ECMWF started assimilating wind data from the European Space Agency's ground-breaking Aeolus satellite operationally on 9 January 2020 after tests showed that they significantly improve weather forecasts. Aeolus was launched in August 2018 to test the usefulness of direct wind profile observations from space for numerical weather prediction. It works by measuring the backscatter of laser light from air molecules ('Rayleigh-clear' data) and from clouds and aerosols ('Mie. The ECMWF (European Centre for Medium-Range Weather Forecasts) is a European global forecast seamless model. It is widely regarded as the best and most reliable model currently in existence. It uses a concept called 4D, which is assimilation that allows the model to be constantly updated as new satellite or other input data becomes available We have found a strong correlation between Aeolus wind data biases and small temperature variations across the 1.5 m diameter telescope used in the Aeolus instrument, says ECMWF's Mike Rennie, whose work on the data is funded by ESA. ECMWF will work closely with ESA on ways to minimise such biases in Aeolus products, which may be applied in possible follow-on missions
This software is distributed under the terms # of the Apache License version 2.0. In applying this license, ECMWF does not # waive the privileges and immunities granted to it by virtue of its status as # an Intergovernmental Organization or submit itself to any jurisdiction. # # ***** LICENSE END ***** # import metview as mv # read ERA5 monthly mean nc = mv.read(era5_2000_aug.nc) # this NetCDF data has the following structure: # # dimensions: # longitude = 1440 ; # latitude. CERA-20C is the ECMWF 10-member ensemble of coupled climate reanalyses of the 20th century, from 1901-2010. It is based on the CERA assimilation system, which assimilates only surface pressure and marine wind observations as well as ocean temperature and salinity profiles. It is an outcome of the ERA-CLIM2 project. For any questions regarding the data access and the data itself, please go to the C3S user service desk and look at the Knowledge Base or contact the User Support via the Enquiry. ERA5 provides hourly estimates of a large number of atmospheric, land and oceanic climate variables. The data cover the Earth on a 30km grid and resolve the atmosphere using 137 levels from the surface up to a height of 80km. ERA5 includes information about uncertainties for all variables at reduced spatial and temporal resolutions. Quality-assured monthly updates of ERA5 (1979 to present) are published within 3 months of real time. Preliminary daily updates of the dataset are available to.
National meteorological services of ECMWF Member and Co-operating States and their authorised users are granted full access to ECMWF archive products via their computing representative. All other users need an archive licence to gain access to the Catalogue of ECMWF Archive Products via the ECMWF web API service. 1. Review the service Before ordering an archive licence: Check the public datasets that are available free-of-charge (individual terms and conditions may apply). If these do not. Plotting in directly in Jupyter notebooks doesn't need output to be specified. Most of the time you will want an output The meteorological wind direction is the direction from which the wind is blowing. Wind direction increases clockwise such that a northerly wind is 0°, an easterly wind is 90°, a southerly wind is 180°, and a westerly wind is 270°. Because trigonometry uses a polar coordinate system in which 0° is along the x axis, the meteorological angle.
