1. Introduction
It is commonly accepted that the tropics influence teleconnection patterns in the extratropics, especially in the winter hemisphere (e.g., Trenberth et al. 1998; L’Heureux and Thompson 2006; Greatbatch et al. 2012) and also that enhanced skill in the tropics improves the simulation of the extratropical general circulation (e.g., Ferranti et al. 1990; Jung et al. 2010; Gollan et al. 2015). The two dominant modes of tropical variability are El Niño–Southern Oscillation (ENSO; interannual to decadal) and the Madden–Julian oscillation (MJO; intraseasonal to interannual).
In addition to the influence on global teleconnection patterns, ENSO variability has been associated with anomalous blocking characteristics in the North Pacific region (Renwick and Wallace 1996; Wiedenmann et al. 2002; Barriopedro et al. 2006; Hinton et al. 2009; Barriopedro and Calvo 2014). Blocking, on the one hand, has major implications for local surface weather and extreme events (e.g., Trigo et al. 2004; Sillmann and Croci-Maspoli 2009; Greatbatch et al. 2015), but has also been identified in certain regions as a precursor for stratospheric anomalies like sudden warmings (e.g., Garfinkel et al. 2010; Woollings et al. 2010; Ayarzagüena et al. 2015), again allowing for a global impact of blocking. Gollan et al. (2015) have shown that the tropics as a whole significantly influence the interannual and decadal variability of midlatitude blocking frequency over the North Pacific–American and the North Atlantic–European regions and discussed tropical climate modes that exert this influence.
There is general agreement on the teleconnectivity of ENSO in the North Pacific region, warm eastern Pacific El Niño events being associated with an anomalously deep Aleutian low or positive Pacific–North American (PNA) pattern (e.g., Trenberth et al. 1998; Garfinkel and Hartmann 2008), but the influence of ENSO on blocking is less clear. Contradictions in the findings concerning blocking anomalies can result from different definitions of blocking indices, with earlier studies often looking for blocking only around a fixed central latitude [one-dimensional (1D) blocking indices; e.g., Tibaldi and Molteni 1990], while more recent studies identify blocking near the climatological position of the storm track (e.g., Pelly and Hoskins 2003) or everywhere in the extratropics (2D blocking indices; e.g., Schwierz et al. 2004; Scherrer et al. 2006; Berrisford et al. 2007). In addition to this, there are many different flavors of ENSO variability, as, for example, some events can be classified as eastern Pacific or central Pacific (e.g., Garfinkel et al. 2013). Concerning classical, eastern Pacific ENSO, earlier studies found increased blocking in the subtropical northeast Pacific region associated with La Niña (vice versa for El Niño; Renwick and Wallace 1996; Wiedenmann et al. 2002; Barriopedro et al. 2006). On the other hand, Hinton et al. (2009) found, using sensitivity experiments with an atmospheric general circulation model, that cold eastern tropical Pacific sea surface temperature (SST) anomalies associated with La Niña lead to suppressed blocking in the North Pacific region, while warm SST anomalies over the Maritime Continent, also associated with La Niña, promote blocking, a duality that could be the reason for contradictory results concerning the blocking response to ENSO.
