826 Use of in situ observations to verify the diurnal cycle of sea surface temperature in ECMWF coupled model forecasts D. Salisbury, K. Mogensen & G. Balsamo Research Department November 2018 Series: ECMWF Technical Memoranda A full list of ECMWF Publications can be found on our web site under: http://www.ecmwf.int/en/research/publications Contact: [email protected] c Copyright 2018 European Centre for Medium-Range Weather Forecasts Shinfield Park, Reading, RG2 9AX, England Literary and scientific copyrights belong to ECMWF and are reserved in all countries. This publication is not to be reprinted or translated in whole or in part without the written permission of the Director- General. Appropriate non-commercial use will normally be granted under the condition that reference is made to ECMWF. The information within this publication is given in good faith and considered to be true, but ECMWF accepts no liability for error, omission and for loss or damage arising from its use. Diurnal cycle of SST Abstract At the European Centre for Medium-Range Weather Forecasts (ECMWF), coupling of the atmo- spheric model to an ocean model has recently been extended to the High-Resolution (HRES) fore- cast model. This move is driven by: (i) encouraging results in coupled Ensemble medium-range and extended-range forecasts; (ii) studies reporting a positive impact of coupling on the prediction of atmospheric events; and (iii) the need to better represent coupling feedbacks. As the lower atmo- spheric boundary condition over the ocean for the atmospheric model, the sea surface temperature (SST) field is key to this coupling. It is known that sub-daily variation in SST—its diurnal cycle— modulates air-sea exchange at the interface, and that resolving this variation can have a positive impact on the forecasting of both the upper ocean and the atmospheric state. In this work, we explore the diurnal cycle of SST in global coupled simulations with the ECMWF Integrated Forecast System (IFS). A year’s worth (March 1, 2015–March 1, 2016) of 10-day forecasts are run under coupled and then uncoupled model configurations: in the uncoupled runs, the (at depth) SST is based on the daily Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) field, with use of a prognostic scheme for the skin surface temperature; in the coupled runs the atmospheric model is coupled to the NEMO ocean model with a one-hour coupling frequency. The amplitude and phase of the diurnal cycle are validated against estimates from in situ oceanographic observations. We also explore the dependencies of the modelled diurnal cycle on key meteorological forcings (10-m wind speed and total cloud cover), and compare with the dependencies exhibited by the observations. 1 Introduction Sea surface temperature (SST) is a key parameter for weather and climate due to its influence on the state and evolution of the Earth’s atmosphere—via atmosphere-ocean interactions—and on ocean dynamics. Accurate SST data are a requirement for climate monitoring, prediction, and research. In addition, measurements or estimates of SST are used in the retrieval of other key ocean and atmosphere parameters from in situ and satellite-based instruments. SST has an important impact on the biogeochemistry of the ocean and is one of the most important physical properties of the marine ecosystem. One dominant mode of variation in SST is its diurnal variability. The daily progression of solar heating and subsequent surface- or mixing-driven cooling of the upper ocean is known as the diurnal cycle of SST. The diurnal cycle is an important feature of atmosphere-ocean interaction as many physical exchanges, including those of sensible and latent heat, and trace gases, are sensitive to the temperature of the ocean surface and its variation. For example, large diurnal warming can increase the heat flux from the ocean by 50–60 Wm−2 during the daytime (Ward, 2006; Fairall et al., 1996). Using data from moored buoys in the tropical Pacific, Zeng and Dickinson(1998) showed evidence of clear diurnal variability in surface latent and sensible heat fluxes. This variability could not be reproduced using daily or monthly mean sea surface skin temperature, SSTskin, suggesting that the diurnal cycle of skin temperature is the main driver of flux diurnal variability. Atmospheric General Circulation Models (AGCMs) often use as input SST analysis fields representing a bulk or foundation SST, constructed from satellite and in situ SST observations. Prognostic and diag- nostic schemes are typically used to represent diurnal SST variation (Fairall et al., 1996; Stuart-Menteth, 2003; Webster et al., 1996; Zeng and Beljaars, 2005; Takaya et al., 2010a; Filipiak et al., 2012) in the absence of an ocean model. Alternatively, the diurnal cycle of SST can be reproduced using an ocean- atmosphere coupled model with a short coupling interval, of roughly 1–3 hours, as long as the ocean component can adequately resolve the near-surface thermal structure. This approach has been used to assess the impact of the diurnal cycle on the atmosphere on sub-daily to intraseasonal timescales. Bernie et al.