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Operational data assimilation systems for coupled atmosphere–ocean prediction are usually "weakly coupled", in which there is no explicit interaction between the atmosphere and ocean within the data assimilation step. Explicitly allowing for cross‐correlations between the ocean and the atmosphere may have potential benefits in improving the consistency of atmosphere and ocean analyses, as well as allowing a better use of observations at the interface. To understand whether such correlations are significant on the time‐scales of numerical weather prediction, we investigate the atmosphere–ocean cross‐correlations of short‐term forecast errors from the Met Office coupled prediction system, considering their temporal and spatial variability. We find that significant correlations exist between atmosphere and ocean forecast errors on these time‐scales, and that these vary diurnally, from day to day, spatially and synoptically. For correlations between errors in the atmospheric wind and ocean temperature, positive correlations in the North Atlantic region are found to be synoptically dependent, with correlation structures extending into the ocean throughout the deep mixed layer, beyond a depth of 100 m. In contrast, negative correlations over the Indian Ocean are very shallow and are associated with the diurnal cycle of solar radiation. The significance and variability of cross‐correlations indicates that there should be a benefit from including them in data assimilation systems, but it will be important to allow for some flow‐dependence in the correlations. Furthermore, the differing vertical extents of the cross‐correlations in different regions implies the need for situation‐dependent localisation of ensemble correlations when including them in coupled data assimilation systems. [ABSTRACT FROM AUTHOR]

Tropical cyclones tend to result in distinctive spatial and temporal characteristics in the upper ocean, which suggests that traditional, parametrisation‐based background‐error covariances in oceanic data assimilation (DA) may not be suitable. Using the case study of Cyclone Titli, which affected the Bay of Bengal in October 2018, we explore hybrid methods that combine the traditional covariance modelling strategy used in variational methods with flow‐dependent estimates of the ocean's error covariance structures based on a short‐range ensemble forecast. This hybrid approach is investigated in the UK Met Office's state‐of‐the‐art system. Single‐observation experiments in the ocean reveal that the hybrid approach is capable of producing analysis increments that are time‐varying, more anisotropic and vertically less uniform. When the hybrid oceanic covariances are incorporated into a weakly coupled DA system, the sea‐surface temperature (SST) in the path of the cyclone is changed, not only through the different specifications of background‐error covariances used in the SST assimilation, but also through the propagation of subsurface temperature differences to the surface as a result of vertical mixing associated with the cyclone's strong winds. The coupling with the atmosphere then leads to a discrepancy in the cyclone's central pressure, which brings forth further SST differences due to the different representations of the cyclone's emerging cold wake. [ABSTRACT FROM AUTHOR]

Daily initialized coupled and uncoupled numerical weather prediction (NWP) forecasts from the global Met Office Unified Model (MetUM) are compared for the 2016 Indian summer monsoon. Three MetUM configurations are used: atmosphere only (ATM), coupled to a mixed‐layer ocean model (KPP), and coupled to a dynamical ocean model (NEMO). The analysis focuses on the impact of air–sea coupling, particularly in the Bay of Bengal (BoB), on NWP for monsoon rainfall. Seasonal‐mean biases in all three configurations are highly consistent and driven by errors in atmospheric processes. Rainfall is initially overestimated over India, but underestimated over the BoB, the latter associated with too much short‐wave radiation and too little cloud cover in MetUM. The excess short‐wave radiation (>40 W·m−2 over the northwest BoB) is partially compensated by additional latent cooling, primarily due to overestimated surface wind speeds. In NEMO and KPP, coupling improves the timing of intraseasonal active and break phases over India, primarily the end of these phases, which are systematically too late in ATM. NEMO and KPP show a more realistic intraseasonal local phase relationship between sea surface temperature (SST) and rainfall throughout the BoB, but no configuration reproduces the observed significant lagged relationship between BoB SST and Indian rainfall. The lack of this relationship may be partly attributed to weak heat flux feedbacks to northern BoB SST, with the forecast short‐wave feedback having systematically the wrong sign (positive) compared to satellite radiation, and thus contributing to SST warming at all lead times. Based on these MetUM forecasts, there is a limited impact of coupling on NWP for monsoon rainfall, both for the mean rainfall and intraseasonal variability. Further research to improve NWP for monsoon rainfall should focus on reducing MetUM atmospheric systematical biases. [ABSTRACT FROM AUTHOR]

This study introduces a new flow‐dependent distribution sampling (FDDS) scheme for air–sea coupling. The FDDS scheme is implemented in a climate model and used to improve the simulated mean and variability of atmospheric and oceanic surface fields and thus air–sea fluxes. Most coupled circulation models use higher resolutions in the sea ice and ocean compared to the atmospheric model component, thereby explicitly simulating the atmospheric subgrid‐scale at the interface. However, the commonly applied averaging of surface fields and air–sea fluxes tends to smooth fine‐scale structures, such as oceanic fronts. The stochastic FDDS scheme samples the resolved spatial ocean (and sea ice) subgrid distribution that is usually not visible to a coarser‐resolution atmospheric model. Randomly drawn nodal ocean values are passed to the corresponding atmospheric boxes for the calculation of surface fluxes, aiming to enhance surface flux variability. The resulting surface field perturbations of the FDDS scheme are based on resolved dynamics, displaying pronounced seasonality with realistic magnitude. The AWI Climate Model is used to test the scheme on interannual time‐scales. Our set‐up features a high ocean‐to‐atmosphere resolution ratio in the Tropics, with grid‐point ratios of about 60:1. Compared to the default deterministic averaging, changes are largest in the Tropics leading to an improved spatial distribution of precipitation with bias reductions of up to 50%. Enhanced sea‐surface temperature variability in boreal winter further improves the seasonal phase locking of temperature anomalies associated with the El Niño–Southern Oscillation. Mean 2m temperature, sea ice thickness and concentration react with a contrasting dipole pattern between hemispheres but a joint increase of monthly and interannual variability. This first approach to implement a flow‐dependent stochastic coupling scheme shows considerable benefits for simulations of global climate, and various extensions and modifications of the scheme are possible. [ABSTRACT FROM AUTHOR]

