scholarly journals Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Validation Using Dropsondes

2017 ◽  
Vol 34 (8) ◽  
pp. 1837-1851 ◽  
Author(s):  
Daniel J. Cecil ◽  
Sayak K. Biswas
Keyword(s):  
Wind Speed ◽  
Rain Rate ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Tropical Storm ◽  
Tropical Cyclone Intensity ◽  
Cyclone Intensity ◽  
The Mean ◽  
Weak Winds ◽  
Wide Swath

AbstractSurface wind speed retrievals have been generated and evaluated using Hurricane Imaging Radiometer (HIRAD) measurements from flights over Hurricane Joaquin, Hurricane Patricia, Hurricane Marty, and the remnants of Tropical Storm Erika—all in 2015. Procedures are described here for producing maps of brightness temperature, which are subsequently used for retrievals of surface wind speed and rain rate across a ~50-km-wide swath for each flight leg. An iterative retrieval approach has been developed to take advantage of HIRAD’s measurement characteristics. Validation of the wind speed retrievals has been conducted, using 636 dropsondes released from the same WB-57 high-altitude aircraft carrying HIRAD during the Tropical Cyclone Intensity (TCI) experiment. The HIRAD wind speed retrievals exhibit very small bias relative to the dropsondes, for winds of tropical storm strength (17.5 m s−1) or greater. HIRAD has reduced sensitivity to winds weaker than tropical storm strength and a small positive bias (~2 m s−1). Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD and large positive biases. From the other flights, the root-mean-square differences between HIRAD and the dropsonde winds are 4.1 m s−1 (33%) for winds below tropical storm strength, 5.6 m s−1 (25%) for tropical storm–strength winds, and 6.3 m s−1 (16%) for hurricane-strength winds. The mean absolute differences for those three categories are 3.2 m s−1 (25%), 4.3 m s−1 (19%), and 4.8 m s−1 (12%), respectively, with a bias near zero for winds of tropical storm and hurricane strength.

scholarly journals Evaluation of the Ocean Surface Wind Speed Change following the Super Typhoon from Space-Borne GNSS-Reflectometry

2020 ◽  
Vol 12 (12) ◽  
pp. 2034 ◽  
Author(s):  
Hongsu Liu ◽  
Shuanggen Jin ◽  
Qingyun Yan
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Mean Error ◽  
Super Typhoon ◽  
The Mean ◽  
Ocean Surface Wind

Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s; the mean error was 3.57 m/s; the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.

scholarly journals Satellite Microwave Surface Observations in Tropical Cyclones

2010 ◽  
Vol 138 (2) ◽  
pp. 421-437 ◽  
Author(s):  
Yves Quilfen ◽  
Bertrand Chapron ◽  
Jean Tournadre
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Surface Wind Speed ◽  
Microwave Measurements ◽  
Dual Frequency

Abstract Sea surface estimates of local winds, waves, and rain-rate conditions are crucial to complement infrared/visible satellite images in estimating the strength of tropical cyclones (TCs). Satellite measurements at microwave frequencies are thus key elements of present and future observing systems. Available for more than 20 years, passive microwave measurements are very valuable but still suffer from insufficient resolution and poor wind vector retrievals in the rainy conditions encountered in and around tropical cyclones. Scatterometer and synthetic aperture radar active microwave measurements performed at the C and Ku band on board the European Remote Sensing (ERS), the Meteorological Operational (MetOp), the Quick Scatterometer (QuikSCAT), the Environmental Satellite (Envisat), and RadarSat satellites can also be used to map the surface wind field in storms. Their accuracy is limited in the case of heavy rain and possible saturation of the microwave signals is reported. Altimeter dual-frequency measurements have also been shown to provide along-track information related to surface wind speed, wave height, and vertically integrated rain rate at about 6-km resolution. Although limited for operational use by their dimensional sampling, the dual-frequency capability makes altimeters a unique satellite-borne sensor to perform measurements of key surface parameters in a consistent way. To illustrate this capability two Jason-1 altimeter passes over Hurricanes Isabel and Wilma are examined. The area of maximum TC intensity, as described by the National Hurricane Center and by the altimeter, is compared for these two cases. Altimeter surface wind speed and rainfall-rate observations are further compared with measurements performed by other remote sensors, namely, the Tropical Rainfall Measuring Mission instruments and the airborne Stepped Frequency Microwave Radiometer.

