Spring 2022

Table of Contents: TCC News No. 68
El Niño Outlook (June - December 2022) ....................................................................................................... 1
JMA's Seasonal Numerical Ensemble Prediction for Boreal Summer 2022 ................................................. 4
Summary of the 2021/2022 Asian Winter Monsoon ..................................................................................... 7
TCC and WMC Tokyo co-contributions to Regional Climate Outlook Forums .......................................... 13

El Niño Outlook (June - December 2022)
Atmospheric and oceanic indicators suggest ongoing La Niña conditions in the equatorial Pacific. La Niña conditions
are likely to continue until early boreal summer (70%). It is more likely to transfer to ENSO-neutral (60%) by the end ofsummer than to continue (40%) until boreal autumn (article based on the El Niño outlook issued on 10 June 2022).
1. El Niño/La Niña
In May 2022, the sea surface temperature (SST) for the NINO.3 region was below normal with a deviation of 1.0°C. Equatorial Pacific SSTs were below normal in central to eastern parts (Figures 1-1 and 1-3 (a)). Subsurface
temperatures were above normal in the western part and below normal in the eastern part (Figures 1-2 and 1-3 (b)).
Atmospheric convective activity near the date line over the equatorial Pacific was suppressed compared to the normal,
and easterly winds in the lower troposphere (i.e., trade winds) over the central equatorial Pacific were stronger thannormal. These oceanic and atmospheric conditions are consistent with features commonly seen in past La Niña events,
and indicate that La Niña conditions remain ongoing in the equatorial Pacific.
Subsurface warm waters observed in the western equatorial Pacific are expected to migrate eastward and slightly
increase SSTs in the eastern part in boreal summer. JMA's seasonal Ensemble Prediction System suggests that NINO.3
SSTs will slightly increase in boreal summer and remain around -0.5°C until boreal autumn (Figure 1-4). In conclusion,
La Niña conditions are likely to continue (70%) until early boreal summer. However, it is more likely to transfer to
ENSO-neutral (60%) by the end of summer than to continue (40%) until boreal autumn (Figure 1-5).
2. Western Pacific and Indian Ocean
The area-averaged SST in the tropical western Pacific (NINO.WEST) region was below normal in May. Index values
are likely to be near or below normal until boreal autumn.

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The area-averaged SST in the tropical Indian Ocean (IOBW) region was below normal in May. Index values are likely
to be near or below normal until boreal autumn.
(SATO Hitoshi, Tokyo Climate Center)* The SST normal for the NINO.3 region (5°S – 5°N, 150°W – 90°W) is defined as a monthly average over the latest
sliding 30-year period (1992-2021 for this year).
* The SST normals for the NINO.WEST region (Eq. – 15°N, 130°E – 150°E) and the IOBW region (20°S – 20°N, 40°E –100°E) are defined as linear extrapolations with respect to the latest sliding 30-year period, in order to remove theeffects of significant long-term warming trends observed in these regions.
(a)

(b)

Figure 1-1 Monthly mean (a) sea surface temperatures (SSTs) and (b) SST anomalies in the Indian and Pacific Ocean areas for May 2022
The contour intervals are 1°C in (a) and 0.5°C in (b). The base period for the normal is 1991 – 2020.

(a)

(b)

Figure 1-2 Monthly mean depth-longitude cross sections of (a) temperatures and (b) temperature anomalies in the equatorial Indian andPacific Ocean areas for May 2022
The contour intervals are 1°C in (a) and 0.5°C in (b). The base period for the normal is 1991 – 2020.

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(a)

(b)

Figure 1-3 Time-longitude cross sections of (a) SST and (b) ocean heat content (OHC) anomalies along the equator in the Indian and Pacific
Ocean areas
OHCs are defined here as vertically averaged temperatures in the top 300 m. The base period for the normal is 1991 – 2020.

Figure 1-4 Outlook of NINO.3 SST deviation produced by theseasonal Ensemble Prediction System
This figure shows a time series of monthly NINO.3 SST deviations.
The thick line with closed circles shows observed SST deviations,and the boxes show the values produced for up to six months
ahead by the El Niño prediction model. Each box denotes the range
into which the SST deviation is expected to fall with a probabilityof 70%.

