Regional Temperature Changes Research Articles

The first firn core from Peter I Island – capturing climate variability across the Bellingshausen Sea

Abstract. Peter I Island is situated in the Bellingshausen Sea, a region that has experienced considerable climate change in recent decades. Warming sea surface temperatures and reduced sea ice cover have been accompanied by warming surface air temperature, increased snowfall, and accelerated mass loss over the adjacent ice sheet. Here we present data from the first firn core drilled on Peter I Island, spanning the period 2001–2017 CE. The stable water isotope data capture regional changes in surface air temperature and precipitation (snow accumulation) at the site, which are highly correlated with the surrounding Amundsen–Bellingshausen seas and the adjacent Antarctic Peninsula (r > 0.6, p < 0.05). The firn core data, together with the unique in situ data from an automatic weather station, confirm the high skill of the ERA5 reanalysis in capturing daily mean temperature and inter-annual precipitation variability, even over a small sub-Antarctic island. This study demonstrates the suitability of Peter I Island for future deep-ice-core drilling, with the potential to provide a valuable archive to explore ice–ocean–atmosphere interactions over decadal to centennial timescales for this dynamic region.

Latitudinal gradients in air density create invisible topography at sea level, affecting animal flight costs.

Regional patterns in wind underpin the low-cost migratory flyways of billions of birds and insects,1,2,3 but the effect of large-scale changes in temperature on flight is unknown. Flight costs should increase with rising temperatures because lift decreases as density decreases, whereas weight remains unchanged. The effects of density are well-established in the context of high-altitude movements and migration.4,5,6,7 Here, we examine the impact of air density on low-flying birds in relation to seasonal, regional, and global changes in temperature. We deployed multi-sensor loggers on red-tailed tropicbirds (Phaethon rubricauda), a large and widely distributed seabird breeding year round in Mauritius. Seasonal changes in air density caused very small differences in flight costs (1%-2%, estimated using aeronautical models) despite being the major driver of seasonal differences in wingbeat frequency. Flight costs should vary in space as well as time, and aeronautical models predicted ≥10% variation in power across the tropicbird's range due to latitudinal temperature gradients. Changes in air density can therefore modulate flight costs across regional scales, even when birds are operating close to sea level. Indeed, creating a 20-year climatology of air density at sea level revealed that temperature gradients cause effective altitude to vary by >2km at a global scale within a given season. This "invisible topography" at sea level could influence the biogeography of flight morphologies, particularly the distribution of birds with the highest flight costs, which generally occur in regions with relatively high air density.

To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles?

AbstractIt depends. The Intergovernmental Panel on Climate Change's (IPCC) Assessment Report Six (AR6) took a step toward ending so‐called ‘model democracy’ by discounting climate models that are too warm over the historical period (i.e., models that ‘run hot’) when making projections of global temperature change. However, the IPCC did not address whether this procedure is reliable for other quantities. Here, we explore the implications of weighting climate models according to their skill in reproducing historical global‐mean surface temperature using three other climate variables of interest: global average precipitation change, regional average temperature change, and regional average precipitation change. We find that the temperature‐based weighting scheme leads to an improved prediction of global average precipitation, though we show that this prediction could be overconfident. On regional scales, we find a heterogeneous pattern of error reduction in future regional precipitation. This stands in sharp contrast with the broad regional pattern of error reduction in future temperature projections, though we do find regions where error is not significantly reduced. Our results demonstrate that practitioners using weighted climate model ensembles for climate projections must take care when weighting by temperature alone, lest they produce unreliable climate projections that result from an inappropriate weighting procedure.