While the influence of the MJO on Northern Hemisphere teleconnections, and also some influence on the stratosphere, has been investigated quite extensively (e.g., Cassou 2008; Lin et al. 2009; Garfinkel et al. 2012b; Yoo et al. 2012a,b; Garfinkel et al. 2014; Adames and Wallace 2014; Bao and Hartmann 2014; Lin et al. 2015), the influence of the MJO on blocking has only recently been explored in some detail by a few studies. Gollan et al. (2015) found that enhanced convection over the Maritime Continent (Indian Ocean) associated with the MJO is succeeded by enhanced (decreased) blocking frequency over Europe. Further, the influence of the MJO on Northern Hemisphere winter blocking has recently been explored using reanalysis data by Henderson et al. (2016, hereinafter HMB16). Using a 2D blocking index, HMB16 analyzed anomalous blocking coinciding with (or following) MJO events and found significant changes in all of the Pacific, the Atlantic, and the European sectors. They used the Wheeler and Hendon (2004) MJO index that defines eight different phases, each phase being associated with precipitation anomalies across the tropical regions of the Indian and Pacific Oceans, their alternation describing the eastward propagation of the MJO. HMB16 found that the strongest anomalies in midlatitude blocking for the Pacific and the Atlantic sectors follow MJO phases 3 and 7, blocking frequency being increased after MJO phase 71 and decreased after MJO phase 3.2 The changes in blocking frequency over the Pacific are, according to HMB16, related to the stationary Rossby wave response to the diabatic tropical heating of the MJO, with resulting changes in storm-track propagation and poleward displacement of warm and low potential vorticity (PV) subtropical air (see also Hinton et al. 2009). The Atlantic blocking response found by HMB16 is consistent with changes in the North Atlantic Oscillation (NAO; see Woollings et al. 2008), a positive NAO thereby being associated with suppressed blocking over the northeastern Atlantic, and is also in agreement with earlier studies investigating the impact of the MJO on the NAO (Cassou 2008; Lin et al. 2009) and the northern annular mode (NAM; Zhou and Miller 2005; Yoo et al. 2012a,b). For the European sector HMB16 found the strongest blocking anomalies following MJO phases 4 (decreased blocking) and 6 (enhanced blocking). These authors suggest that, along with the possibility that the increased blocking after MJO phase 6 is a result of the positive NAO (NAO+) response after MJO phase 3 [as also suggested by Cassou (2008)], MJO phase 6 goes along with negative PNA anomalies in the North Pacific region that direct Rossby wave energy toward Europe.
Recently, the authors of the present study have found a major mode of tropical intraseasonal to interannual variability, being associated with the MJO, but also with shifts of the intertropical convergence zone (ITCZ), measured by the upper-tropospheric zonal-mean zonal wind along the equator [
In the present paper, we will expand on the work by HMB16, by using a set of atmospheric general circulation model (AGCM) experiments where the tropics are relaxed toward European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data, but will also use the reanalysis data itself to analyze the impact of ENSO, the MJO, and [
The paper is organized as follows: data and methods are described in section 2; the results regarding the relationship between extratropical blocking frequency and the tropical modes ENSO, MJO, and [
2. Data and methods
a. Reanalysis data and model
Data are used from the 40-yr ECMWF Re-Analysis (ERA-40; Uppala et al. 2005) and ERA-Interim (Dee et al. 2011) for boreal winters [December, January, and February (DJF)] from 1960/61 to 2013/14 for all atmospheric parameters in this paper. The two datasets are combined, by using ERA-40 data until December 1978 and ERA-Interim data thereafter, the combination then being labeled as “ERA.” Sea surface temperature (SST) from the National Oceanographic and Atmospheric Administration’s (NOAA) Extended Reconstructed SST, version 3b (ERSST.v3b), dataset is used to measure ENSO variability. Additionally, we use output from a set of relaxation experiments performed with the ECMWF Integrated Forecast System (IFS; cycle CY40R1) in its atmosphere-only setup in spectral truncation T255 (approximately 80 km), in which the dynamical atmospheric parameters3 are strongly relaxed (at a time scale of 5 h) toward ERA-Interim data within the tropics4 and SST and sea ice are specified to climatology, covering winters 1979/80 to 2013/14 [CLIM-TROPICS; a detailed model description and experimental setup can be found in Hansen et al. (2017)]. Although the freely running ECMWF model has, as most other models, difficulties in simulating a realistic MJO, in CLIM-TROPICS, tropical variability is relaxed toward the reanalysis data, the latter covering the satellite era (starting in 1979), so that the tropical variability, including the MJO, in the relaxation experiment can be assumed to be realistic (see Oliver 2016). The experiment CLIM-TROPICS is then used to investigate the strength of the tropically forced signal by looking at the mean blocking frequency (see section 2b for definition), obtained by averaging blocking frequency from all nine available ensemble members, to (largely) remove internal extratropical variability as represented by the model. This average blocking frequency then defines our ensemble mean, and blocking anomalies shown for CLIM-TROPICS refer to the departure of the ensemble mean from the model climatology, shown in Fig. 1b. The model blocking climatology is similar to the reanalysis climatology apart from common model biases, (i.e, the climatological blocking frequency is reduced in the model by about 20%–30% compared to the reanalysis). We note here that the reduced blocking frequency in the model results mainly from the episode criterion (see below for definition), indicating that blocking in the model is not as persistent as in observations.
