The role of air-sea interactions in sub-seasonal variability

Lead Research Organisation: University of Reading
Department Name: Meteorology


This fellowship aims to understand the mechanisms by which air-sea interactions control the development and intensification of high-impact weather extremes, and to improve the ability of numerical models to simulate those mechanisms.

Daily-monthly regional variations in weather and climate influence lives and livelihoods by affecting agriculture, hydrology and infrastructure. These sub-seasonal variations are controlled by high-impact phenomena including tropical cyclones; "blocking" high-pressure systems that cause droughts and heatwaves; and broad, organised areas of enhanced or reduced tropical thunderstorm activity that cause active and suppressed periods of monsoon rainfall.

Analysis of field and satellite observations has suggested that transfers of energy and moisture between the atmosphere and the sea surface influence the location and intensity of these phenomena. These transfers result in short-lived (1-2 weeks) changes to sea-surface temperatures (SSTs), which can influence the atmosphere; tropical thunderstorms tend to favour warmer waters, for example. It is not possible to distinguish forcing from response using observations alone, however, preventing understanding of how air-sea feedbacks influence sub-seasonal phenomena. Many short- and medium-range (1-14 days) forecasts use numerical models of only the atmosphere, neglecting potentially critical air-sea interactions. Atmosphere-ocean coupled models that represent these interactions are used for seasonal-to-decadal forecasts and climate-change projections, but often struggle to simulate sub-seasonal variability. These failings limit predictions of regional weather and extremes, create uncertainty in regional climate-change projections and prevent scientists from using these models to understand air-sea feedbacks.

These failings will be addressed through a novel modelling framework of an atmospheric model coupled to a simplified ocean model, which improves simulated short-lived SST variations; minimises errors in the model's mean climate that inhibit the simulation of high-impact phenomena; and allows air-sea feedbacks to be simulated in only certain regions of the globe or at certain times of year, to aid understanding of how these feedbacks influence high-impact phenomena. The framework will used with models from the Met Office, the European Centre for Medium-range Weather Forecasts and the Center for Multiscale Modelling of Atmospheric Processes (U.S.). Using models that differ considerably in their simulated high-impact phenomena permits more thorough testing of hypotheses about the impacts of air-sea interactions.

This framework allows the simulated effects of air-sea interactions on high-impact phenomena to be more cleanly separated from the effect of errors in the simulation of the mean climate. Previous studies have conflated these effects, creating uncertainty about the role of air-sea interactions in sub-seasonal variability. In this framework, variations among models in how high-impact phenomena respond to air-sea interactions will be caused only by variations in the formulations of the atmospheric models. This will inspire experiments to alter these formulations and investigate how the representation of key atmospheric processes, such as the relationship between atmospheric moisture and precipitation, affects the simulation of high-impact phenomena. Re-forecasts of past high-impact phenomena will allow close comparisons of simulations and observations and permit experiments that test the effects of individual processes. Experiments in which model errors in the simulated mean climate are introduced in particular regions, or times of year, will identify those errors that most inhibit sub-seasonal variability. This fellowship will improve understanding of air-sea interactions and their role in sub-seasonal variability, predictions of weekly-monthly variations in weather and climate, and regional projections of climate change.

Planned Impact

This fellowship will impact the U.K. Met Office (UKMO); international modelling centres using UKMO general circulation models (GCMs), including national weather services in Australia, India, Korea and Singapore; the European Centre for Medium-range Weather Forecasts (ECMWF); the insurance and energy-trading industries; the Australian government; and the general public.

The primary impacts of the fellowship will come through improvements in the representation of key aspects of tropical and extra-tropical variability in the GCMs employed in this project, which are used for daily--seasonal forecasting and climate projections. The sub-seasonal phenomena of interest are the Madden--Julian oscillation (MJO), monsoon intra-seasonal variability (ISV; active and break rainfall cycles) and extra-tropical blocking. The MJO and monsoon ISV cause floods and droughts throughout the tropics, including in India, Australia and southeast Asia; extra-tropical blocking is responsible for severe heatwaves and droughts in the Northern and Southern Hemisphere mid-latitudes.

The UKMO and ECMWF will benefit through improved assessments of the ability of their GCMs to simulate these key sub-seasonal phenomena, as well as through the identification of sources of GCM errors that hinder sub-seasonal prediction. Identifying and improving errors in the UKMO and ECMWF GCMs that degrade the representations phenomena will translate into improved sub-seasonal--seasonal prediction skill, as well as more reliable projections of the regional impacts of climate change, such as the statistics of droughts and floods.

