Spring Onset Predictability in the North American Multimodel Ensemble

Carrillo, Carlos M.; Ault, Toby R.; Wilks, Daniel S.

doi:10.1029/2018jd028597

Cited by 8 publications

(8 citation statements)

References 26 publications

(47 reference statements)

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“…10-m winds from one NMME model, CCSM4, were used to force wave models by Bell and Kirtman (2019). Carrillo et al (2018) find promise in the prediction of the beginning of the spring season using daily maximum and minimum temperature, but only after the application of a sophisticated post-processing. They point out that the length of training period and ensemble size are both important for developing a skillful forecast for spring onset, a common theme amongst studies that use the Phase II database.…”

Section: Emerging and Future Directionsmentioning

confidence: 99%

A Decade of the North American Multimodel Ensemble (NMME): Research, Application, and Future Directions

Becker

Kirtman

L’Heureux

et al. 2022

Bulletin of the American Meteorological Society

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Ten years, sixteen fully coupled global models, and hundreds of research papers later, the North American Multi-Model Ensemble (NMME) monthly-to-seasonal prediction system is looking ahead to its second decade. The NMME comprises both real-time, initialized predictions and a substantial research database; both retrospective and real-time forecasts are archived and freely available for research and development. Many US-based and international entities, both private and public, use NMME data for regional or otherwise tailored forecasts. The system’s built-in evolution, with new models gradually replacing older ones, has been demonstrated to gradually improve the skill of 2 m temperature and sea surface temperature, although precipitation prediction remains a difficult problem. This paper reviews some of the NMME-based contributions to seasonal climate prediction research and applications, progress on scientific understanding of seasonal prediction and multi-model ensembles, and new techniques. Several prediction-oriented aspects are explored, including model representation of observed trends and the under-prediction of below-average temperature. We discuss potential new directions, such as higher-resolution models, hybrid statistical-dynamical techniques, or prediction of environmental hazards such as coastal flooding and the risk of mosquito-borne diseases.

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Section: Emerging and Future Directionsmentioning

confidence: 99%

A Decade of the North American Multimodel Ensemble (NMME): Research, Application, and Future Directions

Becker

Kirtman

L’Heureux

et al. 2022

Bulletin of the American Meteorological Society

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“…Improvements could be made to the climate forecast integration, such as improved downscaling methods or the addition of alternative global climate models. Carrillo et al (2018) found a large increase in skill by using a post-hoc ensemble bias correction with a long training time series, and a similar bias correction could be applied to in our system. There are other abiotic drivers which are important for phenology, such as precipitation and daylength (Diez et al, 2012).…”

Section: Discussionmentioning

confidence: 75%

“…While several studies have shown ecological forecasting can be aided by weather and climate forecasts (Carrillo et al, 2018;Van Doren and Horton, 2018), climate forecasts with a lead time of 1 year or less are still rarely used in ecology, likely because of the associated computational challenges (Taylor and White, 2020). Our species level analyses show some potential value for incorporating these climate forecasts, which produced increases in skill for two of the most common plants in our forecast system, Forsythia spp.…”

Section: Discussionmentioning

confidence: 88%

“…However, many aspects of ecological systems are closely tied to weather and climate and should benefit from including these forecasts. For example, Van Doren and Horton (2018) showed a bird migration model had ample explanatory value using a 7-day weather forecast (R 2 =0.62), and Carrillo et al (2018) found that a spring index model had positive skill up to a two month lead time by integrating climate forecasts. Exploring how these forecasted drivers, and their associated uncertainty, affect performance is an important step in evaluating near-term ecological forecasts (Dietze et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Influence of climate forecasts, data assimilation, and uncertainty propagation on the performance of near-term phenology forecasts

