ENVISAT WIND AND WAVE PRODUCTS: MONITORING, VALIDATION AND ASSIMILATION

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1 ENVISAT WIND AND WAVE PRODUCTS: MONITORING, VALIDATION AND ASSIMILATION Peter A.E.M. Janssen (), Saleh Abdalla (), Jean-Raymond Bidlot (3) European Centre for Medium-Range Weather Forecasts, Shinfield Park, RG 9AX, Reading, UK. () () (3) ABSTRACT ENVISAT fast delivery RA- and ASAR wind and wave products are routinely received, monitored and validated at ECMWF. RA- wind speed product is of good quality. Although Ku-band significant wave height (SWH) product is slightly high, it is of high quality. The redundant side B of RA- produced SWH product of even better quality. The S-band wave height product is generally of good quality. The inverted ASAR Wave Mode Level b product agrees well with the wave model counterpart while Level product agrees well with the wave model in terms of swell wave height and mean period only. RA- Ku-band SWH and ASAR Wave Mode Level b products are assimilated in the ECMWF operational wave model. The assimilation has positive impact on model analysis and forecast.. INTRODUCTION On the th of February, the European Space Agency (ESA) launched the ENVISAT satellite that carries onboard 9 instruments, two of which are relevant for understanding of ocean waves, namely the RA- (Radar Altimeter ) and the ASAR (Advanced Synthetic Aperture Radar). Among other parameters, fast delivery (FD) wind and wave products from RA- and ASAR are routinely received, monitored and validated at the European Centre for Medium-Range Weather Forecasts (ECMWF) since late. First guess products from the ECMWF atmospheric and wave models together with available buoy and other in-situ measurements are used for this purpose. Full account of the monitoring and verification activities of these products at ECMWF was already presented by, for example, [] and []. The main conclusions of those reports are summarised as follows. In general, RA- wind speed product is of acceptable quality since early April 3. It will be shown here that it started to be of better quality after the implementation of RA- Instrument Processing Facility (IPF) Version. in October. Although Ku-Band significant wave heights are slightly (3-%) high, they have been of high quality since the beginning (see [], [] and [3]). The S-band wave height product is generally of acceptable quality except for a number of clearly wrong outliers during what is known as RA- S-Band Anomaly. Most of those outliers can be removed when applying stricter quality control based on the comparison between Ku- and S- band backscatter coefficients. Experiments involving the assimilation of the Ku-band SWH product revealed the positive impact it has on the wave model analysis and forecast (see []). This led to the operational assimilation of this product at ECMWF wave model in October 3. It was also shown by [] and [] that the ASAR Wave Mode Level b (ASA_WVS_P) product, which is inverted in-house to obtain the ocean wave spectra, agrees well with the wave model counterpart in terms of all used integrated parameters. On the other hand, ASAR Wave Mode Level Ocean Wave Spectrum (ASA_WVW_P) product agrees well with the wave model in terms of swell significant wave height and mean period. The agreement is not so good for any other parameters describing the spectral shape.. STATUS OF THE RA- PRODUCTS In general, the quality of the RA- near-real time (NRT) products stayed good as usual. The global comparisons between RA- and buoy products during the period from November to 3 October are shown in Fig. for the surface wind speed, in Fig. for the Ku-band SWH and in Fig. 3 for the S-band SWH. It should be noted that most of the buoy measurements are in the Northern Hemisphere (NH). Recently there were several events which had some impact on the quality of the RA- wind and wave products. Two events are considered here. The first is the implementation of the NRT RA/MWR Level b and Level IPF Version. processing chain on October. The second is the anomalous behaviour of the RA- Ultra Stable Oscillator (USO) on 3 March and the consequent events of switching to the redundant Proc. Envisat Symposium 7, Montreux, Switzerland 3 7 April 7 (ESA SP-3, July 7)

2 side (Side B) of the Radio Frequency Module (RFM) and then back to the nominal side (Side A). ENVISAT WINDSPEEDS (M/S) BUOY WINDSPEEDS (M/S) MEAN BUOY MEAN ENVISAT BIAS (ENVISAT - BUOY) Figure : Global comparison between RA- and buoy surface wind speed products during the period from November to 3 October (mainly in the NH). ENVISAT (KU) WAVEHEIGHTS (M) BUOY WAVEHEIGHTS (M) MEAN BUOY MEAN ENVISAT BIAS (ENVISAT - BUOY) Figure : Global comparison between RA- Ku-band and buoy SWH values during the period from November to 3 October (mainly in the NH). ENVISAT (S) WAVEHEIGHTS (M) BUOY WAVEHEIGHTS (M) MEAN BUOY MEAN ENVISAT BIAS (ENVISAT - BUOY) Figure 3: Global comparison between RA- S-band and buoy SWH values during the period from November to 3 October (mainly in the NH). After the implementation of the NRT RA/MWR Level b and Level IPF Version. processing chain on October, the wind product became better than before. This was due to the change of the algorithm used for the surface wind speed (see [] and []). The impact can be well displayed in Figs. and. The time-series