ÓÄÊ 551.513

 

 

Î âëèÿíèè êîëåáàíèÿ Ìàääåíà – Äæóëèàíà
íà öèðêóëÿöèþ àòìîñôåðû âî âíåòðîïè÷åñêèõ øèðîòàõ Ñåâåðíîãî ïîëóøàðèÿ

Å.Ñ. Íåñòåðîâ

Ãèäðîìåòåîðîëîãè÷åñêèé íàó÷íî-èññëåäîâàòåëüñêèé öåíòð
Ðîññèéñêîé Ôåäåðàöèè, ã. Ìîñêâà, Ðîññèÿ

nesterov@mecom.ru

 

Äàåòñÿ îáçîð èññëåäîâàíèé, ïîñâÿùåííûõ êîëåáàíèþ Ìàääåíà – Äæóëèàíà (ÊÌÄ) è åãî âëèÿíèþ íà öèðêóëÿöèþ àòìîñôåðû âî âíåòðîïè÷åñêèõ øèðîòàõ Ñåâåðíîãî ïîëóøàðèÿ. Îñíîâíûì ìåõàíèçìîì ðàñïðîñòðàíåíèÿ â àòìîñôåðå ñèãíàëà ÊÌÄ âî âíåòðîïè÷åñêèå øèðîòû ÿâëÿþòñÿ âîëíû Ðîññáè è âîçáóæäàåìûå èìè íèçêî÷àñòîòíûå êîëåáàíèÿ àòìîñôåðíîé öèðêóëÿöèè. Ïîêàçàíî, ÷òî ÷åðåç íåñêîëüêî íåäåëü ïîñëå àêòèâèçàöèè ÊÌÄ èíòåíñèôèöèðóåòñÿ ñåâåðîàòëàíòè÷åñêîå êîëåáàíèå (ÑÀÊ), íî ïðè ýòîì òîëüêî îêîëî ïîëîâèíû ýïèçîäîâ óñèëåíèÿ ÑÀÊ ñâÿçàíû ñ ÊÌÄ. Çèìíèå àíîìàëèè òåìïåðàòóðû âîçäóõà â Ñåâåðíîé Àìåðèêå, Âîñòî÷íîé Åâðîïå è Âîñòî÷íîé Àçèè, ñâÿçàííûå ñ ÊÌÄ, ó÷èòûâàþò ïðèìåðíî 30 % îáùåé èçìåí÷èâîñòè çèìíèõ àíîìàëèé â ýòèõ ðàéîíàõ.

Êëþ÷åâûå ñëîâà: êîëåáàíèå Ìàääåíà – Äæóëèàíà, âîëíû Ðîññáè, âíåòðîïè÷åñêèå øèðîòû, ñåâåðîàòëàíòè÷åñêîå êîëåáàíèå

 

 

The Madden-Julian oscillation effect on atmospheric
circulation in the Northern Hemisphere
extratropical
latitudes

E.S. Nesterov

Hydrometeorological Research Center
of Russian Federation, Moscow, Russia

nesterov@mecom.ru

 

A review of studies on the Madden-Julian oscillation (MJO) and its effect on the atmospheric circulation in the Northern Hemisphere extratropical latitudes is given. The main mechanism of the MJO signal propagation in the extratropical latitudes is Rossby waves and low-frequency oscillations of atmospheric circulation excited by them. It is shown that a few weeks after the activation of MJO, the North Atlantic Oscillation (NAO) intensifies but only about half of the NAO amplification episodes are associated with MJO. Winter air temperature anomalies in North America, Eastern Europe, and East Asia associated with MJO explain about 30% of the total variability of winter anomalies in these regions.

Keywords: Madden-Julian oscillation, Rossby waves, extratropical latitudes, North Atlantic Oscillation

 

Ââåäåíèå

Îáû÷íî â êà÷åñòâå èñòî÷íèêîâ ïðåäñêàçóåìîñòè ñîñòîÿíèÿ àòìîñôåðû âî âíåòðîïè÷åñêèõ øèðîòàõ íà ñåçîííîì ìàñøòàáå ðàññìàòðèâàþò «ìåäëåííûå» âíåøíèå âîçäåéñòâèÿ (òåìïåðàòóðà ïîâåðõíîñòè îêåàíà, õàðàêòåðèñòèêè ìîðñêîãî ëüäà è ñíåæíîãî ïîêðîâà è ò. ä.). Îäíèì èç òàêèõ èñòî÷íèêîâ ÿâëÿþòñÿ ïðîöåññû â òðîïèêàõ, â ÷àñòíîñòè, ÿâëåíèå Ýëü-Íèíüî – Þæíîå êîëåáàíèå (ÝÍÞÊ) è êîëåáàíèå Ìàääåíà – Äæóëèàíà (ÊÌÄ). Èçó÷åíèå ãëîáàëüíîãî îòêëèêà íà ÝÍÞÊ ïîçâîëèëî çàðåãèñòðèðîâàòü âûçâàííûå èì àíîìàëèè òåìïåðàòóðû âîçäóõà è îñàäêîâ, èçìåíåíèÿ òðàåêòîðèé öèêëîíîâ â ñåâåðíîé ÷àñòè Òèõîãî îêåàíà è ò. ä.

Îáíàðóæåíèå ñèãíàëà ÝÍÞÊ â ñðåäíèõ è âûñîêèõ øèðîòàõ çàòðóäíåíî â ñâÿçè ñ ñèëüíûì âëèÿíèåì âíåòðîïè÷åñêîé àòìîñôåðíîé öèðêóëÿöèè íà ãèäðîìåòåîðîëîãè÷åñêèå ïîëÿ. Âìåñòå ñ òåì â íåêîòîðûõ ðàáîòàõ áûëî ïîêàçàíî, ÷òî âëèÿíèå ÝÍÞÊ íà öèðêóëÿöèþ àòìîñôåðû ïðîñëåæèâàåòñÿ äî 60° ñ. ø. â òå÷åíèå 10–20 ìåñÿöåâ [2].  êà÷åñòâå îñíîâíûõ ìåõàíèçìîâ ðàñïðîñòðàíåíèÿ â àòìîñôåðå ñèãíàëà ÝÍÞÊ âî âíåòðîïè÷åñêèå øèðîòû ðàññìàòðèâàþòñÿ âîëíû Ðîññáè è âîçáóæäàåìûå èìè íèçêî÷àñòîòíûå êîëåáàíèÿ àòìîñôåðíîé öèðêóëÿöèè, â òîì ÷èñëå ñåâåðîàòëàíòè÷åñêîå êîëåáàíèå (ÑÀÊ).

