Second International Conference on Subseasonal to Seasonal Prediction (S2S) and
Second International Conference on Seasonal to Decadal Prediction (S2D)

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Day 1: Over 300 scientists gather to discuss subseasonal to decadal weather and climate predictions

Boulder, CO – Walter Orr, the first president of the University Corporation for Atmospheric Research (UCAR) and the founder of the National Center for Atmospheric Research (NCAR), was known for saying science in support of society, remarked Tony Busalacchi, the current president of UCAR. Busalacchi continued by saying that the subseasonal to seasonal (S2S) and seasonal to decadal (S2D) timescales are poised and ripe areas of research for the community to address the needs of society. This conference is aiming to do just that. Convening over 300 researchers from around the world, the conference will be used as a platform to discuss the latest science and exchange ideas to make advances to more seamless and skillful subseasonal to decadal predictions, which are useful to decision makers and stakeholders.

Gokhan Danabasoglu, NCAR, chaired the opening plenary, which included talks from many of the organizations working on the S2S and S2D topics, including the World Climate Research Programme (WCRP), World Meteorological Organization, World Weather Research Programme, NCAR, and the National Oceanographic and Atmospheric Administration (NOAA), among others. Additionally, specific projects were shown that emphasize some of the cutting edge research and collaboration being led by these organizations, including the S2S Prediction Project, the NOAA S2S Prediction Task Force and SubX projects, and the WCRP Decadal Climate Prediction Project and Working Group on Subseasonal to Interdecadal Prediction. 

Three invited speakers gave stage-setting talks. Tim Palmer, University of Oxford, reflected back on the past 40 years of the key successes across the range of initialized predictions on the subseasonal to decadal timescales. He noted that while process has been made, some current issues remain, including that some of the biases are an order of magnitude as that of the signals they are trying to predict. His hope for the future is the ability to look at model outputs and not be able to know if we are looking at a model or the real world. Arun Kumar, NOAA Climate Prediction Center, discussed the research needs for advancing operational S2D forecasting infrastructure. Current operational issues include the design of the configuration of operational S2D prediction systems and the science that provides the rational, development of products, communication of the forecasts, and the verification of the forecasts. While there is substantial diversity among operational systems, Kumar suggested that lagged ensembles have shown the potential for improving skill. Lisa Goddard, International Research Institute for Climate and Society at Columbia University, tied the research to applications by showing how prediction information has been used in real-world scenarios. For example, El Niño forecasts have been used to determine the seasonal flood potential in Somalia. They’ve also partnered with humanitarian organizations like the World Food Program to provide advance forecast information for emergency events (e.g., drought), so they can be more prepared, such as dispersing funds in advance. She noted that it is our job as a community to direct choices, particularly well-informed choices, that lead to appropriate and effective actions and decisions.

Over the week, two concurrent conferences will be taking place: the Second International Conference on Subseasonal to Seasonal Prediction and the Second International Conference on Seasonal to Decadal Prediction. Below are highlights from each of the conferences during the first day.

Subseasonal to Seasonal Conference Highlights

In the S2S portion, Andrew Robertson, IRI Columbia University, and Frédéric Vitart, ECMWF, chaired the opening session on “Mechanisms of S2S predictability.” Gilbert Brunet, Environment and Climate Change Canada, provided the keynote lecture on identifying wave processes associated with predictability across S2S timescales. Because S2S variability (such as the North Atlantic Oscillation (NAO), Madden-Julian Oscillation (MJO)) can influence high-impact weather, the community should characterize dynamical processes and predictability of S2S variability in reanalyses and reforecasting experiments, which is relevant for attribution studies. Brunet showed that it might be beneficial to see how well models can reproduce low-order adiabatic dynamics using Empirical Normal Mode analysis. 

Additional highlights include: 

