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Update FLDAS-soilmoisture-anomalies.data.mdx
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updated scientific details
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jerikac authored Oct 13, 2023
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<Prose>
FLDAS is the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System. The goal of FLDAS is to use observational and forecast datasets and advanced modeling methods to generate high quality fields of land surface states and fluxes used for FEWS NET decision support. The FLDAS systems are custom instances of the NASA Land Information System (LIS) that have been adapted to work with the domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing countries. Surface soil moisture anomalies are an indicator of wet and dry extremes that have the potential to impact agricultural and food security outcomes.

**Temporal Extent:** January 1982 - June 2023
**Temporal Resolution:** Monthly
**Spatial Extent:** Quasi-Global ( -180.0,-60.0,180.0,90.0)
**Spatial Resolution:** 10 km x 10 km
**Data Units:** Fraction Soil moisture anomaly (mm3/mm3) difference from 1982-2016 monthly mean
**Data Type:** Research
**Data Latency:** Monthly
- **Temporal Extent:** January 1982 - June 2023
- **Temporal Resolution:** Monthly
- **Spatial Extent:** Quasi-Global ( -180.0,-60.0,180.0,90.0)
- **Spatial Resolution:** 10 km x 10 km
- **Data Units:** Fraction Soil moisture anomaly (mm3/mm3) difference from 1982-2016 monthly mean
- **Data Type:** Research
- **Data Latency:** Monthly


**Scientific Details:**
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<Block>
<Prose>
## Source Data Product Citation
Amy McNally NASA/GSFC/HSL (2018), FLDAS Noah Land Surface Model L4 Global Monthly Anomaly 0.1 x 0.1 degree (MERRA-2 and CHIRPS), Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/GNKZZBAYDF4W
Amy McNally, NASA/GSFC/HSL (2018), FLDAS Noah Land Surface Model L4 Global Monthly Anomaly 0.1 x 0.1 degree (MERRA-2 and CHIRPS), Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], [https://doi.org/10.5067/GNKZZBAYDF4W] (10.5067/GNKZZBAYDF4W)

## Dataset Accuracy
This dataset uses CHIRPS precipitation inputs and MERRA-2 reanalysis. While regional, relative, comparisons to remotely sensed estimates and other model products are favorable, users should verify that the data accuracy meets the requirements of their specific application, and interpret results accordingly.
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