Explore the vast range of titles available.

The International Comprehensive Ocean–Atmosphere Dataset (ICOADS) is a cornerstone for estimating changes in sea surface temperatures (SST) over the instrumental era. Interest in determining SST changes to within 0.1°C makes detecting systematic offsets within ICOADS important. Previous studies have corrected for offsets among engine room intake, buoy, and wooden and canvas bucket measurements, as well as noted discrepancies among various other groupings of data. In this study, a systematic examination of differences in collocated bucket SST measurements from ICOADS3.0 is undertaken using a linear-mixed-effect model according to nations and more-resolved groupings. Six nations and a grouping for which nation metadata are missing, referred to as “deck 156,” together contribute 91% of all bucket measurements and have systematic offsets among one another of as much as 0.22°C. Measurements from the Netherlands and deck 156 are colder than the global average by −0.10° and −0.13°C, respectively, both at p < 0.01, whereas Russian measurements are offset warm by 0.10°C at p °0.1. Furthermore, of the 31 nations whose measurements are present in more than one grouping of data (i.e., deck), 14 contain decks that show significant offsets at p < 0.1, including all major collecting nations. Results are found to be robust to assumptions regarding the independence and distribution of errors as well as to influences from the diurnal cycle and spatially heterogeneous noise variance. Correction for systematic offsets among these groupings should improve the accuracy of estimated SSTs and their trends.

Existing estimates of sea surface temperatures (SSTs) indicate that, during the early twentieth century, the North Atlantic and northeast Pacific oceans warmed by twice the global average, whereas the northwest Pacific Ocean cooled by an amount equal to the global average 1 – 4 . Such a heterogeneous pattern suggests first-order contributions from regional variations in forcing or in ocean–atmosphere heat fluxes 5 , 6 . These older SST estimates are, however, derived from measurements of water temperatures in ship-board buckets, and must be corrected for substantial biases 7 – 9 . Here we show that correcting for offsets among groups of bucket measurements leads to SST variations that correlate better with nearby land temperatures and are more homogeneous in their pattern of warming. Offsets are identified by systematically comparing nearby SST observations among different groups 10 . Correcting for offsets in German measurements decreases warming rates in the North Atlantic, whereas correcting for Japanese measurement offsets leads to increased and more uniform warming in the North Pacific. Japanese measurement offsets in the 1930s primarily result from records having been truncated to whole degrees Celsius when the records were digitized in the 1960s. These findings underscore the fact that historical SST records reflect both physical and social dimensions in data collection, and suggest that further opportunities exist for improving the accuracy of historical SST records 9 , 11 . Correction of oddities in the historical record of sea surface temperatures reveals that some basin-wide climate variations were an artefact of systematic biases that stem, in part, from Japanese records being truncated to whole numbers when the records were digitized.

Southern Madagascar experienced a prolonged drought over the last five years, but whether these conditions are a manifestation of global climate change has been unclear. Here, we document trends beginning as early as 1980 towards a later rainy-season onset across three distinct remotely sensed indicators: precipitation, soil moisture, and vegetation greenness. All three indicators closely covary, particularly over the last decade when satellite observational resolution and accuracy is greatest. Furthermore, observed soil moisture trends early in the rainy season agree with the mean from CMIP6 historical and SSP5-8.5 simulations, but are distinct from pre-industrial control simulations, implicating anthropogenic changes in radiative forcing as the source of the trends. Physically, these models simulate a poleward migration of the mid-latitude jet that leads to a delay in the seasonal steering of storm tracks over Southern Madagascar. Soil moisture trends driven by anthropogenic forcing made the recent drought significantly more likely over 2017–2022 ( p  < 0.01), and such droughts are expected to become increasingly likely over this century. These results indicate that, although Madagascar has not substantially contributed to global greenhouse gas emissions, farmers in Southern Madagascar will need to adapt to drier conditions early in the rainy season as a consequence of global climate change.

Air–sea interaction remains one of the most dynamic and influential components of the Earth’s climate system, significantly shaping the variability and predictability of both weather and climate [...]

