An Introduction to the Near–Real–Time QuikSCAT Data

2005 ◽  
Vol 20 (4) ◽  
pp. 476-493 ◽  
Author(s):  
Ross N. Hoffman ◽  
S. Mark Leidner
Keyword(s):  
Data Quality ◽  
Objective Function ◽  
Surface Wind ◽  
Heavy Rain ◽  
Ocean Surface ◽  
Wind Speeds ◽  
The North ◽  
Ocean Surface Winds ◽  
Low Wind Speeds ◽  
Meteorological Features

Abstract The NASA Quick Scatterometer (QuikSCAT) satellite carries the SeaWinds instrument, the first satellite-borne scanning radar scatterometer. QuikSCAT, which was launched on 19 June 1999, is designed to provide accurate ocean surface winds in all conditions except for moderate to heavy rain (i.e., except for vertically integrated rain rate >2.0 km mm h−1, the value used to tune the SeaWinds rain flag). QuikSCAT data are invaluable in providing high-quality, high-resolution winds to detect and locate precisely significant meteorological features and to produce accurate ocean surface wind analyses. QuikSCAT has an 1800-km-wide swath. A representative swath of data in the North Atlantic at 2200 UTC 28 September 2000, which contains several interesting features, reveals some of the capabilities of QuikSCAT. Careful quality control is vital for flagging data that are affected by rain and for flagging errors during ambiguity removal. In addition, an understanding of the instrument and algorithm characteristics provides insights into the factors controlling data quality for QuikSCAT. For example data quality is reduced for low wind speeds, and for locations either close to nadir or to the swath edges. The special data characteristics of the QuikSCAT scatterometer are revealed by examining the likelihood or objective function. The objective function is equal to the sum of squared scaled differences between observed and simulated normalized reflected radar power. The authors present typical examples and discuss the associated data quality concerns for different parts of the swath, for different wind speeds, and for rain versus no rain.

Influence of Assimilating CYGNSS Ocean Surface Wind Data on Tropical Cyclone Analyses and Predictions

2020 ◽  
Author(s):  
Bachir Annane ◽  
Mark Leidner ◽  
Ross Hoffman ◽  
Feixiong Huang ◽  
James Garrisson
Keyword(s):  
Tropical Cyclones ◽  
Surface Wind ◽  
Ocean Surface ◽  
Convective Precipitation ◽  
Weather Research And Forecasting ◽  
Wind Speeds ◽  
Ocean Surface Winds ◽  
Ocean Surface Wind ◽  
The Impact ◽  
Hwrf Model

<div> <div><em>For the analysis and forecasting of tropical cyclones, the main benefits of data from the CYGNSS constellation of satellites are the increased revisit frequency compared with polar-orbiting satellites and the ability to provide ocean surface wind observations through convective precipitation. Consequently, CYGNSS delivers an improved capability to observe the structure and evolution of ocean surface winds in and around tropical cyclones. This study quantifies the impact of assimilating CYGNSS delay-Doppler maps, CYGNSS retrieved wind speeds and derived CYGNSS wind vectors on 6-hourly analyses and 5-day forecasts of developing tropical cyclones, using the 2019 version of NOAA's operational Hurricane Weather Research and Forecasting (HWRF) model.</em></div> </div>

scholarly journals Error Estimates for Ocean Surface Winds: Applying Desroziers Diagnostics to the Cross-Calibrated, Multiplatform Analysis of Wind Speed

2013 ◽  
Vol 30 (11) ◽  
pp. 2596-2603 ◽  
Author(s):  
Ross N. Hoffman ◽  
Joseph V. Ardizzone ◽  
S. Mark Leidner ◽  
Deborah K. Smith ◽  
Robert Atlas
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Speed Error ◽  
Ocean Surface Winds ◽  
Remote Sensing Systems ◽  
Standard Deviations ◽  
The Cross