Figure 1-5 ENSO forecast probabilities based on the seasonal Ensemble
Prediction System
Red, yellow and blue bars indicate probabilities that the five-monthrunning mean of the NINO.3 SST deviation from the latest sliding 30year mean will be +0.5°C or above (El Niño), between +0.4 and -0.4°C(ENSO-neutral) and-0.5°C or below (La Niña), respectively. Regular text
indicates past months, and bold text indicates current and futuremonths.

<<Table of contents <Top of this article

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JMA's Seasonal Numerical Ensemble Prediction for Boreal Summer 2022
This report outlines JMA’s dynamical seasonal ensemble prediction for boreal summer 2022 (June – August,referred to as JJA), which was used as a basis for JMA’s operational three-month outlook issued on 24 May 2022. The
outlook is based on the seasonal ensemble prediction system of the Coupled Atmosphere-ocean General Circulation
Model (CGCM).
Summary: Based on JMA’s seasonal ensemble prediction system, La Niña conditions are likely to continue until early
boreal summer. In association with above-normal SSTs from the southeastern tropical Indian Ocean to around the
Maritime Continent, enhanced convection is expected from west of Sumatra to the southern part of Southeast Asia.
In the lower troposphere, cyclonic circulation anomalies straddling the equator are expected from the central toeastern tropical Indian Ocean, and anti-cyclonic circulation anomalies straddling the equator are expected from thewestern to central tropical Pacific.
1. Sea surface temperature
Figure 2-1 shows predicted SSTs (contours) and related anomalies (shading) for JJA. Negative anomalies are
expected in central-to-eastern parts of the equatorial Pacific. Subsurface warm waters observed in the western partare expected to migrate eastward and slightly increase SSTs in the eastern part in boreal summer. La Niña conditions
are likely to continue until early boreal summer. In the tropical Indian Ocean, positive anomalies in the southeasternpart and negative anomalies in the western part are expected in boreal summer.

Figure 2-1 Predicted SSTs (contours) and SST anomalies (shading) for June–
August 2022 (ensemble mean of 51 members)

2. Prediction for the tropics and sub-tropics
Figure 2-2 (a) shows predicted precipitation (contours) and related anomalies (shading) for JJA. In association withpositive SST anomalies from the southeastern tropical Indian Ocean to around the Maritime Continent, above-normal
precipitation is expected from west of Sumatra to the southern part of Southeast Asia. Below-normal precipitation is
expected over the western-to-central equatorial Pacific.
Figure 2-2 (b) shows predicted velocity potential (contours) and related anomalies (shading) in the upper
troposphere for JJA. In association with the precipitation anomalies detailed above, negative (i.e., large-scale

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divergent) anomalies are expected from the tropical Indian Ocean to the Maritime Continent, while positive (i.e.,large-scale convergent) anomalies are expected near the date line to the eastern part of the equatorial Pacific.
Figure 2-2 (c) shows predicted stream functions (contours) and related anomalies (shading) in the upper
troposphere for JJA. Anti-cyclonic (i.e., positive in the Northern Hemisphere) circulation anomalies straddling theequator are expected from the tropical Atlantic to the tropical Indian Ocean, and cyclonic (i.e., negative in the
Northern Hemisphere) circulation anomalies straddling the equator are expected over the central tropical Pacific.
Figure 2-2 (d) shows predicted stream functions (contours) and related anomalies (shading) in the lower
troposphere for JJA. Cyclonic (i.e., negative in the Northern Hemisphere) circulation anomalies straddling the equator
are expected from the central to eastern tropical Indian Ocean, and anti-cyclonic (i.e., positive in the Northern
Hemisphere) circulation anomalies straddling the equator are expected from the western to central tropical Pacific.
(a)

(b)

(c)

(d)

Figure 2-2 Predicted atmospheric fields over 60°N-60°S for June–August 2022 (ensemble mean of 51 members)(a) Precipitation (contours) and anomaly (shading). The contour interval is 2 mm/day. (b) Velocity potential at 200-hPa(contours) and anomaly (shading). The contour interval is 2 × 106 m2/s. (c) Stream function at 200-hPa (contours) and anomaly(shading). The contour interval is 16 × 106 m2/s. (d) Stream function at 850-hPa (contours) and anomaly (shading). The contour
interval is 5 × 106 m2/s.