of the global wind speed difference (bias) between RA- and ECMWF model since November for the last three years is shown in Fig.. While the bias values during the first two years were more or less the same (around -. m/s), the bias for the same period starting in (after the implementation of IPF Ver..) has moved up by about. m/s (to a positive bias value of about.3 m/s). Similar plot but for the the global standard deviation of the difference (SDE) is shown in Fig.. While the SDE of the years starting in November 3 and was as high as. m/s for most of the year, it was fluctuating around.3 m/s during the last year. More account of the change in the RA- wind speed product and its current status can be found in [] and [7]. Wind Speed Bias (m s - ) Days since November each year Figure : Time-series of the global wind speed difference (bias) between RA- and ECMWF model since November of years 3 (green), (blue) and (red). Wind Speed St. Deviation of Difference (m s - ) Days since November each year Figure : As in Fig. but for the standard deviation of the difference (SDE). The second major event was the anomalous behaviour of RA- USO in March. This anomaly forced the configuration of RA- RFM to its redundant Side B on May. This was followed by a switching back to the instrument nominal Side A on June due to an abrupt drop in the Side B S-band transmission power. It should be noted that the USO anomaly lasted for about a year as it disappeared on March 7. The USO anomaly did not have any impact on RA- wind and wave products.

3 While the RA- configured to its redundant Side B between May and June, the disseminated NRT RA- products were contaminated by a configuration bug affecting their processing. Irrespective of this bug, the SWH product was the best ever. Fig. shows the time series of the daily global SWH bias (defined as the difference between RA- and the model) and standard deviation of difference between RA- Ku-band and the ECMWF model first-guess during the entire months of May and June. The better agreement between the altimeter and the model SWH products cannot be missed. This was supported by the comparison between the RA- and the buoy SWH products (not shown). On the other hand, the wind speed product from Side B was almost of the same quality as the nominal product although it is possible to detect a week signal that Side B wind product may be slightly better as can be seen in Fig. 7. Since all of the S-band products were rejected after the drop of the S-band transmition power, there was no enough data to make any definite statement regarding the S-band SWH product. SWH Bias (m) and SDE (m) SDE Bias S i d e B Figure : Time series of the daily global significant wave height bias ( ) and standard deviation of difference, SDE, (- - -) between RA- Ku-band and the ECMWF model first-guess during the entire months of May and June. U Bias (m s - ) and SDE (m s - ) S i d e B SDE Bias Figure 7: Time series of the daily global surface wind speed bias ( ) and standard deviation of difference, SDE, (- - -) between RA- and the ECMWF model analysis during the entire months of May and June STATUS OF THE ASAR PRODUCTS Validation of wave spectra with large number (several hundreds) of degrees of freedom is not a straightforward task. Therefore, the validation is usually done in terms of a limited number of integrated parameters like the significant wave height (SWH), the mean wave period (MWP) and the wave spectral peakedness factor of Goda (WPF) as defined in []. SWH is the most commonly used parameter for typical validation of ocean wave products. Fig. shows a density scatter plot for globally collocated SWH pairs of inverted ASAR Wave Mode Level b and the analysis ECMWF wave model for a one year period from November. It is clear that the agreement between the ASAR and the model is quite good with ASAR slightly underestimating wave heights (by about cm). The global scatter index (defined as the standard deviation of the difference between the two data sets normalised by the mean of the reference data set) is about.%. Scatter plots of the MWP for the same period show even better agreement between the ASAR product and the wave model (not shown) with virtually no bias and very small scatter index (slightly less than %). On the other hand, the same can not be said about parameters describing the spectral shape such as WPF. Fig. 9 shows the globally collocated pekedness factor pairs of inverted ASAR Level b and the wave model analysis for the same period (November -October ). Although, there is a good agreement for most of the pairs with peakedness values less than about., the agreement does not hold anymore for higher values with a clear split into two families. The scatter index is rather high (~7%) while the correlation coefficient is rather low (~.). ASAR Sig. Wave Height (m) WAM Sig. Wave Height (m) MEAN ASAR Figure : Global comparison between inverted ASAR level b and ECMWF WAM model SWH during the period from November to 3 October. Long-term monitoring of the statistics resulting from the comparison of various integrated parameters from the inverted ASAR Level b and the wave model is usually carried out by inspecting the time-series similar to the one shown in Fig.. The various statistics did not changed during the last two years or so from what was shown in [] and [].