ERA-Interim is a global atmospheric reanalysis that is available from 1 January 1979 to 31 August 2019. It has been superseded by the ERA5 reanalysis. The data assimilation system used to produce ERA-Interim is based on a 2006 release of the IFS (Cy31r2). The system includes a 4-dimensional variational analysis (4D-Var) with a 12-hour analysis window. The spatial resolution o Global Reanalyses. CERA-20C (Jan 1901 - Dec 2010) ERA-20C (Jan 1900 - Dec 2010) ERA-Interim (Jan 1979 - Aug 2019) (Production stopped on 31st August 2019) ERA-Interim/LAND (Jan 1979 - Dec 2010) ERA-20CM (Jan 1900 - Dec 2010) Final. ERA-40 (Sep 1957 - Aug 2002 initial value of wind speed for the wave model: 63 KB: 2015120300/sfcwindin: initial value of 10-meter horizontal wind components and sea ice fraction for the wave model: 2.2 MB * NODE.001_01.model.1 and ifs.stat.model.1 files are from an OpenIFS run at ECMWF and they are provided for comparison with the user run ECMWF wind field and its influence on the different wave parameters were assessed. Model calibration results revealed that enhancing the ECMWF ERA-Interim wind field by 20%-25% gives good matching results in hindcasting significant wave height with better estimates of extreme events using a 25% enhancement factor
To be able to download data via the ECMWF WebAPI, you will need: An ECMWF account. If you don't have an account, please self register at https://apps.ecmwf.int/registration/ A computer with a *nix operating system is highly recommended. Microsoft Windows is known to work too, but is unsupported. The Python programming language Wind and relative humidity at various pressure levels. High resolution forecast . 500-1000 hPa thickness and Mean sea level pressure. High resolution forecast. Indices (CAPE/Kindex/Totalx) High resolution forecast. Significant wave height and mean direction. High resolution forecast. Total Swell, significant wave height and mean direction. High resolution forecast. Windsea: Significant wave. The ECMWF (European Centre for Medium-Range Weather Forecasts) model is highly regarded by Meteorologists and top Navigators around the world. The ECMWF HRES model consistently rates as the top global weather model from a national weather service with the highest rating scores A ground-breaking satellite mission to be launched in late 2017 or early 2018 could herald a step change in the quality of weather forecasts around the globe by providing new wind data, a meeting on tropical modelling held at ECMWF has heard
If wind arrows are to be plotted, then the input data should include three-dimensional wind data, i.e. the u/v/w wind components should all be present. If more than one time and/or forecast step is contained in the GRIB icon, it returns a set of cross sections. Line. Specifies the coordinates of a transect line along which the cross-section is calculated in lat1/lon1/lat2/lon2 format. The. Download a data sample. ECMWF provides a web interface to quickly download a sample dataset for evaluation. Go to ECMWF Web User Interface for ERA-Interim; Make sure you are logged in with your ECMWF user ID (top right of the page) In the left hand menu select if you want daily or monthly data, and surface, pressure levels or model levels; Select the time period you want to download. Since. The data are archived in the ECMWF data archive (MARS) and a pertinent sub-set of the data, ERA5 diurnal cycle for winds: the hourly data reveals a mismatch in the analysed near surface wind speed between the end of one assimilation cycle and the beginning of the next (which occurs at 9:00 and 21:00 UTC). This problem mostly occurs in low latitude oceanic regions, though it can also be. Figure 1 Variance in 25-km ASCAT winds (O) and collocated ECMWF data ( B) below 200 km scales for the u (left) and v (right) components. O-B is the variance of the difference between both and r 2 the total variance of ASCAT minus the total variance in the ECMWF winds, i.e., the green minus the red curve. High-resolution wind Doc ID data-assimilation guide : NWPSAF -KN UD 008, SAF/OSI/CDOP3.
Data unavailable. Data unavailable. Data unavailable. Data unavailable. Data unavailable. Data unavailable. Data unavailable. Sat 08 May 2021 00 UTC. These charts represent forecasts of Mean Sea Level Pressure (MSLP) and Wind speed at 850 hPa all from the ECMWF high resolution forecast (HRES). Select which using the parameter drop down menu (grey box). MSLP . is the surface pressure reduced to. ECMWF 15-Year Reanalysis (ERA-15) Description: Includes monthly mass, moisture and energy budget products, and daily model level and pressure level data.; Record Includes: Jan 1979-Dec 1993 ; See Also: ERA-15 Website, ERA project website, ERA-15 report series, and Trenberth and Guillemot (1995).; ECMWF 40-Year Reanalysis (ERA-40) Description: Includes monthly mass, moisture and energy budget.
