Warming Trend Research Articles

Modulated Trends in Arctic Surface Air Temperature Extremes as a Fingerprint of Climate Change

Abstract Strengthened by polar amplification, Arctic warming provides direct evidence for global climate change. This analysis shows how Arctic surface air temperature (SAT) extremes have changed throughout time. Using ERA5, we demonstrate a pan-Arctic (>60°N) significant upward SAT trend of +0.62°C decade−1 since 1979. Due to this warming, the warmest days of each month in the 1980s to 1990s would be considered average today, while the present coldest days would be regarded as normal in the 1980s to 1990s. Over 1979–2021, there was a 2°C (or 7%) reduction of pan-Arctic SAT seasonal cycle, which resulted in warming of the cold SAT extremes by a factor of 2 relative to the SAT trend and dampened trends of the warm SAT extremes by roughly 25%. Since 1979, autumn has seen the strongest increasing trends in daily maximum and minimum temperatures, as well as counts of days with SAT above the 90th percentile and decreasing trends in counts of days with SAT below the 10th percentile, consistent with rapid Arctic sea ice decline and enhanced air–ocean heat fluxes. The modulated SAT seasonal signal has a significant impact on the timing of extremely strong monthly cold and warm spells. The dampening of the SAT seasonal fluctuations is likely to continue to increase as more sea ice melts and upper-ocean warming persists. As a result, the Arctic winter cold SAT extremes may continue to exhibit a faster rate of change than that of the summer warm SAT extremes as the Arctic continues to warm. Significance Statement As a result of global warming, the Arctic Ocean’s sea ice is receding, exposing more and more areas to air–sea interactions. This reduces the range of seasonal changes in Arctic surface air temperatures (SAT). Since 1979, the reduced seasonal SAT signal has decreased the trend of warm SAT extremes by 25% over the background warming trend and doubled the trend of cold SAT extremes relative to SAT trends. A substantial number of warm and cold spells would not have been identified as exceptional if the reduction of the Arctic SAT seasonal amplitudes had not been taken into account. As the Arctic continues to warm and sea ice continues to diminish, seasonal SAT fluctuations will become more dampened, with the rate of decreasing winter SAT extremes exceeding the rate of increasing summer SAT extremes.

Increasing duration of heatwaves poses a threat to oyster sustainability in the Gulf of Mexico

The future of the wild oyster fishery in the northern Gulf of Mexico is largely uncertain due to changing environmental conditions and declining abundance of harvestable oysters. Specifically, rising temperatures can directly impact the physiological thresholds of the eastern oyster (Crassostrea virginica) at all life history stages and alter the narrow ecological niche this oyster occupies. The impact of rising temperatures is likely most pronounced during atmospheric heatwaves, defined as three or more days above the 90th percentile of daily maximum air temperatures, which have been shown to be increasing in frequency. Increasing exposure to high temperature extremes may contribute to and exacerbate an already declining oyster fishery. Critical to fishery health is recruitment i.e., the addition of new harvestable biomass, which is a dynamic process strongly driven by temperature. Here, we examine the relationship between heatwave characteristics and the prediction of poor oyster recruitment, measured as the abundance of post-larval oysters (e.g. spat) below the site-specific median density observed in historically productive oyster fisheries over 46-years (1976 – 2020) in Mobile Bay, Alabama and 21-years (1993 – 2014) in Apalachicola Bay, Florida. We acquired daily maximum air temperature measurements measured over 50 years (1970 – 2020) at weather monitoring stations adjacent to the bays to identify site specific annual heatwave events (maximum yearly air temperature, yearly and consecutive heatwave days, and number of annual heatwaves). Then, years with extreme heatwaves that exceeded the 75th percentile for the 50-year measurements were compared to years with non-extreme heatwave events. Years with extreme total heatwave days and extreme consecutive heatwave days were correlated with low post-larval oyster density. Across both bay systems, if consecutive heatwave days exceeded 11 days, then poor recruitment of oysters occurred 83 % of the time. Extreme heatwave duration as an indicator for poor recruitment has the potential to be a powerful tool for fishery managers to forecast recruitment and inform sustainable oyster harvest based on year-to-year variability in heatwave duration and long-term warming trends. Our findings illustrate how extreme temperatures can exacerbate multiple physiological and ecological stressors resulting in the loss of a keystone species for healthy and resilient coastal ecosystems.