4 ASAR Peakedness Factor WAM Peakedness Factor MEAN ASAR Figure 9: Global comparison between inverted ASAR level b and ECMWF WAM model WPF during the period from November to 3 October Fig. shows a density scatter plot for globally collocated swell SWH pairs of ASAR Wave Mode Level and the wave model for a one year period starting from November. The agreement between the ASAR Level and the model is quite good for the bulk of the data. However, there are quite a number of outliers. The agreement becomes worse when the comparison is done in terms of the other parameters describing the spectral shape. For example, the globally collocated swell wave peakedness factor (WPF) pairs of ASAR Wave Mode Level and the wave model for the same period are shown in Fig.. One can clearly notice the poor agreement between the ASAR and the model. The ASAR mean value is about twice the model mean value. It indicates that the ASAR spectra are too narrow (i.e. more peaked) compared to the model (see [] for a possible explanation). Furthermore, the standard deviation of the difference is comparable with the ASAR mean value and larger than the model mean value (scatter index much higher than %). More importantly, there is almost no correlation between both quantities. WVW Swell Wave Height (m) MEAN WVW Mean Wave Period Bias (s) Global NH Tropics SH Jun 3 Sep 3 Dec 3 Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Figure : Time series of MWP bias between ASAR Level b inverted product and ECMWF wave model. The large bias shifts are described in [] and []. It is stressed that the integrated parameters used for the various comparisons between the ASAR Wave Mode Level (ASA_WVW_P) and the wave model products are computed for the part of the spectrum which is resolvable by the ASAR instrument. This means that wave components with wavelengths longer than the azimuthal cut-off wavelength reported in the official ASA_WVW_P product are used. The term swell is used for those parameters to reflect this fact. WAM Swell Wave Height (m) Figure : Global comparison between ASAR level (WVW) and ECMWF WAM model swell SWH during the period from November to 3 October. WVW Peakedness Factor WAM Peakedness Factor MEAN WVW Figure : Global comparison between ASAR level (WVW) and ECMWF WAM model swell WPF during the period from November to 3 October. As with Level b product, there was no change in the quality of the product during the last two years or so. For example, Fig. 3 shows the time-series of the scatter index time series of swell wave height over more than three years. It is clearly seen that there was no change during the last two years or so. Significant Wave Height Scatter Index Global NH Tropics SH Jun 3 Sep 3 Dec 3 Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Figure 3: Time series of swell SWH SI between ASAR Level product and the ECMWF wave model.

