NOAA's National Centers for Environmental Information calculates the global temperature anomaly every month based on preliminary data generated from authoritative datasets of temperature observations from around the globe. The major dataset, NOAAGlobalTemp version 5, updated in mid-2019, uses comprehensive data collections of increased global area coverage over both land and ocean surfaces. NOAAGlobalTempv5 is a reconstructed dataset, meaning that the entire period of record is recalculated each month with new data. Based on those new calculations, the new historical data can bring about updates to previously reported values. These factors, together, mean that calculations from the past may be superseded by the most recent data and can affect the numbers reported in the monthly climate reports. The most current reconstruction analysis is always considered the most representative and precise of the climate system, and it is publicly available through Climate at a Glance.
Temperature anomalies and percentiles are shown on the gridded maps below. The anomaly map on the left is a product of a merged land surface temperature and sea surface temperature anomaly analysis. Temperature anomalies for land and ocean are analyzed separately and then merged to form the global analysis. The percentile map on the right provides additional information by placing the temperature anomaly observed for a specific place and time period into historical perspective, showing how the most current month, season or year compares with the past.
The global surface temperature for January 2022 was 0.89°C (1.60°F) above the 20th century average and the sixth highest for January since global records began in 1880. The last eight Januarys (2015–2022) rank among the 10 warmest Januarys on record. January 2022 also marked the 46th consecutive January and the 445th consecutive month with temperatures, at least nominally, above average.
Similar to 2021, the year 2022 began with an episode of a La Niña in the tropical Pacific Ocean. The El Niño-Southern Oscillation (ENSO) can affect global temperatures. La Niña tends to cool global temperatures slightly, while El Niño tends to boost global temperatures. With a slightly cool start to the year, there is only a 10% chance of 2022 ending as the warmest year on record. However, there is over 99% chance of the year ranking among the 10 warmest years on record.
During January 2022, temperatures were much-warmer-than-average across most of South America, resulting in the second warmest January for the continent since continental records began in 1910 with a temperature departure of +1.35°C (+2.43°F). Only January of 2016 was warmer at +1.55°C (+2.79°F). Much of the Atlantic, northern Indian, and western Pacific oceans, as well as parts of southern Mexico, Central America, western and southern Africa, and southern Asia had much-above-average temperatures. Record-warm January temperatures were observed across a large area of central South America and in small areas across the Atlantic, Indian, western Pacific oceans, and Asia. This encompassed about 2.87% of the world's surface with record-warm January temperatures.
Regionally, the Caribbean region had its third warmest January on record at 0.87°C (1.57°F) above average. Only Januarys of 2016 and 2020 were warmer. With a temperature departure at +2.48°C (+4.46°F), Asia had its fourth warmest January on record. Oceania had its seventh warmest January (tied with 2001) on record, while Europe had its 15th warmest January on record.
Hong Kong, China had a warmer-than-average January, with a mean temperature of 1.5°C (2.7°F), which was its fifth warmest January on record.
Meanwhile, cooler-than-average January temperatures were observed across parts of northern North America, northern Africa, India, and the Pacific Ocean. Averaged as a whole, North America had an above-average January; however, its temperature departure was the smallest since January 2009.
The year began with unusually warm temperatures across Europe. In Köflach, Austria, the maximum temperature on January 1, 2022 was 18.8°C (68.8°F)—the highest maximum temperature in Austria for New Year's Day. The previous record was 18.0°C (64.4°F) set in 1984 in Wr. Neustadt.
An intense heat wave affected a large portion of Argentina during the month. This was Argentina's third heat wave during its Southern Hemisphere summer season. According to Argentina's National Weather Service, the heat wave began on January 6 and culminated after 21 consecutive days of extremely warm temperatures, resulting in over 75 new maximum and minimum temperature records. Of note, the city of Buenos Aires had its highest minimum temperature on January 15 since records began in 1906 when minimum temperatures only dropped to 30°C (86°F). Similarly, unusually warm temperatures affected parts of Uruguay during mid-month. By January 14, Florida, Uruguay had a maximum temperature of 44.0°C (111.2°F), tying the national maximum temperature record set in January 1943.