Statistical Analysis for the Detection of Change Points and the Evaluation of Monthly Mean Temperature Trends of the Moulouya Basin (Morocco)

This study examines the spatiotemporal variability of mean monthly temperature in the Moulouya watershed of northeastern Morocco, highlighting associated trends. To this end, statistical methods widely recommended by climate researchers were adopted. We used monthly mean temperature data for the period 1980–2020 from 9 measuring stations belonging to the Moulouya Watershed Agency (ABHM). These stations were rigorously selected, taking into account their reliability, the length of their records, and their geographical position in the basin. In addition, a quality test and homogenization of the temperature series were carried out using the Climatol tool. The results obtained show a significant upward trend in mean monthly temperature, mainly pronounced during the summer months, in the Moulouya watershed. In fact, Z values generally exceeded the 0.05 significance level at all stations during April, May, June, July, August, and October. According to the results of Sen’s slope test, mean monthly temperatures show an annual increase ranging from 0 to 0.13°C. The maximum magnitude of warming is recorded in July, specifically at Oujda Station. On an overall watershed scale, May, August, and July show a rapid warming trend, with average rates of 0.093, 0.086, and 0.08°C per year, respectively. By contrast, the series for the other months show no significant trend. Significant trend change points were also identified at watershed and station scales, mainly around 2000, primarily for accelerated warming of the summer months.

How extreme hydrological events correspond to climate extremes in the context of global warming: A case study in the Luanhe River Basin of North China

AbstractThe consensus on climate warming is well‐established, and extreme values inherently encapsulate more information than averages. Against the backdrop of frequent extreme climate events, studying extreme values holds profound significance. This study aims to reveal the characteristics of extreme climate events and their role in triggering extreme hydrological events in the typical North China basin, that is, the Luanhe River Basin. Trends of 25 extreme climate indices during 1960–2018 are analysed using the Sen's slope and MK significance test to study the changing characteristics of extreme climate. Characteristics of extreme flood and dry events are examined, encompassing trend analyses at different time scales (seasonal, interannual, decadal) and concentration analysis. Finally, and most significantly, correlation analysis is conducted on extreme climate indices and features of extreme hydrological events, followed by principal component analysis of extreme climate indices, to precisely quantify the impact of extreme climate on the occurrence of extreme hydrological events. The results indicate a warming trend in extreme temperature indices, with a more significant rise in minimum temperatures compared to maximum temperatures. There is a significant decrease in precipitation, but precipitation at higher magnitudes is less affected by the overall reduction in total precipitation. Extreme dry events have markedly increased, particularly concentrated in winter with delayed occurrences, primarily induced by extreme temperature events, that is, warming effects. Conversely, extreme flood events have significantly decreased, mainly concentrated in summer and early autumn, predominantly caused by extreme precipitation and extreme high‐temperature events. The climate and hydrological conditions in the study area have become more extreme and complex. Severe river droughts may occur more frequently in winter, while extreme flooding may happen in summer. Therefore, it is necessary to pay more attention to these developments.

A method for homogenization of complex daily mean temperature data: Application at Beijing Observatory (1915–2021) and trend analysis

AbstractA homogenized daily mean temperature series from 1915 to 2021 at Beijing Observatory (BO) has been developed. A thorough investigation of observation records and historical metadata was carried out to identify specific non‐climatic biases. The inhomogeneities were detected and adjusted with the optimally selected reference stations using a statistical reduction methodology. The results indicated three types of non‐climatic biases in temperature records: the first was the relocation of BO from suburban to urban, which caused positive shifts in temperature records, especially for wintertime; the second arose from different methods for calculating daily mean temperature, which caused different sign biases varying with months; and the last was caused by the transition from manual to automatic measurements with site‐specific biases. The corresponding adjustments due to three type biases ranged from −1.13 to 0.63, −0.29 to 0.23 and −0.13 to 0.00°C, respectively. The new homogenized annual mean temperature series showed a warming trend of 0.199°C/decade during 1915–2021. The trend was more pronounced in winter than in the other three seasons. The warming trend in the new series is greater than those in the previous homogenized series (0.136–0.177°C/decade), primarily due to the more effective adjustment associated with the site relocation, particularly for more urban locations.

