Academic literature on the topic 'Decadal prediction'

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Journal articles on the topic "Decadal prediction"

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Meehl, Gerald A., Lisa Goddard, James Murphy, Ronald J. Stouffer, George Boer, Gokhan Danabasoglu, Keith Dixon, et al. "Decadal Prediction." Bulletin of the American Meteorological Society 90, no. 10 (October 2009): 1467–86. http://dx.doi.org/10.1175/2009bams2778.1.

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Haines, Keith, Leon Hermanson, Chunlei Liu, Debbie Putt, Rowan Sutton, Alan Iwi, and Doug Smith. "Decadal climate prediction (project GCEP)." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1890 (December 16, 2008): 925–37. http://dx.doi.org/10.1098/rsta.2008.0178.

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Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.
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Meehl, Gerald A., Lisa Goddard, George Boer, Robert Burgman, Grant Branstator, Christophe Cassou, Susanna Corti, et al. "Decadal Climate Prediction: An Update from the Trenches." Bulletin of the American Meteorological Society 95, no. 2 (February 1, 2014): 243–67. http://dx.doi.org/10.1175/bams-d-12-00241.1.

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This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about 6–9 years. Recent multimodel results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multimodel ensemble decadal hindcasts than in single model results, with multimodel initialized predictions for near-term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6–9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño–Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.
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Mieruch, S., H. Feldmann, G. Schädler, C. J. Lenz, S. Kothe, and C. Kottmeier. "The regional MiKlip decadal forecast ensemble for Europe: the added value of downscaling." Geoscientific Model Development 7, no. 6 (December 17, 2014): 2983–99. http://dx.doi.org/10.5194/gmd-7-2983-2014.

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Abstract. The prediction of climate on time scales of years to decades is attracting the interest of both climate researchers and stakeholders. The German Ministry for Education and Research (BMBF) has launched a major research programme on decadal climate prediction called MiKlip (Mittelfristige Klimaprognosen, Decadal Climate Prediction) in order to investigate the prediction potential of global and regional climate models (RCMs). In this paper we describe a regional predictive hindcast ensemble, its validation, and the added value of regional downscaling. Global predictions are obtained from an ensemble of simulations by the MPI-ESM-LR model (baseline 0 runs), which were downscaled for Europe using the COSMO-CLM regional model. Decadal hindcasts were produced for the 5 decades starting in 1961 until 2001. Observations were taken from the E-OBS data set. To identify decadal variability and predictability, we removed the long-term mean, as well as the long-term linear trend from the data. We split the resulting anomaly time series into two parts, the first including lead times of 1–5 years, reflecting the skill which originates mainly from the initialisation, and the second including lead times from 6–10 years, which are more related to the representation of low frequency climate variability and the effects of external forcing. We investigated temperature averages and precipitation sums for the summer and winter half-year. Skill assessment was based on correlation coefficient and reliability. We found that regional downscaling preserves, but mostly does not improve the skill and the reliability of the global predictions for summer half-year temperature anomalies. In contrast, regionalisation improves global decadal predictions of half-year precipitation sums in most parts of Europe. The added value results from an increased predictive skill on grid-point basis together with an improvement of the ensemble spread, i.e. the reliability.
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Mieruch, S., H. Feldmann, G. Schädler, C. J. Lenz, S. Kothe, and C. Kottmeier. "The regional MiKlip decadal forecast ensemble for Europe." Geoscientific Model Development Discussions 6, no. 4 (November 22, 2013): 5711–45. http://dx.doi.org/10.5194/gmdd-6-5711-2013.

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Abstract. Funded by the German Ministry for Education and Research (BMBF) a major research project called MiKlip (Mittelfristige Klimaprognose, Decadal Climate Prediction) was launched and global as well as regional predictive ensemble hindcasts have been generated. The aim of the project is to demonstrate for past climate change whether predictive models have the capability of predicting climate on time scales of decades. This includes the development of a decadal forecast system, on the one hand to support decision making for economy, politics and society for decadal time spans. On the other hand, the scientific aspect is to explore the feasibility and prospects of global and regional forecasts on decadal time scales. The focus of this paper lies on the description of the regional hindcast ensemble for Europe generated by COSMO-CLM and on the assessment of the decadal variability and predictability against observations. To measure decadal variability we remove the long term bias as well as the long term linear trend from the data. Further, we applied low pass filters to the original data to separate the decadal climate signal from high frequency noise. The decadal variability and predictability assessment is applied to temperature and precipitation data for the summer and winter half-year averages/sums. The best results have been found for the prediction of decadal temperature anomalies, i.e. we have detected a distinct predictive skill and reasonable reliability. Hence it is possible to predict regional temperature variability on decadal timescales, However, the situation is less satisfactory for precipitation. Here we have found regions showing good predictability, but also regions without any predictive skill.
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Meehl, Gerald A., Aixue Hu, and Claudia Tebaldi. "Decadal Prediction in the Pacific Region." Journal of Climate 23, no. 11 (June 1, 2010): 2959–73. http://dx.doi.org/10.1175/2010jcli3296.1.