A century-long China homogenized daily surface air temperature dataset (CUG-CMA CHDT)

Daily meteorological observation data of the early period (pre-1950) were critically important for investigating the long-term trends and multi-decadal scale variability of extreme climate events. The high-resolution surface air temperature (SAT) data for time period before 1950 are lacking in China. We extended the SAT observations of China back to 1840 through developing a pre-1950 daily SAT dataset. The early-period daily SAT were manually corrected for the input and clerical errors, and then according to the length or coverage of time, the main series for each of the cities was determined. The observation time system of unknown sites was determined by the minimum difference method. After these operations, the data of all sites were unified into the same format. By using the ridge regressions established based on data from modern reference stations, the missing maximum temperature (Tmax) and minimum temperature (Tmin) were interpolated. The early-period data were combined with modern data to form the long-term daily SAT dataset of 1840–2020 in China. RHtest software was used to detect and adjust the inhomogeneities in the station data series. Finally, the century-long homogenized daily SAT dataset including 45 key city stations in China was obtained. Among the stations, there are 20 stations with observation record more than one hundred years. The length of temperature observation series of 17 stations is between 80 and 100 years. The series length of the remaining 7 stations is between 68 and 80 years. Finally, the angular distance weighting (ADW) method was used to interpolate the data into grid products, and the grid size is 2.5 ° × 2.5 °. The dataset was named CUG-CMA CHDT, which is applicable in monitoring, studies and assessments of regional extreme temperature change and variability in China.

Subtle changes in plant diversity in the Bavarian Alps over the past eight decades.

Historical resurveys represent a unique opportunity to analyze vegetation dynamics over longer timescales than is typically achievable. Leveraging the oldest historical dataset of vegetation change in the Bavarian Alps, Germany, we address how environmental conditions, vegetation composition, and functional diversity in the calcareous grasslands of the Schachen region have changed across different elevational ranges over an 83-year timeframe. We document changes in regional average temperature and precipitation. We use indicator values (IV) for species' ecological preferences and their palatability to grazers to infer local conditions (temperature, soil moisture/fertility, and grazing regime). We further estimate changes in temporal beta-diversity and functional trait community composition between historical (1936) and contemporary (2019) surveys in two elevational (subalpine and alpine) belts. Both subalpine and alpine sites became drier; subalpine sites also became warmer with more palatable plants. Species occurrence and abundance in the Schachen region has not changed substantially over time despite changing macroclimate and local environmental conditions under anthropogenic change. Yet these grasslands have experienced several "invisible" changes in functional composition over the past 80 years. As the Schachen has become drier, species with traits related to drought tolerance and animal-based dispersal have increased in dominance. Specifically, in alpine sites, community-weighted means revealed that with low fecundity, higher potential for endo- and epizoochory (seed dispersal via animal gut and fur, respectively), higher foliar frost tolerance, and deeper dormancy increased in dominance. Similar trends were found for increasing dominance of low fecundity, epizoochorous species in subalpine sites. Vegetation data from resurveying historical plots in combination with changes in local conditions, classic biodiversity indices, and functional trait indices can provide more holistic insights into changes in the environment and potential impacts of those environmental changes on long-term plant community and functional diversity.

Matlab-Simulink Model of CHMT for Internal Climate in Greenhouses

Over the past twenty years, Kenya's food security has been threatened by the sub-division of land into tiny areas and the clearance of forests to make way for settlement. These actions have an impact on soil moisture, rainfall patterns, and regional temperature changes. Clear response plans and adaption techniques have been required to address the threats that have arisen. Greenhouse farming, where warmer temperatures are attained and the impact of unfavourable weather conditions on plants is mitigated by the enclosure, is one strategy being used to combat the production of food and climate change. Nevertheless, crop production and quality are negatively impacted by traditional techniques of regulating temperature and humidity through arbitrary opening and closing of the greenhouse walls. In light of this, the goal of this research was to enhance greenhouse farming as it exists today by implementing a dynamic, adjustable system that would create ideal climate conditions for plant growth. This mostly entailed controlling the greenhouse's humidity, temperature, and vapour pressure deficit to the ideal ranges needed by various plants. The humidity and air temperature within the greenhouse were the controlled microclimate conditions. These were accomplished by simulating the convectional heat transfer and mass transfer that occur inside the greenhouse to control the temperature and humidity, and by developing mathematical model utilizing differential equations. Proportional Integral Derivative (PID) was utilized to automatically modify SIMULINK, a block-based modelling and simulation tool. Regardless of the different external conditions, the numerical values for internal temperature and humidity were calculated and graphically depicted. The model made it possible to modify the outcomes according to the needs of the plant. To increase crop productivity in greenhouse farming, it was suggested that a physical prototype model be constructed and integrated into the greenhouse construction.