International centres using UKMO models will benefit not only from the above improvements to the UKMO GCM, but also from the integration of the KPP modelling framework (used in this fellowship) into the UKMO modelling infrastructure. The framework is a powerful, flexible tool for understanding and predicting the impacts of local and remote air-sea interactions on regional, sub-seasonal weather and climate phenomena. The framework will be used in an international model inter-comparison, sponsored by the Working Group on Numerical Experimentation MJO Task Force, to diagnose the effects of air-sea interactions on the MJO, which demonstrates the framework's attractiveness for process-based understanding of weather and climate extremes. Research into and prediction of sub-seasonal variability globally will be enhanced by including the framework in the UKMO infrastructure.

The global insurance industry will benefit from financial savings through improved sub-seasonal and seasonal predictions of extreme weather and climate, such as floods and droughts, as well as more reliable projections of the impacts of climate change. Likewise, the energy-trading industry will benefit financially from improved forecasts of extreme weather that affect energy demand and supply from renewable sources (e.g., solar, wind).

The Australian government will benefit from improved predictions of summer-monsoon sub-seasonal variability, heatwaves and droughts that will allow them to implement more effective disaster-management strategies. The increased reliability of the projected impacts of climate change on extreme weather will inform the Australian's governments decisions on adaptation and mitigation, such as water management for irrigation and urban use.

The general public will benefit from financial savings from improved forecasting of regional weather and climate extremes, as well as from more effective decisions on adaptation and mitigation to climate change. The agricultural sector relies on UKMO and ECMWF forecasts to determine planting dates, as well as to mitigate and adapt to extreme events, such as heatwaves or droughts that can stress crops at critical stages during the growing season. Improved extended-range predictions and climate-change projections will allow forecast users to make better-informed decisions in response to extreme events.


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Description This fellowship had the following key achievements:

1. This fellowship advanced our understanding of week-to-week and month-to-month variations in tropical weather patterns, particularly the Madden-Julian Oscillation (MJO). The MJO is a tropical phenomenon that controls global weather patterns, including monsoons, mid-latitude jet streams and tropical cyclones. Research in this fellowship demonstrated how the development and strength of the MJO is controlled by year-to-year climate variations, such as El Nino and La Nina events, and by background variations in tropical moisture patterns.

2. Relatedly, this fellowship advanced our advanced our ability to simulate the MJO in weather and climate models, by demonstrating that the simulated MJO is sensitive to the simulated year-to-year climate variations and by the simulated background (climatological) model state. This revealed that improvements or degradations in a model's ability to simulate the MJO may not arise from changes to the MJO itself, but rather to changes in the background state, or even to sampling variability (i.e., using a single multi-decadal climate simulation to judge MJO performance is not robust).

3. This fellowship investigated the performance of sub-seasonal (2-6 weeks ahead) and seasonal (1-6 months ahead) forecasts of tropical rainfall and temperatures, particularly in Africa and South America. Research supported by this fellowship involved producing, and communicating, operational sub-seasonal and seasonal forecasts to governmental (DFID) and non-governmental (Red Cross) humanitarian agencies. Research on forecast performance included identifying and communicating "windows of opportunity" for more skilful (accurate) forecasts, such as during El Nino and La Nina events or in particular MJO phases.

4. This fellowship developed a novel atmosphere-ocean coupled modelling framework, for understanding and predicting tropical climate variability. This framework consists of an atmospheric model coupled to a high-resolution, one-dimensional ocean model. This fellowship applied the framework to weather and climate models from the Met Office, the National Center for Atmospheric Research (USA) and the European Centre for Medium-range Weather Forecasts. In climate simulations, the framework was used to understand how air-sea interactions on different timescales (e.g., synoptic, sub-seasonal, inter-annual), or in different ocean basins, affect a simulated phenomenon (such as the MJO in the examples above). In weather forecasts, the framework was used to understand how predictions of tropical phenomena, such as the MJO and tropical cyclones, can be improved by including atmosphere-ocean coupled feedbacks. For example, research with the Met Office weather model showed that incorporating air-sea interactions would improve tropical cyclone track forecasts in the western Pacific.

