Data Sources for Offshore Renewable Energy

Data Sources for Offshore Renewable Energy July 20ll Note: All website links in this document were accessed and proved working on August 1 st 201. If links change in future, datasets can be found by an internet search of their title in full. Authors: David Woolf, Jason Mcilvenny A report by Environmental Research Institute, University of the Highlands and Islands – North Highland College (ERI, UHI-NHC) contributing to Work Package 2 of the ORECCA project Contents Introduction 1 Global Atmospheric Re-analysis and Instrument Data Sets 3 ERA-40 4 NCEP/NCAR Reanalysis 7 Hadley Centre Sea Level Pressure dataset 2 (HadSLP2) 9 Twentieth Century Reanalysis (V1) & (V2) 10 ICOADS 11 NOAA Blended Sea Winds 12 Global Atlas of Ocean Waves 13 Public Naval Oceanography Portal (NOP) 13 DTU National Space Institute: DTU10 14 GHCN Monthly Station Data 15 Forecasting System Global Forecasting Systems (GFS) 16 16 Regional Climatic Models 18 REMO 18 NOAA Wavewatch III 19 WAM: Wave Prediction Model 21 ALADIN 22 PRECIS 23 Satellite Data 24 Local & National datasets 30 NORSEWIND 30 CoastDat 31 Royal Dutch Shell plc: Oil Platform data 32 MIDAS land surface station data 33 Crown Estates Data 34 BODC (British Oceanographic Data Centre) 35 Ocean weather Inc. 36 NOAA Wave Buoy Network 36 Channel Coast 37 Wavenet 37 ABPmer :Atlas of UK Marine Renewable Energy Resources 37 Sustainability Development Commission 38 Commercially available products 39 BMT Fluid Mechanics 39 FUGRO Oceanor 40 Metadatabases 43 UKDMOS 43 EDIOS 43 Local resources (Pentland Firth) 44 References 46 Introduction The purpose of this document is to collate information on data sets on ―resources‖ that may be useful to the development of the offshore renewable energy industry. Sources of data with varying levels of details and accuracy are available depending on the scale and type of the study. Reanalysis data is generally used for global resource assessments. National and regional scale resource assessments rely on synoptic scale data or regional scale model data scaled from reanalysis data. Local site specific data is derived from on site wind measurements at specific locations to predict the power production of a single wind turbine or wind farm or to establish the power curve of a wind turbine (Monahan, 2006; Petersen et al., 1997). Here, data sets are divided into global datasets and regional/ local scale datasets. The data and model list is not exhaustive; many other models and data sources exist. This list however describes the principal data sources and models that might realistically be used in offshore renewable energy resource assessment. The data of primary interest to the ORECCA project is wind data, but wave and tidal data are also of interest. Within ORECCA we are primarily interested in data for resource estimates and site identification in the following regions: Area 1: North Sea + Baltic Sea Area 2: Atlantic Ocean Area 3: Mediterranean and Black Sea High quality data are an essential source of information during a resource assessment process. For wind energy, many published studies used data from existing weather station networks operated by meteorological departments. Acceding to World Meteorological Organization WMO, wind measurement should ideally be mounted on wind mast 10 m above the ground; somewhere distortion of the wind field is not significant. Failing that, data needs to be corrected for measurement height and/or flow distortion to a 10-meter-elevation standard. Offshore wind energy companies also need to be able to calculate wind speeds at the height 1 of the wind turbines (often greater than 100 metres). For wind energy resource assessment applications, minimum the amount of wind data should cover a minimum period of one year. Longer periods (10 years) of wind data will provide more reliable results and will identify any long-term variability. The one-year data are usually sufficient to determine diurnal and seasonal variations. Even though data from weather stations were widely used in wind energy resource assessment, they have several limitations which require researchers to find alternative source of accurate data. Even though, wind measurements from weather stations provided data for wind assessment, these types of data have some constraints that disadvantage their use in the assessment process. These main constrains are as follows (Yahyai et al., 2010): Cost Wind Instrument measurements are costly. Installation of a weather station at one location requires infrastructure preparation, communication links, power, sensors and maintenance. Typically, a weather station would cost in the region of $100,000 to $300,000 installation costs depend on location and weather station type. Spatial Resolution Due to cost, weather stations are typically deployed in coarse spatial distributions that vary from one country to the next. Offshore locations include wave buoys, oil industry platforms and sporadic shipboard measurements. Measurement height Standard weather stations measure the wind speed at 10 m above ground height. Wave buoys, oil platforms and ship data differ. For wind energy resource assessment, surface data can introduce errors when using statistics for a 50 – 100 m hub height rotor. 2 Data integrity Instrument data sets can be incomplete due to sensor failure, equipment changes. Older data may not be in digital format. In the new IEC 61400 standard (ed. 3, draft version) there are several wind conditions, which have to be considered when designing a wind farm (Jørgensen et al 2001). The wind conditions, which are important for offshore turbines, are: 1. Extreme winds 2. Wind shear 3. Wind speed probability 4. Turbulence (ambient) 5. Park (wake) turbulence Wave and tidal energy resource assessments have the same data problems as offshore wind resource assessment. Few instrument site data are available, many with short record lengths. Models calibrated with instrument data are commonly used for resource assessment. However trials of wave and tidal devices have been plagued by the loss or damage of devices in the past, highlighting that the extremes from instrument data are as important as the mean annual power for long term commercial investment. Global Atmospheric Re-analysis and Instrument Data Sets Data are available in global datasets which cover the entire globe or substantial parts of it. These datasets are usually gridded at various spatial resolutions or are available in complete coverage via interpolation from data points. Global datasets can be modelled data calibrated by instrument data or directly from instrument data. Global datasets are generally most useful for mapping large scale features, while their resolution and uncertainties can be issues at a smaller scale. They are useful in understanding 3 and studying large-scale spatial and temporal variations in oceanic and atmospheric variables to identify areas of interest for detailed research. One source of reasonably consistent data is reanalysis products. These products are designed to eliminate some of the inconsistencies in long term data sets associated with operational Numerical Weather Forecasting, where the operational model is modified occasionally resulting in ―step changes‖. In a reanalysis, the numerical model is run in a consistent configuration, but will assimilate different data sources as satellites and in situ data sources appear or disappear. (Data assimilation is essentially a mathematical technique to ―nudge‖ numerical model output towards reality, as represented by data). Data from reanalyses are not perfectly consistent over long periods due to the varying data sources and the influence of that data on the model output. There are two large globally gridded atmospheric reanalysis datasets available which are principal sources of data in large scale investigations, the ERA40 and the NCEP/NCAR Reanalysis. These two reanalyses are described below, along with related and similar datasets. ERA-40 ERA-40 stands for ―ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis-40‖. ECMWF is an international organization supported by eighteen European states and with cooperation agreements with several other European states, European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and the World Meteorological Organization (WMO). It is responsible for producing operational global data analyses and medium-range forecasts for its member states, and undertakes a comprehensive programme of research to ensure the continued development and improvement of its product Initially the project intended to be a reanalysis of 40 years of data, hence ERA-40, however it has incorporated 45 years of data and may incorporate more if extended beyond 2002. The reanalysis involved collecting all available conventional and satellite observations (many supplied to ECMWF by DSS) and using a modern, global atmospheric model to create atmospheric analyses ( gridded fields) of many variables on many levels, four times a day, over the 45-year period. The result is an archive of gridded output data. This dataset provides 4 a highly relevant, consistent representation of weather and climate phenomena since 1957. This dataset has been the primary resource for many atmospheric studies and resource assessment studies for example, ―Europe's onshore and offshore wind energy potential: EEA Technical Report No 6/2009‖. Many sources of meteorological observations were used including radiosonde, balloons, aircraft, satellites, buoys