Responses of Lower-Stratospheric Water Vapor to Regional Sea Surface Temperature Changes

Abstract The variability of stratospheric water vapor (SWV) plays a crucial role in stratospheric chemistry and Earth’s energy budget, strongly influenced by sea surface temperature (SST). In this study, we systematically investigate the response of lower-SWV (LSWV) to regional sea surface temperature changes using idealized SST patch experiments within a climate model. The results indicate that LSWV is most sensitive to tropical sea surface temperature, with the strongest response occurring in late autumn and early winter. Warming of the tropical Indian Ocean and western Pacific (WP) leads to stratospheric drying, while warming of the tropical Atlantic (TA) and eastern Pacific results in stratospheric moistening. The drying impact on LSWV due to warming in the western Pacific Ocean exceeds the wet effect in the eastern Pacific Ocean by approximately 60%. The variations in tropical SST influence LSWV by modulating the temperature at the tropical tropopause layer, especially over the Indo-Pacific warm pool through Matsuno–Gill responses. Furthermore, the response of LSWV to tropical SST changes exhibits nonnegligible nonlinearity, which indicates the importance of nonlinearity in determining the LSWV response to global surface warming. Significance Statement In this study, we explore how changes in the temperature of the ocean’s surface can affect the amount of water vapor in the stratosphere, a layer of Earth’s atmosphere. Understanding this relationship is important because water vapor in the stratosphere can influence both our climate and the chemistry of the atmosphere. Using a climate model, we found that water vapor in the lower stratosphere is especially responsive to temperature changes in tropical ocean regions. Specifically, when the Indian Ocean and the western Pacific get warmer, the stratosphere tends to get drier. On the other hand, warming in the Atlantic and eastern Pacific leads to more moisture in the stratosphere. The way these changes add up is complex and not simply a sum of individual parts, especially in tropical warm pool regions. Our findings have implications for how we understand and predict the impacts of climate change on stratospheric water vapor.

Probabilistic UK Climate Projections Conditioned on Global Warming Levels

AbstractProbabilistic projections from the UK Climate Projections 2018 are presented for four global warming levels (GWLs) at 1.5, 2, 3, and 4°C above the 1850–1900 baseline. Our results show how uncertainties associated with climate models and four representative concentration pathways (RCP) emission scenarios translate to UK regional scale changes in maximum temperature and precipitation, with data also available for minimum and mean temperatures, humidity and surface net downward shortwave radiation flux. We compare weighting the likelihood of RCPs based on (hypothetical) policy decisions, against our baseline assumption that each RCP is equally likely. Differences between weighted and unweighted GWL distributions are small, particularly in relation to the full breadth of uncertainties that are incorporated into the probabilistic projections. Finally we quantify the relative importance of scenario, model and internal variability on regional projected GWLs and show that uncertainty associated with an uncertain climate response to forcings dominates at all GWLs.

Decoupling Warming and Monsoon Precipitation Over the Last 3110 Years in Northwestern Yunnan Province, Southwestern China