DJF mean blocking frequency climatologies (i.e., fraction of all days in DJF that are part of a blocking episode) for (left) ERA and (right) CLIM-TROPICS (CT) relaxation experiment using all model realizations separately. Contour interval is 5%.
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
b. Blocking diagnostic
To test the statistical significance of the blocking composites according to the selected climate indices we perform Monte Carlo tests for each index, shuffling the blocking frequency anomalies in time to create artificial realizations (n = 4000). Thereby, seasons and months are viewed as independent from each other, and for daily blocking frequency, periods of 10 consecutive days from the original data are randomly concatenated (allowing overlap) to create 4000 artificial daily time series of blocking frequency that have the same length as the original data. With these artificial time series of blocking frequency anomalies, composites are computed using the original climate indices. At each grid point we choose the 2.5th and 97.5th percentile of the resulting blocking frequency probability distribution as our significance thresholds.5 This procedure is chosen instead of a Student’s t test because the blocking frequency distribution at many locations is non-Gaussian and also the climate indices may be nonnormal.
c. Definition of climate indices
1) Niño-3.4
As a measure for ENSO variability, we use the DJF seasonal mean Niño-3.4 index, which is the area average of SST anomalies over the region 170° to 120°W and 5°S to 5°N, using the ERSST.v3b dataset here. The mean and standard deviation of the DJF mean Niño-3.4 index for the period 1960/61–2013/14 are 26.6 °C and 1.03 K, respectively.
2) MJO
The daily MJO index, defined by Wheeler and Hendon (2004), is used and was downloaded from the home page of the website of the Australian Bureau of Meteorology.6
This MJO index consists of two components, RMM1 and RMM2, that are the first two principal components from a multivariate empirical orthogonal function (EOF) analysis on tropical zonal wind at 850 and 200 hPa, as well as on outgoing longwave radiation, which is continuously available only during the satellite era after 1979. Before the EOF analysis, the seasonal cycle is removed from all variables. Both indices are normalized by their respective standard deviations, and eight MJO phases are defined by the angle of the vector that is spanned by the two components, while the MJO amplitude is defined as the length of the following vector: |RMM1, RMM2| = [(RMM1)2 + (RMM2)2]½.
3) [
As in Gollan and Greatbatch (2015) we use the zonal-mean zonal wind [U], area averaged between 5°S and 5°N at 150 hPa for DJF monthly means. Because this time series is weakly correlated with the monthly mean Niño-3.4 index, we remove that part of variability that is linearly dependent on the Niño-3.4 index and subsequently remove the seasonal cycle by subtracting from each month the climatological monthly mean, the resulting index being called [
All indices in this study (except the MJO index, which is used as is) are linearly detrended before the analysis to focus on intraseasonal to interannual time scales, although Barnes et al. (2014) point out that the observed trends in blocking frequency are not significant compared to interannual and decadal variability. Also, all indices are normalized, (i.e., the time mean is removed and the resulting index is divided by its standard deviation). Composites are then computed by averaging blocking frequency over months (or days) when the respective index exceeds plus/minus one standard deviation.
