AbstractLong-term Atmospheric Radiation Measurement (ARM) datasets collected at the three tropical western Pacific (TWP) sites are used to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. A number of CAM5 simulations are conducted at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from analysis or reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m−2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, produce feedback onto clouds. Both the model and observations show distinct diurnal cycles in total, stratiform, and convective cloud fractions; however, they are out of phase by 12 h and the biases vary by site. The results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. The approach used here can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional models.
Journal of Climate – American Meteorological Society
Published: May 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.
All for just $49/month
Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.
Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.
It’s easy to organize your research with our built-in tools.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera