scholarly journals Sensitivity of Numerical Simulations of Near-Surface Atmospheric Conditions to Snow Depth and Surface Albedo during an Ice Fog Event over Heber Valley

2019 ◽  
Vol 58 (4) ◽  
pp. 797-811 ◽  
Author(s):  
Feimin Zhang ◽  
Zhaoxia Pu
Keyword(s):  
Numerical Simulations ◽  
Snow Depth ◽  
Surface Albedo ◽  
Wrf Model ◽  
Atmospheric Modeling ◽  
Initial Surface ◽  
Atmospheric Conditions ◽  
Surface Cooling ◽  
Near Surface ◽  
Ice Fog

AbstractThis study examines the sensitivity of numerical simulations of near-surface atmospheric conditions to the initial surface albedo and snow depth during an observed ice fog event in the Heber Valley of northern Utah. Numerical simulation results from the mesoscale community Weather Research and Forecasting (WRF) Model are compared with observations from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program fog field program. It is found that near-surface cooling during the nighttime is significantly underestimated by the WRF Model, resulting in the failure of the model to reproduce the observed fog episode. Meanwhile, the model also overestimates the temperature during the daytime. Nevertheless, these errors could be reduced by increasing the initial surface albedo and snow depth, which act to cool the near-surface atmosphere by increasing the reflection of downward shortwave radiation and decreasing the heating effects from the soil layer. Overall results indicate the important effects of snow representation on the simulation of near-surface atmospheric conditions and highlight the need for snow measurements in the cold season for improved model physics parameterizations.

Idealized large-eddy simulations of stratocumulus advecting over cold water. Part 1: Boundary layer decoupling

2021 ◽  
Author(s):  
Youtong Zheng ◽  
Haipeng Zhang ◽  
Daniel Rosenfeld ◽  
Seoung-Soo Lee ◽  
Tianning Su ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Cold Water ◽  
Temperature Inversion ◽  
Atmospheric Modeling ◽  
Sea Surface ◽  
Entrainment Rate ◽  
Surface Cooling ◽  
Near Surface ◽  
Large Eddy

AbstractWe explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking the warm air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the sub-cloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in part 2. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate doesn’t.

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.

scholarly journals Direct radiative effects of intense Mediterranean desert dust outbreaks

2017 ◽  
Author(s):  
Antonis Gkikas ◽  
Vincenzo Obiso ◽  
Carlos Pérez García-Pando ◽  
Oriol Jorba ◽  
Nikos Hatzianastassiou ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Effects ◽  
Surface Cooling ◽  
European Continent ◽  
Near Surface ◽  
Desert Dust ◽  
Mineral Particles ◽  
Strong Surface