3. Relationship between tropical variability and extratropical blocking
a. El Niño–Southern Oscillation
The canonical teleconnection associated with ENSO is the PNA pattern (e.g., Trenberth et al. 1998; Garfinkel and Hartmann 2008), with an anomalously deep (shallow) Aleutian low during El Niño (La Niña) events. Some studies found significantly enhanced (suppressed) blocking during La Niña (El Niño) over the North Pacific, but some of these studies found the signal in the midlatitudes (Renwick and Wallace 1996; Wiedenmann et al. 2002), where our index identifies very few blocking episodes in general (see Fig. 1), and only a more recent study focused on the higher latitudes (Barriopedro and Calvo 2014). However, Hinton et al. (2009) found opposite dipoles in geopotential height over the North Pacific being driven by idealized La Niña–like SST forcing in an AGCM, favoring blocking in the case of warm SST over the Maritime Continent and suppressing blocking in the case of cold SST over the eastern tropical Pacific. Consequently, Hinton et al. (2009) note that the overall impact of ENSO on North Pacific blocking depends on the relative magnitude of the SST anomalies in the two regions during individual events.
Figure 2 shows the seasonal mean blocking frequency anomalies composited according to winters associated with El Niño and La Niña separately, for the reanalysis7 and for the tropical relaxation experiment.8 Different from Barriopedro and Calvo (2014), we find enhanced blocking over the eastern North Pacific (up to 8%) during El Niño winters and decreased blocking over northern Canada/Hudson Bay (up to 8%), very similar in both the reanalysis and the ensemble mean of CLIM-TROPICS, even in terms of the amplitude of the blocking anomalies. It is fairly unusual to see a signal in the ensemble mean being of the same amplitude as in observations,9 giving strong confidence in the signal here. There is also a reduction of blocking frequency (up to 8%) over the western North Pacific and over Siberia during El Niño that, together with the enhanced blocking over the Aleutians, forms a dipole suggesting a northeastward shift of the climatological Siberian blocking peak.
Anomalous blocking frequency composited according to winters (DJF) with anomalous (left) El Niño and (right) La Niña for (top) ERA (1960/61 to 2013/147) and (bottom) CLIM-TROPICS (1979/80 to 2013/148; see text for more details). Red (blue) colors indicate enhanced (decreased) blocking frequency, and contours are drawn every 4% (2%) for ERA (CT), the zero contour being omitted. Plus (circle) symbols indicate significant values [i.e., > (<) the 97.5th (2.5th) percentile according to a Monte Carlo test]. The number of seasons used to calculate the respective composite is given as n in the title of each panel.
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
The blocking anomalies for La Niña conversely indicate reduced blocking frequency over the Aleutians in both the reanalysis and the model but are missing the dipole over the western North Pacific. There is also a weak increase in blocking over the subtropical eastern North Pacific during La Niña, consistent with Renwick and Wallace (1996) and Wiedenmann et al. (2002), but the blocking anomalies are below our lowest plotted contour interval. Therefore, our results emphasize the impact of ENSO on blocking at high latitudes instead of subtropical latitudes. Furthermore, there is a significant decrease in blocking frequency (up to 8%) for La Niña over the western North Atlantic (only in the reanalysis), characteristic of NAO+ (following Woollings et al. 2008), consistent with previous studies (e.g., Brönnimann 2007). Additionally, both the reanalysis and the relaxation experiment indicate slightly increased blocking frequency over central and southern Europe for La Niña winters, possibly related to anticyclonic wave breaking as during NAO+ events.
We note here that the enhanced (suppressed) blocking over the eastern North Pacific during El Niño (La Niña) winters is consistent with the stationary Rossby wave response to ENSO—that is, a deepened and southward-shifted (more shallow and northward shifted) Aleutian low during El Niño (La Niña) that reduces (enhances) the meridional gradient of geopotential height on the northern flank of the anomaly, in line with the argumentation of Hinton et al. (2009) but disagreeing with Barriopedro and Calvo (2014). It might be worth noting that the climatology of the blocking index used by Barriopedro and Calvo (2014; cf. Fig. 4 in Schwierz et al. 2004) differs substantially from the climatology of the blocking index used here (see Fig. 1), a possible explanation for the difference in the ENSO composites.