Reconciling East Asia's mid-Holocene temperature discrepancy through vegetation-climate feedback

The term “Holocene temperature conundrum” refers to the inconsistencies between proxy-based reconstructions and transient model simulations, and it challenges our understanding of global temperature evolution during the Holocene. Climate reconstructions indicate a cooling trend following the Holocene Thermal Maximum, while model simulations indicate a consistent warming trend due to ice-sheet retreat and rising greenhouse gas concentrations. Various factors, such as seasonal biases and overlooked feedback processes, have been proposed as potential causes for this discrepancy. In this study, we examined the impact of vegetation-climate feedback on the temperature anomaly patterns in East Asia during the mid-Holocene (∼6 ka). By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation, our objective was to isolate the influence of vegetation changes on regional temperature patterns. Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia, resulting in spatially diverse temperature changes during the mid-Holocene and significantly improved model-data agreement. These results highlight the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.

Forecasting Tropical Annual Maximum Wet‐Bulb Temperatures Months in Advance From the Current State of ENSO

AbstractHumid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet‐bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong‐to‐very‐strong El Niño at the end of 2023, with an Oceanic Niño Index of ∼2.0, suggests a 2024 tropical land mean TWmax of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TWmax in specific areas.

Projected changes in rainfall and temperature using CMIP6 models over the Okavango River basin, southern Africa

The Okavango River Basin (ORB) which includes a renowned World Heritage site Okavango Delta, contains highly biodiverse ecosystems. Most of its rural population relies on rain-fed subsistence farming. Limited research has been done on future changes in rainfall and temperature in this region. Here, such changes are analysed for the periods 2030–2059 (near term) and 2070–2099 (long term), relative to the historical period 1985–2014. The analysis is based on the Coupled Model Intercomparison Project Phase 6 (CMIP6), under the shared socioeconomic pathways (SSPs) SSP245 and SSP585. The projected changes vary over the ORB. For rainfall, the models project some significant decreasing trends over Ngamiland in the central/southern ORB, but none are significant over the northern ORB. The significant trends during the near term period include those projected by the model average (-30.60 mm/decade) in March–April (MA) under the SSP585 scenario. Some significant decreasing rainfall trends have also been found in December-February (DJF), but none are significant in October–November (ON). DJF is the main growing season whereas ON (MA) is the onset (end) of the rainy season. For temperature, significant warming trends have been found over both Ngamiland and the northern ORB, with the strongest warming in ON particularly during the near term period. For this ON season over the northern ORB, under the SSP585 (SSP245) scenario, the model average projects a warming trend of 0.56 °C/decade (0.67 °C/decade). These findings may help with the management of agricultural activities, water resources and the highly biodiverse ecosystems in the ORB.

Dynamical response of the southwestern Laurentide Ice Sheet to rapid Bølling–Allerød warming