and scatterometers. This data was run through the ECMWF computer model at a 40 km resolution. As the ECMWF's computer model is one of the more highly-regarded in the field of forecasting, many scientists take its reanalysis to have similar merit. The data is stored in GRIB format. A problem with the wave output is apparent from wave height measurements by satelliteborne radar altimeter (available since the launch of ERS-1 in 1991 and continuing indefinitely). The size of waves of low magnitude (less than 1 metre) appears to be too high and the corresponding mean periods too high. The problem is largely confined to enclosed or semi-enclosed seas such as the Mediterranean Sea, Black Sea, Baltic Sea, the Gulf of Mexico and the East China Sea. This has been reported by Caires and Sterl (2005) during their validation exercise. A summary of their outputs is presented in the online wave atlas at: http://www.knmi.nl/waveatlas/. Data is available as native grid format or as spectral data and at various model levels (surface level, pressure level etc). Specific interest to the ORECCA project from this dataset would be 10 meter height and the spectral wave data. A full list of variables, model levels and derived products can be found at the data locations described below. Data uses: Global and regional wind and wave statistics. Data Licensing: Unrestricted free access is provided for research or educational purposes. Studies carried out which give an economic advantage for a particular user or group of users require a specific agreement which must be negotiated between ECMWF and the beneficiary. Details can be 5 found here: http://www.ecmwf.int/about/basic/volume1/rules_of_distribution/conditions.html. Similar restrictions apply to the KNMI wave atlas (http://www.knmi.nl/waveatlas/ ) Data location: A Full description of the available data is available at the ERA-40 website here: http://www.ecmwf.int/products/data/archive/descriptions/e4/oper/an/sfc/index.html The BADC also archives and holds ERA-40 data which is available here http://badc.nerc.ac.uk/data/ecmwf-e40/params.html Basic outputs can be acquired here: http://climexp.knmi.nl/ 6 NCEP/NCAR Reanalysis The National Centres for Environmental Prediction (NCEP) and National Centre for Atmospheric Research (NCAR) have cooperated in a project to produce a retroactive record of more than 50 years of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involved the recovery of land surface, ship, radiosonde, pilot balloon, aircraft, satellite, and other data. The dataset is assimilated using an advanced analysis/forecast system to produce an interpolated gridded dataset with full temporal coverage. These data are quality controlled and assimilated with a data assimilation system kept unchanged over the reanalysis period. This eliminated perceived climate jumps associated with changes in the operational (real time) data assimilation system, although the reanalysis is still affected by changes in the observing systems. During the earliest decade (1948−57), there were fewer upper-air data observations and they were made 3 h later than the current main synoptic times (e.g., 0300 UTC), and primarily in the Northern Hemisphere, so that the reanalysis is less reliable than for the later 40 years. The reanalysis data assimilation system continues to be used with current data in real time (Climate Data Assimilation System or CDAS), so that its products are available from 1948 to the present. The products include, in addition to the gridded reanalysis fields, 8-day forecasts every 5 days, and the binary universal format representation (BUFR) archive of the atmospheric observations. The products can be obtained from NCAR, NCEP, and from the National Oceanic and Atmospheric Administration/ Climate Diagnostics Centre (NOAA/CDC). The dataset is a 2.50 x 2.50 latitude and longitude global grid. The NCEP / NCAR reanalysis has been used to research wind conditions in the European region previously, for example Larsén (2009). A Data Extraction tool has been written in R for this product (Kemp et al., 2009). A related dataset is the more recent NCEP-DOE Reanalysis with an updated forecast system. The NCEP-DOE Reanalysis 2 project is using a state-of-the-art analysis/forecast system to perform data assimilation using past data from 1979 through the previous year (Kanamitsu et al., 2002). A large subset of this data is available from PSD in its original 4 times daily 7 format and as daily averages. Differences between the two datasets are examined by Winterfeldt (2008). Data uses: Global and regional wind and wave statistics Data Licensing: None Data location: A Full description of the available data is available at the main NCEP/NCAR website here: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html The NCEP-DOE Reanalysis is available here: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.html Basic variables of the NCEP/NCAR and NCEP/DOE 2 can be accessed here: http://climexp.knmi.nl/ A Data Extraction tool in R is available here: http://cran.r-project.org/web/packages/RNCEP/index.html 8 Hadley Centre Sea Level Pressure dataset 2 (HadSLP2) The Met Office Hadley Centre's mean sea level pressure data set, (HadSLP2), is a unique combination of monthly globally-complete fields of land and marine pressure observations on 5 degree latitude-longitude grid from 1850 to 2004. This product is also available in an updated form using NCEP/NCAR reanalysis fields, giving the near real time product, HadSLP2r. HadSLP2 was created using marine observations taken 2228 stations around the globe. These land and marine observations were blended and the pressures reconstructed using a reduced-space optimal interpolation procedure, followed by superposition of qualityimproved gridded observations onto the reconstructions to restore local detail. HadSLP2r was created by updating HadSLP2 to include data up to 2005 using monthly NCEP/NCAR data. These fields were then adjusted to account for the differences in climatological averages between the HadSLP2 and NCEP/NCAR products (see http://hadobs.metoffice.com/hadslp2/) Data Uses: Global and regional long temporal scale pressure observations can be used to construct wind data. Data Licensing: The material may be downloaded to file or printer for the purposes of private study and scientific research. Any other proposed use of the material is subject to a copyright licence available from the Met Office. Licences and further information can be obtained from the Met Office IPR Officer, Met Office, FitzRoy Road, Exeter, EX1 3PB, U.K. Email: [email protected]. M,6 Data Location: Met Office website: http://www.metoffice.gov.uk/hadobs/hadslp2/ 9 Twentieth Century Reanalysis (V1) & (V2) The Twentieth Century Reanalysis Project is an effort led by the University of Colorado Climate Diagnostics Centre to produce a reanalysis dataset for the entire twentieth century, using only surface observations of synoptic pressure, monthly sea surface temperature and sea ice distribution. The Project uses a recently-developed Ensemble Filter data assimilation method which directly yields each six-hourly analysis as the most likely state of the global atmosphere, and also estimates uncertainty in the analysis. This dataset will provide the first estimates of global tropospheric and stratospheric variability spanning 1871 to present at sixhourly resolution. The data files are also produced for daily and monthly values of the variables. The first version has a global coverage spanning 1908-1958 with a 2o longitudelatitude horizontal resolution. The reanalysis makes use of observations of surface pressure and sea level pressure from the International Surface Pressure Databank version 1.1 and the ICOADS version 2.4, which were assimilated every six hours. The short-term forecast ensemble is generated in parallel from integrations of a state-of-the-art atmospheric general circulation model, the atmospheric component of the NCEP operational Climate Forecast System model. The model has a spatial resolution of 200 km on an irregular Gaussian grid in the horizontal. The model has a complete suite of physical parameterizations including a solar radiation transfer function, boundary layer vertical diffusion coefficients, cumulus convection parameters and gravity wave drag parameterizations. The specified boundary conditions needed to run the model are derived from the time-evolving sea surface temperature and sea ice fields of the HadISST1.1 dataset obtained courtesy of the United Kingdom Met Office Hadley Centre. Data Uses: Global wind data Data Licence: Educational and Research Data Location: Main page: http://www.esrl.noaa.gov/psd/data/gridded/data.20thC_Rean.html Alternative: http://climexp.knmi.nl/ 10 International Comprehensive Ocean-Atmosphere Data Set (ICOADS) The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) offers surface marine data spanning the past three centuries, and simple gridded monthly summary products for 2° latitude x 2° longitude boxes back to 1800 (and 1°x1° boxes since 1960)—these data and products are freely distributed worldwide. As it contains observations from many different observing systems encompassing the evolution of measurement technology over hundreds of years, ICOADS is probably the most complete and heterogeneous collection of surface marine data in existence Data Uses: Local, regional and global datasets on wind and wave. Data Licence: Contact Eric Freeman, Marine Observation Analyst - STG, Inc. Ingest and Analysis