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Previous studies have emphasized the significance of a strong El Niño preceding La Niña (LN) in the formation of multi-year LN events due to the slow recharge-discharge ocean heat content process. However, observational analyses from 1900 to 2022 reveal that the majority (64%) of multi-year LN events did not necessitate a preceding strong El Niño to generate their second LN, suggesting an overemphasis on traditional views. Instead, here we show that a negative phase of the North Pacific Meridional Mode (PMM) during spring, when the first LN begins to decay, activates the mechanism responsible for triggering another LN and producing a multi-year event. The westward extension of the first LNs cold anomalies, which interact directly with the eastern edge of the western Pacific warm pool, is highlighted as a crucial factor in the occurrence of a negative PMM. Additionally, the PMM mechanism can create a third LN, leading to triple-dip events.

The Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) Version 2.0 (V2.0) monthly mean tropospheric air temperature, specific humidity, and relative humidity profile data were designed for climate model evaluation in the context of the Coupled Model Intercomparison Project (CMIP). Due to the limitations of the Aqua satellite orbit and the AIRS retrieval algorithm, the sampling biases of the AIRS Obs4MIPs V2.0 data can be large for certain cases and must be considered when the AIRS Obs4MIPs V2.0 data are used for climate model evaluation. In this study, we estimate the sampling biases of the AIRS Obs4MIPs V2.0 data based on the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) (ERA5) reanalysis and cross-check them using the Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) reanalysis. We then remove the estimated sampling biases from the AIRS Obs4MIPs V2.0 data and produce the sampling-bias-corrected AIRS Obs4MIPs V2.1 data that have been published at the Earth System Grid Federation (ESGF) data centers and should be used in the future for climate model evaluation.

In this study, the Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) V2.1 tropospheric air temperature, specific humidity, and relative humidity data are utilized to evaluate the global tropospheric temperature and humidity simulations in the fully coupled global climate models from the Coupled Model Intercomparison Project phases 3, 5, and 6 (CMIP3, CMIP5, and CMIP6), and possible simulation improvement in CMIP6 models in comparison to CMIP3 and CMIP5 models. Our analyses indicate that all three phases of CMIP models share similar tropospheric air temperature, specific humidity, and relative humidity biases in their multi‐model ensemble means relative to AIRS. Cold biases up to 4 K and positive relative humidity biases up to 20% are found in the free troposphere almost globally with maxima over the mid‐latitude storm tracks. Warm biases up to 2 K are seen over the Southern Ocean in the lower troposphere. Positive specific and relative humidity biases exist over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere, which are related to the double‐intertropical convergence zone bias in the models. Both the air temperature and specific humidity biases are important to the relative humidity biases except in the tropical free troposphere where the specific humidity biases dominate. The tropospheric air temperature, specific humidity, and relative humidity biases are reduced from CMIP3 to CMIP5 and to CMIP6 at almost all pressure levels except at 300 hPa for specific humidity and in the boundary layer for relative humidity. Plain Language Summary: In this study, we use the Atmospheric Infrared Sounder (AIRS) data to assess how well the fully coupled global climate models simulate temperature and humidity in the troposphere. We focus on the climate models from the recent three phases of Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) and investigate if there is any bias reduction in the recent CMIP6 models compared to the earlier CMIP3 and CMIP5 models. To conduct our evaluation, we compare the CMIP model ensemble averages with the AIRS data and find that all three phases of CMIP models exhibit similar biases in tropospheric temperature and humidity. For example, cold biases up to 4 K and positive relative humidity biases up to 20% are seen in the free troposphere over most regions, with the maximum biases over the midlatitudes. Positive specific and relative humidity biases are found over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere. We also note a possible temperature and humidity bias reduction from the CMIP3 models to the CMIP5 models and then to the CMIP6 models at most pressure levels. Key Points: CMIP Phase 3, 5 and 6 climate models share similar tropospheric air temperature, specific and relative humidity biases relative to Atmospheric Infrared SounderCold biases and positive relative humidity biases are prevalent in free troposphere almost globally with maxima over the mid‐latitude oceansDouble‐intertropical convergence zone bias‐related specific and relative humidity biases are evident in tropical free troposphere: positive (negative) off (near) the equator [ABSTRACT FROM AUTHOR]

We estimate global fresh water discharge from land-to-oceans (Q) and evapotranspiration (ET) on monthly time scales using a number of complimentary hydrologic data sets. This estimate is possible due to the new capability of measuring oceanic and land water mass changes from GRACE as well as the space-based measurements of oceanic and land precipitation (Pl ) and oceanic evaporation. Monthly time series of Q show peaks in July and January, and those of ET show peaks in March, May and August. Our estimates of Q andET are correlated with Pl  indicating qualitatively that our estimates capture temporal patterns of Q and ETreasonably well. Comparison of our Q with two other previous estimates based on the Global Runoff Data Centre (GRDC) river gauges network shows that our maximum peak in Q occurs about a month later than previous estimates. In addition, we compare our estimation of Q and ET to 20th century simulations from the WCRP CMIP3 multi-model archive assessed in the IPCC 4th Assessment Report. Runoff (R) and ET from AOGCMs tend to only exhibit the annual cycle, but the Q estimated in this study exhibits additional semi-annual variations that exists in Pl  as well. In addition, R from the models shows a maximum peak 2 months earlier than the estimated Q, which is due partly to the river discharge time lag that most AOGCMs do not take into account. These results indicate that current AOGCMs exhibit basic shortcomings in simulating Qand ET accurately. The new method developed here can be a useful constraint on these models and can be useful to close budget of global water balance.

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.