Abstract. The shift in climate that occurred between the Last Glacial Maximum (LGM) and the Early Holocene (ca. 18–12 kyr BP) displayed rates of temperature increase similar to present-day warming trends. The most rapid recorded changes in temperature occurred during the abrupt climate oscillations known as the Bølling–Allerød interstadial (14.7–12.9 kyr BP) and the Younger Dryas stadial (12.9–11.7 kyr BP). Reconstructing ice sheet dynamics during these climate oscillations provides the opportunity to assess long-term ice sheet evolution in reaction to a rapidly changing climate. Here, we use glacial geomorphological inversion methods (flowsets) to reconstruct the ice flow dynamics and the marginal retreat pattern of the southwestern sector of the Laurentide Ice Sheet (SWLIS). We combine our reconstruction with a recently compiled regional deglaciation chronology to depict ice flow dynamics that encompass the time period from pre-LGM to the Early Holocene. Our reconstruction portrays three macroscale reorganizations in the orientation and dynamics of ice streaming followed by regional deglaciation associated with rapid warming during the Bølling–Allerød interstadial. Initial westward flow is documented, likely associated with an early set of ice streams that formed during the advance to the LGM. During the LGM ice streaming displays a dominant north to south orientation. Ice sheet thinning at ∼15 ka is associated with a macroscale reorganization in ice stream flow, with a complex of ice streams recording south-eastward flow. A second macroscale reorganization in ice flow is then observed at ∼14 ka, in which southwestern ice flow is restricted to the Hay, Peace, Athabasca, and Churchill river lowlands. Rates of ice sheet retreat then slowed considerably during the Younger Dryas stadial; at this time, the ice margin was situated north of the Canadian Shield boundary and ice flow continued to be sourced from the northeast. Resulting from these changes in ice sheet dynamics, we recognize a three-part pattern of deglacial landform zonation within the SWLIS characterized by active ice margin recession, stagnation and downwasting punctuated by local surging (terrestrial ice sheet collapse): the outer deglacial zone contains large recessional moraines aligned with the direction of active ice margin retreat; the intermediate deglacial zone contains large regions of hummocky and stagnation terrain, in some areas crosscut by the signature of local surges, reflecting punctuated stagnation and downwasting; and the inner deglacial zone contains inset recessional moraines demarcating progressive regional ice margin retreat. We attribute these macroscale changes in ice flow geometry and associated deglacial behaviour to external climatic controls during the Bølling–Allerød and Younger Dryas but also recognize the role of internal (glaciological, lithological and topographic) controls in SWLIS dynamics.

Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning.

Rapid urbanisation has led to significant environmental and climatic changes worldwide, especially in urban heat islands where increased land surface temperature (LST) poses a major challenge to sustainable urban living. In the city of Abha in southwestern Saudi Arabia, a region experiencing rapid urban growth, the impact of such expansion on LST and the resulting microclimatic changes are still poorly understood. This study aims to explore the dynamics of urban sprawl and its direct impact on LST to provide important insights for urban planning and climate change mitigation strategies. Using the random forest (RF) algorithm optimised for land use and land cover (LULC) mapping, LULC models were derived that had an overall accuracy of 87.70%, 86.27% and 93.53% for 1990, 2000 and 2020, respectively. The mono-window algorithm facilitated the derivation of LST, while Markovian transition matrices and spatial linear regression models assessed LULC dynamics and LST trends. Notably, built-up areas grew from 69.40 km2 in 1990 to 338.74 km2 in 2020, while LST in urban areas showed a pronounced warming trend, with temperatures increasing from an average of 43.71°C in 1990 to 50.46°C in 2020. Six landscape fragmentation indices were then calculated for urban areas over three decades. The results show that the Largest Patch Index (LPI) increases from 22.78 in 1990 to 65.24 in 2020, and the number of patches (NP) escalates from 2,531 in 1990 to an impressive 10,710 in 2020. Further regression analyses highlighted the morphological changes in the cities and attributed almost 97% of the LST variability to these urban patch dynamics. In addition, water bodies showed a cooling trend with a temperature decrease from 33.76°C in 2000 to 29.69°C in 2020, suggesting an anthropogenic influence. The conclusion emphasises the urgent need for sustainable urban planning to counteract the warming trends associated with urban sprawl and promote climate resilience.

CH4 control and nitrogen removal from constructed wetlands by plant combination

Global warming trend is accelerating. This study proposes a green and economical methane (CH4) control strategy by plant combination in constructed wetlands (CWs). In this study, a single planting of Acorus calamus L. hybrid constructed wetland (HCW-A) and a mixed planting of Acorus calamus L. and Eichhornia crassipes (Mart.) Solms hybrid constructed wetland (HCW-EA) were constructed. The differences in nitrogen removal performance and CH4 emissions between HCW-A and HCW-EA were compared and analyzed. The findings indicated that HCW-EA demonstrated significant improvements over HCW-A, with NH4+-N and TN removal rates increasing by 21.61% and 16.38% respectively, and CH4 emissions decreased by 43.36%. The microbiological analysis results showed that plant combination promoted the enrichment of Proteobacteria, Alphaproteobacteria and Bacillus. More nitrifying bacteria carrying nxrA genes and denitrifying bacteria carrying nirK genes accelerated the nitrogen transformation process. In addition, the absolute abundance ratio of pmoA/mcrA increased, reducing the release of CH4.