• Due to the how fast the Earth system responds to initial conditions in models and how the definition of prediction inherently depends on the timescale, probabilistic/statistical prediction may, at times, be more beneficial than deterministic prediction at S2S timescales. (Zoltan Toth, NOAA Earth System Research Lab)
• Using the linear inverse model, after about three weeks the increased skill should be attributed to the El Niño-Southern Oscillation (ENSO) instead of the MJO, due to the longer term dynamics of ENSO in comparison to the MJO. This is because larger scale phenomena take longer to be affected by initial condition errors that amplify via instabilities. (Matt Newman, University of Colorado/CIRES & NOAA Earth System Research Lab)
• The strength of the Holton-Tan (H-T) relationship – a phenomenon in which the strength of northern stratospheric winter polar vortex synchronizes with the equatorial quasi-biennial oscillation – may not be robust based on the reanalysis ensemble. The members produce different flavors of the H-T relationship that are particularly sensitive to stratospheric sudden warmings during the quasi-biennial oscillation easterly phase. (Judith    Perlwitz, University of Colorado/CIRES & NOAA Earth System Research Lab)
• Statistically predicted sea ice improves S2S prediction over the Arctic in early winter and over East Asia and North America in late winter. (Baek-Min Kim, Korea Polar Research Institute)
• Wave properties can be partitioned into slow, basic state variations and fast perturbations. Analyzing the perturbations, it appears that adiabatic dynamics are just common resonant (Rossby-like) modes under varying basic states. (Gilbert Brunet, Environment and Climate Change Canada)
• The subseasonal forecast skill of many extratropical phenomena is dependent on the amplitude and/or phase of the MJO. (multiple speakers)
• Conditional skill (i.e., skill of extratropical forecasts as a function of skill in the tropics) is a useful diagnostic tool for characterizing the propagation of forecast errors from the tropics to the mid-latitudes. (Juliana Dias, University of Colorado/CIRES & NOAA Earth System Research Lab)
• Subseasonal prediction requires a good representation of the basic state for teleconnections between the MJO and the North Atlantic to be correct. (Robert Lee, NCAR/U. Reading)

Seasonal to Decadal Conference Highlights

The S2D track also opened with a session on “Mechanisms of S2D predictability,” chaired by Doug Smith, UK Met Office, and Steve Yeager, NCAR. The session’s keynote speaker, Jon Robson, University of Reading, dedicated his talk to mechanisms that give rise to predictive skill on interannual to decadal timescales, stressing that increasing skill must go hand-in-hand with increased insight by the community into underlying mechanisms of predictability. Robson highlighted that initialization of the Labrador Sea density leads to skillful predictions for the North Atlantic and a number of climate impacts such as hurricanes, Sahel rainfall, and temperature in China via circumglobal teleconnection. However, predicting the Labrador Sea density remains a challenge that will likely require multi-year predictability of the NAO, which in turn suffers from the signal-to-noise paradox.

Later in the afternoon, Thomas Delworth, NOAA Geophysical Fluid Dynamics Laboratory, presented on decadal variability and predictability in the Southern Ocean. He noted that recent observed trends in the Southern Ocean (i.e., surface ocean cooling and sea ice growth from 1979 to the present) are similar to transitions associated with an internal mode of Southern Ocean variability seen in long coupled control simulations, namely one characterized by long (multidecadal) predictability. Experiments starting from periods of active Southern Ocean convection exhibit highly predictable transitions to inactive Southern Ocean convection with trends of ocean cooling and sea ice growth, which closely match those observed, whereas experiments started from neutral or inactive states do not show matching trends.

Additional highlights include:

• The Interdecadal Pacific Oscillation (IPO) phase transitions are preceded by anomalies in off-equatorial western Pacific Ocean heat content and wind stress and can be triggered by El Niño/La Niña events, if the anomalies are sufficiently large. (Gerald Meehl, NCAR)
• Sub-decadal variability in the tropical Pacific had different characteristics in the 2000s compared to previous decades, likely caused by tropical Atlantic anomalies. (Takashi Mochizuki, JAMSTEC)
• Wildfire occurrence in the Southwest US is predictable on multi-year timescales, with skill arising from trans-basin variability and integrated soil moisture anomalies. (June-Yi Lee, Pusan National University)
• Recently revealed, the Pacific Decadal Precession is a robust mode of variability characterized by approximately 10-year counterclockwise progression of an atmospheric pressure dipole, with potential influence on precipitation in the Northwest US. (Bruce Anderson, Boston University)
• Model bias in the tropics greatly inhibits predictability of tropical cyclones otherwise expected from interannual (El Niño) to decadal (Atlantic Multidecadal Variability (AMV)) ocean modes. (Yohan Ruprich-Robert, Barcelona Supercomputing Center, Princeton University, GFDL; Christina Patricola, Lawrence Berkeley National Laboratory)
• AMV ensemble pacemaker experiments reveal substantial impacts on European winter climate given sufficiently strong SST forcing. This implies a potential predictability of European winter climate that has been overlooked because of low signal-to-noise in models. (Rym Msadek, NOAA GFDL, presenting work by Christophe Cassou, CECI/Université de Toulouse/CNRS/CERFACS)
• Suppression of African easterly wave variability in a high-resolution tropical channel model does not diminish mean cyclone activity, despite their hypothesized role in Atlantic cyclogenesis. (Christina Patricola, Lawrence Berkeley National Laboratory)

The meetings are being live streamed all week.