Accurate historical records of Earth’s surface temperatures are central to climate research and policy development. Widely-used estimates based on instrumental measurements from land and sea are, however, not fully consistent at either global or regional scales. To address these challenges, we develop the Dynamically Consistent ENsemble of Temperature (DCENT), a 200-member ensemble of monthly surface temperature anomalies relative to the 1982–2014 climatology. Each DCENT member starts from 1850 and has a 5° × 5° resolution. DCENT leverages several updated or recently-developed approaches of data homogenization and bias adjustments: an optimized pairwise homogenization algorithm for identifying breakpoints in land surface air temperature records, a physics-informed inter-comparison method to adjust systematic offsets in sea-surface temperatures recorded by ships, and a coupled energy balance model to homogenize continental and marine records. Each approach was published individually, and this paper describes a combined approach and its application in developing a gridded analysis. A notable difference of DCENT relative to existing temperature estimates is a cooler baseline for 1850–1900 that implies greater historical warming.

Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1 o scale over China from 1990 to 2100 and investigated the temporal evolution of Koppen-Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions （7%-8% of China＇s land area） by 2010, including rapid replacement of mixed forest （Dwb） by deciduous forest （Dwa） over Northeast China, strong shrinkage of alpine climate type （ET） on the Tibetan Plateau, weak northward expansion of subtropical winter- dry climate （Cwa） over Southeast China, and contraction of oceanic climate （Cwb） in Southwest China. Under all future RCP （Representative Concentration Pathway） scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010-30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario （RCP8.5）, sub-polar continental winter dry climate over Northeast China would disappear by 2040-50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9% and 50.8% of China＇s land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China＇s ecoregions in future decades.

Most historical sea surface temperature (SST) estimates indicate warmer World War II SSTs than expected from forcing and internal climate variability. If real, this World War II warm anomaly (WW2WA) has important implications for decadal variability, but the WW2WA may also arise from incomplete corrections of biases associated with bucket and engine room intake (ERI) measurements. To better assess the origins of the WW2WA, we develop five different historical SST estimates (reconstructions R1–R5). Using uncorrected SST measurements from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) version 3.0 (R1) gives a WW2WA of 0.41°C. In contrast, using only buckets (R2) or ERI observations (R3) gives WW2WAs of 0.18° and 0.08°C, respectively, implying that uncorrected biases are the primary source of the WW2WA. We then use an extended linear-mixed-effect method to quantify systematic differences between subsets of SSTs and develop groupwise SST adjustments based on differences between pairs of nearby SST measurements. Using all measurements after applying groupwise adjustments (R4) gives a WW2WA of 0.13°C [95% confidence interval (c.i.): 0.01°–0.26°C] and indicates that U.S. and U.K. naval observations are the primary cause of the WW2WA. Finally, nighttime bucket SSTs are found to be warmer than their daytime counterparts during WW2, prompting a daytime-only reconstruction using groupwise adjustments (R5) that has a WW2WA of 0.09°C (95% c.i.:−0.01° to 0.18°C). R5 is consistent with the range of internal variability found in either the CMIP5 (95% c.i.: −0.10° to 0.10°C) or CMIP6 ensembles (95% c.i.: −0.11° to 0.10°C). These results support the hypothesis that the WW2WA is an artifact of observational biases, although further data and metadata analyses will be important for confirmation.