During January 21–23, a heat wave affected parts of Western and Northern Cape, South Africa. According to the South African Weather Service, the station in Alexander Bay set a new high minimum temperature of 22.8°C (73.0°F), surpassing the previous record of 22.5°C (72.5°F) set on January 16, 1963.
Australia's January mean temperature was 1.09°C (1.96°F) above the 1961–1990 average, resulting in the nation's 13th warmest January since national temperature records began in 1910. Regionally, Tasmania had its second highest January mean temperature on record at 2.45°C (4.41°F) above average. This value was only 0.06°C (0.11°F) shy of tying the record warm January set in 2019. Meanwhile, Tasmania's minimum temperature was the highest on record at +2.32°C (+4.18°F), surpassing the previous record by 0.43°C (0.77°F) set in 2016. Victoria also had its highest minimum January temperature with an anomaly of +3.65°C (+6.57°F), besting the now-second highest set in 2019 (+3.25°C / +5.85°F).
- A very warm airmass over Western Australia brought unusually hot temperatures to the region mid-month. On January 13, maximum temperatures were over 50.0°C (122.0°F), with the Onslow Airport reporting a maximum temperature of 50.7°C (123.3°F)—this is the highest temperature on record for Western Australia, besting the previous record of 50.5°C (122.9°F) set at Mardie on February 19, 1998. This value also tied Australia's highest maximum temperature on record first set on January 2, 1960 at Oodnadatta, South Australia.
(out of 143 years)
|Land||+1.49 ± 0.13||+2.68 ± 0.23||Warmest||6th||2020||+2.08||+3.74|
|Ocean||+0.67 ± 0.15||+1.21 ± 0.27||Warmest||5th||2016||+0.92||+1.66|
|Land and Ocean||+0.89 ± 0.15||+1.60 ± 0.27||Warmest||6th||2020||+1.14||+2.05|
|Land||+1.65 ± 0.16||+2.97 ± 0.29||Warmest||8th||2007||+2.43||+4.37|
|Ocean||+0.80 ± 0.14||+1.44 ± 0.25||Warmest||4th||2016||+1.10||+1.98|
|Land and Ocean||+1.13 ± 0.13||+2.03 ± 0.23||Warmest||5th||2020||+1.49||+2.68|
|Land||+1.08 ± 0.11||+1.94 ± 0.20||Warmest||5th||2019||+1.45||+2.61|
|Ocean||+0.57 ± 0.16||+1.03 ± 0.29||Warmest||6th||2016||+0.78||+1.40|
|Land and Ocean||+0.65 ± 0.15||+1.17 ± 0.27||Warmest||6th||2016||+0.86||+1.55|
|Land and Ocean||+2.30 ± 1.17||+4.14 ± 2.11||Warmest||12th||1981||+4.35||+7.83|
500 mb maps
In the atmosphere, 500-millibar height pressure anomalies correlate well with temperatures at the Earth's surface. The average position of the upper-level ridges of high pressure and troughs of low pressure—depicted by positive and negative 500-millibar height anomalies on the January 2022 map—is generally reflected by areas of positive and negative temperature anomalies at the surface, respectively.
The maps shown below represent precipitation percent of normal (left, using a base period of 1961–1990) and precipitation percentiles (right, using the period of record) based on the GHCN dataset of land surface stations.
As is typical, precipitation anomalies during January 2022 varied significantly around the world. January precipitation was generally drier than normal across much of the central and western contiguous U.S., Mexico, central and western Europe, western Australia, northern New Zealand, and across parts of the Korean peninsula and Japan. Wetter-than-normal conditions were notable across parts of Asia, southern South America, eastern Europe, and central and southeastern Australia.