Enhanced blocking over the eastern North Pacific has been identified as a precursor for stratospheric polar vortex splitting (weakening) events (Martius et al. 2009), whereas northward shifts of blocking over the western North Pacific (as seen here for the model during El Niño) have been identified as precursors of intensified stratospheric polar vortex regimes (Woollings et al. 2010). In the end, sudden stratospheric warming (SSW) frequency [measured by the algorithm of Charlton and Polvani (2007)] is enhanced during both El Niño and La Niña winters in both the reanalysis and in the model,10 consistent with Garfinkel et al. (2012a) and Barriopedro and Calvo (2014). Nevertheless, the increased SSW frequency during ENSO winters does not enhance seasonal mean blocking anomalies over the western North Atlantic as could be inferred from the stratospheric downward influence on the NAO noted by previous studies (e.g., Ineson and Scaife 2009). Woollings et al. (2010) also showed that SSWs are followed by increased blocking over the Pacific basin, potentially offering a positive feedback from the stratosphere supporting the enhanced blocking over the eastern North Pacific seen for El Niño (but not for La Niña).
b. Madden–Julian oscillation
As summarized in the introduction, HMB16 investigated the influence of the MJO on Northern Hemisphere winter blocking. Our analysis is very similar to the analysis by HMB16, although here 1) we use a slightly longer time series of blocking (December 1979 to February 2014 instead of December 1979 to February 2010), 2) we use θPV2 to compute the 2D blocking index instead of 500-hPa geopotential height, and, 3) in addition to the reanalysis data, we also have model output to gain confidence in the results. Furthermore, we add the case of the suppressed MJO to the analysis. Gollan et al. (2015) found that the influence of the MJO on midlatitude blocking is relatively weak on interannual time scales but that on weekly time scales, early (late) MJO phases are associated with weakened (strengthened) blocking over Europe, consistent also with Cassou (2008). Early MJO phases (1–4) correspond to enhanced convection over the Indian Ocean and suppressed convection over the Maritime Continent, while late MJO phases (5–8) correspond to enhanced convection over the Maritime Continent and the western tropical Pacific and suppressed convection over the Indian Ocean. While both Cassou (2008) and HMB16 found the strongest increase in blocking over Europe following MJO phase 6, Cassou (2008) related the increase in blocking after MJO phases 3–4 to the increased occurrence of NAO+ regimes. HMB16 additionally identified a role for a negative PNA pattern prior to the occurrence of MJO phase 6 that redirects Rossby wave energy toward Europe.
We show blocking frequency anomalies averaged over days 8 to 12 (labeled as lag 10 in the following) after the occurrence of each of the eight MJO phases when active (active meaning that |MJO| ≥ 1.5) in Fig. 3 for the reanalysis and in Fig. 4 for CLIM-TROPICS. Time lags 5, 10, and 15 are given for MJO phase 6 in Fig. 5, for the reanalysis only, showing that a 10-day lag is a reasonable time scale for anomalies driven by the MJO to reach the European sector. In the reanalysis, blocking frequency is increased strongly over the western North Atlantic after MJO phase 7, similar to negative NAO-like (NAO−) blocking anomalies (see Woollings et al. 2008). In the model, the NAO− signal is present after all of the MJO phases 6–8, but extending over a smaller region and shifted to the northwest compared to the reanalysis. Furthermore, North Atlantic blocking anomalies following MJO phases 3 and 4 (only phase 3 in the model) are similar to the blocking anomalies associated with NAO+ (i.e., less blocking over the western North Atlantic; see Woollings et al. 2008). These findings are consistent with Cassou (2008), who found the probability for NAO+ (NAO−) to be increased 10 days after the occurrence of MJO phase 3 (phase 6).
