Hurricane Surface Wind Measurements from an Operational Stepped Frequency Microwave Radiometer

2007 ◽  
Vol 135 (9) ◽  
pp. 3070-3085 ◽  
Author(s):  
Eric W. Uhlhorn ◽  
Peter G. Black ◽  
James L. Franklin ◽  
Mark Goodberlet ◽  
James Carswell ◽  
...  

Abstract For the first time, the NOAA/Aircraft Operations Center (AOC) flew stepped frequency microwave radiometers (SFMRs) on both WP-3D research aircraft for operational hurricane surface wind speed measurement in 2005. An unprecedented number of major hurricanes provided ample data to evaluate both instrument performance and surface wind speed retrieval quality up to 70 m s−1 (Saffir–Simpson category 5). To this end, a new microwave emissivity–wind speed model function based on estimates of near-surface winds in hurricanes by global positioning system (GPS) dropwindsondes is proposed. For practical purposes, utilizing this function removes a previously documented high bias in moderate SFMR-measured wind speeds (10–50 m s−1), and additionally corrects an extreme wind speed (>60 m s−1) underestimate. The AOC operational SFMRs yield retrievals that are precise to within ∼2% at 30 m s−1, which is a factor of 2 improvement over the NOAA Hurricane Research Division’s SFMR, and comparable to the precision found here for GPS dropwindsonde near-surface wind speeds. A small (1.6 m s−1), but statistically significant, overall high bias was found for independent SFMR measurements utilizing emissivity data not used for model function development. Across the range of measured wind speeds (10–70 m s−1), SFMR 10-s averaged wind speeds are within 4 m s−1 (rms) of the dropwindsonde near-surface estimate, or 5%–25% depending on speed. However, an analysis of eyewall peak wind speeds indicates an overall 2.6 m s−1 GPS low bias relative to the peak SFMR estimate on the same flight leg, suggesting a real increase in the maximum wind speed estimate due to SFMR’s high-density sampling. Through a series of statistical tests, the SFMR is shown to reduce the overall bias in the peak surface wind speed estimate by ∼50% over the current flight-level wind reduction method and is comparable at extreme wind speeds. The updated model function is demonstrated to behave differently below and above the hurricane wind speed threshold (∼32 m s−1), which may have implications for air–sea momentum and kinetic energy exchange. The change in behavior is at least qualitatively consistent with recent laboratory and field results concerning the drag coefficient in high wind speed conditions, which show a fairly clear “leveling off” of the drag coefficient with increased wind speed above ∼30 m s−1. Finally, a composite analysis of historical data indicates that the earth-relative SFMR peak wind speed is typically located in the hurricane’s right-front quadrant, which is consistent with previous observational and theoretical studies of surface wind structure.

Author(s):  
Shakeel Asharaf ◽  
Duane E. Waliser ◽  
Derek J. Posselt ◽  
Christopher S. Ruf ◽  
Chidong Zhang ◽  
...  

AbstractSurface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass and momentum across the Earth’s surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near surface wind speed over the tropical and sub-tropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s-1 root mean squared difference, meeting the NASA science mission Level-1 uncertainty requirement for wind speeds below 20 m s-1. The quality of the CYGNSS wind is further assessed under different precipitation conditions, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air-sea interaction in regions that are relatively under-sampled by other observing platforms.


2010 ◽  
Vol 23 (5) ◽  
pp. 1209-1225 ◽  
Author(s):  
Hui Wan ◽  
Xiaolan L. Wang ◽  
Val R. Swail

Abstract Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends. This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.


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%).


Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5425
Author(s):  
Justė Jankevičienė ◽  
Arvydas Kanapickas

Developing wind energy in Lithuania is one of the most important ways to achieve green energy goals. Observational data show that the decline in wind speeds in the region may pose challenges for wind energy development. This study analyzed the long-term variation of the observed 2006–2020 and projected 2006–2100 near-surface wind speed at the height of 10 m over Lithuanian territory using data of three models included in the Coupled Model Intercomparison Project phase 5 (CMIP5). A slight decrease in wind speeds was found in the whole territory of Lithuania for the projected wind speed data of three global circulation models for the scenarios RCP2.6, RCP4.5, and RCP8.5. It was found that the most favorable scenario for wind energy production is RCP2.6, and the most unfavorable is the RCP4.5 scenario under which the decrease in wind speed may reach 12%. At the Baltic Sea coastal region, the decline was smaller than in the country’s inner regions by the end of the century. The highest reduction in speed is characteristic of the most severe RCP8.5 scenario. Although the analysis of wind speeds projected by global circulation models (GCM) confirms the downward trends in wind speeds found in the observational data, the projected changes in wind speeds are too small to significantly impact the development of wind farms in Lithuania.


2020 ◽  
Author(s):  
Kaiqiang Deng ◽  
Cesar Azorin-Molina ◽  
Lorenzo Minola ◽  
Deliang Chen

<p>The changes in near-surface (10-m height) wind speed have direct impacts on human society, such as utilization of wind energy, air pollution dispersion and dust storm frequency, which requires comprehensive assessment and improved understanding. Based on ground-based observations and multiple atmospheric reanalysis datasets, previous research revealed significant negative and positive trends in wind speed over land and oceans, respectively. In this study, we used Coupled Model Intercomparison Project Phase 6 (CMIP6) historical simulations to investigate the association between global mean wind speed changes and human-induced forcing. It is found that both unforced pre-industrial control run and historical natural forcing experiments failed in reproducing the observed trends in land and ocean wind speeds. However, the CMIP6 historical greenhouse gas forcing successfully simulated the increasing trend in ocean wind speed, while the CMIP6 historical aerosol forcing and experiments with land use changes seemed to have caused a decreasing trend in wind speeds over both land and ocean, suggesting that anthropogenic forcings are crucial drivers for the recent changes in global wind speed. Further attribution studies are needed to better understand wind speed variability under a warming climate.</p>


2020 ◽  
Author(s):  
Lorenzo Minola ◽  
Fuqing Zhang ◽  
Cesar Azorin-Molina ◽  
Amir Ali Safaei Pirooz ◽  
Richard Flay ◽  
...  

<p>Driven by the twenty-century surface air temperature rise, extreme wind events could change in their frequency and magnitude of occurrence, with drastic impacts on human and ecosystems. As a matter of fact, windstorms and extreme wind conditions contribute to more than half of the economic losses associated with natural disasters in Europe. Across Scandinavia, the occurrence of wind gust events can affect aviation security, as well as damage buildings and forests, representing severe hazards to people, properties and transport. Comprehensive extreme wind datasets and analysis can help improving our understanding of these changes and help the society to cope with these changes. Unfortunately, due to the difficulty in measuring wind gust and the lack of homogeneous and continuous datasets across Sweden, it is challenging to assess and attribute their changes. Global reanalysis products represent a potential tool for assessing changes and impact of extreme winds, only if their ability in representing observed near-surface wind statistics can be demonstrated.</p><p>In this study the new ERA5 reanalysis product has been compared with hourly near-surface wind speed and gust observations across Sweden for 2013-2017. We found that ERA5 shows better agreement with both mean wind speed and gust measurements compared to the previous ERA-Interim reanalysis dataset. Especially across coastal regions, ERA5 has a closer agreement with observed climate statistics. However, significant discrepancies are still found for inland and high-altitude regions. Therefore, the gust parametrization used in ERA5 is further analyzed to better understand if the adopted gust formulation matches the physical processes behind the gust occurrence. Finally, an improved formulation of the gust parametrization is developed across Sweden and further tested for Norway, which is characterized by more complex topography.</p>


