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QiFeng Qian, XiaoJing Jia, Hai Lin, and Ruizhi Zhang

Abstract

In this study, four machine-learning (ML) models [gradient boost decision tree (GBDT), light gradient boosting machine (LightGBM), categorical boosting (CatBoost), and extreme gradient boosting (XGBoost)] are used to perform seasonal forecasts for nonmonsoonal winter precipitation over the Eurasian continent (30°–60°N, 30°–105°E) (NWPE). The seasonal forecast results from a traditional linear regression (LR) model and two dynamic models are compared. The ML and LR models are trained using the data for the period of 1979–2010, and then these empirical models are used to perform the seasonal forecast of NWPE for 2011–18. Our results show that the four ML models have reasonable seasonal forecast skills for the NWPE and clearly outperform the LR model. The ML models and the dynamic models have skillful forecasts for the NWPE over different regions. The ensemble means of the forecasts including the ML models and dynamic models show higher forecast skill for the NWEP than the ensemble mean of the dynamic-only models. The forecast skill of the ML models mainly benefits from a skillful forecast of the third empirical orthogonal function (EOF) mode (EOF3) of the NWPE, which has a good and consistent prediction among the ML models. Our results also illustrate that the sea ice over the Arctic in the previous autumn is the most important predictor in the ML models in forecasting the NWPE. This study suggests that ML models may be useful tools to help improve seasonal forecasts of the NWPE.

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Ivana Cerovečki and Andrew J. S. Meijers

Abstract

The deepest wintertime (July–September) mixed layers associated with Subantarctic Mode Water (SAMW) formation develop in the Indian and Pacific sectors of the Southern Ocean. In these two sectors the dominant interannual variability of both deep wintertime mixed layers and SAMW volume is an east–west dipole pattern in each basin. The variability of these dipoles is strongly correlated with the interannual variability of overlying winter quasi-stationary mean sea level pressure (MSLP) anomalies. Anomalously strong positive MSLP anomalies are found to result in the deepening of the wintertime mixed layers and an increase in the SAMW formation in the eastern parts of the dipoles in the Pacific and Indian sectors. These effects are due to enhanced cold southerly meridional winds, strengthened zonal winds, and increased surface ocean heat loss. The opposite occurs in the western parts of the dipoles in these sectors. Conversely, strong negative MSLP anomalies result in shoaling (deepening) of the wintertime mixed layers and a decrease (increase) in SAMW formation in the eastern (western) regions. The MSLP variabilities of the Pacific and Indian basin anomalies are not always in phase, especially in years with a strong El Niño, resulting in different patterns of SAMW formation in the western versus eastern parts of the Indian and Pacific sectors. Strong isopycnal depth and thickness anomalies develop in the SAMW density range in years with strong MSLP anomalies. When advected eastward, they act to precondition downstream SAMW formation in the subsequent winter.

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Helene Asbjørnsen, Helen L. Johnson, and Marius Årthun

Abstract

The inflow across the Iceland–Scotland Ridge determines the amount of heat supplied to the Nordic seas from the subpolar North Atlantic (SPNA). Consequently, variable inflow properties and volume transport at the ridge influence marine ecosystems and sea ice extent farther north. Here, we identify the upstream pathways of the Nordic seas inflow and assess the mechanisms responsible for interannual inflow variability. Using an eddy-permitting ocean model hindcast and a Lagrangian analysis tool, numerical particles are released at the ridge during 1986–2015 and tracked backward in time. We find an inflow that is well mixed in terms of its properties, where 64% comes from the subtropics and 26% has a subpolar or Arctic origin. The local instantaneous response to the NAO is important for the overall transport of both subtropical and Arctic-origin waters at the ridge. In the years before reaching the ridge, the subtropical particles are influenced by atmospheric circulation anomalies in the gyre boundary region and over the SPNA, forcing shifts in the North Atlantic Current (NAC) and the Subpolar Front. An equatorward-shifted NAC and westward-shifted Subpolar Front correspond to a warmer, more saline inflow. Atmospheric circulation anomalies over the SPNA also affect the amount of Arctic-origin water rerouted from the Labrador Current toward the Nordic seas. A high transport of Arctic-origin water is associated with a colder, fresher inflow across the Iceland–Scotland Ridge. The results thus demonstrate the importance of gyre dynamics and wind forcing in affecting the Nordic seas inflow properties and volume transport.