5 . ASSIMILATION OF ASAR LEVEL B In general, assimilation of ASAR Level b product into the wave model is not straightforward. The product needs to be inverted to remove the directional ambiguity and the nonlinear distortion. The resolved part of ASAR spectrum (i.e. with wavelengths above the azimuthal cut-off value) can be assimilated. The implemented assimilation procedure is based on the assimilation of wave systems as derived from a partitioning scheme. The spectrum is divided into several systems using the principle of the inverted catchment area (e.g. [9]). The different wave systems are characterised by their total energy, mean frequency and mean propagation direction. These integrated parameters are assimilated using a simple Optimum Interpolation (OI) scheme (see []) following a cross assignment procedure to correlate the observed systems with the modelled first-guess (FG) ones. The analysis (AN) integrated parameters obtained from the OI scheme are used to construct the AN spectra by resizing and reshaping the FG spectra. Several numerical experiments were carried out to assess the impact of ASAR Wave Mode Level b assimilation. Fig. shows the mean impact over the whole month of April compared to the in-situ buoy wave spectra. In general the impact is positive although rather limited (compared to altimeter assimilation for example; e.g. []). ASAR Level b product has been assimilated in the ECMWF wave model since February.. CONCLUSIONS ENVISAT fast delivery RA- and ASAR wind and wave products are routinely received, monitored and validated at ECMWF. RA- wind speed product is of good quality. Its quality was enhanced after the implementation of the NRT RA-/MWR Level b and Level IPF Version. in October. Although Ku-band significant wave height (SWH) product is slightly high, it is of high quality. The S-band wave height product is generally of good quality after filtering out the erroneous products contaminated with the S-band anomaly. The RA- USO anomaly during the period from March to March 7 had no impact on the RA- wind and wave products. Irrespective of a configuration bug, the redundant side B of the RA- instrument produced (in May and June ) products of even better quality especially for Ku-band SWH. The inverted ASAR Wave Mode Level b product agrees well with the wave model counterpart while Level product agrees well with the wave model in terms of swell wave height and mean period only. There was no change in the quality of ASAR Wave Mode products during the last two years or so. Bias = model - buoy (m) Normalised St. Deviation of Error Wave Period (s) ENVISAT ASAR ERS- SAR. Wave Period (s) ENVISAT ASAR ERS- SAR Figure : ASAR assimilation impact on wave spectrum according to buoy data around Hawaii in terms of equivalent -s SWH (- April ). RA- Ku-band SWH and ASAR Wave Mode Level b products are assimilated in the ECMWF operational wave model. The assimilation has positive impact on model analysis and forecast. ACKNOWLEDGMENTS This work was carried out with ESA support through ESA contract No. 7 (Global Validation of Envisat Data Products). REFERENCES. Abdalla, S. and Janssen, P.A.E.M. (). Global Validation of ENVISAT RA- Wind and Wave, and MWR Products. Proc. of the ENVISAT-ERS Symposium, Salzburg, Austria, - September.. Abdalla, S. (). Global Validation of ENVISAT Wind, Wave and Water Vapour Products from RA-, MWR, ASAR and MERIS, ECMWF Final Report for ESA contract 7, 7 p. Available online at: publications/

6 3. Janssen, P.A.E.M., Abdalla, S. and Hersbach, H. (3). Error Estimation of Buoy, Satellite and Model Wave Height Data. ECMWF Tech. Memo.. Available online at: Abdalla, S. Bidlot, J.-R. and Janssen, P. (). Assimilation of ERS and ENVISAT Wave Data at ECMWF. Proc. of the ENVISAT-ERS Symposium, Salzburg, Austria, - September.. Abdalla, S. Bidlot, J.-R. and Janssen, P. (). Global Validation and Assimilation of ENVISAT ASAR Wave Mode Spectra. Advances in SAR Oceanography from ENVISAT and ERS Missions (SEASAR ), ESA-ESRIN, Frascati, Italy, 3- January. Available online at: Abdalla, S. (7a). Ku-Band Radar Altimeter Surface Wind Speed Algorithm, ECMWF Tech. Memo.. ECMWF, Reading, UK. Available online at: publications/ 7. Abdalla, S. (7b). Ku-Band Radar Altimeter Surface Wind Speed Algorithm, Proc. of the ENVISAT Symposium 7, Montreux, Switzerland, 3-7 April 7.. Janssen, P.A.E.M. (7). On the Nonlinear Mapping of a Surface Gravity Wave Spectrum into a SAR Image Spectrum and Freak Wave Detection, Proc. of the ENVISAT Symposium 7, Montreux, Switzerland, 3-7 April Hasselmann, S., Lionello, P., and Hasselmann, K. (997). An Optimal Interpoltion Scheme for the Assimilation of Spectral Data. J. Geophys. Res.,, Lionello, P., Gunther, H. and Janssen, P.A.E.M. (99). Assimilation of Altimeter Data in a Global Third Generation Model, J. Geophys. Res., 97, 3-7.