Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were u...

Current understanding of the behaviour of sea breezes in the offshore environment is limited but rapidly requires improvement due, not least, to the expansion of the offshore wind energy industry. Here we report on contrasting characteristics of three sea-breeze types on five coastlines around the southern North Sea from an 11 year model-simulated climatology. We present and test an identification method which distinguishes sea-breeze types which can, in principle, be adapted for other coastlines around the world. The coherence of the composite results for each type demonstrates that the method is very effective in resolving and distinguishing characteristics and features. Some features, such as jets and calm zones, are shown to influence offshore wind farm development areas, including the sites of the proposed wind farms up to 200 km offshore. A large variability in sea-breeze frequency between neighbouring coastlines of up to a factor of 3 is revealed. Additionally, there is a strong association between sea-breeze type on one coastline and that which may form coincidentally on another nearby. This association can be as high as 86% between, for example, the North Norfolk and East Norfolk coasts. We show, through associations between sea-breeze events on coastlines with contrasting orientations, that each coastline can be important for influencing the wind climate of another. Furthermore, we highlight that each sea-breeze type needs separate consideration in wind power resource assessment and that future larger turbines will be more sensitive to sea-breeze impacts.

Background and Aims: From 2004 to 2013, the vineyard area in the United Kingdom (UK) increased 148%. Observed climate change and underlying weather variability were assessed for their influence on the development and viability of UK viticulture. Methods and Results: The perspectives of grapegrowers in the UK on climate change and weather variability were complemented by a quantitative analysis of climate and weather data for the main UK viticultural regions. The variability of growing season average temperature (GST) was calculated and also mapped using a modelling approach. Since 1993, GST has consistently been above the 13°C cool climate viticulture threshold. Alone, GST does not reliably assure yield predictability but does correlate more closely following the recent increasing UK focus on sparkling wine cultivars. June precipitation demonstrates the strongest relationship with yield. Conclusions: Increasing GST superficially suggests enhanced UK cool climate viticultural opportunities, but critically masks the additional impact of shorter term temperature and precipitation events and a high degree of inter-annual variability that continues to threaten productivity. A recent change in dominant UK vine cultivars appears to have increased viticultural sensitivity to interannual weather variability. Significance of the Study: This first quantitative and qualitative analysis of climate vulnerability in UK viticulture identifies threats and opportunities and helps steer studies of the impact of future climate change.

The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s-1 offshore gradient wind, from 0 km to 21 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes respectively. The corkscrew type restricts the development of a backdoor sea breeze on the opposite coast and is also capable of traversing a 100 km offshore domain even under high along-shore gradient wind speed (>15 m s-1) conditions. Realistic variations in sea surface skin temperature and initializing vertical thermodynamic profile do not significantly alter the resulting circulation, though the strengths of the simulated sea breezes are modulated if the effective land-sea thermal contrast is altered. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of both assessments of the offshore wind energy climate and forecasts of wind energy output

The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the Southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the <i>pure</i> and the little known <i>corkscrew</i> and <i>backdoor</i> sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that <i>pure</i> sea breezes, in contrast to <i>corkscrew</i> and <i>backdoor</i> types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a <i>pure</i> sea breeze produced in a 2 m s^&minus;1 offshore gradient wind, from 10 km to 40 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes, respectively. The <i>corkscrew</i> type restricts the development of a <i>backdoor</i> sea breeze on the eastern coast and is also capable of traversing a 100 km offshore domain even under high gradient wind speed (>15 m s^&minus;1) conditions. Realistic variations in sea surface skin temperature during the sea breeze season do not significantly affect the circulation, suggesting that a thermal contrast is only needed as a precondition to the development of the sea breeze. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of assessments of the offshore wind energy climate

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