AbstractUnderstanding the variability and related dynamic mechanisms of the Indian summer monsoon evolution over the past millenniums is crucial for disaster prevention and mitigation in the context of strengthening global warming. Here, we present a high‐resolution hydroclimate reconstruction over the past 3110 years in northwestern Yunnan Province, southwestern China, based on grain size analysis using the End‐member modeling algorithm and other environmental proxies. The results indicate that the temperature in northwestern Yunnan Province generally decreased since 3110 cal. yr BP, aligning with other temperature records on regional and global scales. Precipitation in the study area remained relatively stable before 1000 cal. yr BP, but exhibited an obvious out‐phase change compared with the temperature records over multidecadal to centennial timescale. While after 1000 cal. yr BP, the precipitation steadily increased, revealing the hydroclimate pattern of notably dry Medieval Warm Period (MWP) and relatively wet Little Ice Age (LIA) in the study area. The decoupling combination of temperature and precipitation spanning the MWP and LIA in southwestern China contrasts with that in the East Asian summer monsoon area and the Indian subcontinent which is also controlled by the Indian summer monsoon, indicating the spatial heterogeneity of precipitation in the Asian summer monsoon region. The discussion about dynamic mechanisms points out that solar activity emerges as a significant factor influencing regional temperature changes, and El Niño‐Southern Oscillation and Intertropical Convergence Zone migration jointly impact the precipitation change in the study area and the hydroclimate discrepancy in the Asian summer monsoon region.

Tropical Warming and Intensification of the West African Monsoon During the Miocene Climatic Optimum

AbstractStudying monsoon dynamics during past warm time periods such as the Miocene Climatic Optimum (MCO; ∼16.9–14.5 Ma) could greatly aid in better projecting monsoon intensity, in the context of future greenhouse warming. However, studies on regional MCO temperature change and its effect on the monsoons during this time period are lacking. Here, we present the first high‐resolution, low‐latitude record of sea surface temperature (SST) and paleoceanographic change covering the Miocene Climatic Optimum, in the eastern equatorial Atlantic, at Ocean Drilling Program Site 959, based on TEX86 paleothermometry. SSTs were ∼1.5°C warmer at the onset of the MCO (16.9 Ma) relative to the pre‐MCO (∼18.3–17.7 Ma). This warming was accompanied by a transient increase in %total organic carbon. Prior to the MCO, sediment composition, geochemical proxy data as well as dinoflagellate cyst assemblages imply a productive surface ocean at Site 959. Immediately following the MCO onset (∼16.9–16.5 Ma), we record an intensification of the West African Monsoon (WAM) characterized by higher amplitude variability in all proxy records on precession to obliquity timescales. We interpret increased orbital‐scale SST, biogenic Ba and dinocyst assemblage variability to represent intensification of equatorial upwelling, forced by the WAM strength. Furthermore, higher SSTs during eccentricity maxima correlate to increased relative abundances of the warm and stratification‐favoring dinocyst Polysphaeridium zoharyi, during periods of low WAM intensity. Finally, while long‐term SSTs decline toward the middle Miocene, maximum SSTs and Polysphaeridium zoharyi abundances occur during MCO peak warming at ∼15.6 Ma.

Tree-ring based summer temperature variability since 1790 CE in the Hindu Kush region of northern Pakistan.

The Hindu Kush high-altitude regions of Pakistan are currently experiencing severe consequences as a result of global warming. In this sense, increasing soil erosion and the quick melting of glaciers are two particularly evident effects. In such a scenario, understanding long-term temperature changes is crucial for making accurate forecasts about how the Hindu Kush region may experience regional temperature changes in the future. In this study, the climate tree-ring width (TRW) analysis designated a positive and significant correlation (r = 0.622, p < 0.001) between the TRW chronology and the June to September (summer) mean maximum temperature (MMT). Using the tree-ring width of Pinus wallichiana A. B. Jackson, we reconstructed summer temperatures in the Hindu Kush region from 1790 CE. Statistical analysis showed that the reconstruction model has explained 38.7% of the climate variance during the instrumental period of 1967 to 2018 CE. Five extremely warm summer periods (≥ 4 years; before the instrumental period 1967-2018 CE) of 1804-1830, 1839-1862, 1876-1879, 1905-1910, 1923-1935 CE, and six cold summer periods of 1790-1803, 1832-1838, 1863-1875, 1880-1904, 1911-1922, and 1936-1945 CE have been observed during the past 229 years. Individually, the year 1856 CE experienced severe warmth (31.85°C), whereas 1794 CE was relatively cooler (29.60°C). The spectral multi-taper method (MTM) shows significant (p < 0.05) cycles, which take place about every 9.3, 5.7, 4.2, and 3.6 years. In particular, the 9.3-year cycle, which closely aligns with the 11-year solar activity cycle, suggests a potential correlation between solar activity and local temperature fluctuations. Moreover, our reconstruction demonstrates a significant degree of consistency when compared to actual climate data and regional temperature reconstruction series, reporting a strong logic of trust in the reliability and accuracy of our findings. This evidence reaffirms that our reconstruction shows significant and dependable regional temperature signals, notably being representative for the Hindu Kush region.