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Abstract A “perfect model” configuration with a global coupled climate model 30-member ensemble is used to address decadal prediction of Pacific SSTs. All model data are low-pass filtered to focus on the low-frequency decadal component. The first three EOFs in the twentieth-century simulation, representing nearly 80% of the total variance, are used as the basis for early twenty-first-century predictions. The first two EOFs represent the forced trend and the interdecadal Pacific oscillation (IPO), respectively, as noted in previous studies, and the third has elements of both trend and IPO patterns. The perfect model reference simulation, the target for the prediction, is taken as the experiment that ran continuously from the twentieth to twenty-first century using anthropogenic and natural forcings for the twentieth century and the A1B scenario for the twenty-first century. The other 29 members use a perturbation in the atmosphere at year 2000 and are run until 2061. Since the IPO has been recognized as a dominant contributor to decadal variability in the Pacific, information late in the twentieth century and early in the twenty-first century is used to select a subset of ensemble members that are more skillful in tracking the time evolution of the IPO (EOF2) in relation to a notional start date of 2010. Predictions for the 19-yr period centered on the year 2020 use that subset of ensemble members to construct Pacific SST patterns based on the predicted evolution of the first three EOFs. Compared to the perfect model reference simulation, the predictions show some skill for Pacific SST predictions with anomaly pattern correlations greater than +0.5. An application of the Pacific SST prediction is made to precipitation over North America and Australia. Even though there are additional far-field influences on Pacific SSTs and North American and Australian precipitation involving the Atlantic multidecadal oscillation (AMO) in the Atlantic, and Indian Ocean and South Asian monsoon variability, there is qualitative skill for the pattern of predicted precipitation over North America and Australia using predicted Pacific SSTs. This exercise shows that, in the presence of a large forced trend like that in the large ensemble, much of Pacific region decadal predictability about 20 years into the future arises from increasing greenhouse gases.
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Knight, Jeff R., Martin B. Andrews, Doug M. Smith, Alberto Arribas, Andrew W. Colman, Nick J. Dunstone, Rosie Eade, et al. "Predictions of Climate Several Years Ahead Using an Improved Decadal Prediction System." Journal of Climate 27, no. 20 (October 7, 2014): 7550–67. http://dx.doi.org/10.1175/jcli-d-14-00069.1.

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Abstract Decadal climate predictions are now established as a source of information on future climate alongside longer-term climate projections. This information has the potential to provide key evidence for decisions on climate change adaptation, especially at regional scales. Its importance implies that following the creation of an initial generation of decadal prediction systems, a process of continual development is needed to produce successive versions with better predictive skill. Here, a new version of the Met Office Hadley Centre Decadal Prediction System (DePreSys 2) is introduced, which builds upon the success of the original DePreSys. DePreSys 2 benefits from inclusion of a newer and more realistic climate model, the Hadley Centre Global Environmental Model version 3 (HadGEM3), but shares a very similar approach to initialization with its predecessor. By performing a large suite of reforecasts, it is shown that DePreSys 2 offers improved skill in predicting climate several years ahead. Differences in skill between the two systems are likely due to a multitude of differences between the underlying climate models, but it is demonstrated herein that improved simulation of tropical Pacific variability is a key source of the improved skill in DePreSys 2. While DePreSys 2 is clearly more skilful than DePreSys in a global sense, it is shown that decreases in skill in some high-latitude regions are related to errors in representing long-term trends. Detrending the results focuses on the prediction of decadal time-scale variability, and shows that the improvement in skill in DePreSys 2 is even more marked.
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Towler, Erin, Debasish PaiMazumder, and James Done. "Toward the Application of Decadal Climate Predictions." Journal of Applied Meteorology and Climatology 57, no. 3 (March 2018): 555–68. http://dx.doi.org/10.1175/jamc-d-17-0113.1.

