Regional Surface Temperature Research Articles

A Comparison of Diagnostics for AMOC Heat Transport Applied to the CESM Large Ensemble

AbstractAtlantic time‐mean heat transport is northward at all latitudes and exhibits strong multidecadal variability between about 30°N and 55°N. Atlantic heat transport variability influences many aspects of the climate system, including regional surface temperatures, subpolar heat content, Arctic sea‐ice concentration and tropical precipitation patterns. Atlantic heat transport and heat transport variability are commonly partitioned into two components: the heat transport by the Atlantic Meridional Overturning Circulation (AMOC) and the heat transport by the gyres. In this paper we compare four different methods for performing this partition, and we apply these methods to the Community Earth System Model Large Ensemble at 34°N, 26°N and 5°S. We discuss the strengths and weaknesses of each method. The four methods all give significantly different estimates for the proportion of the time‐mean heat transport performed by AMOC. One of these methods is a new physically‐motivated method based on the pathway of the northward‐flowing part of AMOC. This paper presents a preliminary version of our method that works only when the AMOC follows the western boundary of the basin. All the methods agree that at 26°N, 80%–100% of heat transport variability at 2–10 years timescales is performed by AMOC, but there is more disagreement between methods in attributing multidecadal variability, with some methods showing a compensation between the AMOC and gyre heat transport variability.

Recent trends and variability of temperature and atmospheric water vapor over South Asia

This study examines the recent trends and variability of temperature and atmospheric water vapor over South Asia during the summer monsoon season from 1970 to 2022. We employ gridded reanalysis and observational datasets to assess the trends and variability in surface temperature and further investigate the associated physical processes. Our results show that the surface temperature over South Asia has increased by 0.5 °C per decade. Notably, we find a statistically significant major transition in the surface temperature series in 1995, such that 1970–1994 (1995–2022) is associated with anomalous cooling (anomalous warming). Since 1995, not only have the temporal variations in regional surface temperature, atmospheric water vapor, and clear-sky downward longwave radiation been synchronous at interannual scales, but their largest spatial variations have been located mainly over the same region. A diagnosis of the atmospheric moisture budget reveals that the observed changes in water vapor convergence over South Asia are dominated by changes in mean circulation dynamics, while the change in thermodynamics is relatively small. The enhancement of the Somali low-level jet may contribute to increased water vapor in South Asia by modulating low-level circulations.

The examination of the relationship between land cover and land surface temperature in Karang Baru Sub-District, Aceh Province, Indonesia

Abstract Land cover change can lead to variations in land surface temperature, primarily because different materials have varying capacities to receive, absorb, and re-emit solar radiation. Karang Baru, situated as the capital of Aceh Tamiang Regency near North Sumatra, one of the most densely populated Regency, has been experiencing continuous development since 2002, following its separation from East Aceh Regency. The development in Karang Baru has resulted in a noticeable influence on land surface temperature. The primary objective of this study is to investigate the relationship between land cover and land surface temperature in Karang Baru from 2002 to 2022. This research classified land cover using the supervised classification method employing the Maximum Likelihood Algorithm, and land surface temperature was estimated using the Split Window Algorithm method. Subsequently, simple regression analysis in this context indicates a quantitative approach to understanding the relationship between land cover and land surface temperature in Karang Baru, providing valuable insights for environmental and urban planning considerations. The findings of this research indicate that the type of land cover indeed influences the land surface temperature in Karang Baru. In summary, this study establishes that land cover can substantially impact the regional surface temperature, with temperature increases associated with surfaces featuring buildings, roads, fields, or similar materials. In contrast, vegetated surfaces tend to exhibit lower land surface temperatures in the area.