Assessing Regional-Scale Heterogeneity in Blue–Green Water Availability under the 1.5°C Global Warming Scenario

Abstract The 2015 Paris Agreement outlined limiting global warming to 1.5°C relative to the preindustrial levels, necessitating the development of regional climate adaptation strategies. This requires a comprehensive understanding of how the 1.5°C rise in global temperature would translate across different regions. However, its implications on critical agricultural components, particularly blue and green water, remains understudied. This study investigates these changes using a rice-growing semiarid region in central India. The aim of this study is to initiate a discussion on the regional response of blue–green water at specific warming levels. Using different global climate models (GCMs) and shared socioeconomic pathways (SSPs), the study estimated the time frame for reaching the 1.5°C warming level and subsequently investigated changes in regional precipitation, temperature, surface runoff, and blue–green water. The results reveal projected reductions in precipitation and surface runoff by approximately 5%–15% and 10%–35%, respectively, along with decrease in green and blue water by approximately 12%–1% and 40%–10%, respectively, across different GCMs and SSPs. These findings highlight 1) the susceptibility of blue–green water to the 1.5°C global warming level, 2) the narrow time frame available for the region to develop the adaptive strategies, 3) the influence of warm semiarid climate on the blue–green water dynamics, and 4) the uncertainty associated with regional assessment of a specific warming level. This study provides new insights for shaping food security strategies over highly vulnerable semiarid regions and is expected to serve as a reference for other regional blue/green water assessment studies. Significance Statement This study helps to drive home the message that a global agreement to limit the warming level to 1.5°C does not mean local-scale temperature (and associated hydrological) impacts would be limited to those levels. The regional changes can be more exaggerated and uncertain, and they also depend on the choice of the climate model and region. Therefore, local-scale vulnerability assessments must focus on the multidimensional assessment of a 1.5°C warmer world involving different climate models, climate-sensitive components, and regions. This information is relevant for managing vulnerable agricultural systems. This study is among the first to investigate the critical agricultural components such as the blue–green water over a semiarid Indian region, and the findings and methodology are expected to be transferable for performing regional-scale assessments elsewhere.

Physical science research needed to evaluate the viability and risks of marine cloud brightening.

Marine cloud brightening (MCB) is the deliberate injection of aerosol particles into shallow marine clouds to increase their reflection of solar radiation and reduce the amount of energy absorbed by the climate system. From the physical science perspective, the consensus of a broad international group of scientists is that the viability of MCB will ultimately depend on whether observations and models can robustly assess the scale-up of local-to-global brightening in today's climate and identify strategies that will ensure an equitable geographical distribution of the benefits and risks associated with projected regional changes in temperature and precipitation. To address the physical science knowledge gaps required to assess the societal implications of MCB, we propose a substantial and targeted program of research-field and laboratory experiments, monitoring, and numerical modeling across a range of scales.