Ïîìèìî ÝÍÞÊ, âàæíîé õàðàêòåðèñòèêîé àòìîñôåðíîé öèðêóëÿöèè â òðîïèêàõ ÿâëÿåòñÿ êîëåáàíèå Ìàääåíà – Äæóëèàíà, êîòîðîå ÿâëÿåòñÿ äîìèíèðóþùåé ìîäîé èçìåí÷èâîñòè íà ñóáñåçîííîì ìàñøòàáå. ÊÌÄ îòëè÷àåòñÿ îò äðóãèõ àòìîñôåðíûõ ÿâëåíèé â òðîïèêàõ áîëüøèì ïðîñòðàíñòâåííûì ìàñøòàáîì, õàðàêòåðíûì âðåìåííûì ìàñøòàáîì 30–60 ñóòîê è ðàñïðîñòðàíåíèåì íà âîñòîê íàä Èíäèéñêèì è Òèõèì îêåàíîì ñî ñðåäíåé ñêîðîñòüþ îêîëî 430 êì/ñóò [1].

Èññëåäîâàíèÿ ïîñëåäíèõ ëåò ïîêàçàëè, ÷òî ÊÌÄ îêàçûâàåò âëèÿíèå íà ïîãîäó è êëèìàò çà ïðåäåëàìè òðîïè÷åñêîé îáëàñòè.  ñâÿçè ñ ýòèì ïðîãíîç ÊÌÄ ñòàë ÷àñòüþ îïåðàòèâíîé ïðîäóêöèè â êðóïíûõ ìåòåîðîëîãè÷åñêèõ öåíòðàõ. Ïðîãíîç àíîìàëüíûõ ÿâëåíèé ïîãîäû íà ñóáñåçîííîì ìàñøòàáå ïðåäñòàâëÿåò èíòåðåñ äëÿ ìíîãèõ ïîëüçîâàòåëåé. Ñ öåëüþ ïîâûøåíèÿ ýôôåêòèâíîñòè ïðîãíîçîâ íà ýòîì ìàñøòàáå â ðàìêàõ Âñåìèðíîé ïðîãðàììû èññëåäîâàíèÿ êëèìàòà ñîçäàí ïðîåêò S2S (Sub-seasonal to Seasonal prediction project). Ñëåäóåò îòìåòèòü, ÷òî â ðóññêîÿçû÷íîé íàó÷íîé ëèòåðàòóðå ÿâëåíèå ÊÌÄ îïèñûâàåòñÿ ðåäêî [1–5], âìåñòå ñ òåì â [3] îòìå÷àåòñÿ âîçìîæíîå âëèÿíèå ÊÌÄ íà âíóòðèñåçîííûå êîëåáàíèÿ õàðàêòåðèñòèê àòìîñôåðû â óìåðåííûõ øèðîòàõ Åâðîïû è Àçèè. 

 äàííîé ñòàòüå äàåòñÿ îáçîð èññëåäîâàíèé ïî âëèÿíèþ ÊÌÄ íà öèðêóëÿöèþ àòìîñôåðû âî âíåòðîïè÷åñêèõ øèðîòàõ Ñåâåðíîãî ïîëóøàðèÿ,
è â ÷àñòíîñòè íà ÑÀÊ.

 

Õàðàêòåðèñòèêè êîëåáàíèÿ Ìàääåíà – Äæóëèàíà

Êîëåáàíèå Ìàääåíà – Äæóëèàíà – ýòî îáëàñòü àòìîñôåðíîé êîíâåêöèè â òðîïè÷åñêèõ øèðîòàõ Èíäèéñêîãî è Òèõîãî îêåàíîâ, ñîñòîÿùàÿ
èç ÷åðåäóþùèõñÿ çîí óñèëåííîé è ïîäàâëåííîé êîíâåêöèè. Äëÿ êîëè÷åñòâåííîé õàðàêòåðèñòèêè ÊÌÄ èñïîëüçóåòñÿ èíäåêñ, ñîñòîÿùèé èç äâóõ êîìïîíåíòîâ, ïðåäñòàâëÿþùèõ ïåðâûé è âòîðîé ñîáñòâåííûå âåêòîðû ýìïèðè÷åñêèõ îðòîãîíàëüíûõ ôóíêöèé çíà÷åíèé óõîäÿùåé äëèííîâîëíîâîé ðàäèàöèè è ñêîðîñòè âåòðà íà 200 è 850 ãÏà, îñðåäíåííûõ â ïîëîñå 15° ñ. ø. – 15° þ. ø. [10, 23]. Ïåðâûé êîìïîíåíò õàðàêòåðèçóåò êîððåëÿöèþ ìåæäó êîíâåêòèâíîé àêòèâíîñòüþ â Èíäèéñêîì îêåàíå è â çàïàäíîé ÷àñòè Òèõîãî îêåàíà, âòîðîé – êîíâåêòèâíóþ àêòèâíîñòü íàä Ìîðñêèì Êîíòèíåíòîì (ñì. äàëåå). Ýòè äâå ìîäû ó÷èòûâàþò 27 % îáùåé èçìåí÷èâîñòè êîíâåêöèè.

Îñîáîå ìåñòî â ðàñïðîñòðàíåíèè ÊÌÄ íà âîñòîê çàíèìàåò òàê íàçûâàåìûé Ìîðñêîé Êîíòèíåíò (Maritime Continent), ïîä êîòîðûì ïîäðàçóìåâàåòñÿ îáøèðíûé ðàéîí ìåæäó Èíäèéñêèì è Òèõèì îêåàíîì, âêëþ÷àþùèì Èíäîíåçèéñêèé àðõèïåëàã, îñòðîâà Áîðíåî, Íîâàÿ Ãâèíåÿ, Ôèëèïïèíñêèå îñòðîâà è îêðóæàþùèå ìîðÿ.  ýòîì ðàéîíå ïðîèñõîäèò èíòåíñèâíîå âçàèìîäåéñòâèå îêåàíà è àòìîñôåðû ñ ôîðìèðîâàíèåì áîëüøèõ ïîòîêîâ òåïëà è âëàãè, ÷òî ñóùåñòâåííî âëèÿåò íà èçìåí÷èâîñòü êîíâåêöèè.

