MERRA: Modern Era-Retrospective Analysis for Research and Applications
MERRA is a Global Modeling and Assimilation Office (GMAO) reanalysis that integrates observational data with NASA’s GEOS-5 atmosphere model to create a spatially and temporally consistent record of Earth’s weather and climate. In covering the entire satellite era—from 1979 to the present—MERRA assimilates over 70 billion observations from satellites, ground stations, weather balloons, ships, and aircraft. Spatial resolution for most of the MERRA data collection is 1/2° latitude × 2/3° longitude × 72 vertical levels extending through the stratosphere. The most common temporal resolution is 3 hours, with 1- and 6-hour data available for certain parameters.
The 160-terabyte MERRA dataset allows exploration of 26 key climate variables cutting across physical quantities and chemical composition. With a special focus on Earth’s water cycle, MERRA users can investigate and compare phenomena such as prolonged periods of flood and drought.
MERRA Analytics Service
There is growing demand for reanalysis data products by a large and diverse applications community representing all of NASA’s Applied Sciences Program themes: disasters, ecological forecasting, health and air quality, water resources, agriculture, climate energy, oceans, and weather.
CDS has developed the MERRA Analytics Service (MERRA/AS) to make MERRA data more easily accessible to an expanding community of consumers, including local governments, federal agencies, and private-sector customers.
MERRA/AS combines several advanced data management and analysis technologies.
CDS is storing the entire MERRA data collection on a high-performance parallel computing cluster running the integrated Rule-Oriented Data System (iRODS) to manage the data and Hadoop/MapReduce to efficiently assemble and transmit data of interest to users within several minutes.
MERRA/AS includes a library of operations for calculating values including minimum; maximum; average (e.g., monthly, seasonal, annual); sum (e.g., total precipitation); and variance (e.g., temperature variation over 6 months). Users also can request data subsets by variable, geographic
region, atmospheric pressure range, and time span. Planned enhancements include adding data
from NCCS-hosted CMIP5 climate simulations for comparison studies.
Knitting these capabilities together for a wide variety of users is the CDS Application Programming Interface (API). For MERRA/AS, the CDS API supports web service access to consumer applications, a graphical user interface for interactive requests, a command line interface for users familiar with basic CDS commands, and advanced programmatic access for Python-savvy users.