The files described here are the Main Hawaiian Islands (MHI) Atlantis Ecosystem model input files used in for testing CMIP6 climate scenarios developed by main Hawaiian Islands ROMS. These input files were used to run forecast simulations under three different CMIP6 climate change scenarios: low-emission (SSP1-2.6), moderate-emission (SSP2-4.5), and high-emission (SSP3-7.0). Files included are parameter (.prm), initial conditions (.nc), and land-based source pollutants (LBSP) forcing files. The parameter files include a run file, biological parameters, forcing parameters (list climate and pollution forcing files), harvest parameters (fishing mortality), and physics parameters. The LBSP forcing files are time series files representing spatial deposition of nutrients and sediments from land to the nearshore regions covered by Hawaii Atlantis. In recalibrating the current model based on updated climate forcing files (ROMS projections), the parameter and initial conditions files have been adjusted since initial model development. The ROMS projections used to force Hawaii Atlantis are not included in this data set, as they are from a different project. Hawaii Atlantis was initially developed at PIFSC and further details regarding the model, as well as outputs of a model run based on older inputs, are hosted as InPort catalog item 55245. The LBSP forcing files hosted here were developed based on Ocean Tipping Points project data as part of initial model development.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). Aside from these typical bioclimatic variables, we also calculated annual and mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate. As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.

Tabular data output from a series of modeling simulations for the seven main Hawaiian Islands. We used the LUCAS model to project changes in ecosystem carbon balance resulting from land use, land use change, climate change, and wildfire. The model was run at a 250-m spatial resolution on an annual timestep from the years 2010 to 2100. We simulated four unique scenarios, consisting of all combinations of two land-use scenarios and two radiative forcing scenarios. For each scenario, we ran 30 Monte Carlo realizations of the model. Results presented here have been aggregated from the individual cell level and summarized by island or vegetation class. Model input data and the R code used to generate it, as well as R code used to summarize and analyze model output data, can be found in the HI_Model GitHub repository (https://github.com/selmants/HI_Model).

The goal of this project was to produce estimates of the change in three ecosystem services - water yield, sediment runoff, and reef productivity (or seafood benefits) - under climate change and three newly developed land cover scenarios. The developed land cover scenarios expanded upon the Hawaii Carbon Assessment by simulating future land cover scenarios. The resulting scenarios used measures of invasive species spread and fire-driven forest loss to compare baseline conditions of current ecosystem protection (Protection) with “No Protection”, and “Protection and Restoration” for years 2070-2100. Using the land cover scenarios as an input to the ecosystem services models the results for water yield and sediment yield benefits are provided as the difference between worse case scenario and protection scenarios, each as a raster of per pixel change and the reef productivity, or estimated fish catch per ha, is provided as a shapefile summarized by Moku (Hawaiian Land Division), only for the difference between Targeted Protection and No Protection.

We integrated recent climate model projections developed for the State of Hawai’i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used observation-based data for the baseline bioclimatic variables from the Rainfall Atlas of Hawai’i. We used the most up-to-date dynamically downscaled future projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two projections into a suite of 19 bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions specifically for the Hawaiian Islands. These bioclimatic variables are available state-wide for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under RCP 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections). As Hawai’i is characterized by two 6-month seasons, we also provide mean seasonal variables for all scenarios based on the dry (May-October) and wet (November-April) seasonality of Hawaiian climate.