4. Research in this fellowship demonstrated the relationship between errors in daily mean rainfall in climate models, which have been frequently studied, and errors in the spatial and temporal organisation of sub-daily rainfall. This included developing diagnostics and metrics of spatial and temporal coherence and applying them to output from several climate models (including output at the model native timestep) and to output from sensitivity experiments of a single model, the Met Office climate model. The research concluded that the commonly disparaged "drizzle problem" in many models actually arises from overly intense, but infrequent, convection at the timestep level. This provided key information to model developers, primarily at the Met Office, that led to revisions to the sub-gridscale parameterisation of convection.
Exploitation Route The outcomes of this funding can be taken forward through:
1. Community use of the air-sea coupled modeling framework developed, both in the UK and US. This could be through use of the framework in operational forecasting (e.g., the Met Office are using this framework for high-resolution coupled weather forecasting in Southeast Asia) , or through process-based studies to explore the sensitivity of various phenomena (e.g., tropical cyclones, monsoons, persistent extratropical circulations) to regional or global atmosphere-ocean coupling or to variations in the background climate state (e.g., La Nina and El Nino events).

2. Use of the operational sub-seasonal and seasonal forecasting products, developed in this fellowship, by humanitarian agencies. The products developed in this fellowship are now issued operationally by the Met Office, as a continuing service to DFID and its partner non-governmental humanitarian agencies. The research related to sub-seasonal and seasonal forecast performance, both unconditional and conditional skill, also has applications to the use of sub-seasonal and seasonal predictions by energy and insurance companies.
Sectors Energy,Environment

Description Climate Briefing Notes
Amount £73,538 (GBP)
Funding ID 2215064 
Organisation Government of the UK 
Department Department for International Development (DfID)
Sector Public
Country United Kingdom
Start 09/2015 
Description Collaborative Research: Assessing Oceanic Predictability Sources for MJO Propagation
Amount $507,662 (USD)
Funding ID NOAA 
Organisation National Oceanic And Atmospheric Administration 
Sector Public
Country United States
Start 06/2016 
End 06/2020
Description Predicting Impacts of Cyclones in South-East Africa (PICSEA)
Amount £252,393 (GBP)
Funding ID NE/S005897/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 11/2018 
End 10/2020
Description Understanding air-sea feedbacks to the MJO through process evaluation of observations and E3SM experiments
Amount $1,030,932 (USD)
Organisation U.S. Department of Energy 
Sector Public
Country United States
Start 08/2019 
End 08/2022
Description World Meteorological Organization Travel Award
Amount CHF 860 (CHF)
Funding ID 20128686 
Organisation World Meteorological Organization 
Sector Public
Country Switzerland
Start 05/2015 
End 06/2015
Description CSU CMMAP Collaboration 
Organisation Colorado State University
Department Department of Atmospheric Science
Country United States 
Sector Academic/University 
PI Contribution My contribution to this collaboration involved coupling the multi-column configuration of the K Profile Parameterization (KPP) ocean model to the Super-Parameterized Community Atmospheric Model (SPCAM) provided by my partners. The resulting atmosphere-ocean coupled model is called SPCAM-KPP. I have performed a range of simulations with SPCAM-KPP aimed at understanding the roles of atmosphere-ocean interactions and the ocean mean state on tropical sub-seasonal variability, particularly the Madden-Julian oscillation.
Collaborator Contribution My partners provided the SPCAM atmospheric model, as well as technical assistance with implementing SPCAM on UK supercomputing facilities. They have also provided assistance with interpreting results from my SPCAM-KPP coupled simulations.
Impact The SPCAM-KPP coupled model is an output of this collaboration. This collaboration is not multi-disciplinary.
Start Year 2015
Description SPCAM-KPP comprises the Super-Parameterized Community Atmospheric Model (SPCAM), coupled to the multi-column implementation of the K Profile Parameterization (KPP) one-dimensional ocean model. SPCAM was developed previously by the Center for Multi-scale Modelling of Atmospheric Processes at Colorado State University. It is based on the National Center for Atmospheric Research Community Atmospheric Model (CAM), but replacing the conventional convective parameterization with a cloud-resolving model. Our work has been to couple SPCAM to the multi-column KPP model, which was developed at the National Centre for Atmospheric Science. The coupled model allows atmosphere-ocean interactions while maintaining a realistic ocean mean state through corrections to ocean temperature and salinity. 
Type Of Technology Software 
Year Produced 2015 
Impact SPCAM-KPP is being used to investigate the role of atmosphere-ocean interactions in the Madden-Julian oscillation (MJO), as well as other modes of tropical and extra-tropical sub-seasonal variability. SPCAM-KPP allows the effects of air-sea interactions to be cleanly separated from any changes in the basic state, as well as enabling sensitivity experiments to determine the impacts of air-sea interactions in particular ocean basins (e.g., the Indian Ocean, the Pacific Ocean). SPCAM-KPP is being used by scientists at the University of Reading, as well as at Colorado State University. The model underpins a collaborative research proposal between investigators at these two universities, submitted to the US National Oceanic and Atmospheric Administration.