 [7] ïîêàçàíî, ÷òî õàðàêòåðèñòèêè ÊÌÄ çíà÷èòåëüíî ìåíÿþòñÿ ïðè ïðîõîæäåíèè íàä Ìîðñêèì Êîíòèíåíòîì (ÌÊ) â çàâèñèìîñòè îò ñåçîíà è îò òîãî, êàê ÊÌÄ ïåðåñåêàåò ÌÊ: ê ñåâåðó èëè ê þãó îò ýêâàòîðà. Ïîñëåäíåå ñâÿçàíî ñ òåì, ÷òî ê þãó îò ýêâàòîðà ñóøà çàíèìàåò áîëüøóþ òåððèòîðèþ, ÷åì ê ñåâåðó, è òàì íàõîäÿòñÿ áîëåå âûñîêèå ãîðû.  [15] îáñóæäàåòñÿ âîïðîñ, ÿâëÿåòñÿ ëè ÌÊ áàðüåðîì äëÿ ðàñïðîñòðàíåíèÿ ÊÌÄ íà âîñòîê è ïîä÷åðêèâàåòñÿ íåîáõîäèìîñòü äàëüíåéøåãî ðàçâèòèÿ ìîäåëåé ýâîëþöèè ÊÌÄ â ýòîì ðàéîíå.

Åæåäíåâíóþ àêòèâíîñòü ÊÌÄ ïðèíÿòî äåëèòü íà 8 ôàç ïðîäîëæèòåëüíîñòüþ 7–8 äíåé, êîòîðûå ïðåäñòàâëÿþò òèïè÷íóþ ýâîëþöèþ êîëåáàíèÿ [8,15,21] (ðèñ. 1). Ýòè ôàçû èëè êëàññû ìîæíî èíòåðïðåòèðîâàòü êàê òðîïè÷åñêèå àíàëîãè âíåòðîïè÷åñêèõ ïîãîäíûõ ðåæèìîâ. Íàïðèìåð, ôàçû 2 è 3 õàðàêòåðèçóþò óñèëåííóþ êîíâåêöèþ íàä Èíäèéñêèì îêåàíîì, ôàçû 4 è 5 – íàä Ìîðñêèì Êîíòèíåíòîì, ôàçû 6 è 7 – íàä çàïàäíîé ÷àñòüþ Òèõîãî îêåàíà, ôàçû 1 è 8 – íàä Àôðèêîé è Çàïàäíûì ïîëóøàðèåì. Íåîáõîäèìî îòìåòèòü, ÷òî àêòèâíîñòü ÊÌÄ ìîæåò èñïûòûâàòü çíà÷èòåëüíóþ ìåæãîäîâóþ èçìåí÷èâîñòü ïîä âëèÿíèåì òàêèõ êðóïíîìàñøòàáíûõ ÿâëåíèé êàê ÝÍÞÊ [15].

 

Âëèÿíèå ÊÌÄ íà öèðêóëÿöèþ àòìîñôåðû
âî âíåòðîïè÷åñêèõ øèðîòàõ

 ïóáëèêàöèÿõ ðàññìàòðèâàþòñÿ äâà îñíîâíûõ ìåõàíèçìîâ ðàñïðîñòðàíåíèÿ â àòìîñôåðå ñèãíàëà ÊÌÄ âî âíåòðîïè÷åñêèå øèðîòû. Ïåðâûé – ýòî âîëíû Ðîññáè è âîçáóæäàåìûå èìè íèçêî÷àñòîòíûå êîëåáàíèÿ àòìîñôåðíîé öèðêóëÿöèè, â òîì ÷èñëå ÑÀÊ (ðèñ. 2). Âòîðîé – êîñâåííîå âëèÿíèå âîëí Ðîññáè íà ïðîöåññû â ñòðàòîñôåðå; ïðè ýòîì èçìåíÿåòñÿ ñèëà ïîëÿðíîãî ñòðàòîñôåðíîãî âèõðÿ, ÷òî çàòåì âëèÿåò íà ÑÀÊ.  ÷àñòíîñòè, òàêîé ìåõàíèçì íàáëþäàëñÿ ïðè âíåçàïíûõ ñòðàòîñôåðíûõ ïîòåïëåíèÿõ [14].

 

 

 

 

Ð1

 

 

 

 

Ð2

 

 

 

 

Ð3

 

 

 

 

Ð4

 

 

 

 

Ð5

 

 

 

 

Ð6

 

 

 

 

Ð7

 

 

 

 

Ð8

 

Ðèñ. 1. Êîìïîçèòû æèçíåííîãî öèêëà ÊÌÄ: àíîìàëèè äëèííîâîëíîâîé óõîäÿùåé ðàäèàöèè (Âò/ì2, çàëèâêà) è çîíàëüíîãî êîìïîíåíòà ñêîðîñòè âåòðà íà 850 ãÏà (èçîëèíèè ñ èíòåðâàëîì 0,5 ì/ñ), ðàññ÷èòàííûå äëÿ êàæäîé èç
8 ôàç ÊÌÄ (Ð1-Ð8) çà 1981-2013 ãã. 
[15].

Fig. 1. MJO life cycle composite maps for outgoing longwave radiation (Wm-2, shading) and 850-hPa zonal wind (contour interval is 0.5 ms-1) anomalies calculated for each of the eight MJO phases (P1–P8) for all season from 1981 to 2013 [15].

 

Ðèñ. 2. Àíîìàëèè ãåîïîòåíöèàëà (Í-ïîëîæèòåëüíûå, L-îòðèöàòåëüíûå), âûçâàííûå ÊÌÄ (óñèëåííîé êîíâåêöèåé â Èíäèéñêîì îêåàíå è ïîäàâëåííîé êîíâåêöèåé â çàïàäíîé ÷àñòè Òèõîãî îêåàíà). Îðàíæåâûå ëèíèè – ëîêàëüíàÿ öèðêóëÿöèÿ Õýäëè íàä Èíäèéñêèì îêåàíîì è Âîñòî÷íîé Àçèåé. Êðàñíûå è ñèíèå ëèíèè – òðàåêòîðèè âîëí Ðîññáè, äîñòèãàþùèå Ñåâåðíîé Àìåðèêè è Âîñòî÷íîé Åâðîïû, ñîîòâåòñòâåííî. Êðàñíûå è ñèíèå èçîãíóòûå ñòðåëêè – àäâåêöèÿ òåïëà íà Ñåâåðíóþ Àìåðèêó è àäâåêöèÿ õîëîäà íà Âîñòî÷íóþ Åâðîïó, ñîîòâåòñòâåííî [21].

