WiSED: A Quality-Controlled Surface Wind European Database

2020 ◽  
Author(s):  
Cristina Rojas-Labanda ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
Jorge Navarro ◽  
Etor E. Lucio-Eceiza ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Storage ◽  
Measurement Errors ◽  
Climate Model ◽  
Surface Wind ◽  
Added Value ◽  
European Database ◽  
Spatial Coverage ◽  
Wind Behaviour ◽  
Three Phases

<p>Surface wind is a fundamental meteorological variable that is relevant for a wide array of topics (e.g., crop growth, extreme events, power generation). Yet, for many regions, there is still a scarcity of good quality observational datasets and the uncertainties within data sources like reanalysis products and between those and observational databases are large, limiting the understanding of this variable and hampering the accuracy of subsequent analyses.</p><p>In order to address this need and within the frame of the NEWA's (New European Wind Atlas) project, a quality-controlled Wind Surface European Database (WiSED) is created. WiSED feeds from eight different datasets, provided by different institutions and with varying levels of quality control. This initial version is then submitted to a Quality Control (QC) process structured into six phases that deal with the detection of various issues in data quality: 1) compilation; 2) duplication errors; 3) physical consistency in the ranges of recorded values; 4) temporal consistency, regarding abnormally high/low variability in the time series; 5) detection of medium-term biases; and 6) removal of isolated records. The first three phases deal with issues often related to data storage and management, whereas the last three phases deal with measurement errors related to problems in the instruments, calibration procedures or siting.</p><p>The improved quality of the data and the high temporal and spatial resolution, as well as its spatial coverage, represents an added value over previous products available for the same region. </p><p>This work summarises the application of the quality control, showing the results of different steps throughout it. Additionally, a preliminary analysis of the surface wind behaviour over Europe is presented.</p><p>With a maximum timespan of about 100 years, the creation of such database will allow for analyzing different aspects of both wind speed and direction variability over Europe from intra-daily to multidecadal timescales. Within the potentially relevant applications, it is worth to mention: the identification of subregions in Europe with homogeneous wind behaviour (regionalization), statistical downscaling exercises, analyses of wind extremes, wind power assessment and evaluation of climate model, both global and regional, simulations.</p>

Midlatitude cyclones in convection permitting climate simulations: the added value offered for extreme wind speeds and sting-jets

2021 ◽  
Author(s):  
Colin Manning ◽  
Elizabeth Kendon ◽  
Hayley Fowler ◽  
Nigel Roberts ◽  
Segolene Berthou ◽  
...  
Keyword(s):  
Climate Model ◽  
Surface Wind ◽  
Added Value ◽  
Large Contribution ◽  
High Wind ◽  
Wind Speeds ◽  
Wind Gusts ◽  
Climate Simulations ◽  
Extreme Wind ◽  
Extreme Wind Speeds

<p>Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a phenomenon known as a sting-jet account for some of the most damaging storms. A sting-jet (SJ) is a mesoscale core of high wind speeds that occurs in particular types of cyclones, specifically Shapiro-Keyser (SK) cyclones, and can produce extremely damaging surface wind gusts. High-resolution climate models are required to adequately model SJs and so it is difficult to gauge their contribution to current and future wind risk. In this study, we develop a low-cost methodology to automate the detection of sting jets, using the characteristic warm seclusion of SK cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations. Following this, we quantify the contribution of such storms to wind risk in Northern Europe in current and future climate simulations, and secondly assess the added value offered by the CPM compared to a traditional coarse-resolution climate model. This presentation will give an overview of the developed methods and the results of our analysis.</p><p>Comparing with observations, we find that the representation of wind gusts is improved in the CPM compared to ERA-Interim reanalysis data. Storm severity metrics indicate that SK cyclones account for the majority of the most damaging windstorms. The future simulation produces a large increase (>100%) in the number of storms exceeding high thresholds of the storm metric, with a large contribution to this change (40%) coming from windstorms in which a sting-jet is detected. Finally, we see a systematic underestimation in the GCM compared to the CPM in the frequency of extreme wind speeds at 850hPa in the cold sector of cyclones, likely related to better representation of sting-jets and the cold conveyor belt in the CPM. This underestimation is between 20-40% and increases with increasing wind speed above 35m/s. We conclude that the CPM adds value in the representation of severe surface wind gusts, providing more reliable future projections and improved input for impact models.</p>

Assessing Sting-Jets in Convection-Permitting Climate Simulations

2020 ◽  
Author(s):  
Colin Manning ◽  
Elizabeth Kendon ◽  
Hayley Fowler ◽  
Nigel Roberts ◽  
Ségolène Berthou
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Surface Wind ◽  
Severity Index ◽  
Added Value ◽  
Reanalysis Dataset ◽  
Objective Indicator ◽  
Wind Speeds ◽  
Climate Simulations ◽  
Strong Winds