Abstract The Desroziers diagnostics (DD) are applied to the cross-calibrated, multiplatform (CCMP) ocean surface wind datasets to estimate wind speed errors of the ECMWF background, the microwave satellite observations, and the resulting CCMP analysis. The DD confirm that the ECMWF operational surface wind speed error standard deviations vary with latitude in the range 0.8–1.3 m s−1 and that the cross-calibrated Remote Sensing Systems (RSS) wind speed retrievals’ standard deviations are in the range 0.5–0.7 m s−1. Further, the estimated CCMP analysis wind speed standard deviations are in the range 0.2–0.3 m s−1. The results suggest the need to revise the parameterization of the errors of the first guess at appropriate time (FGAT) procedure. Errors for wind speeds <16 m s−1 are homogeneous; however, for the relatively rare but critical higher wind speed situations, errors are much larger.

scholarly journals The relationship between some meteorological parameters and the tropospheric concentrations of ozone in the urban area of Belgrade

2005 ◽  
Vol 70 (12) ◽  
pp. 1487-1495 ◽  
Author(s):  
Dragan Markovic ◽  
Dragan Markovic
Keyword(s):  
Meteorological Parameters ◽  
Wind Speeds ◽  
Ozone Concentrations ◽  
The North ◽  
Measuring Site ◽  
Ozone Transport ◽  
Photochemical Ozone ◽  
Low Wind Speeds ◽  
The Relationship ◽  
Tropospheric Concentrations

During the period between June and December 2002, the concentrations of ozone in the air at 4 measuring sites in Belgrade were measured. The measuring periods varied from 10 days to several weeks. The maximal measured daily concentrations of ozone ranged from 19ppbv (23 December 2002) to 118ppbv (23 June 2002).Ozone concentrations higher than, or equal to 90ppbv were registered at three measuring sites. It was shown that at measuring sites characterized as urban, maximal O3 concentrations equal to, or higher than 90ppbv occurred at high temperatures (higher than 30?C) and low wind speeds (mostly from the north). The measured ozone concentrations mostly showed characteristics usual for a daily photochemical ozone cycle, excluding the specificities influenced by the measuring site itself. Ozone transport was recorded at increased wind speeds, primarily from south-easterly directions. On the basis of he correlations between ozone concentration and the corresponding meteorological parameters, a validation of the measuring sites was performed from the aspect of their representativeness for the measurements.

Near-surface wind speeds in ERA5: Climatology, decadal variability and long-term trends

2021 ◽  
Author(s):  
Terhi K. Laurila ◽  
Victoria A. Sinclair ◽  
Hilppa Gregow
Keyword(s):  
Iberian Peninsula ◽  
North Atlantic ◽  
Decadal Variability ◽  
Surface Wind ◽  
Northern Europe ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

<p>The knowledge of long-term climate and variability of near-surface wind speeds is essential and widely used among meteorologists, climate scientists and in industries such as wind energy and forestry. The new high-resolution ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will likely be used as a reference in future climate projections and in many wind-related applications. Hence, it is important to know what is the mean climate and variability of wind speeds in ERA5.</p><p>We present the monthly 10-m wind speed climate and decadal variability in the North Atlantic and Europe during the 40-year period (1979-2018) based on ERA5. In addition, we examine temporal time series and possible trends in three locations: the central North Atlantic, Finland and Iberian Peninsula. Moreover, we investigate what are the physical reasons for the decadal changes in 10-m wind speeds.</p><p>The 40-year mean and the 98th percentile wind speeds show a distinct contrast between land and sea with the strongest winds over the ocean and a seasonal variation with the strongest winds during winter time. The winds have the highest values and variabilities associated with storm tracks and local wind phenomena such as the mistral. To investigate the extremeness of the winds, we defined an extreme find factor (EWF) which is the ratio between the 98th percentile and mean wind speeds. The EWF is higher in southern Europe than in northern Europe during all months. Mostly no statistically significant linear trends of 10-m wind speeds were found in the 40-year period in the three locations and the annual and decadal variability was large.</p><p>The windiest decade in northern Europe was the 1990s and in southern Europe the 1980s and 2010s. The decadal changes in 10-m wind speeds were largely explained by the position of the jet stream and storm tracks and the strength of the north-south pressure gradient over the North Atlantic. In addition, we investigated the correlation between the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO) in the three locations. The NAO has a positive correlation in the central North Atlantic and Finland and a negative correlation in Iberian Peninsula. The AMO correlates moderately with the winds in the central North Atlantic but no correlation was found in Finland or the Iberian Peninsula. Overall, our study highlights that rather than just using long-term linear trends in wind speeds it is more informative to consider inter-annual or decadal variability.</p>