Fig. 2. Geopotential height anomalies (H-positive, L-negative) are forced by MJO-enhanced convection over the Indian Ocean and suppressed convection over the western Pacific. The local Hadley circulation is shown as the orange lines over the Indian Ocean and East Asia, accordingly. The Rossby wave trajectories reaching North America are denoted as a red lines and reaching East Europe are denoted as a blue lines. Warm advection over North America is denoted as a red curved arrows, and cold advection over East Europe is denoted as a blue curved arrows [21].

 

Âûïîëíåííûå â [14] ÷èñëåííûå ýêñïåðèìåíòû ïîêàçàëè, ÷òî ïðè àêòèâèçàöèè ÊÌÄ ÷åðåç íåñêîëüêî íåäåëü ïðîèñõîäèò ïîâûøåíèå ïðèìåðíî íà 70 % ÷àñòîòû âîçíèêíîâåíèÿ ôàç ÑÀÊ. Äëÿ óòî÷íåíèÿ ðîëè ÊÌÄ â ôîðìèðîâàíèè ÑÀÊ âñå ýïèçîäû ÑÀÊ áûëè ðàçäåëåíû íà äâå êàòåãîðèè: 1) êîòîðûì ïðåäøåñòâîâàëà èíòåíñèôèêàöèÿ ÊÌÄ; 2) êîòîðûå íå ñâÿçàíû ñ ÊÌÄ. Ýïèçîäîì ñ÷èòàëñÿ ñëó÷àé, åñëè ïîäðÿä òðè è áîëåå ñóòîê èíäåêñ ÑÀÊ áûë áîëüøå îäíîãî ñòàíäàðòíîãî îòêëîíåíèÿ. Ïî ñóòî÷íûì äàííûì ïðèçåìíîãî äàâëåíèÿ çà äåêàáðü-ôåâðàëü 1979-2006 ãã. áûë âûäåëåí 31 ýïèçîä ñ ïîëîæèòåëüíîé ôàçîé ÑÀÊ è 24 ýïèçîäà ñ îòðèöàòåëüíîé ôàçîé.  ðåçóëüòàòå îêàçàëîñü, ÷òî òîëüêî îêîëî 50 % ýïèçîäîâ ÑÀÊ áûëè ñâÿçàíû ñ ÊÌÄ.

 [16, 17] óñòàíîâëåíà ñòàòèñòè÷åñêè çíà÷èìàÿ ñâÿçü ìåæäó ÊÌÄ è ÑÀÊ. Âûÿâëåíî, ÷òî ïðîèñõîäèò çíà÷èòåëüíîå óñèëåíèå ïîëîæèòåëüíîé (îòðèöàòåëüíîé) ôàçû ÑÀÊ ÷åðåç 5–15 ñóòîê ïîñëå òîãî êàê ïîäàâëåííàÿ (óñèëåííàÿ) êîíâåêöèÿ, ñâÿçàííàÿ ñ ÊÌÄ, äîñòèãàåò òðîïè÷åñêîé çîíû öåíòðàëüíîé ÷àñòè Òèõîãî îêåàíà. Íà îñíîâå ãëîáàëüíîé ìîäåëè âûïîëíåíû ïðîãíîçû ÑÀÊ çèìîé íà 45 äíåé â 1985–2008 ãã.

Òàêæå ïîêàçàíî, ÷òî ïðîãíîç ÑÀÊ ñ çàáëàãîâðåìåííîñòüþ îäèí ìåñÿö áîëåå óñïåøåí â òîì ñëó÷àå, åñëè íà÷àëüíûé ñèãíàë ÊÌÄ äîñòàòî÷íî ñèëüíûé. Óñïåøíîñòü ïðîãíîçà ÑÀÊ òàêæå çàâèñèò îò ôàçû ÊÌÄ â íà÷àëüíûé ïåðèîä. Íàèëó÷øèå ïðîãíîçû ïîëó÷åíû, åñëè â íà÷àëüíûõ óñëîâèÿõ ó÷èòûâàëèñü ôàçû 2, 3, 6, 7. Ýòî îçíà÷àåò, ÷òî ïðîãíîç áîëåå óñïåøåí, åñëè â íà÷àëå ñóùåñòâóåò çîíàëüíûé äèïîëü ñ óñèëåííîé êîíâåêöèåé â âîñòî÷íîé ÷àñòè Èíäèéñêîãî îêåàíà è ïîäàâëåííîé êîíâåêöèåé â çàïàäíîé ÷àñòè Òèõîãî îêåàíà (èëè íàîáîðîò), ÷åì åñëè åñòü òîëüêî îäèí öåíòð êîíâåêöèè íàä Ìîðñêèì Êîíòèíåíòîì.

Ñòàòèñòè÷åñêàÿ ìîäåëü äëÿ îöåíêè ïîòåíöèàëüíîé ïðåäñêàçóåìîñòè èíäåêñà ÑÀÊ èëè çíàêà ôàçû ÑÀÊ áûëà ðàçðàáîòàíà â [8].  êà÷åñòâå ïðåäèêòîðà èñïîëüçîâàëèñü õàðàêòåðèñòèêè ïðåäøåñòâóþùåé ôàçû ÊÌÄ. Âûïîëíåííûå ïðîãíîçû áûëè óñïåøíû â ~70 % ñëó÷àåâ.

Ïîìèìî ïðîãíîçà ÑÀÊ, õàðàêòåðèñòèêè ÊÌÄ èñïîëüçîâàëèñü òàêæå äëÿ ïðîãíîçîâ â äðóãèõ ðåãèîíàõ.  [21] áûëî ðàññìîòðåíî âëèÿíèå ÊÌÄ íà òðè ðàéîíà: Ñåâåðíàÿ Àìåðèêà, Âîñòî÷íàÿ Åâðîïà è Âîñòî÷íàÿ Àçèÿ. Ïîëó÷åíî, ÷òî àíîìàëèè òåìïåðàòóðû âîçäóõà (ÒÂ), ñâÿçàííûå ñ ÊÌÄ, ó÷èòûâàþò ïðèìåðíî 30 % îáùåé èçìåí÷èâîñòè çèìíèõ àíîìàëèé â ýòèõ ðàéîíàõ. Îòðèöàòåëüíûå àíîìàëèè Ò â Âîñòî÷íîé Åâðîïå íà÷èíàþò ðàçâèâàòüñÿ, åñëè óñèëåííûé íàãðåâ ïðè êîíâåêöèè ðàñïîëîæåí â öåíòðàëüíîé ÷àñòè Èíäèéñêîãî îêåàíà (ôàçà 2). Îñíîâíûì ìåõàíèçìîì ÿâëÿåòñÿ ãîðèçîíòàëüíàÿ àäâåêöèÿ òåìïåðàòóðû, ñâÿçàííàÿ ñ âîëíàìè Ðîññáè, âîçáóæäåííûìè ÊÌÄ. Ìàêñèìóì îòðèöàòåëüíîé àíîìàëèè Ò âîçíèêàåò ÷åðåç 10–15 äíåé ïîñëå èíòåíñèôèêàöèè ÊÌÄ.

