Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR) are sometimes visible and atmospheric and wake models are here shown to convincingly reproduce the observed very long wind farm wakes. The present study mainly focuses on wind farm wake climatology based on Envisat ASAR. The available SAR data archive covering the large offshore wind farms at Horns Rev has been used for geo-located wind farm wake studies. However, the results are difficult to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases, but not always, the second. In the new method all wind field maps are rotated such that the wind is always coming from the same relative direction. By applying the new method to the SAR wind maps, mesoscale and microscale model wake aggregated wind-fields results are compared. The SAR-based findings strongly support the model results at Horns Rev 1.

The ESA Earth Explorer CryoSat-2 was launched on 8 April 2010 to monitor the precise changes in the thickness of terrestrial ice sheets and marine floating ice. To do that, CryoSat orbits the planet at an altitude of around 720 km with a retrograde orbit inclination of 92^∘ and a quasi repeat cycle of 369 d (30 d subcycle). To reach the mission goals, the CryoSat products have to meet the highest quality standards to date, achieved through continual improvements of the operational processing chains. The new CryoSat Ice Baseline-D, in operation since 27 May 2019, represents a major processor upgrade with respect to the previous Ice Baseline-C. Over land ice the new Baseline-D provides better results with respect to the previous baseline when comparing the data to a reference elevation model over the Austfonna ice cap region, improving the ascending and descending crossover statistics from 1.9 to 0.1 m. The improved processing of the star tracker measurements implemented in Baseline-D has led to a reduction in the standard deviation of the point-to-point comparison with the previous star tracker processing method implemented in Baseline-C from 3.8 to 3.7 m. Over sea ice, Baseline-D improves the quality of the retrieved heights inside and at the boundaries of the synthetic aperture radar interferometric (SARIn or SIN) acquisition mask, removing the negative freeboard pattern which is beneficial not only for freeboard retrieval but also for any application that exploits the phase information from SARIn Level 1B (L1B) products. In addition, scatter comparisons with the Beaufort Gyre Exploration Project (BGEP; https://www.whoi.edu/beaufortgyre, last access: October 2019) and Operation IceBridge (OIB; Kurtz et al., 2013) in situ measurements confirm the improvements in the Baseline-D freeboard product quality. Relative to OIB, the Baseline-D freeboard mean bias is reduced by about 8 cm, which roughly corresponds to a 60 % decrease with respect to Baseline-C. The BGEP data indicate a similar tendency with a mean draft bias lowered from 0.85 to −0.14 m. For the two in situ datasets, the root mean square deviation (RMSD) is also well reduced from 14 to 11 cm for OIB and by a factor of 2 for the BGEP. Observations over inland waters show a slight increase in the percentage of good observations in Baseline-D, generally around 5 %–10 % for most lakes. This paper provides an overview of the new Level 1 and Level 2 (L2) CryoSat Ice Baseline-D evolutions and related data quality assessment, based on results obtained from analyzing the 6-month Baseline-D test dataset released to CryoSat expert users prior to the final transfer to operations.

Greenland Ice Sheet surface melting has increased since the 1990s, affecting the rheology and scattering properties of the near‐surface firn. We combine firn cores and modeled firn densities with 7 years of CryoVEx airborne Ku‐band (13.5 GHz) radar profiles to quantify the impact of melting on microwave radar penetration in West Central Greenland. Although annual layers are present in the Ku‐band radar profiles to depths up to 15 m below the ice sheet surface, fluctuations in summer melting strongly affect the degree of radar penetration. The extreme melting in 2012, for example, caused an abrupt 6.2 ± 2.4 m decrease in Ku‐band radar penetration. Nevertheless, retracking the radar echoes mitigates this effect, producing surface heights that agree to within 13.9 cm of coincident airborne laser measurements. We also examine 2 years of Ka‐band (34.5 GHz) airborne radar data and show that the degree of penetration is half that of coincident Ku‐band.

The aim of the paper is to present offshore wind farm wake observed from satellite Synthetic Aperture Radar (SAR) wind fields from RADARSAT-1/-2 and Envisat and to compare these wakes qualitatively to wind farm wake model results. From some satellite SAR wind maps very long wakes are observed. These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting (WRF) model in high resolution and WRF with coupled microscale parametrization.

CryoSat-2 (CS2) is the first mission equipped with a pulse-limited radar altimeter capable of operating in Synthetic Aperture Radar (SAR) Interferometric (SARIn) mode. Over ice sheets and ice caps, CS2 SARIn data have been used to retrieve surface elevations over an across-track ground ``swath.'' This work demonstrates that retracking multiple coherent peaks of CS2 SARIn waveforms, in combination with the interferometric phase, enables to obtain more than one valid height estimate from single SARIn waveforms over Arctic sea ice. For some SARIn waveforms, the scattering from sea ice at the satellite nadir is successfully separated from returns originating from off-nadir leads. An average bias of -1.8 cm is found for absolute sea ice elevations when using a 50% threshold retracker. It is shown that including multiple SARIn peaks and the associated phase difference in the processing does not introduce any bias on the average sea ice freeboard heights compared with the estimates from regular SAR processing schemes, while significantly increasing the number of valid sea surface height retrievals (+55%) and the number of freeboard estimates in the coastal domain and in multi-year ice regions (~3 times). This results in an average ~34% reduction of the gridded random freeboard uncertainty, corresponding to a ~20% reduction of the gridded total sea ice thickness uncertainty. The results of this work show that SARIn acquisitions over Arctic sea ice provide improved spatial coverage and denser sampling of sea level and sea ice freeboard compared with the SAR mode, with accuracy being largely driven by the retracking algorithm.