Full catalog/M2SMNXPCT
M2SMNXPCT·v1·dataset

Monthly weather statistics like highs and lows (MERRA-2)

MERRA-2 statM_2d_pct_Nx: 2d, Single-Level, Monthly Percentiles V1 (M2SMNXPCT) at GES DISC
atmosphere NASA GES_DISC Level 4
In plain English

What it measures. Monthly statistics that flag extreme weather: percentiles for 2-meter air temperature (daily highs, lows and averages) and total precipitation, showing how a given month compares against the historical norm.

How it's made. Derived from MERRA-2, NASA's modern reanalysis that blends decades of satellite-era observations into a consistent record of the atmosphere; this collection computes percentiles relative to a 1981-2010 baseline.

How & where you'd use it. Helps identify and characterize extreme heat, cold and rainfall events and place them in historical context.

What's measured

ATMOSPHERE › ATMOSPHERIC TEMPERATURE › SURFACE TEMPERATURE › AIR TEMPERATURECLIMATE INDICATORS › ATMOSPHERIC/OCEAN INDICATORS › EXTREME WEATHER › EXTREME DROUGHTCLIMATE INDICATORS › ATMOSPHERIC/OCEAN INDICATORS › EXTREME WEATHER › HEAT/COLD WAVE FREQUENCY/INTENSITYCLIMATE INDICATORS › ATMOSPHERIC/OCEAN INDICATORS › EXTREME WEATHER › EXTREME PRECIPITATIONATMOSPHERE › PRECIPITATION › PRECIPITATION RATEATMOSPHERE › ATMOSPHERIC TEMPERATURE › SURFACE TEMPERATURE › MAXIMUM/MINIMUM TEMPERATURE › 24 HOUR MAXIMUM TEMPERATUREATMOSPHERE › ATMOSPHERIC TEMPERATURE › SURFACE TEMPERATURE › MAXIMUM/MINIMUM TEMPERATURE › 24 HOUR MINIMUM TEMPERATURE

Coverage & cadence

  • Time span1980-01-01 → 2022-12-31
  • Measured byMERRA-2 (NOT APPLICABLE)
  • Processing levelLevel 4
  • Spatial extent-180, -90, 180, 90
  • StatusCOMPLETE

What you can do with it

  • Map air pollutants — NO₂, aerosols, ozone
  • Track greenhouse gases and Earth's energy budget
  • Feed weather and air-quality analysis
Official description

M2SMNXPCT (or statM_2d_pct_Nx) is a 2-dimensional monthly data collection for percentile statistics derived from monthly Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) datasets. V1, the original version of this percentile data collection, is computed based on the 1981-2010 climatology, covering the period from January 1980 to December 2022. In contrast, V2, the second version, is calculated based on a 30-year climatology (1991-2020), covering the period from January 1980 to the present. This collection consists of percentiles used to identify or characterize extreme weather events associated with temperature (maximum, mean, and minimum 2-m air temperature), as well as with precipitation (total precipitation). MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by the NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present, with a latency of ~3 weeks after the end of the previous month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes”, linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original filename. MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changes to tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list. Questions: If you have a question, please read the "MERRA-2 File Specification Document'', “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page for more information. If these documents do not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov).

Get the data

m2smnxpct_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="M2SMNXPCT",
    version="1",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from GES_DISC
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.