JCDP

Takehiko Mikami

Continuous records of lake-freezing dates since the 15th century come from central Japan, where a small lake is known for a mysterious winter phenomenon.

Ice-cracking phenomena known as Omiwatari at Lake Suwa. Photos were taken by T.Mikami on 31 January 1998

Lake Suwa is a small lake located in central Japan, and is known for its mysterious phenomenon called Omiwatari in the winter season. We made an attempt at reconstructing winter temperatures based on the Lake Suwa freezing record. When the lake froze, shrinkage and expansion of the ice due to diurnal tem-perature variations caused an ice-cracking phenomenon Omiwatari, which was said to resemble ‘a bridge crossing the lake. The ancient village people might have believed it to be the track of a god visiting a goddess on the opposite shore. Since the fifteenth century, the formation of Omiwatari has been celebrated in a ceremony a couple of days after its occurrence.

Source: Hidetoshi Arakawa(1954):Fujiwara on five centuries of freezing dates of Lake Suwa in the central Japan. Archiv fur Meteorologie, Geophysik und Bioklimatologie, Series B 6 (1954): 153, table 2.

Year-to-year variations in December-January temperatures at Lake Suwa, 1444-1870 (reconstructed) and 1891-2010(observed). Thick blue lines indicate 11-year running means.

Source: T.Mikami, M.Zaiki and J.Hirano (2015): A history of climate change in Japan. In B.L.Batten and P.C.Brown Ed. ”Environment and Society in the Japanese Islands – From Prehistory to the Present” , Oregon State University Press.

The dates of complete freezing and Omiwatari have been recorded by the Suwa shrine since the fifteenth century, and also by the Suwa Meteorological Observatory independently since 1951. During a cold winter, Omiwatari would already have occurred by mid-December, whereas in a warm winter, it would be delayed until the end of February, or no Omiwatari would have occurred at all.

In recent years, occurrence frequency of Omiwatari phenomena has been decreasing rapidly, probably due to the global warming. There may be a possibility of rare opportunity to cerebrate Omiwatari phenomena at Lake Suwa in future.

Topics

Anomaly maps in “Climate Atlas”

　　　　　　　　　　　　　　　　　　　　　　　
Junpei Hirano

In climatology, we use values called “anomalies” to understand the average state of climatic elements (atmospheric pressure, temperature, precipitation, sunshine duration, and solar radiation, etc.). The “normal” is defined as the average value of climatic factors during the past 30 years. Since the average value changes due to climate change such as global warming, the normal is updated every ten years. For example, for the 10-year period from 2011 to 2020, the 1981-2010 average was used as the “normal,” but it was updated in 2021, and for the 10-year period from 2021 to 2030, the 1991-2020 average will be used as the “new normal.

In weather forecasting, the term “warmer (colder) than normal” is sometimes used, but in this case, “normal” refers to the “normal” value of temperature. In other words, the “normal value” of temperature is the standard for evaluating the warmth (coldness), etc. of each year. The difference between the temperature of each year and the normal is called the ” anomaly”. In the case of temperature, a positive anomaly indicates a warmer than normal year, while a negative anomaly indicates a colder than normal year. A map of temperature anomalies shows the distribution of areas with warmer-than-normal temperatures (positive anomaly areas) and areas with colder-than-normal temperatures (negative anomaly areas).

Similar to temperature, precipitation can also be plotted based on the “normal” value. However, in the case of precipitation, anomalies are generally expressed as the ratio of precipitation to the normal (ratio of normal to precipitation). For example, if you draw a precipitation anomaly map for a year with an El Niño or La Niña event, you can see areas with more or less rainfall than normal. Global precipitation anomaly maps for summer (June-August) and winter (December-February) of El Niño events are available on the Climate Atlas “World” page. However, as the basis for the anomalies, we have used the 43-year average for the period 1979-2021, for which precipitation data are available, instead of the 30-year “normal. Green-colored areas indicate areas of higher-than-normal rainfall, while brown-colored areas indicate areas of lower-than-normal rainfall. It can be seen that in El Niño years, there is more rainfall in the eastern tropical Pacific and less in the western tropical Pacific.

Furthermore, by comparing the precipitation anomaly map with the SST anomaly map, we can see the relationship between SST anomalies and precipitation anomalies. For example, in the “Winter DJF SST anomaly map for El Niño years”, the eastern tropical Pacific is colored red, indicating that SSTs are higher than normal. In an El Niño year, the sea surface temperature in this region is high, which activates cumulus convection and leads to heavy rainfall.

Global precipitation anomaly maps for summer (June – August) and winter (December – February) La Niña years show the opposite pattern (heavy rainfall in the eastern tropical Pacific and less rainfall in the western tropical Pacific). In La Niña years, sea surface temperatures (SSTs) drop below normal in the eastern tropical Pacific (see SST anomaly distribution in La Niña years), which suppresses cumulus convection and results in less rainfall.

The JCDP “Climate Atlas” will include various climate anomaly maps in the future. We recommend that you use the anomaly maps in the JCDP Climate Atlas when explaining “extreme weather” and its spatial distribution in high school geography and geology courses and in university liberal arts courses.