Name Short Name Units Parameter ID GRIB1 GRIB2 NetCDF . Last updated on the 27 Apr 2021 . © European Centre for Medium-Range Weather Forecast ECMWF data has a very high acquisition cost, and this is why the data is not widely used by many weather websites, and has been traditionally used only by top yacht racing teams and meteorologists. SPIRE: Is a truly innovative company with the largest nanosatellite network in space. Spire uses a unique technique of measuring the earth's atmosphere with 3x more radio occultation data than any.
ECMWF Public Datasets To access these datasets, you need to agree on the corresponding terms and conditions that can be found under the Licence link in the table below. licenc You are browsing the contents of the Archive Catalogue. For further information on how to access data from the Archive Catalogue please check our Order historical datasets page.. Operational data This free app from PredictWind allows the seamless downloading of multiple GRIB files for your coastal or offshore passage. The intuitive interface allows you to download and immediately view GRIB files, weather routes, GMDSS text forecasts and Satellite Imagery Tags: number wind data ecmwf level Filter Results wind data (6) wind (6) vectors (6) vector (6) v1.1 (6) v-wind (6) v-component (6) u-wind (6) Show More Tags. Formats HTML (6) WMS (3) Licenses There are no Licenses that match this search. close..
Tags: number wind data ecmwf level Filter Results. CCMP Winds, Atlas FLK v1.1 Derived Surface Winds (Level 3.5a), Global, 0.25 D... This dataset is derived under the Cross-Calibrated Multi-Platform (CCMP) project and contains a value-added 5-day mean ocean surface wind and pseudostress to approximate a... HTML; CCMP Winds, Atlas FLK v1.1 Derived Surface Winds (Level 3.0), Global, 0.25 De. Professional ECMWF weather forecasts - worldwide. Download; Content; Q&A; Pflotsh ; Deutsch ; If it's important, people check the Euro ECMWF model. It is known worldwide for its accuracy. For forecasts, over 80 weather parameters are available, complemented by a comprehensive archive. Pflotsh ECMWF is our pro app: With a subscription to it, all other Pflotsh apps are unlocked. Professional. This CDS API script can be used to retrieve the 4v 10m wind components from the ECMWF data archive, MARS. For more information on how to use CDS API scripts, see How to download ERA5.For the temporal specification, the CDS uses the validity date and time, whereas MARS uses date, time and step (there is further discussion of step in the section Date and time specification of the ERA5 data. ECMWF data has a very high acquisition cost, and this is why the data is not widely used by many weather websites, and has been traditionally used only by top yacht racing teams and meteorologists. SPIRE . Spire uses the community MPAS model: Model for Prediction Across Scales. Spire uses a unique technique of measuring the earth's atmosphere with 3 times more radio occultation data than any. Weather radar, wind and waves forecast for kiters, surfers, paragliders, pilots, sailors and anyone else. Worldwide animated weather map, with easy to use layers and precise spot forecast. METAR, TAF and NOTAMs for any airport in the World. SYNOP codes from weather stations and buoys. Forecast models ECMWF, GFS, NAM and NEM
Evaluation of ECMWF wind data for wave hindcast in Chabahar zone 381 The present study investigates the quality of two sources of surface winds, i.e. the measured synoptic data and the ECMWF numerical weather prediction data for the wave modeling near the Chabahar zone in the Gulf of Oman. For simulating wave parameters the third generation spectral SWAN model (Booij et al., 1999) was utilized. . ECMWF has been closely involved with the mission right from the design phase. Of particular note in 2018 was ECMWF's direct involvement in the Aeolus ground segment, resulting in the first production of level-2 wind data from Aeolus less than two