scholarly journals The role of boundary and initial conditions for dynamical seasonal predictability

2003 ◽  
Vol 10 (3) ◽  
pp. 211-232 ◽  
Author(s):  
T. J. Reichler ◽  
J. O. Roads
Keyword(s):  
Boundary Conditions ◽  
Time Scales ◽  
General Circulation ◽  
Initial Conditions ◽  
Spatial Scales ◽  
Circulation Model ◽  
Forecast Skill ◽  
Initial State ◽  
Tropical Forcing ◽  
The Impact

Abstract. The importance of initial state and boundary forcing for atmospheric predictability is explored on global to regional spatial scales and on daily to seasonal time scales. A general circulation model is used to conduct predictability experiments with different combinations of initial and boundary conditions. The experiments are verified under perfect model assumptions as well as against observational data. From initial conditions alone, there is significant instantaneous forecast skill out to 2 months. Different initial conditions show different predictability using the same kind of boundary forcing. Even on seasonal time scales, using observed atmospheric initial conditions leads to a substantial increase in overall skill, especially during periods with weak tropical forcing. The impact of boundary forcing on predictability is detectable after 10 days and leads to measurable instantaneous forecast skill at very long lead times. Over the Northern Hemisphere, it takes roughly 4 weeks for boundary conditions to reach the same effect on predictability as initial conditions. During events with strong tropical forcing, these time scales are somewhat shorter. Over the Southern Hemisphere, there is a strongly enhanced influence of initial conditions during summer. We conclude that the long term memory of initial conditions is important for seasonal forecasting.

scholarly journals Forecast Skill of the Madden–Julian Oscillation in Two Canadian Atmospheric Models

2008 ◽  
Vol 136 (11) ◽  
pp. 4130-4149 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet ◽  
Jacques Derome
Keyword(s):  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Skill Score ◽  
Forecast Skill ◽  
Second Phase ◽  
Equatorial Waves ◽  
Madden Julian Oscillation ◽  
Atmospheric Models ◽  
Convectively Coupled Equatorial Waves

Abstract The output of two global atmospheric models participating in the second phase of the Canadian Historical Forecasting Project (HFP2) is utilized to assess the forecast skill of the Madden–Julian oscillation (MJO). The two models are the third generation of the general circulation model (GCM3) of the Canadian Centre for Climate Modeling and Analysis (CCCma) and the Global Environmental Multiscale (GEM) model of Recherche en Prévision Numérique (RPN). Space–time spectral analysis of the daily precipitation in near-equilibrium integrations reveals that GEM has a better representation of the convectively coupled equatorial waves including the MJO, Kelvin, equatorial Rossby (ER), and mixed Rossby–gravity (MRG) waves. An objective of this study is to examine how the MJO forecast skill is influenced by the model’s ability in representing the convectively coupled equatorial waves. The observed MJO signal is measured by a bivariate index that is obtained by projecting the combined fields of the 15°S–15°N meridionally averaged precipitation rate and the zonal winds at 850 and 200 hPa onto the two leading empirical orthogonal function (EOF) structures as derived using the same meridionally averaged variables following a similar approach used recently by Wheeler and Hendon. The forecast MJO index, on the other hand, is calculated by projecting the forecast variables onto the same two EOFs. With the HFP2 hindcast output spanning 35 yr, for the first time the MJO forecast skill of dynamical models is assessed over such a long time period with a significant and robust result. The result shows that the GEM model produces a significantly better level of forecast skill for the MJO in the first 2 weeks. The difference is larger in Northern Hemisphere winter than in summer, when the correlation skill score drops below 0.50 at a lead time of 10 days for GEM whereas it is at 6 days for GCM3. At lead times longer than about 15 days, GCM3 performs slightly better. There are some features that are common for the two models. The forecast skill is better in winter than in summer. Forecasts initialized with a large amplitude for the MJO are found to be more skillful than those with a weak MJO signal in the initial conditions. The forecast skill is dependent on the phase of the MJO at the initial conditions. Forecasts initialized with an MJO that has an active convection in tropical Africa and the Indian Ocean sector have a better level of forecast skill than those initialized with a different phase of the MJO.