Identifying Climate Impacts From Different Stratospheric Aerosol Injection Strategies in UKESM1

AbstractStratospheric Aerosol Injection (SAI) is a proposed method of climate intervention aiming to reduce the impacts of human‐induced global warming by reflecting a portion of incoming solar radiation. Many studies have demonstrated that SAI would successfully reduce global‐mean surface air temperatures; however the vast array of model scenarios and strategies result in a diverse range of climate impacts. Here we compare two SAI strategies—a quasi‐ equatorial injection and a multi‐latitude off‐equatorial injection—simulated with the UK Earth System Model (UKESM1), both aiming to reduce the global‐mean surface temperature from that of a high‐end emissions scenario to that of a moderate emissions scenario. We compare changes in the surface and stratospheric climate under each strategy to determine how the climate response depends on the injection location. In agreement with previous studies, an equatorial injection results in a tropospheric overcooling in the tropics and a residual warming in the polar regions, with substantial changes to stratospheric temperatures, water vapor and circulation. Previous comparisons of equatorial versus off‐equatorial injection strategies are limited to two studies using different versions of the Community Earth System Model. Our study evaluates how the climate responds in UKESM1 under these injection strategies. Our results are broadly consistent with previous findings, concluding that an off‐equatorial injection strategy can minimize regional surface temperature and precipitation changes relative to the target. We also present more in‐depth analysis of the associated changes in Hadley Circulation and regional temperature changes, and call for a new series of inter‐model SAI comparisons using an off‐equatorial strategy.

Global and regional temperature change over the past 4.5 million years.

Much of our understanding of Cenozoic climate is based on the record of δ18O measured in benthic foraminifera. However, this measurement reflects a combined signal of global temperature and sea level, thus preventing a clear understanding of the interactions and feedbacks of the climate system in causing global temperature change. Our new reconstruction of temperature change over the past 4.5 million years includes two phases of long-term cooling, with the second phase of accelerated cooling during the Middle Pleistocene Transition (1.5 to 0.9 million years ago) being accompanied by a transition from dominant 41,000-year low-amplitude periodicity to dominant 100,000-year high-amplitude periodicity. Changes in the rates of long-term cooling and variability are consistent with changes in the carbon cycle driven initially by geologic processes, followed by additional changes in the Southern Ocean carbon cycle.

Limited reversal of regional climate signals in overshoot scenarios

Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5 °C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5 °C above pre-industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project we find that temperature changes are largely reversible in many regions, but also report significant land–ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.

Attribution of differences in observed warming among subregions of China and observationally constrained projection

AbstractUnderstanding the impact of different external forcings on regional temperature changes in China and constraining future changes is important for formulating targeted climate mitigation policies. We conducted a detection and attribution analysis to examine the effects of different external forcings on the differences in warming across China and seven subregions. This analysis spanned from 1965 to 2014 and used observations as well as data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The signals of anthropogenic (ANT) forcing can be detected and separated from natural (NAT) forcing in all regions, and the effect of greenhouse gases are found to account for a significant portion of the observed warming in these regions. In the Yangtze River Basin, southeast China and southwest China, the observed warming trends are lower than other subregions. This can be attributed to the relatively weak impact of greenhouse gases, resulting in a temperature increase of only 0.51°C in the Yangtze River Basin, which accounts for 48.57% of the observed warming. While both southeast China and southwest China experience a cooling effect of aerosols, leading to temperature decreases of 0.20 and 0.53°C, respectively, even though the signal of aerosol forcing is not detected. In terms of future projection, the use of attribution constraint approach effectively corrects the biases of the CMIP6 model simulation and reduces projection uncertainty in China and most subregions under the new shared socioeconomic pathway (SSP) SSP2‐4.5 and SSP5‐8.5. The Tibetan Plateau has the largest reduction of the uncertainty range among seven subregions, with the decrease of 39.02% under SSP2‐4.5 scenario in the long‐term (2081–2098). In addition, north China and southwest China will experience the highest and lowest warming in the long‐term (2081–2098) after attribution constraints, increasing by 3.41 and 2.14°C, respectively, under SSP2‐4.5 scenario.

