Abstract

Using station observations of the number of days covered by snow (SCD) and snowfall over the Tibetan Plateau (TP), the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis, and precipitation from rain gauge stations in China for the period of 1973–2001, temporal/spatial variations of SCD over the TP and its associations with the hemispheric extratropical atmospheric circulation and East Asian summer monsoon rainfall are investigated.

An increase of spring (April–May) SCD over the TP is associated with decreases of local tropospheric temperature and geopotential height in the spring and early summer (June). The anomalies in the tropospheric temperature and geopotential height show a westward propagation from the TP to western Asia as a result of the westward propagation of the anomalous wave energy. These tropospheric anomalies over the TP are connected with changes in the hemispheric extratropical atmospheric circulation along the westerly jet stream that acts as a waveguide.

The increase of the spring SCD is also associated with the variation of the East Asian summer monsoon rainfall. Soil moisture in May–June might act as a bridge linking the spring snow anomaly and the subsequent summer monsoon. Corresponding to the increase of SCD, there is a significant decrease of the June 500-mb geopotential height from the TP to the western North Pacific. Meanwhile, the anomalous northeasterlies extend from Japan, through the east coast of China, to central-eastern China, which weaken the East Asian summer monsoon, leading to a decrease of surface air temperature and rainfall in the Yangtze and Hwai Rivers and an increase of rainfall in southeastern China.

Additionally, the spring SCD anomaly is likely due to a variation of local synchronous snowfall, rather than previous winter SCD conditions. The spring SCD is not related to previous winter El Niño/La Niña events, but is associated with the equatorial central and eastern Pacific sea surface temperature from the subsequent summer through winter. The climatic implications for this relationship are not clear.

Abstract

This study focuses on the month-to-month variability of winter temperature anomalies over Northeast China (NECTA), especially the out-of-phase change between December and January–February (colder than normal in December and warmer than normal in January–February, and vice versa), which accounts for 30% of the past 37 years (1980–2016). Our analysis shows that the variability of sea ice concentration (SIC) in the preceding November over the Davis Strait–Baffin Bay (SIC_DSBB) mainly affects NECTA in December, whereas the SIC over the Barents–Kara Sea (SIC_BKS) significantly impacts NECTA in January–February. A possible reason for the different effects of SIC_DSBB and SIC_BKS on NECTA is that the month-to-month increments (here called DM) of SIC over these two areas between October and November are different. A smaller DM of SIC_DSBB in November can generate eastward-propagating Rossby waves toward East Asia, whereas a larger DM of SIC_BKS can affect upward-propagating stationary Rossby waves toward the stratosphere in November. Less than normal SIC_DSBB in November corresponds to a negative phase of the sea surface temperature tripole pattern over the North Atlantic, which contributes to a negative phase of the North Atlantic Oscillation (NAO)-like geopotential height anomalies via the eddy-feedback mechanism, ultimately favoring cold conditions over Northeast China. However, positive November SIC_BKS anomalies can suppress upward-propagating Rossby waves that originate from the troposphere in November, strengthening the stratospheric polar vortex and leading to a positive phase of an Arctic Oscillation (AO)-like pattern in the stratosphere. Subsequently, these stratospheric anomalies propagate downward, causing the AO-like pattern in the troposphere in January–February, favoring warm conditions in Northeast China, and vice versa.

Abstract

Interdecadal changes in the relationship between El Niño–Southern Oscillation (ENSO) and midlatitude atmospheric circulation are investigated in this study. Comparison of associations between ENSO and midlatitude atmospheric circulation anomalies between 1958–76 and 1977–2010 suggest that during 1958–76, ENSO exerted a strong impact on the East Asian winter monsoon (EAWM) and the associated atmospheric circulation pattern was similar to the positive North Pacific Oscillation (NPO). In contrast, during 1977–2010, the NPO-like atmospheric pattern disappeared. Instead, ENSO exerted a strong impact on the eastern North Pacific Ocean (NP) and North America, and the associated atmospheric circulation pattern resembled the Pacific–North America (PNA) teleconnection. Also, significant correlations between ENSO and sea surface temperature anomalies (SSTAs) over the western subtropical NP during 1958–76 became insignificant during 1977–2010, whereas negative correlations between ENSO and SSTAs in the central and northeastern subtropical NP became more significant since the mid-1970s. Further analyses suggest that the interdecadal shift of the Aleutian low, which occurred around the mid-1970s, might be responsible for the identified changes. Before the mid-1970s, warm ENSO events generated an anomalous anticyclone over the western NP, which is a key system bridging ENSO and EAWM-related atmospheric circulation. After the mid-1970s, the Aleutian low intensified and shifted eastward, leading to the impact of ENSO prevailing over the eastern NP. In addition, the weakened (strengthened) ENSO–NPO/EAWM (ENSO–PNA) relationship likely contributed to the weakened (strengthened) relationship between ENSO and SSTAs over the western (central and eastern) subtropical NP.

