BER launches Environmental System Science Program. Visit our new website under construction!

U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Modeled Clouds in the Tropics Get a Reality Check
Published: March 27, 2018
Posted: July 02, 2018

Scientists established a new procedure to evaluate the ability of Earth system models to simulate various cloud types in the tropics.

The Science
Due to a scarcity of useful observations to guide model development, Earth system models often miss the mark in predicting tropical clouds and their effects on incoming and outgoing energy in the atmosphere. For most of the past two decades, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, a scientific user facility, collected data at three surface sites in the Tropical Western Pacific (TWP) to improve the data record in this sparsely sampled region. Scientists at DOE’s Pacific Northwest National Laboratory analyzed the ARM TWP data to evaluate Earth system model results. They found that model errors in cloudiness are dependent on model resolution, which can further lead to errors in ambient temperature and humidity and, in turn, feedback on clouds.

The Impact
Marine boundary layer convection and tropical clouds—key elements of the global energy balance and water cycle—remain an important source of uncertainty in understanding tropical cloud feedback processes and climate sensitivity and in predicting Earth system changes. The long-term ARM TWP data sets provide an excellent resource for evaluating Earth system models using both statistical and process-oriented approaches and to reduce errors in cloud treatments. This measurement-to-model approach can be easily adapted for evaluating new schemes being developed for the Community Atmosphere Model version 5 (CAM5) or other Earth system models.

Atmospheric moist convection in the tropics redistributes heat, moisture, and momentum globally. Recent generations of Earth system models have underestimated the coverage of tropical low clouds but overestimated their thickness and cooling effects. This is referred to as the “too few, too bright” tropical low-cloud problem. Compensating for this problem by adjusting estimates of different cloud properties may reduce the total error in energy budget estimates but hide other problems in model representations.

Researchers used ARM’s long-term TWP data sets to evaluate the CAM5’s ability to simulate the various types of tropical clouds (i.e., convective vs. liquid or ice stratiform), their seasonal and diurnal variations, and their influence on surface radiation, as well as the resolution dependency of modeled clouds. Increases up to 20 percent in the modeled annual mean total cloud cover were attributable to the large overestimation of stratiform ice clouds. Higher-resolution simulations reduced the overestimation of ice clouds, but increased the underestimation of convective clouds and low-level liquid clouds. Compared to the meteorological sounding data, the cooler and more humid air simulated in the model also caused overestimation of clouds at all altitudes. Comparing the modeled occurrence of convective clouds against ARM observations revealed the model deficiency in triggering deep convection too often, which affects the vertical transport of vapor and injection of liquid and ice to the upper air. This error manifested itself in the out-of-phase cloud diurnal cycle simulated by CAM5, causing the inaccurate vertical distribution of stratiform clouds.

Contacts (BER PMs)
Ashley Williamson
Atmospheric System Research

Shaima Nasiri
Atmospheric System Research

Dorothy Koch
Earth System Modeling

Sally McFarlane
Atmospheric Radiation Measurement (ARM) Climate Research Facility

(PNNL Contact)
Hailong Wang
Pacific Northwest National Laboratory

This research is based on work supported by the U.S. Department of Energy (DOE) Office of Science, Biological and Environmental Research (BER) as part of the Atmospheric System Research and Earth System Modeling programs. This research used data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, a DOE Office of Science user facility. The research used computational resources at the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science user facility located at Lawrence Berkeley National Laboratory, and the Environmental Molecular Sciences Laboratory (EMSL), a DOE Office of Science user facility sponsored by BER and located at Pacific Northwest National Laboratory.

Wang, H., C.D. Burleyson, P.-L. Ma, J.D. Fast, P.J. Rasch. “Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds.” Journal of Climate 31: 3301-3325 (2018). [DOI: 10.1175/JCLI-D-17-0362.1]

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research
  • Research Area: Earth and Environment Systems Data Management
  • Facility: DOE ARM User Facility

Division: SC-33.1 Earth and Environmental Sciences Division, BER


BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

Jan 11, 2022
No Honor Among Copper Thieves
Findings provide a novel means to manipulate methanotrophs for a variety of environmental and in [more...]

Dec 06, 2021
New Genome Editing Tools Can Edit Within Microbial Communities
Two new technologies allow scientists to edit specific species and genes within complex laborato [more...]

Oct 27, 2021
Fungal Recyclers: Fungi Reuse Fire-Altered Organic Matter
Degrading pyrogenic (fire-affected) organic matter is an important ecosystem function of fungi i [more...]

Oct 19, 2021
Microbes Offer a Glimpse into the Future of Climate Change
Scientists identify key features in microbes that predict how warming affects carbon dioxide emi [more...]

Aug 25, 2021
Assessing the Production Cost and Carbon Footprint of a Promising Aviation Biofuel
Biomass-derived DMCO has the potential to serve as a low-carbon, high-performance jet fuel blend [more...]

List all highlights (possible long download time)