Data Catalogue

🌎

Historical reference

What happened. Observation-forced, for validation and attribution.

  • ForcingGSWP3-W5E5
  • Period1960–2019
  • Files6
  • Size1.31 TiB
📈

Scenarios

What could happen. GCM-forced, baseline plus three SSPs.

  • Forcing5 CMIP6 GCMs
  • Period1960–2014, 2015–2100
  • Files104
  • Size9.70 TiB
⚠️

Quality assurance

Simulation quality information.

  • Forcing—
  • CoverageGlobal
  • Layers3
  • StatusAwaiting deposit

GLOBGM is a two-layer groundwater model, with outputs available for both layers. Properly interpreting these layers is essential for selecting the appropriate data in your analysis.

The aquifer type at any location is determined by the data presence in each layer:

The four continental scale groundwater models that constitute GLOBGM - a global groundwater model. Dark overlays indicate the presence of a confining layer and grids visualises the data structure regarding the two model layers.

Historical reference

Forcing GSWP3-W5E5 (observational)
Period 1960–2019
Members Single run, no ensemble
Recommended use Validation, attribution
Archive YODA landing page
ⓘAggregation Period Variable Size (GiB) Download
Average1960–2019Head5.38Download
Average1960–2019Water table depth5.38Download
Annual1960–2019Head47.84Download
Annual1960–2019Water table depth54.90Download
Monthly1960–2019Head574.04Download
Monthly1960–2019Water table depth658.84Download

