A spatial triage of at-risk conifer forests to support seed collection efforts and sustainable forestry.

At-risk conifer stands growing in hot, arid conditions at low elevations may contain the most climate change-adapted seeds needed for sustainable forestry. This study used a triage framework to identify high-priority survey areas for Pinus ponderosa (Pipo) within a large region, by intersecting an updated range map with a map of seed zones and elevation bands (SZEBs). The framework assesses place-based climate change and potential wildfire risks by rank-order across 740 potential collection units.

Will there be water? Climate change, housing needs, and future water demand in California.

Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and-transition simulation model that integrates climate, land-use change, water demand, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand in five counties along the Central Coast from 2010 to 2060.

A Dynamical Model of Equatorial Magnetosonic Waves in the Inner Magnetosphere: A Machine Learning Approach.

Equatorial magnetosonic waves (EMS), together with chorus and plasmaspheric hiss, play key roles in the dynamics of energetic electron fluxes in the magnetosphere. Numerical models, developed following a first principles approach, that are used to study the evolution of high energy electron fluxes are mainly based on quasilinear diffusion. The application of such numerical codes requires statistical models for the distribution of key magnetospheric wave modes to estimate the appropriate diffusion coefficients.

Comparative analysis of NOAA REFM and SNBGEO tools for the forecast of the fluxes of high-energy electrons at GEO.

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1.

Simulation of high-energy radiation belt electron fluxes using NARMAX-VERB coupled codes.

This study presents a fusion of data-driven and physics-driven methodologies of energetic electron flux forecasting in the outer radiation belt. Data-driven NARMAX (Nonlinear AutoRegressive Moving Averages with eXogenous inputs) model predictions for geosynchronous orbit fluxes have been used as an outer boundary condition to drive the physics-based Versatile Electron Radiation Belt (VERB) code, to simulate energetic electron fluxes in the outer radiation belt environment. The coupled system has been tested for three extended time periods totalling several weeks of observations.