(top left to bottom middle) Blocking frequency anomalies averaged over days 8 to 12 (phase 1 to 8) after days that are characterized by the respective MJO phase with sufficient amplitude, |MJO| ≥ 1.5. Red (blue) colors indicate enhanced (decreased) blocking frequency. (bottom right) The respective composite according to a suppressed MJO (|MJO| ≤ 0.25). Winter months (DJF) are used for the period 1979/80–2013/14, while blocking data is from ERA-Interim and the MJO index used is the Wheeler and Hendon (2004) index. Contour interval is 4%, and the number of dates going into the composite (i.e., active MJO of the given phase and suppressed MJO) is given in each panel. Plus (circle) symbols indicate significant values [i.e., > (<) the 97.5th (2.5th) percentile according to a Monte Carlo test].
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
As in Fig. 3, but for CLIM-TROPICS. Blocking anomalies are multiplied by a factor of 2 to give a similar amplitude compared to Fig. 3.
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
As in Fig. 3, but for MJO phase 6 only and for time lags (top)–(bottom) of 5 to 15 days.
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
The findings by Gollan et al. (2015) and HMB16 concerning European blocking are largely confirmed here, as blocking is reduced after an early MJO (after phase 4 in the reanalysis, after phases 2 and 3 in the model), the signal being slightly weaker than in HMB16. In the reanalysis (after phase 4) and in the model (after phase 3), the reduced blocking over Europe goes along with reduced blocking over the North Atlantic extending upstream to the western North Atlantic, where reduced blocking is characteristic of NAO+, as noted above. Furthermore, in the reanalysis, blocking over Europe and the eastern North Atlantic is enhanced after late MJO phases, especially after MJO phase 6, while in the model the increase in blocking over Europe is more confined to southern Europe. The NAO-like increase in blocking over the western North Atlantic following MJO phase 7 occurs after the blocking over Europe associated with MJO phase 6, suggesting that European blocking can induce NAO− regimes upstream. Additionally, blocking frequency is reduced (enhanced) over almost all the Northern Hemisphere after the occurrence of MJO phases 1–3 (phases 6–7), such as one would expect in association with a positive (negative) NAM in both the reanalysis and model. Previous studies on the NAO/NAM found a similar relationship (see discussion in section 4; Zhou and Miller 2005; L’Heureux and Higgins 2008; Yoo et al. 2012a,b; Lin et al. 2015; Dahlke 2015).
We also note here the strong decrease in blocking over the (western) North Pacific following MJO phase 1 and 2 (in both the reanalysis and the model), which coincides with the region where Garfinkel et al. (2014) identified negative sea level pressure anomalies as precursors for SSWs [and, inversely but consistently, Woollings et al. (2010) found intensified polar vortex regimes after enhanced blocking]. Moreover, blocking frequency is increased over the western North Pacific following MJO phase 6 (6 and 7 in the model), consistent with Adames and Wallace (2014) and Bao and Hartmann (2014). These authors point out that, when the MJO heating is centered over the Maritime Continent (like in phase 6), the flanking Rossby waves lead to negative geopotential height anomalies in the central subtropical North Pacific region, decreasing the climatological gradient north of the anomaly. These authors also suggest that the flanking subtropical Rossby waves associated with late-MJO-like heating can induce poleward-propagating wave trains when they reach the climatological jet-exit region. Both facts are consistent with the increased blocking frequency for late MJO phases found here and with decreased blocking frequency for early MJO phases when inverting the sign of the heating.