Assessment of Frost Depth and Frost Heave in Romania

The investigation of extreme weather and climate events has gained momentum in the last few decades, spurred in part by political involvement. However, not enough attention has been paid to the historical recorded data of climate monitoring. An accurate estimate of maximum soil frost depth is an important factor in determining construction costs and structures’ foundations, and designers also need reliable information about local meteorological parameters. In this study, the calculations of the parameters for the city of Arad are presented as an example. An updated Romanian frost depth map and a new Romanian freeze–thaw cycle (FTC) map are needed since recent climate studies have documented an increase in global and regional surface temperatures, with the greatest shift in warming occurring over the last three decades. This trend is particularly pronounced when comparing the 1990–2020 period with earlier periods, which could be indicative of broader climate change trends. It is important to note that these conclusions are based solely on the provided statistical parameters and do not take into account other potential factors influencing temperature trends in the region. The results from this investigation could be used to achieve a reduction in frost disasters and the formulation of policies and measures for the adaptation of geotechnical/structural design for Romanian territory. They may also support the development of maps that help to visualize and understand the evolving climate patterns in the region, including changes in frost depth and the frequency of freeze–thaw cycles, which are important for various sectors such as agriculture, construction, and infrastructural planning. Given the documented increase in global and regional surface temperatures, updating such maps will also provide valuable information for policymakers, researchers, and stakeholders on how to adapt to ongoing climate change and its impacts on the Romanian region.

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.

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.

Effect of urbanization on aerosol optical depth over Beijing: Land use and surface temperature analysis

With the progress of the urbanization process, the air pollution problem has become more serious. To improve air quality, it is necessary to study the correlation between haze weather and local climate, as well as the causes of local climate, such as surface temperature, land use, and social development factors. In this paper, we have taken Beijing as the study area, and remote sensing and data mining has been used as study methods. First, the correlation between local haze weather and surface temperature has been discussed. It was found that the studied regional aerosol optical thickness is positively correlated with the regional surface temperature. Second, the correlation analysis of land use and surface temperature showed a significant positive correlation between them. Finally, this paper used grey correlation analysis to analyze the impact of social development factors on air quality. The results showed that among the 16 identified social factors, energy consumption per 10,000-yuan GDP and exhaust emissions contribute the most to the haze composition. Therefore, this study believes that human activities brought about by urbanization affect the formation of haze, and the analysis of formative factors can provide a reference for government departments to formulate relevant policies.

Critical Review on Radiative Forcing and Climate Models for Global Climate Change since 1970

This review identifies a critical problem in the fundamental physics of current climate models. The large greenhouse effect of rising CO2 assumed in climate models is assessed by six key observations from ground- and satellite-based measurements. This assessment is enhanced by statistical analyses and model calculations of global or regional mean surface temperature changes by conventional climate models and by a conceptual quantum physical model of global warming due to halogen-containing greenhouse gases (halo-GHGs). The postulated large radiative forcing of CO2 in conventional climate models does not agree with satellite observations. Satellite-observed warming pattern resembles closely the atmospheric distribution of chlorofluorocarbons (CFCs). This review helps understand recent remarkable observations of reversals from cooling to warming in the lower stratosphere over most continents and in the upper stratosphere at high latitudes, surface warming cessations in the Antarctic, North America, UK, and Northern-Hemisphere (NH) extratropics, and the stabilization in NH or North America snow cover, since the turn of the century. The complementary observation of surface temperature changes in 3 representative regions (Central England, the Antarctic, and the Arctic) sheds new light on the primary mechanism of global warming. These observations agree well with not CO2-based climate models but the CFC-warming quantum physical model. The latter offers parameter-free analytical calculations of surface temperature changes, exhibiting remarkable agreement with observations. These observations overwhelmingly support an emerging picture that halo-GHGs made the dominant contribution to global warming in the late 20th century and that a gradual reversal in warming has occurred since ~2005 due to the phasing out of halo-GHGs. Advances and insights from this review may help humans make rational policies to reverse the past warming and maintain a healthy economy and ecosystem.

