An observationally based evaluation of cloud ice water in CMIP3 and CMIP5 GCMs and contemporary reanalyses using contemporary satellite data

By Juilin Li, Duane Waliser, Wei‐Ting Chen, B. Guan, T. Kubar, Graeme L. Stephens, Hsi‐Yen Ma, Min Deng, Leo Donner, C. Seman and 1 more. 2012

196 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation (2015, background): “…tropical boundary layer clouds were ‘too few and too bright’; Li et al. (2013) reported that the mean annual ice water path in 19 climate models varied by factors of 2–10, and Li et al. (2012) looked at 20 models and discovered regional radiation biases in annual mean fluxes of up to ±30 W m–2.”
Characterizing and understanding radiation budget biases in CMIP3/CMIP5 GCMs, contemporary GCM, and reanalysis (2013, methodology): “Figure 14 shows that similar underestimates of liquid water occur in the same regions [see Li et al., 2012] and exacerbates the challenge of obtaining an accurate representation of the radiation fields.”
On the Correspondence between Mean Forecast Errors and Climate Errors in CMIP5 Models (2013, background): “…Climate Research Programme (WCRP)CoupledModel IntercomparisonProject (CMIP3), large systematic errors in precipitation, clouds, andwater vapor remain in the simulated climatemean state for majority of the climate models in the recent CMIP5 (Jiang et al. 2012; Li et al. 2012; Klein et al. 2013).”