We also show the blocking frequency anomalies following a suppressed MJO (|MJO| ≤ 0.25)) in the bottom-right panels of Figs. 3 and 4. Suppressed MJO means that precipitation in the tropics is close to climatology that is, in fact, characterized by a zonally asymmetric dipole in the MJO region with strong precipitation over the Maritime Continent and weak precipitation over the western Indian Ocean and Africa (e.g., Adler et al. 2003). While this zonal dipole is known to be an important driver of the tropical circulation and especially of the zonal-mean wind along the equator (see, e.g., Kraucunas and Hartmann 2005), a suppressed MJO leads to easterly anomalies in the zonal-mean zonal wind along the equator, which can itself have an extratropical impact [see Gollan and Greatbatch (2015) and next section]. Associated with a suppressed MJO there is, in the reanalysis, enhanced blocking frequency over central and eastern Europe (up to 12%), while in the model there is slightly decreased blocking over Europe for the suppressed MJO. The blocking anomalies associated with a suppressed MJO in the reanalysis bear slight resemblance to the blocking anomalies associated with MJO phase 6, which is associated with precipitation anomalies that amplify the climatological diabatic heating dipole. The disagreement between reanalysis and model regarding the blocking response to a suppressed MJO suggests that different features of the MJO might have an opposing extratropical impact (see next section).
c. Upper-tropospheric zonal-mean zonal wind along the equator
The monthly mean or seasonal mean upper-tropospheric zonal-mean zonal wind along the equator [
Figure 6 shows the anomalous 2D blocking frequency during months of anomalously westerly and easterly [
Anomalous blocking frequency composited over months (DJF) with anomalously (left) westerly [
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
Over the European sector, blocking frequency is reduced during the westerly phase and slightly enhanced during the easterly phase (over the British Isles, albeit not statistically significant),13 consistent with the findings of Gollan et al. (2015) that seasonal mean blocking over Europe is negatively correlated with [
To investigate the blocking anomalies associated with [
Blocking frequency anomalies composited with respect to (top) westerly and (bottom) easterly anomalies in the daily [
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
As in Fig. 7, but for CLIM-TROPICS. Blocking anomalies are multiplied by a factor of 2 to give a similar amplitude compared to Fig. 7.
Citation: Journal of Climate 30, 22; 10.1175/JCLI-D-16-0742.1
The enhanced blocking over northern Europe associated with easterly [
4. Summary and discussion
Gollan et al. (2015) have shown that the tropics as a whole have a significant impact on boreal winter midlatitude blocking over the Northern Hemisphere. In the present paper, the influence of some tropical modes on mid- and high-latitude blocking has been investigated using a 2D blocking index rather than the 1D index used by Gollan et al. (2015). Results for the combined ERA-40 and ERA-Interim reanalysis data (ERA) were compared with results from a model using relaxation toward ERA-Interim data in the tropics. Our model is the ECMWF seasonal Integrated Forecast System (IFS) in an atmosphere-only setup, where the model is strongly relaxed toward reanalysis data (ERA-Interim; 1979/80–2013/14) within the tropics during the course of the seasonal forecast so that the tropics, including the MJO, in the model are close to observations. The results are summarized briefly in Table 1.
Summary of the statistically significant blocking anomalies associated with the tropical modes under investigation in this study. Subtropical to midlatitudes (sub) are defined as the range 30°–48°N and mid- to high latitudes (high) are defined as the range 48°–72°N. Plus (+) signs indicate enhanced blocking, circles indicate decreased blocking, and Minus (–) signs indicates no change, while no differentiation is made between time scales. Asterisks mark agreement between reanalysis and relaxation experiment, and for the MJO, a signal for early (late) phases has to agree for at least 2 out of phases 1–4 (5–8) to be noted here. Results that contrast with previous results are marked with square brackets, and novel results are marked with curly brackets.
For the warm phase of ENSO (measured here by the DJF mean Niño-3.4 index), an increase in high-latitude blocking frequency over the North Pacific was shown (suppressed blocking for cold ENSO). While this finding is contrary to the findings of Barriopedro and Calvo (2014), the ENSO blocking signal over the North Pacific is underpinned by the model experiment CLIM-TROPICS and also consistent with Hinton et al. (2009). The large-scale circulation response to ENSO, namely, cyclonic anomalies over the North Pacific during El Niño (anticyclonic during La Niña), leads to decreased meridional gradients and higher potential for blocking (increased gradient and suppressed blocking during La Niña) on the northern flank of the anomaly. Over the lower and midlatitudes of the North Pacific, we only find weak and insignificant signals associated with ENSO, indicating enhanced (suppressed) blocking during La Niña (El Niño), agreeing with previous studies in the sign of the anomalies (e.g., Renwick and Wallace 1996; Wiedenmann et al. 2002). The relationship between ENSO and blocking over Europe is weak, although there is some indication for NAO+-like blocking anomalies (see Woollings et al. 2008) during La Niña winters (i.e., decreased blocking over the western North Atlantic and increased blocking over southern Europe). The increased blocking over southern Europe during La Niña is also consistent with enhanced anticyclonic wave breaking during NAO+ (e.g., Martius et al. 2007).