Future variation of land surface temperature in the Yangtze River Basin based on CMIP6 model

ABSTRACT In recent years, past changes in global and regional land surface temperatures (LST) have been well studied, however, future LST changes have been largely ignored owing to data limitations. In this study, three climate variables of CMIP6, namely air temperature (AT), precipitation (Pre), and leaf area index (LAI), were spatially corrected using the Delta downscaling method. On this basis, by combining MODIS LST, elevation, slope and aspect, a random forest (RF) model was built to calculate the LST from 2022 to 2100. The absolute variability (AV) and Mann-Kendall (M-K) tests were used to quantitatively detect interannual and seasonal LST changes in different Shared Socioeconomic Pathways (SSPs) scenarios. The results showed that the AV value increased successively from SSP1-2.6 to SSP2-4.5 and then to SSP5-8.5. Compared with the base period (2003-2021), the increment in interannual, spring, summer and autumn LST during 2022–2100 was mainly between 1 and 2 °C under three scenarios. The interannual and seasonal LST were spatially characterized by significant warming over large areas, and the increasing was the fastest under SSP5-8.5. These results indicate that, in the future, LST will increase further over large areas, especially in winter.

Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate

Abstract. The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the Max Planck Institute (MPI) Earth System Model to investigate how different plausible assumptions for the representation of permafrost hydrology modulate land–atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively “wet” or “dry” conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land–atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover during spring and summer and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.

Unequal exposure to heatwaves in Los Angeles: Impact of uneven green spaces.

Cities worldwide are experiencing record-breaking summer temperatures. Urban environments exacerbate extreme heat, resulting in not only the urban heat island but also intracity variations in heat exposure. Understanding these disparities is crucial to support equitable climate mitigation and adaptation efforts. We found persistent negative correlations between daytime land surface temperature (LST) and median household income across the Los Angeles metropolitan area based on Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station observations from 2018 to 2021. Lower evapotranspiration resulting from the unequal distribution of vegetation cover is a major factor leading to higher LST in low-income neighborhoods. Disparities worsen with higher regional mean surface temperature, with a $10,000 decrease in income leading to ~0.2°C LST increase at 20°C and up to ~0.7°C at 45°C. With more frequent and intense heat waves projected in the future, equitable mitigation measures, such as increasing surface albedo and tree cover in low-income neighborhoods, are necessary to address these disparities.

Two Distinct Phases of North Atlantic Eastern Subpolar Gyre and Warming Hole Evolution under Global Warming

Abstract The North Atlantic subpolar gyre (SPG) plays a crucial role in determining the regional ocean surface temperature (SST), which has profound implications on the surrounding continental and coastal climate. Here, we analyze the Max Planck Institute-Grand Ensemble global warming experiments and show that the SPG can evolve in two distinct phases under continuous global warming. In the first phase, as the global mean surface temperature approaches 2-K warming, the eastern SPG intensifies in combination with a weakening Atlantic meridional overturning circulation (AMOC), accompanied by a cooling of subpolar North Atlantic SST, known as the warming hole. The associated oceanic fingerprint matches with the observations over the last 15 years, where an intensification and cooling of the eastern SPG is related to salinity reduction at the eastern side of the SPG. However, for further warming beyond 2 K, in spite of a continuous decline in the AMOC, a northward shift of the mean zonal wind extends the subtropical gyre northward with an associated disruption of the eastern SPG intensification, resulting in the cessation of the warming hole. Therefore, a shift from the initially dominating oceanic drivers to the atmospheric driver results into a two-phase evolution of the North Atlantic Ocean SPG circulation and the associated SST under continuous global warming.

Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming

Vegetation change can alter surface energy balance and subsequently affect the local climate. This biophysical impact has been well studied for forestation cases, but the sign and magnitude for persistent earth greening remain controversial. Based on long-term remote sensing observations, we quantify the unidirectional impact of vegetation greening on radiometric surface temperature over 2001–2018. Here, we show a global negative temperature response with large spatial and seasonal variability. Snow cover, vegetation greenness, and shortwave radiation are the major driving factors of the temperature sensitivity by regulating the relative dominance of radiative and non-radiative processes. Combined with the observed greening trend, we find a global cooling of −0.018 K/decade, which slows down 4.6 ± 3.2% of the global warming. Regionally, this cooling effect can offset 39.4 ± 13.9% and 19.0 ± 8.2% of the corresponding warming in India and China. These results highlight the necessity of considering this vegetation-related biophysical climate effect when informing local climate adaptation strategies.