2011 ◽  
Vol 41 (1) ◽  
pp. 247-251 ◽  
Author(s):  
Hans Hersbach

Abstract Near the surface, it is commonly believed that the behavior of the (turbulent) atmospheric flow can be well described by a constant stress layer. In the case of a neutrally stratified surface layer, this leads to the well-known logarithmic wind profile that determines the relation between near-surface wind speed and magnitude of stress. The profile is set by a surface roughness length, which, over the ocean surface, is not constant; rather, it depends on the underlying (ocean wave) sea state. For instance, at the European Centre for Medium-Range Weather Forecasts this relation is parameterized in terms of surface stress itself, where the scale is set by kinematic viscosity for light wind and a Charnock parameter for strong wind. For given wind speed at a given height, the determination of the relation between surface wind and stress (expressed by a drag coefficient) leads to an implicit equation that is to be solved in an iterative way. In this paper a fit is presented that directly expresses the neutral drag coefficient and surface roughness in terms of wind speed without the need for iteration. Since the fit is formulated in purely dimensionless quantities, it is able to produce accurate results over the entire range in wind speed, level height, and values for the Charnock parameter for which the implicit set of equations is believed to be valid.


2020 ◽  
Vol 33 (10) ◽  
pp. 4027-4043 ◽  
Author(s):  
Xu Dong ◽  
Yetang Wang ◽  
Shugui Hou ◽  
Minghu Ding ◽  
Baoling Yin ◽  
...  

AbstractNear-surface wind speed observations from 30 manned meteorological stations and 26 automatic weather stations over the Antarctic Ice Sheet are used to examine the robustness of wind speed climatology in six recent global reanalysis products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Japan Meteorological Agency 55-Year Reanalysis (JRA-55), the Climate Forecast System Reanalysis (CFSR), the National Centers for Environmental Prediction–U.S. Department of Energy (DOE) Reanalysis 2 (NCEP2), and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and fifth-generation reanalysis (ERA5). Their skills for representing near-surface wind speeds vary by season, with better performance in summer than in winter. At the regional scale, all reanalysis datasets perform more poorly for the magnitude, but better for their year-to-year changes in wind regimes in the escarpment than the coastal and plateau regions. By comparison, ERA5 has the best performance for the monthly averaged wind speed magnitude and the interannual variability of the near-surface wind speed from 1979 onward. Intercomparison exhibits high and significant correlations for annual and seasonal wind speed Antarctic-wide averages from different datasets during their overlapping timespans (1980–2018), despite some regional disagreements between the different reanalyses. Furthermore, all of the reanalyses show positive trends of the annual and summer wind speeds for the 1980–2018 period, which are linked with positive polarity of the southern annular mode.


2021 ◽  
Author(s):  
Xia Li ◽  
Yongjie Pan ◽  
Yingsha Jiang

Abstract Near-surface wind speed is of great significance in many aspects of the human production and living. This study analyses the spatiotemporal characteristics of the near-surface wind speed and wind speed percentiles with meteorological station observations in China from 1979 to 2019. Furthermore, the mechanisms of the wind speed variations are also investigated with ERA-Interim reanalysis dataset. Spatially, the wind speeds in the northern and eastern regions of China are larger than that in the central and southern regions. Seasonally, the wind speed in spring is significantly larger than that in the other seasons. The dispersion degree of wind speed in spring is larger than that in the other seasons both spatially and temporally. The near-surface wind speed in China shows significantly decreasing trends during 1979–2019, particularly in 1979–1999, but the wind speed trend reversed after 2000. After dividing the wind speed into different percentiles, it recognizes that the decreasing trend of stronger winds are more significant than that of weaker winds. The weaker the wind speed, the more significant increasing trend after 2000. Therefore, the decreasing wind speed trend before 2000 is mainly caused by the significant reduction of strong wind, while the reversal trend after 2000 results from the increase of weak wind. The variations of the wind speed over China attributed to both the U and V wind components, and the variations of zonal wind is closely related to the weakened upper westerly wind field and the uneven warming between high and low latitudes.


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