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AbstractDecadal prediction is a relatively new branch of climate science that bridges the gap between seasonal climate forecasts and multidecadal-to-century projections of climate change. This paper develops a three-step framework toward the potential application of decadal temperature predictions using the Community Climate System Model, version 4 (CCSM4). In step 1, the predictions are evaluated and it is found that the temperature hindcasts show skill over some regions of the United States and Canada. In step 2, the predictions are manipulated using two methods: a deterministic-anomaly approach (like climate change projections) and a probabilistic tercile-based approach (like seasonal forecasts). In step 3, the predictions are translated by adding a delta (for the anomaly manipulation) and conducting a weighted resample (for the probabilistic manipulation), as well as using a new hybrid method. Using the 2010 initialized hindcast, the framework is demonstrated for predicting 2011–15 over two case-study watersheds [Ottawa (Canada) and Colorado]. For the Colorado watershed, there was a noticeable shift toward higher temperatures, and the delta, weighted resample, and hybrid translations all were better at capturing the observed temperatures than was an approach that used climatological values. For the Ottawa watershed, the observed temperatures over the period of prediction were only subtly different than the climatological values; therefore, the difference between the translation methods was less noticeable. The advantages and disadvantages of the manipulation and translation approaches are discussed, as well as how their use will depend on the user context. The authors emphasize that skill evaluations should be tailored to particular applications and identify additional steps that are needed before the decadal temperature predictions can be readily incorporated into applications.
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Li, Hongmei, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz. "Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model." Earth System Dynamics 14, no. 1 (February 1, 2023): 101–19. http://dx.doi.org/10.5194/esd-14-101-2023.

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Abstract. The global carbon budget (GCB) – including fluxes of CO2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO2 growth, air–land CO2 fluxes, and air–sea CO2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO2 fluxes, and 2 years for the air–land CO2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.
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Gaetani, Marco, and Elsa Mohino. "Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations." Journal of Climate 26, no. 19 (September 24, 2013): 7708–19. http://dx.doi.org/10.1175/jcli-d-12-00635.1.

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Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.
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Dissertations / Theses on the topic "Decadal prediction"

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Robson, Jonathan Ian. "Understanding the performance of a decadal prediction system." Thesis, University of Reading, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529958.

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Hossain, Md Monowar. "CMIP5 Decadal Precipitation at Catchment Level and Its Implication to Future Prediction." Thesis, Curtin University, 2022. http://hdl.handle.net/20.500.11937/89149.

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This study assesses the monthly precipitation of CMIP5 decadal experiment over Brisbane River catchment for a spatial resolution of 0.050 and then predicts the monthly precipitation for decadal timescale through a Bidirectional LSTM and Machine Learning Algorithms using GCMs and observed data. To use GCM data in this future prediction, investigations were carried out for a suitable spatial interpolation method, a better simulation period, model drifts, and drift correction alternatives based on different skill tests.
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Kaleem, Muhammad [Verfasser]. "A sensitivity study of decadal climate prediction to aerosol variability using Echam6-HAM (GCM) / Muhammad Kaleem." Bonn : Universitäts- und Landesbibliothek Bonn, 2016. http://d-nb.info/1124540237/34.

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Liu, Xueyuan [Verfasser], and Detlef [Akademischer Betreuer] Stammer. "Impact of Consistency between the Climate Model and its Initial Conditions on Decadal Climate Prediction / Xueyuan Liu. Betreuer: Detlef Stammer." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2015. http://d-nb.info/1069376671/34.

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Ward, Neil M. "Tropical North African rainfall and worldwide monthly to multi-decadal climate variations : directed towards the development of a corrected ship wind dataset, and improved diagnosis, understanding and prediction of North African rainfall." Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385252.

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Ndiaye, Cassien Diabe. "Attribution et prévision des modulations de la mousson ouest-africaine à l’échelle de temps décennale." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS327.

