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

Materia, Stefano; Borrelli, Andrea; Bellucci, Alessio; Alessandri, Andrea; Pietro, Pierluigi Di; Athanasiadis, P.; Navarra, Antonio; Gualdi, Silvio

doi:10.1175/jcli-d-14-00163.1

Cited by 37 publications

(21 citation statements)

References 58 publications

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“…Land‐atmosphere coupling , which is the mutual interaction between land surface and atmosphere, plays an important role in the predictability of the climate system by transferring and modulating soil state anomalies to the atmosphere. As demonstrated more than 30 years ago by the experiments of Shukla and Mintz [] and strongly restated in the 2001 American Meteorological Society Council [ American Meteorological Society Statement , ], knowledge of land surface initial condition is imperative for subseasonal [ Guo et al ., ] and seasonal [ Materia et al ., ] predictions.…”

Section: Land Surfacementioning

confidence: 99%

Advancements in decadal climate predictability: The role of nonoceanic drivers

Bellucci

Haarsma

Booth

et al. 2015

Reviews of Geophysics

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We review recent progress in understanding the role of sea ice, land surface, stratosphere, and aerosols in decadal-scale predictability and discuss the perspectives for improving the predictive capabilities of current Earth system models (ESMs). These constituents have received relatively little attention because their contribution to the slow climatic manifold is controversial in comparison to that of the large heat capacity of the oceans. Furthermore, their initialization as well as their representation in state-of-the-art climate models remains a challenge. Numerous extraoceanic processes that could be active over the decadal range are proposed. Potential predictability associated with the aforementioned, poorly represented, and scarcely observed constituents of the climate system has been primarily inspected through numerical simulations performed under idealized experimental settings. The impact, however, on practical decadal predictions, conducted with realistically initialized full-fledged climate models, is still largely unexploited. Enhancing initial-value predictability through an improved model initialization appears to be a viable option for land surface, sea ice, and, marginally, the stratosphere. Similarly, capturing future aerosol emission storylines might lead to an improved representation of both global and regional short-term climatic changes. In addition to these factors, a key role on the overall predictive ability of ESMs is expected to be played by an accurate representation of processes associated with specific components of the climate system. These act as "signal carriers," transferring across the climatic phase space the information associated with the initial state and boundary forcings, and dynamically bridging different (otherwise unconnected) subsystems. Through this mechanism, Earth system components trigger low-frequency variability modes, thus extending the predictability beyond the seasonal scale.

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Section: Land Surfacementioning

confidence: 99%

Advancements in decadal climate predictability: The role of nonoceanic drivers

Bellucci

Haarsma

Booth

et al. 2015

Reviews of Geophysics

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“…Numerous studies have indicated that the persistence of soil moisture anomalies is from weeks to several months, both in observations (Entin et al, ; Ghannam et al, ; Hollinger & Isard, ; Liu et al, ; Orth & Seneviratne, ; Orth, ; Seneviratne & Koster, ; Vinnikov et al, ; Vinnikov & Yeserkepova, ) and in model simulations (Dirmeyer, ; Douville, ; Fennessy & Shukla, ; Ferranti & Viterbo, ; Guo et al, ; Hirsch et al, ; Kanae et al, ; Koster et al, ; Koster et al, ; Koster & Suarez, ; Materia et al, ; Paolino et al, ; Qi & Song, ; Schlosser & Milly, ; Seneviratne et al, ; Seneviratne & Koster, ; Wu & Dickinson, ; Xiang et al, ). Moreover, Langford et al () examined the decadal variability in precipitation over southwestern North America, and found the most of the variability appears to be explained by local anomalies associated with land‐atmosphere feedbacks, in which soil moisture plays an important role.…”

Section: Introductionmentioning

confidence: 99%

Soil Moisture Memory and Its Effect on the Surface Water and Heat Fluxes on Seasonal and Interannual Time Scales

et al. 2019

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The persistence of soil moisture anomalies has an important effect on the weather and climate forecasts. Numerous observational and modeling studies have addressed the memory of soil moisture anomalies and its effects at the seasonal scale, and few studies have focused on the interannual scale. This study investigates the soil moisture memory and its effect on the surface heat and water fluxes under different atmospheric conditions on seasonal and interannual scales using the Community Land Model Version 4.5 driven by the observations at the Tongyu site. The results indicate that the soil moisture anomalies can persist for more than 1 year. It was found that the decay rate of soil moisture anomalies depends mainly on initial soil moisture anomalies, followed by atmospheric condition in this study. Under the same atmospheric condition, the wet anomalies of soil moisture decay faster than dry anomalies of soil moisture. With the same initial soil moisture anomalies, soil moisture memory is usually shorter under the wet atmospheric condition. Moreover, the soil moisture anomalies have an obvious exponential decrease over the years. The anomalies of the surface heat fluxes have significant interannual attenuation trend and seasonal variations, and they are closely related to the anomalies of surface temperature, which are mainly affected by the anomalies of soil specific heat capacity. This study provides a scientific support for understanding the persistence of soil moisture anomalies, and it may be useful for the research on the seasonal and interannual variability of climate.

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“…(Cohen et al 2014, p. 631), or Suckling andSmith (2013) and Materia et al (2014). Although by increasing ensemble size an arbitrarily low-amplitude atmospheric response can be made to pass statistical significance tests, utility of small-amplitude response for anticipating evolution of the earth system, and its usefulness for making skillful prediction still remains marginal.…”

Section: Introductionmentioning

confidence: 99%

Inherent Predictability, Requirements on the Ensemble Size, and Complementarity

Kumar

Chen

2015

Monthly Weather Review

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Faced with the scenario when prediction skill is low, particularly in conjunction with long-range predictions, a commonly proposed solution is that an increase in ensemble size will rectify the issue of low skill. Although it is well known that an increase in ensemble size does lead to an increase in prediction skill, the general scope of this supposition, however, is that low prediction skill is not a consequence of constraints imposed by inherent predictability limits, but an artifact of small ensemble sizes, and further, increases in ensemble sizes (that are often limited by computational resources) are the major bottlenecks for improving long-range predictions. In proposing that larger ensemble sizes will remedy the issue of low skill, a fact that is not well appreciated is that for scenarios with high inherent predictability, a small ensemble size is sufficient to realize high predictability, while for scenarios with low inherent predictability, much larger ensemble sizes are needed to realize low predictability. In other words, requirements on ensemble size (to realize the inherent predictability) and inherent predictability are complementary variables. A perceived need for larger ensembles, therefore, may also imply the presence of low predictability.

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

Cited by 37 publications

References 58 publications

Advancements in decadal climate predictability: The role of nonoceanic drivers

Advancements in decadal climate predictability: The role of nonoceanic drivers

Soil Moisture Memory and Its Effect on the Surface Water and Heat Fluxes on Seasonal and Interannual Time Scales

Inherent Predictability, Requirements on the Ensemble Size, and Complementarity

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