Scenarios

Forcing 5 CMIP6 GCMs, bias-corrected
Baseline CMIP6 historical, 1960–2014
Projections SSP1-2.6, SSP3-7.0, SSP5-8.5, 2015–2100
Archives Average · Annual · Monthly
ⓘMember Period Scenario Aggregation Variable Size (GiB) Download
Ensemble1960–2014CMIP6 historicalAverageHead5.38Download
Ensemble1960–2014CMIP6 historicalAverageWater table depth5.38Download
Ensemble1960–2014CMIP6 historicalAnnualHead43.98Download
Ensemble1960–2014CMIP6 historicalAnnualWater table depth50.44Download
Ensemble1960–2014CMIP6 historicalMonthlyHead526.28Download
Ensemble1960–2014CMIP6 historicalMonthlyWater table depth603.83Download
Ensemble2015–2100SSP1-2.6AverageHead5.38Download
Ensemble2015–2100SSP1-2.6AverageWater table depth5.38Download
Ensemble2015–2100SSP1-2.6AnnualHead68.92Download
Ensemble2015–2100SSP1-2.6AnnualWater table depth78.81Download
Ensemble2015–2100SSP1-2.6MonthlyHead826.19Download
Ensemble2015–2100SSP1-2.6MonthlyWater table depth945.04Download
Ensemble2015–2100SSP3-7.0AverageHead5.38Download
Ensemble2015–2100SSP3-7.0AverageWater table depth5.38Download
Ensemble2015–2100SSP3-7.0AnnualHead68.95Download
Ensemble2015–2100SSP3-7.0AnnualWater table depth78.81Download
Ensemble2015–2100SSP3-7.0MonthlyHead826.59Download
Ensemble2015–2100SSP3-7.0MonthlyWater table depth945.03Download
Ensemble2015–2100SSP5-8.5AverageHead5.38Download
Ensemble2015–2100SSP5-8.5AverageWater table depth5.38Download
Ensemble2015–2100SSP5-8.5AnnualHead68.95Download
Ensemble2015–2100SSP5-8.5AnnualWater table depth78.80Download
Ensemble2015–2100SSP5-8.5MonthlyHead826.57Download
Ensemble2015–2100SSP5-8.5MonthlyWater table depth944.98Download
GFDL-ESM41960–2014CMIP6 historicalAverageHead5.38Download
GFDL-ESM41960–2014CMIP6 historicalAverageWater table depth5.38Download
GFDL-ESM41960–2014CMIP6 historicalAnnualHead43.99Download
GFDL-ESM41960–2014CMIP6 historicalAnnualWater table depth50.45Download
GFDL-ESM42015–2100SSP1-2.6AverageHead5.38Download
GFDL-ESM42015–2100SSP1-2.6AverageWater table depth5.38Download
GFDL-ESM42015–2100SSP1-2.6AnnualHead68.89Download
GFDL-ESM42015–2100SSP1-2.6AnnualWater table depth78.85Download
GFDL-ESM42015–2100SSP3-7.0AverageHead5.38Download
GFDL-ESM42015–2100SSP3-7.0AverageWater table depth5.38Download
GFDL-ESM42015–2100SSP3-7.0AnnualHead68.90Download
GFDL-ESM42015–2100SSP3-7.0AnnualWater table depth78.85Download
GFDL-ESM42015–2100SSP5-8.5AverageHead5.38Download
GFDL-ESM42015–2100SSP5-8.5AverageWater table depth5.38Download
GFDL-ESM42015–2100SSP5-8.5AnnualHead68.89Download
GFDL-ESM42015–2100SSP5-8.5AnnualWater table depth78.85Download
IPSL-CM6A-LR1960–2014CMIP6 historicalAverageHead5.38Download
IPSL-CM6A-LR1960–2014CMIP6 historicalAverageWater table depth5.38Download
IPSL-CM6A-LR1960–2014CMIP6 historicalAnnualHead43.98Download
IPSL-CM6A-LR1960–2014CMIP6 historicalAnnualWater table depth50.45Download
IPSL-CM6A-LR2015–2100SSP1-2.6AverageHead5.38Download
IPSL-CM6A-LR2015–2100SSP1-2.6AverageWater table depth5.38Download
IPSL-CM6A-LR2015–2100SSP1-2.6AnnualHead68.87Download
IPSL-CM6A-LR2015–2100SSP1-2.6AnnualWater table depth78.83Download
IPSL-CM6A-LR2015–2100SSP3-7.0AverageHead5.38Download
IPSL-CM6A-LR2015–2100SSP3-7.0AverageWater table depth5.38Download
IPSL-CM6A-LR2015–2100SSP3-7.0AnnualHead68.93Download
IPSL-CM6A-LR2015–2100SSP3-7.0AnnualWater table depth78.85Download
IPSL-CM6A-LR2015–2100SSP5-8.5AverageHead5.38Download
IPSL-CM6A-LR2015–2100SSP5-8.5AverageWater table depth5.38Download
IPSL-CM6A-LR2015–2100SSP5-8.5AnnualHead68.92Download
IPSL-CM6A-LR2015–2100SSP5-8.5AnnualWater table depth78.84Download
MPI-ESM1-2-HR1960–2014CMIP6 historicalAverageHead5.38Download
MPI-ESM1-2-HR1960–2014CMIP6 historicalAverageWater table depth5.38Download