3. Prediction for the mid- and high- latitudes of the Northern Hemisphere
Figure 2-3 (a) shows predicted 500-hPa geopotential heights (contours) and related anomalies (shading) for JJA.
Positive anomalies are expected over the Northern Hemisphere mid-latitudes, especially to the northeast of Japan.
Figure 2-3 (b) shows predicted sea level pressure (contours) and related anomalies (shading) for JJA. Positive
anomalies are expected over a wide area of the North Pacific, and negative anomalies are expected over a wide areaof Eurasia and the northern part of North America.

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(a)

(b)

Figure 2-3 Predicted atmospheric fields in the Northern Hemisphere for June–August 2022 (ensemble mean of 51 members)(a) Geopotential height at 500-hPa (contours) and anomaly (shading). The contour interval is 60 m. (b) Sea level pressure(contours) and anomaly (shading). The contour interval is 4 hPa.

Note: JMA operates a seasonal Ensemble Prediction System (EPS) using the Coupled atmosphere-ocean General
Circulation Model (CGCM) to make seasonal predictions beyond a one-month time range. The EPS produces
perturbed initial conditions by means of a combination of the initial perturbation method and the lagged average
forecasting (LAF) method. Prediction is made using 51 members from the latest 17 initial dates (3 members are usedevery day). Details of the prediction system and verification maps based on 30-year hindcast experiments (1991–2020) are available at https://ds.data.jma.go.jp/tcc/tcc/products/model/.
(SATO Hitoshi, Tokyo Climate Center)<<Table of contents <Top of this article

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Summary of the 2021/2022 Asian Winter Monsoon
This report summarizes the characteristics of the surface climate and atmospheric/oceanographic conditions
related to the Asian winter monsoon for 2021/2022.
Note: The Japanese 55-year Reanalysis dataset (JRA-55; Kobayashi et al. 2015) and COBE-SST (Ishii et al. 2005) wereused to analyze atmospheric circulation and sea surface temperature (SST). NOAA Interpolated Outgoing Longwave
Radiation (OLR) data (Liebmann and Smith 1996) from the U.S. NOAA Physical Sciences Laboratory (PSL)(https://psl.noaa.gov/data/gridded/data.interp_OLR.html) were used to infer tropical convective activity. The baseperiod for the normal is 1991 to 2020. The term “anomaly” as used in this report refers to deviation from the normal.
1. Surface climate conditions
In winter 2021/2022, three-month (DJF) mean temperatures were above normal in and around Central Asia andbelow normal over southwestern China and western Japan (Figure 3-1 (a)). Above-normal temperatures over partsof Eastern Siberia and below-normal temperatures over western Japan were seen in January and February (Figure 31 (c–d)), in contrast to the temperature anomaly observed in December (Figure 3-1 (b)). Temperatures weresignificantly below normal over most of East Asia in February (Figure 3-1 (d)), corresponding to a stronger-thannormal East Asian Winter Monsoon (EAWM). Precipitation amounts during the winter period were above normal overa wide region from South Asia to southwestern China and the southeastern part of Eastern Siberia, and were below
normal from the Korean Peninsula to western Japan (Figure 3-2). Above-normal precipitation over a wide region ofSoutheast Asia was clearly seen in February in particular (Figure 3-2 (d)).

Figure 3-1 Temperature anomalies for (a) December 2021 to February 2022, (b) December 2021, (c) January 2022 and (d)February 2022
Categories are defined by the three-month/monthly mean temperature anomaly against the normal divided by its standard
deviation and averaged in 5° × 5° grid boxes. The thresholds of each category are –1.28, –0.44, 0, +0.44 and +1.28. Standard
deviations were calculated from 1991 – 2020 statistics. Areas over land without graphical marks are those where observation
data are insufficient or where normal data are unavailable.

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Figure 3-2 Precipitation ratio for (a) December 2021 to February 2022, (b) December 2021, (c) January 2022 and (d) February
2022
Categories are defined by the three-month/monthly precipitation ratio against the normal and averaged in 5° × 5° grid boxes.
The thresholds of each category are 70, 100 and 120%. Areas over land without graphical marks are those where observation
data are insufficient or where normal data are unavailable.

