Seasonal predictability of baroclinic wave activity

AbstractMidlatitude baroclinic waves drive extratropical weather and climate variations, but their predictability beyond 2 weeks has been deemed low. Here we analyze a large ensemble of climate simulations forced by observed sea surface temperatures (SSTs) and demonstrate that seasonal variations of baroclinic wave activity (BWA) are potentially predictable. This potential seasonal predictability is denoted by robust BWA responses to SST forcings. To probe regional sources of the potential predictability, a regression analysis is applied to the SST-forced large ensemble simulations. By filtering out variability internal to the atmosphere and land, this analysis identifies both well-known and unfamiliar BWA responses to SST forcings across latitudes. Finally, we confirm the model-indicated predictability by showing that an operational seasonal prediction system can leverage some of the identified SST-BWA relationships to achieve skillful predictions of BWA. Our findings help to extend long-range predictions of the statistics of extratropical weather events and their impacts.

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Medium-Range, Monthly, and Seasonal Prediction for Europe and the Use of Forecast Information

Journal of Climate ◽

10.1175/jcli3944.1 ◽

2006 ◽

Vol 19 (23) ◽

pp. 6025-6046 ◽

Cited By ~ 35

Author(s):

Mark J. Rodwell ◽

Francisco J. Doblas-Reyes

Keyword(s):

Coupled Model ◽

Seasonal Prediction ◽

Model Potential ◽

Mitigation Strategies ◽

General Level ◽

Seasonal Forecasts ◽

Seasonal Predictability ◽

Potential Predictability ◽

Medium Range ◽

The Impact

Abstract Operational probabilistic (ensemble) forecasts made at ECMWF during the European summer heat wave of 2003 indicate significant skill on medium (3–10 day) and monthly (10–30 day) time scales. A more general “unified” analysis of many medium-range, monthly, and seasonal forecasts confirms a high degree of probabilistic forecast skill for European temperatures over the first month. The unified analysis also identifies seasonal predictability for Europe, which is not yet realized in seasonal forecasts. Interestingly, the initial atmospheric state appears to be important even for month 2 of a coupled forecast. Seasonal coupled model forecasts capture the general level of observed European deterministic predictability associated with the persistence of anomalies. A review is made of the possibilities to improve seasonal forecasts. This includes multimodel and probabilistic techniques and the potential for “windows of opportunity” where better representation of the effects of boundary conditions (e.g., sea surface temperature and soil moisture) may improve forecasts. “Perfect coupled model” potential predictability estimates are sensitive to the coupled model used and so it is not yet possible to estimate ultimate levels of seasonal predictability. The impact of forecast information on different users with different mitigation strategies (i.e., ways of coping with a weather or climate event) is investigated. The importance of using forecast information to reduce volatility as well as reducing the expected expense is highlighted. The possibility that weather forecasts can affect the cost of mitigating actions is considered. The simplified analysis leads to different conclusions about the usefulness of forecasts that could guide decisions about the development of “end-to-end” (forecast-to-user decision) systems.

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Single Precision in the Dynamical Core of a Nonhydrostatic Global Atmospheric Model: Evaluation Using a Baroclinic Wave Test Case

Monthly Weather Review ◽

10.1175/mwr-d-17-0257.1 ◽

2018 ◽

Vol 146 (2) ◽

pp. 409-416 ◽

Cited By ~ 9

Author(s):

Masuo Nakano ◽

Hisashi Yashiro ◽

Chihiro Kodama ◽

Hirofumi Tomita

Keyword(s):

Finite Volume Method ◽

Finite Volume ◽

Double Precision ◽

Baroclinic Wave ◽

Single Precision ◽

Dynamical Core ◽

Wave Growth ◽

Climate Simulations ◽

Weather And Climate ◽

Volume Method

Abstract Reducing the computational cost of weather and climate simulations would lower electric energy consumption. From the standpoint of reducing costs, the use of reduced precision arithmetic has become an active area of research. Here the impact of using single-precision arithmetic on simulation accuracy is examined by conducting Jablonowski and Williamson’s baroclinic wave tests using the dynamical core of a global fully compressible nonhydrostatic model. The model employs a finite-volume method discretized on an icosahedral grid system and its mesh size is set to 220, 56, 14, and 3.5 km. When double-precision arithmetic is fully replaced by single-precision arithmetic, a spurious wavenumber-5 structure becomes dominant in both hemispheres, rather than the expected baroclinic wave growth only in the Northern Hemisphere. It was found that this spurious wave growth comes from errors in the calculation of gridcell geometrics. Therefore, an additional simulation was conducted using double precision for calculations that only need to be performed for model setup, including calculation of gridcell geometrics, and single precision everywhere else, meaning that all calculations performed each time step used single precision. In this case, the model successfully simulated the growth of the baroclinic wave with only small errors and a 46% reduction in runtime. These results suggest that the use of single-precision arithmetic will allow significant reduction of computational costs in next-generation weather and climate simulations using a fully compressible nonhydrostatic global model with the finite-volume method.