MPI-ESM1-2-HR1960–2014CMIP6 historicalAnnualHead43.99Download
MPI-ESM1-2-HR1960–2014CMIP6 historicalAnnualWater table depth50.45Download
MPI-ESM1-2-HR2015–2100SSP1-2.6AverageHead5.38Download
MPI-ESM1-2-HR2015–2100SSP1-2.6AverageWater table depth5.38Download
MPI-ESM1-2-HR2015–2100SSP1-2.6AnnualHead68.91Download
MPI-ESM1-2-HR2015–2100SSP1-2.6AnnualWater table depth78.85Download
MPI-ESM1-2-HR2015–2100SSP3-7.0AverageHead5.38Download
MPI-ESM1-2-HR2015–2100SSP3-7.0AverageWater table depth5.38Download
MPI-ESM1-2-HR2015–2100SSP3-7.0AnnualHead68.93Download
MPI-ESM1-2-HR2015–2100SSP3-7.0AnnualWater table depth78.85Download
MPI-ESM1-2-HR2015–2100SSP5-8.5AverageHead5.38Download
MPI-ESM1-2-HR2015–2100SSP5-8.5AverageWater table depth5.38Download
MPI-ESM1-2-HR2015–2100SSP5-8.5AnnualHead68.92Download
MPI-ESM1-2-HR2015–2100SSP5-8.5AnnualWater table depth78.84Download
MRI-ESM2-01960–2014CMIP6 historicalAverageHead5.38Download
MRI-ESM2-01960–2014CMIP6 historicalAverageWater table depth5.38Download
MRI-ESM2-01960–2014CMIP6 historicalAnnualHead43.98Download
MRI-ESM2-01960–2014CMIP6 historicalAnnualWater table depth50.45Download
MRI-ESM2-02015–2100SSP1-2.6AverageHead5.38Download
MRI-ESM2-02015–2100SSP1-2.6AverageWater table depth5.38Download
MRI-ESM2-02015–2100SSP1-2.6AnnualHead68.97Download
MRI-ESM2-02015–2100SSP1-2.6AnnualWater table depth78.87Download
MRI-ESM2-02015–2100SSP3-7.0AverageHead5.38Download
MRI-ESM2-02015–2100SSP3-7.0AverageWater table depth5.38Download
MRI-ESM2-02015–2100SSP3-7.0AnnualHead68.99Download
MRI-ESM2-02015–2100SSP3-7.0AnnualWater table depth78.88Download
MRI-ESM2-02015–2100SSP5-8.5AverageHead5.38Download
MRI-ESM2-02015–2100SSP5-8.5AverageWater table depth5.38Download
MRI-ESM2-02015–2100SSP5-8.5AnnualHead68.99Download
MRI-ESM2-02015–2100SSP5-8.5AnnualWater table depth78.88Download
UKESM1-0-LL1960–2014CMIP6 historicalAverageHead5.38Download
UKESM1-0-LL1960–2014CMIP6 historicalAverageWater table depth5.38Download
UKESM1-0-LL1960–2014CMIP6 historicalAnnualHead44.00Download
UKESM1-0-LL1960–2014CMIP6 historicalAnnualWater table depth50.46Download
UKESM1-0-LL2015–2100SSP1-2.6AverageHead5.38Download
UKESM1-0-LL2015–2100SSP1-2.6AverageWater table depth5.38Download
UKESM1-0-LL2015–2100SSP1-2.6AnnualHead68.93Download
UKESM1-0-LL2015–2100SSP1-2.6AnnualWater table depth78.85Download
UKESM1-0-LL2015–2100SSP3-7.0AverageHead5.38Download
UKESM1-0-LL2015–2100SSP3-7.0AverageWater table depth5.38Download
UKESM1-0-LL2015–2100SSP3-7.0AnnualHead68.97Download
UKESM1-0-LL2015–2100SSP3-7.0AnnualWater table depth78.86Download
UKESM1-0-LL2015–2100SSP5-8.5AverageHead5.38Download
UKESM1-0-LL2015–2100SSP5-8.5AverageWater table depth5.38Download
UKESM1-0-LL2015–2100SSP5-8.5AnnualHead68.97Download
UKESM1-0-LL2015–2100SSP5-8.5AnnualWater table depth78.86Download

Quality assurance

Archive YODA landing page

  • Static quality flags: karst aquifers, mountainous regions and permafrost, each held as a separate variable. These are the settings where the model’s physical assumptions hold least well.

  • Spin-up completion: the month, as YYYYMM, at which spin-up is achieved for each cell. Output earlier than that month has not equilibrated and should not be used.

  • GRACE agreement: categorical classes recording where GRACE observations agree with the modelled storage change.

ⓘItem Contents Size (MiB) Download
Static quality flagsKarst aquifers, mountainous regions and permafrost, each as a separate variable24.46Download
Spin-up completionMonth (YYYYMM) at which spin-up is achieved for each cell49.08Download
GRACE agreementCategorical classes recording where GRACE agrees with the modelled storage change0.13Download