Open access
Zhe Wang, Jiankai Zhang, Tao Wang, Wuhu Feng, Yihang Hu, and Xiran Xu

Abstract

The factors responsible for the size of the Antarctic ozone hole in November are analyzed. Comparing two samples of anomalously large and small November ozone holes with respect to 1980–2017 climatology in November, the results show that the anomalously large ozone hole in austral late winter is not a precondition for the anomalously large ozone hole in November. The size of the Antarctic ozone hole in November is mainly influenced by dynamical processes from the end of October to mid-November. During anomalously large November ozone hole events, weaker dynamical ozone transport appears from the end of October to mid-November, which is closely related to planetary wave divergence in the stratosphere between 60° and 90°S. Further analyses indicate that the wave divergence is partially attributed to less upward propagation of planetary waves from the troposphere, which is associated with weak baroclinic disturbances at the end of October. Subsequently, zonal wind speed in the upper stratosphere intensifies, and the distance between the critical layer (U = 0) and wave-reflecting surfaces becomes larger. As a result, more planetary waves are reflected and then wave divergence is enhanced. The processes responsible for the anomalously small Antarctic ozone holes in November are almost opposite to those for the anomalously large Antarctic ozone holes.

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Se-Yong Song, Sang-Wook Yeh, and Hyun-Su Jo

Abstract

The leading modes of the North Pacific jet (NPJ) variability include intensity changes and meridional shifts in jet position on low-frequency time scales. These leading modes of NPJ variability are closely associated with weather and climate conditions spanning from Asia to the United States. In this study, we investigated changes in the NPJ’s role as a conduit for U.S. surface air temperature (SAT) anomalies during the boreal winter across the late 1990s. We found that the leading mode of NPJ variability changed from the NPJ intensity changes to meridional shifts in NPJ position across the late 1990s. It leads to the change in the role of the NPJ as a conduit for U.S. SAT anomalies. Before the late 1990s, the variability of NPJ intensity significantly impacted western U.S. SAT anomalies related to the anomalous surface cyclonic circulation over the North Pacific. After the late 1990s, however, the variability of the NPJ’s meridional shift significantly influenced the eastern U.S. SAT anomalies in association with the anomalous surface cyclonic circulation over the northern North Pacific. Further analysis and model experiments revealed that the western to central North Pacific Ocean has been warming since the late 1990s and modulates atmospheric baroclinicity. This phenomenon mainly leads to a northward NPJ shift and implies that the eddy-driven mechanism on the NPJ’s formation, which acts to enhance the meridional variability of NPJ position, becomes dominant. We conclude that this northward shift of NPJ could have contributed to enhancing the NPJ’s meridional shift variability, significantly influencing the eastern U.S. SAT anomalies since the late 1990s.

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XiaoJing Jia, Chao Zhang, Renguang Wu, and QiFeng Qian

Abstract

The present study explores the changed relationship between the interannual variations in spring (April–May) precipitation over southern China (SPSC) and sea surface temperature (SST) anomalies in the tropical Pacific and south Indian Oceans during the 1960–2017 period. Observational analysis shows that the relation between SPSC and El Niño–Southern Oscillation (ENSO) was significant before the mid-1980s (P1) and after the early 2000s (P3) but insignificant in between, from the mid-1980s to the early 2000s (P2). In P2, positive anomalous SPSC was significantly correlated with negative anomalous SST in the south Indian Ocean. During this period, an anomalous anticyclone and intensified southwesterly winds tended to appear over tropical India accompanied by a negative anomalous south Indian Ocean SST, which caused anomalous low-level convergence over the western Pacific. As a result, the western Pacific subtropical high (WPSH) tended to weaken and retreat eastward. This resulted in anomalous moisture convergence in southern China, favoring enhanced SPSC. Further analysis shows that the negative south Indian Ocean SST anomalies tended to induce anomalous cross-equatorial vertical circulation where the south Indian Ocean and southern China are controlled by descending and ascending airflow. The ascending motion may also contribute to positive anomalous SPSC. The observed contribution of the south Indian Ocean SST anomalies to the SPSC variation is confirmed by numerical experiments using an atmospheric model. The intensified variance of SST in the south Indian Ocean and the eastward shift of the ENSO-related circulation anomalies over the western tropical Pacific may partly account for the changes in the SST–SPSC relationship.