Âàæíûé âûâîä ýòîé ðàáîòû ñîñòîèò â òîì, ÷òî õîòÿ âî ìíîãèõ èññëåäîâàíèÿõ ïîêàçàíî ñóùåñòâåííîå âëèÿíèå àðêòè÷åñêîãî êîëåáàíèÿ, óìåíüøåíèÿ ïëîùàäè ëüäà â àðêòè÷åñêèõ ìîðÿõ è ñíåæíîãî ïîêðîâà Åâðàçèè íà ýêñòðåìàëüíî õîëîäíûå çèìû âî âíåòðîïè÷åñêèõ øèðîòàõ Ñåâåðíîãî ïîëóøàðèÿ, ÊÌÄ òàêæå ÿâëÿåòñÿ ïîòåíöèàëüíûì èñòî÷íèêîì ïðåäñêàçóåìîñòè ýòèõ ÿâëåíèé.

Èññëåäîâàíèå âëèÿíèÿ ÊÌÄ íà òåìïåðàòóðíûé ðåæèì âíåòðîïè÷åñêèõ øèðîò Ñåâåðíîãî ïîëóøàðèÿ òàêæå ïîêàçàëî, ÷òî â õîëîäíóþ ÷àñòü ãîäà (íîÿáðü – àïðåëü) â ðåçóëüòàòå àêòèâèçàöèè ÊÌÄ ÷àñòîòà ýêñòðåìóìîâ òåìïåðàòóðû âîçäóõà âîçðàñòàåò â äâà ðàçà ïî ñðàâíåíèþ ñ íåàêòèâíûìè ïåðèîäàìè ÊÌÄ [19]. Äåëàåòñÿ âûâîä, ÷òî ó÷åò âëèÿíèÿ ÊÌÄ â ïðîãíîñòè÷åñêèõ ìîäåëÿõ âàæåí äëÿ çàáëàãîâðåìåííîãî ïðåäóïðåæäåíèÿ îá ýêñòðåìàëüíûõ òåìïåðàòóðàõ.

Èíòåðåñíîå èññëåäîâàíèå ñîâìåñòíîãî âëèÿíèÿ ÊÌÄ è ÝÍÞÊ
íà ÷àñòîòó âîçíèêíîâåíèÿ áëîêèíãà â âûñîêèõ øèðîòàõ âûïîëíåíî â [12]. Ïîêàçàíî, ÷òî â ïåðèîä Ýëü-Íèíüî ïðîèñõîäèò óâåëè÷åíèå ÿâëåíèé
áëîêèíãà â Òèõîì è Àòëàíòè÷åñêîì îêåàíàõ âñëåä çà ôàçîé 7 ÊÌÄ,
õàðàêòåðèçóþùåéñÿ ïîâûøåííîé êîíâåêöèåé íàä âîñòî÷íîé ÷àñòüþ Èíäèéñêîãî îêåàíà è ïîäàâëåííîé êîíâåêöèåé íàä çàïàäíîé ÷àñòüþ Òèõîãî îêåàíà.  Ñóùåñòâåííîå óìåíüøåíèå áëîêèíãà ïðîèñõîäèò âñëåä çà ôàçîé 3, êîãäà êîíâåêöèÿ íàä âîñòî÷íîé ÷àñòüþ Èíäèéñêîãî îêåàíà ïîäàâëåíà, à íàä çàïàäíîé ÷àñòüþ Òèõîãî îêåàíà óñèëåíà. Âëèÿíèå ÊÌÄ íà ôîðìèðîâàíèå áëîêèíãà íàä Ñåâåðíîé Àòëàíòèêîé è Åâðîïîé áûëî òàêæå âûÿâëåíî â
[9].

 [24] ïîêàçàíî, ÷òî ÊÌÄ ñóùåñòâåííî âëèÿåò íà ïîãîäó â Ñåâåðíîé Àìåðèêå íà âíóòðèñåçîííîì ìàñøòàáå. Âûÿâëåí ìåðèäèîíàëüíûé ñäâèã øòîðì-òðåêà, ñâÿçàííûé ñ ÊÌÄ, ñ êîòîðûì, â ñâîþ î÷åðåäü, ñâÿçàíû àíîìàëèè òåìïåðàòóðû âîçäóõà è îñàäêîâ â ðàçëè÷íûõ ðåãèîíàõ Ñåâåðíîé Àìåðèêè. Íà âîçíèêíîâåíèå ñäâèãà ïîâëèÿëè öåïî÷êè âîëí Ðîññáè, âîçáóæäåííûå àíîìàëèÿìè êîíâåêöèè, ñâÿçàííûìè ñ ôàçàìè 3 è 8 ÊÌÄ. Ýòè âîëíîâûå öåïî÷êè, ðàñïðîñòðàíÿÿñü ÷åðåç Òèõèé îêåàí è Ñåâåðíóþ Àìåðèêó, âûçûâàþò ìåðèäèîíàëüíûé ñäâèã çàïàäíîãî ñòðóéíîãî òå÷åíèÿ è èçìåíåíèÿ â àêòèâíîñòè øòîðì-òðåêà. Òàêæå íàéäåíî, ÷òî âîëíû Ðîññáè, ñâÿçàííûå ñ ôàçàìè 2 è 6, âëèÿþò íà ïîãîäó çàïàäíîãî ïîáåðåæüÿ Ñåâåðíîé Àìåðèêè.  [11] ïîêàçàíî, ÷òî ÊÌÄ âëèÿåò íå òîëüêî íà øòîðì-òðåê íàä Ñåâåðíîé Àìåðèêîé, íî è íà åãî ïðîäîëæåíèå íàä Ñåâåðíîé Àòëàíòèêîé è Åâðîïîé.

