Search for: All records

Abstract Following the interdecadal shift of El Niño–Southern Oscillation (ENSO) properties that occurred in 1976/77, another regime shift happened in 1999/2000 that featured a decrease of variability and an increase in ENSO frequency. Specifically, the frequency spectrum of Niño-3.4 sea surface temperature shifted from dominant variations at quasi-quadrennial (~4 yr) periods during 1979–99 to weaker fluctuations at quasi-biennial (~2 yr) periods during 2000–18. Also, the spectrum of warm water volume (WWV) index had almost no peak in 2000–18, implying a nearly white noise process. The regime shift was associated with an enhanced zonal gradient of the mean state, a westward shift in the atmosphere–ocean coupling in the tropical Pacific, and an increase in the static stability of the troposphere. This shift had several important implications. The whitening of the subsurface ocean temperature led to a breakdown of the relationship between WWV and ENSO, reducing the efficacy of WWV as a key predictor for ENSO and thus leading to a decrease in ENSO prediction skill. Another consequence of the higher ENSO frequency after 1999/2000 was that the forecasted peak of sea surface temperature anomaly often lagged that observed by several months, and the lag increased with the lead time. The ENSO regime shift may have altered ENSO influences on extratropical climate. Thus, the regime shift of ENSO in 1999/2000 as well as the model default may account for the higher false alarm and lower skill in predicting ENSO since 1999/2000. 

Analyzing a long simulation and a set of seasonal reforecasts of the Climate Forecast System version 2 (CFSv2), this study demonstrates a large model cold bias in the deep soil layer (100–200 cm) over most of North America continent during summer due to weaker seasonal change in summer. The summer subsurface temperature (SUBT) cold bias influences the land surface temperature (LST) during the summer and subsequent seasons in different ways over different geographical regions in North America: West of the Rocky Mountains, the SUBT's effect on LST is largely overruled by the stronger upstream marine influence from the Pacific. Over the central Great Plains, however, it is a major cause for severe cold LST bias during summer in the model simulation and reforecasts. As a result, model underestimates sensible heat flux into the atmosphere but overestimates latent heat flux. The latter may contribute to an excessive summer rainfall in the region. Over the northeast region, the SUBT cold bias persists to August and September, which causes an additional surface cooling in the fall and helps to bring LST to the freezing point early. This sets up the stage for a prolonged snow‐albedo feedback. In particular, the model long simulation that passes through previous summer and fall demonstrates longer persistence of snow cover over the northeast region than reforecasts initialized in late winter and spring do. A cold bias of the water temperature in the North Atlantic seems also to play a role to prolong cold bias in the northeast region.

 

Based on observational data, this work examines the multi-time-scale feature of the sea surface temperature (SST) variability averaged in the whole North Atlantic Ocean (to be referred to as NASST), as well as its time-scale-dependent connections with El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Traditionally, the NASST index is used to characterize the SST trend and multidecadal variability in the North Atlantic. This study found that superimposed on a prominent long-term trend, NASST is nonnegligible at subannual and interannual time scales, compared with that at decadal to multidecadal time scales. Spatially, the interannual variation of NASST is characterized by a horseshoe-like pattern of the SST anomaly (SSTA) in the North Atlantic. It is mainly a lagged response to ENSO through the atmospheric bridge, and NAO plays a secondary role. At the subannual time scale, both ENSO and NAO play a role in generating the fluctuations of NASST and a horseshoe-like pattern in the North Atlantic. Nevertheless, both the ENSO- and NAO-driven variations only explain a small fraction of the variances in both the interannual and subannual time scales. Thus, other factors unrelated to ENSO or NAO may play a more important role. The associated thermodynamical processes are similar at the two time scales; however, the dynamical processes have a significant contribution to the subannual component, but not to the interannual component. Thus, the SSTA averaged in the North Atlantic as a whole varies at different time scales and is associated with different mechanisms.

 

This work demonstrates the influence of the initial amplitude of the sea surface temperature anomaly (SSTA) associated with El Niño–Southern Oscillation (ENSO) following its evolutionary phase on the forecast skill of ENSO in retrospective predictions of the Climate Forecast System, version 2. It is noted that the prediction skill varies with the phase of the ENSO cycle. The averaged skill (linear correlation) of Niño-3.4 index is in a range of 0.15–0.55 for the amplitude of Niño-3.4 index smaller than 0.5°C (e.g., initial phase or neutral condition of ENSO), and 0.74–0.93 for the amplitude larger than 0.5°C (e.g., mature condition of ENSO) for 0–6-month lead predictions. The dependence of the prediction skills of ENSO on its phase is linked to the variation of signal-to-noise ratio (SNR). This variation is found to be mainly due to the changes in the amplitude of the signal (prediction of the ensemble mean) during different phases of the ENSO cycle, as the noise (forecast spread among the ensemble members), both in the Niño-3.4 region and the whole Pacific, does not depend much on the Niño-3.4 amplitude. It is also shown that the spatial pattern of unpredictable noise in the Pacific is similar to the predictable signal. These results imply that skillful prediction of the ENSO cycle, either at the initial time of an event or during the transition phase of the ENSO cycle, when the anomaly signal is weak and the SNR is small, is an inherent challenge.

 

This study evaluates the possible influence of the winter surface conditions in Eurasia on the summer circulation over the Asian continent and Indo‐Pacific region. We have analysed multi‐seasonal ensemble reforecasts for 30 years (1979–2008) using the National Centers for Environmental Prediction Climate Forecast System version 2 initialized at the beginning of each month from January to May. It is found that the reforecasts initialized in winter (e.g., February) overestimate the snow cover fraction, depth and water equivalent, as well as surface albedo in the excessively snow‐covered portion of Eurasia from March to June. These biases are generated and perpetuated by a snow‐albedo feedback, leading to excessive upwards shortwave radiation reflected from the overly snow‐covered surface and an intense cold bias from the surface to mid‐troposphere. Originating over land, the cold bias is extended eastwards over the northwestern North Pacific by the advection of prevailing westerly winds. The cold air temperature in the broad mid‐latitude Asian‐Pacific region causes significantly lower geopotential heights at pressure levels in the middle and upper troposphere and thus increases the upper‐level westerly winds on its southern flank over the Asian continent and Indo‐Pacific. A slower than observed snow melting rate helps the winter cold bias persists well into the summer season in these runs. As a result, compared with the reforecasts initialized in spring (e.g., May), winter‐initialized reforecasts feature lower geopotential heights in the upper troposphere over Eurasia and a stronger subtropical jet over the Asian continent and the North Pacific from May to September, especially in early summer. The CFSv2 reforecasts in both sets of cases have too little total cloud fraction over Eurasia during June–August, leading to enhanced downwards shortwave radiation.