The Role of Radiative Interactions in Tropical Cyclone Development under Realistic Boundary Conditions

2020 ◽  
pp. 1-38
Author(s):  
Bosong Zhang ◽  
Brian J. Soden ◽  
Gabriel A. Vecchi ◽  
Wenchang Yang
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Latent Heat Release ◽  
Synoptic Scale ◽  
Spatially Varying ◽  
The Impact ◽  
Realistic Boundary Conditions

AbstractThe impact of radiative interactions on tropical cyclones (TC) climatology is investigated using a global, TC-permitting general circulation model (GCM) with realistic boundary conditions. In this model, synoptic-scale radiative interactions are suppressed by overwriting the model-generated atmospheric radiative cooling rates with its monthly-varying climatological values. When radiative interactions are suppressed, the global TC frequency is significantly reduced, indicating that radiative interactions are a critical component of TC development even in the presence of spatially varying boundary conditions. The reduced TC activity is primarily due to a decrease in the frequency of pre-TC synoptic disturbances (“seeds”), whereas the likelihood that the seeds undergo cyclogenesis is less affected. When radiative interactions are suppressed, TC genesis shifts toward coastal regions, whereas TC lysis locations stay almost unchanged; together the distance between genesis and lysis is shortened, reducing TC duration. In a warmer climate, the magnitude of TC reduction from suppressing radiative interactions is diminished due to the larger contribution from latent heat release with increased sea surface temperatures. These results highlight the importance of radiative interactions in modulating the frequency and duration of TCs.

Multi-decadal variability in long-range ENSO predictions (SEAS5-20C)

2020 ◽  
Author(s):  
Antje Weisheimer ◽  
Magdalena Balmaseda ◽  
Tim Stockdale
Keyword(s):  
Time Scales ◽  
Decadal Variability ◽  
Initial Conditions ◽  
Forecast Skill ◽  
First Year ◽  
Initial State ◽  
First Results ◽  
Forecasting System ◽  
Similar Good ◽  
Ocean Observations

<p>Motivated by the high skill in predicting ENSO on seasonal time scales with ECMWF’s seasonal forecasting system SEAS5 and by previous findings of multi-decadal variability in seasonal forecast skill of extratropical dynamics, we have carried out an extensive set of 24-month long coupled hindcasts from 1901 to 2010. The hindcasts were run with SEAS5 in reduced resolution and are initialised from, and verified against, reanalyses of the 20<sup>th</sup>Century. They allow us to analyse ENSO forecast skill beyond the first year, to study how skill varies on decadal time scales and to test sensitivities to atmospheric wind forcings and the assimilation of ocean observations in the initial conditions.</p><p>First results show a substantial amount of multi-decadal variability in both ENSO mean state and forecast skill. We find periods in the early-to-mid 20<sup>th</sup>Century with much reduced levels of skill, in particular after the spring barrier in the first forecast year. Periods at the beginning and at the end of the Century show broadly similar good performances with substantial skill even after the first year spring barrier. Combined effects of the wind forcing and the assimilation of ocean data on the initial state seem to play a crucial role in understanding this behaviour.</p>

scholarly journals A Modeling Study of the Causes and Predictability of the Spring 2011 Extreme U.S. Weather Activity

2016 ◽  
Vol 29 (21) ◽  
pp. 7869-7887 ◽  
Author(s):  
Siegfried Schubert ◽  
Yehui Chang ◽  
Hailan Wang ◽  
Randal Koster ◽  
Max Suarez
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Primary Source ◽  
Ohio River ◽  
Eastern United States ◽  
Initial State ◽  
Continental Scale ◽  
Sst Forcing ◽  
The Impact

Abstract This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Niña conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric–stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign.

scholarly journals Impact of Atmosphere and Land Surface Initial Conditions on Seasonal Forecasts of Global Surface Temperature