Below-average precipitation engulfed much of Spain. The national precipitation total was 26% of normal and was the fifth driest January since 1961.
According to the Japan Meteorological Agency, snowfall fell across parts of northern Japan from late December to early January, with some locations setting new snowfall records. Of note, Hikone in Shiga Prefecture observed a total of 78 cm (30.7 inches), which is a new 48-hour snowfall record for this location.
The Bahrain International Airport at the Kingdom of Bahrain had a total of 58 mm (2.3 inches) of precipitation for the month, which is a little over triple its monthly average rainfall of 18.1 mm (0.7 inch). This was its sixth wettest January since records began in 1902. According to Bahrain's Meteorological Directorate Climate Section, January 1 had the highest daily precipitation during the month when a total of 36.2 mm (1.4 inches) fell. This was the fifth highest daily total for the airport since 1948.
Tropical Storm Ana was the first named storm of the year for the Southwest Indian Ocean basin. On January 24, Ana made landfall in northern Mozambique. According to ReliefWeb, the storm was responsible for destroying over 12,000 homes and damaging over 25 health centres. It was reported that water supply systems, power poles, and roads were also damaged. Heavy rain associated with the storm caused floods, including the flooding of more than 37,000 hectares of crops.
Global Precipitation Climatology Project (GPCP)
The following analysis is based upon the Global Precipitation Climatology Project (GPCP) Interim Climate Data Record. It is provided courtesy of the GPCP Principal Investigator team at the University of Maryland.
January, in the heart of Northern Hemisphere (NH) winter and Southern Hemisphere (NH) summer, has its monthly precipitation features pushed far to the south (see top panel in Fig. 1). Over tropical oceans the Inter-Tropical Convergence Zone (ITCZ) extends in narrow bands east-west across the Pacific and Atlantic, straddling the Equator. The South Pacific Convergence Zone (SPCZ) extends southeastward from the Maritime Continent into mid-ocean and in the Indian Ocean larger amounts of rainfall are south of the Equator. Over Africa, Australasia and South America, the seasonal rain has also shifted south. At higher latitudes the precipitation patterns have also seasonally shifted southward bringing mid-latitude cyclonic systems to lower latitudes in the NH and higher latitudes in the SH.
Of course, in addition to these seasonal shifts, large-scale climate variations including long-term trends related to global warming and inter-annual-scale changes related to phenomenon such as El Nino-Southern Oscillation (ENSO) combine with synoptic-scale events during the month to achieve the monthly total map, and the anomalies (from the January climatology) seen in Fig. 1 (middle and bottom panels). As has been the case over much of the past 18 months, relative low Sea Surface Temperatures (SST) over the central-eastern Pacific along the Equator, defining the current La Niña conditions, affect the distribution rainfall anomalies across a wide area of the Pacific and beyond. However, for this month a possible weakening La Niña seems to have a more limited range of effect. In Fig. 2 the precipitation anomalies for January 2022 are repeated in the bottom panel and the top panel is a composite anomaly map for La Niña Januarys during the GPCP period (1979–2020). Although the core of the cool SSTs is to the east along the Equator, the westward movement of convective systems results in a relative minimum (negative anomaly) near and surrounding 180° longitude, both in the composite and this January, although the negative feature is more intense in the composite than for this month. The negative feature stretches narrowly to the east along the ITCZ in both maps, but to the west over the Maritime Continent the general positive anomaly in the composite is not well matched by this month's anomaly pattern, which is very mixed. To the south, over Australia, which typically has abundant rainfall during La Niña, there is generally a match with this month's mean continental totals, but the pattern is different.
