#TBC
#methods_to_learn
#closure_techniques
#data_products
https://www.sciencedirect.com/science/article/pii/S0034425720305642
https://journals.ametsoc.org/view/journals/clim/33/5/jcli-d-19-0036.1.xml
https://journals.ametsoc.org/view/journals/hydr/21/5/jhm-d-19-0255.1.xml
#methods_to_learn #closure_techniques #data_products #tbc
#data_products
#terrestrial_water_storage
Name: GRACE-REC
Spatial coverage: global
Spatial resolution: 0.5 degrees
Temporal coverage: MSWEP-based reconstruction 1979-2016, ERA5-based 1979-present, GSWP3-based 1901-2014
Temporal resolution: Monthly (100 ensemble members for each combination of the three meteorological datasets and two GRACE satellite mascons), daily (ensemble mean only)
Gap-free: Yes
Year of publication: 2019
Algorithm: (1) linear water storage model, driven by temperature and precipitation, calibrated against de-seasonalized, de-trendedd GRACE satellite data (2002-2017), (2) spatial autoregressive model was used to generate an ensemble of spatially autocorrelated residuals, to facilitate uncertainty propagation from grid-level to regional or global averages. This method to propagate uncertainty is noteworthy.
Pros: outperforms hydrological and land surface models when evaluated against de-seasonalized, de-trended GRACE terrestrial water data, sea-level budget, basin-scale water balance, and streamflow.
Cons: The trends in GRACE-REC is purely driven by precipitation changes, therefore missing a ton of relevant factors (evapotranspiration change, dams, human water withdrawal, ice melt...). The seasonality is constant and not particularly reliable, either.
#data_products #terrestrial_water_storage
#carbon_emissions
#data_products
Spatial coverage: Global
Spatial resolution: country x sector x fuel
Temporal coverage: 1750-most recent year
Temporal resolution: annual
Gap-free: Yes
Year of publication: continually updated
Algorithm: N/A (not examined)
#Carbon_emissions #data_products
#data_products
#evapotranspiration
Name: The Global LAnd Surface Satellite evapotranspiration product version 5.0 (GLASS ET)
Spatial coverage: Global
Spatial resolution: 1 km
Temporal coverage: 2001-2015
Temporal resolution: 8 day
Gap-free: Yes
Year of publication: 2022
Algorithm: machine learning, integrating five satellite-derived ET products
https://www.sciencedirect.com/science/article/pii/S0022169422005650
#data_products #evapotranspiration