2014 ◽  
Vol 27 (24) ◽  
pp. 9253-9271 ◽  
Author(s):  
Stefano Materia ◽  
Andrea Borrelli ◽  
Alessio Bellucci ◽  
Andrea Alessandri ◽  
Pierluigi Di Pietro ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Initial Conditions ◽  
Seasonal Prediction ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Initial State ◽  
Predictive Skill ◽  
The Impact ◽  
Initialization Strategy

Abstract The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial condition affects forecast skill for several months. In particular, the ENSO region, eastern tropical Atlantic, and North Pacific benefit significantly from the atmosphere initialization. On the mainland, the effect of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects forecast skill in the following seasons. Winter forecasts in the high-latitude plains benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region and central Asia. However, the initialization strategy based on the full value technique may not be the best choice for land surface, since soil moisture is a strongly model-dependent variable: in fact, initialization through land surface reanalysis does not systematically guarantee a skill improvement. Nonetheless, using a different initialization strategy for land, as opposed to atmosphere and ocean, may generate inconsistencies. Overall, the introduction of a realistic initialization for land and atmosphere substantially increases skill and accuracy. However, further developments in the procedure for land surface initialization are required for more accurate seasonal forecasts.

Long-Range Predictability in the Tropics. Part II: 30–60-Day Variability

2005 ◽  
Vol 18 (5) ◽  
pp. 634-650 ◽  
Author(s):  
Thomas Reichler ◽  
John O. Roads
Keyword(s):  
Boundary Conditions ◽  
Long Range ◽  
General Circulation ◽  
Initial Conditions ◽  
Southern Oscillation ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Circulation Model ◽  
Lead Times ◽  
Initial And Boundary Conditions

Abstract It is suggested that the slow evolution of the tropical Madden–Julian oscillation (MJO) has the potential to improve the predictability of tropical and extratropical circulation systems at lead times beyond 2 weeks. In practice, however, the MJO phenomenon is extremely difficult to predict because of the lack of good observations, problems with ocean forecasts, and well-known model deficiencies. In this study, the potential skill in forecasting tropical intraseasonal variability is investigated by eliminating all those errors. This is accomplished by conducting five ensemble predictability experiments with a complex general circulation model and by verifying them under the perfect model assumption. The experiments are forced with different combinations of initial and boundary conditions to explore their sensitivity to uncertainties in those conditions. When “perfect” initial and boundary conditions are provided, the model produces a realistic climatology and variability as compared to reanalysis, although the spectral peak of the simulated MJO is too broad. The effect of initial conditions is noticeable out to about 40 days. The quality of the boundary conditions is crucial at all lead times. The small but positive correlations at very long lead times are related to intraseasonal variability of tropical sea surface temperatures (SSTs). When model, initial, and boundary conditions are all perfect, the useful forecast skill of intraseasonal variability is about 4 weeks. Predictability is insensitive to the El Niño–Southern Oscillation (ENSO) phenomenon, but it is enhanced during years when the intraseasonal oscillation is more active. The results provide evidence that the MJO must be understood as a coupled system. As a consequence, it is concluded that further progress in the long-range predictability effort may require the use of fully interactive ocean models.

scholarly journals Comparative Evaluation of Two Ensembles for Long-Range Forecasting of Monsoon Rainfall

2009 ◽  
Vol 137 (9) ◽  
pp. 2893-2907 ◽  
Author(s):  
P. Goswami ◽  
K. C. Gouda
Keyword(s):  
Long Range ◽  
Time Scales ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Ensemble Average ◽  
Ensemble Forecasting ◽  
Initial States