Abstract

Consistency and discrepancy of air–sea latent and sensible heat fluxes (LHF and SHF, respectively) in the Southern Ocean for current-day flux products are analyzed from climatology and interannual-to-decadal variability perspectives. Five flux products are examined, including the National Oceanography Centre, Southampton flux dataset version 2 (NOCS2), the National Centers for Environmental Prediction/Department of Energy Global Reanalysis 2 (NCEP-2), the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data version 3 (HOAPS-3), and the objectively analyzed air–sea fluxes (OAFlux).

Comparisons suggest that most datasets show encouraging agreement in the spatial distribution of the annual-mean LHF, the meridional profile of the zonal-averaged LHF, the leading empirical orthogonal function (EOF) mode of the LHF and SHF, and the large-scale response of the LHF and SHF to the Antarctic Oscillation (AAO) and El Niño–Southern Oscillation (ENSO). However, substantial spatiotemporal discrepancies are noteworthy. The largest across-data scatter is found in the central Indian sector of the Antarctic Circumpolar Current (ACC) for the annual-mean LHF, and in the Atlantic and Indian sectors of the ACC for the annual-mean SHF, which is comparable to and even larger than their respective interannual variability. The zonal mean of the SHF varies widely across the datasets in the ACC. There is a large spread in the seasonal cycle for the LHF and SHF among the datasets, particularly in the cold season. The datasets show interannual variability of various amplitudes and decadal trends of different signs. The flux variability of the NOCS2 is substantially different from the other datasets. Possible attributions of the identified discrepancies for these flux products are discussed based on the availability of the input meteorological state variables.

Abstract

Arctic sea ice in summer shows both interannual and long-term variations, and atmospheric circulation anomalies are known to play an important role. This study compares the summertime large-scale circulation anomalies associated with Arctic sea ice on interannual and decadal time scales. The results indicate that the circulation anomalies associated with decreased sea ice on an interannual time scale are characterized by a barotropic anticyclonic anomaly in the central Arctic, and the thermodynamic process is important for the circulation–sea ice coupling. On one hand, the descending adiabatic warming in low levels associated with the central Arctic anticyclonic anomaly leads to decreased sea ice by enhancing the downwelling longwave radiation. On the other hand, the anticyclonic anomaly also induces more moisture in low levels. The enhanced moisture and temperature (coupled with each other) further favor the reduction of sea ice by emitting more downwelling longwave radiation. By contrast, associated with the decadal sea ice decline, there is an anticyclonic anomaly over Greenland and a cyclonic anomaly over northern Siberia, and the wind-driven sea ice drift dominates the sea ice decline. The transpolar circulation anomalies between the anticyclonic and cyclonic anomalies promote transport of the ice away from the coasts of Siberia toward the North Pole, and drive the ice out of the Arctic Ocean to the North Atlantic. These circulation anomalies also induce sea ice decline through thermodynamic process, but it is not as significant as that on an interannual time scale.

Abstract

Current climate models project that Antarctic sea ice will decrease by the end of the twenty-first century. Previous studies have suggested that Antarctic sea ice changes have impacts on atmospheric circulation and the mean state of the Southern Hemisphere. However, little is known about whether Antarctic sea ice loss may have a tangible impact on climate extremes over the southern continents and whether ocean–atmosphere coupling plays an important role in changes of climate extremes over the southern continents. In this study, we conduct a set of fully coupled and atmosphere-only model experiments forced by present and future Antarctic sea ice cover. It is found that the projected Antarctic sea ice loss by the end of the twenty-first century leads to an increase in the frequency and duration of warm extremes (especially warm nights) over the southern continents and a decrease in cold extremes over most regions. The frequency and duration of wet extremes are projected to increase over South America and Antarctica, whereas changes in dry days and the longest dry spell vary with regions. Further Antarctic sea ice loss under a quadrupling of CO₂ leads to similar but larger changes. Comparison between the coupled and atmosphere-only model experiments suggests that ocean dynamics and their interactions with the atmosphere induced by Antarctic sea ice loss play a key role in driving the identified changes in temperature and precipitation extremes over southern continents. By comparing with global warming experiments, we find that Antarctic sea ice loss may affect temperature and precipitation extremes for some regions under greenhouse warming, especially Antarctica.

