WRF Evaluation During Storm Ophelia Using Remote Sensing and In-situ Measurements at Mace Head, Ireland

Mapping Intimacies ◽

10.20944/preprints202109.0093.v1 ◽

2021 ◽

Author(s):

Clare Noone ◽

Jana Preißler

Keyword(s):

Remote Sensing ◽

Wind Speed ◽

Wind Direction ◽

Extreme Weather Events ◽

Research Station ◽

Preliminary Evaluation ◽

Major Power ◽

Simulated Wind ◽

Simulated Wind Speed

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

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Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations

Advances in Science and Research ◽

10.5194/asr-13-107-2016 ◽

2016 ◽

Vol 13 ◽

pp. 107-112 ◽

Cited By ~ 1

Author(s):

Anika Obermann ◽

Benedikt Edelmann ◽

Bodo Ahrens

Keyword(s):

Surface Roughness ◽

Wind Speed ◽

Wind Direction ◽

Roughness Length ◽

Western Mediterranean ◽

Sea Surface ◽

Surface Roughness Length ◽

Sea Surface Roughness ◽

Simulated Wind ◽

Simulated Wind Speed

Abstract. The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.

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H2020 SINOPTICA (Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM) project: initial results

10.5194/egusphere-egu21-891 ◽

2021 ◽

Author(s):

Antonio Parodi ◽

Marco Temme ◽

Olga Gluchshenko ◽

Markus Kerschbaum ◽

Nicola Surian ◽

...

Keyword(s):

Remote Sensing ◽

Traffic Management ◽

Wrf Model ◽

Weather Forecast ◽

Extreme Weather Events ◽

Weather Stations ◽

Occultation Data ◽

Nwp Model ◽

Initial Results

The H2020 SINOPTICA Project (2020-2022) aims at exploiting the untapped potential of assimilating remote sensing (EO-derived and ground-based radar) as well as GNSS-derived datasets (including radio occultation data) and in-situ weather stations data. Those data will be used for very high-resolution, very short-range numerical weather forecasts to improve the prediction of extreme weather events to the benefit of Air Traffic Management (ATM) operations. This will be done by setting up a continuously updated database of remote sensing-derived, GNSS-derived and in-situ weather stations variables, in combination with an automated assimilation system to feed an NWP model. SINOPTICA weather forecast results will be integrated into ATM decision-support tools, visualizing weather information on the controller's display, and generating new 4D trajectories to avoid severe weather areas. This contribution presents the initial results of the assimilation of aforementioned observations into the WRF model, operated at cloud-resolving grid spacing, for two case studies: a hailstorm event occured on 11 May 2019 nearby Malpensa airport and a severe convection episode occurred near Punta Raisi airport (Palermo) on 15 July 2020.

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The Large-eddy Observatory Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially-distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing

10.5194/essd-2020-392 ◽

2021 ◽

Author(s):

Karl Lapo ◽

Anita Freundorfer ◽

Antonia Fritz ◽

Johann Schneider ◽

Johannes Olesch ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Wind Speed ◽

Air Temperature ◽

Wind Direction ◽

Fiber Optic ◽

Layer Structure ◽

Distributed Sensing ◽

Near Surface ◽

Large Eddy

Abstract. The weak-wind Stable Boundary Layer (wwSBL) is poorly described by theory and breaks basic assumptions necessary for observations of turbulence. Understanding the wwSBL requires distributed observations capable of separating between submeso and turbulent scales. To this end, we present the Large Eddy Observatory, Voitsumra Experiment 2019 (LOVE19) which featured 1350 m of fiber optic distributed sensing (FODS) of air temperature and wind speed, as well as an experimental wind direction method, at scales as fine as 1 s and 0.127 m in addition to a suite of point observations of turbulence and ground-based remote sensing. Additionally, flights with a fiber optic cable attached to a tethered balloon provide an unprecedented detailed view of the boundary layer structure with a resolution of 0.254 m and 10 s between 1–200 m height. Two examples are provided demonstrating the unique capabilities of the LOVE19 data for examining boundary layer processes: 1) FODS observations between 1m and ~200 m height during a period of gravity waves propagating across the entire boundary layer and 2) tracking a near-surface, transient submeso structure that causes an intermittent burst of turbulence. All data can be accessed at Zenodo through the DOI https://doi.org/10.5281/zenodo.4312976 (Lapo et al., 2020a).

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Supplementing Oscat winds with Saral Altika observations for cyclone studies

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-1059-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 1059-1064 ◽

Cited By ~ 1

Author(s):

K. Niharika ◽

H. S. V. Usha Sundari ◽

A. V. V. Prasad ◽

E. V. S. Sita Kumari ◽

V. K. Dadhwal ◽

...

