Clouds and the Earth's Radiant Energy System

Clouds and the Earth's Radiant Energy System
Name	Clouds and the Earth's Radiant Energy System
Acronym	CERES
Established	1998
Operator	NASA / Langley Research Center
Mission type	Earth radiation budget
Instruments	Scanning radiometers
Satellites	Tera, Aqua, Suomi NPP, NOAA-20
Website	NASA CERES

Clouds and the Earth's Radiant Energy System is a NASA-led program of spaceborne radiometers designed to quantify Earth's top-of-atmosphere radiative fluxes and their relationship to clouds and aerosols. The project integrates satellite platforms, instrument teams, and climate research centers to produce long-term datasets used by Intergovernmental Panel on Climate Change, National Oceanic and Atmospheric Administration, European Space Agency, Japan Aerospace Exploration Agency, and academic groups for model evaluation and climate diagnostics.

Overview

CERES originates from collaborations among NASA, Langley Research Center, Jet Propulsion Laboratory, and university partners such as University of Maryland, Massachusetts Institute of Technology, and University of Colorado Boulder. The program builds on heritage from missions like Earth Radiation Budget Experiment and complements sensors aboard Terra, Aqua, Suomi NPP, and NOAA-20. Objectives include quantifying reflected solar radiation, emitted longwave radiation, and the influence of cloud properties on the planetary energy balance, supporting assessments by Intergovernmental Panel on Climate Change and operational centers like National Centers for Environmental Prediction.

Instrumentation and Data Products

CERES instrumentation comprises scanning broadband radiometers calibrated against standards maintained by National Institute of Standards and Technology and integrated with imager suites such as MODIS on Terra and Aqua. Data products include instantaneous, diurnal, and monthly radiative flux fields at top-of-atmosphere, surface, and within-atmosphere layers, plus cloud fraction and cloud property retrievals co-registered with imagers and reanalysis systems like ERA-Interim, ERA5, MERRA-2, and CFSR. Product suites (e.g., SYN, EBAF) are widely used by researchers at Princeton University, Columbia University, California Institute of Technology, Purdue University, and national laboratories including Lawrence Berkeley National Laboratory. Calibration and validation campaigns have involved facilities and programs such as ARM Climate Research Facility, NOAA field campaigns, and international efforts coordinated with European Space Agency and Japan Aerospace Exploration Agency.

Role of Clouds in Earth's Radiation Budget

Clouds modulate planetary albedo and greenhouse trapping by reflecting incoming solar radiation and emitting longwave radiation, a dual role studied by teams at NASA Goddard Space Flight Center, NASA Langley Research Center, NOAA, and universities listed above. High cirrus influence outgoing longwave flux similar to effects documented in studies by Intergovernmental Panel on Climate Change Working Groups; low stratocumulus control shortwave reflection over subtropical oceans described in regional research near California Current, Peru Current, and Canary Current. Cloud radiative effects are crucial for understanding feedbacks in climate projections produced by modeling centers such as Hadley Centre, National Center for Atmospheric Research, Geophysical Fluid Dynamics Laboratory, IPSL, and Max Planck Institute for Meteorology.

Cloud Detection, Classification, and Retrieval Methods

CERES radiances are combined with imager algorithms (e.g., from MODIS, VIIRS, AVHRR) and ancillary datasets like Global Precipitation Measurement and reanalyses (ERA5, MERRA-2) to detect cloud presence, phase, optical depth, particle size, and cloud-top height. Cloud classification schemes apply machine-learning methods developed at institutions such as MIT, Stanford University, Carnegie Mellon University, and University of Oxford and rely on radiative transfer models (RTMs) from groups at Laboratoire de Météorologie Dynamique, Geophysical Fluid Dynamics Laboratory, and NASA Ames Research Center. Retrieval uncertainties are benchmarked against in situ and ground-based networks including ARM Climate Research Facility, AERONET, and ship-based campaigns associated with NOAA and CSIRO.

Scientific Findings and Applications

CERES datasets have quantified global mean top-of-atmosphere radiative fluxes, diurnal cycle influences on net radiation, and cloud forcing patterns linked to climate variability modes such as El Niño–Southern Oscillation, Madden–Julian Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation. Studies using CERES inform attribution research for extreme events analyzed by IPCC reports and national assessments by U.S. Global Change Research Program. Applications span model evaluation at PCMDI, parameter development for CMIP experiments, and operational services at NOAA National Weather Service. Regional impacts have been examined for polar ice mass balance in studies by National Snow and Ice Data Center and for cloud–aerosol interactions in collaborations with Aerosol Robotic Network investigators and teams at Scripps Institution of Oceanography and WHOI.

Limitations, Uncertainties, and Future Directions

Limitations include calibration drift, angular sampling biases, and retrieval ambiguities in multilayer cloud scenes; these challenges are addressed through cross-calibration with missions like CERES–FM1, intercomparisons with CloudSat, CALIPSO, and incorporation into reanalyses (ERA5). Uncertainties in cloud feedbacks remain a dominant source of spread among CMIP6 projections, motivating advances in high-resolution modeling at Princeton University, enhanced satellite constellations from European Space Agency and NASA (e.g., missions coordinated with NOAA), and algorithmic improvements via machine learning from research groups at Google AI, DeepMind, and university collaborators. Future directions emphasize sustained observations, integrated lidar–radar–radiometer approaches exemplified by CloudSat and CALIPSO, and tighter linkage between CERES-like radiometry and in situ networks such as ARM Climate Research Facility and AERONET to reduce uncertainties in cloud radiative effects for policy-relevant climate projections by IPCC and national agencies.

Category:Earth observation