Abstract. The direct radiative effect (DRE) of 20 intense and widespread dust outbreaks that affected the broader Mediterranean basin during the period March 2000 – February 2013, has been calculated with the regional NMMB-MONARCH model. The DREs have been calculated based on short-term simulations (84 hours) for a domain covering the Sahara and most part of the European continent. At midday, desert dust outbreaks induce locally a NET (shortwave plus longwave) strong atmospheric warming (DREATM values up to 285 Wm−2), a strong surface cooling (DRENETSURF values down to −337 Wm−2) whereas they strongly reduce the downward radiation at the ground (DRESURF values down to −589 Wm−2). During nighttime, reverse effects of smaller magnitude are found. At the top of the atmosphere (TOA), positive (planetary warming) DREs up to 85 Wm−2 are found over highly reflective surfaces while negative (planetary cooling) DREs down to −184 Wm−2 are computed over dark surfaces at noon. Desert dust outbreaks significantly affect the regional radiation budget, with regional clear-sky NET DRE values ranging from −13.9 to 2.6 Wm−2, from −43.6 to 4 Wm−2, from −26.3 to 3.9 Wm−2 and from −3.7 to 28 Wm−2 for TOA, SURF, NETSURF and ATM, respectively. Although the shortwave (SW) DREs are larger than the longwave (LW) ones, the latter are comparable or even larger at TOA, particularly over the Sahara at midday. As a response to the strong surface cooling during daytime, dust outbreaks cause a reduction of the regional sensible and latent heat fluxes by up to 45 Wm−2 and 4 Wm−2, respectively, averaged over land areas of the simulation domain. Dust outbreaks reduce the temperature at 2 meters by up to 4 K during day, whereas a reverse tendency of similar magnitude is found during night. Depending on the vertical distribution of dust loads and time, mineral particles heat (cool) the atmosphere by up to 0.9 K (0.8 K) during daytime (nighttime) within atmospheric dust layers. Beneath and above the dust clouds, mineral particles cool (warm) the atmosphere by up to 1.3 K (1.2 K) at noon (night). When dust radiative effects are taken into account in numerical simulations, the total emitted dust and dust AOD, computed on a regional mean basis, are decreased (negative feedback) by 19.5 % and 6.9 %. The consideration of dust radiative effects in numerical simulations improves the model predictive skills. More specifically, it reduces the model positive and negative biases for the downward surface SW and LW radiation, respectively, with respect to Baseline Surface Radiation Network (BSRN) measurements. In addition, they also reduce the model near-surface (at 2 meters) nocturnal cold biases by up to 0.5 K (regional averages), as well as the model warm biases at 950 and 700 hPa, where the dust concentration is maximized, by up to 0.4 K.

scholarly journals Atmospheric Processes and Climatological Characteristics of the 79N Glacier (Northeast Greenland)

2019 ◽  
Vol 147 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Jenny V. Turton ◽  
Thomas Mölg ◽  
Dirk Van As
Keyword(s):  
Air Temperature ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Greenland Ice Sheet ◽  
Cloud Formation ◽  
Atmospheric Conditions ◽  
Subsequent Increase ◽  
Near Surface ◽  
Surface Mass ◽  
Atmospheric Processes

Abstract The Nioghalvfjerdsfjorden glacier (the 79 fjord, henceforth referred to as 79N) has been thinning and accelerating since the early 2000s, as a result of calving episodes at the front of the glacier. As 8% of the Greenland Ice Sheet area drains into 79N, changes in the stability of 79N could propagate into the interior of Greenland. Despite this concern, relatively little is known about the atmospheric conditions over 79N. We present the surface atmospheric processes and climatology of the 79N region from analyses of data from four automatic weather stations (AWS) and reanalysis data from ERA-Interim. Over the floating section of the glacier, the annual average air temperature is −16.7°C, decreasing to −28.5°C during winter. Winds over the glacier are predominantly westerly and are of katabatic origin. Over the last 39 years the near-surface air temperature has increased at a rate of +0.08°C yr−1. In addition, we find that large, rapid (48 h) temperature increases (>10°C) occur during the five-month dark period (November–March). Eight (±4) warm-air events occur annually from 1979 to 2017. We use the Weather Research and Forecasting (WRF) Model to simulate a particular warm-air event with above-freezing air temperatures between 30 November and 2 December 2014. The warm event was caused by warm-air advection from the southeast and a subsequent increase in the longwave radiation toward the surface due to low-level cloud formation. The frequent nature of the temperature jumps and the magnitude of the temperature increases are likely to have an impact on the surface mass balance of the glacier by bringing the skin temperatures to the melting point.

scholarly journals A wind-albedo-wind feedback driven by landscape evolution

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jordan T. Abell ◽  
Alex Pullen ◽  
Zachary J. Lebo ◽  
Paul Kapp ◽  
Lucas Gloege ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Dust Emission ◽  
Wrf Model ◽  
Gobi Desert ◽  
Surface Winds ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Fine Grained ◽  
Wind Speeds ◽  
Modify Surface

