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This study evaluates the decadal prediction skill of 13 forecast systems in predicting winter precipitation over Eurasia, contributing to the Decadal Climate Prediction Project of the Coupled Model Intercomparison Project Phase 6. Northeast Asia stands out as a region with improved decadal prediction skill for forecast years 2–5 due to the initialization. Observations show anticyclonic and cyclonic wind anomalies over the North Pacific and Northeast Asia, respectively, with southwesterly flow to the east of Northeast Asia. Ten forecast systems reproduce such circulation anomalies favoring abundant winter precipitation in Northeast Asia. The significant positive (negative) correlations between the detrended Northeast Asian precipitation (NEAP) and AMV (PDO-like) time series are reproduced by seven (nine) forecast systems. However, most forecast systems underestimate the correlation between the NEAP and the AMV, and have relatively low skill in predicting the PDO. Further improvements in these aspects will help to improve the decadal prediction skill of winter precipitation over Northeast Asia. The multi-model ensemble (MME) is able to reproduce both links of NEAP with AMV and PDO-like variability. The MME demonstrates significant skill and outperforms the individual forecast systems in predicting the NEAP for all 4-year averaged periods in the range of 1–8 years, demonstrating the benefits of using the ensemble mean of multiple models. [ABSTRACT FROM AUTHOR]

The reliability of the near-land-surface air temperature (LSAT) projections from the state-of-the-art climate-system models that participated in the Coupled Model Intercomparison Project phase six (CMIP6) is debatable, particularly on regional scales. Here we introduce a method of constructing a constrained multi-model-ensemble (CMME), based on rejecting models that fail to reproduce observed LSAT trends. We use the CMME to constrain future LSAT projections under the Shared Socioeconomic Pathways 5–8.5 (SSP5–8.5) and 2–4.5 (SSP2–4.5), representing the high and intermediate scenarios. In comparison with the "raw" (unconstrained) CMIP6 multi-model ensemble (MME) mean, the impact of the observation-based constraint is less than 0.05oC 100 years−1 at a global scale over the second half of 21st century. However, the regional results show a wider range of positive and negative adjustments, from -1.0oC 100 years−1 to 1oC 100 years−1 under the SSP5–8.5 scenario. Although amplitude under SSP2–4.5 is relatively smaller, the CMME adjustment is similar to that under SSP5–8.5, indicating the scenario independency of the CMME impact. The ideal 1pctCO2 experiment suggests that the response of LSAT to carbon dioxide (CO2) forcing on regional scales is responsible for the MME biases in the historical period, implying the high reliability of CMME in the 21st century projections. The advantage of CMME is that it goes beyond the idea of "model democracy" assumed in MME. The unconstrained CMIP6 MME may be overestimating the risks of future warming over North America, but underestimating the risks over Asia. [ABSTRACT FROM AUTHOR]

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry–climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with "weak" (SSP3-7.0) versus "strong" (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM 2.5) and ozone (O3) decrease by -2.2±0.32 µ g m -3 and -4.6±0.88 ppb, respectively (changes quoted here are for the entire 2015–2055 time period; uncertainty represents the 95 % confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.25±0.12 K and 0.03±0.012 mm d -1 , respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0.66±0.20 K and 0.03±0.02 mm d -1), south Asia (0.47±0.16 K and 0.17±0.09 mm d -1), and east Asia (0.46±0.20 K and 0.15±0.06 mm d -1). Relatively large warming and wetting of the Arctic also occur at 0.59±0.36 K and 0.04±0.02 mm d -1 , respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals. [ABSTRACT FROM AUTHOR]

Several monsoon indices have been applied to multiple models from the sub-seasonal to seasonal ( S2S) prediction project database during the period May to October 1999-2010 to assess their ability to simulate the Asian monsoon. The bivariate anomaly correlation ( BAC) of the Boreal Summer IntraSeasonal Oscillation ( BSISO) index suggests that the operational models can predict the BSISO1 and BSISO2 events up to 6-24.5 and 6.5-14 days in advance respectively, although the models tend to underestimate the amplitude of BSISO as the lead time increases. For the strong BSISO events, BSISO1 ( BSISO2) display lower skill mostly in phases 3-5 for all the models, suggesting that the BSISO1 ( BSISO2) is not easy to predict when it is located over India and the Maritime Continent (South China Sea and Bay of Bengal). On the other hand, the higher skills appear in different phases for different models. For instance, the limit of predictive skill of strong BSISO1 and BSISO2 events in phases 6-7 for the ECMWF ensemble forecast could exceed 30 and 28 days, respectively. The comparisons of the BSISO life cycle among the ECMWF, NCEP and CMA models also indicate that the ECMWF model can better predict the evolution of strong BSISO events. Predictions of additional monsoon circulation indices including the Webster-Yang index ( WY), Indian Summer Monsoon index ( ISM), South Asian Monsoon index ( SAM), and SouthEast Asian Monsoon index ( SEAM) in the S2S models have statistically significant skill over the corresponding monsoon regions up to 9-31, 3-17, 7-13 and 7-14 days, respectively. However, the significant skill of summer monsoon precipitation over the SAM and SEAM regions varies significantly among the models, with the skill ranging from 2 days to 2 weeks lead time. [ABSTRACT FROM AUTHOR]

In this study, the authors apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM, version 2.1 (BCC_AGCM2.1). The results herein show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulated precipitation climatology could be remarkably improved, including increased precipitation over the equatorial Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic mei-yu distribution over eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It is shown that simulations with better ASM precipitation climatology can also produce more realistic precipitation anomalies during El Niño-decaying summer. In the low-skill experiments for precipitation climatology, the ENSO-induced precipitation anomalies are most significant over continents (vs over ocean in observations) in the South Asian monsoon region. More realistic results are derived from the higher-skill experiments with stronger anomalies over the Indian Ocean and weaker anomalies over India and the western Pacific Ocean, favoring more evident easterly anomalies forced by the tropical Indian Ocean warming and stronger Indian Ocean-western Pacific teleconnection as observed. The model results reveal a strong connection between the simulated ASM precipitation climatological state and interannual variability in BCC_AGCM2.1 when key parameters are perturbed. [ABSTRACT FROM AUTHOR]

Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability (IAV) and intraseasonal variability (ISV) of the Asian-western Pacific summer monsoon are diagnosed. Predictions show reasonable skill with respect to some basic characteristics of the ISV and IAV of the western North Pacific summer monsoon (WNPSM) and the Indian summer monsoon (ISM). However, the links between the seasonally averaged ISV (SAISV) and seasonal mean of ISM are overestimated by the model. This deficiency may be partially attributable to the overestimated frequency of long breaks and underestimated frequency of long active spells of ISV in normal ISM years, although the model is capable of capturing the impact of ISV on the seasonal mean by its shift in the probability of phases. Furthermore, the interannual relationships of seasonal mean, SAISV, and seasonally averaged long-wave variability (SALWV; i.e., the part with periods longer than the intraseasonal scale) of the WNPSM and ISM with SST and low-level circulation are examined. The observed seasonal mean, SAISV, and SALWV show similar correlation patterns with SST and atmospheric circulation, but with different details. However, the model presents these correlation distributions with unrealistically small differences among different scales, and it somewhat overestimates the teleconnection between monsoon and tropical central-eastern Pacific SST for the ISM, but underestimates it for the WNPSM, the latter of which is partially related to the too-rapid decrease in the impact of El Niño-Southern Oscillation with forecast time in the model. [ABSTRACT FROM AUTHOR]