Branch Global Climate Applications Division NOAA's National Climatic Data Centre 151 Patton Avenue Asheville, NC 28801-5001 USA Phone: +1 828-271-4463 FAX: +1 828-271-4022 e-mail: [email protected] Data Location: http://icoads.noaa.gov/products.html http://icoads.noaa.gov/ 11 NOAA Blended Sea Winds ―The Blended Sea Winds contain globally gridded, high resolution ocean surface vector winds and wind stresses on a global 0.25° grid, and multiple time resolutions of 6-hourly, daily, monthly, and 11-year (1995-2005) climatological monthlies. The period of record is 9 July 1987 - present. The wind speeds were generated by blending observations from multiple satellites (up to six satellites since June 2002 …‖. This is a research product that has been commercialized and marketed for offshore wind resources as ―WindScan‖ (Atmos Consulting). http://en.wikipedia.org/wiki/WindScan. Initial research on applying this data to offshore wind was conducted at UHI – North Highland College (ERI). Data Licence: Research Purposes Only (Blended Sea Winds) Commercial Use (WindScan) Data Source: Main NOAA Webpage http://www.noaa.gov/ Direct link http://www.ncdc.noaa.gov/oa/rsad/air-sea/seawinds.html WindScan http://en.wikipedia.org/wiki/WindScan http://www.4coffshore.com/windfarms/windspeeds.aspx http://www.atmosconsulting.com/contact/ 12 Global Atlas of Ocean Waves: Based on VOS Observations This Atlas is the result of a co-operative project, funded by European Union (INTAS grant 96-2089) "Intercomparison of ocean waves from in-situ measurements, voluntary observing ship data, remote sensing, and modelling". The main goal of this project is to quantify biases between wave fields available from different sources. Project participants were P.P.Shirshov Institute of Oceanology, Russian Academy of Science (Moscow), Southampton Oceanography Centre (Southampton) and Royal Netherlands Meteorological Institute (De Bilt). The atlas covers the globe from 84S to 84N for the period 1958-1997. The project used the re-processed COADS Releases 1a and 1b, which cover respectively the periods 19501979 and 1980-1997. Data Licence: None Data Location: http://www.sail.msk.ru/atlas/index.htm Public Naval Oceanography Portal (NOP) US Navy wave data, including forecast for North Atlantic for up to 5 days. Good graphical representations and fairly accurate forecasts. Commander, Naval Meteorology and Oceanography Command is consolidating the command's web presence in accordance with Department of Defense (DoD) and Navy guidance. The U.S. Naval Oceanography portal will be the single access point for all public facing Meteorology and Oceanography products and services. This publicly-accessible portal is currently online at http://www.usno.navy.mil and is being populated. In the near future, non-DoD users will be redirected to this portal. Archived and forecast data available includes:    Global Ensemble Ocean Wave Prediction Charts (WW3 Ensemble) Global atmospheric wave prediction (WW3) Global & Regional Weather Prediction Charts (WXMAP) 13   Global Ensemble Weather Prediction Charts (EFS) Global Sea Surface Temperature and Sea Surface Temperature Anomaly Charts (NCODA) Data Licence: Free public data Data Location: https://www.fnmoc.navy.mil/public/?color=b&area=natl DTU National Space Institute: DTU10 The DTU10 global ocean tide model is an update of the AG95 ocean tide. Resolution is 0.125º x 0.125º, including the 12 major tidal constituents. A new global ocean tide model DTU10 (Technical University of Denmark) is developed based on FES2004 (Finite Element Solutions) and the ‗response method‘ (Munk and Cartwright, 1966). Using the latest seventeen years multi-mission measurements from TOPEX/POSEIDON (phase A and phase B), Jason-1(phase A and phase B) and Jason-2 satellite altimetry for sea level residuals analysis, the harmonic coefficients corresponding to the new global ocean tide model are developed (Cheng & Anderson, 2010). Data Licence: Reference: Please acknowledge all use referencing: Yongcun Cheng, Ole Baltazar Andersen, (2010). Improvement in global ocean tide model in shallow water regions. Poster, SV.1-68 45, OSTST, Lisbon, Oct.18-22. Data Location: http://www.space.dtu.dk/English/Research/Scientific_data_and_models/Global_Ocean_Tide_Model.aspx 14 GHCN Monthly Station Data The Global Historical Climatology Network (GHCN) monthly climate dataset comes from NOAA/NCDC (National Oceanic and Atmospheric Administration / National Climatic Data Centre). The data comes in two formats, ―adjusted‖ and ―unadjusted‖. The first set has been corrected for urban effects and other biases by comparing urban stations to nearby rural stations. The GHCN monthly database contains historical temperature, precipitation, and pressure data for thousands of land stations worldwide. The period of record varies from station to station, with several thousand records extending back to 1950 and several hundred being updated monthly surface observations. The data are available without charge through the NCDC anonymous FTP service2. Both historical and near-real-time GHCN data undergo rigorous quality assurance reviews. These reviews include pre-processing checks on source data, time series checks that identify anomalous changes in the mean and variance, spatial comparisons that verify the accuracy of the climatological mean values, seasonal cycles and the identification of chronological and spatial outliers. One of the primary goals of GHCN monthly analysis was the acquisition of additional data in order to enhance spatial and temporal coverage. There were three reasons for this: a) data for recent months allows one to assess current climatic conditions and place them in historical perspective; b) denser coverage facilitates the analysis of regional climate change, and c) certain areas (or certain times in certain areas) are under-sampled even from the perspective of a global analysis. GHCN-Monthly‘ is used operationally by NCDC to monitor long-term trends in temperature and precipitation. It has also been employed in several international climate assessments, including the Intergovernmental Panel on Climate Change 4th Assessment Report, the Arctic Climate Impact Assessment, and the "State of the Climate" report published annually by the Bulletin of the American Meteorological Society. Data Licence: Research use only, for commercial use contact NOAA/NCDC Data Location: Main page: http://www.ncdc.noaa.gov/ghcnm/v2.php (Alternative: http://climexp.knmi.nl/) 15 Forecasting Systems Global Forecasting Systems (GFS) The Global Forecast System (GFS) is a global numerical weather prediction computer model run by NOAA. This mathematical model is run four times a day and produces forecasts up to 16 days in advance, but with decreasing spatial and temporal resolution over time. It is widely accepted that beyond 7 days the forecast is very general and not very accurate, and most nongovernmental agencies rarely use any of the model's results beyond 10 days (mainly because there is no other 16-day model with which to compare). Along with the ECMWF's Integrated Forecast System (IFS) and the Canadian Global Environmental Multiscale Model (GEM), both of which output predictions for up to10 days in advance, it is one of the three predominant synoptic scale medium-range weather forecasting systems in general use. The model is run in two parts: the first part has a higher resolution and goes out to 180 hours (7 days) in the future; the second part runs from 180 to 384 hours (16 days) at a lower resolution. The resolution of the model varies in each part of the model: horizontally, it divides the surface of the earth into 35 or 70 kilometre grid squares; vertically, it divides the atmosphere into 64 layers and temporally, it produces a forecast for every 3rd hour for the first 180 hours, after that they are produced for every 12th hour. The GFS is also used to produce model output statistics, both in a short range (every 3 hours, out to 72 hours) and in an extended range (every 12 hours, out to 8 days). In addition to the main model, the GFS is also the basis of a 20-member (22, counting the control and operational members) ensemble that runs concurrent with the operational GFS and is available on the same time scales. This is variously referred to as a "Global Ensemble Forecast System" (GEFS or GENS) or the "Medium Range Forecast" (MRF). Ensemble model output statistics are also available out to 8 days. This is the only global model for which all output is available, for free in the public domain, over the internet (as a result of U.S. law), and as such is the basis for non-state weather companies, e.g., Weather Underground, AccuWeather, The Weather Channel and MeteoGroup. (Source: http://en.wikipedia.org/wiki/Global_Forecast_System) 16 Data Use: Global scale atmospheric forecasts Data Licence: None Data Location http://www.nco.ncep.noaa.gov/pmb/nwprod/analysis/ 17 Regional Climatic Models Atmospheric regional climate models (RCMs) serve a variety of purposes in climate research, such as process studies, weather forecasting or long-term simulations (Feser et al., 2011). Reviews on regional climate modelling can be found in Foley (2010), Giorgi and Mearns (1999), Rummukainen (2010), and Wang et al. (2004). RCMs are forced by time-variable conditions along the lateral atmospheric boundaries, sometimes also with large-scale constraints in the interior. These constraints are taken either from global model scenarios or from global reanalysis products. They use high