Consistent with HMB16, the MJO is found to have a strong influence on blocking frequency variability all over the Northern Hemisphere. In particular, blocking frequency is decreased over the North Pacific after early MJO phases (1–4), and blocking frequency is increased, especially over Europe, after late MJO phases (5–8). While our results are consistent with HMB16, we use a slightly different blocking index than HMB16 and also show model output that broadly confirms the results from the reanalysis.
Additionally, we investigate the case of a generally suppressed MJO and find, in the reanalysis, a significant increase in blocking frequency, especially over central and eastern Europe, an example of which is the winter of 1962/63 when the MJO was suppressed throughout the winter and a persistent blocking episode occurred over Europe leading to extremely low temperatures (Greatbatch et al. 2015). A suppressed MJO is associated with precipitation close to climatology (i.e., a zonally asymmetric dipole along the equator in the MJO region; e.g., Adler et al. 2003) and easterly [
For [
The decrease in blocking frequency over the northern North Pacific, as found for the easterly phase of [
Overall, our results underline the importance of a realistic representation of tropical dynamics in forecasting and climate models. In particular, a good representation of the MJO on intraseasonal to interannual time scales is important; indeed we have seen here the influence of MJO and [
Acknowledgments
We want to thank three anonymous reviewers for helpful comments that substantially improved the manuscript. Also, many thanks to the ECMWF for the provision of the model used and computer facilities through an ECMWF Special Project. Thanks also to Prof. Dr. Thomas Jung who carried out the model runs reported here. Support from the German Ministry for Education (BMBF) through MiKlip2, subproject 01LP1517D (ATMOS-MODINI), is also gratefully acknowledged, as is support from the GEOMAR Helmholtz Centre for Ocean Research Kiel. Model data used in this paper and script for the calculation of the blocking index are available at http://data.geomar.de.
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MJO phase 7 is associated with enhanced convection over the western tropical Pacific.
MJO phase 3 is associated with enhanced convection over the eastern Indian Ocean.
The dynamical parameters are zonal and meridional wind (u, υ), temperature T, and the logarithm of surface pressure ln(ps).
The relaxation coefficient reduces to zero between 10° and 30°N using a hyperbolic tangent function of latitude.
We do not plot significance on grid points, where the 2.5th and 97.5th percentiles are separated by a blocking frequency of less than 4% (2% for the model).
El Niño winters: 1965/66, 1972/73, 1982/83, 1986/87, 1991/92, 1994/95, 1997/98, 2002/03, and 2009/10. La Niña winters: 1970/71, 1973/74, 1975/76, 1988/89, 1998/99, 1999/2000, 2007/08, and 2010/11.
Only events after 1979/80 apply for the model.
Note that the model anomalies are plotted at only half of the contour interval as the reanalysis anomalies.
Average number of SSWs per winter (DJF) in ERA: 0.68 (El Niño), 0.58 (La Niña), and 0.37 (neutral). In CLIM-TROPICS: 0.86 (El Niño), 0.60 (La Niña), and 0.48 (neutral).
An active MJO, late MJO, or an ITCZ close to the equator favor westerly [
Here, the monthly blocking anomalies refer to the seasonal mean climatology.
Over Europe, the relaxation experiment confirms the reanalysis, the signal only being statistically significant in the case of easterly [
SSWs are measured by the algorithm of Charlton and Polvani (2007).