Soils ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Ch4 Flux ◽  
Flux Measurements

Abstract. Accurate quantification of soil-atmosphere gas exchange is essential for understanding the magnitude and controls of greenhouse gas emissions. We used an automatic closed dynamic chamber system to measure the fluxes of CO2 and CH4 for several years at the ombrotrophic Mer Bleue peatland near Ottawa, Canada and found that atmospheric turbulence and chamber deployment period had a considerable influence on the observed flux rates. With a short deployment period of 2.5 min, CH4 flux exhibited strong diel patterns and both CH4 and nighttime CO2 effluxes were highly and negatively correlated with friction velocity as were the CO2 concentration gradients in the top 20 cm of peat. This suggests winds were flushing the very porous and relatively dry near surface peat layers, altering the concentration gradient and resulting in a 9 to 57% underestimate of CH4 flux at any time of day and a 13 to 21% underestimate of nighttime CO2 fluxes in highly turbulent conditions. Conversely, there was evidence of an overestimation of ~100% of CH4 and nighttime CO2 effluxes in calm atmospheric conditions possibly due to enhanced near-surface gas concentration gradient by mixing of chamber headspace air by fans. These problems were resolved by extending the deployment period to 30 min. After 13 min of chamber closure, the flux rate of CH4 and nighttime CO2 became constant and were not affected by turbulence thereafter, yielding a reliable estimate of the net biological fluxes. The measurement biases we observed likely exist to some extent in all chamber flux measurements made on porous and aerated substrate, such as peatlands, organic soils in tundra and forests, and snow-covered surfaces, but would be difficult to detect unless high frequency, semi-continuous observations are made.

scholarly journals Wind plants can impact long-term local atmospheric conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Patrick Moriarty
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Weather Prediction ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Direct Observations ◽  
Stable Conditions ◽  
Weather And Climate ◽  
Central United States

AbstractLong-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30  km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

scholarly journals PROMICE automatic weather station data

2021 ◽  
Author(s):  
Robert S. Fausto ◽  
Dirk van As ◽  
Kenneth D. Mankoff ◽  
Baptiste Vandecrux ◽  
Michele Citterio ◽  
...  
Keyword(s):  
Surface Energy Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Atmospheric Conditions ◽  
Production Chain ◽  
Near Surface ◽  
Surface Mass ◽  
Future Assessment

Abstract. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheetproperties since 2007. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate is important for reliablepresent and future assessment of changes to the Greenland ice sheet. Here we present the PROMICE vision, methodology,and each link in the production chain for obtaining and sharing quality-checked data. In this paper we mainly focus on thecritical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic webbaseddatabase of known data quality issues is associated with the data products at (https://github.com/GEUS-PROMICE/PROMICE-AWS-data-issues/). As part of the living data option, the datasets presented and described here are available atDOI: 10.22008/promice/data/aws, https://doi.org/10.22008/promice/data/aws (Fausto and van As, 2019).

Sign in / Sign up

Export Citation Format

Share Document