As we move away from the core central Pacific area, the match between the composite and this month's anomaly pattern is generally weak, with patterns over Africa, South America and South Asia being definitely mismatched. But, over the Pacific and Atlantic ITCZs, the SPCZ area and over the northeast Pacific, off the North American continent, there seems to be a match, indicating an extensive Pacific La Niña effect. Closer to home, over North America, the La Niña composite and this month's map in Fig. 2 agree very well, both showing precipitation deficits over the southwest U.S. and Mexico, and even to the east. A long-term drought continues over this region, and the presence of La Niña doesn't help.
Elsewhere across the globe the precipitation anomalies for this January reflect mostly smaller-scale events. Southeast Africa displays an intense positive anomaly, mainly associated with Tropical Cyclone Ana that hit Madagascar and Mozambique. Positive anomalies across the Middle East and South Asia do not match the typical dry season usually observed in these areas and included unusual floods in Iran and Oman. Even Quito, Ecuador, in the middle of a broad negative anomaly in northwest South America, had devastating floods and landslides at the end of the month. Much of western Europe had a precipitation deficit for January and this had prolonged the drought conditions over much of that region, although the positive anomaly to the east over Russia has helped to alleviate similar conditions there.
Expanding our time scale we can look at the observed trend map for January (Fig. 3, top panel), along with the January climatology map (Fig. 3, bottom panel). Strong positive and negative features are observed over the tropical oceans (the global trend is very near zero) and help to verify climate models, when they are forced by observed SSTs, and these features are related in part to global warming. Over the eastern Pacific off the west coast an observed drying trend exists from Hawaii into the southern U.S. and Mexico. Combining this negative trend feature with the inter-annual La Niña negative push there (see Fig. 2) indicates that the current general drought in this region is related to occurrences at various time scales, which sometimes must be analyzed together to help understand even an individual month's precipitation anomalies. For example, Los Angeles had one of its driest Januarys ever this past month, most likely related to a combination of these causes, occurring at various time scales.
- Adler, R., G. Gu, M. Sapiano, J. Wang, G. Huffman 2017. Global Precipitation: Means, Variations and Trends During the Satellite Era (1979-2014). Surveys in Geophysics 38: 679-699, doi:10.1007/s10712-017-9416-4
- Adler, R., M. Sapiano, G. Huffman, J. Wang, G. Gu, D. Bolvin, L. Chiu, U. Schneider, A. Becker, E. Nelkin, P. Xie, R. Ferraro, D. Shin, 2018. The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation. Atmosphere. 9(4), 138; doi:10.3390/atmos9040138
- Gu, G., and R. Adler, 2022. Observed Variability and Trends in Global Precipitation During 1979-2020. Climate Dynamics, doi:10.1007/s00382-022-06567-9
- Huang, B., Peter W. Thorne, et. al, 2017: Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5), Upgrades, validations, and intercomparisons. J. Climate, doi: 10.1175/JCLI-D-16-0836.1
- Huang, B., V.F. Banzon, E. Freeman, J. Lawrimore, W. Liu, T.C. Peterson, T.M. Smith, P.W. Thorne, S.D. Woodruff, and H-M. Zhang, 2016: Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4). Part I: Upgrades and Intercomparisons. J. Climate, 28, 911-930, doi:10.1175/JCLI-D-14-00006.1.
- Menne, M. J., C. N. Williams, B.E. Gleason, J. J Rennie, and J. H. Lawrimore, 2018: The Global Historical Climatology Network Monthly Temperature Dataset, Version 4. J. Climate, in press. https://doi.org/10.1175/JCLI-D-18-0094.1.
- Peterson, T.C. and R.S. Vose, 1997: An Overview of the Global Historical Climatology Network Database. Bull. Amer. Meteorol. Soc., 78, 2837-2849.
- Vose, R., B. Huang, X. Yin, D. Arndt, D. R. Easterling, J. H. Lawrimore, M. J. Menne, A. Sanchez-Lugo, and H. M. Zhang, 2021. Implementing Full Spatial Coverage in NOAA's Global Temperature Analysis. Geophysical Research Letters 48(10), e2020GL090873; doi:10.1029/2020gl090873.