A Coupled-Pixel Model (CPM) Atmospheric Retrieval Algorithm for High-Resolution Imagers

2015 ◽  
Vol 32 (10) ◽  
pp. 1866-1879 ◽  
Author(s):  
Mary Morris ◽  
Christopher S. Ruf
Keyword(s):  
Wind Speed ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Low Frequency ◽  
Surface Wind Speed ◽  
Retrieval Algorithm ◽  
Single Column ◽  
Simplifying Assumptions ◽  
Cross Track

AbstractLow-frequency passive microwave observations allow for oceanic remote sensing of surface wind speed and rain rate from spaceborne and airborne platforms. For most instruments, the modeling of contributions of rain absorption and reemission in a particular field of view is simplified by the observing geometry. However, the simplifying assumptions that can be applied in most applications are not always valid for the scenes that the airborne Hurricane Imaging Radiometer (HIRAD) regularly observes. Collocated Stepped Frequency Microwave Radiometer (SFMR) and HIRAD observations of Hurricane Earl (2010) indicate that retrieval algorithms based on the usual simplified model, referred to here as the decoupled-pixel model (DPM), are not able to resolve two neighboring rainbands at the edge of HIRAD’s swath. The DPM does not allow for the possibility that a single column of atmosphere can affect the observations at multiple cross-track positions. This motivates the development of a coupled-pixel model (CPM) that is developed and tested in this paper. Simulated observations as well as HIRAD’s observations of Hurricane Earl (2010) are used to test the CPM algorithm. Key to the performance of the CPM algorithm is its ability to deconvolve the cross-track scene, as well as unscramble the signatures of surface wind speed and rain rate in HIRAD’s observations. While the CPM approach was developed specifically for HIRAD, other sensors could employ this method in similar complicated observing scenarios.

scholarly journals Deriving the effect of wind speed on clean marine aerosol optical properties using the A-Train satellites

2011 ◽  
Vol 11 (22) ◽  
pp. 11401-11413 ◽  
Author(s):  
V. P. Kiliyanpilakkil ◽  
N. Meskhidze
Keyword(s):  
Optical Properties ◽  
Wind Speed ◽  
Optical Depth ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Marine Aerosol ◽  
Marine Aerosols ◽  
Aerosol Optical Properties ◽  
The Mean ◽  
532 Nm

Abstract. The relationship between "clean marine" aerosol optical properties and ocean surface wind speed is explored using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses are carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. Based on remotely sensed optical properties the CALIPSO algorithm is capable of discriminating "clean marine" aerosols from other types often present over the ocean (such as urban/industrial pollution, desert dust and biomass burning). The global mean optical depth of "clean marine" aerosol at 532 nm (AOD532) is found to be 0.052 ± 0.038 (mean plus or minus standard deviation). The mean layer integrated particulate depolarization ratio of marine aerosols is 0.02 ± 0.016. Integrated attenuated backscatter and color ratio of marine aerosols at 532 nm were found to be 0.003 ± 0.002 sr−1 and 0.530 ± 0.149, respectively. A logistic regression between AOD532 and 10-m surface wind speed (U10) revealed three distinct regimes. For U10 ≤ 4 m s−1 the mean CALIPSO-derived AOD532 is found to be 0.02 ± 0.003 with little dependency on the surface wind speed. For 4 < U10 ≤ 12 m s−1, representing the dominant fraction of all available data, marine aerosol optical depth is linearly correlated with the surface wind speed values, with a slope of 0.006 s m−1. In this intermediate wind speed region, the AOD532 vs. U10 regression slope derived here is comparable to previously reported values. At very high wind speed values (U10 > 18 m s−1), the AOD532-wind speed relationship showed a tendency toward leveling off, asymptotically approaching value of 0.15. The conclusions of this study regarding the aerosol extinction vs. wind speed relationship may have been influenced by the constant lidar ratio used for CALIPSO-derived AOD532. Nevertheless, active satellite sensor used in this study that allows separation of maritime wind induced component of AOD from the total AOD over the ocean could lead to improvements in optical properties of sea spray aerosols and their production mechanisms.