Îòäåëüíî ñëåäóåò îñòàíîâèòüñÿ íà ðàáîòàõ, â êîòîðûõ èññëåäóåòñÿ âëèÿíèå ÊÌÄ íà ïðîöåññû â ñòðàòîñôåðå è, â ÷àñòíîñòè, íà âíåçàïíûå ñòðàòîñôåðíûå ïîòåïëåíèÿ.  [18] èññëåäóåòñÿ âëèÿíèå ÊÌÄ íà ðàçëè÷íûå òèïû ñòðàòîñôåðíûõ ïîòåïëåíèé, ñâÿçàííûõ ñî ñìåùåíèåì èëè ðàñùåïëåíèåì ïîëÿðíîãî âèõðÿ. Âûÿâëåíî, ÷òî ÊÌÄ ñèëüíåå âëèÿåò íà âòîðîé òèï ïîòåïëåíèé âñëåäñòâèå òîãî, ÷òî ïåðåä ýòèì òèïîì ñìåùåíèå îáëàñòè àêòèâíîé êîíâåêöèè â òðîïèêàõ íà âîñòîê âûðàæåíî íàèáîëåå çíà÷èòåëüíî.  [20] óñòàíîâëåíî, ÷òî áîëåå ÷åì ïîëîâèíå ñòðàòîñôåðíûõ ïîòåïëåíèé ïðåäøåñòâîâàëè ôàçû 6 è 7 ÊÌÄ.

 

×èñëåííîå ìîäåëèðîâàíèå âëèÿíèÿ ÊÌÄ
íà öèðêóëÿöèþ àòìîñôåðû

Ñïîñîáíîñòü ìîäåëåé ïðîãíîçèðîâàòü ÊÌÄ è åãî âëèÿíèå íà âíåòðîïè÷åñêèå øèðîòû èññëåäîâàëîñü â ïðîåêòå S2S íà îñíîâå äàííûõ çà 1999–2010 ãã. [22]. Ïîëó÷åíî, ÷òî ìîäåëè, ó÷àñòâóþùèå â ïðîåêòå S2S, ñïîñîáíû ïðîãíîçèðîâàòü ÊÌÄ íà ñðîê îò äâóõ äî ÷åòûðåõ íåäåëü.  ñîîòâåòñòâèè ñ äàííûìè ðåàíàëèçà ERA-Interim ìîäåëè âîñïðîèçâîäÿò óâåëè÷åíèå âåðîÿòíîñòè âîçíèêíîâåíèÿ ïîëîæèòåëüíîé ôàçû ÑÀÊ âñëåä çà àêòèâèçàöèåé ÊÌÄ íàä Èíäèéñêèì îêåàíîì è îòðèöàòåëüíîé ôàçû ÑÀÊ âñëåä çà àêòèâèçàöèåé ÊÌÄ íàä çàïàäíîé ÷àñòüþ Òèõîãî îêåàíà. Íî ïðè ýòîì â Àòëàíòèêî-Åâðîïåéñêîì ðåãèîíå ìîäåëè äàþò çíà÷èòåëüíî áîëåå ñëàáûé îòêëèê íà ÊÌÄ, ÷åì ïî äàííûì ðåàíàëèçà. Íåîáõîäèìî îòìåòèòü, ÷òî ïðîãíîçû ÊÌÄ áîëåå óñïåøíû â çèìíèé ïåðèîä, ïîñêîëüêó â ýòî âðåìÿ ñèãíàë ÊÌÄ âûðàæåí ñèëüíåå, ÷åì ëåòîì [15].

Ïðîáëåìû ìîäåëèðîâàíèÿ ÊÌÄ èññëåäîâàëèñü òàêæå â ïðîåêòå CMIP5 (Coupled Model Intercomparison Project phase 5) [6, 13]. Îòìå÷àåòñÿ, ÷òî áîëüøèíñòâî ìîäåëåé, ó÷àñòâóþùèõ â ïðîåêòå, çàíèæàþò àìïëèòóäó ÊÌÄ, îñîáåííî êîãäà äëÿ îöåíêè èñïîëüçóåòñÿ óõîäÿùàÿ äëèííîâîëíîâàÿ ðàäèàöèÿ, è åñòü ïðîáëåìû â âîñïðîèçâåäåíèè êîãåðåíòíîñòè ìåæäó ðàñïðîñòðàíåíèåì íà âîñòîê îáëàñòè êîíâåêöèè/îñàäêîâ è ïîëåì âåòðà. Òàêæå åñòü òðóäíîñòè â ìîäåëèðîâàíèè âëèÿíèÿ ÊÌÄ íà êðóïíîìàñøòàáíûå êîëåáàíèÿ öèðêóëÿöèè àòìîñôåðû (òåëåñâÿçè).

Âìåñòå ñ òåì â [21] äåëàåòñÿ îïòèìèñòè÷íûé âûâîä, ÷òî àíîìàëèè òåìïåðàòóðû âîçäóõà, ñâÿçàííûå ñ ÊÌÄ, ìîãóò áûòü ïðåäñêàçàíû ñ çàáëàãîâðåìåííîñòüþ 10–20 äíåé. Ñ ó÷åòîì òîãî, ÷òî ñîâðåìåííûå ìîäåëè îêåàí-àòìîñôåðà â Åâðîïåéñêîì öåíòðå ñðåäíåñðî÷íûõ ïðîãíîçîâ ïîãîäû è â Ñëóæáå ïîãîäû ÑØÀ ìîãóò ïðåäñêàçûâàòü ÊÌÄ ñ çàáëàãîâðåìåííîñòüþ 20–30 äíåé, ìîæíî îæèäàòü, ÷òî çàáëàãîâðåìåííîñòü ïðîãíîçà êðóïíûõ àíîìàëèé òåìïåðàòóðû âîçäóõà âî âíåòðîïè÷åñêèõ øèðîòàõ äîñòèãíåò 30–45 äíåé.

 

Çàêëþ÷åíèå

 ðàçëè÷íûõ èññëåäîâàíèÿõ ïîêàçàíî, ÷òî êîëåáàíèå Ìàääåíà – Äæóëèàíà âëèÿåò íà öèðêóëÿöèþ àòìîñôåðû âî âíåòðîïè÷åñêèõ øèðîòàõ Ñåâåðíîãî ïîëóøàðèÿ.  ÷àñòíîñòè, âûÿâëåíî, ÷òî ÷åðåç íåñêîëüêî íåäåëü ïîñëå àêòèâèçàöèè ÊÌÄ èíòåíñèôèöèðóåòñÿ ñåâåðîàòëàíòè÷åñêîå êîëåáàíèå, íî ïðè ýòîì òîëüêî îêîëî ïîëîâèíû ýïèçîäîâ óñèëåíèÿ ÑÀÊ ñâÿçàíû ñ ÊÌÄ. Çèìíèå àíîìàëèè òåìïåðàòóðû âîçäóõà â Ñåâåðíîé Àìåðèêå, Âîñòî÷íîé Åâðîïå è Âîñòî÷íîé Àçèè, ñâÿçàííûå ñ ÊÌÄ, ó÷èòûâàþò ïðèìåðíî 30 % îáùåé èçìåí÷èâîñòè çèìíèõ àíîìàëèé â ýòèõ ðàéîíàõ. Åñòü ïðîãðåññ â ìîäåëèðîâàíèè âëèÿíèÿ ÊÌÄ íà ôîðìèðîâàíèå àíîìàëèé òåìïåðàòóðû âîçäóõà âî âíåòðîïè÷åñêèõ øèðîòàõ.