<p>This study assesses the added-value offered by a regional convection-permitting climate model (CPM) in its representation of sting-jets (SJs); a mesoscale slanted core of strong winds within a Shapiro-Keyser type of cyclone that can lead to extremely damaging surface wind speeds close to southern side of a cyclone’s centre. Low-resolution climate models cannot resolve SJs, and so estimates of risk posed by extreme winds due to SJs are difficult to determine and will likely be underestimated in coarse-resolution climate simulations.</p><p>We analyse three 10-year simulations from the UK Met Office, run at a 2.2km resolution over a European domain. The simulations include a hindcast driven by the ERA-Interim reanalysis dataset (ERAI) for the period 2001-2010, as well as a present day (2001-2010) and future simulation (2100-2109) that follows the RCP8.5 scenario. Both climate simulations are driven by a 25km GCM. To diagnose potential SJ storms in each simulation, we firstly identify cyclone tracks with a cyclone tracking algorithm and apply an objective indicator that identifies the warm seclusion of a Shapiro-Keyser cyclone and the slanted core of strong winds of the sting-jet.</p><p>Within this presentation, we will present the objective indicator as well as results of the added value seen in the CPM. In order to identify any added value of the CPM, we analyse differences between the CPM and its respective driving data, in terms of storm severity metrics and their future projections.  An example metric used is the Storm Severity Index that quantifies the overall severity of a storm. In all simulations, the conditional PDF of SSI for sting-jet storms is shifted towards higher values compared to PDF of the SSI from all storms within the studied domain. However, we see little difference in the SSI derived from the CPM and its respective driving model/reanalysis when CPM wind speeds are upscaled to the respective driving reanalysis/GCM grid. In further analysis, we will look to explore the added value at a local scale on the native CPM grid.</p>

scholarly journals Quality Control of Surface Wind Observations in Northeastern North America. Part I: Data Management Issues

2018 ◽  
Vol 35 (1) ◽  
pp. 163-182 ◽  
Author(s):  
Etor E. Lucio-Eceiza ◽  
J. Fidel González-Rouco ◽  
Jorge Navarro ◽  
Hugo Beltrami
Keyword(s):  
Quality Control ◽  
Wind Speed ◽  
North America ◽  
Data Management ◽  
Wind Direction ◽  
Measurement Errors ◽  
Surface Wind ◽  
Error Type ◽  
Northeastern North America ◽  
Management Issues

AbstractA quality control (QC) process has been developed and implemented on an observational database of surface wind speed and direction in northeastern North America. The database combines data from 526 land stations and buoys spread across eastern Canada and five adjacent northeastern U.S. states. It combines the observations of three different institutions spanning from 1953 to 2010. The quality of these initial data varies among source institutions. The current QC process is divided into two parts. Part I, described herein, is focused on issues related to data management: issues stemming from data transcription and collection; differences in measurement units and recording times; detection of sequences of duplicated data; unification of calm and true north criteria for wind direction; and detection of physically unrealistic data measurements. As a result, around ~0.1% of wind speed and wind direction records have been identified as erroneous and deleted. The most widespread error type is related to duplications within the same station, but the error type that entails more erroneous data belongs to duplications among different sites. Additionally, the process of data compilation and standardization has had an impact on more than 90% of the records. A companion paper (Part II) deals with a group of errors that are conceptually different, and is focused on detecting measurement errors that relate to temporal consistency and biases in wind speed and direction.

scholarly journals Quality Control of Surface Wind Observations in Northeastern North America. Part II: Measurement Errors

2018 ◽  
Vol 35 (1) ◽  
pp. 183-205 ◽  
Author(s):  
Etor E. Lucio-Eceiza ◽  
J. Fidel González-Rouco ◽  
Jorge Navarro ◽  
Hugo Beltrami ◽  
Jorge Conte
Keyword(s):  
Quality Control ◽  
Wind Speed ◽  
North America ◽  
Wind Direction ◽  
Measurement Errors ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Eastern Canada ◽  
Error Type ◽  
Northeastern North America

AbstractA quality control (QC) process has been developed and applied to an observational database of surface wind speed and wind direction in northeastern North America. The database combines data from three datasets of different initial quality, including a total of 526 land stations and buoys distributed over the provinces of eastern Canada and five adjacent northeastern U.S. states. The data span from 1953 to 2010. The first part of the QC deals with data management issues and is developed in a companion paper. Part II, presented herein, is focused on the detection of measurement errors and deals with low-variability errors, like the occurrence of unrealistically long calms, and high-variability problems, like rapid changes in wind speed; some types of biases in wind speed and wind direction are also considered. About 0.5% (0.16%) of wind speed (wind direction) records have been flagged. Additionally, 15.87% (1.73%) of wind speed (wind direction) data have been corrected. The most pervasive error type in terms of affected sites and erased data corresponds to unrealistic low wind speeds (89% of sites affected with 0.35% records removed). The amount of detected and corrected/removed records in Part II (~9%) is approximately two orders of magnitude higher than that of Part I. Both management and measurement errors are shown to have a discernible impact on the statistics of the database.