How summertime temperature variability will change with warming has important implications for climate adaptation and mitigation. CMIP5 simulations indicate a compound risk of extreme hot temperatures in western Europe from both warming and increasing temperature variance. CMIP6 simulations, however, indicate only a moderate increase in temperature variance that does not covary with warming. To explore this intergenerational discrepancy in CMIP results, we decompose changes in monthly temperature variance into those arising from changes in sensitivity to forcing and changes in forcing variance. Across models, sensitivity increases with local warming in both CMIP5 and CMIP6 at an average rate of 5.7 ([3.7, 7.9]; 95% c.i.) × 10−3°C per W m−2 per °C warming. We use a simple model of moist surface energetics to explain increased sensitivity as a consequence of greater atmospheric demand (∼70%) and drier soil (∼40%) that is partially offset by the Planck feedback (∼−10%). Conversely, forcing variance is stable in CMIP5 but decreases with warming in CMIP6 at an average rate of −21 ([−28, −15]; 95% c.i.) W2 m−4 per °C warming. We examine scaling relationships with mean cloud fraction and find that mean forcing variance decreases with decreasing cloud fraction at twice the rate in CMIP6 than CMIP5. The stability of CMIP6 temperature variance is, thus, a consequence of offsetting changes in sensitivity and forcing variance. Further work to determine which models and generations of CMIP simulations better represent changes in cloud radiative forcing is important for assessing risks associated with increased temperature variance. Plain Language Summary CMIP5 models show that, in the Northern Hemisphere midlatitudes, summertime temperature variability increases as the surface warms, indicating a compound risk of extreme hot months that have important implications for climate adaptation and mitigation. CMIP6 models, however, show only a moderate increase in temperature variability that is unrelated to warming. To understand this intergenerational discrepancy in CMIP results, we develop a framework to decompose changes in temperature variability into contributions from changes in the variability of external forcing and changes in the sensitivity of temperature to that forcing. We find that both CMIP5 and CMIP6 models show consistent increases in sensitivity as the surface warms, which we demonstrate to arise mainly from warming and drying using a simple diagnostic model. Changes in forcing variability, however, differ between CMIP5 and CMIP6. Whereas, forcing variability is stable in CMIP5, it decreases substantially with warming in CMIP6 and offsets the effect of sensitivity growth. Hence, although midlatitude land surface tends to become more sensitive in all models, whether temperature variability will increase with warming remains uncertain and relies on how forcing variability changes. Key Points Summer temperature variance increases with warming in Northern Hemisphere midlatitudes in CMIP5 but not in CMIP6 We develop a decomposition framework and a simple model to explain differences in variance changes across models Temperature sensitivity increases in both CMIP5 and CMIP6 but is offset by lower forcing variance in CMIP6

Anthropogenic forcings have contributed to global and regional warming in the last few decades and likely affected terrestrial precipitation. Here we examine changes in major Köppen climate classes from gridded observed data and their uncertainties due to internal climate variability using control simulations from Coupled Model Intercomparison Project 5 (CMIP5). About 5.7% of the global total land area has shifted toward warmer and drier climate types from 1950–2010 and significant changes include expansion of arid and high-latitude continental climate zones, shrinkage in polar and midlatitude continental climates, poleward shifts in temperate, continental and polar climates and increasing average elevation of tropical and polar climates. Using CMIP5 multi-model averaged historical simulations forced by observed anthropogenic and natural, or natural only, forcing components, we find that these changes of climate types since 1950 cannot be explained as natural variations but are driven by anthropogenic factors.

Differences in sea surface temperature (SST) biases among groups of bucket measurements in the International Comprehensive Ocean–Atmosphere Dataset, version 3.0 (ICOADS3.0), were recently identified that introduce offsets of as much as 1°C and have first-order implications for regional temperature trends. In this study, the origin of these groupwise offsets is explored through covariation between offsets and diurnal cycle amplitudes. Examination of an extended bucket model leads to expectations for offsets and amplitudes to covary in either sign, whereas misclassified engine room intake (ERI) temperatures invariably lead to negative covariance on account of ERI measurements being warmer and having a smaller diurnal amplitude. An analysis of ICOADS3.0 SST measurements that are inferred to come from buckets indicates that offsets after the 1930s primarily result from the misclassification of ERI measurements in points of five lines of evidence. 1) Prior to when ERI measurements become available in the 1930s, offset–amplitude covariance is weak and generally positive, whereas covariance is stronger and generally negative subsequently. 2) The introduction of ERI measurements in the 1930s is accompanied by a wider range of offsets and diurnal amplitudes across groups, with 3) approximately 20% of estimated diurnal amplitudes being significantly smaller than buoy and drifter observations. 4) Regressions of offsets versus amplitudes intersect independently determined end-member values of ERI measurements. 5) Offset-amplitude slopes become less negative across all regions and seasons between 1960 and 1980, when ERI temperatures were independently determined to become less warmly biased. These results highlight the importance of accurately determining measurement procedures for bias corrections and reducing uncertainty in historical SST estimates.