AbstractThe accurate characterization of near-surface winds is critical to our understanding of past and modern climate. Dust lofted by these winds has the potential to modify surface and atmospheric conditions as well as ocean biogeochemistry. Stony deserts, low dust emitting regions today, represent expansive areas where variations in surficial geology through time may drastically impact near-surface conditions. Here we use the Weather Research and Forecasting (WRF) model over the western Gobi Desert to demonstrate a previously undocumented process between wind-driven landscape evolution and boundary layer conditions. Our results show that altered surficial thermal properties through winnowing of fine-grained sediments and formation of low-albedo gravel-mantled surfaces leads to an increase in near-surface winds by up to 25%; paradoxically, wind erosion results in faster winds regionally. This wind-albedo-wind feedback also leads to an increase in the frequency of hours spent at higher wind speeds, which has implications for dust emission potential.

scholarly journals Observations and Modeling of Atmospheric Profiles in the Arctic Seasonal Ice Zone

2015 ◽  
Vol 143 (1) ◽  
pp. 39-53 ◽  
Author(s):  
Zheng Liu ◽  
Axel Schweiger ◽  
Ron Lindsay
Keyword(s):  
Boundary Layer ◽  
Relative Humidity ◽  
Wrf Model ◽  
Specific Humidity ◽  
The Arctic ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Low Level ◽  
The Mean ◽  
Seasonal Ice Zone

Abstract The authors use the Polar Weather Research and Forecasting (WRF) Model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) in the summer of 2013 over the Beaufort Sea. With the SIZRS dropsonde data, the performance of WRF simulations and two forcing datasets is evaluated: the Interim ECMWF Re-Analysis (ERA-Interim) and the Global Forecast System (GFS) analysis. General features of observed mean profiles, such as low-level temperature inversion, low-level jet (LLJ), and specific humidity inversion are reproduced by all three models. A near-surface warm bias and a low-level moist bias are found in ERA-Interim. WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing. The improvement in the mean LLJ is likely related to the lower values of the boundary layer diffusion in WRF than in ERA-Interim and GFS, which also explains the lower near-surface temperature in WRF than the forcing. The relative humidity profiles have large differences between the observations, the ERA-Interim, and the GFS. The WRF simulated relative humidity closely resembles the forcings, suggesting the need to obtain more and better-calibrated humidity data in this region. The authors find that the sea ice concentrations in the ECMWF model are sometimes significantly underestimated due to an inappropriate thresholding mechanism. This thresholding affects both ERA-Interim and the ECMWF operational model. The scale of impact of this issue on the atmospheric boundary layer in the marginal ice zone is still unknown.

scholarly journals Numerical Simulations of Radiative Cooling beneath the Anvils of Supercell Thunderstorms

2010 ◽  
Vol 138 (8) ◽  
pp. 3024-3047 ◽  
Author(s):  
Jeffrey Frame ◽  
Paul Markowski
Keyword(s):  
Surface Layer ◽  
Numerical Simulations ◽  
Radiative Heating ◽  
Shortwave Radiation ◽  
Surface Winds ◽  
Model Surface ◽  
Surface Cooling ◽  
Near Surface ◽  
Regional Prediction ◽  
Supercell Thunderstorms

Abstract Numerical simulations of supercell thunderstorms that include parameterized radiative transfer and surface fluxes are performed using the Advanced Regional Prediction System (ARPS) to investigate the effects of anvil shadows on the near-storm environment. If the simulated storm is nearly stationary, the maximum low-level air temperature deficits within the shadows are about 2 K, which is roughly half the cooling found in some previous observations. It is shown that the extinction of downwelling shortwave radiation by the anvil cloud creates a differential in the flux of downwelling shortwave radiation between the sun and the shade that is at least an order of magnitude greater than the differential of any other term in either the surface radiation or the surface energy budgets. The loss of strong solar heating of the model surface within the shaded regions leads to a reduction of surface temperatures and stabilization of the model surface layer beneath the anvil. The reduction in vertical mixing results in a shallow, strongly vertically sheared layer near the surface and calmer near-surface winds, which are limited to regions in the anvil shadow. This difference in radiative heating is shown not to affect the vertical thermodynamic or wind profiles above the near-surface layer (approximately the lowest 500 m). It is also found that these results are highly sensitive to the magnitude of the near-surface winds. If the initial hodograph is shifted such that the simulated storm acquires a substantial eastward propagation speed, the temperature deficit within the shadow is greatly diminished. This is due to both a weaker surface sensible heat flux and less time during which surface cooling and boundary layer stabilization can occur beneath the anvil.