The River Runner: a low-cost sensor prototype for continuous dissolved greenhouse gas measurements

Abstract. Freshwater ecosystems are sources of the two most relevant greenhouse gases (GHGs): CO2 and CH4. Understanding the importance of freshwater ecosystems in the global carbon cycle and their role in global warming trends requires the accurate quantification of gas fluxes from the water phase to the atmosphere. These fluxes depend on the gas exchange velocity and the concentration gradient between the phases, which both cause high spatio-temporal variability in fluxes. On a global scale, the estimation of fluxes is limited by the lack of cheap and accurate methods to measure dissolved gas concentrations. Low-cost sensors, as an alternative to expensive gas analysers, are available; however, to date, the in situ performance of such sensors has been poorly examined. Here, we present an inexpensive data-logging sensor prototype that provides continuous measurements of dissolved CO2 and CH4 in submerged environments. Gas measurements are done in a confined gas space, which is rapidly equilibrated with the water phase through a single-layer polytetrafluoroethylene (PTFE) membrane, by a miniature non-dispersive infrared (NDIR) sensor for CO2 (Sunrise sensor, Senseair, Sweden) and a cheap metal oxide sensor for CH4 (TGS2611-E, Figaro Engineering Inc., Japan). Pressure, temperature and humidity are measured to correct raw sensor readings. For freshwater, the dissolved gas concentration is directly obtained from the measured molar fraction and temperature and pressure readings. In air, we measured the molar fraction of CO2 in a range from 400 to 10 000 ppm and the molar fraction of CH4 in a range from 2 to 50 ppm with an accuracy of ± 58 and ± 3 ppm respectively. We successfully used our prototype to measure diurnal variations in dissolved CO2 in a natural stream. We further calibrated the CH4 sensor for in situ use at concentrations ranging from 0.01 to 0.3 µmol L−1. Underwater, we were able to measure the molar fraction of CH4 in the prototype head with an accuracy of ± 13 ppm in the range from 2 to 172 ppm. The underwater measurement error of CH4 is always higher than for the same concentration range in air, and CH4 is highly overestimated below 10 ppm. At low CH4, humidity was the most important influence on the TGS2611-E sensor output in air, whereas temperature became the predominant factor underwater. We describe the response behaviour of low-cost sensors in submerged environments and report calibration methods to correct for temperature and humidity influence on the sensor signal if used underwater. Furthermore, we provide do-it-yourself instructions to build a sensor for submerged continuous measurements of dissolved CO2 and CH4. Our prototype does not rely on an external power source, and we anticipate that such robust low-cost sensors will be useful for future studies of GHG emissions from freshwater environments.

Spatial and temporal evolution of heatwaves in Taiwan in a changing climate using multi-dimensional complementary ensemble empirical mode decomposition