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 The use of reflected GPS signals to retrieve ocean surface wind speeds in tropical cyclones

Radio Science ◽  
2013 ◽  
Vol 48 (4) ◽  
pp. 371-387 ◽  
Author(s):  
Stephen J. Katzberg ◽  
Jason Dunion ◽  
George G. Ganoe
Keyword(s):  
Tropical Cyclones ◽  
Surface Wind ◽  
Ocean Surface ◽  
Wind Speeds ◽  
Ocean Surface Wind

scholarly journals A Surface Wind Extremes (“Wind Lulls” and “Wind Blows”) Climatology for Central North America and Adjoining Oceans (1979–2012)

2015 ◽  
Vol 54 (3) ◽  
pp. 643-657 ◽  
Author(s):  
Jonny W. Malloy ◽  
Daniel S. Krahenbuhl ◽  
Chad E. Bush ◽  
Robert C. Balling ◽  
Michael M. Santoro ◽  
...  
Keyword(s):  
United States ◽  
North America ◽  
North American ◽  
North Atlantic Ocean ◽  
Grid Point ◽  
Surface Wind ◽  
Wind Speeds ◽  
The North ◽  
Anomalous Wind

AbstractThis study explores long-term deviations from wind averages, specifically near the surface across central North America and adjoining oceans (25°–50°N, 60°–130°W) for 1979–2012 (408 months) by utilizing the North American Regional Reanalysis 10-m wind climate datasets. Regions where periods of anomalous wind speeds were observed (i.e., 1 standard deviation below/above both the long-term mean annual and mean monthly wind speeds at each grid point) were identified. These two climatic extremes were classified as wind lulls (WLs; below) or wind blows (WBs; above). Major findings for the North American study domain indicate that 1) mean annual wind speeds range from 1–3 m s−1 (Intermountain West) to over 7 m s−1 (offshore the East and West Coasts), 2) mean durations for WLs and WBs are high for much of the southeastern United States and for the open waters of the North Atlantic Ocean, respectively, 3) the longest WL/WB episodes for the majority of locations have historically not exceeded 5 months, 4) WLs and WBs are most common during June and October, respectively, for the upper Midwest, 5) WLs are least frequent over the southwestern United States during the North American monsoon, and 6) no significant anomalous wind trends exist over land or sea.

scholarly journals Comparison of regional and global reanalysis near-surface winds with station observations over Germany

2015 ◽  
Vol 12 (1) ◽  
pp. 187-198 ◽  
Author(s):  
A. K. Kaiser-Weiss ◽  
F. Kaspar ◽  
V. Heene ◽  
M. Borsche ◽  
D. G. H. Tan ◽  
...  
Keyword(s):  
Information Source ◽  
Surface Wind ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Energy Applications ◽  
The North ◽  
Independent Observations ◽  
Spatio Temporal ◽  
The North Atlantic Oscillation

Abstract. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications. Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). In this period, the station time series in Germany can be expected to be mostly homogeneous. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations. We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.

scholarly journals CYGNSS Ocean Surface Wind Validation in the Tropics

2020 ◽  
Author(s):  
Shakeel Asharaf ◽  
Duane E. Waliser ◽  
Derek J. Posselt ◽  
Christopher S. Ruf ◽  
Chidong Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Cold Pool ◽  
Tropical Ocean ◽  
Near Surface ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
Global Navigation Satellite

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.

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