 

Ñïèñîê ëèòåðàòóðû

1. Ãóùèíà Ä.Þ., Äåâèòò Á. ßâëåíèå Ýëü-Íèíüî è åãî âëèÿíèå íà ïðîöåññû â àòìîñôåðå è îêåàíå // Òðóäû ÃÎÈÍ. 2016. Âûï. 217. Ñ. 184-208.

2. Æåëåçíîâà È.Â., Ãóùèíà Ä.Þ. Îòêëèê ãëîáàëüíîé öèðêóëÿöèè àòìîñôåðû íà äâà òèïà Ýëü-Íèíüî // Ìåòåîðîëîãèÿ è ãèäðîëîãèÿ. 2015. ¹ 3. Ñ. 36-50.

3. Èâàíîâ Â.Í., Ñòåðèí À.Ì., Õîõëîâà À.Â. Âíóòðèñåçîííûå êîëåáàíèÿ àòìîñôåðû â óìåðåííûõ øèðîòàõ Åâðîïû è Àçèè è èõ ïàðàìåòðû // Ìåòåîðîëîãèÿ è ãèäðîëîãèÿ. 2003. ¹ 5. Ñ. 31-43.

4. Êèêòåâ Ä.Á., Òîëñòûõ Ì.À., Ìèðâèñ Â.Ì. Î ïðåäñêàçóåìîñòè ýêñòðåìàëüíûõ ìåòåîðîëîãè÷åñêèõ ÿâëåíèé íà âðåìåííûõ ìàñøòàáàõ äî ñåçîíà // Ýêñòðåìàëüíûå ïàâîäêè â áàññåéíå ð. Àìóð: ïðè÷èíû, ïðîãíîçû, ðåêîìåíäàöèè.  Ì., 2014. Ñ. 54-66.

5. Ïåòðîñÿíö Ì.À., Ñåìåíîâ Å.Ê., Ãóùèíà Ä.Þ., Ñîêîëèõèíà Å.Â., Ñîêîëèõèíà Í.Í. Öèðêóëÿöèÿ àòìîñôåðû â òðîïèêàõ: êëèìàò è èçìåí÷èâîñòü. Ì.: ÌÀÊÑ Ïðåññ, 2005. 670 ñ.

6. Ahn M., Kim D., Sperber K., Kang I., Maloney E., Waliser D., Hendon H. MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis // Clim. Dyn. 2017. Vol.49, no. 11-12. P. 4023-4045.

7. Burleyson C.D.Hagos S.M., Feng Z., Kerns B.W.J., Kim D. Large-scale environmental characteristics of MJOs that strengthen and weaken over the Maritime Continent // J. Clim. 2018. Vol. 31, no. 14. P. 5731-5748.

8. Cassou C. Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation // Nature. 2008. Vol. 455. P. 523-527.

9. Gollan G., Greatbatch R. The relationship between northern hemisphere winter blocking and tropical modes of variability // J. Clim. 2017. Vol. 30, no. 22. P. 9321-9337.

10. Gottschalck J., Meng J., Rodell M., Houser P. A framework for assessing operational Madden–Julian oscillation forecasts: A CLIVAR MJO working group project // Bull. Amer. Met. Soc. 2010. Vol. 91, no. 9. P.1247-1258.

11. Guo Y., Shinoda T., Lin J., Chang E. K. M. Variations of Northern Hemisphere storm track and extratropical cyclone activity associated with the Madden–Julian oscillation // J. Clim. 2017. Vol. 30, no. 13. P. 4799-4818.

12. Henderson S.A., Maloney E.D. The impact of the Madden–Julian oscillation on high-latitude winter blocking during El Niño–Southern oscillation events // J. Clim. 2018. Vol. 31, no. 13. P. 5293-5318.

13. Henderson S.A., Maloney E.D., Son S.-W. Madden–Julian oscillation Pacific teleconnections: the impact of the basic state and MJO representation in general circulation models // J. Clim. 2017. Vol. 30, no. 12. P. 4567-4587.

14. Jiang Z., Feldstein S.B., Lee S. The relationship between the Madden–Julian Oscillation and the North Atlantic Oscillation // Quart. J. Roy. Met. Soc. 2017. Vol. 143, no. 702. P. 240-250.

15. Kim H-M., Kim D., Vitart F., Toma V.E., Kug J.-S., Webster P.J. MJO Propagation across the Maritime Continent in the ECMWF Ensemble Prediction System // J. Clim. 2016. Vol. 29, no. 11. P. 3973-3988.

16. Lin H., Brunet G., Derome J. An observed connection between the North Atlantic Oscillation and the Madden–Julian Oscillation // J. Clim. 2009. Vol. 22, no. 2. P. 364-380.

17. Lin H., Brunet G., Fontecilla J.S. Impact of the Madden–Julian Oscillation on the intraseasonal forecast skill of the North Atlantic Oscillation // Geophys. Res. Lett. 2010. Vol. 37: L19803. Doi: 10.1029/2010GL044315.

18. Liu C., Tian B., Li K.-F., Manney G.L., Livesey N.J., Yung Y.L., Waliser D.E. Northern hemisphere mid-winter vortex-displacement and vortex-split stratospheric sudden warmings: influence of the Madden–Julian oscillation and quasi-biennial oscillation // J. Geophys. Res. Atmospheres. 2014. Vol. 119, no. 22. P. 12599-12620.

19. Matsueda S., Takaya Y. The global influence of the Madden–Julian Oscillation on extreme temperature events // J. Clim. 2015. Vol. 28, no. 10. P. 4141-4151.

20. Schwartz C., Garfinkel C. Relative roles of the MJO and stratospheric variability in North Atlantic and European winter climate // J. Geophys. Res. Atmospheres. 2017. Vol. 122, no. 8. P. 4184-4201.

21. Seo K-H., Lee H-J., Frierson D.M.W. Unraveling the teleconnection mechanisms that induce wintertime temperature anomalies over the Northern Hemisphere continents in response to the MJO // J. Atm. Sci. 2016. Vol. 73, no. 9. P. 3557-3571.

