Climate Conditions at Perennially Ice-Covered Lake Untersee, East Antarctica

2015 ◽  
Vol 54 (7) ◽  
pp. 1393-1412 ◽  
Author(s):  
Dale T. Andersen ◽  
Christopher P. McKay ◽  
Victor Lagun

AbstractIn November 2008 an automated meteorological station was established at Lake Untersee in East Antarctica, producing a 5-yr data record of meteorological conditions at the lake. This dataset includes five austral summer seasons composed of December, January, and February (DJF). The average solar flux at Lake Untersee for the four years with complete solar flux data is 99.2 ± 0.6 W m−2. The mean annual temperature at Lake Untersee was determined to be −10.6° ± 0.6°C. The annual degree-days above freezing for the five years were 9.7, 37.7, 22.4, 7.0, and 48.8, respectively, with summer (DJF) accounting for virtually all of this. For these five summers the average DJF temperatures were −3.5°, −1.9°, −2.2°, −2.6°, and −2.5°C. The maximum (minimum) temperatures were +5.3°, +7.6°, +5.7°, +4.4°, and +9.0°C (−13.8°, −12.8°, −12.9°, −13.5°, and −12.1°C). The average of the wind speed recorded was 5.4 m s−1, the maximum was 35.7 m s−1, and the average daily maximum was 15 m s−1. The wind speed was higher in the winter, averaging 6.4 m s−1. Summer winds averaged 4.7 m s−1. The dominant wind direction for strong winds is from the south for all seasons, with a secondary source of strong winds in the summer from the east-northeast. Relative humidity averages 37%; however, high values will occur with an average period of ~10 days, providing a strong indicator of the quasi-periodic passage of storms across the site. Low summer temperatures and high wind speeds create conditions at the surface of the lake ice resulting in sublimation rather than melting as the main mass-loss process.

2021 ◽  
Vol 12 (4) ◽  
pp. 1239-1251
Author(s):  
Jan Wohland ◽  
Doris Folini ◽  
Bryn Pickering

Abstract. Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well-established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20-year timescales by 1 order of magnitude, despite the fact that smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble-mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind-related infrastructure like wind energy.


2018 ◽  
Vol 64 (248) ◽  
pp. 990-1002 ◽  
Author(s):  
FLORENT DOMINE ◽  
MARIA BELKE-BREA ◽  
DENIS SARRAZIN ◽  
LAURENT ARNAUD ◽  
MATHIEU BARRERE ◽  
...  

ABSTRACTBasal depth hoar that forms in Arctic snowpacks often has a low thermal conductivity, strongly contributing to the snowpack thermal insulance and impacting the permafrost thermal regime. At Ward Hunt Island (Canadian high Arctic, 83°05′N, 74°07′W) almost no depth hoar was observed in spring 2016 despite favorable thermal conditions. We hypothesize that depth hoar formation was impeded by the combination of two factors (1) strong winds in fall that formed hard dense wind slabs where water vapor transport was slow and (2) low soil moisture that led to rapid ground cooling with no zero-curtain period, which reduced soil temperature and the temperature gradient in the snowpack. Comparisons with detailed data from the subsequent winter at Ward Hunt and from Bylot Island (73°09′N, 80°00′W) and with data from Barrow and Alert indicate that both high wind speeds after snow onset and low soil moisture are necessary to prevent Arctic depth hoar formation. The role of convection to form depth hoar is discussed. A simple preliminary strategy to parameterize depth hoar thermal conductivity in snow schemes is proposed based on wind speed and soil moisture. Finally, warming-induced vegetation growth and soil moisture increase should reduce depth hoar thermal conductivity, potentially affecting permafrost temperature.


2013 ◽  
Vol 26 (4) ◽  
pp. 1172-1191 ◽  
Author(s):  
Nick Earl ◽  
Steve Dorling ◽  
Richard Hewston ◽  
Roland von Glasow

Abstract The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter- and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980–2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameter k spatially varying from 1.4 to 2.1, highlighting that the commonly assumed k = 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors' analyses place the particularly “low wind” year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of ±20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.


2021 ◽  
pp. 1-52
Author(s):  
Cheng Shen ◽  
Jinlin Zha ◽  
Jian Wu ◽  
Deming Zhao

AbstractInvestigations of variations and causes of near-surface wind speed (NWS) further understanding of the atmospheric changes and improve the ability of climate analysis and projections. NWS varies on multiple temporal scales; however, the centennial-scale variability in NWS and associated causes over China remains unknown. In this study, we employ the European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA-20C) to study the centennial-scale changes in NWS from 1900–2010. Meanwhile, a forward stepwise regression algorithm is used to reveal the relationships between NWS and large-scale ocean-atmosphere circulations. The results show three unique periods in annual mean NWS over China from 1900–2010. The annual mean NWS displayed a decreasing trend of -0.87% decade-1 and -11.75% decade-1 from 1900–1925 and 1957–2010, respectively, which were caused by the decreases in the days with strong winds, with trends of -6.64 and -4.66 days decade-1, respectively. The annual mean NWS showed an upward trend of 55.47% decade-1 from 1926–1956, which was caused by increases in the days with moderate (0.43 days decade-1) and strong winds (23.55 days decade-1). The reconstructed wind speeds based on forward stepwise regression algorithm matched well with the original wind speeds; therefore, the decadal changes in NWS over China at centennial-scale were mainly induced by large-scale ocean-atmosphere circulations, with the total explanation power of 66%. The strongest explanation power was found in winter (74%), and the weakest explanation power was found in summer (46%).