Keyword(s):

Remote Sensing ◽

Life Cycle ◽

Wind Speed ◽

Storm Surge ◽

Disaster Management ◽

Management Practices ◽

In Situ Observations ◽

Remote Sensing Techniques ◽

Microwave Sensors

Accurate prediction of life cycle of cyclone is very critical to the disaster management practices. Since the cyclones originate over the oceans where in situ observations are limited, we have to resort to the remote sensing techniques. Both optical and microwave sensors help studying the cyclones. While scatterometer provide wind vectors, altimeters can give only wind speed. In this paper we present how altimeter measurements can supplement the scatterometer observations in determining the radius of maximum winds (RMW). Sustained maximum winds, indicator for the intensity of the cyclone, are within the eye wall of a cyclone at a distance of RMW. This parameter is also useful in predicting right time of the storm surge. In this paper we used the wind speed estimations from AltiKa, an altimeter operating at Ka band.

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Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

Remote Sensing ◽

10.3390/rs10101655 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1655 ◽

Cited By ~ 4

Author(s):

Nariane Bernardo ◽

Enner Alcântara ◽

Fernanda Watanabe ◽

Thanan Rodrigues ◽

Alisson Carmo ◽

...

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Wind Speed ◽

In Situ Measurements ◽

Colored Dissolved Organic Matter ◽

The Third ◽

Sensing Applications ◽

Remote Sensing Reflectance ◽

Remote Sensing Applications

The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s−1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.

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Predicting Wind Speed for Wind Energy; Progress of the WINDENG Project

Wind Engineering ◽

10.1260/030952405775992616 ◽

2005 ◽

Vol 29 (5) ◽

pp. 393-408 ◽

Cited By ~ 5

Author(s):

Silke Dierer ◽

Tim de Paus ◽

Francesco Durante ◽

Erik Gregow ◽

Bernhard Lange ◽

...

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Dynamical Downscaling ◽

Atmospheric Stability ◽

Stable Stratification ◽

Average Wind Speed ◽

Geographical Regions ◽

Pbl Parameterization ◽

Simulated Wind ◽

Simulated Wind Speed

The suitability of the computer model MM5 for predicting wind speed, and hence wind energy, is investigated by performing simulations for different geographical regions. The focus is on wind speed in the lowest 200 m of the planetary boundary layer (PBL). The dependency of the simulated wind speed on PBL parameterization and atmospheric stability is studied. The smallest deviation between measured and simulated wind speed, averaged over a three-day period, is 1% and occurs for an off-shore simulation with unstable stratification. The largest deviations of 31% and 20% occur with orographically structured terrain, stable stratification and weak synoptic forcing. The results suggest that unstable conditions are simulated with better accuracy by MM5. Changes of the PBL scheme cause wind speed variations between 9% and 40% of the average wind speed. None of the PBL schemes is clearly the best and their performance can strongly vary for different conditions. Nevertheless, the Mellor-Yamada-Janjic (ETA) and the Blackadar PBL parameterization (BLK) schemes seem to be the most suitable schemes for wind energy applications. Additionally, MM5 was successfully adapted for idealised, stationary simulations in order to calculate a wind-climatology for Sardinia using a statistical-dynamical downscaling approach.

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1997–2007 CO trend at the high Alpine site Jungfraujoch: a comparison between NDIR surface in situ and FTIR remote sensing observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-6735-2011 ◽

2011 ◽

Vol 11 (13) ◽

pp. 6735-6748 ◽

Cited By ~ 15

Author(s):

B. Dils ◽

J. Cui ◽

S. Henne ◽

E. Mahieu ◽

M. Steinbacher ◽

...

Keyword(s):

Remote Sensing ◽

Sea Level ◽

Measurement Techniques ◽

Surface Concentration ◽

Infrared Spectrometry ◽

Research Station ◽

Strong Impact ◽

Solar Absorption ◽

Combining Data

Abstract. Within the atmospheric research community, there is a strong interest in integrated datasets, combining data from several instrumentations. This integration is complicated by the different characteristics of the datasets, inherent to the measurement techniques. Here we have compared two carbon monoxide time series (1997 till 2007) acquired at the high-Alpine research station Jungfraujoch (3580 m above sea level), with two well-established measurement techniques, namely in situ surface concentration measurements using Non-Dispersive Infrared Absorption technology (NDIR), and ground-based remote sensing measurements using solar absorption Fourier Transform Infrared spectrometry (FTIR). The profile information available in the FTIR signal allowed us to extract an independent layer with a top height of 7.18 km above sea level, appropriate for comparison with our in situ measurements. We show that, even if both techniques are able to measure free troposphere CO concentrations, the datasets exhibit marked differences in their overall trends (−3.21 ± 0.03 ppb year−1 for NDIR vs. −0.8 ± 0.4 ppb year−1 for FTIR). Removing measurements that are polluted by uprising boundary layer air has a strong impact on the NDIR trend (now −2.62 ± 0.03 ppb year−1), but its difference with FTIR remains significant. Using the LAGRANTO trajectory model, we show that both measurement techniques are influenced by different source regions and therefore are likely subject to exhibit significant differences in their overall trend behaviour. However the observation that the NDIR-FTIR trend difference is as significant before as after 2001 is at odds with available emission databases which claim a significant Asian CO increase after 2001 only.