weeks after launch. The new near-real. Windy provides the option to choose from several different weather models. Below is a brief overview of all models which you can find on Windy. Global models: ECMWF (European Centre for Medium-Range Weather Forecasts) is sometimes informally known in th.. At ECMWF we are very excited about the prospect of using the novel space-based wind profile information of Aeolus to improve our weather forecasts. We are proud to take a significant role in the operational Ground Segment processing and in the expert teams that will work on achieving a useful wind product Title: Operational assimilation of surface wind data from the MetOp ASCAT scatterometer at ECMWF: Publication Type: Newsletter Feature Article: Date Publishe
ECMWF is the European Centre for Medium-Range Weather Forecasts. We are both a research institute and a 24/7 operational service, producing global numerical weather predictions and other data for our Member and Co-operating States and the broader community. The Centre has one of the largest supercomputer facilities and meteorological data archives in the worl . Independent Variables (Grids) hdate grid: /hdate (months since 1960-01-01) ordered (1993) to (2015) by 12.0 N= 23 pts :grid Lead (forecast_period) grid: /L (days) ordered (0.0 days) to. other satellite wind data shown in ECMWF OSEs • Aeolus <1% by number of data assimilated; good OSE impact demonstrates the benefit of satellite winds with good vertical resolution • FSOI confirms the OSE positive impact • Other NWP centres corroborate the positive impact e.g. DWD, Météo-France, Met Office, NOAA, Indian NCMRWF, HARMONIE consortium • Aeolus is still very new and the. ECMWF S2S UKMO reforecast perturbed pressure_level_wind v: V-Component of Wind data pressure_level_wind v V-Component of Wind from ECMWF S2S UKMO reforecast perturbed: UKMO reforecasts with 2 ensemble members. Independent Variables (Grids) hdate grid: /hdate (months since 1960-01-01) ordered (Jul 1993 - Jun 1994) to (Jul 2014 - Jun 2015) by 12.0 N= 22 pts :grid Lead (forecast_period) grid: /L.
Evaluation of ECMWF wind data for wave hindcast in Chabahar zone. Wind waves are the most important environmental forces acting on the marine structures. Due to the incompleteness of measured wave parameters, wave prediction plays a key role in the design of coastal and offshore structures. Nowadays, numerical wind wave models are widely used for wave hindcast and forecast. Since wind is the. The fantastic achievements of ESA with the Aeolus satellite and our close partnership with the teams involved (the German Aerospace Center, DLR; Météo-France; the Dutch national meteorological service, KNMI; and the software company DoRIT) allowed Aeolus to be ready for implementation for data assimilation at ECMWF at the end of 2019. Implementing continuous data assimilation in operations. Analysis of the climatology and variability of the stratosphere and mesosphere in measurements and model data. Provision of daily stratospheric winter diagnostics and meteorological support for measurement campaigns. Investigation of radiative, chemical and dynamical processes, and their inter -actions using a state-of-the-art global Chemistry-Climate-Model with focus on: anthropogenic. Estimating typhoon waves based on the modified ECMWF ERA-5 wind data. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1177-1182. Coconut Creek (Florida), ISSN 0749-0208. ERA-5 is a recently released reanalysis meteorological dataset provided by European Centre for Medium-Range Weather Forecasts (ECMWF). This study. data and also TAMDAR wind/temperature/humidity ECMWF Tech Memo 855 • March 2016 ECMWF started assimilating AMDAR humidity operationally •2017: Reduced horizontal and vertical thinning of aircraft reports •Late 2017: ECMWF noted B787 wind problem -partially addressed by blacklist changes •2019: B787 winds still causing some problems, tried switching the v-wind to match EC.