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Nadia Bloemendaal ◽  
Hans de Moel ◽  
Sanne Muis ◽  
Ivan D. Haigh ◽  
Jeroen C. J. H. Aerts

Abstract Tropical cyclones (TC) are one of the deadliest and costliest natural disasters. To mitigate the impact of such disasters, it is essential to know extreme exceedance probabilities, also known as return periods, of TC hazards. In this paper, we demonstrate the use of the STORM dataset, containing synthetic TCs equivalent of 10,000 years under present-day climate conditions, for the calculation of TC wind speed return periods. The temporal length of the STORM dataset allows us to empirically calculate return periods up to 10,000 years without fitting an extreme value distribution. We show that fitting a distribution typically results in higher wind speeds compared to their empirically derived counterparts, especially for return periods exceeding 100-yr. By applying a parametric wind model to the TC tracks, we derive return periods at 10 km resolution in TC-prone regions. The return periods are validated against observations and previous studies, and show a good agreement. The accompanying global-scale wind speed return period dataset is publicly available and can be used for high-resolution TC risk assessments.


2018 ◽  
Vol 57 (3) ◽  
pp. 659-674 ◽  
Author(s):  
Brian H. Tang ◽  
Nick P. Bassill

AbstractA statistical downscaling algorithm is introduced to forecast surface wind speed at a location. The downscaling algorithm consists of resolved and unresolved components to yield a time series of synthetic wind speeds at high time resolution. The resolved component is a bias-corrected numerical weather prediction model forecast of the 10-m wind speed at the location. The unresolved component is a simulated time series of the high-frequency component of the wind speed that is trained to match the variance and power spectral density of wind observations at the location. Because of the stochastic nature of the unresolved wind speed, the downscaling algorithm may be repeated to yield an ensemble of synthetic wind speeds. The ensemble may be used to generate probabilistic predictions of the sustained wind speed or wind gusts. Verification of the synthetic winds produced by the downscaling algorithm indicates that it can accurately predict various features of the observed wind, such as the probability distribution function of wind speeds, the power spectral density, daily maximum wind gust, and daily maximum sustained wind speed. Thus, the downscaling algorithm may be broadly applicable to any application that requires a computationally efficient, accurate way of generating probabilistic forecasts of wind speed at various time averages or forecast horizons.


2008 ◽  
Vol 38 (6) ◽  
pp. 1313-1326 ◽  
Author(s):  
Naoto Kihara ◽  
Hiromaru Hirakuchi

Abstract A boundary layer model for evaluating sensible and latent heat fluxes over a mature sea accounting for sea spray effects at wind speeds of up to 28 m s−1 is presented. Heat exchange across the ocean surface controls the development of tropical cyclones, and Emanuel’s theory suggests that the ratio of the exchange coefficient of total enthalpy to the drag coefficient should be greater than 0.75 to maintain the intensity of tropical cyclones. However, traditional bulk algorithms predict a monotonic decrease in this ratio with increasing wind speed, giving a value of less than 0.5 under tropical cyclone conditions. The present model describes a decrease in the ratio with increasing wind speed under weak to moderate winds (<20 m s−1), and a plateau at approximately 0.7 under strong winds (>20 m s−1).


2013 ◽  
Vol 30 (9) ◽  
pp. 2063-2080 ◽  
Author(s):  
Katja Friedrich ◽  
Stephanie Higgins ◽  
Forrest J. Masters ◽  
Carlos R. Lopez

Abstract The influence of strong winds on the quality of optical Particle Size Velocity (PARSIVEL) disdrometer measurements is examined with data from Hurricane Ike in 2008 and from convective thunderstorms observed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) in 2010. This study investigates an artifact in particle size distribution (PSD) measurements that has been observed independently by six stationary PARSIVEL disdrometers. The artifact is characterized by a large number concentration of raindrops with large diameters (>5 mm) and unrealistic fall velocities (<1 m s−1). It is correlated with high wind speeds and is consistently observed by stationary disdrometers but is not observed by articulating disdrometers (instruments whose sampling area is rotated into the wind). The effects of strong winds are further examined with a tilting experiment, in which drops are dripped through the PARSIVEL sampling area while the instrument is tilted at various angles, suggesting that the artifact is caused by particles moving at an angle through the sampling area. Most of the time, this effect occurs when wind speed exceeds 20 m s−1, although it was also observed when wind speed was as low as 10 m s−1. An alternative quality control is tested in which raindrops are removed when their diameters exceed 8 mm and they divert from the fall velocity–diameter relationship. While the quality control does provide more realistic reflectivity values for the stationary disdrometers in strong winds, the number concentration is reduced compared to the observations with an articulating disdrometer.


2012 ◽  
Vol 531 ◽  
pp. 584-588
Author(s):  
Lian Zhong Zhang ◽  
Jing Min Li

Composite generator of solar and wind energy materials the generators, energy-saving environmental protection as a precondition to full use of green renewable energy, making wind power in weak wind conditions and strong winds can maintain normal operation of wind turbines how wind instability Under normal operation, but at higher wind speeds, the blades are not damaged? We start from the pressure-controlled device, the mechanical components and microelectronic technology combine to complete the slurry from the regulator controlled by changing the role of plasma from the body, strengthen the control of wind turbines, wind generators can adapt to changes in wind speed. In the initial wind speed easy to start; in the design of wind speed and wind speed between the initial access to higher wind energy utilization coefficient; In addition, the weak and the solar wind is sufficient,solar power can also get the power to add the function to ensure that the entire power system running smoothly, to achieve full power generation purposes.


2021 ◽  
Author(s):  
Jan Wohland ◽  
Doris Folini ◽  
Bryn Pickering

Abstract. Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20 year timescales by one order of magnitude. Albeit smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind related infrastructure like wind energy.


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