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Aanchal's Notes

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Asetia1 edited this page Jun 20, 2023 · 11 revisions

GRACE DATA

  • It only has gravity measurements; further data processing is requited to extract terrestrial water storage by region from this data
  • monthly and annual recordings; GRACE-F has sub-monthly and inter-annually recordings too

Components of GRACE DATA

  • groundwater, soil moisture, surface waters, snow, ice and permafrost as the primary components of TWS retrieved from GRACE gravity observations

Uses

  • estimates of the rates

  • of ice losses

  • river discharge (the volume of water moving down a stream or river per unit of time)

  • snow mass (average amount of snow mass present during the winter season in regions located at high latitudes)

  • of ground water depletion in India, America, China, and so on

  • global assessments of groundwater storage changes from 2002

  • researchers used direct on-site measurements of soil moisture and snow water equivalent, as well as modeled data, to isolate groundwater storage changes from GRACE (Gravity Recovery and Climate Experiment) Total Water Storage (TWS) data. The combination of on site measurements and modeled data allowed for a more accurate estimation and understanding of groundwater storage changes.

  • operational flood & drought monitoring

Removing anomalies from GRACE

  • "Soil moisture and snow were simulated by the Global Land Data Assimilation System (GLDAS) and used to isolate groundwater storage anomalies from GRACE water storage data for the Mississippi River basin and its four major sub-basins" (Rodell et al, 2007)

Computations

  • GRACE-based estimates of terrestrial water storage variations (ΔTWS) and numerically modeled changes in soil moisture (ΔSM) and snow water equivalent (ΔSWE), groundwater storage variations (ΔGW) were computed as
  • deltaGW = deltaTWS - (deltaSM +deltaSWE)

Complementary Datasets

  • Soil moisture and snow water equivalent (SWE) were simulated by the Noah (Ek et al. 2003), Common Land Model version 2 (CLM2; Dai et al. 2003), and Mosaic (Koster and Suarez 1996) land surface models driven by the Global Land Data Assimilation System (GLDAS; Rodell et al. 2004a).

  • The baseline meteorological forcing data for the three model simulations was produced by:

    • the US National Oceanic and Atmospheric Administration’s (NOAA) Global Data Assimilation System (GDAS) atmospheric analysis system.
    • A spatially and temporally downscaled version (Gottschalck et al. 2005) of the NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP; Xie and Arkin 1997) product replaced the GDAS precipitation;
    • observation based downward radiation products derived using Air Force Weather Agency fields and procedures (Rodell et al. 2004a) replaced the GDAS radiation

  • GLDAS ingests satellite- and ground-based observational data products in order to generate optimal fields of land surface states (e.g., soil moisture, snow, surface temperature) and fluxes (e.g., evapotranspiration, ground heat flux).

      • This paper estimates groundwater storage variability based on remotely sensed terrestrial water storage observations from GRACE.
      • The approach appears to be appropriate for regions larger than about 900,000 km2, based on the results for the Mississippi River basin and its four major sub-basins.

GLDAS

  • soil moisture and snow were simulated by the Global Land Data Assimilation System (GLDAS)
  • used to isolate groundwater storage anomalies from GRACE water storage data for the Mississippi River basin and its four major sub-basins

REPLACEMENTS IN GLDAS The baseline meteorological forcing data for the three model simulations was produced by the US National Oceanic and Atmospheric Administration’s (NOAA) Global Data Assimilation System (GDAS) atmospheric analysis system.

  • A spatially and temporally downscaled version (Gottschalck et al. 2005) of the NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP; Xie and Arkin 1997) product replaced the GDAS precipitation; observation based downward radiation products derived using Air Force Weather Agency fields and procedures (Rodell et al. 2004a) replaced the GDAS radiation.
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