Winds 1

A comprehensive database with ocean wind fields has been built up at the Technical University of Denmark (DTU) through consistent processing of Synthetic Aperture Radar (SAR) observations from Envisat (2002-12) and Sentinel-1 (2014-present). The archived wind fields cover the European seas up to 100 km from the coastline. They can be seen as a series of snapshots showing the instantaneous wind conditions for the areas most relevant for offshore wind power generation. Through statistical processing, these instantaneous snapshots are combined to give maps of the offshore wind resources for the standard output level of 10 m above the sea surface. This presentation demonstrates the effects of two recent improvements related to satellite-based wind resource mapping:

1)      The number of satellite samples has increased dramatically since the launch of Sentinel-1A/B

2)      A new method looks promising for routine extrapolation of wind fields to the height of modern wind turbines

At DTU, wind maps are retrieved in near-real-time from ESA’s L1 SAR products using the SAROPS processing tool developed by the US National Oceanic and Atmospheric Administration (NOAA). The geophysical model function CMOD5.N is used to obtain the equivalent neutral wind speed. A correction is applied to compensate for lower radar backscatter at HH polarization compared to VV polarization. Ancillary data used for the SAR-wind processing include wind directions from the Global Forecast System (GFS) and ice mask data from the US National Ice Center.

Once the instantaneous wind maps are stored in our database, they can be organized as time series in order to calculate wind resources for any point location or area. Since the time series comprises data from both Envisat and Sentinel-1, a check of the data calibration against one or more independent data sources is needed. Based on the calibrated time series, a Weibull fit is made to calculate the mean wind speed, Weibull scale and shape parameters, and the wind power density. The spatial grid of the output wind resource maps is 0.02 degrees in latitude and longitude.

To extrapolate the 10-m wind resource maps from SAR to higher levels within the atmospheric boundary layer, we estimate a wind profile for each grid cell in the maps. Simulations from the Weather Research and Forecasting (WRF) model are used to correct this profile for long-term atmospheric stability effects. Accounting for atmospheric stability allows us to estimate the wind speed at different levels with greater accuracy compared to methods that assume a neutral atmospheric boundary layer. For the Northern European seas, the inclusion of atmospheric stability increases the mean wind speed at 100 m on the order of 0.5m/s.

The SAR-based wind resource maps are used in the New European Wind Atlas – an EU-funded project where European nations work together to produce an updated and validated wind atlas for Europe.

Recent work has shown that, in contrast to global numerical weather prediction models, space-borne scatterometers are able to resolve the increased wind variability near convection areas. This unique capability is essential for climate applications, since wind variability directly impacts air-sea fluxes and, as such, air-sea interaction.

In the present work westudyocean winds in heavy rain events occurring in Mesoscale Convective Systems (MCSs) in the Tropical Atlantic using ocean winds measured a short time apart at the same latitude and longitude.This is made possible by the ASCAT tandem mission (ASCAT-A and ASCAT-B pass over the tropics with overlapping swaths and a time difference of 50 minutes) and Meteosat Second Generation (MSG) precipitation time series (every 15 minutes) collocated with the ASCAT-A and B collocations..

We show that the ASCAT derived surface divergence and vorticity fields contain small scale structures with large spatial gradients (conveniently characterized using Singularity Analysis) which we interpret as strong updraft and downdraft events.The strength of these events varies in response to the precipitation. Our objective is to quantify this change and to compare with similar results obtained for ECMWF background and 2DVAR analysis winds. 

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission provides multi-angular L-band brightness temperature images of the Earth. Because upwelling radiation at 1.4 GHz is significantly less affected by rain and atmospheric effects than at higher microwave frequencies, the SMOS measurements offer unique opportunities to complement existing ocean satellite high wind observations in tropical cyclones and severe weather that are often erroneous in such conditions. The physical basis for surface wind speed retrievals in extreme weather from passive microwave radiometers involves emission from a rough, foam-covered sea surface. The objective of the SMOS STORM STSE project is to exploit the identified capability of SMOS satellite Brightness Temperatures acquired at L-band to monitor wind speed and whitecap statistical properties beneath Tropical Cyclones and severe Extra Tropical storms.

In this talk, we will present the status of the ESA project called SMOS+STORMS Evolution started in April 2014 for a period of 2 years which aim is to Demonstrate the performance, utility and impact of SMOS L-band measurements at high wind speeds over the ocean during Tropical and Extra-Tropical storm conditions.  We will present in detail new developments of a Geophysical model function for wind speed retrieval from L-band ocean surface brightness temperature contrasts. The capability of such new data for infering structural properties of the wind and wave 2D fields in TC, as well as the monitoring of their intensity will be demonstrated. The 5 years-long archive of storms as seen in the  L-band SMOS high wind speed products, their validation,  the developments of new blended multi-mission oceanic wind speed products in storms (SMOS-AMSR-2-SMAP), and the use of these products for air-sea interaction studies and maritime applications will be illustrated. 

An increasing amount of users uses scatterometer wind and stress data for climate studies. However, the stress-equivalent wind retrieval algorithms have been continuously improved over the years and the currently existing archives of near-real time data are not always suitable to fulfil the need for homogeneous data sets spanning a longer period of time. Currently only few validated vector wind and stress climate data sets are available. Therefore, the EUMETSAT OSI SAF plans to re-process the following off-line data sets:

Metop-A ASCAT stress-equivalent wind vectors (U10S), ice probabilities, 2007-2015, data set to become available in 2015;

QuikSCAT SeaWinds U10S, ice probabilities, 1999-2009, data set to become available in 2015;

ERS-1 and ERS-2 U10S, 1991-2000, availability depending on the ESA SCIROCCO project to provide consistency between ERS and ASCAT backscatter records, data set to become available in 2016;

Oceansat-2 OSCAT U10S, 2009 to 2014, data set to become available in 2016.

The characteristics and data formats of the products will be the same as their NRT equivalents but the data sets will be processed with the newest algorithms and with fully calibrated input data. Both level 2 swath data and level 3 and level 4 gridded data will become available. Sea ice probabilities will also be produced as part of the Bayesian ice screening in the wind processing.

Maximum product quality and stability will be guaranteed. The use of NWP Ocean Calibration ensures precise intercalibration between different instruments and provides consistent ocean backscatter that may be used in standard C and Ku-band stress-equivalent wind retrieval at KNMI. The products will be monitored and validated against collocated ECMWF ERA-Interim model U10S and in situ buoy U10S using automated procedures, including triple collocation analysis. The effect of instrument sampling errors on monthly climatologies is assessed and time-continuous scatterometer-enhanced ERA fields are put available.The qualities and application of these products will be discussed at the symposium.

The EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) produces near-real time scatterometer winds already since the beginning of its existence. Data from the European Remote Sensing satellites (ERS-1 and ERS-2 scatterometer), QuikSCAT (SeaWinds), Metop (ASCAT), Oceansat-2 (OSCAT) and RapidScat on the International Space Station have been or are produced. The OSI SAF scatterometer products provide superior comparison to both buoy and Numerical Weather Prediction (NWP) data sets. Moreover, the wind processing software is freely available through the EUMETSAT NWP SAF.