scholarly journals Assessing Past Climate Biases and the Added Value of CORDEX-CORE Precipitation Simulations over Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2058
Author(s):  
Gnim Tchalim Gnitou ◽  
Guirong Tan ◽  
Ruoyun Niu ◽  
Isaac Kwesi Nooni
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Spatial Coverage ◽  
Wide Range

The present study investigates the skills of CORDEX-CORE precipitation outputs in simulating Africa’s key seasonal climate features, emphasizing the added value (AV) of the dynamical downscaling approach from which they were derived. The results indicate the models’ good skills in capturing African rainfall patterns and dynamics at satellite-based observation resolutions, with up to 65.17% significant positive AV spatial coverage for the CCLM5 model and up to 55.47% significant positive AV spatial coverage for the REMO model. Unavoidable biases are however present in rainfall-abundant areas and are reflected in the AV results, but vary based on the season, the sub-area, and the Global Climate Model–Regional Climate Models (GCM-RCM) combination considered. The RCMs’ ensemble mean generally performs better than individual GCM–RCM simulations. A further analysis of the GCM–RCM model chain indicates a strong influence of the dynamical downscaling approach on the driving GCMs. However, exceptions are found in some seasons for specific RCMs’ outputs, where GCMs are influential. The findings also revealed that observational uncertainties can influence AV and contribute to a 6 to 34% difference in significant positive AV spatial coverage results. An analysis of these results suggests that the AV by CORDEX-CORE simulations over Africa depend on how well the GCM physics are integrated to those of the RCMs and how these features are accommodated in the high-resolution setting of the downscaling experiments. The deficiencies of the CORDEX-CORE simulations could be related to how well key processes are represented within the RCM models. For Africa, these results show that CORDEX-CORE products could be adequate for a wide range of high-resolution precipitation data applications.

scholarly journals The Driving Mechanisms on Southern Ocean Upwelling Change during the Last Deglaciation

Geosciences ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 266
Author(s):  
Wei Liu ◽  
Zhengyu Liu ◽  
Shouwei Li
Keyword(s):  
Southern Ocean ◽  
Climate Model ◽  
Model Simulation ◽  
Early Stage ◽  
Surface Wind ◽  
Ekman Pumping ◽  
Last Deglaciation ◽  
Buoyancy Forcing ◽  
Local Topography ◽  
The Last Deglaciation

We explore the change in Southern Ocean upwelling during the last deglaciation, based on proxy records and a transient climate model simulation. Our analyses suggest that, beyond a conventional mechanism of the Southern Hemisphere westerlies shift, Southern Ocean upwelling is strongly influenced by surface buoyancy forcing and the local topography. Over the Antarctic Circumpolar Current region, the zonal mean and local upwelled flows exhibited distinct evolution patterns during the last deglaciation, since they are driven by different mechanisms. The zonal mean upwelling is primarily driven by surface wind stress via zonal mean Ekman pumping, whereas local upwelling is driven by both wind and buoyancy forcing, and is tightly coupled to local topography. During the early stage of the last deglaciation, the vertical extension of the upwelled flows increased downstream of submarine ridges but decreased upstream, which led to enhanced and diminished local upwelling, downstream and upstream of the submarine ridges, respectively.

An Assessment of Observed and Simulated Temperature Variability in Sierra de Guadarrama (Spain)

2021 ◽  
Author(s):  
Cristina Vegas Cañas ◽  
J. Fidel González Rouco ◽  
Jorge Navarro Montesinos ◽  
Elena García Bustamante ◽  
Etor E. Lucio Eceiza ◽  
...  
Keyword(s):  
Western Europe ◽  
Climate Model ◽  
Regional Climate ◽  
Monitoring Network ◽  
Horizontal Resolution ◽  
Temperature Variability ◽  
Added Value ◽  
Seasonal Temperature ◽  
Temperature Trends ◽  
Highly Correlated

<p>This work provides a first assessment of temperature variability from interannual to multidecadal timescales in Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes, up to 2225 masl, and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at high altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.</p><p>The analysis of temperature trends shows a warming in the area during the last 20 years, very significant in autumn. When spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of 1℃/decade develop, most of them happening during de 1970s, although not as intense as during the last 20 years.</p><p>The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.</p>

On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

2017 ◽  
Vol 49 (11-12) ◽  
pp. 3813-3838 ◽  
Author(s):  
Thierry C. Fotso-Nguemo ◽  
Derbetini A. Vondou ◽  
Wilfried M. Pokam ◽  
Zéphirin Yepdo Djomou ◽  
Ismaïla Diallo ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Added Value ◽  
Climate Change Signal

scholarly journals Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 262 ◽  
Author(s):  
Coraline Wyard ◽  
Sébastien Doutreloup ◽  
Alexandre Belleflamme ◽  
Martin Wild ◽  
Xavier Fettweis
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Radiative Flux ◽  
Added Value ◽  
Historical Trends ◽  
The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

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