21st Century Global and Regional Surface Temperature Projections

AbstractMany countries and regions across the globe broke their surface temperature records in recent years. Recent crippling heat waves swept across the Earth, further sparking concerns about the impending arrival of “tipping points” later in the 21st century. This study analyzes observed global surface temperature trends in three target latitudinal regions: the Arctic Circle, Tropics, and the Antarctic Circle. We show that global warming is accelerating unevenly across the planet, with the Arctic warming at more than three times the average rate of our world. We also analyzed the reliability of latitude‐dependent surface temperature simulations from a suite of Coupled Model Intercomparison Project Phase 6 (CMIP6) models and their multi‐model mean (MMM) by comparing their outputs to observational data sets. We selected the best‐performing models based on their statistical abilities to reproduce historical, latitude‐dependent values adapted from these data sets. The surface temperature projections were calculated from ensemble simulations of the Shared Socioeconomic Pathway 2–4.5 (SSP2–4.5) by the selected CMIP6 models. We estimate the calendar years of when surface temperatures will increase by 1.5, 2.0, and 2.5°C relative to the preindustrial period, both globally and in the three target regions. Our results reaffirm a dramatic, upward trend in projected surface temperatures, with unprecedented acceleration in the Arctic Circle, which could lead to catastrophic consequences across the Earth. Further studies are necessary to determine the most efficient solutions to reduce global warming acceleration and maintain a low SSP, both globally and regionally.

Grassland greening impacts on global land surface temperature.

Grassland vegetation greenness has been increasing globally during the past decades. Although the vegetation coverage change could have significant effects on climate by affecting albedo and evapotranspiration (ET), the effects of global grassland greening on climate remain unclear due to the lack of long-term field observation data. Here, we used satellite measurements of land surface temperature (LST) from high coverage grassland and adjacent low coverage grassland (divided according to the leaf area index) to quantify, for the first time, the biogeophysical effects of global grassland greening on surface temperatures. Results showed that grassland greening decreased the annual mean LST and daytime LST (LSTD), but did not significantly change nighttime LST (LSTN) globally from 2003 to 2017. Spatially, grassland greening had significant cooling effects on the annual mean LST and LSTD for latitudes south of 50°N due to the cooling effect of increased ET, whereas warming affects on the annual mean LST and LSTD in the high northern latitudes (> 50°N) because of the warming effects of decreased albedo. This study revealed that the effects of grassland greening on surface temperatures changed with latitude. During June, July, and August (JJA), the increasing grassland vegetation coverage decreased the LST between 25°S and 50°N, but increased the mean LST in high northern latitudes. By contrast, grassland greening has no significant effect on the mean LST in the temperate southern hemisphere (> 25°S) during JJA due to cooling and warming effects on LSTD and LSTN, respectively. During December, January, and February, grassland greening decreased the mean LST and LSTD for latitudes south of 25°N, but increased the mean LST and LSTN for latitudes north of 25°N. This study highlights the importance of including grassland vegetation coverage in models of regional surface temperature dynamics and future climate forecast.

Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

AbstractUsing a large suite of Green's function perturbation experiments, we construct the emergent dynamical operator for surface temperature and extract the most excitable mode. The leading mode turns out to be the most dominant mode excited by the climate forcing of doubling CO2, alone capturing 56% of the total spatial variances of the surface temperature response. The pattern of the leading mode is partly organized by the atmospheric annular modes in both hemispheres, and further modulated by the feedbacks from ocean circulations. Though derived from a single model, the leading mode can capture the spatio‐temporal variabilities of the global mean surface temperature over the past century in both the CMIP6 model simulations and observations. Moreover, the leading mode is most efficiently excited by radiative forcings from the midlatitude bands centered around 45°N and 25°S, where most human activities take place, suggesting the potency of human influence on the climate change.

Supporting Data: Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Supporting Data: Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Supporting Data: Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Supporting Data: Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Monitoring land use land cover changes and its impacts on land surface temperature over Mardan and Charsadda Districts, Khyber Pakhtunkhwa (KP), Pakistan.

