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The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a ‘‘best estimate’’ of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

In the summer (July and August) of 2022, unprecedented heat wave occurred along the Yangtze River Valley (YRV) over East Asia while unprecedented flood occurred over western South Asia (WSA), which are located on the eastern and western sides of Tibetan Plateau (TP). Here, by analyzing the interannual variability based on observational and reanalysis data, we show evidences that the anomalous zonal flow over subtropical Tibetan Plateau (TP) explains a major fraction the extreme events occurred in 2022. As isentropic surfaces incline eastward (westward) with altitude on the eastern (western) side of the warm center over TP in summer, anomalous easterly (westerly) flow in upper troposphere generates anomalous descent (ascent) on the eastern side of TP and anomalous ascent (descent) on the western side of TP via isentropic gliding. The anomalous easterly flow is extremely strong to reverse the climatological westerly flow over subtropical TP in 1994, 2006, 2013 and 2022. The easterly flow in 2022 is the strongest since 1979, and it generates unprecedented descent (ascent) anomaly on the eastern (western) side of TP, leading to extreme heat wave over YRV and extreme flood over WSA in 2022. The anomalously strong easterly flow over subtropical TP in 2022 is dominated by atmospheric internal variability related to mid-latitude wave train, while the cold sea surface temperature anomaly over the tropical Indian Ocean increases the probability of a reversed zonal flow over TP by reducing the meridional gradient of tropospheric temperature.

The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within themeteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.

The monthly Extended Reconstructed Sea Surface Temperature (ERSST) dataset, available on global 2° × 2° grids, has been revised herein to version 4 (v4) from v3b. Major revisions include updated and substantially more complete input data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) release 2.5; revised empirical orthogonal teleconnections (EOTs) and EOT acceptance criterion; updated sea surface temperature (SST) quality control procedures; revised SST anomaly (SSTA) evaluation methods; updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2); and buoy SST bias adjustment not previously made in v3b. Tests show that the impacts of the revisions to ship SST bias adjustment in ERSST.v4 are dominant among all revisions and updates. The effect is to make SST 0.1°–0.2°C cooler north of 30°S but 0.1°–0.2°C warmer south of 30°S in ERSST.v4 than in ERSST.v3b before 1940. In comparison with the Met Office SST product [the Hadley Centre Sea Surface Temperature dataset, version 3 (HadSST3)], the ship SST bias adjustment in ERSST.v4 is 0.1°–0.2°C cooler in the tropics but 0.1°–0.2°C warmer in the midlatitude oceans both before 1940 and from 1945 to 1970. Comparisons highlight differences in long-term SST trends and SSTA variations at decadal time scales among ERSST.v4, ERSST.v3b, HadSST3, and Centennial Observation-Based Estimates of SST version 2 (COBE-SST2), which is largely associated with the difference of bias adjustments in these SST products. The tests also show that, when compared with v3b, SSTAs in ERSST.v4 can substantially better represent the El Niño/La Niña behavior when observations are sparse before 1940. Comparisons indicate that SSTs in ERSST.v4 are as close to satellite-based observations as other similar SST analyses.

A sequence of extreme cold events occurred across Eurasia and North America during winter 2020/21. Here, we explore the causes and associated mechanisms for the extremely cold temperatures using both observations and large-ensemble simulations. Experiments were conducted with observed ocean surface boundary conditions prescribed globally, and regionally to discern the specific influence of Arctic, tropical Pacific, and North Pacific drivers. Increased likelihood of daily cold extremes in mid-December to mid-January are found in Eurasian midlatitudes in response to reduced Arctic sea ice. Tropical sea surface temperature anomalies, more specifically the La Niña pattern, increased probability of extreme cold over high-latitude Eurasia in early January to early February. Both reduced Arctic sea ice and La Niña increased the probability of daily cold extremes over western North America in late January to late February. We conclude that a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming in January 2021 were factors in the February 2021 extreme cold wave that caused huge societal disruptions in Texas and the southern Great Plains. Although the magnitude of the simulated cold extremes are relatively small when compared with observed anomalies, the Arctic and Pacific Ocean surface conditions in winter 2020/21 increased the probability of cold days as cold or colder than observed by approximately 17%–43%.

