scholarly journals High-Resolution Numerical Modelling of Near-Surface Atmospheric Fields in the Complex Terrain of James Ross Island, Antarctic Peninsula

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 360
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Antarctic Peninsula ◽  
Wind Direction ◽  
Wrf Model ◽  
Lower Altitude ◽  
Near Surface ◽  
James Ross Island ◽  
The Antarctic ◽  
The Impact

The Antarctic Peninsula belongs to the regions of the Earth that have seen the highest increase in air temperature in the past few decades. The warming is reflected in degradation of the cryospheric system. The impact of climate variability and interactions between the atmosphere and the cryosphere can be studied using numerical atmospheric models. In this study, the standard version of the Weather Research and Forecasting (WRF) model was validated on James Ross Island in the northern part of the Antarctic Peninsula. The aim of this study was to verify the WRF model output at 700 m horizontal resolution using air temperature, wind speed and wind direction observations from automatic weather stations on the Ulu Peninsula, the northernmost part of James Ross Island. Validation was carried out for two contrasting periods (summer and winter) in 2019/2020 to assess possible seasonal effects on model accuracy. Simulated air temperatures were in very good agreement with measurements (mean bias −1.7 °C to 1.4 °C). The exception was a strong air temperature inversion during two of the winter days when a significant positive bias occurred at the coastal and lower-altitude locations on the Ulu Peninsula. Further analysis of the WRF estimates showed a good skill in simulating near-surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). However, bias and RMSE for wind speed tended to be better in summer. The performance of three WRF boundary layer schemes (MYJ, MYNN, QNSE) was further evaluated. The QNSE scheme was generally more accurate than MYNN and MYJ, but the differences were quite small and varied with time and place. The MYNN and QNSE schemes tended to achieve better wind speed simulation quality than the MYJ scheme. The model successfully captured wind direction, showing only slight differences to the observed values. It was shown that at lower altitudes the performance of the model can vary greatly with time. The model results were more accurate during high wind speed southwestern flow, while the accuracy decreased under weak synoptic-scale forcing, accompanied by an occurrence of mesoscale atmospheric processes.

scholarly journals Assessment of the WRF model performance in air temperature and wind speed simulation over a complex Antarctic topography

2021 ◽  
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Antarctic Peninsula ◽  
Wind Direction ◽  
Surface Wind ◽  
Wrf Model ◽  
Seasonal Effects ◽  
Winter Period ◽  
Glacier Mass Balance ◽  
Model Accuracy

<p>The Antarctic Peninsula experiences a strong climate variability which is well reflected in glacier mass balance and state of the other cryospheric components. A better insight into the interactions of the atmosphere and the cryosphere can be obtained using numerical atmospheric models. In the presented work, the Weather Research and Forecasting (WRF) model at 700 m horizontal resolution was validated in the northern part of James Ross Island, Antarctic Peninsula. The model topography was based on the Reference Elevation Model of Antarctica. Sea ice cover was updated daily using high–resolution satellite observations. The WRF output was compared with air temperature, wind speed and wind direction observations from multiple automatic weather stations located in a complex topography and a mosaic of land cover types of Ulu Peninsula. Two periods in 2019/2020 representing contrasting seasons (summer and winter) were selected to identify possible seasonal effects on model accuracy. The three WRF boundary layer schemes (MYJ, MYNN, QNSE) were tested and the spatial and seasonal variability in their performance was evaluated. Simulated air temperatures were in very good agreement with measurements (mean bias –1.7 °C to 1.4 °C). The model was within 2 °C of observations in 47–72 % of the winter period and in 66–79 % of the summer period. An exception was a strong air temperature inversion at two winter days when the model accuracy decreased at low–altitude sites. Additional analysis of the WRF output revealed a good skill in simulating near–surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). Wind speed mean bias was mostly lower than 2.5 m·s<sup>–1</sup>, but higher wind speed overestimation was found at a coastal site during the winter validation period. The model successfully captured wind direction, showing only small differences to the observed values. Finally, the model accuracy at coastal and low–altitude sites was found to be more sensitive to the strength of synoptic–scale wind than at higher–altitude sites.  </p>

scholarly journals The Large-eddy Observatory Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially-distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing

2021 ◽  
Author(s):  
Karl Lapo ◽  
Anita Freundorfer ◽  
Antonia Fritz ◽  
Johann Schneider ◽  
Johannes Olesch ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Wind Speed ◽  
Air Temperature ◽  
Wind Direction ◽  
Fiber Optic ◽  
Layer Structure ◽  
Distributed Sensing ◽  
Near Surface ◽  
Large Eddy

Abstract. The weak-wind Stable Boundary Layer (wwSBL) is poorly described by theory and breaks basic assumptions necessary for observations of turbulence. Understanding the wwSBL requires distributed observations capable of separating between submeso and turbulent scales. To this end, we present the Large Eddy Observatory, Voitsumra Experiment 2019 (LOVE19) which featured 1350 m of fiber optic distributed sensing (FODS) of air temperature and wind speed, as well as an experimental wind direction method, at scales as fine as 1 s and 0.127 m in addition to a suite of point observations of turbulence and ground-based remote sensing. Additionally, flights with a fiber optic cable attached to a tethered balloon provide an unprecedented detailed view of the boundary layer structure with a resolution of 0.254 m and 10 s between 1–200 m height. Two examples are provided demonstrating the unique capabilities of the LOVE19 data for examining boundary layer processes: 1) FODS observations between 1m and ~200 m height during a period of gravity waves propagating across the entire boundary layer and 2) tracking a near-surface, transient submeso structure that causes an intermittent burst of turbulence. All data can be accessed at Zenodo through the DOI https://doi.org/10.5281/zenodo.4312976 (Lapo et al., 2020a).

scholarly journals Canopy Urban Heat Island and Its Association with Climate Conditions in Dubai, UAE

Climate ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 81 ◽  
Author(s):  
Afifa Mohammed ◽  
Gloria Pignatta ◽  
Evangelia Topriska ◽  
Mattheos Santamouris
Keyword(s):  
Wind Speed ◽  
Urban Heat Island ◽  
Rural Area ◽  
Air Temperature ◽  
Negative Correlation ◽  
Wind Direction ◽  
Weather Data ◽  
Heat Island ◽  
Urban Heat ◽  
The Impact

The impact that climate change and urbanization are having on the thermal-energy balance of the built environment is a major environmental concern today. Urban heat island (UHI) is another phenomenon that can raise the temperature in cities. This study aims to examine the UHI magnitude and its association with the main meteorological parameters (i.e., temperature, wind speed, and wind direction) in Dubai, United Arab Emirates. Five years of hourly weather data (2014–2018) obtained from weather stations located in an urban, suburban, and rural area, were post-processed by means of a clustering technique. Six clusters characterized by different ranges of wind directions were analyzed. The analysis reveals that UHI is affected by the synoptic weather conditions (i.e., sea breeze and hot air coming from the desert) and is larger at night. In the urban area, air temperature and night-time UHI intensity, averaged on the five year period, are 1.3 °C and 3.3 °C higher with respect to the rural area, respectively, and the UHI and air temperature are independent of each other only when the wind comes from the desert. A negative and inverse correlation was found between the UHI and wind speed for all the wind directions, except for the northern wind where no correlation was observed. In the suburban area, the UHI and both temperatures and wind speed ranged between the strong and a weak negative correlation considering all the wind directions, while a strong negative correlation was observed in the rural area. This paper concludes that UHI intensity is strongly associated with local climatic parameters and to the changes in wind direction.

Topographical effect of the Antarctic Peninsula on a strong wind event

2021 ◽  
pp. 1-11
Author(s):  
Hataek Kwon ◽  
Seong-Joong Kim ◽  
Sang-Woo Kim ◽  
Sinu Kim
Keyword(s):  
Wind Speed ◽  
Antarctic Peninsula ◽  
Critical Role ◽  
Wrf Model ◽  
Strong Discontinuity ◽  
Strong Wind ◽  
Easterly Wind ◽  
Wind Event ◽  
Topographical Effect ◽  
The Antarctic