PDF | On Oct 9, 2017, Liliana Rusu and others published Prediction of storm conditions using wind data from the ECMWF and NCEP reanalysis | Find, read and cite all the research you need on. Meteorological data sets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) are among those data frequently used for Lagrangian transport simulations. In 2006, the ECMWF implemented the ERA-Interim reanalysis ( Dee et al. , 2011 ) , which has since been successfully applied in thousands of research applications
Iso-latitude comparison of modeled wind speed issued of ECMWF and NCEP-MM5 data for f = +15 N, +20 N, and +25 N and for the 6 March 2004 00:00 (left) and 12:00 UTC (right). D16201 MENUT: SENSITIVITY OF MODELED HOURLY SAHARAN DUST EMISSIONS TO WIND SPEED 3of8 D16201. Figure 4. Distribution of wind speed for three sites, Bodele (Chad), Banizoumbou (Niger), and Dakar (Senegal), and two periods. The skewT plugin now runs with ECMWF data. Use the picker to open a skewT and explore the world's profiles :) This version is still a little buggy I'm afraid (mostly the wind barbs), but I'll publish a few fixes soon. It's also slower than I'd like. Two things that would really help me for the next version are . Is there a simple way to get surface pressure? I've tried getting it from the. This GIF shows wind speed over the Norwegian archipelago of Svalbard. The first image is based on lower resolution #ERA5 data, and the second is the new #CARRA data. The advantage of the new higher resolution data is particularly clear at the centre of Svalbard, where it captures the localised high windspeeds. Today marks the release of the first batch of data, covering 1998 to 2019. Find out.
With the operational assimilation of Aeolus data at ECMWF, a major milestone for this novel mission has been reached. Other operational weather centres across the world are also seeing positive impact of Aeolus observations and plan to start assimilating data during the course of this year. This mission milestone also paves the way for a possible future fleet of operational Doppler wind lidar. ECMWF ozone layer forecasts in the Windy application. Credit: Windy and ECMWF. But where does this information come from? A lot of the weather data is provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), which implements CAMS on behalf of the European Union. ECMWF also contributes some information about the ozone layer, but environmental information is otherwise limited. BACKGROUND: MetDesk Limited understands that your privacy is important to you and that you care about how your personal data is used. We respect and value the privacy of everyone who visits this website, www.wxcharts.com (Our Site) and will only collect and use personal data in ways that are described here, and in a way that is consistent with our obligations and your rights under the law Aeolus on the other hand gathers its wind data across the entire Earth, from the ground to the stratosphere (30km) above thick clouds. How to measure the wind from space image copyright ES Wind trajectory with ECMWF ERA-5 hourly wind data. GitHub Gist: instantly share code, notes, and snippets
. 65, pp. 380-385, ISSN 0749-0208. Wind waves are the most important environmental forces acting on the marine structures. Due to the incompleteness of measured wave parameters, wave prediction plays a key role in. One of the most important factors in design of coastal and marine structures is the wind-induced wave characteristics. Hence, an accurate estimation of wave parameters is considerably important. In this paper, SWAN third generation spectral models with unstructured mesh have been used for the prediction of wave parameters in the Caspian Sea. The new reanalysis wind datasets provided by ECMWF.
This data set contains ECMWF model forecast wind shear imagery over the Western Pacific Ocean. The products include 850-200mb and 850-500mb wind shear . The imagery were produced from the 00 and 12 UTC model runs every six hours to 36 hours and every 12 hours from 36 to 144 hours. These images were developed by ECMWF and are in png format. Data access. ORDER data for delivery by FTP; Preview. The data remains also listed in ECMWF's public data catalogue. To 10 metre U wind component: m s-1: 10m_u_component_of_wind: 10u: 165: Fast access: 10 metre V wind component: m s-1: 10m_v_component_of_wind: 10v: 166: Fast access: 10 metre wind gust in the last 3 hours: m s-1: 10m_wind_gust_in_the_last_3_hours: 10fg3 : 228028: 2 metre dewpoint temperature: K: 2m_dewpoint_temperature: 2d. Title: Assessment of European wind profiler data, in an NWP context: Publication Type: Technical memorandum: Date Published: 06/2002: Secondary Title: ECMWF Technical Memorand Request PDF | Impact of Scatterometer Surface Wind Data in the ECMWF Coupled Assimilation System | The European Centre for Medium-Range Weather Forecasts (ECMWF) has developed a coupled. Request PDF | ERS-Scatterometer wind data impact on ECMWF's tropical cyclone forecasts | This paper describes the positive impact of ERS scatterometer data on tropical cyclone analyses and.