resolution topographic details and can provide multi-year to multi-decadal weather information for past or future scenarios. An important utility of such multi-decadal model data is to quantitatively describe hazards and changing conditions in the regional earth system – such as ocean currents, sea level, storm surges or ocean wave conditions and related threats (Feser et al., 2011). In addition to prevailing large-scale conditions, local climate is influenced by regional aspects such as local orography, land-sea-contrast, and small-scale atmospheric features such as convective cells, which are not well represented in global climate models (GCMs). Limited computer resources prevent the practical use of high-resolution models for global simulations of long time periods. An alternative is a GCM with regional refinement. RCMs are therefore constructed for limited areas with considerably higher resolution to describe regional-scale climate variability and change. During the simulations these RCMs are controlled by the global climate driving data via various mathematical routines. This technique is called dynamical downscaling (Feser et al., 2011). Weiss et al (2009) describe some of the models output from the NCEP/ NCAR datasets. Relevant and widely used RCM‘s are described below: REMO The REMO model developed by the Max Planck Institute for Meteorology in Hamburg (Jacob & Podzun, 1997). The regional climate model REMO is based on the ―Europamodell‖, the former numerical weather prediction model of the German Weather Service. Further development of the model took place at the Max-Planck-Institute for Meteorology, where the physical parameterizations from ECHAM4/T106 were implemented into the Europamodell 18 code (Jacob and Podzun, 1997, Jacob, 2001). Details and references about the physical parameterizations can be found in Jacob et al. (2001). REMO can be used in the forecast mode (e.g., consecutive 30 h forecasts without assimilation cycle) or in the climate mode. This means, continuous runs for long time periods up to decades with updates of the lateral boundaries every 6 hours. Here, the limited area model is nested into the driving fields using a ―sponge zone‖ of 8 grid points to harmonize the fields. REMO uses NCEP–NCAR reanalyses for forcing data, covers Western Europe/adjacent seas on a grid of 0.5 * 0.5 degrees and over a time span from 1948 –2007. Data Restrictions: None: (http://mms.dkrz.de/pdf/klimadaten//SGAFiles/Conditions_of_use_REMO.1106.pdf) Data Usage: Wind analysis Data Location: Main Page; http://www.dkrz.de/daten-en/wdcc/projects_cooperations/past-projects/remo-uba Example Project; http://www.ecmwf.int/about/special_projects/jacob_regional_ensemble_prediction/ Description; http://gems.ecmwf.int/documents/workdescription/8_REMO_MPI_M.html NOAA Wavewatch III The operational ocean wave predictions of NOAA (National Oceanic and Atmospheric Administration )/ NWS (National Weather Service)/NCEP (National Centre for Environmental Prediction) use WAVEWATCH III® (a third generation wave model) that takes operational NCEP products as input; those products include satellite and wave buoy data. The NOAA WAVEWATCH III® operational wave model suite consists of a set of five wave models, based on version 2.22 of WAVEWATCH III®. All models use the default settings of WAVEWATCH III® unless specified differently. 19 The global NWW3 model:   The regional Alaskan Waters (AKW) model  The regional North Atlantic Hurricane (NAH) model  The regional Western North Atlantic (WNA) model  The regional Eastern North Pacific (ENP) model The regional North Pacific Hurricane (NPH) model All regional models obtain hourly boundary data from the global model. All models are run on the 00z, 06z, 12z and 18z model cycles, and start with a 6h hindcast to assure continuity of swell. All models provides 126 hour forecasts, with the exception of the NAH model (72 hour forecast). No assimilation of wave data is performed. All models are based on shallow water physics without mean currents. Additional model information is provided in the table and bullets below. The four time steps are the global step, propagation step for longest wave, refraction step and minimum source term step. Models inputs are as follows:  Winds from the operational Global Data Assimilation Scheme (GDAS) and the aviation cycle of the Medium Range Forecast model (Kanamitsu, 1989; Kanamitsu et al., 1991; Derber et al., 1991; Caplan et al., 1997). This forecast/analysis system is now called the Global Forecast System or GFS (see earlier section). The winds are converted to 10m height assuming neutral stability. The wind fields are available at 3h  intervals (using analyses and 3h forecasts in the hindcast part of the wave model run)  hurricane winds when possible. These wind fields are available hourly  concentration analysis (Grumbine, 1996) and are updated daily For the NAH and NPH models, the above wind fields are blended with GFDL Ice concentrations are obtained from NCEP's automated passive microwave sea ice Sea Surface Temperatures as needed in the stability correction for wave growth are obtained taken from the GDAS 20  Boundary data for the regional models are obtained from the global model and are updated hourly Data Uses: Hindcast regional wave fields back to 1997 Data Licence: Data is free to use Data Location: NOAA Environmental Modelling Centre main page http://polar.ncep.noaa.gov/waves/index2.shtml Data access page http://polar.ncep.noaa.gov/waves/download.shtml? ftp://polar.ncep.noaa.gov/pub/history/waves WAM: Wave Prediction Model The European Centre for Medium-Range Weather Forecasts (ECMWF) has incorporated the WAM wave model as part of its ensemble forecasting system. This model includes 30 frequency bins, 24 propagation directions, and an average spatial resolution of 40 km. Wave prediction model (WAM), the result of the international Wave Modelling (WAM) group, is the most widely used and one of the best tested wave model of third generation, predicting directional spectra and wave characteristics – significant wave height, mean wave direction and frequency, swell wave height and mean direction. (WADMI, 1988; Weisse & Günther, 2007). The model uses forcing data from Near-surface wind fields from REMO reconstruction resulting in two nested grids 50 km × 50 km and 5 km × 5 km covering North East Atlantic, North Sea south of 56°N. Time period 1948 –2007, as it uses REMO data. 21 Data Use: Wave prediction Data Licence: None Data Location: http://www.ecmwf.int/products/forecasts/guide/The_ocean_wave_model_1.html ALADIN The numerical model ALADIN (Aire Limitée Adaptation dynamique Développement InterNational) is a limited area bi-spectral atmospheric model. It is in fact the limited area version of the ARPEGE model. Historically, it has been developed since the beginning of the 1990s within a broad consortium gathering numerous weather centres in Europe. Forcings resulting from ARPEGE-Climate and from the reanalysis ERA40 are used currently. The studies carried out cover (Spiridonov et al., 2005): Regional climate processes Air-sea flux over the Mediterranean at the regional scale Test of physical parameterizations Regional climate change scenarios Comparison of regional climate methods Data use: Atmospheric modelling, wind. Data Licence: Data location: http://www.cnrm.meteo.fr/alatnet/ http://www.cnrm.meteo.fr/gmapdoc/ http://www.cnrm.meteo.fr/aladin/ 22 PRECIS PRECIS is developed at the Met Office Hadley Centre. It is a regional climate modelling system designed to run on a Linux based PC and can be easily applied to any area of the globe to generate detailed climate change projections. Annexes I & II of the PRECIS handbook describes the (very similar) scientific formulations of the PRECIS regional model and HadAM3P, the model that provides the default lateral boundary conditions (LBCs). Both are based on the atmospheric component of the Hadley Centre's coupled climate model, HadCM3. HadAM3P is a global atmosphere-only model with a resolution of order 150km, forced by surface boundary conditions (sea-surface temperature and sea-ice fraction) from HadCM3 and observations. It has been run for two "time slices": 1960-1990 and 2070-2100. The Hadley Centre is running a suite of climate change experiments, sampling a range of scenarios from the IPCC Special Report on Emissions Scenarios (SRES), using HadAM3P. Data Use: Regional climatic model for climate change prediction Data Licence: Users from institutions in developed countries will be assessed a charge of about 5000 Euros plus VAT. This charge contributes to the costs of development and providing training. For more information please e-mail: [email protected]. Subject to the terms of the PRECIS licence agreement Data Location: http://www.metoffice.gov.uk/precis/ 23 Satellite Data Satellite data can provide measurements of wind and waves. Some of these data are used within operational NWP and reanalysis systems, but they can be used directly. In studies of wind or wave climate they can provide a complementary view to reanalyses and other numerical-model-based products. For example, their use has been demonstrated to study wave climate at a global, regional and national scale (e.g. Woolf et al., 2002 and 2003). Satellite carry various instruments for different application, of which space based radar are of particular interest to the ORECCA project. Data from three different types of rdar instrument are useful for wave, tidal and wind applications.    