Persistent Model Biases in the Spatial Variability of Winter North Atlantic Atmospheric Circulation

AbstractThe three leading modes of the North Atlantic atmospheric circulation explain about 70% of the winter climate variability. Although climate models generally can capture these modes, biases may induce large uncertainties in regional climate predictions. Here, we evaluate the leading winter modes simulated by CMIP5‐PMIP3 and CMIP6‐PMIP4 models from the last millennium to future scenarios in comparison with historical reanalysis and paleo‐reconstructions. The models generally have a good representation of the average spatial pattern of the North Atlantic Oscillation (NAO) while showing a larger spread in performance for the East Atlantic and Scandinavian patterns. In contrast to historical reanalysis, the simulated NAO pattern tends to be rather stationary under various climate states over the years 861–2100. Such underestimated spatial variability in the simulated NAO is directly related to the biased spatial shifts in NAO‐related regional temperature and precipitation changes, inducing uncertainties in climate projections over the North Atlantic sector.

Palynological Evidence From the Altai Mountains for the Links Between the Asian Westerly Jet Streams and Monsoon System During the Holocene

AbstractThe Asian westerly jet streams in the upper troposphere play a pivotal role in shaping precipitation patterns, sustaining the diverse but fragile ecosystems in arid Central Asia. Despite their significance, the evolution history of these jet streams and their synergistic effects with the monsoon systems on regional climate change in Asia during the Holocene remain poorly understood. To address this gap, we present a continuous pollen record since 8.6 cal ka BP from Lake Shuang in the Altai Mountains. The first two principal components of the pollen data are employed to track regional changes in vegetation, summer moisture, and winter temperature. Meanwhile, the pollen data and the TraCE‐21ka simulation results were compared to reveal the dynamic mechanism of regional climate change. Results indicate a humid phase spanning the interval ∼8 to 5 cal ka BP in this region, which broadly coincides with the intensification of the Indian Summer Monsoon. This temporal correlation is potentially linked to the poleward shift of the Asian jet, as suggested by simulation results. Furthermore, our data show a consistent winter warming trend throughout the Holocene, indicated by changes in the dominant tree pollen taxa and a reduction of cold‐resistant‐taxa. This trend is associated with the weakening of the East Asian Winter Monsoon, influenced by increasing winter solar insolation and atmospheric CO2 concentration. Overall, our research provides strong paleoclimatological evidence highlighting the interconnected meteorological roles of the Asian jet and monsoon systems in shaping regional climates.

Effects of different irrigation methods on regional climate in North China Plain: A modeling study

Agricultural irrigation is important in boosting crop yields in especially water-stressed regions, but little is known about the distinct climatic effects induced by different irrigation methods, particularly in the North China Plain (NCP) where irrigation is applied extensively. Here we examine the climatic effects of flood (FI), sprinkler (SI) and drip irrigation (DI) over NCP during the growing season using dynamic irrigation schemes implemented into a coupled land-atmosphere model. The model generally captures the spatial distribution of surface temperature, relative humidity and precipitation. The changes in regional average surface temperature induced by FI, SI and DI are –0.43, –0.53 and –0.19 °C, respectively. The relatively larger cooling effect for SI than that for FI is associated with enhanced cloud formation. By shifting the surface energy balance, FI and SI cause a wet, cool, cloudy and shallow planetary boundary layer, while DI exhibits the smallest effect and indeed inhibits cloud formation. The increases in convective available potential energy and precipitable water induced by FI and SI enhance convective precipitation over NCP by 0.8–1.2 mm d–1. In contrast, the reduced precipitation due to surface cooling within DI leads to a warmer and drier surface from June to August, which likely increases upper-level geopotential heights and in turn suppresses precipitation in a series of climate feedbacks. The distinct hydrometeorological interactions and feedbacks arising from different irrigation methods are likely related to different irrigation rates, frequencies and approaches of water application. While DI is recognized as the most water-saving method, it also generates the least surface cooling among the three methods and is thus less effective in safeguarding grain yields against rising temperatures. Our study emphasizes the need for more sustainable and adaptive irrigation methods to ensure food security, water conservation and climate stability in the face of climate change.