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Extracting Subseasonal Scenarios: An Alternative Method to Analyze Seasonal Predictability of Regional-Scale Tropical Rainfall

Journal of Climate ◽

10.1175/jcli-d-12-00357.1 ◽

2013 ◽

Vol 26 (8) ◽

pp. 2580-2600 ◽

Cited By ~ 19

Author(s):

Vincent Moron ◽

Pierre Camberlin ◽

Andrew W. Robertson

Keyword(s):

Rainy Season ◽

Early Stage ◽

Regional Scale ◽

Spatial Coherence ◽

Daily Rainfall ◽

Seasonal Prediction ◽

East African ◽

Seasonal Predictability ◽

Potential Predictability ◽

Noise Component

Abstract Current seasonal prediction of rainfall typically focuses on 3-month rainfall totals at regional scale. This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall. This approach may hide potentially predictable signals when rainfall is lower: for example, near the onset or cessation of the rainy season. The authors illustrate such a case for the East African long rains (March–May) on a network of 36 stations in Kenya and north Tanzania from 1961 to 2001. Spatial coherence and potential predictability of seasonal rainfall anomalies associated with tropical sea surface temperature (SST) anomalies clearly peak during the early stage of the rainy season (in March), while the largest rainfall (in April and May) is far less spatially coherent; the latter is shown to contain a large noise component at the station scale that characterizes interannual variability of the March–May seasonal total amounts. Combining the empirical orthogonal function of both interannual and subseasonal variations with a fuzzy k-means clustering is shown to capture the most spatially coherent subseasonal “scenarios” that tend to filter out the noisier variations of the rainfall field and emphasize the most consistent signals in both time and space. This approach is shown to provide insight into the seasonal predictability of long dry spells and heavy daily rainfall events at local scale and their subseasonal modulation.

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d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

Progress in Earth and Planetary Science ◽

10.1186/s40645-020-00367-7 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Masayoshi Ishii ◽

Nobuhito Mori

Keyword(s):

Risk Assessment ◽

Global Warming ◽

High Resolution ◽

Climate Changes ◽

Future Climate ◽

Atmospheric Models ◽

Large Ensemble ◽

Past Climate ◽

The Past ◽

Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

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Seasonal prediction of the boreal winter stratosphere

Climate Dynamics ◽

10.1007/s00382-021-05787-9 ◽

2021 ◽

Author(s):

Alice Portal ◽

Paolo Ruggieri ◽

Froila M. Palmeiro ◽

Javier García-Serrano ◽

Daniela I. V. Domeisen ◽

...

Keyword(s):

Southern Oscillation ◽

Polar Vortex ◽

Seasonal Prediction ◽

Wave Activity ◽

Boreal Winter ◽

Quasi Biennial Oscillation ◽

Stratospheric Polar Vortex ◽

Eddy Heat Flux ◽

Prediction Systems ◽

Model Database

AbstractThe predictability of the Northern Hemisphere stratosphere and its underlying dynamics are investigated in five state-of-the-art seasonal prediction systems from the Copernicus Climate Change Service (C3S) multi-model database. Special attention is devoted to the connection between the stratospheric polar vortex (SPV) and lower-stratosphere wave activity (LSWA). We find that in winter (December to February) dynamical forecasts initialised on the first of November are considerably more skilful than empirical forecasts based on October anomalies. Moreover, the coupling of the SPV with mid-latitude LSWA (i.e., meridional eddy heat flux) is generally well reproduced by the forecast systems, allowing for the identification of a robust link between the predictability of wave activity above the tropopause and the SPV skill. Our results highlight the importance of November-to-February LSWA, in particular in the Eurasian sector, for forecasts of the winter stratosphere. Finally, the role of potential sources of seasonal stratospheric predictability is considered: we find that the C3S multi-model overestimates the stratospheric response to El Niño–Southern Oscillation (ENSO) and underestimates the influence of the Quasi–Biennial Oscillation (QBO).