a Synthetic aperture radar (SAR) for high-resolution imaging a Radar altimeter, to measure the ocean topography a wind scatterometer to measure wind speed and direction A satellite radar-altimeter is a nadir-looking radar with very high range resolution, which allows to measure (with an accuracy in the order of few centimetres) the sea surface profile. Additionally, analysis of the echo amplitude and shape allows to extract information about the wind speed and wave height, respectively. A wind scatterometer observes the same portion of the ocean surface from different (at least 3), angles of view as the satellite passes by measuring the echo amplitude and the corresponding surface reflectivity. This in turn is affected by the ocean surface "roughness", from this it is possible to determine the wind speed and direction. Scatterometers have become the instrument of choice for global wind vector measurement In contrast to the smaller wavelength scatterometers, SAR radars produce higher resolution images. While conventional scatterometry is useful and important for wind vector measurement on a global scale, it fails close to shore. Contamination from land reflections degrades scatterometer measurements near land. BY contrast, high resolution SAR imagery offers the prospect of extending the wind speed measurements right up to the shore to obtain information valuable to coastal areas. Despite the fact that SAR views the surface at only one 24 aspect angle, clear wind speed signatures were seen in even the earliest SEASAT SAR images in which there were bright areas associated with high wind speed. In the early imagery, there were other areas where the wind speed was so low that the ocean surface was smooth and therefore reflected radar energy in resulted in dark patches in SAR images (Jackson et al., 2004). NASA Data: Portal to many NASA missions including TOPEX, JASON and OSTM/JASON 2 altimeter missions. http://www.jpl.nasa.gov/missions/index.cfm. Of particular interest to ORECCA is the SeaWinds mission. (http://winds.jpl.nasa.gov/) AVISO: (Archiving, Validation, Interpretation of Satellite Oceanographic Data) Portal for satellite altimeter data and other oceanographic datasets. http://www.aviso.oceanobs.com/en/data/index.html CERSAT The CERSAT (Centre ERS d'Archivage et de Traitement - French ERS Processing and Archiving Facility) is part of IFREMER (French Research Institute for Exploitation of the Sea. It was created in 1991 as a node of the ESA (European Space Agency) ground segment for the ERS-1 and ERS-2 Earth observation satellites, performing off-line processing of the ERS-1 and ERS-2 "low-bit rate" sensors. CERSAT has then evolved towards a multimission data centre for archiving, processing and validating data from spaceborne sensors (such as altimeters, scatterometers, radiometers, SAR,...). It is intended for the oceanographic community, making available homogeneous time series of value-added data relevant to the sea surface state (wind fields, fluxes, waves or sea-ice). http://cersat.ifremer.fr/data/ ―data distributed by CERSAT‖. See ftp://ftp.ifremer.fr/ifremer/cersat/products/swath/altimeters/waves/ for a direct link to an important satellite-altimeter-based data set for significant wave height 25 ([email protected] ) RSS: Remote Sensing Systems LTD Remote Sensing Systems is a research-oriented business located in Santa Rosa, California. The company was established in 1974 by Frank J. Wentz, a graduate in physics from Massachusetts Institute of Technology. Headed by Frank, the team of scientists includes Marty Brewer, Chelle Gentemann, Kyle Hilburn, Carl Mears, Thomas Meissner, Scott Pustay, Lucrezia Ricciardulli and Deborah Smith. Their website offers an excellent access point for several US satellite data sets. ―QSCAT‖ (SeaWinds on QuikScat, launched June 1999) was a particularly useful data set for winds, providing global and high resolution wind vectors (speed and direction) twice daily with only a short delay; however this satellite failed in November 2009. http://www.remss.com/ ESA Main portal for the European Space Agency. Of particular Interest is data derived from ASCAT, ENVISAT and ERS data. The ASCAT is MetOp's Advanced SCATterometer. Its primary function is to provide measurements of wind velocity over the world's oceans using radar. The Meteorological Operational satellite programme (MetOp) is a new European undertaking providing weather data services that will be used to monitor climate and improve weather forecasts. The MetOp programme‘s series of three satellites has been jointly established by ESA and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), forming the space segment of EUMETSAT's Polar System (EPS). The instrument is the enhanced successor to the highly successful scatterometers flown on ESA's ERS-1 and ERS-2 satellites. Its use of six antennas allows the simultaneous coverage of two swaths on either side of the satellite ground track and hence provides twice the 26 information of the earlier instruments. On an experimental basis, ASCAT also provides measurements at a higher than nominal resolution. In addition to wind measurements, ASCAT will also find roles in areas as diverse as land and sea ice monitoring, soil moisture, snow properties and soil thawing. http://www.esa.int/esaCP/index.html ENVISAT In March 2002, the European Space Agency launched Envisat, an advanced polar-orbiting Earth observation satellite which provides measurements of the atmosphere, ocean, land, and ice ENVISAT includes the ASAR and RA-2 instruments. The ASAR is an Advanced Synthetic Aperture Radar, operating at C-band, ASAR ensures continuity with the image mode (SAR) and the wave mode of the ERS-1/2 AMI. It features enhanced capability in terms of coverage, range of incidence angles, polarisation, and modes of operation. This enhanced capability is provided by significant differences in the instrument design: a full active array antenna equipped with distributed transmit/receive modules which provides distinct transmit and receive beams, a digital waveform generation for pulse "chirp" generation, a block adaptive quantisation scheme, and a ScanSAR mode of operation by beam scanning in elevation. ASAR provides an option for acquiring information on the open ocean and coastal region. Several new SAR ocean applications can be expected to reach pre-operational or operational status during the lifetime of ENVISAT, notably in the areas of pollution monitoring, ship detection, and ocean feature nowcasting. This information can be useful for offshore engineering activities, operational fisheries surveillance, and storm forecast operations. Some of the key areas of interest will include the following:   Wave Characteristics Ocean Fronts 27   Coastal Dynamics Oil Slicks and ShipTraffic ENVISAT is also equipped with the Radar Altimeter 2 (RA-2). This is an instrument for determining the two-way delay of the radar echo from the Earth's surface to a very high precision: less than a nanosecond. It also measures the power and the shape of the reflected radar pulses. http://envisat.esa.int/earth/www/area/index.cfm?fareaid=6 ERS The ERS-2 satellite was retired in July 2010. ERS-2 was launched in 1995, following its sister, the first European Remote Sensing satellite, which was launched four years earlier. Of particular interest are the following instruments equipped on the ERS missions: RA: The Radar Altimeter is a Ku-band (13.8 GHz) nadir-pointing active microwave sensor designed to measure the time return echoes from ocean and ice surfaces. SAR: Synthetic Aperture Radar wave mode provides two-dimensional spectra of ocean surface waves. In image mode the SAR provides high resolution two-dimensional images with a spatial resolution of 26 m in range (across track) and between 6 and 30 m in azimuth (along track). Image data is acquired for a maximum duration of approximately ten minutes per orbit. WS: The purpose of the Wind Scatterometer is to obtain information on wind speed and direction at the sea surface for incorporation into models, global statistics and climatological datasets. It operates by recording the change in radar reflectivity of the sea due to the perturbation of small ripples by the wind close to the surface. http://earth.esa.int/object/index.cfm?fobjectid=3978 28 EUMETSAT The main purpose of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is to deliver weather and climate-related satellite data, images and products– 24 hours a day, 365 days a year. This information is supplied to the National Meteorological Services of the organisation's Member and Cooperating States in Europe, as well as other users world-wide. EUMETSAT is an international organisation and was founded in 1986. EUMETSAT contributes to the global effort to meet the climate challenge. Its Meteosat and Metop satellites, as well as data and product from the Jasonsatellites already provide a wealth of environmental and climate data and products generated by EUMETSAT as well as its Network of Satellite Application Facilities (SAFs) that are distributed rapidly to the global user community. The organisation also possesses a unique archive of relevant long-term satellite data dating back to 1981. http://www.eumetsat.int/Home/index.htm 29 Local & National datasets NORSEWIND On the 1st of August 2008, the EC FP7 project NORSEWIND officially kicked-off. Aimed at bringing high quality Wind Atlases to the North, Irish and Baltic Seas, the project will create one of the biggest dedicated instrumentation networks to acquire