Second International Conference on Subseasonal to Seasonal Prediction (S2S) and
Second International Conference on Seasonal to Decadal Prediction (S2D)

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Day 2: A look at modeling and forecast challenges and advancements

For the second day of meetings, participants learned about modeling issues, ensemble predictions, and forecast information available from the subseasonal to decadal timescales. The concurrent sessions continued for both the S2S and S2D topics; below are some highlights.

Subseasonal to Seasonal Conference Highlights

Operational forecast centers are striving to increase the accuracy of forecasts. And while each year progress is made, challenges remain in the methods and initialization of the models, increasing or identifying the appropriate resolution, determining the ensemble size, and simulating and understanding uncertainties. The use of large ensembles show promise in identifying some of these challenges. Many talks also described how S2S predictions can be used for extreme and high-impact events.

The first session of the day was on modeling issues, chaired by Anca Brookshaw, ECMWF. Yuhei Takaya, Japan Meteorological Agency, presented a keynote lecture on the art and science and goes into designing operational forecast systems. He reviewed current practices and approaches, including the pros and cons, at operational centers. He noted that larger ensembles are better, but there is diminishing returns to skill improvement. He also showed ocean and atmosphere initialization shocks and model drifts that appear on short timescales – often from using different models, versions, or configurations – and that a possible solution is to use coupled data assimilation. Another major challenge for coupled S2S modeling is the lack of observations, such as sea ice and land.

As part of the ensemble predictions and forecast information session, Laura Ferranti, ECMWF, was interested in knowing how far in advance we can predict changes in large-scale flow that influences severe cold weather over Europe and other extreme events. Looking at the predictability of the North Atlantic Oscillation (NAO) and blocking, she found that S2S systems exhibit useful skill well beyond 10 days, which provide the potential for early warning systems. She also emphasized the need to collaborate with users to get a clear idea on what they want to know, and only with that can we make a useful product for longer range forecasts.

The day was wrapped up with a group discussion on the S2S Prediction Project database, with the leads looking for users’ experience in accessing the data and ideas for improvement. Some of the discussion centered on accessibility. Specifically, the S2S Prediction Project releases their forecasts on a three-week delay (due to embargoed data), but with the emergence of other projects, like SubX, that have immediate, open availability of model outputs that are useful when developing forecasts products, the three-week delay may need to be revised and renegotiated.

Thomas M. Hamill, Cécile Penland, both from NOAA ESRL, and Cristiana Stan, George Mason University, also chaired sessions throughout the day.

Additional highlights include: 

• Many operational centers are subjected to practical constraints dictated by operational activities (timeliness, costs, priorities), and they face a challenge of identifying suitable compromises, which have no detrimental effect on the skill of predictions. (multiple speakers)
• Multiple operational centers are moving towards a unified, coupled forecast system that can work across timescales from days (or shorter) to seasons (or longer). As forecast systems become more complex and more expensive computationally, while evidence in favor of the need for large ensembles of simulations mounts up, ideas on fundamental changes to the modeling paradigm are being tested in research mode (e.g., single-precision modelling). (multiple speakers)

• There is an ongoing debate about whether high-resolution models are necessary for S2S predictions. Some argue that inexpensive options – linear inverse models (for seasonal ranges) and low-resolution models (25–50km) with stochastic parameterisations (for subseasonal ranges) – are competitive candidates to high-resolution global climate models. However, it was acknowledged that the conclusion may be different when the emphasis shifts to medium range (~10 days) forecasts, where deterministic aspects are of high interest. (Prashant Sardeshmukh, University of Colorado/CIRES & NOAA Earth System Research Lab)   
• A common topic throughout the day was the Madden-Julian Oscillation (MJO), which depends crucially on moisture budget and geographical distribution of moisture. Thus, dry biases in models adversely affects MJO representation and prediction, especially when it comes to propagation through the maritime continent and into the Pacific warm pool. (multiple speakers)
• Using a verification framework for evaluating subseasonal South American precipitation prediction, which assesses weekly hindcast/real-time forecast quality, researchers were able to address the quality of prediction attributes (i.e., association, accuracy, reliability, and resolution). (Caio Coelho, Weather Prevision Center and Climate Studies/INPE, Brazil)  
• Researchers have found that the MJO and Quasi-Biennial Oscillation (QBO) can be used to improve the subseasonal predictability of atmospheric rivers, in addition to skillfully forecasting other anomalous extreme weather events, by using an index to quantify the diagonal “stripey-ness” of composite plots of anomalies. (Elizabeth Barnes, Colorado State University)
• Improvement in model skill is possible through different techniques, such as using a statistical model based on lagged composite fields associated to teleconnection patterns or a multimodel weighted calibrated ensemble. However, the improvement is only slight. (multiple speakers)
• The ability of statistical or dynamical models to skillfully predict surface air temperature on S2S timescales is regionally dependent – such as East Asia, which sees the highest impact from teleconnection patterns which are upstream. Additionally, the skill of models seems to be better when forecasting minimum temperature and minimum-temperature-related heat waves than maximum temperature or heat waves. (Changhyun Yoo, Ewha Womans University, Korea; Lauriane Batté, National Centre for Meteorological Research, France)
• Conditional states of the climate system offer opportunities for skillful forecasts over limited spatio-temporal subsets of the observed record. (Violeta Toma, Climate Forecast Applications Network)