Figure 3-3 Extreme climate stations for (a) December 2021, (b) January 2022 and (c) February 2022
ΔT, SD and Rd indicate temperature anomaly, standard deviation and quintile, respectively.

Figure 3-3 plots stations where extreme climate conditions were observed during the period from December 2021
to February 2022. Extremely low temperatures were seen in and around southern China in February (Figure 3-3 (c);see also Figure 3-1 (d)). Extremely high precipitation amounts were seen in and around northwestern India in January(Figure 3-3 (b)) and on and around the Indochina Peninsula in February (Figure 3-3 (c)). Extremely low precipitation
amounts were seen in and around western Japan in February (Figure 3-3 (c)).

2. Characteristic atmospheric circulation and oceanographic conditions
This section presents characteristics of atmospheric circulation and oceanographic conditions averaged for winter2021/2022.

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2.1 Conditions in the tropics
Figure 3-4 shows three-month mean SST anomalies and anomalous convective activity seen during the winterperiod. SSTs exhibited negative anomalies east of 170oE in the equatorial Pacific and positive anomalies over thetropical western North Pacific (Figure 3-4 (a)) in association with the La Niña event that persisted from boreal autumn
2021 onward. In the Indian Ocean, remarkably positive SST anomalies were seen in the Bay of Bengal and west of
Sumatra (Figure 3-4 (a)). Convective activity inferred from OLR was enhanced from the Philippines to the seas northof New Guinea and suppressed from near the date line to the central part of the equatorial Pacific (Figure 3-4 (b)),
corresponding to SST anomalies associated with the La Niña event (Figure 3-4 (a)). In the upper troposphere, largescale divergence anomalies were dominant near the Maritime Continent, and large-scale convergence anomalies
were seen from the date line to the east over the equatorial Pacific, concomitant with tropical convection (Figure 34 (b)). Large-scale anomalous divergence promoted northward divergent winds from the Maritime Continent to theseas south of Japan (vectors in Figure 3-4 (b)), partly contributing to a meandering of the subtropical jet stream (STJ)
as described later.

Figure 3-4 Three-month mean (a) SST anomalies and (b) anomalous convective activity in winter 2021/2022
Shading in (a) and (b) shows SST anomalies [°C] and OLR anomalies [W/m2]. Contours and vectors in (b) indicate 200-hPa
velocity potential anomalies at intervals of 0.5 × 10 6 m2/s and divergent wind anomalies, respectively. Negative (cold color)and positive (warm color) OLR anomalies show enhanced and suppressed convective activity compared to the normal,
respectively.

Figure 3-5 shows three-month mean 200-hPa and 850-hPa stream function anomalies for the winter period. In theupper troposphere, a Rossby wave train was dominant along the STJ from the eastern part of Northern Africa to theseas east of Japan. The wave train was associated with anti-cyclonic circulation anomalies over the East China Sea
and cyclonic circulation anomalies near western China and to the east of Japan (Figure 3-5 (a)). The cyclonic
circulation anomalies near western China, which imply a southward meandering of the STJ, correspond to belownormal temperatures and above-normal precipitation near southwestern China (Figures 3-1 (a) and 3-2 (a)). The anticyclonic circulation anomalies over the East China Sea may have been partly caused by northward divergent winds
from the Maritime Continent, where enhanced convection was seen (Figure 3-4 (b)). This is also supported by vorticity
budget analysis and the results of a numerical experiment conducted using a linear baroclinic model (Watanabe andKimoto 2000, 2001) (not shown). In the central tropical Pacific, cyclonic circulation anomalies straddling the equator
were seen in response to suppressed convection from near the date line to the eastern part of the equatorial Pacific(Figure 3-5 (a)). A great circle wave train was clearly seen from the central tropical North Pacific via North America to
the North Atlantic, which is similar to behavior seen in the negative phase of the Pacific-North American (PNA)
teleconnection pattern (e.g., Barnston and Livezey 1987, Horel and Wallace 1981). In the lower troposphere, anti-

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cyclonic circulation anomalies straddling the equator were seen from the central to eastern tropical Pacific inresponse to suppressed convection from near the date line to the eastern part of the equatorial Pacific (Figure 3-5(b)).