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Profiling Methodology and Performance Tuning of the Met Office Unified Model for Weather and Climate Simulations

2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum ◽

10.1109/ipdps.2011.283 ◽

2011 ◽

Cited By ~ 2

Author(s):

Peter E. Strazdins ◽

Margaret Kahn ◽

Joerg Henrichs ◽

Tim Pugh ◽

Mike Rezny

Keyword(s):

Unified Model ◽

Performance Tuning ◽

Climate Simulations ◽

Weather And Climate ◽

And Performance

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Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

Journal of Climate ◽

10.1175/jcli-d-21-0775.1 ◽

2021 ◽

pp. 1-45

Keyword(s):

Time Scale ◽

Climate Model ◽

Southern Oscillation ◽

Seasonal Prediction ◽

Seasonal Rainfall ◽

The Arctic ◽

Sea Ice Concentration ◽

Potential Predictability ◽

Subseasonal Variability ◽

The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

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Wave Activity for Large-Amplitude Disturbances Described by the Primitive Equations on the Sphere

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-0228.1 ◽

2013 ◽

Vol 70 (6) ◽

pp. 1616-1630 ◽

Cited By ~ 14

Author(s):

John Methven

Keyword(s):

Large Amplitude ◽

Potential Temperature ◽

Lower Boundary ◽

Propagation Speed ◽

Analysis Data ◽

Wave Activity ◽

Primitive Equations ◽

Baroclinic Wave ◽

Boundary Potential ◽

Background State

Abstract Pseudomomentum and pseudoenergy are both measures of wave activity for disturbances in a fluid, relative to a notional background state. Together they give information on the propagation, growth, and decay of disturbances. Wave activity conservation laws are most readily derived for the primitive equations on the sphere by using isentropic coordinates. However, the intersection of isentropic surfaces with the ground (and associated potential temperature anomalies) is a crucial aspect of baroclinic wave evolution. A new expression is derived for pseudoenergy that is valid for large-amplitude disturbances spanning isentropic layers that may intersect the ground. The pseudoenergy of small-amplitude disturbances is also obtained by linearizing about a zonally symmetric background state. The new expression generalizes previous pseudoenergy results for quasigeostrophic disturbances on the β plane and complements existing large-amplitude results for pseudomomentum. The pseudomomentum and pseudoenergy diagnostics are applied to an extended winter from the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis data. The time series identify distinct phenomena such as a baroclinic wave life cycle where the wave activity in boundary potential temperature saturates nonlinearly almost two days before the peak in wave activity near the tropopause. The coherent zonal propagation speed of disturbances at tropopause level, including distinct eastward, westward, and stationary phases, is shown to be dictated by the ratio of total hemispheric pseudoenergy to pseudomomentum. Variations in the lower-boundary contribution to pseudoenergy dominate changes in propagation speed; phases of westward progression are associated with stronger boundary potential temperature perturbations.

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Interhemispheric asymmetry of climate change projections of boreal winter surface winds in CanESM5 large ensemble simulations

10.21203/rs.3.rs-476108/v1 ◽

2021 ◽

Author(s):

Bin Yu ◽

Xuebin Zhang ◽

Guilong Li ◽

Wei Yu

Keyword(s):

Climate Variability ◽

Wind Power ◽

Atmospheric Circulation ◽

Large Scale ◽

Boreal Winter ◽

Interhemispheric Asymmetry ◽

Large Ensemble ◽

Internal Climate Variability ◽

Climate Simulations ◽

Extreme Wind

Abstract A recent study of future changes in global wind power using an ensemble of ten CMIP5 climate simulations indicated an interhemispheric asymmetry of wind power changes over the 21st century, featured by power decreases across the Northern Hemisphere mid-latitudes and increases across the tropics and subtropics of the Southern Hemisphere. Here we analyze future global projections of surface mean and extreme winds by means of a single-model initial-condition 50-member ensemble of climate simulations generated with CanESM5, the Canadian model participated in CMIP6. We analyze the ensemble mean and spread of boreal winter mean and extreme wind trends over the next half-century (2021-2070) and explore the contribution of internal climate variability to these trends. Surface wind speed is projected to mostly decrease in northern mid-low latitudes and southern mid-latitudes and increase in northern high latitudes and southern tropical and subtropical regions, with considerable regional variations. Large ensemble spreads are apparent, especially with remarkable differences over northern parts of South America and northern Russia. The interhemispheric asymmetry of wind projections is found in most ensemble members, and can be related to large-scale changes in surface temperature and atmospheric circulation. The extreme wind has similar structure of future projections, whereas its reductions tend to be more consistent over northern mid-latitudes. The projected mean and extreme wind changes are attributed to changes in both externally anthropogenic forced and internal climate variability generated components. The spread in wind projections is partially due to large-scale atmospheric circulation variability.

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