22. Vitart F. Madden-Julian oscillation prediction and teleconnections in the S2S database // Quart. J. Roy. Met. Soc. 2017. Vol. 143, no. 706. P. 2210-2220.

23. Wheeler M. C., Hendon H. H. An all-season real-time multivariate MJO index: development of an index for monitoring and prediction // Mon. Weath. Rev. 2004. Vol. 132, no. 8. P. 1917-1932.

24. Zheng C., Chang E. K-M., Kim H-M., Zhang M., Wang W. Impacts of the Madden–Julian oscillation on storm-track activity, surface air temperature, and precipitation over North America // J. Clim. 2018. Vol. 31, no. 15. P. 6113-6134.

 

References

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2. Zheleznova I.V., Gushchina D.Yu. The response of global atmospheric circulation to two types of El Niño. Russ. Meteorol. Hydrol., 2015, vol. 40, no. 3, pp. 170-179. DOI: 10.3103/S1068373915030036.

3. Ivanov V. N., Sterin A. M., and Khokhlova A. V. Atmospheric Intraseasonal Oscillations in the Middle Latitudes of Europe and Asia and Their Parameters. Russ. Meteorol. Hydrol., 2003, no. 5, pp. 22-31.

4. Kiktev D.B., Tolstykh M.A., Mirvis V.M O predskazuemosti ehkstremal'nykh meteorologicheskikh yavleniy na vremennykh masshtabakh do sezona. Ehkstremal'nye pavodki v basseyne r. Amur: prichiny, prognozy, rekomendatsii. Moscow, 2014, pp. 54-66. [in Russ.].

5. Petrosyants M.A., Semenov E. K., Gushchina D.Yu., Sokolikhina E. V., Sokolikhina N. N.. Tsirkulyatsiya atmosfery v tropikakh: klimat i izmenchivost'. Moscow, MAKS Press Publ., 2005, 670 p. [in Russ.].

6. Ahn M., Kim D., Sperber K., Kang I., Maloney E., Waliser D., Hendon H. MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis. Clim. Dyn., 2017, vol. 49, no. 11-12, pp. 4023-4045.

7. Burleyson C.D.Hagos S.M., Feng Z., Kerns B.W.J., Kim D. Large-scale environmental characteristics of MJOs that strengthen and weaken over the Maritime Continent. J. Clim., 2018, vol. 31, no. 14, pp. 5731-5748.

8. Cassou C. Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation. Nature, 2008, vol. 455, pp. 523-527.

9. Gollan G., Greatbatch R. The relationship between northern hemisphere winter blocking and tropical modes of variability. J. Clim., 2017, vol. 30, no. 22, pp. 9321-9337.

10. Gottschalck J., Meng J., Rodell M., Houser P. A framework for assessing operational Madden–Julian oscillation forecasts: A CLIVAR MJO working group project. Bull. Amer. Met. Soc., 2010, vol. 91, no. 9, pp.1247-1258.

11. Guo Y., Shinoda T., Lin J., Chang E. K. M. Variations of Northern Hemisphere storm track and extratropical cyclone activity associated with the Madden–Julian oscillation. J. Clim., 2017, vol. 30, no. 13, pp. 4799-4818.

12. Henderson S.A., Maloney E.D. The impact of the Madden–Julian oscillation on high-latitude winter blocking during El Niño–Southern oscillation events. J. Clim., 2018, vol. 31, no. 13, pp. 5293-5318.

13. Henderson S.A., Maloney E.D., Son S.-W. Madden–Julian oscillation Pacific teleconnections: the impact of the basic state and MJO representation in general circulation models. J. Clim., 2017, vol. 30, no. 12, pp. 4567-4587.

14. Jiang Z., Feldstein S.B., Lee S. The relationship between the Madden–Julian Oscillation and the North Atlantic Oscillation. Quart. J. Roy. Met. Soc., 2017, vol. 143, no. 702, pp. 240-250.

15. Kim H-M., Kim D., Vitart F., Toma V.E., Kug J.-S., Webster P.J. MJO Propagation across the Maritime Continent in the ECMWF Ensemble Prediction System. J. Clim., 2016, vol. 29, no. 11, pp. 3973-3988.

16. Lin H., Brunet G., Derome J. An observed connection between the North Atlantic Oscillation and the Madden–Julian Oscillation. J. Clim. 2009, vol. 22, no. 2, pp. 364-380.

17. Lin H., Brunet G., Fontecilla J.S. Impact of the Madden–Julian Oscillation on the intraseasonal forecast skill of the North Atlantic Oscillation. Geophys. Res. Lett., 2010, vol. 37: L19803. DOI: 10.1029/2010GL044315.

18. Liu C., Tian B., Li K.-F., Manney G.L., Livesey N.J., Yung Y.L., Waliser D.E. Northern hemisphere mid-winter vortex-displacement and vortex-split stratospheric sudden warmings: influence of the Madden–Julian oscillation and quasi-biennial oscillation. J. Geophys. Res.
Atmospheres,
2014, vol. 119, no. 22, pp. 12599-12620.

19. Matsueda S., Takaya Y. The global influence of the Madden–Julian Oscillation on
extreme temperature events.
J. Clim., 2015, vol. 28, no. 10, pp. 4141-4151.

20. Schwartz C., Garfinkel C. Relative roles of the MJO and stratospheric variability
in North Atlantic and European winter climate. J. Geophys. Res. Atmospheres., 2017, vol.
122, no. 8, pp. 4184-4201.

21. Seo K-H., Lee H-J., Frierson D.M.W. Unraveling the teleconnection mechanisms that induce wintertime temperature anomalies over the Northern Hemisphere continents in response to the MJO. J. Atm. Sci., 2016, vol. 73, no. 9, pp. 3557-3571.

22. Vitart F. Madden-Julian oscillation prediction and teleconnections in the S2S database. Quart. J. Roy. Met. Soc., 2017, vol. 143, no. 706, pp. 2210-2220.

23. Wheeler M. C., Hendon H. H. An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon. Weath. Rev., 2004, vol. 132, no. 8, pp. 1917-1932.

24. Zheng C., Chang E. K-M., Kim H-M., Zhang M., Wang W. Impacts of the Madden–Julian oscillation on storm-track activity, surface air temperature, and precipitation over North America. J. Clim., 2018, vol. 31, no. 15, pp. 6113-6134.

 

Ïîñòóïèëà â ðåäàêöèþ 25.10.2018 ã.

Received by the editor 25.10.2018.