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Xiuhua Zhu

Abstract

This work proposes a framework to examine interactions of climate modes that are identified as leading EOF modes; their coupling structure is unveiled through correlation analysis and helps in constructing a regression model, whose performance is compared across GCMs, thereby providing a quantitative overview of model performances in simulating mode interaction. As a demonstration surface temperature is analyzed for five CMIP5 preindustrial control (PiControl) simulations. Along with the seasonal land and ocean modes, four interannual modes are identified: the tropical mode (TM) associated with the Hadley circulation, the tropical Pacific mode (TPM) characterizing a zonal temperature contrast between the eastern tropical Pacific and the Atlantic/Indian Oceans, and two annular modes, the Arctic mode (AM) and Antarctic mode (AAM). All GCMs converge on the following points: 1) TM strongly couples with seasonal signals of the previous year; 2) TPM leads TM by 1 year, and thus a weaker zonal temperature contrast in the tropics contributes to warming in the entire tropical band 1 year later; and 3) AM weakly couples to TM at a 1-yr lead, suggesting that a colder North Pole may contribute to colder tropics. In addition, all GCMs do not support a linear coupling between AAM and TM. The above-learned coupling structure is incorporated to construct an optimum regression model that demonstrates considerable predictive power. The proposed approach may both serve as a useful tool for dynamical analysis and lend insight into GCM differences. Its merit is demonstrated by the finding that different representations of the mean seasonal cycle in GCMs may account for the GCM dependence of relative contributions of seasonal and interannual modes to TM variability.

Open access
Victor C. Mayta, George N. Kiladis, Juliana Dias, Pedro L. Silva Dias, and Maria Gehne

Abstract

Rainfall over tropical South America is known to be modulated by convectively coupled Kelvin waves (CCKWs). In this work, the origin and dynamical features of South American Kelvin waves are revisited using satellite-observed brightness temperature, radiosonde, and reanalysis datasets. Two main types of CCKWs over the Amazon are considered: Kelvin waves with a Pacific precursor, and Kelvin waves with a precursor originating over South America. Amazonian CCKWs associated with a preexisting Kelvin convection in the eastern Pacific account for about 35% of the total events. The cases with South American precursors are associated with either pressure surges in the western Amazon from extratropical wave train activity, responsible for 40% of the total events, or “in situ” convection that locally excites CCKWs, accounting for the remaining 25%. The analysis also suggests that CCKWs associated with different precursors are sensitive to Pacific sea surface temperature. Kelvin wave events with a Pacific precursor are more common during ENSO warm events, while Kelvin waves with extratropical South American precursors show stronger activity during La Niña events. This study also explores other triggering mechanisms of CCKWs over the Amazon. These mechanisms are associated with 1) extratropical Rossby wave trains not necessarily of extratropical South American origin; 2) CCKWs initiated in response to the presence of the southern and/or double intertropical convergence zone (ITCZ) in the eastern Pacific Ocean; and 3) possible interaction between CCKWs and other equatorial waves in the Amazon.

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Yue Li, James T. Randerson, Natalie M. Mahowald, and Peter J. Lawrence

Abstract

Phosphorus contained in atmospheric mineral dust aerosol originating from Africa fertilizes tropical forests in Amazonia. However, the mechanisms influencing this nutrient transport pathway remain poorly understood. Here we use the Community Earth System Model to investigate how large-scale deforestation affects mineral dust aerosol transport and deposition in the tropics. We find that the surface biophysical changes that accompany deforestation produce a warmer, drier, and windier surface environment that perturbs atmospheric circulation and enhances long-range dust transport from North Africa to the Amazon. Tropics-wide deforestation weakens the Hadley circulation, which then leads to a northward expansion of the Hadley cell and increases surface air pressure over the Sahara Desert. The high pressure anomaly over the Sahara, in turn, increases northeasterly winds across North Africa and the tropical North Atlantic Ocean, which subsequently increases dust transport to the South American continent. We estimate that the annual atmospheric phosphorus deposition from dust significantly increases by 27% (P < 0.01) in the Amazon under a scenario of complete deforestation. These interactions exemplify how land surface changes can modify tropical nutrient cycling, which, in turn, may have consequences for long-term changes in tropical ecosystem productivity and biodiversity.

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Daniel F. Schmidt and Kevin M. Grise

Abstract

Climate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each. This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in twenty-first-century U.S. winter precipitation trends across CMIP6 models under the SSP3–7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, El Niño–Southern Oscillation (ENSO), the Pacific–North America (PNA) pattern, and the east Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern United States result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern United States result from a combination of strong global warming and a negative PNA trend.

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