Land use/land cover (LULC) changes due to urban growth on the regional scale affect land surface temperature (LST). The present study aims to assess the LULC changes and their impact on LST over Mardan and Charsadda districts of Khyber Pakhtunkhwa (KP), Pakistan, in the period from 1990 to 2019. Landsat satellite (TM& ETM +) datasets in the period from 1990 to 2010 and Sentinel-2 images from 2016 to 2019 were used in this study. All the datasets were pre-processed and the LULC types were classified by maximum likelihood classification algorithm. The vegetation degradation was computed from normalized difference vegetation index (NDVI), and the LST was derived based on the LULC changes. The results showed that the overall accuracy of LULC classification was 87.84%. Dramatic LULC changes were observed during the last three decades, where the vegetation degradation area was decreased from 1307.8 (59.27%) to 1147.6 km2 (52.1%) and the barren land area increased from 816.6 (37.07%) to 961.4 km2 (42.64%). Similarly, the built-up area has also increased from 57.2 (2.5%) to 104.3 km2 (4.73%) in the years 1990 and 2019, respectively. These variations in LULC types have significantly influenced the LST from 1990 to 2019; specifically, the LST of built-up area, barren land, and vegetation cover increased from 20.1 to 32.1°C, 21.5 to 35.5°C, and 17.1 to 28.2°C, respectively. The regression line plotted defines that the LST has a negative correlation with NDVI and a positive correlation with normalized difference of built-up index (NDBI). In particular, the vegetation and land covers dramatically transformed to barren land and/or to urban development over the study area in the period from 1990 to2019, which has severely affected the LST and the natural resources of the study area. Therefore, our study will be very helpful for managing the rapid environmental changes and urban planning.

Research on the spatiotemporal coupling relationships between land use/land cover compositions or patterns and the surface urban heat island effect.

Urbanization leads to changes in landscape configuration and land use/land cover (LULC) patterns, and these changes are important factors affecting the surface urban heat island (SUHI) effect. However, from the perspective of spatiotemporal changes, quantitative analytical results regarding the impacts of the LULC composition, configuration, and pattern in inland plateau lakeside cities on the SUHI effect, and the responsive relationships among these factors remain unclear. By combining satellite remote sensing data with analytical methods, such as urban-rural gradients, spatial statistics, and landscape pattern indices, the impacts of LULC changes on the SUHI effect in Kunming, China, are revealed. The results show the following. (1) The explosive growth in impervious surfaces (ISs) caused by urbanization, leading to changes in the LULC composition, configuration and pattern, is the main reason for the deterioration of the SUHI effect. Over the past 30years, Kunming's ISs have increased by 304.58 km2, SUHI has expanded by 764.26 km2, and the regional average land surface temperature (LST) has increased by 1°C. (2) This study also found that a large area of bare ground is another important reason for the sharp rise in LST, explaining why bare land (BL) has the highest average LST (28.72°C). (3) The pattern of LULC can well explain the spatial distribution characteristics of SUHIs. The normalized difference built-up index (NDBI), normalized difference bareness index (NDBaI), and LST have the same change curve along the urban-rural gradient, while the normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), and LST have opposite trends. (4) ISs and water body (WB) are the main types of warming and cooling, respectively, but the warming effect of ISs is greater than the cooling effect of WB. From the average value of the correlation coefficient with LST, NDBI (0.84) > MNDWI (-0.63). (5) Kunming's remote sensing index values do not have simple linear relationships with the LST. NDBaI, NDBI, and LST show significant exponential relationships, and NDVI, MNDWI, and LST show significant quadratic polynomial relationships. (6) The dominant landscape type determines the correlation between the landscape shape index (LSI) and the LST of green spaces (GSs). (7) Adopting a simple and regular landscape layout can effectively reduce the SUHI effect. These research results could provide a scientific decision-making basis for the spatial urban planning and ecological construction of Kunming and could have practical significance for guiding the green, healthy, and sustainable development of the city.