scholarly journals Large Temperature Fluctuations due to Cold-Air Pool Displacement along the Lee Slope of a Desert Mountain

2017 ◽  
Vol 56 (4) ◽  
pp. 1083-1098 ◽  
Author(s):  
Matthew E. Jeglum ◽  
Sebastian W. Hoch ◽  
Derek D. Jensen ◽  
Reneta Dimitrova ◽  
Zachariah Silver
Keyword(s):  
Low Frequency ◽  
Temperature Fluctuations ◽  
Atmospheric Modeling ◽  
Large Temperature ◽  
Complex Flow ◽  
Near Surface ◽  
Cold Air ◽  
Flow Interactions ◽  
Initial Drop ◽  
Program Temperature

AbstractLarge temperature fluctuations (LTFs), defined as a drop of the near-surface temperature of at least 3°C in less than 30 min followed by a recovery of at least half of the initial drop, were frequently observed during the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. Temperature time series at over 100 surface stations were examined in an automated fashion to identify and characterize LTFs. LTFs occur almost exclusively at night and at locations elevated 50–100 m above the basin floors, such as the east slope of the isolated Granite Mountain (GM). Temperature drops associated with LTFs were as large as 13°C and were typically greatest at heights of 4–10 m AGL. Observations and numerical simulations suggest that LTFs are the result of complex flow interactions of stably stratified flow with a mountain barrier and a leeside cold-air pool (CAP). An orographic wake forms over GM when stably stratified southwesterly nocturnal flow impinges on GM and is blocked at low levels. Warm crest-level air descends in the lee of the barrier, and the generation of baroclinic vorticity leads to periodic development of a vertically oriented vortex. Changes in the strength or location of the wake and vortex cause a displacement of the horizontal temperature gradient along the slope associated with the CAP edge, resulting in LTFs. This mechanism explains the low frequency of LTFs on the west slope of GM as well as the preference for LTFs to occur at higher elevations later at night, as the CAP depth increases.

Machine learning analyses of remote sensing measurements establish strong relationships between vegetation and snow depth in the boreal forest of Interior Alaska

2021 ◽  
Author(s):  
Thomas Douglas ◽  
Caiyun Zhang
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Snow Depth ◽  
Spatial Scales ◽  
Critical Role ◽  
Winter Season ◽  
Thermal Conditions ◽  
Near Surface ◽  
Lidar Measurements ◽  
Remote Sensing Methods

The seasonal snowpack plays a critical role in Arctic and boreal hydrologic and ecologic processes. Though snow depth can be different from one season to another there are repeated relationships between ecotype and snowpack depth. Alterations to the seasonal snowpack, which plays a critical role in regulating wintertime soil thermal conditions, have major ramifications for near-surface permafrost. Therefore, relationships between vegetation and snowpack depth are critical for identifying how present and projected future changes in winter season processes or land cover will affect permafrost. Vegetation and snow cover areal extent can be assessed rapidly over large spatial scales with remote sensing methods, however, measuring snow depth remotely has proven difficult. This makes snow depth–vegetation relationships a potential means of assessing snowpack characteristics. In this study, we combined airborne hyperspectral and LiDAR data with machine learning methods to characterize relationships between ecotype and the end of winter snowpack depth. Our results show hyperspectral measurements account for two thirds or more of the variance in the relationship between ecotype and snow depth. An ensemble analysis of model outputs using hyperspectral and LiDAR measurements yields the strongest relationships between ecotype and snow depth. Our results can be applied across the boreal biome to model the coupling effects between vegetation and snowpack depth.

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