Abstract It is now well known that changes in initial conditions can give rise to substantial changes in the forecasts even at the long range. Ensemble averaging of forecasts from different initial conditions provides an efficient way of assessing and reducing uncertainties in the forecasts due to inherent uncertainties in the initial conditions. However, the procedure for generating the ensemble of forecasts has to be based on careful consideration. Although there now exist several well-tested frameworks for ensemble forecasting at the short range, the procedure for and impact of ensemble forecasting on long-range forecasting of monsoons remain relatively less explored. In particular, the procedure for the choice of the ensemble for long-range forecasting of monsoons needs special considerations. The Indian summer monsoon is characterized by a number of intraseasonal oscillations (ISOs) whose phases and amplitudes can significantly affect the monsoon forecast and that can be adequately sampled only using initial states spread over time scales comparable to the characteristic time scales of these ISOs. It is shown that use of initial states spread over a longer period (such as 1 April–1 May) results in a better ensemble average for long-range forecasting of Indian summer monsoon than that from an ensemble of closely packed states with a shorter lead. An optimized configuration for long-range forecasting of monsoons using a variable resolution general circulation model is adopted. The climatological monthly mean SST field is used to assess realizable skill, as use of observed SST provides only potential skill. Then five-member wide-lead (1 April–1 May) ensemble average forecasts are compared with five-member compact-lead (27 April–1 May) ensemble average forecasts for 24 (1980–2003) hindcasts; it is shown that the skill of the wide-lead ensemble average is superior to that of the compact-lead ensemble at different spatial and temporal scales in spite of the longer lead of the former.

scholarly journals Exploring the Lyapunov instability properties of high-dimensional atmospheric and climate models

2018 ◽  
Author(s):  
Lesley De Cruz ◽  
Sebastian Schubert ◽  
Jonathan Demaeyer ◽  
Valerio Lucarini ◽  
Stéphane Vannitsem
Keyword(s):  
Lyapunov Exponents ◽  
Time Scales ◽  
General Circulation ◽  
Climate Models ◽  
Large Deviation ◽  
Circulation Model ◽  
Ocean Dynamics ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
The Impact

Abstract. The stability properties of intermediate-order climate models are investigated by computing their Lyapunov exponents (LEs). The two models considered are PUMA (Portable University Model of the Atmosphere), a primitive-equation simple general circulation model, and MAOOAM (Modular Arbitrary-Order Ocean-Atmosphere Model), a quasi-geostrophic coupled ocean-atmosphere model on a β-plane. We wish to investigate the effect of the different levels of filtering on the instabilities and dynamics of the atmospheric flows. Moreover, we assess the impact of the oceanic coupling, the dissipation scheme and the resolution on the spectra of LEs. The PUMA Lyapunov spectrum is computed for two different values of the meridional temperature gradient defining the Newtonian forcing to the temperature field. The increase of the gradient gives rise to a higher baroclinicity and stronger instabilities, corresponding to a larger dimension of the unstable manifold and a larger first LE. The Kaplan-Yorke dimension of the attractor increases as well. The convergence rate of the rate functional for the large deviation law of the finite-time Lyapunov exponents (FTLEs) is fast for all exponents, which can be interpreted as resulting from the absence of a clear-cut atmospheric time-scale separation in such a model. The MAOOAM spectra show that the dominant atmospheric instability is correctly represented even at low resolutions. However, the dynamics of the central manifold, which is mostly associated to the ocean dynamics, is not fully resolved because of its associated long time scales, even at intermediate orders. As expected, increasing the mechanical atmosphere-ocean coupling coefficient or introducing a turbulent diffusion parametrization reduces the Kaplan-Yorke dimension and Kolmogorov-Sinai entropy. In all considered configurations, it is possible to robustly define large deviations laws describing the statistics of the FTLEs corresponding to the strongly damped modes, while the opposite holds for near-zero LEs and, somewhat unexpectedly, also for the positive LEs. This paper highlights the need to investigate the natural variability of the atmosphere-ocean coupled dynamics by associating rate of growth and decay of perturbations to the physical modes described using the formalism of the covariant Lyapunov vectors and to consider long integrations in order to disentangle the dynamical processes occurring at all time scales.

scholarly journals Impact of ECCO Ocean-State Estimates on the Initialization of Seasonal Climate Forecasts

