Nicholas P. Klingaman

The impacts of the Madden-Julian Oscillation (MJO) on the South American monsoon season (December-February) and possible changes during El Niño (EN) and La Niña (LN) events are analyzed in the UK Met Office Unified Model Global Ocean Mixed Layer configuration (MetUM-GOML3). Experiments sixty years long, with and without El Niño-Southern Oscillation (ENSO), considering different spatial resolutions, are performed to assess if ENSO influences several MJO characteristics, including the teleconnections to South America (SA). Simulations without ENSO show: (i) an extratropical teleconnection triggered by enhanced convection in the central-east subtropical South Pacific (CSSP) and its strongest impact on central-east South American precipitation in phase 8, earlier than in observations (phase 1). (ii) An extratropical teleconnection, triggered by suppressed convection over the same region, with strongest impact on South American precipitation in phase 4, with opposite sign. (iii) Increased resolution enhances the MJO convection and the South American circulation-precipitation dipole. ENSO affects the basic state and the MJO convection, which modulate teleconnections to SA in simulations with ENSO cycles. EN (LN) strengthens (deteriorates) MJO propagation and its convection. However, both EN and LN produce enhanced convection over the CSSP in phase 8. The extratropical teleconnections and their impacts are stronger under ENSO with respect to those in simulations without ENSO. Hence, both simulated ENSO states generate forcing that more efficiently triggers teleconnections than simulations without ENSO, indicating nonlinear ENSO effects on MJO anomalies over SA.

A new regional coupled modelling framework is introduced – the Regional Coupled Suite (RCS). This provides a flexible research capability with which to study the interactions between atmosphere, land, ocean, and wave processes resolved at kilometre scale, and the effect of environmental feedbacks on the evolution and impacts of multi-hazard weather events. A configuration of the RCS focussed on the Indian region, termed RCS-IND1, is introduced. RCS-IND1 includes a regional configuration of the Unified Model (UM) atmosphere, directly coupled to the JULES land surface model, on a grid with horizontal spacing of 4.4 km, enabling convection to be explicitly simulated. These are coupled through OASIS3-MCT libraries to 2.2 km grid NEMO ocean and WAVEWATCH III wave model configurations. To examine a potential approach to reduce computation cost and simplify ocean initialization, the RCS includes an alternative approach to couple the atmosphere to a lower resolution Multi-Column K-Profile Parameterization (KPP) for the ocean. Through development of a flexible modelling framework, a variety of fully and partially coupled experiments can be defined, along with traceable uncoupled simulations and options to use external input forcing in place of missing coupled components. This offers a wide scope to researchers designing sensitivity and case study assessments. Case study results are presented and assessed to demonstrate the application of RCS-IND1 to simulate two tropical cyclone cases which developed in the Bay of Bengal, namely Titli in October 2018 and Fani in April 2019. Results show realistic cyclone simulations, and that coupling can improve the cyclone track and produces more realistic intensification than uncoupled simulations for Titli but prevents sufficient intensification for Fani. Atmosphere-only UM regional simulations omit the influence of frictional heating on the boundary layer to prevent cyclone over-intensification. However, it is shown that this term can improve coupled simulations, enabling a more rigorous treatment of the near-surface energy budget to be represented. For these cases, a 1D mixed layer scheme shows similar first-order SST cooling and feedback on the cyclones to a 3D ocean. Nevertheless, the 3D ocean generally shows stronger localized cooling than the 1D ocean. Coupling with the waves has limited feedback on the atmosphere for these cases. Priorities for future model development are discussed.

The East Asian summer monsoon (EASM) is a complex phenomenon, influenced by both tropical and mid-latitude dynamics and by the presence of the Tibetan Plateau. The EASM front (EASMF) separates tropical and extratropical air masses as the monsoon marches northwards. Although the different factors behind EASM progression are illustrated in a number of studies, their interactions, in particular between tropical and extratropical air masses, still need to be clarified. In this study we apply Eulerian and Lagrangian methods to the ERA5 reanalysis dataset to provide a comprehensive study of the seasonal progression of and interannual variability in the EASM, and we highlight the dynamics of the air masses converging at its front. A frontal detection algorithm is used to perform a front-centred analysis of EASM progression. The analysis highlights the primary role of the subtropical westerly jet (STWJ) and of the western North Pacific subtropical high (WNPSH) in controlling the strength and the poleward progression of the EASMF, in particular during Mei Yu, the primary stage of EASM progression. These forcings act to steer the southerly advection of low-level moist tropical air, modulated by the seasonal cycle of the Asian monsoon. The Mei Yu stage is distinguished by an especially clear interaction between tropical and extratropical air masses converging at the EASMF. The analysis of composites based on the latitude of the EASMF during Mei Yu reveals the influence exerted by the STWJ on the cool extratropical flow impacting on the northern side of the EASMF, whose progression is also dependent on the location of the WNPSH. In turn, this affects the extent of the warm moist advection on its southern side and the distribution and intensity of resultant rainfall over China. This study shows the validity of an analysis of EASM progression focused on its front and on the related low- and mid-level airstreams, at least in the Mei Yu stage. The framework highlighted shows how the regional flow over East Asia drives the low-level airstreams that converge at the EASMF, thus controlling the shape of EASM progression. This framework provides a basis for studies of climate variability and extreme events and for model evaluation.

