Evaluation of the Pacific Decadal Oscillation from 1901 to 2014 in CMIP6 models

Abstract

The simulation of internal climate variability is key to understanding climate change. Internal fluctuations can fully obscure or amplify the underlying climate-change signal in many fields over years to decades. The Pacific Decadal Oscillation (PDO) is an important mechanism that dominates interdecadal climate variations. Here, the capacity of 36 Coupled Model Intercomparison Project Phase 6 (CMIP6) models for reproducing the PDO during the period 1901-2014 was evaluated across spatial pattern, amplitude, periodicity and phase aspects. The results suggested that approximately 71% of the models were capable of capturing the spatial pattern of the PDO. However, most of the other models underestimated the percentage of the variance explained and the pattern amplitude. CMIP6 models can capture the periodicity over shorter periods (<20 yr), while most CMIP6 models underestimate the periodicity of the PDO on the interdecadal scale (60 yr periods). In particular, the probability distribution functions (PDFs) of the raw PDO index showed that most CMIP6 models could capture the unimodal probability distribution. Some of the models were able to reproduce the bimodal probability distribution of the PDO index filtered by the ensemble empirical mode decomposition method. Moreover, the findings also showed that the multimodel ensemble (MME) for 36 CMIP6 models could effectively capture the spatial pattern and periodicity over a shorter period (<20 yr) of the PDO. Moreover, the MME exhibited higher fidelity to the observation in the PDF of the PDO index, although the positive area was larger than the observation. These findings are crucial because they may help detect simulation gaps and provide valuable references for the design and applicability of future models worldwide.

Assessing Climate Change Effects on Winter Wheat Production in the 3H Plain: Insights from Bias-Corrected CMIP6 Projections

“…An anticipated increase in precipitation across most of the 3H Plain under both scenarios suggests improved water resource conditions, potentially reducing drought probability and meeting the water demands of winter wheat in the northern 3H Plain, which has been a major constraint on production [8]. In contrast, the southern 3H Plain, with its relatively abundant water resources, may experience rainfall in excess of the winter wheat's water demand, leading to potential increases in plant diseases, pest outbreaks, and flooding, thus resulting in lower yields [21,78].…”

“…Among these, the decision support system for agrotechnology transfer (DSSAT) CERES-Wheat model stands out for its widespread application in analyzing climate change effects on crop yield [13][14][15], growth period [16,17], climate suitability [18,19], and agricultural planning [10,20]. The DSSAT CERES-Wheat model has demonstrated strong adaptability in China [21]. For example, the impacts of planning date shifts on the phenology of double cropping rice was determined by changing the planning date in the DSSAT CERES-Wheat model [22].…”

Understanding the Inter-Model Spread of PDO’s Impact on Tropical Cyclone Frequency over the Western North Pacific in CMIP6 Models

“…The reverse pattern is observed during the negative phase of PDO. Previous studies have extensively assessed the performances of the simulated PDO in CMIP3-6 models [21][22][23][24][25][26][27]. Considerable inter-model spread in reproducing the PDO-related SST anomaly is found in the CMIP3 models [21,23].…”