2008 ◽  
Vol 21 (9) ◽  
pp. 1929-1947 ◽  
Author(s):  
Gabriel Cazes-Boezio ◽  
Dimitris Menemenlis ◽  
Carlos R. Mechoso
Keyword(s):  
Los Angeles ◽  
General Circulation ◽  
Initial Conditions ◽  
Circulation Model ◽  
Massachusetts Institute Of Technology ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Institute Of Technology ◽  
The Impact ◽  
Seasonal Climate Forecasts

Abstract The impact of ocean-state estimates generated by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) on the initialization of a coupled general circulation model (CGCM) for seasonal climate forecasts is examined. The CGCM consists of the University of California, Los Angeles, Atmospheric GCM (UCLA AGCM) and an ECCO ocean configuration of the Massachusetts Institute of Technology GCM (MITgcm). The forecasts correspond to ensemble seasonal hindcasts for the period 1993–2001. For the forecasts, the ocean component of the CGCM is initialized in either early March or in early June using ocean states provided either by an unconstrained forward ocean integration of the MITgcm (the “baseline” hindcasts) or by data-constrained ECCO results (the “ECCO” hindcasts). Forecast skill for both the baseline and the ECCO hindcasts is significantly higher than persistence and compares well with the skill of other state-of-the art CGCM forecast systems. For March initial conditions, the standard errors of sea surface temperature (SST) anomalies in ECCO hindcasts (relative to observed anomalies) are up to 1°C smaller than in the baseline hindcasts over the central and eastern equatorial Pacific (150°–120°W). For June initial conditions, the errors of ECCO hindcasts are up to 0.5°C smaller than in the baseline hindcasts. The smaller standard error of the ECCO hindcasts is, in part, due to a more realistic equatorial thermocline structure of the ECCO initial conditions. This study confirms the value of physically consistent ocean-state estimation for the initialization of seasonal climate forecasts.

scholarly journals Intensification of North American Megadroughts through Surface and Dust Aerosol Forcing*

2013 ◽  
Vol 26 (13) ◽  
pp. 4414-4430 ◽  
Author(s):  
Benjamin I. Cook ◽  
Richard Seager ◽  
Ron L. Miller ◽  
Joseph A. Mason
Keyword(s):  
Boundary Conditions ◽  
Land Surface ◽  
General Circulation ◽  
Atmospheric Stability ◽  
Circulation Model ◽  
Dust Aerosol ◽  
Central Plains ◽  
Model Experiments ◽  
Aerosol Forcing ◽  
The Impact

Abstract Tree-ring-based reconstructions of the Palmer drought severity index (PDSI) indicate that, during the Medieval Climate Anomaly (MCA), the central plains of North America experienced recurrent periods of drought spanning decades or longer. These megadroughts had exceptional persistence compared to more recent events, but the causes remain uncertain. The authors conducted a suite of general circulation model experiments to test the impact of sea surface temperature (SST) and land surface forcing on the MCA megadroughts over the central plains. The land surface forcing is represented as a set of dune mobilization boundary conditions, derived from available geomorphological evidence and modeled as increased bare soil area and a dust aerosol source (32°–44°N, 105°–95°W). In the experiments, cold tropical Pacific SST forcing suppresses precipitation over the central plains but cannot reproduce the overall drying or persistence seen in the PDSI reconstruction. Droughts in the scenario with dust aerosols, however, are amplified and have significantly longer persistence than in other model experiments, more closely matching the reconstructed PDSI. This additional drying occurs because the dust increases the shortwave planetary albedo, reducing energy inputs to the surface and boundary layer. The energy deficit increases atmospheric stability, inhibiting convection and reducing cloud cover and precipitation over the central plains. Results from this study provide the first model-based evidence that dust aerosol forcing and land surface changes could have contributed to the intensity and persistence of the central plains megadroughts, although uncertainties remain in the formulation of the boundary conditions and the future importance of these feedbacks.

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