GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast

NASA/GEOS-CF/v1/rpl/htf
Dataset Availability
2018-01-01T00:00:00Z–2022-07-03T00:00:00
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("NASA/GEOS-CF/v1/rpl/htf")
Tags
composition forecast geos gmao nasa

Description

This dataset contains meteorological replay (rpl) of high-temporal frequency data (htf).

The Goddard Earth Observing System Composition Forecast (GEOS-CF) system is a high-resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office(GMAO).

GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space-based and in-situ observations. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide hindcasts and 5-days forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.

Evaluation of GEOS-CF against satellite, ozonesonde, and surface observations for years 2018–2019 shows realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of −0.1 to 0.3, normalized root mean square errors between 0.1–0.4, and correlations between 0.3–0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO2 and an overprediction of summertime O3 over the Southeast United States.

GEOS-CF v1.0 generally overestimates aerosols by 20%–50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions. The 5-days forecasts have skill scores comparable to the 1-day hindcast. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

Bands

Resolution
27750 meters

Bands

Name Units Description
CO mol mol-1

Carbon monoxide (CO, MW = 28.00 g mol-1) volume mixing ratio dry air

NO2 mol mol-1

Nitrogen dioxide (NO2, MW = 46.00 g mol-1) volume mixing ratio dry air

O3 mol mol-1

Ozone (O3, MW = 48.00 g mol-1) volume mixing ratio dry air

PM25_RH35_GCC ug m-3

Particulate matter with diameter below 2.5 um RH 35

PM25_RH35_GOCART kg m-3

Total reconstructed PM2.5 RH 35

Q kg kg-1

Specific humidity

RH

Relative humidity after moist

SLP Pa

Sea level pressure

SO2 mol mol-1

Sulfur dioxide (SO2, MW = 64.00 g mol-1) volume mixing ratio dry air

T K

Air temperature

U m s-1

Eastward wind

V m s-1

Northward wind

Terms of Use

Terms of Use

Unless otherwise noted, all NASA-produced data may be used for any purpose without prior permission. For more information and exceptions visit the NASA Data & Information Policy page.

Citations

Citations:
  • Keller, C. A., Knowland, K. E., Duncan, B. N., Liu, J., Anderson, D. C., Das, S., ... & Pawson, S. (2021). Description of the NASA GEOS composition forecast modeling system GEOS-CF v1. 0. Journal of Advances in Modeling Earth Systems, 13(4), e2020MS002413. doi:10.1029/2020MS002413

DOIs

Explore in Earth Engine

var imageVisParamNO2 = {
  'bands': ['NO2'],
  'min': 6.96e-11,
  'max': 4.42e-8,
};

var imageVisParamT = {
  'bands': ['T'],
  'min': 220,
  'max': 320,
  'palette': ['d7191c', 'fdae61', 'ffffbf', 'abd9e9', '2c7bb6'],
};

var geosCf = ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf');

Map.setCenter(100, 20, 3);

var weeklyT =
    geosCf.select('T').filterDate('2019-06-01', '2019-06-08').median();
Map.addLayer(weeklyT, imageVisParamT, 'Weekly T', false, 1);

var NO2 = ee.Image('NASA/GEOS-CF/v1/rpl/htf/20190601_0000z');
Map.addLayer(NO2, imageVisParamNO2, 'NO2', true, 1);