Challenges in developing a high-quality surface wind-speed data-set for Australia

AbstractWe have developed C-band compact polarimetry geophysical model functions for RADARSAT Constellation Mission ocean surface wind speed retrieval. A total of 1594 RADARSAT-2 images acquired in quad-polarization SAR imaging mode were collocated with in situ buoy observations. This data set is first used to simulate compact polarimetric data and to examine their dependencies on radar incidence angle and wind vectors. We find that RR-pol radar backscatters are less sensitive to incidence angles and wind directions but are more dependent on wind speeds, compared to RH-, RV-, and RL-pol. Subsequently, the matchup data pairs are used to derive the coefficients of the transfer functions for the proposed compact polarimetric geophysical model functions, and to validate the associated wind speed retrieval accuracy. Statistical comparisons show that the retrieved wind speeds from CMODRH, CMODRV, CMODRL, CMODRR are in good agreement with buoy measurements, with root mean square errors of 1.38, 1.51, 1.47, 1.25 m/s, respectively. The results suggest that compact polarimetry is a good alternative to linear polarization for wind speed retrieval. CMODRR is more appropriate to retrieve high wind speeds than CMODRH, CMODRV or CMODRL.

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Deterministic prediction of surface wind speed variations

Annales Geophysicae ◽

10.5194/angeo-32-1415-2014 ◽

2014 ◽

Vol 32 (11) ◽

pp. 1415-1425 ◽

Cited By ~ 4

Author(s):

G. V. Drisya ◽

D. C. Kiplangat ◽

K. Asokan ◽

K. Satheesh Kumar

Keyword(s):

Wind Speed ◽

Arima Model ◽

Surface Wind ◽

Surface Wind Speed ◽

Temporal Variations ◽

Short Term ◽

Deterministic Models ◽

Wind Speed Data ◽

Wind Speeds ◽

Past Data

Abstract. Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error) of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

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Impact studies of AMSR-E ocean surface wind speed data in NWP at JMA

2009 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2009.5418214 ◽

2009 ◽

Author(s):

Masahiro Kazumori

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Ocean Surface ◽

Surface Wind Speed ◽

Wind Speed Data ◽

Impact Studies ◽

Ocean Surface Wind

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Impact of Assimilating CYGNSS Data on Tropical Cyclone Analyses and Forecasts in a Regional OSSE Framework

Marine Technology Society Journal ◽

10.4031/mtsj.51.1.1 ◽

2017 ◽

Vol 51 (1) ◽

pp. 7-15 ◽

Cited By ~ 11

Author(s):

Brian McNoldy ◽

Bachir Annane ◽

Sharanya Majumdar ◽

Javier Delgado ◽

Lisa Bucci ◽

...

Keyword(s):

Wind Speed ◽

Large Scale ◽

Surface Wind ◽

Ocean Surface ◽

Surface Wind Speed ◽

Satellite System ◽

Directional Information ◽

Wind Speed Data ◽

Ocean Surface Wind ◽

The Impact

AbstractThe impact of assimilating ocean surface wind observations from the Cyclone Global Navigation Satellite System (CYGNSS) is examined in a high-resolution Observing System Simulation Experiment (OSSE) framework for tropical cyclones (TCs). CYGNSS is a planned National Aeronautics and Space Administration constellation of microsatellites that utilizes existing GNSS satellites to retrieve surface wind speed. In the OSSE, CYGNSS wind speed data are simulated using output from a “nature run” as truth. In a case study using the regional Hurricane Weather Research and Forecasting modeling system and the Gridpoint Statistical Interpolation data assimilation scheme, analyses of TC position, structure, and intensity, together with large-scale variables, are improved due to the assimilation of the additional surface wind data. These results indicate the potential importance of CYGNSS ocean surface wind speed data and furthermore that the assimilation of directional information would add further value to TC analyses and forecasts.

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Construction of long-term data set of sea surface wind speed/stress vectors by continuous satellite observations

International Journal of Remote Sensing ◽

10.1080/01431161.2015.1137991 ◽

2016 ◽

Vol 37 (9) ◽

pp. 2032-2046 ◽

Cited By ~ 2

Author(s):

Suguru Kameda ◽

Kunio Kutsuwada

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Satellite Observations ◽

Sea Surface ◽

Data Set ◽

Sea Surface Wind Speed ◽

Sea Surface Wind ◽

Term Data

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Estimation of Ocean Surface Wind Speed and Direction From Polarimetric Radiometry Data

10.21236/ada533831 ◽

2008 ◽

Author(s):

David R. Lyzenga

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Ocean Surface ◽

Surface Wind Speed ◽

Ocean Surface Wind

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Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.599-601.1605 ◽

2014 ◽

Vol 599-601 ◽

pp. 1605-1609 ◽

Cited By ~ 1

Author(s):

Ming Zeng ◽

Zhan Xie Wu ◽

Qing Hao Meng ◽

Jing Hai Li ◽

Shu Gen Ma

Keyword(s):

Wind Speed ◽

Surface Wind ◽

Surface Wind Speed ◽

Recurrence Plot ◽

Sampling Frequency ◽

Near Surface ◽

Gas Leakage ◽

Time Period ◽

Characteristics Analysis ◽

Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

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Large-Scale and Deep-Seated Gravitational Slope Deformations on Mars: A Review

Geosciences ◽

10.3390/geosciences11040174 ◽

2021 ◽

Vol 11 (4) ◽

pp. 174

Author(s):

Marco Emanuele Discenza ◽

Carlo Esposito ◽

Goro Komatsu ◽

Enrico Miccadei

Keyword(s):

Large Scale ◽

High Quality ◽

Surface Data ◽

Geomorphological Processes ◽

Gravitational Processes ◽

Quality Surface ◽

High Quality Surface ◽

Mars Missions

The availability of high-quality surface data acquired by recent Mars missions and the development of increasingly accurate methods for analysis have made it possible to identify, describe, and analyze many geological and geomorphological processes previously unknown or unstudied on Mars. Among these, the slow and large-scale slope deformational phenomena, generally known as Deep-Seated Gravitational Slope Deformations (DSGSDs), are of particular interest. Since the early 2000s, several studies were conducted in order to identify and analyze Martian large-scale gravitational processes. Similar to what happens on Earth, these phenomena apparently occur in diverse morpho-structural conditions on Mars. Nevertheless, the difficulty of directly studying geological, structural, and geomorphological characteristics of the planet makes the analysis of these phenomena particularly complex, leaving numerous questions to be answered. This paper reports a synthesis of all the known studies conducted on large-scale deformational processes on Mars to date, in order to provide a complete and exhaustive picture of the phenomena. After the synthesis of the literature studies, the specific characteristics of the phenomena are analyzed, and the remaining main open issued are described.

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