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En Afrique de l’Ouest, les précipitations durant la période d’été ont connu, au cours du XXe siècle, de fortes modulations aux échelles de temps décennales. On note en particulier une période très humide vers les années 60 suivie d'un épisode de sécheresse durant les années 80 et une reprise des pluies au cours des années 2000. Ces modulations ont des conséquences socio-économiques régionales majeures. Considérées comme l’un des plus grands signaux du changement climatique en Afrique, elles ont fait l'objet de nombreuses études afin de comprendre leur(s) origine(s) et d’anticiper les prochains changements. Ces modulations ont longtemps été associées à la variabilité interne du système climatique et notamment à un rôle de la température de surface de l’océan Atlantique. De récentes études montrent cependant une contribution notable des forçages externes notamment les gaz à effet de serre et les aérosols anthropiques en particulier au cours de la seconde moitié du XXe siècle, soit via les températures de surface de l’océan Atlantique soit via un forçage radiatif direct. Dans tous les cas, le lien avec les températures de surface de l’océan offrent des perspectives de prévisibilité de ces modulations des précipitations. Les prévisions climatiques décennales ont été développées afin d’exploiter cette source de prévisibilité. Elles sont potentiellement très importantes pour la planification économique et structurelle en Afrique de l’Ouest. Dans cette thèse, nous proposons d’attribuer, en premier lieu, les modulations décennales des précipitations au Sahel sur la période temporelle de 1901-2014. En second lieu, nous proposons d’évaluer la prévision des précipitations en Afrique de l’Ouest à l’échelle de temps décennale sur la période 1968-2012. Toute cette étude est réalisée par le diagnostic de simulations climatiques réalisées à partir de modèles contribuant à la phase 6 du projet d’intercomparaison des modèles couplés. Étant donné que les modèles couplés sous-estiment communément le maximum de précipitation au Sahel durant la période d’été, nous avons commencé par proposer un domaine adaptatif des pluies au Sahel. Nos résultats de la première partie de cette thèse montrent que les forçages externes en particulier les aérosols anthropiques contribuent significativement à la chronologie des modulations décennales des précipitations sahéliennes. Ces aérosols modulent en effet la température de surface de l'océan qui se traduit en modulations de précipitation au Sahel par les déplacements de la zone de convergence intertropicale et de la dépression thermique saharienne. La seconde partie de cette thèse s'intéresse à la prévisibilité des précipitations à l’échelle de temps décennale en Afrique de l’Ouest et en particulier au Sahel. Nos résultats montrent que les précipitations sont prévisibles au Sahel dans 5⁄8 des modèles étudiés à une échéance temporelle entre 1 et 10 ans. Cependant, seuls 3 de ces 5 modèles simulent un signal décennal combiné à une variance totale réaliste à ces échéances. La moyenne multi-modèle est généralement plus prévisible que la majorité des modèles individuels. L’initialisation des variables climatiques permet d’améliorer les scores de prévision des précipitations au Sahel pour la moyenne multimodèle et 3⁄5 des modèles montrant une prévisibilité et la fiabilité des prévisions pour un seul modèle. Cet impact de l’initialisation relativement réduit corrobore l’importance des forçages externes déduits de la première étude. En conclusion, nos résultats suggèrent que les effets anthropiques sur le climat deviennent des facteurs majeurs pour expliquer les modulations décennales des précipitations moyennes de mousson au Sahel. En perspective, ces modulations sont associées, au cours du XXe siècle, à des pluies extrêmes qui sont devenues fréquentes de nos jours. Il serait intéressant de se demander si ces pluies extrêmes sont prévisibles en Afrique de l’Ouest aux échelles de temps décennales
In West Africa, rainfall during the summer period (July, August and September) has shown strong modulations on decadal time scales during the 20th century. In particular, there was a very wet period in the 1960s followed by a drought in the 1980s and a recovery of rainfall in the 2000s. These modulations have major regional socio-economic consequences. Considered as one of the most important signals of climate change in Africa, they have been the subject of numerous studies in order to understand their origin(s) and to anticipate future changes. These modulations have long been associated with the internal variability of the climate system and in particular with the role of the surface temperature of the Atlantic Ocean. However, recent studies show a significant contribution of external forcings, notably greenhouse gases and anthropogenic aerosols, in particular during the second half of the 20th century, either via Atlantic Ocean surface temperatures or via direct radiative forcing. In all cases, the link with ocean surface temperatures offers prospects for predicting these precipitation modulations. Decadal climate forecasts, i.e. with a 5-30 year time horizon, have been developed to exploit this source of predictability. They are potentially very important for economic and structural planning in West Africa. In this thesis, we propose to attribute, first, the decadal modulations of Sahel rainfall over the time period of 1901-2014. Secondly, we propose to evaluate the prediction of rainfall in West Africa on the decadal time scale over the period 1968-2012. All this study is carried out through the diagnosis of climate simulations carried out from models contributing to the phase 6 of the coupled models intercomparison project. Since coupled models commonly underestimate the maximum rainfall in the Sahel region during the summer period, we first proposed an adaptive rainfall domain for the Sahel. Our results from the first part of this thesis show that external forcings, in particular anthropogenic aerosols, contribute significantly to the timing of decadal modulations of Sahel rainfall. These aerosols indeed modulate the ocean surface temperature which is translated into precipitation modulations in the Sahel by the displacement of the intertropical convergence zone and the Saharan Heat Low. The second part of this thesis focuses on the predictability of precipitation on decadal time scales in West Africa and in particular in the Sahel. Our results show that rainfall is predictable in the Sahel in 5⁄8 of the models studied at lead times between 1 and 10 years. However, only 3 of these 5 models simulate a decadal signal combined with a realistic total variance (signal-to-noise ratio close to 1) at these lead times. The multi-model mean is generally more predictable than the majority of individual models. Initialization of climate variables improves Sahel rainfall prediction skills for the multi-model mean and 3⁄5 of the models showing predictability and forecast reliability for a single model. This relatively small impact corroborates the importance of external forcings inferred from the first part of this thesis. In conclusion, our results suggest that anthropogenic effects on climate become major factors in explaining decadal modulations of mean monsoon rainfall in the Sahel. In perspective, these modulations are associated, during the 20th century, with extreme rainfall events that have become frequent nowadays. It would be interesting to ask whether these extreme events are predictable in West Africa on decadal time scales
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Kruschke, Tim [Verfasser]. "Winter wind storms : Identifcation, verifcation of decadal predictions, and regionalization / Tim Kruschke." Berlin : Freie Universität Berlin, 2015. http://d-nb.info/107549334X/34.