wind speed data offshore. NORSEWIND is made up of 15 organisations, and coordinated by Oldbaum Services. Output example results from the data can be seen in Berge et al., (2009), Hasager et al., (2009), Oldroyd et al., (2009) and Griesbaum (2008). This is an ongoing FP7 project that is highly relevant to ORECCA since it may provide wind resource products for the North Sea and Baltic Sea. Data Licence: Restrictions apply: Email: [email protected] Data Access: Oldbaum Services Limited, School House, Brig O' Turk By Callander, Scotland. UK. FK17 8HT Tel: +44 (0) 1877 376718 Email: [email protected] http://www.norsewind.eu/public/index.html 30 CoastDat ―coastDat‖ comprises a compilation of coastal analyses (that is hindcasts and reconstructions) and scenarios for the future obtained from numerical models. The objective is to provide a consistent meteorological-marine data set that best represents past conditions in order to complement the existing but limited observations. Based on model results coastDat may thus provide information over long time spans, at high spatial and temporal detail, and at places and for variables for which no observations have been taken. As an additional benefit, coastDat also provides consistent coastal scenarios for the near future, allowing for an assessment of expected future changes relative to changes observed over the past few decades (Weisse et al., 2008). The CoastDat website also has a link to an ―Atlas of consistent meteorological-oceanographic (wind, waves and storm surges) data for European Coastal Seas‖ which is under development. Data Location: http://www.coastdat.de/ 31 Royal Dutch Shell plc: Oil Platform data Oil Platform data is available from Shell. It is Shell‘s policy not to be involved in research or supply data for research. All data is commercially sensitive, some data may be purchased for commercial usage with restrictions. Data available includes wave, current, wind, temperature (sea / air) and pressure. Data has been recorded on individual platforms, however Shell produce three representative datasets produced from combined datasets of more than one platform for: North-North Sea, Central-North Sea, South-North Sea and Atlantic. Combined datasets represent average conditions over a large area with a larger temporal resolution than individual datasets. The data includes long-term time series that would be very useful for understanding seasonal climate and climate variability (particularly of wind and waves in the context of ORECCA). For example, limited access to wave data from a single platform, North Cormorant, has helped elucidate the long term variability of North Sea wave climate (Woolf et al., 2006). Data Location and Licence: Contact details are below for initial enquiry. The Environmental Research Institute (Thurso) have requested three indicative datasets for research, which Shell have kindly agreed to supply strictly for research only. Jon Upton, PTE/ECSO Senior Metocean Engineer Projects & Technology - Project & Engineering Services Shell International Petroleum Company Limited Seafield House (4B-150) Hill of Rubislaw, Anderson Drive, Aberdeen, AB15 6BL e-mail: [email protected] Internet: http://www.shell.com 32 MIDAS land surface station data MIDAS (Met Office Integrated Data Archive) and surface station data can be acquired from the BADC (British Atmospheric Data Centre). This dataset contains land surface measurements as reported by stations in the UK and globally and archived in the MIDAS Land Surface Observation database at the Met Office. Parameters include daily and hourly weather observations, hourly wind parameters, maximum and minimum air temperatures, daily, hourly and sub-hourly rain measurements, soil temperature parameters, sunshine duration and radiation measurements from 1853 to date. Daily, hourly and sub-hourly measurements form a long-term record of historical UK weather conditions. The daily and hourly data are available online from UK stations in 154 UK counties. Sub-hourly rain data is available for some stations from 1853 to April 2005. Global weather data is available from 1974 to date: Meteorological values observed at 3-hourly intervals by non-UK stations, covering Africa, Asia, South America, Central America, West Pacific, Europe and Antarctic. The ERI (Environmental Research Institute) has downloaded and archived many sites around the North of Britain and noted that datasets do require processing before analysis. Data Uses: Land based wind observations around the UK Data Licence: Strictly for research purposes only. Any commercial work requires special licence which must be negotiated with the Met Office. Data Location: http://badc.nerc.ac.uk/view/badc.nerc.ac.uk__ATOM__dataent_ukmo-midas 33 Crown Estates Data This is the source for the environmental data and information generated under The Crown Estate's second Licensing Round for offshore renewables. Short term local instrument data is available from numerous test sites around the UK. Wind data downloaded from Crown Estate:   Shell Flats Meteorological Mast Data  Docking Shoal MetMast data logger A  Race Bank MetMast data logger A  Dudgeon Meteorological Mast Data  Docking Shoal MetMast data logger B  Race Bank MetMast data logger B Gywny Y Mor Offshore Wind farm data Data Restrictions: Data restrictions may apply for commercial use of the data Data Location: http://data.offshorewind.co.uk/catalogue/ 34 BODC (British Oceanographic Data Centre) BODC hold a wealth of publicly accessible marine data collected using a variety of instruments and samplers and collated from many sources. They hold biological, chemical, physical and geophysical data; databanks contain measurements of nearly 22,000 different oceanographic variables. Includes holdings for ―South Uist buoys‖ from the 1980s, which investigated the potential of wave energy to the west of Hebrides. Also, access in principle to data from oil and gas industry. Data Uses: Local tidal current, wind Data Licence: Various, Free for research and education, but under licence arrangement with BODC for commercial work ―BODC encourage the use of data holdings for science, education and industry, as well as the wider public. BODC makes data available under a licence agreement. In the case of NERC data the conditions are in line with the NERC Data Policy that formally lays down the conditions under which the data may be used. For data from non-NERC organisations the conditions are broadly similar. These will be explained following a request prior to the delivery of data.‖ Data Location: Access to data can be arranged on the website: http://www.bodc.ac.uk/data/where_to_find_data/ 35 Ocean weather Inc. Reputable wave forecasts from Oceanweather Inc. A free service displays the latest marine data, including graphical representation from wave models, marine observation from offshore stations (wind and wave vectors) and SST. Available for a number of regions including North Sea, northern North Atlantic and Mediterranean. EMEC (European Marine Energy Centre Ltd) used directional spectral wave and wind data from Oceanweather Inc‘s GROWFAB database (1986- 2005) to drive a wave model to understand wave and tidal conditions at their test sites in the Orkney Islands (Lawerence et al., 2009). Oceanweather functions as a specialized consulting firm serving the coastal and ocean engineering communities with its unique capacity to integrate several areas of expertise into specification of definitive design data on the physical environment. Since 1983, Oceanweather has operated a real time forecasting division following a unique approach which optimally combines the traditional approach to weather forecasting, which retains the contributions of individual forecasters, and Oceanweather's high-level technology developed and applied so successfully in its hindcasting and consulting divisions. The system includes a global wind and wave forecast system and various high resolution regional applications. Oceanweather Inc. is likely to be a data source data to many renewable energy firms around the UK in the future. Data Location: http://www.oceanweather.com/data/ NOAA Wave Buoy Network Main portal to offshore wave buoy data. US-based but includes much European data. Data Location: http://www.ndbc.noaa.gov/ http://www.ndbc.noaa.gov/maps/United_Kingdom.shtml: (a direct link to buoys around British Isles including UK Met Office offshore network, a similar Irish network and ―private industry‖ (mainly Oil & Gas in North Sea). 36 Channel Coast Portal for wave data from many wave buoys and other instrumentation around the English coastline. Generally close to shore. Includes link to WaveNet. Data Location: http://www.channelcoast.org/ WaveNet WaveNet, ―The DEFRA strategic wave monitoring network for England and Wales‖. N.B. Contrary to the front page description, WaveNet also now includes 4 directional wave buoys around the Scottish coast, including a ―west of Hebrides buoy‖ that is highly significant to wave resource estimation Data Location: http://www.cefas.co.uk/data/wavenet.aspx . ABPmer :Atlas of UK Marine Renewable Energy Resources A project commissioned by BERR in 2007 has taken the existing UK Marine Renewable Energy Resources Atlas forward. This new stage of development for the Atlas has enabled an enhanced definition of the primary resource variables and is now a product that is being made more accessible though a webGIS interface. The charts in the Atlas indicate the distribution of potential resource for the future deployment of renewable energy technologies – wind, wave and tidal. The project team was led by ABP Marine Environmental Research and included the providers of major marine data holdings (Met Office and Proudman Oceanographic Laboratory (POL)). The Atlas represents the most detailed regional description of potential marine energy resources in UK waters ever completed to date at a national scale, and will be used to help guide policy and planning decisions for future site leasing rounds. 