Causal discovery seeks to recover cause–effect relationships from statistical data using graphical models. One goal of this paper is to provide an accessible introduction to causal discovery methods for climate scientists, with a focus on constraint-based structure learning. Second, in a detailed case study constraint-based structure learning is applied to derive hypotheses of causal relationships between four prominent modes of atmospheric low-frequency variability in boreal winter including the Western Pacific Oscillation (WPO), Eastern Pacific Oscillation (EPO), Pacific–North America (PNA) pattern, and North Atlantic Oscillation (NAO). The results are shown in the form of static and temporal independence graphs also known as Bayesian Networks. It is found that WPO and EPO are nearly indistinguishable from the cause–effect perspective as strong simultaneous coupling is identified between the two. In addition, changes in the state of EPO (NAO) may cause changes in the state of NAO (PNA) approximately 18 (3–6) days later. These results are not only consistent with previous findings on dynamical processes connecting different low-frequency modes (e.g., interaction between synoptic and low-frequency eddies) but also provide the basis for formulating new hypotheses regarding the time scale and temporal sequencing of dynamical processes responsible for these connections. Last, the authors propose to use structure learning for climate networks, which are currently based primarily on correlation analysis. While correlation-based climate networks focus on similarity between nodes, independence graphs would provide an alternative viewpoint by focusing on information flow in the network.

Observations show that increased Arctic cloud cover in the spring is linked with sea ice decline. As the atmosphere and sea ice can influence each other, which one plays the leading role in spring remains unclear. Here we demonstrate, through observational data diagnosis and numerical modeling, that there is active coupling between the atmosphere and sea ice in early spring. Sea ice melting and thus the presence of more open water lead to stronger evaporation and promote cloud formation that increases downward longwave flux, leading to even more ice melt. Spring clouds are a driving force in the disappearance of sea ice and displacing the mechanism of atmosphere‐sea ice coupling from April to June. These results suggest the need to accurately model interactions of Arctic clouds and radiation in Earth System Models in order to improve projections of the future of the Arctic.

The modulation of the North Pacific storm track by tropical convection on intraseasonal time scales (30–90 days) in boreal winter (December–March) is investigated using the NCEP–NCAR reanalysis and NOAA satellite outgoing longwave radiation (OLR) data. Multivariate empirical orthogonal function (MEOF) analysis and case compositing based upon the principal components (PCs) of the EOFs reveal substantial changes in the structure and intensity of the Pacific storm track quantified by vertically (925–200 mb) averaged synoptic eddy kinetic energy (SEKE) during the course of a typical Madden–Julian oscillation (MJO) event. The storm-track response is characterized by an amplitude-varying dipole propagating northeastward as the center of the anomalous tropical convection moves eastward across the eastern Indian Ocean and the western-central Pacific. A diagnosis of the SEKE budget indicates that the storm-track anomaly is induced primarily by changes in the convergence of energy flux, baroclinic conversion, and energy generation due to the interaction between synoptic eddies and intraseasonal flow anomalies. This demonstrates the important roles played by eddy–mean flow interaction and eddy–eddy interaction in the development of the extratropical response to MJO variability. The feedback of synoptic eddy to intraseasonal flow anomalies is pronounced: when the center of the enhanced tropical convection is located over the Maritime Continent (western Pacific), the anomalous synoptic eddy forcing partly drives an upper-tropospheric anticyclonic (cyclonic) and, to its south, a cyclonic (anticyclonic) circulation anomaly over the North Pacific. Associated with the storm-track anomaly, a three-band (dry–wet–dry) anomaly in both precipitable water and surface precipitation propagates poleward over the eastern North Pacific and induces intraseasonal variations in the winter hydroclimate over western North America.

The variability of Southeastern (SE) United States (U.S.) summer precipitation in the current and future climate is analyzed using Coupled Model Intercomparison Project‐Phase 5 (CMIP5) models. By comparing simulated historical precipitation variability with observations, we categorize CMIP5 models into two groups: Group 1 (G1) models that simulate the summer precipitation variability reasonably well and Group 2 (G2) models that need further improvements. Our analysis suggests that the relatively higher skill of G1 models is attributable to their ability to accurately represent the dynamical linkage between SE U.S. summer precipitation variability and North Atlantic Subtropical High (NASH) western ridge position. In contrast, the inability of G2 models to represent such linkage leads to their biases in simulating SE U.S. summer precipitation variability. According to our analysis, the ensemble projection of CMIP5 models suggests that under the Representative Concentration Pathway (RCP) 4.5 scenario, SE U.S. summer precipitation variability will intensify and that this intensification is more pronounced among G1 models. Our analysis further suggests that this intensification is most likely due to the projected pattern shift of the NASH western ridge in a warming climate. Under the RCP4.5 scenario, the NASH western ridge will extend further westward leading to more frequent occurrences of the northwestward and southwestward ridge patterns that are respectively related to dry and wet summers in the SE U.S. Consequently, more frequent occurrence of summer precipitation extremes would be expected over the SE U.S. in the future.