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Stolzenberger, Sophie [Verfasser]. "On the probabilistic evaluation of decadal and paleoclimate model predictions / Sophie Stolzenberger." Bonn : Universitäts- und Landesbibliothek Bonn, 2017. http://d-nb.info/1149154012/34.

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Uhlig, Marianne [Verfasser], and C. [Akademischer Betreuer] Kottmeier. "Regional decadal climate predictions for Europe – Feasibility & Skill / Marianne Uhlig ; Betreuer: C. Kottmeier." Karlsruhe : KIT-Bibliothek, 2016. http://d-nb.info/1132996732/34.

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Kadow, Christopher [Verfasser]. "Improving decadal climate predictions by ocean ensemble dispersion filtering and an efficient systematic evaluation / Christopher Kadow." Berlin : Freie Universität Berlin, 2019. http://d-nb.info/1178424464/34.

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Books on the topic "Decadal prediction"

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United Way of America. Strategic Planning Division., ed. What lies ahead--a mid-decade view: An environmental scan report. Alexandria, Va. (701 N. Fairfax St., Alexandria 22314-2045): United Way of America, Strategic Planning Division, 1985.

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Laermer, Richard. 2011: Trendspotting for the next decade. New York: McGraw-Hill, 2008.

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2011: Trendspotting for the next decade. New York: McGraw-Hill, 2008.

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T, Anderson D. L., ed. The TOGA decade: Reviewing the progress of El Niño research and prediction. Washington DC: American Geophysical Union, 1998.

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W, Willingham Warren, Angoff William 1919-, College Entrance Examination Board, and Educational Testing Service, eds. Predicting college grades: An analysis of institutional trends over two decades. [Princeton, N.J.]: Educational Testing Service, 1990.

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Namita, Bhandare, ed. Vision 2020 challenges for the next decade: Hindustan Times Leadership Summit. New Delhi: Roli Books, 2010.

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V, Sawhill Isabel, ed. Challenge to leadership: Economic and social issues for the next decade. Washington, D.C: Urban Institute Press, 1988.

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Payne, Mark R., Alistair J. Hobday, Brian R. MacKenzie, and Desiree Tommasi, eds. Seasonal to Decadal Prediction of Marine Ecosystems: Opportunities, Approaches, and Applications. Frontiers Media SA, 2019. http://dx.doi.org/10.3389/978-2-88945-881-3.

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Seasonal-to-Decadal Predictions of Arctic Sea Ice. Washington, D.C.: National Academies Press, 2012. http://dx.doi.org/10.17226/13515.

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Seasonal-To-Decadal Predictions of Arctic Sea Ice: Challenges and Strategies. National Academies Press, 2012.

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Book chapters on the topic "Decadal prediction"

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Alves, Oscar, Debra Hudson, Magdalena Balmaseda, and Li Shi. "Seasonal and Decadal Prediction." In Operational Oceanography in the 21st Century, 513–42. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0332-2_20.

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Wu, Bo, and Bin Wang. "Decadal Climate Prediction of FGOALS." In Flexible Global Ocean-Atmosphere-Land System Model, 233–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41801-3_28.

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Mamalakis, Antonios, Imme Ebert-Uphoff, and Elizabeth A. Barnes. "Explainable Artificial Intelligence in Meteorology and Climate Science: Model Fine-Tuning, Calibrating Trust and Learning New Science." In xxAI - Beyond Explainable AI, 315–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04083-2_16.