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1997–2007 CO trend at the high Alpine site Jungfraujoch: a comparison between NDIR surface in situ and FTIR remote sensing observations

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-8977-2011 ◽

2011 ◽

Vol 11 (3) ◽

pp. 8977-9017

Author(s):

B. Dils ◽

J. Cui ◽

S. Henne ◽

E. Mahieu ◽

M. Steinbacher ◽

...

Keyword(s):

Remote Sensing ◽

Measurement Techniques ◽

Surface Concentration ◽

Infrared Spectrometry ◽

Research Station ◽

Solar Absorption ◽

Combining Data ◽

Alpine Research ◽

Different Characteristics

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CATDS CEC-LOCEAN debiased version 4 Sea Surface Salinity

10.5194/egusphere-egu2020-7545 ◽

2020 ◽

Author(s):

Clovis Thouvenin-Masson ◽

Jacqueline Boutin ◽

Jean-Luc Vergely ◽

Dimitry Khvorostyanov ◽

Stéphane Tarot

Keyword(s):

Remote Sensing ◽

Wind Speed ◽

Sea Surface ◽

Sea Surface Salinity ◽

Global Ocean ◽

Surface Salinity ◽

The Mean ◽

Analysis System ◽

Areas Of Interest

The Centre Aval de Traitement des Donn&#233;es SMOS (CATDS), developped by the CNES in collaboration with the CESBIO and IFREMER, produces and continuously improves SMOS sea surface salinity (SSS) products.The aim of this poster is to present the last version of CATDS L3 products developed by the LOCEAN CATDS Expertise Center (CEC-LOCEAN debiased v4, https://www.catds.fr/Products/Available-products-from-CEC-OS/CEC-Locean-L3-Debiased-v4), and to highlight its main improvements with respect to previous version 3.The L3 products are available for 9-day and 18-day Gaussian averaging. Both versions 3 and 4 contain a bias correction based on internal consistency of SMOS SSS retrieved in various locations across swath, and on seasonal variability of salinity. The main evolutions of version 4 consist in refining the absolute correction methodology, limiting wind speed to 16m/s, add a refined filtering for sea ice and radio frequency contamination based on SMOS retrieved pseudo dielectric constant, the so-called ACARD (Waldteufel et al. 2004) and an improved sea surface temperature (SST) correction in cold waters based on Dinnat et al. (2019) observed dependency.Improvements with respect to version 3 are assessed through systematic validation that consists in two main stages: (1) Comparison with respect to in-situ measurements (repetitive ship transects across Atlantic and Arctic regions, and Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) moorings); (2) Comparison with the In-Situ Analysis System (ISAS) monthly fields (Kolodziejczyk, 2017), in terms of both mean spatial maps and time series of key statistics parameters. The key statistics parameters are computed both over the global ocean and for individual areas of interest. Thus, both the mean spatial patterns and temporal variability in various regions are evaluated.Comparisons between the two last versions exposed in this poster are based on relevant examples from this systematic validation: main improvements are observed in high latitudes (over 45&#176; latitude).In the Southern Ocean modification of wind speed filtering and SST correction lead to a decrease in the mean difference between SMOS&#160; and ISAS SSS south of 45S from 0.16+/-0.07 to 0.02+/-0.05pss. Std of the differences and r2 are also improved over global ocean. Statistics obtained with this new version are close to the ones obtained with SMAP RemSS v4 SSS.&#160;Dinnat, E.P.; Le Vine, D.M.; Boutin, J.; Meissner, T.; Lagerloef, G. Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of Retrieval Parameters. Remote Sens. 2019, 11, 750.Kolodziejczyk Nicolas, Prigent-Mazella Annaig, Gaillard Fabienne (2017). ISAS-15 temperature and salinity gridded fields. SEANOE. https://doi.org/10.17882/52367Waldteufel, P., J. L. Vergely, and C. Cot, A modified cardioid model for Processing multiangular radiometric observations, IEEE Transactions on Geoscience and Remote Sensing, vol.42, issue.5, pp.1059-1063, 2004. DOI : 10.1109/TGRS.2003.821698.

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