ECMWF IFS HRES (10 days) - Current model charts of parameter Mean wind speed for map Indi The Global Wind Atlas is a free, web-based application developed to help policymakers, planners, and investors identify high-wind areas for wind power generation virtually anywhere in the world, and then perform preliminary calculations
ABSTRACT Saket, A., Etemad-Shahidi, A., Moeini, M.H., 2013. Evaluation of ECMWF wind data for wave hindcast in Chabahar zone Wind waves are the most important environmental forces acting on the marine structures. Due to the incompleteness of measured wave parameters, wave prediction plays a key role in the design of coastal and offshore structures Wind mph Dir ° Gust mph Dir ° Press During the first month, data is saved every 1 h. ECMWF saves a full restart file at the end of each month, which is defined to be 00 UTC on the last day of the month. (The list of restart times is: 744, 1464, 2208, 2952, 3648, 4392, 5112, 5856, 6576, 7320, 8064, 8784, 9528, 10248.) Plans are to rerun at least one additional month at 1-h. Investigation of wind speed trend changes in central Iran using ECMWF Reanalysis data
Enhance the map with your own data. Use our maps to display the information you prefer. 1. Choose from weather models, layers and isolines 1 000€ for ECMWF Upgrade your trial API key. Trial: Professional : Sessions per day. 500. 10 000 * * can be increased by agreement. Available models. gfs. gfs, icon, nam, arome, geos5, ecmwf * * for internal use only. Available layers. wind. Data Library ECMWF S2S UKMO reforecast perturbed pressure_level_wind u X 0.75W - 0.75W Y 90.75S - 90.75N P [-45.0 1055.0] hPa M 1.5 L [0.0 60.0] days S 1 Jan 2016 - 8 May 2019 hdate 1993-2015. Description; Documentation; Views; Data Filters; Data Selection; Data Files; Data Tables; Expert Mode; served from IRI/LDEO Climate Data Library. ECMWF S2S UKMO reforecast perturbed pressure_level_wind u. wind velocities as well as temperature for the selected dates. ECMWF data was chosen ECMWF data was chosen because of higher resolution in the horizontal plane than other available online sources ∂ P [ ECMWF S2S ECCC forecast perturbed pressure_level_wind v ]: ∂ P V-Component of Wind data forecast perturbed pressure_level_wind v ∂ P V-Component of Wind from ECMWF S2S ECCC: ECCC Ensemble Prediction System. Independent Variables (Grids) Lead (forecast_period) grid: /L (days) ordered (0.0 days) to (32.0 days) by 1.0 N= 33 pts :grid Ensemble Member (realization) grid: /M (ids. Wind data are typically provided from a separate atmospheric model from an operational weather forecasting center. ECMWF has incorporated WAM into its deterministic and ensemble forecasting system., known as the Integrated Forecast System (IFS). The model currently comprises 36 frequency bins and 36 propagation directions at an average spatial resolution of 25 km. The model has been.
∫dP ∫dM [ ECMWF S2S NCEP forecast perturbed pressure_level_wind v ] : V-Component of Wind data forecast perturbed pressure_level_wind v int_dM int_dM V-Component of Wind from ECMWF S2S NCEP: NCEP CFSv2 Ensemble. Independent Variables (Grids) Lead (forecast_period) grid: /L (days) ordered (0.0 days) to (44.0 days) by 1.0 N= 45 pts :grid M (realization) grid: /M (ids) ordered (0.5) to (15.5. Instead, we start with basic variables such as wind speed at 10 m, 2 m (dewpoint) temperature and precipitation, to get you going. We will add data for snow cover, solar radiation, 100 m wind speeds, surface temperature, soil moisture, and temperature, soon. Please contact us if you are interested in data beyond that
The CCMP wind analysis is a near-global, high spatial and temporal resolution gridded dataset of surface wind vectors spanning 1987-present. The input data are a combination of inter-calibrated satellite data from numerous radiometers and scatterometers and in-situ data from moored buoys ECMWF ERA5 global 0.25° x 0.25° reanalysis. ERA5 Reanalysis - monthly mean, daily mean and hourly for select variables . ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades. The data assimilation system used to produce ERA5 is the IFS Cycle 41r2 4D-Var. ERA5 reanalysis currently covers the 1979 to present time period and replaces the.