We examine the merit of atmosphere–ocean coupled models for tropical cyclone (TC) predictions in the western North Pacific (WNP), where accurate TC predictions remain challenging. The UK Met Office operational atmospheric global numerical weather prediction (NWP) model is compared with two trial coupled configurations, in which the operational atmospheric model is coupled to a one‐dimensional mixed‐layer ocean model and a three‐dimensional dynamical ocean model. Reforecasts for the 2016 TC season show that the coupled models outperform the NWP model for TC location predictions, with a systematic improvement of 50–100 km over the seven‐day forecasts, but the coupled models amplify the underestimation of TC intensity in the NWP model. Nearly identical TC predictions (for both location and intensity) are found in the two coupled models, indicating the dominance of thermodynamic processes at the air–sea interface for TC predictions on these timescales. The improved prediction of the TC position in the coupled models is associated with an enhanced Western North Pacific Subtropical High (WNPSH), which introduces an anticyclonic steering flow anomaly that shifts TC tracks further west in the southern part of the region and further east in the northern part. Based on sensitivity experiments, we show that these improvements in the coupled models are due mainly to colder initial sea‐surface temperatures (SSTs). Air–sea feedbacks do not change the WNPSH or TC tracks noticeably. Apart from the effect of the initial SSTs, tropical ocean warming due to air–sea interaction in the coupled forecasts can also reduce the predicted TC intensity, presumably due to a stronger regional Hadley circulation with increased subtropical subsidence. [ABSTRACT FROM AUTHOR]

The Mediterranean Sea is an important source of heat and moisture for heavy precipitation events (HPEs). Moreover, the ocean mixed layer (OML) evolves rapidly under such intense events. Whereas short-term numerical weather prediction systems generally use low-resolution non-evolving sea surface temperature (SST), the development of high-resolution high-frequency coupled system allows us to fully take into account the fine-scale interactions between the low-level atmosphere and the OML which occur during HPEs. The aim of this study is to investigate the impact of fine-scale air-sea interactions and coupled processes involved during the HPEs which occurred during 12-15 October 2012 (IOP13) and 26-28 October 2012 (IOP16a/b) of the HyMeX first field campaign. For that purpose, the high-resolution coupled system AROME-NEMO WMED was developed. This system is based on the 2.5 km-resolution non-hydrostatic convection-permitting atmospheric model AROME-WMED and the 1/36°-resolution NEMO-WMED36 ocean model. The coupling frequency is 1 h. To distinguish the effects due to the change in the initial SST field from that due to the interactive 3D ocean, the coupled run is compared to two AROME-WMED atmosphere-only experiments with no SST evolution during the 48 h forecast cycles-one using the AROME-WMED SST analysis, the second using the SST field of the coupled experiment each day at 0000 UTC. The results of the three experiments re-assert that the SST initial condition strongly influences the HPE forecast, in terms of intensity and location. With water budget analyses, the significant impact of the ocean interactive evolution on the surface evaporation water supply for HPEs is also highlighted. In cases of strong and intense air-sea exchanges, as in the mistral event of IOP16b, the coupling reproduces the intense and rapid surface cooling and demonstrates the importance of representing the ocean turbulent mixing with entrainment at the OML base. [ABSTRACT FROM AUTHOR]

Heavy precipitation events (HPEs) can be a major cause of damage and casualties in the Mediterranean basin. With the use of atmosphere-ocean coupled regional climate models (AORCMs) and the advantage of 24 years of simulation (1989-2012), we identified regions with potential impact of submonthly air-sea coupling on HPEs from among the regions hit by heavy rain during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) first special observation period (SOP1): Valencia in Spain, the Cévennes in Southern France, Liguria in Northwestern Italy, Calabria in Southern Italy and Northeastern Italy. A first evaluation of the two AORCMs (MORCE and CNRM-RCSM4) against gridded precipitation datasets showed that 70-90% of the 30 most intense HPEs simulated were observed HPEs for most regions. The Cévennes, Valencia and Calabria were the only three regions to show a statistical relationship between rain differences and sea-surface temperature (SST) differences where the low-level jets that feed the events most frequently blow. This sensitivity of precipitation to SST changes is due to low-level wind changes related to changes in surface heat fluxes. Based on the calculation of submonthly variations in these regions during HyMeX, HPEs on 28 September 2012 and 12 October 2012 in Valencia and on 25-26 October 2012 in the Cévennes have most probably been affected by submonthly air-sea coupling. [ABSTRACT FROM AUTHOR]