The monthly global 2° × 2° Extended Reconstructed Sea Surface Temperature (ERSST) has been revised and updated from version 4 to version 5. This update incorporates a new release of ICOADS release 3.0 (R3.0), a decade of near-surface data from Argo floats, and a new estimate of centennial sea ice from HadISST2. A number of choices in aspects of quality control, bias adjustment, and interpolation have been substantively revised. The resulting ERSST estimates have more realistic spatiotemporal variations, better representation of high-latitude SSTs, and ship SST biases are now calculated relative to more accurate buoy measurements, while the global long-term trend remains about the same. Progressive experiments have been undertaken to highlight the effects of each change in data source and analysis technique upon the final product. The reconstructed SST is systematically decreased by 0.077°C, as the reference data source is switched from ship SST in ERSSTv4 to modern buoy SST in ERSSTv5. Furthermore, high-latitude SSTs are decreased by 0.1°–0.2°C by using sea ice concentration from HadISST2 over HadISST1. Changes arising from remaining innovations are mostly important at small space and time scales, primarily having an impact where and when input observations are sparse. Cross validations and verifications with independent modern observations show that the updates incorporated in ERSSTv5 have improved the representation of spatial variability over the global oceans, the magnitude of El Niño and La Niña events, and the decadal nature of SST changes over 1930s–40s when observation instruments changed rapidly. Both long-(1900–2015) and short-term (2000–15) SST trends in ERSSTv5 remain significant as in ERSSTv4.

In summer 2014, north China and large areas of northeastern Asia (NCNEA) suffered from the most severe drought of the past 60 years. This study indicates that the East Asian summer precipitation in 2014 exhibited a tripole anomaly, with severe negative anomalies in NCNEA, strong positive anomalies in south China, South Korea, and Japan, and intense negative anomalies in the western North Pacific. Along with the severe tripole precipitation anomalies, there were strong intensities of the Silk Road pattern, the Pacific–Japan pattern, and the Eurasian teleconnection pattern, which were responsible for the strong precipitation anomaly in 2014 through changes to the western Pacific subtropical high (WPSH) and the East Asian trough. Further analysis indicates that the sea surface temperature (SST) in the North Pacific was nearly the warmest in the past 60 years and, together with the strong SST warming in the warm pool region, thus caused the strong Pacific–Japan teleconnection pattern, southward positioning of the WPSH, and weakened East Asian summer monsoon. Additionally, the summertime sea ice cover in the Arctic Ocean was anomalous, resulting in high SST in the Laptev–Kara Sea and, hence, triggering a strong Eurasian teleconnection pattern and contributing to the severe drought of NCNEA. Furthermore, the intense warming over the European Continent and Caspian Sea favored the Silk Road pattern, also contributing to the southward positioning of the WPSH and the NCNEA drought. The NCNEA severe drought was therefore the joint result of Pacific SST anomalies, Arctic sea ice anomalies, and warming over the European Continent and Caspian Sea.

Recent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS‐E2.1‐G simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. There are detectable differences in zonal‐mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all‐forcing historical simulations in future coupled model intercomparisons. Plain Language Summary Simulations of recent historical periods are a key test of climate model reliability and skill. These model simulations require an accounting of all the drivers of climate change. We show that the impact of historical changes in freshwater fluxes from ice sheets and ice shelves on the ocean (through changes in salinity and stratification) are detectable in sea surface temperature and sea ice trends, and help improve the match between the modeled climate changes and observations. We recommend that more accurate estimates of these drivers be included in all climate simulations that do not explicitly model ice sheets and ice shelves. Key Points The response to anomalous meltwater from ice sheets and shelves is large enough for it to be a forcing in historical climate simulations When the GISS model includes these drivers, Southern Ocean SST and sea ice trends better match observations Steric and dynamic impacts on regional sea level in parts of the North Atlantic and coastal Antarctica are significant

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.

El Niño events differ substantially in their spatial pattern and intensity. Canonical Eastern Pacific El Niño events have sea surface temperature anomalies that are strongest in the far eastern equatorial Pacific, whereas peak ocean warming occurs further west during Central Pacific El Niño events. The event types differ in their impacts on the location and intensity of temperature and precipitation anomalies globally. Evidence is emerging that Central Pacific El Niño events have become more common, a trend that is projected by some studies to continue with ongoing climate change. Here we identify spatial and temporal patterns in observed sea surface temperatures that distinguish the evolution of Eastern and Central Pacific El Niño events in the tropical Pacific. We show that these patterns are recorded by a network of 27 seasonally resolved coral records, which we then use to reconstruct Central and Eastern Pacific El Niño activity for the past four centuries. We find a simultaneous increase in Central Pacific events and a decrease in Eastern Pacific events since the late twentieth century that leads to a ratio of Central to Eastern Pacific events that is unusual in a multicentury context. Compared to the past four centuries, the most recent 30 year period includes fewer, but more intense, Eastern Pacific El Niño events.Compared to the past few centuries, Central Pacific El Niño events have become more frequent, whereas the number of Eastern Pacific events has declined in the most recent decades, according to reconstructions from a network of seasonally resolved coral records.