The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Lars Norin - One of the best experts on this subject based on the ideXlab platform.
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The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather Radar network
Atmospheric Measurement Techniques, 2014Co-Authors: Abhay Devasthale, Lars NorinAbstract:Abstract. Using measurements from the national network of 12 weather Radar Stations for the 11-year period 2000–2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the Radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate- to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of Radar Stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all Radar Stations. Apart from its operational applications, the present study demonstrates the potential of the weather Radar data set for studying climatic features of precipitation over Sweden.
Abhay Devasthale - One of the best experts on this subject based on the ideXlab platform.
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The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather Radar network
Atmospheric Measurement Techniques, 2014Co-Authors: Abhay Devasthale, Lars NorinAbstract:Abstract. Using measurements from the national network of 12 weather Radar Stations for the 11-year period 2000–2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the Radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate- to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of Radar Stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all Radar Stations. Apart from its operational applications, the present study demonstrates the potential of the weather Radar data set for studying climatic features of precipitation over Sweden.
Weili Wang - One of the best experts on this subject based on the ideXlab platform.
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Inversion and assessment of swell waveheights from HF Radar spectra in the Iroise Sea
Ocean Dynamics, 2016Co-Authors: Weili Wang, Philippe Forget, Changlong GuanAbstract:As an extension of previous work in Wang et al. (Ocean Dyn 64:1447-1456, 2014), this article presents significant waveheights of swell inverted from a 13 month dataset of two high-frequency (HF) phased array Radars. As an important intermediate variable in the calculation of significant waveheights, relative swell directions obtained by two different methods from a single Radar station are also presented. The impact of the inaccuracy of relative swell direction on the calculation of waveheight is investigated and an alternative way of using constant swell direction is proposed. Radar-inverted swell significant waveheights using different ranges of relative swell directions are investigated. Results are assessed by WAVEWATCH III model hind casts. Analysis of the complete database shows that Radar-inverted swell significant waveheights agree reasonably well with model estimates with large scatter. Standard deviation of the difference between the two estimations increases with waveheight, whereas the relative standard deviation, normalized by waveheight, keeps nearly constant. The constant direction scheme of waveheight inversion gives good estimations except for energetic swell exceeding the small perturbation assumption. Statistical analysis suggests that Radar measurement uncertainty explains a considerable part of the difference between Radar and model estimates. Swell estimates from both Radar Stations are consistent. This enables combined use of both Radar spectra at common Radar cells. Use of double spectra solves the ambiguity of relative swell direction, i.e., absolute swell direction is obtained, and effectively improves the accuracy of swell direction by the least-squares method.
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Remote sensing of swell and currents in coastal zone by HF Radar
2015Co-Authors: Weili WangAbstract:Nearshore marine environment contains many complex processes, but the lack of high-resolution data over a large area during a long time is often the primary obstacle to further research. High-frequency (HF) Radar is a mean of remote sensing which obtains continuous near-real time sea surface information over a large area. Thus the study of inversion of marine parameters from HF Radar data is very meaningful. Thisthesis makes use of a 13-month-long dataset collected by two phased array HF Radar to investigate the characteristics of the sea echo signals, study the data processing and inversion methods, compute sea surface parameters and evaluate the accuracy of Radarinversion of swell parameters.The thesis refers to the ground wave HF Radar, whose radio waves interact with ocean by Bragg resonance scattering. The development history and applications of HF Radar is introduced. The basic theory of electromagnetic wave is reviewed. The principles of inversion of sea surface current, wind direction and swell parameters are described. The feasibility of the swell parameter inversion is investigated. Based on theoretical analysis and statistical studies of a large number of samples, the thesis proposes a series of methods on raw signal processing and quality control, including the determination of the noise level, data averaging in space and time, the proper identification of spectral peaks, the peak width threshold, etc. Respecting the characteristics of different physical processes, inversions of current and wind use spectra collected every 20 min; inversion of swell parameters uses