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AbstractIn recent years, artificial intelligence and specifically artificial neural networks (NNs) have shown great success in solving complex, nonlinear problems in earth sciences. Despite their success, the strategies upon which NNs make decisions are hard to decipher, which prevents scientists from interpreting and building trust in the NN predictions; a highly desired and necessary condition for the further use and exploitation of NNs’ potential. Thus, a variety of methods have been recently introduced with the aim of attributing the NN predictions to specific features in the input space and explaining their strategy. The so-called eXplainable Artificial Intelligence (XAI) is already seeing great application in a plethora of fields, offering promising results and insights about the decision strategies of NNs. Here, we provide an overview of the most recent work from our group, applying XAI to meteorology and climate science. Specifically, we present results from satellite applications that include weather phenomena identification and image to image translation, applications to climate prediction at subseasonal to decadal timescales, and detection of forced climatic changes and anthropogenic footprint. We also summarize a recently introduced synthetic benchmark dataset that can be used to improve our understanding of different XAI methods and introduce objectivity into the assessment of their fidelity. With this overview, we aim to illustrate how gaining accurate insights about the NN decision strategy can help climate scientists and meteorologists improve practices in fine-tuning model architectures, calibrating trust in climate and weather prediction and attribution, and learning new science.
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Seager, Richard, Alicia R. Karspeck, Mark A. Cane, Yochanan Kushnir, Alessandra Giannini, Alexey Kaplan, Ben Kerman, and Jennifer Velez. "Predicting Pacific Decadal Variability." In Earth's Climate, 105–20. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/147gm06.

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Goddard, Lisa. "Climate Predictions, Seasonal-to-Decadal." In Encyclopedia of Sustainability Science and Technology, 2119–48. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_368.

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Goddard, Lisa. "Climate Predictions, Seasonal-to-Decadal." In Climate Change Modeling Methodology, 261–301. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5767-1_11.

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Panitz, H. J., G. Schädler, M. Breil, S. Mieruch, H. Feldmann, K. Sedlmeier, N. Laube, and M. Uhlig. "Application of the Regional Climate Model CCLM for Studies on Urban Climate Change in Stuttgart and Decadal Climate Prediction in Europe and Africa." In High Performance Computing in Science and Engineering ´15, 593–606. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24633-8_38.

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Kirtman, Ben, David Anderson, Gilbert Brunet, In-Sik Kang, Adam A. Scaife, and Doug Smith. "Prediction from Weeks to Decades." In Climate Science for Serving Society, 205–35. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6692-1_8.

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Demortain, David. "The Digitalisation of Risk Assessment: Fulfilling the Promises of Prediction?" In Safety in the Digital Age, 11–19. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-32633-2_2.

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AbstractRisk assessment is a scientific exercise that aims at anticipating hazards. Prediction has always been a rallying call for the scientists that gave birth to this interdisciplinary movement in the 1970s. Several decades later, the broad movement of digitalisation and the promises of artificial intelligence seem to be pushing the limits of risk assessment and herald an era of faster and more precise predictions. This chapter briefly reviews the history of chemical risk assessment methods developed by regulatory bodies and associated research groups, and the complex ways it has digitalised. It unpacks digitalisation, to probe how its various aspects—datafication, computational innovation and modelling theories—align to meaningfully transform it, and determine whether the ever-revamped technological promise of prediction is within a closer reach than it was before.
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Wong, Peter Kok-Yiu, Chin Pok Lam, Yin Ni Lee, Chung Lam Ting, Jack C. P. Cheng, and Pak Him Leung. "Predictive Safety Monitoring for Lifting Operations with Vision-Based Crane-Worker Conflict Prediction." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality, 648–56. Florence: Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.64.

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Construction industry has reported among the highest accident and fatality rates over the past decade. In particular, crane lifting is a notably hazardous operation on construction sites, causing fatal accidents like workers being struck by the boom or objects fallen from tower cranes. Manual monitoring by on-site safety officers is labour-intensive and error-prone, while incorporating computer vision techniques into surveillance cameras would enable more automatic and continuous monitoring of construction site operations. However, existing studies for lifting safety mainly detect the presence of individual objects (e.g. workers, crane components), while a methodology is needed to predict their potential collision more proactively before accidents happen. This paper develops a vision-based framework for predictive lifting safety monitoring, including three modules: (1) object detection and classification: targeting at hook and lifting materials to enable danger zone estimation, along with workers and their personal protective equipment; (2) worker movement tracking and prediction: analyzing the historical moving trajectory of each unique worker to foresee his/her future movement in certain period ahead; (3) multi-level safety assessment: issuing predictive warning in real-time upon any crane-worker conflict foreseen. The proposed framework is applicable to real-time site video processing and enables end-to-end lifting safety monitoring with instant alerting upon unsafe scenarios observed. Importantly, the proposed framework predicts the future movement of workers to proactively identify potential site hazard, in order to trigger earlier safety alert for more timely decision-making. With a large video dataset capturing tower crane operations, the proposed framework demonstrates competitive accuracy and computational efficiency in crane-worker conflict prediction, validating its practicality for real-time lifting safety monitoring
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Conference papers on the topic "Decadal prediction"