Recent decades have witnessed noticeable warming in highly developed cities. Taiwan, a densely populated island characterized by its monsoon-dominated climate and unique mountainous topography, has experienced an average temperature increase of 1.0–1.4 °C in the last century, significantly exceeding the global average. This research introduces the Multi-dimensional Complementary Ensemble Empirical Mode Decomposition (MCEEMD) algorithm, providing a novel approach for analyzing gridded climate data and uncovering spatiotemporal temperature patterns in Taiwan. This methodology offers valuable insights into the localized impacts of climate change. The spatiotemporal evolution of temperature from 1960 to 2020 is analyzed to estimate the warming trend associated with climate change. Essential factors related to the urban heat island (UHI) effect, which leads to temperature disparities between urban and rural areas, are also examined. Warming and the UHI effect are critical components of climate change, increasing the likelihood of extreme weather events in urban areas. The study investigates extreme weather events from 1960 to 2020, focusing on heatwaves. It projects changes in the frequency and duration of heatwaves for the mid (2046–2065) and late 21st century (2081–2100). Notably, Taipei experienced a warming trend exceeding 1.5°C in the 2010s, which was likely influenced by urbanization. Additionally, areas experiencing the sharpest increase in heatwave events (more than 1.5 events) by 2000 were predominantly in highly developed cities across northern and southern Taiwan. Further analysis under the RCP8.5 scenario suggests that, by the end of the 21st century, heatwave events could last for at least 20 days in many regions, with the potential to extend to nearly a month during the summer.

Secular changes in the tropical stratospheric water vapour entry induced by the Indo-Pacific warm pool warming

A decreasing trend in the tropical (30°S ∼ 30°N) stratospheric water vapour (SWV) entry in recent four decades (from 1984 to 2020) is detected based on the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) measurements and the ERA5 reanalysis dataset using linear regression and Ensemble Empirical Mode Decomposition (EEMD) analysis. With the concurrent warming of the sea surface temperature (SST), the Indo-Pacific warm pool (IPWP) appears to be the most significant region among the tropical oceans based on correlation analysis. >43% of the decreasing tropical lower SWV trend is likely to be related to the IPWP SST warming. To validate this relationship, two groups of idealized runs are carried out with version 4 of the Whole Atmosphere Community Climate Model (WACCM4) and version 5 of the Community Atmosphere Model (CAM5). Both simulations agree with the observational-based linkage. The IPWP-SST-warming forced simulations show that the temperature in the tropical tropopause has decreased at the rate of around 0.318 K per decade in the coldest point region, as the tropical convection over the IPWP has become more vigorous and excited stronger equatorial waves to produce adiabatic cooling around tropopause. This cooling tropical tropopause leads to a dehydrating tropical lower stratosphere at the rate of 0.025 ppmv per decade, as expected by the freeze-drying mechanism. These results imply the substantial warming trend of IPWP is an important factor for the long-term trend of the tropical SWV entry under climate change, and a better representation of this relationship in the model is critical for the SWV projection under future climate scenarios.

Fast Enhancement of the Stratification in the Indian Ocean over the Past 20 Years

Abstract Indian Ocean (IO) stratification has important effects on the air–sea interaction, ocean dynamics, and ecology. It is, therefore, of significance to investigate the changes in IO stratification. In this study, we use ensemble empirical mode decomposition (EEMD) to extract the nonlinear long-term trend in the upper IO stratification quantified by potential energy anomalies. The results show that the strengthening of the stratification is spatially and temporally nonuniform. Specifically, the trend of stratification intensified gradually before 1996, but accelerated rapidly after 1996. Temperature and salinity changes play a crucial role in the fast enhancement of stratification and its regional differences. Temperature variations dominate the stratification trend in ∼90% of the IO area, while the contributions of salinity changes are mainly in the southeast Indian Ocean (SEIO). Vertically, the rapid enhancement of stratification is caused by the trend of temperature and salt in the upper 400 m. We further perform temperature budget analysis and find that the warming trend in the upper 400 m south of the IO is mainly modulated by vertical advection and meridional advection, while the warming in the north of the IO is mainly induced by air–sea heat fluxes. Salinity budget analysis shows that ocean advection has played a primary role in modulating SEIO salinity over the past 20 years.

