A 1900-onward global monthly precipitation anomaly reconstruction merges historical gauge data with modern satellite-era statistics. The dataset, documented by Smith et al. in 2012, is produced by SCIOPS and represents the latest in a series of improved reconstructions. It incorporates an annual first guess adjusted with monthly increments, canonical correlation analysis for oceanic observations, and reinjection of available gauge data.
Use Cases
- Analyzing long-term trends in global precipitation anomalies from 1900 onward.
- Validating climate model simulations of hydrological cycles using the reconstructed anomaly fields.
- Studying the spatial and temporal patterns of historical droughts and pluvials via the monthly anomaly data.
- Investigating the impact of oceanic observations on land precipitation reconstructions through the canonical correlation analysis method.
Strengths
- Reconstruction period begins in 1900, providing over a century of data.
- Method incorporates three major improvements over prior versions, including an annual first guess with monthly adjustments.
Limitations
- Data is a reconstruction/model product, not direct measurements, introducing inherent uncertainty.
- The underlying source data availability and density varies significantly across the globe and over time.
- Last documented update was in 2012, potentially missing recent methodological advances.
Provenance
- Source
- SCIOPS, based on work documented by Smith et al. (2012).
- Collection Method
- Statistical reconstruction minimizing mean-squared error, merging historical gauge data with satellite-era statistics.
- Time Range
- Beginning 1900.
- Freshness
- null
- Geography
- Global land-ocean coverage.