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   https://doi.org/10.1016/j.scitotenv.2024.174473  

   Bai, Husile; Strong, Courtenay; LaMontagne, Jalene M; Widick, Ivy V; Zuckerberg, Benjamin (July 2024, Science of The Total Environment)

   Atmospheric variability can impact biological populations by triggering facultative migrations, but the stability of these atmosphere-biosphere connections may be vulnerable to climate change. As an example, we consider the leading mode of continental-scale facultative migration of Pine Siskins, where the associated ecological mechanism is changes in resource availability, with a mechanistic pathway of climate conditions affecting mast seeding patterns in trees which in turn drive bird migration. The three summers prior to pine siskin irruption feature an alternating west-east mast-seeding dipole in conifer trees with opposite anomalies over western and eastern North America. The climate driver of this west-east mast-seeding dipole, referred to as the North American Dipole, occurs during summer in the historical record, but shifts to spring in response to future climate warming during this century in a majority of global climate models. Identification of future changes in the timing of the climate driver of boreal forest mast seeding have broadly important implications for the dynamics of forest ecosystems. 

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2. Climate sensitivity functions and net primary production: A framework for incorporating climate mean and variability

   https://doi.org/10.1002/ecy.2136  

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3. Microbiology and Climate Change: a Transdisciplinary Imperative

   https://doi.org/10.1128/mbio.03335-22  

   Lennon, J. T.; Frost, S. D.; Nguyen, N. K.; Peralta, A. L.; Place, A. R.; Treseder, K. K. (February 2023, mBio)

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   Climate change is a complex problem involving nonlinearities and feedback that operate across scales. No single discipline or way of thinking can effectively address the climate crisis. 

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4. STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change

   https://doi.org/10.5194/gmd-11-3713-2018  

   Singer, Michael Bliss; Michaelides, Katerina; Hobley, Daniel E. (January 2018, Geoscientific Model Development)

   Abstract. Assessments of water balance changes, watershed response, and landscapeevolution to climate change require representation of spatially andtemporally varying rainfall fields over a drainage basin, as well as theflexibility to simply modify key driving climate variables (evaporativedemand, overall wetness, storminess). An empirical–stochastic approach to theproblem of rainstorm simulation enables statistical realism and the creationof multiple ensembles that allow for statistical characterization and/or timeseries of the driving rainfall over a fine grid for any climate scenario.Here, we provide details on the STOchastic Rainfall Model (STORM), which usesthis approach to simulate drainage basin rainfall. STORM simulates individualstorms based on Monte Carlo selection from probability density functions(PDFs) of storm area, storm duration, storm intensity at the core, and stormcenter location. The model accounts for seasonality, orography, and theprobability of storm intensity for a given storm duration. STORM alsogenerates time series of potential evapotranspiration (PET), which arerequired for most physically based applications. We explain how the modelworks and demonstrate its ability to simulate observed historical rainfallcharacteristics for a small watershed in southeast Arizona. We explain the datarequirements for STORM and its flexibility for simulating rainfall forvarious classes of climate change. Finally, we discuss several potentialapplications of STORM. 

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5. Climate Change and Drought: a Precipitation and Evaporation Perspective

   https://doi.org/10.1007/s40641-018-0101-6  

   Dai, Aiguo; Zhao, Tianbao; Chen, Jiao (January 2018, Current Climate Change Reports)