Seasonal to Decadal Conference Highlights

On the second day of the conferences, participants in the S2D track reassembled to continue with presentations on the theme of “Mechanisms of S2D Predictability.” Speakers discussed important sources of S2D hydroclimate predictability, including remote ocean forcing (such as ENSO, Pacific Decadal Oscillation (PDO)/Interdecadal (IPO), tropical Atlantic SST, Atlantic meridional overturning circulation (AMOC)/Atlantic multidecadal variability (AMV), tropical monsoon convection (such as the Indian summer monsoon) exerting atmospheric teleconnection, and local land memories mainly due to soil moisture and vegetation. The speakers noted that realistic initializations and simulations of land-atmosphere interactions and processes, such as soil moisture and vegetation sensitivity, can provide improvement in S2D prediction skill. The influence of ENSO on climate variability and S2D prediction skill in many parts of the globe was seen as highlighting the importance of improving ENSO prediction. It was noted that recent advances in global seasonal forecast models tend to breach the ENSO springtime predictability barrier.

The second session was on “Modeling Issues in S2D Prediction.” The opening keynote by Wolfgang Müller (Germany's National Meteorological Service, Deutscher Wetterdienst) presented on the operationalization of seasonal-to-decadal climate predictions with the Max Planck Institute Earth System Model (ESM). Müller underlined that preparing an ESM for operational S2D predictions requires joint effort of different communities, including S2D predictions, climate modeling, and data assimilation. He addressed prominently the problem of model biases, a topic thoroughly discussed throughout the session. Given that model biases are not expected to vanish any time soon, speakers suggested different ways to reduce or overcome model biases, for example by exploring innovation on and understanding of model bias, process-oriented model diagnostics and biases in variability, the evolution of model biases with lead time, and by comparing the evolution to historical/unconstrained model simulations and/or Atmospheric Model Intercomparison Project (AMIP)-experiments.

Tuesday afternoon speakers highlighted the improvement of skill in their climate prediction models, but also noted that newer model versions with different configurations can lead to decreased skill in some areas. Further techniques to improve predictive skill were introduced. For example, it was reported that initialization with reanalyses assimilating upper atmosphere observations can improve wintertime NAO skill of seasonal forecasts – a topic strongly related to correct QBO initial conditions. The introduction of an ensemble dispersion filter to the MiKlip – a German research project on decadal predictions – improved the forecast skill for years 2–5. Ocean filtering and atmospheric variations, such as the MJO, were presented both as important contributors to initialization. However, filtering is not recommended for the initialization of the MJO.

Tuesday’s last three talks opened the theme of “S2D Ensemble Predictions and Forecast Information.” A keynote by Stephen Yeager, NCAR, addressed near-term hydroclimate outlooks, based on the Community Earth System Model (CESM) Decadal Prediction Large Ensemble. Results from this large ensemble showed that decadal land-based precipitation skill is complex, varying with region, season, lead-time, ensemble size, inclusion or non-inclusion of trend, spatial filtering, and other factors. Promising results were, however, presented for the Sahel region, Northern Europe, and Eurasia, specifically. Additionally, SST skill improves with lead-time, resulting in improved land-based precipitation skill. Further presentations addressed multi-year prediction of La Niña events, where exact results depend on underlying model dynamics, but were shown to hold skill out to 24 months ahead. An open question remains whether these results can transfer to warm events.