Taylor

White

2020

Preprint

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Evaluation of ecological forecasts is a vital step in the continuous improvement of near-term ecological forecasts. Here we performed a thorough evaluation of a near-term phenological forecast system which has been operating for several years. We evaluated point forecast accuracy and the reliability of the prediction intervals. We also tested the contribution of upstream climate forecasts on phenology forecast proficiency. We found that 9 month climate forecasts contributed little skill overall, though some species did benefit from them. The assimilation of observed winter and spring temperature provided the largest improvement of forecast skill throughout the spring. We also found that phenology forecast prediction intervals were most robust when uncertainty was propagated from climate, phenological model, and model parameters as opposed to using climate uncertainty alone. Our analysis points the way toward several potential improvements to the forecasting system, which can be re-evaluated at a future date in a continuous cycle of forecast refinement.

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“…Demand for information and ecological forecasts at multiple time scales is growing considerably among natural resource managers to guide planning and anticipate change (Bradford et al, ; Dietze et al, ). This information could serve as a valuable complement to seasonal and shorter‐term weather and phenology forecasts (Carillo et al, ; Kirtman et al, ; Mo & Lettenmaier, ; Saha et al, ).…”

Section: Introductionmentioning

confidence: 99%

Does an Early Spring Indicate an Early Summer? Relationships Between Intraseasonal Growing Degree Day Thresholds

Crimmins

2019

JGR Biogeosciences

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Spring heat accumulation plays a major role in the timing of events such as leaf-out, leaf expansion, flowering, and insect hatch in temperate systems. Accordingly, heat accumulation can serve as a proxy for the timing of plant and insect phenological activity and can be used in a predictive way when the timing of heat accumulation thresholds being reached can be anticipated. This has strong value for a host of planning and management applications. If relationships exist between earlier-and later-season thresholds at a location, then the timing of later-season phenological events that are forced by the accumulation of warmth could be anticipated based on when earlier-season thresholds are met. Using high-resolution daily temperature data, we calculated the coherence in pairs of spring-season heat accumulation (growing degree day) threshold anomalies over 1948-2016. Overall, relationships between thresholds spanning the entire spring season were relatively low, while later season thresholds exhibited much higher correlations. This pattern is generally the result of decreasing variability in heat accumulation with season progression. However, correlation strengths did not follow latitudinal or gradients, revealing that within-season heat accumulation and interannual variability in threshold timing are unique to the specified base temperature and thresholds being compared. We show that the relationships between earlier-and later-season heat accumulation thresholds were sufficient to accurately predict the timing of phenological events in plants in two case examples. Plain Language SummaryIn several recent years, spring has arrived especially early across much of the United States. Warm temperatures occurred earlier than average, and consequently, many trees and crops put on leaves or flowered days or weeks ahead of normal. Whether an early start to spring season weather conditions-and subsequently, plant and insect activity-leads to similarly early initiation of later-season events in plant and insect life cycles is not well understood. In some locations in the United States, the timing of the arrival of warm spring temperatures is a strong predictor of when biological events that occur in the middle and later part of spring would occur: an early start to spring will mean that later events will continue to occur ahead of schedule. In many other locations, the relationship is not as strong. These findings are important for scheduling management activities later in the season. For example, insect pest managers might use information regarding whether warm temperatures in the beginning or middle of spring are occurring ahead of schedule to plan whether crews should be dispatched earlier than usual. Key Points: • The ability to anticipate the timing of late spring phenological events using the timing of early-season heat is variable across the United States • Locations exhibiting strong relationships between the timing of early-season and later-season thresholds vary by base temperature • As the season progresses, relati...

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Spring Onset Predictability in the North American Multimodel Ensemble

Cited by 8 publications

References 26 publications

A Decade of the North American Multimodel Ensemble (NMME): Research, Application, and Future Directions

A Decade of the North American Multimodel Ensemble (NMME): Research, Application, and Future Directions

Influence of climate forecasts, data assimilation, and uncertainty propagation on the performance of near-term phenology forecasts

Does an Early Spring Indicate an Early Summer? Relationships Between Intraseasonal Growing Degree Day Thresholds

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