one-hour averaged spectra. The statistics of qualified spectra for swell parameter calculations are presented for both Stations. A set of efficient, with a reduced computational cost, automatic computing programs are developed to do the processing and derive marine parameters. Radial current velocities are derived from single Radar station. Current vector fields are obtained by combination of both Stations. One-year mean flow field in the Iroise Sea is shown, together with the computation of vorticity and divergence. A one-month SeaSonde Radar dataset off Qingdao is studied. One-month mean flow pattern together with vorticity and divergence are presented.Relative wind direction with respect to Radar look direction is measured through ratio of Bragg peaks amplitudes. Different empirical models are employed to derive Radar-inverted relative wind direction. Results show reasonable agreement with model estimations. Different directional distribution models are used to measure the spreading factor for the Iroise Sea. The thesis focuses on the study of swell parameters. Results are validated by buoy and wave model (WAVEWATCH III) data. The assessments show that the accuracy of swell frequency is very good, the accuracy of swell significant waveheight is reasonable, and the accuracy of relative swell direction is low.Consistency of measurements by both Radar Stations is verified by comparison between the two. This also supports the use of double samples to do the inversion. Use of two Radars not only further improves the accuracy but also solves the ambiguity of relative swell direction from single station and gives the absolute wave direction to a certain precision. The thesis proposes a constant relative directionmethod to derive swell significant waveheight, based on the studies of Radar integral equation and the inverted results of relative swell direction. This proposal is demonstrated to improve the agreement of Radar inversion and buoy/model provided significant waveheight and increases significantly the number of samples. The thesis investigates the accuracy of swell parameters obtained by HF Radar. Contributions of random errors in Radar observations are quantified. Comparing the differences between Radar and buoy/model estimations gives assessments of the contribution of Radar intrinsic uncertainty and contribution of other factors.
Changlong Guan - One of the best experts on this subject based on the ideXlab platform.
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Inversion and assessment of swell waveheights from HF Radar spectra in the Iroise Sea
Ocean Dynamics, 2016Co-Authors: Weili Wang, Philippe Forget, Changlong GuanAbstract:As an extension of previous work in Wang et al. (Ocean Dyn 64:1447-1456, 2014), this article presents significant waveheights of swell inverted from a 13 month dataset of two high-frequency (HF) phased array Radars. As an important intermediate variable in the calculation of significant waveheights, relative swell directions obtained by two different methods from a single Radar station are also presented. The impact of the inaccuracy of relative swell direction on the calculation of waveheight is investigated and an alternative way of using constant swell direction is proposed. Radar-inverted swell significant waveheights using different ranges of relative swell directions are investigated. Results are assessed by WAVEWATCH III model hind casts. Analysis of the complete database shows that Radar-inverted swell significant waveheights agree reasonably well with model estimates with large scatter. Standard deviation of the difference between the two estimations increases with waveheight, whereas the relative standard deviation, normalized by waveheight, keeps nearly constant. The constant direction scheme of waveheight inversion gives good estimations except for energetic swell exceeding the small perturbation assumption. Statistical analysis suggests that Radar measurement uncertainty explains a considerable part of the difference between Radar and model estimates. Swell estimates from both Radar Stations are consistent. This enables combined use of both Radar spectra at common Radar cells. Use of double spectra solves the ambiguity of relative swell direction, i.e., absolute swell direction is obtained, and effectively improves the accuracy of swell direction by the least-squares method.
I. Rodriguez-iturbe - One of the best experts on this subject based on the ideXlab platform.
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Spatial-temporal rainfall fields: modelling and statistical aspects
Hydrology and Earth System Sciences Discussions, 2000Co-Authors: H. S. Wheater, V. S. Isham, D. R. Cox, R. E. Chandler, A. Kakou, P. J. Northrop, C. Onof, I. Rodriguez-iturbeAbstract:The HYREX experiment has provided a data set unique in the UK, with a dense network of raingauges available for studying the rainfall at a fine local scale and a network of Radar Stations allowing detailed examination of the spatial and temporal structure of rainfall at larger scales. In this paper, the properties and characteristics of the rainfall process, as measured by the HYREX recording network of rainguages and Radars, are studied from a statistical perspective. The results of these analyses are used to develop various models of the rainfall process, for use in hydrological applications. Some typical results of these various modelling exercises are presented. Keywords: Rainfall statistics, rainfall models, hydrological design
