A database containing sub-seasonal to seasonal forecasts from 11 operational 30 centres is available to the research community and will help advance our understanding of 31 the sub-seasonal to seasonal time range.Abstract 51 52Demands are growing rapidly in the operational prediction and applications communities for 53 forecasts that fill the gap between medium-range weather and long-range or seasonal 54

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high-and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

The intraseasonal variability of SST associated with the passage of the Madden–Julian oscillation (MJO) is well documented; yet coupled model integrations generally underpredict the magnitude of this SST variability. Observations from the Improved Meteorological Instrument (IMET) mooring in the western Pacific during the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) showed a large diurnal signal in SST that is modulated by the passage of the MJO. In this study, observations from the IOP of the TOGA COARE and a one-dimensional (1D) ocean mixed layer model incorporating the K-Profile Parameterization (KPP) vertical mixing scheme have been used to investigate the rectification of the intraseasonal variability of SST by the diurnal cycle and the implied impact of the absence of a representation of this process on the modeled intraseasonal variability in coupled GCMs. Analysis of the SST observations has shown that the increase of the daily mean SST by the diurnal cycle of SST accounts for about one-third of the magnitude of intraseasonal variability of SST associated with the Madden–Julian oscillation in the western Pacific warm pool. Experiments from the 1D model forced with fluxes at a range of temporal resolutions and with differing vertical resolution of the model have shown that to capture 90% of the diurnal variability of SST, and hence 95% of the intraseasonal variability of SST, requires a 3-h or better temporal resolution of the fluxes and a vertical grid with an upper-layer thickness of the order of 1 m. In addition to the impact of the representation of the diurnal cycle on the intraseasonal variability of SST, the strength of the mixing across the thermocline was found to be enhanced by the proper representation of the nighttime deep mixing in the ocean, implying a possible impact of the diurnal cycle onto the mean climate of the tropical ocean.

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The Madden-Julian oscillation (MJO) is a convectively coupled 30-70 day (intraseasonal) tropical atmospheric mode that drives variations in global weather but which is poorly simulated in most atmospheric general circulation models. Over the past two decades, field campaigns and modeling experiments have suggested that tropical atmosphere-ocean interactions may sustain or amplify the pattern of enhanced and suppressed atmospheric convection that defines the MJO and encourage its eastward propagation through the Indian and Pacific Oceans. New observations collected during the past decade have advanced our understanding of the ocean response to atmospheric MJO forcing and the resulting intraseasonal sea surface temperature fluctuations. Numerous modeling studies have revealed a considerable impact of the mean state on MJO ocean-atmosphere coupled processes, as well as the importance of resolving the diurnal cycle of atmosphere-upper ocean interactions. New diagnostic methods provide insight to atmospheric variability and physical processes associated with the MJO but offer limited insight on the role of ocean feedbacks. Consequently, uncertainty remains concerning the role of the ocean in MJO theory. Our understanding of how atmosphere-ocean coupled processes affect the MJO can be improved by collecting observations in poorly sampled regions of MJO activity, assessing oceanic and atmospheric drivers of surface fluxes, improving the representation of upper ocean mixing in coupled model simulations, designing model experiments that minimize mean state differences, and developing diagnostic tools to evaluate the nature and role of coupled ocean-atmosphere processes over the MJO cycle.

Idealized explicit convection simulations of the Met Office Unified Model exhibit spontaneous selfaggregation in radiative-convective equilibrium, as seen in other models in previous studies. This selfaggregation is linked to feedbacks between radiation, surface fluxes, and convection, and the organization is intimately related to the evolution of the column water vapor field. Analysis of the budget of the spatial variance of column-integrated frozen moist static energy (MSE), following Wing and Emanuel (2014), reveals that the direct radiative feedback (including significant cloud longwave effects) is dominant in both the initial development of self-aggregation and the maintenance of an aggregated state. A low-level circulation at intermediate stages of aggregation does appear to transport MSE from drier to moister regions, but this circulation is mostly balanced by other advective effects of opposite sign and is forced by horizontal anomalies of convective heating (not radiation). Sensitivity studies with either fixed prescribed radiative cooling, fixed prescribed surface fluxes, or both do not show full self-aggregation from homogeneous initial conditions, though fixed surface fluxes do not disaggregate an initialized aggregated state. A sensitivity study in which rain evaporation is turned off shows more rapid self-aggregation, while a run with this change plus fixed radiative cooling still shows strong selfaggregation, supporting a ''moisture-memory'' effect found in Muller and Bony (2015). Interestingly, selfaggregation occurs even in simulations with sea surface temperatures (SSTs) of 295 and 290 K, with direct radiative feedbacks dominating the budget of MSE variance, in contrast to results in some previous studies.

ABSTRACT:The role of coupled processes in the Madden-Julian Oscillation (MJO) is investigated in the European Centre for Medium-Range Weather Forecasts Monthly Forecasting System.A series of forecasts initialized daily for 47 days during the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) period are performed with sea surface temperatures (SSTs) provided by persistence of initial conditions, and coupling to either a full dynamical ocean model with vertical resolution in the upper ocean typical of coupled models (10 m), or, a 1D mixed layer ocean model with high (∼1 m) vertical resolution in the upper ocean.The experiment with the full dynamical model shows improved skill compared with the persisted SST experiment, indicating a role for coupled processes in the MJO. The experiment with the mixed layer model shows a further improvement in skill over the full dynamical ocean, particularly for the phases of the MJO where the convection is active over the Indian Ocean or West Pacific. This further improvement comes about from an enhanced sensitivity of the SST to the surface flux anomalies associated with the MJO.Additional sensitivity experiments reveal that the improved representation of the diurnal cycle which results from the increased vertical resolution is a significant factor in the improved skill of the experiments with the mixed layer model.