The Contrast Precipitation Patterns in Yangtze River Valley Between the Two La Niña Decaying Summers in 2021 and 2022

AbstractAlthough the summers of 2021 and 2022 are both in the two successive La Niña decaying stages and under the same climate background of negative Pacific Decadal Oscillation (PDO) phase and global warming trend, they exhibit significantly different and even opposite precipitation patterns in the Yangtze River Valley (YRV) as well as in the Indian monsoon region (IMR). In contrast to the abundant precipitation and lower temperature in the YRV in summer 2021, in summer 2022 the YRV experiences severe drought and extremely high temperatures, which is also accompanied by Mega‐floods in the IMR. This study identifies the joint influence of sea surface temperature anomalies (SSTAs) in Niño4 and Barents Sea (BS) regions as the underlying cause for the contrast YRV precipitation anomalies in the summers of 2021 and 2022. Specifically, the cold SSTAs in both Niño4 and BS regions in summer 2021 favor stronger and southward shifted western North Pacific subtropical high (WNPSH), leading to more precipitation in the YRV, which is however generally reversed but more intense in summer 2022 because of the synergistic effect of cold Niño4 and warm BS SSTAs. Moreover, the induced extreme precipitation in the IMR in summer 2022, which is absent in summer 2021 due to the offsetting effect of cold SSTAs in both Niño4 and BS regions, in turn further strengthens the anomalous atmospheric circulations via its released large diabatic heating and serves as a relay pathway for the dramatic drought and heat wave in the YRV.

An Improved Ensemble of Land Surface Air Temperatures Since 1880 Using Revised Pair-Wise Homogenization Algorithms Accounting for Autocorrelation

Abstract Land surface air temperatures (LSAT) inferred from weather station data differ among major research groups. The estimate by NOAA’s monthly Global Historical Climatology Network (GHCNm) averages 0.02°C cooler between 1880 and 1940 than Berkeley Earth’s and 0.14°C cooler than the Climate Research Unit estimates. Such systematic offsets can arise from differences in how poorly documented changes in measurement characteristics are detected and adjusted. Building upon an existing pairwise homogenization algorithm used in generating the fourth version of NOAA’s GHCNm(V4), PHA0, we propose two revisions to account for autocorrelation in climate variables. One version, PHA1, makes minimal modification to PHA0 by extending the threshold used in breakpoint detection to be a function of LSAT autocorrelation. The other version, PHA2, uses penalized likelihood to detect breakpoints through optimizing a model-selection problem globally. To facilitate efficient optimization for series with more than 1000 time steps, a multiparent genetic algorithm is proposed for PHA2. Tests on synthetic data generated by adding breakpoints to CMIP6 simulations and realizations from a Gaussian process indicate that PHA1 and PHA2 both similarly outperform PHA0 in recovering accurate climatic trends. Applied to unhomogenized GHCNmV4, both revised algorithms detect breakpoints that correspond with available station metadata. Uncertainties are estimated by perturbing algorithmic parameters, and an ensemble is constructed by pooling 50 PHA1- and 50 PHA2-based members. The continental-mean warming in this new ensemble is consistent with that of Berkeley Earth, despite using different homogenization approaches. Relative to unhomogenized data, our homogenization increases the 1880–2022 trend by 0.16 [0.12, 0.19]°C century−1 (95% confidence interval), leading to continental-mean warming of 1.65 [1.62, 1.69]°C over 2010–22 relative to 1880–1900. Significance Statement Accurately correcting for systematic errors in observational records of land surface air temperature (LSAT) is critical for quantifying historical warming. Existing LSAT estimates are subject to systematic offsets associated with processes including changes in instrumentation and station movement. This study improves a pairwise homogenization algorithm by accounting for the fact that climate signals are correlated over time. The revised algorithms outperform the original in identifying discontinuities and recovering accurate warming trends. Applied to monthly station temperatures, the revised algorithms adjust trends in continental mean LSAT since the 1880s to be 0.16°C century−1 greater relative to raw data. Our estimate is most consistent with that from Berkeley Earth and indicates lesser and greater warming than estimates from NOAA and the Met Office, respectively.