scholarly journals Deriving the effect of wind speed on clean maritime aerosol optical properties using the A-Train satellites

2011 ◽  
Vol 11 (2) ◽  
pp. 4599-4630 ◽  
Author(s):  
V. P. Kiliyanpilakkil ◽  
N. Meskhidze
Keyword(s):  
Optical Properties ◽  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Salt ◽  
Marine Aerosol ◽  
Marine Aerosols ◽  
Aerosol Optical Properties ◽  
The Mean ◽  
532 Nm

Abstract. Relationship between "clean marine" aerosol optical properties and ocean surface wind speed is explored using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses are carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to June 2010. Based on remotely sensed optical properties the CALIPSO algorithm is capable of discriminating "clean marine" aerosols from other types often present over the ocean (such as urban/industrial pollution, desert dust and biomass burning). The global mean optical depth of "clean marine" aerosol at 532 nm (AOD532) is found to be 0.052 ± 0.038. The mean layer integrated volume depolarization ratio of marine aerosols is 0.016 ± 0.012, the value representative of sea salt crystals. Integrated attenuated backscatter and color ratio of marine aerosols at 532 nm were obtained to be 0.003 ± 0.002 sr−1 and 0.530 ± 0.149, respectively. A logistic regression between AOD532 and 10-meter surface wind speed (U10) revealed three distinct regions. For surface winds lower than 4 m s−1, the mean CALIPSO-derived AOD532 is found to be 0.02 ± 0.003 with little dependency on the surface wind speed. For surface winds from 4 m s−1 to 12 m s−1, representing the dominant fraction of all available data, marine aerosol optical depth is linearly correlated with the U10, with a slope of 0.0062 s m−1. In this intermediate wind speed region, the AOD532 vs. U10 regression derived here is comparable to previously reported relationships. At very high wind speed values (U10 > 18 m s−1), the AOD532-wind speed relationship showed a tendency toward leveling off, suggesting the existence of some maximum value for maritime AOD. Results of our calculations suggest that considerable improvements to both optical properties of marine aerosols and their production mechanisms can be achieved by discriminating "clean marine" aerosols (or sea salt particles) from all other types of aerosols present over the ocean.

scholarly journals Effects of surface wind speed decline on modeled hydrological conditions in China

2014 ◽  
Vol 18 (8) ◽  
pp. 2803-2813 ◽  
Author(s):  
X. Liu ◽  
X.-J. Zhang ◽  
Q. Tang ◽  
X.-Z. Zhang
Keyword(s):  
Soil Moisture ◽  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
River Basins ◽  
Annual Runoff ◽  
Infiltration Capacity ◽  
Hydrological Conditions ◽  
Speed Change ◽  
The Mean

Abstract. Surface wind speed decline in China has been widely reported, but its effects on hydrology have not been fully evaluated to date. In this study, the effects of wind speed change on modeled hydrological conditions are investigated using the Variable Infiltration Capacity (VIC) hydrological model for China during the 1966–2011 period. Two model experiments, i.e., VIC simulations with the observed (EXP1) and detrended wind speed (EXP2), are performed over the major river basins in China. The differences between the two experiments are analyzed to assess the effects of wind speed decline. Results show that wind speed has decreased by 29% in China. The wind speed decline would have resulted in a decrease in evapotranspiration of 1–3% of mean annual evapotranspiration and an increase in runoff of 1–6% of mean annual runoff at most basins in China. The sensitivities of evapotranspiration and runoff changes to wind speed change are larger in humid areas than dry areas, while the sensitivity of soil moisture change to wind speed change is situation dependent. The wind speed decline would have offset the expansion of the drought area in China. It has contributed to reducing drought areas by 8.8% of the mean drought area (i.e., approximate 106 × 103 km2 out of 1.2 × 106 km2) over China. The reductions of soil moisture drought induced by wind speed decline are large (more than 5% of the mean drought area) in most basins, except in the Southwest and Pearl River basins.