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Hurrell, J,W,, J,W, Hurrell, J,W, Hurrell, J,W, Hurrell, J,W, Hurrell, J,W, Hurrell, J,W, Hurrell, et al. "Decadal Climate Prediction: Opportunities and Challenges." In OceanObs'09: Sustained Ocean Observations and Information for Society. European Space Agency, 2010. http://dx.doi.org/10.5270/oceanobs09.cwp.45.

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Hurrell, J. W., M. Latif, M. Visbeck, T. L. Delworth, G. Danabasoglu, D. Dommenget, H. Drange, et al. "Decadal Climate Variability, Predictability and Prediction: Opportunities and Challenges." In OceanObs'09: Sustained Ocean Observations and Information for Society. European Space Agency, 2010. http://dx.doi.org/10.5270/oceanobs09.pp.23.

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Latif, Mojib, Mojib Latif, Mojib Latif, Mojib Latif, Mojib Latif, Mojib Latif, Mojib Latif, Mojib Latif, and Mojib Latif. "Dynamics of Decadal Climate Variability and Implications for its Prediction." In OceanObs'09: Sustained Ocean Observations and Information for Society. European Space Agency, 2010. http://dx.doi.org/10.5270/oceanobs09.cwp.53.

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Chaudhary, Niharika, and Sanjay Saini. "A Progress on Protein Structure Prediction using Various Soft Computing Techniques." In 9th International Conference on Computer Science and Information Technology (CSIT 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121410.

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In molecular and computational biology, predicting the three-dimensional structure of a protein from its amino acid sequence has long been an outstanding goal. Soft computing techniques for solving protein structure prediction problems have been gaining the attention of researchers because of their capacity to accommodate imprecision and uncertainty in vast and complicated search spaces. This paper provides a comprehensive overview of recent protein structure prediction efforts and progress using various soft computing techniques. This paper summarises key research in the field of protein structure prediction that has been published in the recent decade. Despite significant research efforts in recent decades, there is still a lot of room for improvement in this field.
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Rosa-Cánovas, Juan José, Matilde García-Valdecasas Ojeda, Emilio Romero-Jiménez, Patricio Yeste, César Quishpe-Vásquez, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, and María Jesús Esteban-Parra. "Assessing The Predictive Skill Of Drought With High-Resolution Decadal Climate Predictions In The Iberian Peninsula." In Proceedings of the 39th IAHR World Congress From Snow to Sea. Spain: International Association for Hydro-Environment Engineering and Research (IAHR), 2022. http://dx.doi.org/10.3850/iahr-39wc252171192022929.

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Kolla, Srinivas Swaroop, Ram S. Mohan, and Ovadia Shoham. "Mechanistic Modeling of Liquid Carry-Over for 3-Phase Flow in GLCC© Compact Separators." In ASME 2018 5th Joint US-European Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fedsm2018-83407.

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Gas-Liquid Cylindrical Cyclone (GLCC©) Separators have been in use in petroleum and other related industries for over two decades. Prediction of Liquid Carry-Over Operational Envelope (LCO-OE) is essential for designing and proper operation of GLCC©. Earlier mechanistic models for predicting LCO-OE were based on gas-liquid phase flow. A new mechanistic model has been developed for the prediction of the LCO-OE incorporating the effect of watercut and fluid properties for a GLCC© under liquid level and pressure control configuration. The new model captures the effect of viscosity and surface tension on the LCO-OE and the effect of water cut on the onset of annular mist velocity. Comparison between the developed mechanistic model predictions for LCO-OE with the experimental data show a good agreement.
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Toro Ortiz, Yenny Marcela, Sonia Raquel Gámiz-Fortis, Yolanda Castro-Díez, Reiner Palomino-Lemus, María Jesús Esteban-Parra, and Samir Córdoba-Machado. "High-resolution decadal predictions analysis of drought events in Colombia." In Proceedings of the 39th IAHR World Congress From Snow to Sea. Spain: International Association for Hydro-Environment Engineering and Research (IAHR), 2022. http://dx.doi.org/10.3850/iahr-39wc2521711920221413.

