The double‐intertropical convergence zone (ITCZ) bias is one of the most outstanding errors in all previous generations of climate models. Here, the annual double‐ITCZ bias and the associated precipitation bias in the latest climate models for Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) are examined in comparison to their previous generations (CMIP Phase 3 [CMIP3] and CMIP Phase 5 [CMIP5]). All three generations of CMIP models share similar systematic annual multi‐model ensemble mean precipitation errors in the tropics. The notorious double‐ITCZ bias and its big inter‐model spread persist in CMIP3, CMIP5, and CMIP6 models. Based on several tropical precipitation bias indices, the double‐ITCZ bias is slightly reduced from CMIP3 or CMIP5 to CMIP6. In addition, the annual equatorial Pacific cold tongue persists in all three generations of CMIP models, but its inter‐model spread is reduced from CMIP3 to CMIP5 and from CMIP5 to CMIP6.

Using NASA's A‐Train satellite measurements, we evaluate the accuracy of cloud water content (CWC) and water vapor mixing ratio (H₂O) outputs from 19 climate models submitted to the Phase 5 of Coupled Model Intercomparison Project (CMIP5), and assess improvements relative to their counterparts for the earlier CMIP3. We find more than half of the models show improvements from CMIP3 to CMIP5 in simulating column‐integrated cloud amount, while changes in water vapor simulation are insignificant. For the 19 CMIP5 models, the model spreads and their differences from the observations are larger in the upper troposphere (UT) than in the lower or middle troposphere (L/MT). The modeled mean CWCs over tropical oceans range from ∼3% to ∼15× of the observations in the UT and 40% to 2× of the observations in the L/MT. For modeled H₂Os, the mean values over tropical oceans range from ∼1% to 2× of the observations in the UT and within 10% of the observations in the L/MT. The spatial distributions of clouds at 215 hPa are relatively well‐correlated with observations, noticeably better than those for the L/MT clouds. Although both water vapor and clouds are better simulated in the L/MT than in the UT, there is no apparent correlation between the model biases in clouds and water vapor. Numerical scores are used to compare different model performances in regards to spatial mean, variance and distribution of CWC and H₂O over tropical oceans. Model performances at each pressure level are ranked according to the average of all the relevant scores for that level.

The height of the planetary boundary layer (PBL) is an important parameter that relates to the various processes associated with the PBL. In this paper, we use Global Positioning System radio occultation (GPSRO) measurements to derive a global climatology of PBL heights. Utilizing the strength of GPSRO in capturing fine vertical structures, the top of the PBL is defined to be the height at which the vertical gradient of the refractivity or water vapor partial pressure is minimum, corresponding to the height where the refractivity or water vapor pressure changes most rapidly. A “sharpness parameter” is defined that quantifies the applicability of these definitions. The sharpness parameter is largest over the subtropical regions characterized by strong subsidence. When the sharpness parameter is large, the refractivity‐ and moisture‐based heights are shown to converge. We derived global PBL height climatology using three years (Dec. 2006–Nov. 2009) of COSMIC/FORMOSAT‐3 measurements and compared with values calculated from ECMWF Reanalysis Interim (ERA‐Int). We found that the mean PBL heights from GPSRO shared similar spatial and seasonal variations with ERA‐Int; however, GPSRO heights were higher by 500 m. The standard deviation was also higher from GPSRO, especially in the tropics. We present detailed comparisons between GPSRO and ERA‐Int over the Pacific Ocean and the Sahara desert and examine the PBL height distributions as well as its annual and diurnal variabilities. These results suggest that the underlying causes of the bias between GPSRO and ERA‐Int likely vary from region to region.

The atmospheric moisture and temperature profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit on the NASA Aqua mission, in combination with the precipitation from the Tropical Rainfall Measuring Mission (TRMM), are employed to study the vertical moist thermodynamic structure and spatial–temporal evolution of the Madden–Julian oscillation (MJO). The AIRS data indicate that, in the Indian Ocean and western Pacific, the temperature anomaly exhibits a trimodal vertical structure: a warm (cold) anomaly in the free troposphere (800–250 hPa) and a cold (warm) anomaly near the tropopause (above 250 hPa) and in the lower troposphere (below 800 hPa) associated with enhanced (suppressed) convection. The AIRS moisture anomaly also shows markedly different vertical structures as a function of longitude and the strength of convection anomaly. Most significantly, the AIRS data demonstrate that, over the Indian Ocean and western Pacific, the enhanced (suppressed) convection is generally preceded in both time and space by a low-level warm and moist (cold and dry) anomaly and followed by a low-level cold and dry (warm and moist) anomaly. The MJO vertical moist thermodynamic structure from the AIRS data is in general agreement, particularly in the free troposphere, with previous studies based on global reanalysis and limited radiosonde data. However, major differences in the lower-troposphere moisture and temperature structure between the AIRS observations and the NCEP reanalysis are found over the Indian and Pacific Oceans, where there are very few conventional data to constrain the reanalysis. Specifically, the anomalous lower-troposphere temperature structure is much less well defined in NCEP than in AIRS for the western Pacific, and even has the opposite sign anomalies compared to AIRS relative to the wet/dry phase of the MJO in the Indian Ocean. Moreover, there are well-defined eastward-tilting variations of moisture with height in AIRS over the central and eastern Pacific that are less well defined, and in some cases absent, in NCEP. In addition, the correlation between MJO-related midtropospheric water vapor anomalies and TRMM precipitation anomalies is considerably more robust in AIRS than in NCEP, especially over the Indian Ocean. Overall, the AIRS results are quite consistent with those predicted by the frictional Kelvin–Rossby wave/conditional instability of the second kind (CISK) theory for the MJO.

Despite decades of climate research and model development, two outstanding problems still plague the latest global climate models (GCMs): the double‐Intertropical Convergence Zone (ITCZ) bias and the 2−5°C spread of equilibrium climate sensitivity (ECS). Here we show that the double‐ITCZ bias and ECS in 44 GCMs from Coupled Model Intercomparison Project Phases 3/5 are negatively correlated. The models with weak (strong) double‐ITCZ biases have high (low)‐ECS values of ~4.1(2.2)°C. This indicates that the double‐ITCZ bias is a new emergent constraint for ECS based on which ECS might be in the higher end of its range (~4.0°C) and most models might have underestimated ECS. In addition, we argue that the double‐ITCZ bias can physically affect both cloud and water vapor feedbacks (thus ECS) and is a more easily measured emergent constraint for ECS than previous ones. It can be used as a performance metric for evaluating and comparing different GCMs.