Figure 3-5 Three-month mean (a) 200-hPa and (b) 850-hPa stream function anomalies in winter 2021/2022
Contours indicate stream function anomalies at intervals of (a) 3 × 106 m2/s and (b) 1.5 × 106 m2/s, and shading shows OLR
anomalies [W/m2]. Vectors denote horizontal components of wave activity flux [m 2/s2] as defined by Takaya and Nakamura(2001).

2.2 Conditions in the extratropics
Figure 3-6 shows three-month mean 500-hPa height, sea level pressure and 850-hPa temperature in the Northern
Hemisphere. In the 500-hPa height field (Figure 3-6 (a)), significant positive anomalies were seen over Eastern Siberia,
implying significantly frequent blocking-high formation over the region (figure not shown), and negative anomalies
were seen to the south. The north-south dipole pattern of the height anomalies resembles the Western Pacific (WP)
teleconnection pattern (Wallace and Gutzler 1981). The tropospheric polar vortex in the Northern Hemispherecentered from the Arctic region to northern Canada was stronger than normal. Part of the enhanced polar vortex
split and moved southward to just north of Japan (contours in Figure 3-6 (a)). Wave trains associated with heightanomalies were seen from Eurasia to Japan along the polar-front jet (PFJ) over northern Eurasia and the STJ oversouthern Eurasia. Another wave train in the Western Hemisphere from the mid-latitude North Pacific to the western
North Atlantic corresponded to the negative phase of the PNA pattern (see also Figure 3-5 (a)). In the sea levelpressure field (Figure 3-6 (b)), the Aleutian Low was stronger than normal and shifted southwestward from its normal
position. Positive SLP anomalies from Eastern Siberia to China indicate a stronger-than-normal Siberian High. The
pattern of SLP anomalies indicates a stronger-than-normal EAWM, corresponding to below-normal temperaturesfrom southern China to mainland Japan in the lower troposphere (Figure 3-6 (c)). Lower-level temperatures, bycontrast, were above normal over Siberia in association with positive 500-hPa height anomalies (Figure 3-6 (a)).

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Figure 3-6 Three-month mean (a) 500-hPa height, (b) sea level pressure and (c) 850-hPa temperature in winter 2021/2022
Contour intervals are (a) 60 m, (b) 4 hPa and (c) 4 °C. Shading denotes related anomalies.

Figure 3-7 Three-month mean (a) 30-hPa and (b) 100-hPa height in winter 2021/2022
Contour intervals are (a) 120 m and (b) 60 m. Shading denotes related anomalies.

In the sea level pressure field, significant negative and positive anomalies with a north-south dipole pattern wereseen over the North Atlantic, showing the positive phase of the North-Atlantic Oscillation (NAO; e.g., Hurrell 1995).
The NAO in winter is known to be associated with stratospheric circulation caused by stratosphere-troposphereinteraction (e.g., Ambaum and Hoskins 2002, Ineson and Scaife 2009). Figure 3-7 shows three-month mean 30-hPa
and 100-hPa height in the Northern Hemisphere. Negative height anomalies at 30 hPa and 100 hPa were clearly seenfrom the Arctic region to northern Canada, indicating that the stratospheric polar vortex was stronger than normal
and slightly shifted toward Canada during the winter period. The negative anomalies seen over northern Canada in
the stratosphere correspond well with those seen in the troposphere (Figure 3-6 (a)) and near the surface (Figure 36 (b)), suggesting a close relationship to the positive phase of the NAO resulting from stratosphere–troposphereinteraction.
(Kazuto Takemura, Tokyo Climate Center)

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References
Ambaum, M. H. P., and B. J. Hoskins, 2002: The NAO troposphere–stratosphere connection. J. Climate, 15, 1969−1978.
Barnston, A. G., and R. E. Livezey, 1987: Classification, seasonality and persistence of low-frequency atmosphericcirculation patterns. Mon. Wea. Rev., 115, 1083–1126.
Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmospheric phenomena associated with the Southern
Oscillation. Mon. Wea. Rev., 109, 813–829.
Hurrell, J. W., 1995: Decadal trends in the North Atlantic Oscillation and relationships to regional temperature andprecipitation. Science, 269, 676–679.
Ineson, S., and I. I. Scaife, 2009: The role of the stratosphere in the European climate response to El Niño. Nature
Geosci., 2, 32−36.
Ishii, M., A. Shouji, S. Sugimoto, and T. Matsumoto, 2005: Objective analyses of sea-surface temperature and marine
meteorological variables for the 20th century using ICOADS and the Kobe Collection. Int. J. Climatol., 25, 865–879.
Kobayashi, S., Y. Ota, Y. Harada, A. Ebita, M. Moriya, H. Onoda, K. Onogi, H. Kamahori, C. Kobayashi, H. Endo, K. Miyaoka,
and K. Takahashi, 2015: The JRA-55 Reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan,
93, 5–48.
Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset.
Bull. Amer. Meteor. Soc., 77, 1275–1277.
Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary andmigratory quasigeostrophic eddies on a zonally varying basic flow, J. Atom. Sci., 58, 608–627.
Wallace, J, M., and D. S. Gutzler, 1981: Teleconnections in the geopotential height field during the Northern
Hemisphere winter, Mon. Wea. Rev., 109, 784–812.
Watanabe, M., and M. Kimoto, 2000: Atmospheric-ocean thermal coupling in the North Atlantic: A positive feedback.
Quart. J. Roy. Meteor. Soc., 126, 3343–3369.
Watanabe, M., and M. Kimoto, 2001: Corrigendum. Quart. J. Roy. Meteor. Soc., 127, 733–734.

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TCC and WMC Tokyo co-contributions to Regional Climate Outlook Forums

WMO Regional Climate Outlook Forums (RCOFs) bring together national, regional and international climate
experts on an operational basis to produce regional climate outlooks based on input from participating NMHSs,
regional institutions, Regional Climate Centres (RCCs) and global producers of climate predictions. By providing aplatform for countries with similar climatological characteristics to discuss related matters, these forums ensure
consistency in terms of access to and interpretation of climate information.
In spring 2022, experts from TCC and the World Meteorological Centre (WMC) Tokyo gave presentations on
climate outlooks and TCC activities at the following RCOFs, which were held online due to the ongoing COVID-19
pandemic.
 the 18th session of the Forum on Regional Climate Monitoring, Assessment and Prediction for Regional
Association II (FOCRA II-18)
 the 22th summer session of the South Asian Climate Outlook Forum (SASCOF-22)
As part of collaborative activities between TCC and WMC Tokyo, the experts from TCC and WMC Tokyo provided
summer season outlooks including probabilistic forecasts based on JMA’s dynamical seasonal ensemble prediction
system as well as Copernicus Climate Change Service (C3S) multi-model ensemble prediction, which the Japan
Meteorological Agency (JMA) has joined in since October 2020. The presenters also covered climate monitoring andhighlighted efforts to promote the use of TCC climate prediction information. These activities are intended to support
the output of country-scale outlooks by National Meteorological and Hydrological Services (NMHSs), contribute to
the summarization of consensus outlooks and reduce climate disaster risks in the water, agriculture and health sectors
for each target area. TCC and WMC Tokyo are committed to collaboration with operational climate communities toenhance progress in forecast skill and application of climate information toward the resolution of common issues andrealizing a climate-resilient world.
(TAKAHASHI Kiyotoshi, Tokyo Climate Center)<<Table of contents <Top of this article

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You can find the latest newsletter from the Japan International Cooperation Agency (JICA).
JICA Magazine
https://jicamagazine.jica.go.jp/en/"JICA magazine" is a public relations magazine published by JICA. It introduces the current situations of developing
countries around the world, the people who are active in the field, and the content of their activities.
Any comments or inquiry on this newsletter and/or
the TCC website would be much appreciated.
Please e-mail to tcc@met.kishou.go.jp.
(Editors: NEMOTO Noboru, TAKAHASHI Kiyotoshi)

Tokyo Climate Center, Japan Meteorological Agency
3-6-9 Toranomon, Minato City, Tokyo 105-8431, Japan
TCC Website:
https://ds.data.jma.go.jp/tcc/tcc/index.html<<Table of contents

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