37 Data Location: http://www.renewables-atlas.info/ Sustainability Development Commission Published ―Tidal Power in the UK‖. Also numerous other publications and annexes, including estimates of practical tidal resource. Data Location: http://www.sd-commission.org.uk/pages/tidal-power.html 38 Commercially available products BMT Fluid Mechanics BMT Fluid Mechanics offer online databases, wave / wind atlases, measured data and forecast services. They offer several online data access portals which are available at commercial rates and are described below: waveclimate.com provides information on offshore wind and wave conditions of oceans and seas worldwide. Using a near shore translation model it is possible to generate information for coastal locations. http://www.waveclimate.com tidalinfo.com provides information on tidal heights and tidal currents for locations worldwide. The tidal information is based on the integration of approximately 5000 tidal stations and 15 years of satellite radar altimeter into a depth average global tidal model. http://www.tidalinfo.com/ routeclimate.com provides information to be used for the planning of routes and assessing the appropriate cargo fastening conditions. Based on satellite measurements of wind speed and wave height one can determine the probability of exceedance of wind and wave conditions along a route and assess which parts of the route are most critical. www.routeclimate.com coastalwaterquality.com provides information on sediment and chlorophyll concentrations in the water. Using satellite imagery, water bodies are analyzed and the presence of suspended matter and chlorophyll is estimated. The service provides information on the water quality and shows trends of the water quality for locations / areas. www.coastalwaterquality.com The above services require a user name and password. If you have no log in details and you would like to experience the portals first hand click the service of interest and log in with username "demo" and leave the password open. 39 They also provide global wave data statistics. Global Wave Statistics provides nearly worldwide coverage of wave climate in 104 sea areas, and an additional database providing smaller sea areas for the North European Continental Shelf. Based on 130 years of ship visual observations to provide a stable climatic average, the data has been quality enhanced by the well established NMIMET process. Global Wave Statistics provides average climate data for relatively large sea areas and is ideal for a low cost first look at the conditions to be expected in a given area. BMT is also able to provide wind wave and current data for much more specific locations based upon satellite and hind cast data FUGRO: OCEANOR Fugro OCEANOR is a high technology company specialising in the design, manufacture, technological development, installation and support of private and public sector environmental monitoring, ocean observing and forecasting systems. The Company is a part of the Fugro Group of companies, and is located in with it main office in Trondheim. The Company has over 25 years of international experience and a staff with multidisciplinary backgrounds within marine technology, hydrology and instrumentation including engineering, electronics, marine surveying and operations, applied meteorology, oceanography, mathematics, software development. A major element of the Company profile is the establishment of a long-term co-operation both with almost all of our main customers and with Norwegian and international institutions or agencies in applied oceanography and meteorology. In the SEAWATCH projects we often establish local companies in close co-operation with the client, to maintain and operate the buoy system. Fugro OCEANOR also participates in several international R&D programs. Our marine monitoring buoys and systems are, as an example, developed in close cooperation with the European research program EUREKA/EUROMAR (where 11 countries participate), IOC (Intergovernmental Oceanography Commission) and with recommendations from the GOOS (Global Observing System) program. Relevant data products the company supplies are: 40 World Wave Atlas (WWA) has been on the market since 1995. It is in fact both our global satellite altimeter wind and wave database which is fully integrated with our WorldWaves product and the collective name for a series of comprehensive high resolution interactive wind and wave atlases based, primarily, on satellite altimeter data, providing accurate wind and wave climate statistics worldwide or for any country or region. World Wave Atlas contains quality controlled data from Topex (1993–2001), available buoy data and global wave model data, which are carefully validated in order to ensure the data homogeneity. This data was used in Dragani et al. (2010) to investigate wave height on the south American continental shelf. WorldWaves: WorldWaves: a complete database/software package for providing wave climate data and statistics anywhere globally both in deep and shallow waters (Barstow et al., 2009). Fugro OCEANOR have created a global 10-year WorldWaves dataset covering the period 1997 to 2006. All grid points have been calibrated against a combined Topex and Jason altimeter dataset covering the same time period. Please note that when we you order WorldWaves data for a particular location, an enhanced calibration is performed using all available satellite altimeter data (also GFO, Topex2 and Envisat data). This is the main reason that WorldWaves data is not available for on-line download (a fully automatic global calibration to the highest quality is not possible). Weather Windows is a software tool that allows the potential impact of weather downtime to be quantified for any offshore operation. It is available either as a service or can be purchased as a software package. WorldWideWaveStatistics (WWWS) The basic WorldWaves database consists of wave model time series for 9,665 positions calibrated against Topex and Jason data. In addition to the data for these 9,665 locations, Fugro OCEANOR holds uncalibrated data in some 26,000 positions. These latter grid points can be calibrated on demand for clients. We may then use additional satellites other than Topex and Jason. This can then give even higher quality data in coastal but deep water regions with large spatial gradients in wave conditions. This benefit is less in the open ocean areas which we are most concerned with in what we call our WorldWideWaveStatistics (WWWS) database. Those of us who have been around for some 41 years will remember the old voluminous Global Wave Statistics (GWS) book compiled by Neil Hogben and associates from, primarily, visual observations from the voluntary observing fleet. WWWS is a modern-day equivalent based on the highest quality WorldWaves data and providing ready-to-go wave statistics for 150 sea areas globally in a similar format to GWS. It was originally developed on the initiative of a leading Japanese shipping company. It will primarily be of interest to other shipping companies and classification societies requiring modern reliable global wave data. Fugro Oceanor products are detailed in their two published papers, Mork et al. (2010) and Bartstow et al. (2009). Data Location: http://www.oceanor.no/Services/wwa_info/ 42 Metadatabases UKDMOS UKDMOS is the United Kingdom Directory of the Marine-observing Systems, a unique searchable metadatabase of marine monitoring conducted by UK organisations. The monitoring programmes in UKDMOS may also be searched and viewed with other European monitoring programmes in the European Directory of the Ocean Observing System. Data Location: http://www.ukdmos.org/# EDIOS The EDIOS directory provides a new internet-based tool for searching information on observing systems operating repeatedly, regularly and routinely in European waters. The EDIOS directory contains metadata on European observing systems such as platforms, repeated ship-borne measurements, buoys, remote imagery, etc. EDIOS is an initiative of the European Global Ocean Observing System (EuroGOOS). The directory was developed during the EDIOS project, co-funded by the European Commission Research Directorate General. Data Location: http://www.edios.org/ 43 Local resources (Pentland Firth) The following data and resources are available from the ERI (Environmental Research Institute, Thurso) Tidal stream observations from the British Oceanographic Data Centre Courtesy of Wimpol Ltd Data acquisitions are available from the British Oceanographic Data Centre courtesy of Wimpol Ltd1. ADCP were deployed on three different sites on the seabed and measured tidal currents for 10 days each in 1980. The measurements were executed at 10 minute intervals. Tidal stream observations from the Oceanography Department of Guardline Surveys In 2001, a project was conducted by the Oceanography Department of Guardline Surveys to complete tidal stream observations in the Pentland Firth3. Two data acquisition stages were