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Hydro Climate Evaluation Map

The site hydro.rap.ucar.edu/hydro-climate-eval is an interactive web map of hydro-climate data based on CarbonPlan's maps.

Map Viewing Options

Viewing Option Descriptin Variables
Ave. Map of metrics averages over the time period Year Range , Downscaling Method, Climate Model, Metrics
Dif. Map of the difference of the climate data against an observational dataset Dif. Obs. Data, Downscaling Method, Climate Model, Metrics
Climate Signal: Method & Model View climate signal based on specific method and model Downscaling Method, Climate Model, Metrics, RCP Scenario
Climate Signal: Metric Performance View climate signal averaging over best performing datasets Selecting Performance Metrics

Variable Details

Year Range

Name Description
1981-2004 Time range past yearly data averaged over
2006-2099 Time range future yearly data averaged over

Downscaling Methods

See this detailed downscaling methods matrix document for more information on some of the datasets mapped.

Name URL
ICAR Intermediate Complexity Atmospheric Research Model
GARD_R2 GARD analog regression on precipitation and 500mb horizontal wind
GARD_R3 GARD analog regression on 500mb water vapor and 500mb horizontal wind
LOCA_8th LOcalized Constructed Analog (LOCA)
MACA Multivariate Adaptive Constructed Analogs
NASA-NEX NCCS NASA

Climate Models

Name URL
ACCESS1-3 Australian Community Climate and Earth System Simulator
CanESM2 Canadian Earth System Model
CCSM4 Community Climate System Model
MIROC5 Model for Interdisciplinary Research on Climate
NorESM-M Norwegian Earth System Model

Metrics

Name Description
DJF_P Dec/Jan/Feb seasonal mean of precipitation
DJF_T Dec/Jan/Feb seasonal mean of temperature
JJA_P Jun/Jul/Aug seasonal mean of precipitation
JJA_T Jun/Jul/Aug seasonal mean of temperature
MAM_P Mar/Apr/May seasonal mean of precipitation
MAM_T Mar/Apr/May seasonal mean of temperature
N34PR Nino 3.4 precipitation teleconnection pattern spactial correlation
N34T Nino 3.4 temperature teleconnection pattern spactial correlation
PR90 Precipitation extremes in the 90th percentile
PR99 Precipitation extremes in the 99th percentile
PTREND Precipitation trends
SON_P Sep/Oct/Nov seasonal mean of precipitation
SON_T Sep/Oct/Nov seasonal mean of temperature
T90 Temperature extremes in the 90th percentile
T99 Temperature extremes in the 99th percentile
TTREND Temperature trends

Dif. Obs. Data

Observational dataset used to compute the difference against.

Name Description
CONUS404 Four-kilometer long-term regional hydroclimate reanalysis
GMET Gridded Meteorological Ensemble Tool
Livneh Livneh hydrometeorological dataset
Maurer Maurer hydrometeorological dataset
NLDAS North American Land Data Assimilation System
PRISM PRISM Climate Group

Representative Concentration Pathway (RCP) Scenario

Name Description
4.5 Radiative forcing levels of 4.5 W/m² above pre-industrial levels by 2100
8.5 Radiative forcing levels of 8.5 W/m² above pre-industrial levels by 2100

Selecting Performance Metrics

Steps Description
1. Select Metrics Select metrics to use as the criteria for choicing the best performing maps
2. Select Future RCP Scenario RCP scenario to map
3. Number of Datasets Number of climate signal datasets to average over
4. Compute Climate Signal Compute climate signal map after completing previous steps
Plot Metric Plot selected metrics

Build

Prerequisites

Local Build

$ npm install .
$ npm local
$ npm run

Production Build

For hosting at hydro.rap.ucar.edu/hydro-climate-eval

$ npm install .
$ npm run dev
$ npm start

View Local Map

Go to localhost:3000 in a browser to preview website.

image

License

License is based on CarbonPlan's maps. All the original code in this repository is MIT licensed. The library contains code from mapbox-gl-js version 1.13 (3-Clause BSD licensed). Please provide attribution if reusing any of our digital content (graphics, logo, copy, etc.).