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NICHOLLS, ROBERT J., JON FRENCH, HELENE BURNINGHAM, BAREND VAN MAANEN, ANDRES PAYO, JAMES SUTHERLAND, MIKE WALKDEN, et al. "IMPROVING DECADAL COASTAL GEOMORPHIC PREDICTIONS: AN OVERVIEW OF THE iCOASST PROJECT." In Coastal Sediments 2015. WORLD SCIENTIFIC, 2015. http://dx.doi.org/10.1142/9789814689977_0227.

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Kaminsky, George M., Maarten C. Buijsman, and Peter Ruggiero. "Predicting Shoreline Change at Decadal Scale in the Pacific Northwest, USA." In 27th International Conference on Coastal Engineering (ICCE). Reston, VA: American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40549(276)188.

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Hu, Bin, Yong Huang, Fang Wang, and Fa Xie. "Numerical Simulation of Cold Flow Field of Aero-Engine Combustors for Lean Blow Off Analysis." In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/gt2011-45467.

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Lean blow off (LBO) performance is critical to the operational performance of combustion system in propulsion and power generation. Current predictive tools for LBO are based on decades-old empirical correlations that have limited applicability for modern combustor designs. Recent advances in computational fluids dynamics (CFD) have provided new insight into the fundamental processes that occur in these flows. In this paper, it is envisaged a new methodology for the LBO predictions that is predicting the LBO fuel/air ratio based on the cold flow field of the combustor. Comparing to the traditional tools, this methodology has the lower prediction cost, especially in the designing stage of the combustor. The study presented here is the preliminary study of this method. According to the Lefebvre’s LBO model, a new load parameter (mr·Vf) extracted from the cold flow field is obtained for LBO analysis. Commercial software FLUENT is used to simulate the velocity and concentration field without combustion in different combustors. LBO fuel/air ratios are obtained from the model combustor experiments. Flammable zone volume (Vf) is used instead of Vc (as defined in Lefebvre’s model: combustor volume ahead of the dilution holes) in this LBO analysis. Vf is defined according to the lean/rich limits and increased with the increase of φLBO. In addition, the mass flow rate of back-flow air which enters the flammable zone (mr) is used to account for the combustion air. φLBO is increased in a parabolic way with the increase of mr. The load parameter (mr·Vf) could represent the actual combustion load of the combustor near LBO and relates φLBO to the cold flow field of the combustor. It will be encouraging and beneficial to the study of LBO prediction in the future.
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Reports on the topic "Decadal prediction"

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Ghil, Michael, Andrew W. Robertson, Edward R. Cook, Rosanne D’Arrigo, Upmanu Lall, and Padhraic J. Smyth. Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia. Office of Scientific and Technical Information (OSTI), January 2015. http://dx.doi.org/10.2172/1168586.

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McClean, Julie L. Towards a Fine-Resolution Global Coupled Climate System for Prediction on Decadal/Centennial Scales. Office of Scientific and Technical Information (OSTI), November 2013. http://dx.doi.org/10.2172/1105025.

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Smyth, Padhraic. Final technical report for Decadal Prediction and Stochastic Simulation of Hydroclimate over Monsoonal Asia. Office of Scientific and Technical Information (OSTI), March 2016. http://dx.doi.org/10.2172/1241554.

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Branstator, Grant. Initial value predictability of intrinsic oceanic modes and implications for decadal prediction over North America. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1165163.

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Gutowski, William J. Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1415029.

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Liu, Zhengyu, J. Kutzbach, R. Jacob, and C. Prentice. Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1030607.

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Katzenberger, John. Aspen Global Change Institute (AGCI) Interdisciplinary Science Workshop: Decadal Climate Prediction; Aspen, CO; June 22-28, 2008. Office of Scientific and Technical Information (OSTI), March 2010. http://dx.doi.org/10.2172/1130064.

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Mao, Jiafu, Yaoping Wang, Daniel Ricciuto, Salil Mahajan, Forrest Hoffman, Xiaoyoing Shi, and Giri Prakash. AI-Based Integrated Modeling and Observational Framework for Improving Seasonal to Decadal Prediction of Terrestrial Ecohydrological Extremes. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1769666.

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Hoffman, Forrest, Jitendra Kumar, Zheng Shi, Anthony Walker, Jiafu Mao, Yaoping Wang, Abigail Swann, et al. AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1769668.

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Maslowski, Wieslaw, John J. Cassano, William J. Gutowski, Jr., William H. Lipscomb, Bart Nijssen, Andrew Roberts, William Robertson, Slawek Tulaczyk, and Xubin Zeng. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM). Office of Scientific and Technical Information (OSTI), May 2011. http://dx.doi.org/10.2172/1329071.

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