Seasonal trends in the Early Twentieth Century Warming (ETCW) in a centennial instrumental temperature record from Central Europe

The goal of the present paper is to investigate whether any objectively defined and statistically significant changes can be discovered in one of the longest homogenized instrumental temperature records in East-Central Europe. Thus, it is hoped that the present analysis will add to earlier attempts and elucidate the persistence of the warming period observed in the early 20th century. Similar to the global tendency, the Early Twentieth Century Warming (hereinafter, ETCW) period can be identified between 1931 and 1951 in the annual mean temperature time series of Keszthely, a small town in Hungary. The Mann-Kendall trend test was used to determine whether a monotonic trend was present, as it is not possible to regard the residuals of the linear trend as normally distributed. A significant rising trend can be observed in the warming period in spring of the years between 1925 and 1951. In case of summer and autumn, this period cannot be characterized as having any significant identifiable trend. A rise in the mean can, however, be recognized. Overall, the specific regional manifestation of the global ETCW may clearly be illustrated in this study via detailed statistical analysis of the temperature records for Keszthely, a location with one of the longest temperature records in Hungary. However, other regions surrounding Hungary show similar climatic trends, emphasizing the fact that the behaviour presented here is not unique to Central and Eastern Europe.

Process-Based Modeling of Phenology and Radial Growth in Pinus tabuliformis in Response to Climate Factors over a Cold and Semi-Arid Region.

(1) Background: Climate change significantly impacts the phenology and dynamics of radial tree growth in alpine dryland forests. However, there remains a scarcity of reliable information on the physiological processes of tree growth and cambial phenology in response to long-term climate change in cold and semi-arid regions. (2) Methods: We employed the process-based Vaganov-Shashkin (VS) model to simulate the phenology and growth patterns of Chinese pine (Pinus tabuliformis) in the eastern Qilian Mountains, northeastern Tibetan Plateau. The model was informed by observed temperature and precipitation data to elucidate the relationships between climate factors and tree growth. (3) Results: The simulated tree-ring index closely aligned with the observed tree-ring chronology, validating the VS model's effectiveness in capturing the climatic influences on radial growth and cambial phenology of P. tabuliformis. The model outputs revealed that the average growing season spanned from mid-April to mid-October and experienced an extension post-1978 due to ongoing warming trends. However, it is important to note that an increase in the duration of the growing season did not necessarily result in a higher level of radial growth. (4) Conclusions: While the duration of the growing season was primarily determined by temperature, the growth rate was predominantly influenced by water conditions during the growing season, making it the most significant factor contributing to ring formation. Our study provides valuable insights into the potential mechanisms underlying tree growth responses to climate change in cold and semi-arid regions.

Investigating extreme marine summers in the Mediterranean Sea

Abstract. The Mediterranean Sea (MS) has undergone significant surface warming, particularly pronounced during summers and associated with devastating impacts on marine life. Alongside the ongoing research on warming trends and marine heatwaves (MHWs), here we address the importance of understanding anomalously warm conditions also on the seasonal timescale. We propose the concept of extreme marine summers (EMSs) and investigate their characteristics in the MS, using sea surface temperature (SST) reanalysis data spanning 1950–2020. We define EMSs at a particular location, as the summers with a mean summer SST exceeding the 95th percentile. A marine summer may become extreme, under various SST substructures. Results show that, in most of the basin, EMSs are formed primarily due to the warmer summer days being warmer than normal. Areas where the warmest (coldest) part of the SST distribution is more variable experience EMSs primarily due to the warmest (coldest) part of the distribution being anomalously warm. MHWs occurring within EMSs are more intense, longer lasting, and more frequent than usual mainly in the northern MS regions. These enhanced MHW conditions occur mainly within the warmest part of the SST distribution. By means of temporal coverage of MHW conditions, a more pronounced occurrence of MHWs in EMSs is found for the central and eastern basin where up to 55 % of MHW days over 1950–2020 fall within EMSs. The role of air–sea heat fluxes in driving EMSs is quantified through a newly proposed metric. Results suggest that surface fluxes primarily drive EMSs in the northern half of the MS, while oceanic processes play a major role in southern regions. Upper-ocean preconditioning also contributes to the formation of EMSs. Finally, a detrended dataset was produced to examine how the SST multi-decadal variability affects the studied EMS features. Despite leading to warmer EMSs basin-wide, the multi-decadal signal does not significantly affect the dominant SST substructures during EMSs. Results also highlight the fundamental role of latent heat flux in modulating the surface heat budget during EMSs, regardless of the long-term trends.