Abstract The topographical effect on a strong wind event that occurred on 7 January 2013 at King Sejong Station (KSJ), Antarctica, was investigated using the Polar Weather Research and Forecasting (WRF) model. Numerical experiments applying three different terrain heights of the Antarctic Peninsula (AP) were performed to quantitatively estimate the topographical effect on the selected strong wind event. The experiment employing original AP topography successfully represented the observed features in the strong wind event, both in terms of peak wind speed (by ~94%; ~19.7 m/s) and abrupt transitions of wind speed. In contrast, the experiment with a flattened terrain height significantly underestimated the peak wind speeds (by ~51%; ~10.4 m/s) of the observations. An absence of AP topography failed to simulate both a strong discontinuity of sea-level pressure fields around the east coast of the AP and a strong south-easterly wind over the AP. As a result, the observed downslope windstorm, driven by a flow overriding a barrier, was not formed at the western side of the AP, resulting in no further enhancement of the wind at KSJ. This result demonstrates that the topography of the AP played a critical role in driving the strong wind event at KSJ on 7 January 2013, accounting for ~50% of the total wind speed.

scholarly journals An Assessment of ERA5 Reanalysis for Antarctic Near-Surface Air Temperature

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 217
Author(s):  
Jiangping Zhu ◽  
Aihong Xie ◽  
Xiang Qin ◽  
Yetang Wang ◽  
Bing Xu ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Antarctic Peninsula ◽  
Austral Summer ◽  
Correlation Coefficients ◽  
East Antarctica ◽  
West Antarctica ◽  
Austral Spring ◽  
Reanalysis Dataset ◽  
Near Surface ◽  
The Antarctic

The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 °C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.

scholarly journals Observed Boundary Layer Wind Structure and Balance in the Hurricane Core. Part I: Hurricane Georges

2006 ◽  
Vol 63 (9) ◽  
pp. 2169-2193 ◽  
Author(s):  
Jeffrey D. Kepert
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Radial Profile ◽  
Lower Altitude ◽  
Near Surface ◽  
Wind Structure ◽  
The Right ◽  
Tropical Cyclone Boundary Layer ◽  
Upper Boundary

Abstract The GPS dropsonde allows observations at unprecedentedly high horizontal and vertical resolution, and of very high accuracy, within the tropical cyclone boundary layer. These data are used to document the boundary layer wind field of the core of Hurricane Georges (1998) when it was close to its maximum intensity. The spatial variability of the boundary layer wind structure is found to agree very well with the theoretical predictions in the works of Kepert and Wang. In particular, the ratio of the near-surface wind speed to that above the boundary layer is found to increase inward toward the radius of maximum winds and to be larger to the left of the track than to the right, while the low-level wind maximum is both more marked and at lower altitude on the left of the storm track than on the right. However, the expected supergradient flow in the upper boundary layer is not found, with the winds being diagnosed as close to gradient balance. The tropical cyclone boundary layer model of Kepert and Wang is used to simulate the boundary layer flow in Hurricane Georges. The simulated wind profiles are in good agreement with the observations, and the asymmetries are well captured. In addition, it is found that the modeled flow in the upper boundary layer at the eyewall is barely supergradient, in contrast to previously studied cases. It is argued that this lack of supergradient flow is a consequence of the particular radial structure in Georges, which had a comparatively slow decrease of wind speed with radius outside the eyewall. This radial profile leads to a relatively weak gradient of inertial stability near the eyewall and a strong gradient at larger radii, and hence the tropical cyclone boundary layer dynamics described by Kepert and Wang can produce only marginally supergradient flow near the radius of maximum winds. The lack of supergradient flow, diagnosed from the observational analysis, is thus attributed to the large-scale structure of this particular storm. A companion paper presents a similar analysis for Hurricane Mitch (1998), with contrasting results.

scholarly journals Snow density along the route traversed by the Japanese-Swedish Antarctic Expedition 2007/08

2012 ◽  
Vol 58 (209) ◽  
pp. 529-539 ◽  
Author(s):  
Shin Sugiyama ◽  
Hiroyuki Enomoto ◽  
Shuji Fujita ◽  
Kotaro Fukui ◽  
Fumio Nakazawa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Coastal Region ◽  
Snow Density ◽  
Syowa Station ◽  
Near Surface ◽  
A Value ◽  
Surface Snow ◽  
The Mean ◽  
The Antarctic

AbstractDuring the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m-3 over a region spanning an elevation range of 365-3800 ma.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m-3 (m s-1)-1. This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed.

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