A new regional coupled modelling framework is introduced – the Regional Coupled Suite (RCS). This provides a flexible research capability with which to study the interactions between atmosphere, land, ocean and wave processes resolved at km-scale, and the effect of environmental feedbacks on the evolution and impacts of multi-hazard weather events. A configuration of the RCS focussed on the Indian region, termed RCS-IND1, is introduced. RCS-IND1 includes a regional configuration of the Unified Model (UM) atmosphere, directly coupled to the JULES land surface model, on a grid with horizontal spacing of 4.4 km, enabling convection to be explicitly simulated. These are coupled through OASIS3-MCT libraries to 2.2 km grid NEMO ocean and WAVEWATCH III wave model configurations. To examine a potential approach to reduce computation cost, and simplify ocean initialisation, the RCS includes an alternative approach to couple the atmosphere to a lower resolution Multi-Column K Profile Parameterization (KPP) for the ocean. Through development of a flexible modelling framework, a variety of fully and partially coupled experiments can be defined, along with traceable uncoupled simulations and options to use external input forcing in place of missing coupled components. This offers a wide scope to researchers designing sensitivity and case study assessments. Case study results are presented and assessed to demonstrate the application of RCS-IND1 to simulate two tropical cyclone cases which developed in the Bay of Bengal, namely Titli in October 2018 and Fani in April 2019. Results show realistic cyclone simulations, and that coupling can improve the cyclone track and produces more realistic intensification than uncoupled simulations for Titli but prevents sufficient intensification for Fani. Atmosphere-only UM regional simulations omit the influence of frictional heating on the boundary layer to prevent cyclone over-intensification. However, it is shown that this term can improve coupled simulations, enabling a more rigorous treatment of the near-surface energy budget to be represented. For these cases, a 1D mixed layer scheme shows similar first-order SST cooling and feedback on the cyclones as a 3D ocean. Nevertheless, the 3D ocean generally shows stronger localised cooling than the 1D ocean. Coupling with the waves have limited feedback on the atmosphere for these cases. Priorities for future model development are discussed.

Land–atmosphere feedbacks, through water and energy exchanges, provide subseasonal‐to‐seasonal predictability of the hydrological cycle. We analyse subseasonal land–atmosphere coupling over South America (SA) during extended austral summer for the soil moisture‐to‐precipitation and soil moisture‐to‐air temperature feedback pathways. We evaluate subseasonal hindcasts from global forecasting systems from the UK Met Office, the National Centers for Environmental Prediction (NCEP), the European Centre for Medium Range Weather Forecasts and the Center for Weather Forecast and Climate Studies (CPTEC), for the common period of 1999–2010, against two reanalyses. Biases in land–atmosphere states are established in the first week of hindcasts and increase with lead time. By Week 5, all the models only demonstrate good performance over northern, northeastern and southeastern SA for soil moisture and evapotranspiration and over tropical and subtropical SA for temperature. The hindcasts show stronger coupling at longer lead–lag between variables than reanalyses. Our results highlight possible deficiencies in feedbacks between soil moisture and precipitation in CPTEC and NCEP forecasts over the Amazon due to initial dry soil moisture biases, and in feedbacks between soil moisture and temperature for all four investigated models over southeastern SA due to erroneous representations of evapotranspiration.

More frequent and stronger flood hazards in the last two decades have caused considerable environmental and socio‐economic losses in many regions of the Amazon basin. It is therefore critical to advance predictions for flood levels, with adequate lead times, to provide more effective and earlier warnings to safeguard lives and livelihoods. Water‐level variations in large, low‐lying, free‐flowing river systems in the Amazon basin, such as the Negro River, follow large‐scale precipitation anomalies. This offers an opportunity to predict maximum water levels using observed antecedent rainfall. This study aims to investigate possible improvements in the performance and extension of the lead time of existing operational statistical forecasts for annual maximum water level of the Negro River at Manaus, occurring between May and July. We develop forecast models using multiple linear regression methods, to produce forecasts that can be issued in March, February and January. Potential predictors include antecedent catchment rainfall and water levels, large‐scale modes of climate variability and the long‐term linear trend in water levels. Our statistical models gain one month of lead time against existing models for same skill level, but are only moderately better than existing models at similar lead times. All models lose performance at longer lead times, as expected. However, our forecast models can issue skilful operational forecasts in March or earlier. We show the forecasts for the Negro River maximum water level at Manaus for 2020 and 2021.