Monthly Diurnal Radiation Diagnostics from MERRA-2 Reanalysis

Monthly diurnal means of radiation diagnostics from NASA's MERRA-2 global atmospheric reanalysis. The collection includes hourly data fields such as surface albedo and cloud area fraction, time-stamped from 00:30 to 23:30 UTC. NASA's Global Modeling and Assimilation Office (GMAO) produces this data, which covers the period from 1980 to the present with approximately a three-week latency.

Use Cases

• Modeling surface energy balance using surface incoming shortwave flux and surface net downward shortwave flux.
• Analyzing cloud radiative effects by correlating cloud area fraction with upwelling longwave flux at the top of the atmosphere.
• Studying albedo feedbacks and seasonal changes by tracking surface albedo across the global 0.625 x 0.5 degree grid.
• Validating climate model output for outgoing longwave radiation (OLR) using the provided hourly time-series data.
• Investigating in-cloud optical thickness variations and their impact on atmospheric heating rates.

Strengths

• Global spatial coverage on a consistent 0.625 x 0.5 degree latitude/longitude grid.
• Long temporal coverage from 1980 to present, providing over 40 years of climate data.
• Provides hourly-resolution data within monthly means, capturing diurnal cycles.
• Produced by NASA's GMAO using the validated GEOS 5.12.4 model and data assimilation system.

Limitations

• Data is a model reanalysis product, not direct observation, introducing assimilation uncertainties.
• Spatial resolution of about 50-60 km may not resolve local-scale phenomena.
• Latency of approximately three weeks after each month limits near-real-time applications.

Provenance

Source

NASA Global Modeling and Assimilation Office (GMAO) via the Goddard Earth Sciences Data and Information Services Center (GES DISC).

Collection Method

Generated by the Goddard Earth Observing System Model (GEOS) version 5.12.4, which assimilates satellite and observational data.

Time Range

1980 to present.

Freshness

Updated monthly with a ~3 week latency.

Geography

Global.