envisaged: one with an Acoustic Doppler Current Profiler (ADCP) mounted in a moving vessel and one with fixed ADCP deployments in the seabed during a full lunar cycle (30 days) at three different sites. Field collected data The Environmental Research Institute has collected fixed and ship mounted ADCP data, Side-Scan sonar data, CTD data and ROV survey data covering the Inner Sound and Pentland Firth. Publications of tidal energy resource work in the Pentland Firth include: DACRE and BULLEN, Pentland Firth Tidal Current Energy Feasibility Study – Phase 1, Aberdeen, UK, The Robert Gordon University and The International Centre for Island Technology, 2001, 95p 44 DILLON, Tidal Energy in the Pentland Firth, Scotland: High Resolution Mapping using GIS techniques, Thesis MSc Environmental Science, University of Aberdeen, 2006/2007, 172p ―RLG‖ The Scottish Government. Pentland Firth and Orkney Waters Marine Spatial Plan Framework & Regional Location Guidance for Marine Energy SALMOND, Harnessing the energy potential of the Pentland Firth, Edinburgh, UK, 5th February 2008, Edinburgh, Pentland Alliance, 2008, 3p WEMYSS, Tidal Development Scenarios for the Pentland Firth, Thesis MSc Marine Resource Management, Heriot Watt University, 2004/2005, 150p ―Tocardo‖. TOCARDO BV, Tidal Energy in the Pentland Firth, Zijdewind, Holland, Tocardo BV, February 2008, 78p 45 References Al-Yahyai, S., Charabi, Y., Gastli, A. (2010) A Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment. Renewable & Sustainable Energy Reviews (RSER), 14, 3192-3198 (http://dx.doi.org/10.1016/j.rser.2010.07.001). Barstow, S., Mørk, G., Lønseth, L. & Mathisen, J. P. (2009) WorldWaves wave energy resource assessments from the deep ocean to the coast. Proceedings of the 8th European Wave and Tidal Energy Conference, Uppsala, Sweden. Berge, E., Byrkjedal, O., Ydersbond, Y. & Kindler, D. (2009) Modelling of offshore wind resources. Comparison of a meso-scale model and measurements from FINO-1 and North Sea oil rigs. Scientific Proceedings EWEC'09 Marseille. Caires, S. & Sterl, A. (2005) A new non-parametric method to correct model data: Application to significant wave height from the ERA-40 reanalysis. J. Atmospheric and Oceanic Tech., 22, 443-459. Cheng, Y. & Andersen, O. B.(2010) Improvement of global ocean tide models in shallow water regions. Altimetry for Oceans and Hydrology OST-ST Meeting Poster Number: SV.1-68 45. Available online at: http://www.space.dtu.dk/upload/institutter/space/data_og_modeller/tide/yongcuncheng-nosv.1-68%2045.pdf Dragani, W.C., Martin, P.B., Simionato, C.G., Campos, M.I. (2010) Are wind wave heights increasing in south-eastern south American continental shelf between 32ºS and 40 º S?, Continental Shelf Research, 30, 481-490. 46 Europe's onshore and offshore wind energy potential: EEA Technical report No 6/2009 Fugro GEOS (2001) Wind and wave frequency distributions for sites around the British Isles. Offshore Technology Report 2001/030. HSE. http://www.hse.gov.uk Feser, F., Rockel, B., Von Storch, H., Winterfeldt, J. and Zahn, M. (2011) Regional Climate Models add Value to Global Model Data: A Review and selected Examples. Bulletin of the American Meteorological Society, 92, 1-32. doi: 10.1175/2011BAMS3061.1. Foley, A., M., (2010) Uncertainty in regional climate modelling: A review, Progress in Physical Geography, 1-24, DOI: 10.1177/0309133310375654. Giorgi, F., and L. O. Mearns, (1999) Introduction to special section: Regional climate modeling revisited. J. Geophys. Res. 104, No. D6, 6335–6352 Griesbaum, M. (2008) An EC FP7 Programme Mapping the North Irish and Baltic Seas. WindTECH International October 2008. Available online at: (http://www.windtechinternational.com/content/view/2014/62) Hasager C B; Mouche A; Badger M; Astrup P; Nielsen M; Husson R. (2009) Satellite Winds in EU-Norsewind. Scientific Proceedings EWEC'09 Marseille, March 2009. Presentation Paper Hervouet, J., and L. V. Haren, 1996: TELEMAC2D version 3.0. Electricité de France, Département Laboratoire National d’Hydraulique, Principle Note EDF HE-4394052B, 98 pp IEC (1999) International standard IEC61400-1, Safety requirements, 2nd edition IEC (2005) International standard IEC61400-1, Safety requirements, 3rd edition, FDIS 47 IEC (2005) International standard IEC61400-12-1, Power performance measurements of electricity producing wind turbines, 1st edition Jackson, C., R. & Apel, J., R. Eds. (2004) Synthetic Aperature Radar Marine Users Manual. (2004) U. S Dept of Commerce (2005). Jacob D (2001) A note to the simulation of the annual and inter-annual variability of the water budget over the Baltic Sea drainage basin. Meteorol Atmos Phys 77. 61-73 Jacob, D., Van den Hurk, B., Andrae, U., Elgered,G., Fortelius C, Graham LP, Jackson SD, Karstens U, Köpken C, Lindau R, Podzun R, Rockel B, Rubel F, Sass BH, Smith RNB, and Yang, X. (2001) A comprehensive model inter-comparison study investigating the water budget during the BALTEX-PIDCAP period. Meteorol. Atmos. Phys. 77. 19-43 Jacob D, Podzun R (1997) Sensitivity studies with the regional climate model REMO. Meteorol Atmos Phys, 63. 119-129 Jørgensen, H.E.; Nielsen, M.; Barthelmie, R.J.; Mortensen, N.G., Modelling offshore wind resources and wind conditions. In: Proceedings (CD-ROM). Copenhagen offshore wind conference 2005, Copenhagen (DK), 25-28 Sep 2005. (Copenhagen Offshore Wind, Copenhagen, 2005) 10 p. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Jenne, Roy, Joseph, Dennis. (1996) The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society. 77, 437-472. Kanamitsu, M., W. Ebisuzaki, J. Woollen, S. K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter (2002) NCEP- DOE AMIP-II Reanalysis (R-2). Bulletin Am. Meteo- rol. Soc., 83, 1631–1643. 48 Kemp, M. U., Emiel van Loon, E., Shamoun-Baranes, J. and Bouten, W. (2011), RNCEP: global weather and climate data at your fingertips. Methods in Ecology and Evolution. doi: 10.1111/j.2041-210X.2011.00138.x Larsén, X. G,. & Mann, J. (2009) Extreme Winds over Denmark from the NCEP/NCAR Reanalysis. Wind Energy 12, 556-573 J. Lawrence, H. Kofoed-Hansen, C. Chevalier (2009): High-resolution metocean modelling at EMEC's (UK) marine energy test sites. Proc. EWTEC, Uppsala, Sweden Monahan, A. H., 2006. 'The Probability Distribution of Sea Surface Wind Speeds. Part II: Dataset Intercomparison and Seasonal Variability'. Journal of Climate 19, 521–534. Mork, G., Bartstow, S., Kabuth, A. & Pontes, M. T. (2010) Assesing the global wave energy potential. Proc. Of OMAE2010. 29th International Conference on Ocean Mechanics and Arctic Engineering. June 6-11, 2010, Shanghai, China. Munk, W. H. and D. E. Cartwright, 1966, Tidal Spectroscopy and Prediction. Philos. Trans. R. Soc. London, A, 259:533-583. Oldroyd A; Kindler D; Courtney M. (2009) Testing and Calibration of Various LiDAR Remote Sensing Devices for a 2 year Offshroe Wind Measurement campaign. Scientific Proceedings EWEC'09 Marseille March 2009. Presentation Paper Petersen, E. L.; Mortensen, N. G.; Landberg, L.; Hojsdtrup, J. and Frank H. P., (1997). Wind power meteorology. Risø National Laboratory, Denmark. Rummukainen, M., 2010: State-of-the-art with regional climate models, Wiley Interdiscipl Rev Climate Change, 1, 82-96 Spiridonov V., Somot S., Déqué M. (2005): ALADIN-Climate: from the origins to present date. ALADIN Newsletter n. 29 (nov. 2005) 49 Wang, Y., L. R. Leung, J. L. McGregor, D.-K. Lee, W.-C. Wang, Y. Ding, and F. Kimura, 2004: Regional Climate Modeling: Progress, Challenges, and Prospects. J. Meteor. Soc. Japan, 82, 1599–1628 WAMDI Group, 1988: The WAM model—A third generation ocean wave prediction model. J. Phys. Oceanogr., 18, 1776–1810 Weisse, R., H. von Storch, U. Callies, A. Chrastansky, F. Feser, I. Grabemann, H. Guenther, A. Pluess, T. Stoye, J. Tellkamp, J. Winterfeldt and K. Woth. (2009) Regional nkjmeteorological-marine reanalyses and climate change projections: Results for Northern Europe and potentials for coastal and offshore applications. Bull. Amer. Meteor. Soc., 90, 849-860. Weisse, R. and H. Günther, 2007: Wave climate and long-term changes for the Southern North Sea obtained from a high-resolution hindcast 1958-2002. Ocean Dyn., 57, 161–172. Weisse, R., and A. Pluess, 2006: Storm-related sea level variations along the North Sea coast as simulated by a high-resolution model 1958-2002. Ocean Dyn., 56, 16–25 Winterfeldt, J., (2008) Comparison of measured and simulated wind speed data in the North Atlantic. Ph.D. thesis, GKSS Research Center, GKSS Rep. 2008/2, 102 pp. [Available online at www.gkss.de/central _ deparents/library/publcations/report2008/index.html.de.] Winterfeldt, J. and R. Weisse, 2009: Assessment of value added for surface marine wind obtained from two Regional Climate Models (RCMs). Mon. Wea. Rev., 137, 2955-2965, doi:10.1175/2009MWR2704.1 Woolf, D.K., P.G. Challenor and P.D. Cotton. 2002. The variability and predictability of North Atlantic wave climate. Journal of Geophysical Research, 107, 3145, doi: 10.1029/2001JC001124. 50 Woolf, D.K., P.D. Cotton and P.G. Challenor. 2003. Measurements of the offshore wave climate around the British Isles by satellite altimeter. Philosophical Transactions: Mathematical, Physical & Engineering Sciences, 361, 27-31, doi: 10.1098/rsta.2002.1103 Woolf, D.K., C. Gommenginger, N. Sykes, M.A. Srokosz and P.G. Challenor. 2006. Satellite and other long-term data sets on wave climate; application to the North Atlantic region. Proceedings of World Renewable Energy Congress IX, MT11, Elsevier, ISBN 008 44671 X. 51