Overview | Double thresholds | Data prep | Calculating thresholds | Calculating events | Creating visuals | Alternative second thresholds | Filtering with a second threshold | Filtering events | Visualising filtered events | Summary | References

Data | Calculating marine heatwaves (MHWs) | Visualising marine heatwaves (MHWs) | Default MHW visuals | Custom MHW visuals | Spicy MHW visuals | Calculating marine cold-spells (MCSs) | Visualising marine cold-spells (MCSs) | Default MCS visuals | Custom MCS visuals | Minty MCS visuals | Interactive visuals

Categories | Calculating MHW categories | Multiple time series | Visualising MHW categories | Default MHW category visuals | Custom MHW category visuals | Calculating MCS categories | Visualising MCS categories | Default MCS category visuals | Custom MCS category visuals | Category colour palettes

Exceedances | Calculating exceedances | Visualising exceedances | Calculating negative exceedances | Visualising negative exceedances

Overview | Setup | Downloading subsetted data | File information | Download function | Date range | Download/prep data | Visualise data | Save data | Downloading global data | Download data | Load data

ts2clm() | Details | Value | Internal functions | make_whole_fast()

Overview | MEOW | Download data and calculate climatologies | Summarise MHW metrics by year, season, and bioregion | Trends in MHW metrics at NZ scale + Bioregions | Pixel-based case scenario | References

Overview | Caveat emptor | Workflow | List of available fjords | Download a fjord | Get geographic parameters | Get bathymetry | Get climatologies of PAR0m, Kpar, and PARbottom | Get monthly time series of PARbottom | Get monthly time series of KPAR | Standard deviations for climatologies | P-functions | References

Overview | Loading data | Event detection | Two good choices: dplyr vs. plyr | The dplyr method | The plyr technique | A harmonious third option | Case study | Trend detection | Visualising the results

Overview | Subsetting using a python script | Combine daily netCDFs into an über netCDF using CDO | Extract SST data using tidync, and parallel process individual 'slices' | Apply the slice and detect functions | References

Overview | Loading data | Prepare the data | Create NetCDF shell | Create NetCDF file | Visualising the results