Abstract

Decadal trends are compared in various fields between Northern Hemisphere early winter, November–December (ND), and late-winter, February–March (FM), months using reanalysis data. It is found that in the extratropics and polar region the decadal trends display nearly opposite tendencies between ND and FM during the period from 1979 to 2003. Dynamical trends in late winter (FM) reveal that the polar vortex has become stronger and much colder and wave fluxes from the troposphere to the stratosphere are weaker, consistent with the positive trend of the Arctic Oscillation (AO) as found in earlier studies, while trends in ND appear to resemble a trend toward the low-index polarity of the AO. In the Tropics, the Hadley circulation shows significant intensification in both ND and FM, with stronger intensification in FM. Unlike the Hadley cell, the Ferrel cell shows opposite trends between ND and FM, with weakening in ND and strengthening in FM. Comparison of the observational results with general circulation model simulations is also discussed.

Abstract

Sea surface temperature (SST) forecast products from the NCEP Climate Forecast System (CFSv2) that are widely used in climate research and prediction have nonstationary bias. In this study, we develop single- (ANN1) and three-hidden-layer (ANN3) neural networks and examine their ability to correct the SST bias in the NCEP CFSv2 extended seasonal forecast starting from July in the extratropical Northern Hemisphere. Our results show that the ensemble-based ANN1 and ANN3 can reduce the uncertainty associated with parameters assigned initially and dependence on random sampling. Overall, ANN1 reduces RMSE of the CFSv2 forecast SST substantially by 0.35°C (0.34°C) for the testing (training) data and ANN3 further reduces RMSE relatively by 0.49°C (0.47°C). Both the ensemble-based ANN1 and ANN3 can significantly reduce the spatially and temporally varying bias of the CFSv2 forecast SST in the Pacific and Atlantic Oceans, and ANN3 shows better agreement with the observation than that of ANN1 in some subregions.

Abstract

Sea ice variability in the North Pacific and its associations with the east Asia–North Pacific winter climate were investigated using observational data. Two dominant modes of sea ice variability in the North Pacific were identified. The first mode features a dipole pattern between the Sea of Okhotsk and the Bering Sea. The second mode is characterized by more uniform ice changes throughout the North Pacific.

Using the principal components of the two dominant modes as the indices (PC1 and PC2), analyses show that the positive phases of PC1 feature a local warming (cooling) in the Sea of Okhotsk (the Bering Sea), which is associated with the formation of the anomalous anticyclone extending from the northern Pacific to Siberia, accompanied by a weakening of the east Asian jet stream and trough. The associated anomalous southeasterlies/easterlies reduce the climatological northwesterlies/westerlies, leading to warm and wet conditions in northeast China and central Siberia. The positive phases of PC2 are characterized by a strong local warming in the northern Pacific that coincides with the anomalous cyclone occupying the entire North Pacific, accompanied by a strengthening of the east Asia jet stream and trough. The associated anomalous northerlies intensify the east Asian winter monsoon (EAWM), leading to cold and dry conditions in the east coast of Asia. The intensified EAWM also strengthens the local Hadley cell, which in turn strengthens the east Asian jet stream and leads to a precipitation deficit over subtropical east Asia. The linkages between PC1 and PC2 and large-scale modes of climate variability were also discussed. It is found that PC1 is a better indicator than the Arctic Oscillation of the recent Siberian warming, whereas PC2 may be a valuable predictor of EAWM.

Abstract

The Arctic has experienced rapid changes in recent decades. For the first time, we intercompare five snow mass budget processes over Arctic sea ice simulated by 22 models from the Coupled Model Intercomparison Project phase 6 (CMIP6) using new diagnostics that have not been available for previous CMIPs. Our analysis suggests that snowfall accumulation (melt) is the dominant process contributing to nearly 100% (70.4% ± 10.1%) of the annual snow growth (loss). Snow mass change through sea ice dynamics, snow–ice conversion, and sublimation contribute 10.9% ± 4.9%, 9.7% ± 5.9%, and 9.0% ± 7.7% to the total snow mass loss. The seasonal cycle of various snow processes simulated by most of the CMIP6 models generally follows similar variations. There is reduced snowfall accumulation, melt, and sea ice dynamics during 1993–2014. However, substantial temporal and spatial discrepancies are noteworthy between the CMIP6 models. There is a large spread of snowfall accumulation and snowmelt in summer and fall, snow–ice conversion from autumn to spring, sublimation in late spring and summer, and snow mass change due to sea ice dynamics from winter to midspring. About half the models show decreasing trends of snowfall accumulation during 1993–2014, with no trends in others. Divergent trends in snow–ice conversion and sublimation occur in the Greenland and Barents Seas. The discrepancies are attributed equally to internal variability and model structural differences. Future projections that remove the identified outlier models suggest a significant reduction in snowfall accumulation, snowmelt, and snow mass change due to sea ice dynamics in the Arctic Ocean from 2015 to 2099. Snow–ice conversion and sublimation are also projected to be reduced but with less confidence.