scholarly journals Historical changes in the Davis Strait Baffin Bay surface winds and waves, 1979-2016

2021 ◽  
pp. 1-44
Author(s):  
Xiaolan L. Wang ◽  
Mercè Casas-Prat ◽  
Yang Feng ◽  
Alex Crosby ◽  
Val R. Swail
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Open Water ◽  
Surface Wind Speed ◽  
Water Area ◽  
Positive Trend ◽  
Baffin Bay ◽  
Historical Changes ◽  
Davis Strait ◽  
The Mean

AbstractThis study presents and analyzes Environment Canada’s Davis Strait Baffin Bay (EC-DSBB) Wind and Wave Reanalysis for the period 1979-2016, to characterize the historical changes in the surface wind speed and ocean surface waves. The trend analysis is carried out only for the months of May-December, when there is a significant ice-free sea area. The results show that 10-meter wind speed (Ws) has increased significantly in most area of the domain in September-December, with some significant decreases over the open water area in June and July. The Ws increases are most extensive in September, with significant increases in both the mean and extremes. It is also shown that the mean wind direction (Wd) has a distinctive seasonal variation, being mainly north- and northwest-ward in June-August, and predominantly south- and southeast-ward in May and September-December. The most notable changes in Wd are seen in June. The results also show that significant wave height (Hs) and wave power (Wp) have significantly increased in September-December and decreased in June. For example, the September regional mean Hs has increased at a rate of 0.4%/year. In September-December, the local Ws increases seem to be the main driver for the Hs and Wp increases, but such southeast-ward direction is favored by increasing fetch as sea ice retreats. In September and December, the positive trend in both Ws and Hs has intensified in the 2001-2016. In June, however, the mean Wd and the changes therein also play an important role in the Hs changes, which are more affected by remotely generated waves.

scholarly journals Stilling and Recovery of the Surface Wind Speed Based on Observation, Reanalysis, and Geostrophic Wind Theory over China from 1960 to 2017

2020 ◽  
Vol 33 (10) ◽  
pp. 3989-4008 ◽  
Author(s):  
Zhengtai Zhang ◽  
Kaicun Wang
Keyword(s):  
Wind Speed ◽  
Decadal Variability ◽  
Surface Wind ◽  
Geostrophic Wind ◽  
Surface Wind Speed ◽  
Strong Wind ◽  
Wind Speeds ◽  
The North ◽  
Wind Theory ◽  
Weak Winds

AbstractSurface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.

Stilling and Recovery of the Surface Wind Speed Based on Observation, Reanalysis, and Geostrophic Wind Theory over China from 1960 to 2017

2020 ◽  
Author(s):  
Zhengtai Zhang ◽  
Kaicun Wang
Keyword(s):  
Wind Speed ◽  
Decadal Variability ◽  
Surface Wind ◽  
Geostrophic Wind ◽  
Surface Wind Speed ◽  
Strong Wind ◽  
Wind Speeds ◽  
The North ◽  
Wind Theory ◽  
Weak Winds

&lt;p&gt;Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of -0.24 m/s decade&lt;sup&gt;-1 &lt;/sup&gt;from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95&lt;sup&gt;th&lt;/sup&gt; and 5&lt;sup&gt;th&lt;/sup&gt; percentiles of monthly mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of -8 % decade&lt;sup&gt;-1&lt;/sup&gt; from 1960 to 2017, but weak wind showed an insignificant decreasing trend of -2 % decade&lt;sup&gt;-1&lt;/sup&gt;. GWS decreased with a significant trend of -3 % decade&lt;sup&gt;-1 &lt;/sup&gt;before the 1990s, during the 1990s, GWS increased with a trend of 3 % decade&lt;sup&gt;-1 &lt;/sup&gt;whereas SWS continued to decrease with a trend of 10 % decade&lt;sup&gt;-1&lt;/sup&gt;. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrended, both of SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability, and can not capture the decreasing trend of SWS either.&lt;/p&gt;

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