ERA-5 is a recently released reanalysis meteorological dataset provided by European Centre for Medium-Range Weather Forecasts (ECMWF). This study evaluates the representation of tropical cyclones (TC) in ERA-5 and the widely used ECMWF ERA-Interim (ERA-I) reanalysis data in the northwest Pacific region during year 2013 to 2015. Although ERA-5 wind data has a great improvement of precision. Assimilation of Global Positioning System Radio Occultation Data in the ECMWF ERA-Interim Reanalysis. Quarterly Journal of the Royal Meteorological Society 136: 1972-1990. Quarterly Journal of the Royal Meteorological Society 136: 1972-1990 ∫dS ∫dY [ ECMWF S2S NCEP forecast perturbed pressure_level_wind v ] : V-Component of Wind data forecast perturbed pressure_level_wind v v int_dY V-Component of Wind from ECMWF S2S NCEP: NCEP CFSv2 Ensemble. Independent Variables (Grids) L (forecast_period) grid: /L (days) ordered (0.5 days) to (43.5 days) by 1.0 N= 44 pts :grid Ensemble Member (realization) grid: /M (ids) ordered (1) to. Since wind is the most important forcing term in the numerical wind wave model, the selection of appropriate wind source is a vital step in the wave modeling. In the present study, two wind sources i.e. the measured synoptic and the ECMWF (European Center for Medium Range Weather Forecasts) data, were evaluated for wave simulation near the Chabahar zone. To simulate wave parameters the third.
Title: Report on ERS-2 Radar Altimeter wave height and wind speed data. By: Saleh Abdalla Date: 2 February 2010 Overview: Based on the data received at ECMWF during the whole month, on average, 3538 observations arrived at ECMWF every 6 hours of which 69.54% passed the quality control. As can be seen in Figure 1, there was no data during the 6-hour time windows centred at (all times are UTC. Title: Report on ERS-2 Radar Altimeter wave height and wind speed data. By: Saleh Abdalla Date: 12 March 2010 Overview: Based on the data received at ECMWF during the whole month, on average, 3804 observations arrived at ECMWF every 6 hours of which 50.3% passed the quality control. As can be seen in Figure 1, there was no data during the 6-hour time windows centred at (all times are UTC and.
It utilizes the best available observation data from satellites and in-situ stations, which are assimilated and processed using ECMWF's Integrated Forecast System (IFS) Cycle 41r2. The dataset provides all essential atmospheric meteorological parameters like, but not limited to, air temperature, pressure and wind at different altitudes, along with surface parameters like rainfall, soil. Rolf Brennerfelt, Chair of ECMWF Policy Advisory Committee, commented: ECMWF Member States have been keen for the Centre's data to be open and free for a while. The societal benefits associated with free and open data are big. We are aware that the move comes with its financial challenges, but the benefits outweigh those challenges. We are in a period of transition, and this first batch. SOURCE: Data Support Section Dataset ds126.0 [See also: Data Support Section Dataset ds119.0] DATA DESCRIPTION: ECMWF ERA-40 High Resolution Surface Analysis: T85 resolution: monthly means UPDATED THROUGH: Aug 2002. FORMAT: netCDF GRID: T85 Gaussian (256 x 128) LEVELS: Single level fields: at/near surface, categorical cloud levels TIMES: Monthly Means CURRENT HOLDINGS: Sep 1957 - Aug 200