(2007) used a diurnally-forced ocean GCM to investigate the impact of resolving the diurnal cycle Technical Memorandum No. 826 1 Diurnal cycle of SST on the SST response to the Madden–Julian Oscillation (MJO). Across the Indo-Pacific, the diurnal cycle has been shown to increase the intraseasonal SST response to the MJO by around 20%. The diurnal cycle also modifies momentum exchange between currents, resulting in a 10% increase in the strength of Ekman cells and equatorial upwelling. In the second part of the study, Bernie et al.(2008) investigated the impact of a resolved ocean diurnal cycle on the climate simulations of a coupled GCM, showing that inclusion of the diurnal cycle leads to increase of the mean SST, with an increase of 0.2–0.3◦C across the equatorial Pacific. In turn, these changes had profound impact on up-scale variability in the tropi- cal climate. Other studies have linked the diurnal cycle of SST to convection over the Tropical Pacific (Johnson et al., 1999), to the diurnal cycle of precipitation (Dai and Trenberth, 2004), and shown that the SST diurnal cycle modulates the mean climate of atmospheric models (Brunke et al., 2008). In numerical weather prediction, coupled models traditionally show good skill in seasonal and monthly prediction, in particular in forecasting SST, the MJO, and the prediction of hurricanes and cyclones (Brassington et al., 2015). It is thought that part of this success is due to inclusion of diurnal SST variability, and that the increase in forecast skill could be seen in short- and medium-range forecasts, given the variable nature of air-sea interaction on even hourly time scales. McLay et al.(2012) report that inclusion of SST variation in the Navy Operational Global Atmospheric Prediction System improves medium-range forecast skill in the tropics, with a smaller impact in the midlatitudes. In the tropics, most of the increased skill was due to SST analysis perturbations rather than from inclusion of diurnal variability. The move to coupled forecasting systems at ECMWF is driven by improvement in the modelling of air-sea interaction processes, the development of ocean-atmosphere coupled data analysis, and use of coupled wave-sea-ice-atmosphere forecasts at all time ranges. Atmosphere-ocean coupling has recently been extended to the High-Resolution (HRES) forecast model (cycle 45r1). In preparation for such a move, it is important to quantify how well the diurnal cycle is represented in the coupled simulations. This study aims to verify the diurnal cycle in a coupled implementation of the ECMWF IFS model, and compare with results from an uncoupled implementation. The amplitude and phase of the diurnal cycle are validated against estimates from in situ oceanographic observations. We also explore the dependency of the modelled and observed diurnal cycle amplitude on key meteorological forcings of diurnal variabil- ity in SST—the 10-m wind speed and total cloud cover. In Section 2 we give an overview of the diurnal cycle and its representation in the ECMWF model. Model experiments and data are described in Section 3, and the methodology is outlined in Section 4. Results are given in Section 5, followed by discussion (Section 6) and conclusions (Section 7). 2 Background 2.1 Definition and measurement of sea surface temperatures Traditionally, the sea surface temperature observed from ships and buoys is reported as the “bulk” SST— the temperature at a depth of roughly 1 m or deeper (Donlon et al., 2007). Note that the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution SST Pilot Project (GHRSST-PP) Science Team recommends using SSTdepth rather than “bulk” SST; this is to avoid confusion relating to po- tential drastic changes in the bulk temperature with depth, and to encourage reporting of the depth of the temperature measurement. SSTbulk can differ markedly from the skin temperature (SSTskin) of the water in the top several microns 2 Technical Memorandum No. 826 Diurnal cycle of SST of depth. As the atmosphere senses only the interface of the ocean, SSTskin is of great importance as it represents the temperature closest to that of the interface. The skin temperature can be measured by in situ- or satellite-based radiometric instruments, although substantive effort is involved in quality control of the observations. Under most oceanographic and meteorological conditions, SSTskin is greater than a bulk temperature at depth, and shows larger diurnal variation due to the decrease in solar heating of the ocean surface boundary layer with depth. However, during the night, or under strong winds and with wave-induced mixing, the two temperatures can show little difference. Indeed, under such conditions—i.e., in the absence of a diurnal thermocline—SSTskin can be lower than SSTbulk due to the cool-skin effect (Fairall et al., 1996).