Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model

Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI.

青藏高原乡村人群对气候变化影响的感知与适应

青藏高原是全球气候变化的敏感区和脆弱区。研究青藏高原乡村人群对气候变化的感知与适应状况,对提高乡村人群气候变化的适应能力,促进青藏高原地区的社会稳定和可持续发展意义重大。本文采用问卷调查和访谈相结合的方式,分析了青藏高原乡村人群对气候变化感知与适应的现状。结果表明:在气候变化对农牧业的影响感知方面,68%的调查对象认为草场返青时间提前,62%认为在气候变化后草场状况恶化,78%认为农作物播种时间提前。在气候变化带来的不利影响感知方面,调查对象最担心的 3 个问题依次是:干旱更加严重(50.4%)、水资源矛盾突出(48.5%)、农业粮食安全(36.8%)。对气候变化的适应对策主要是:完善水利设施,采用高效节水灌溉技术(73.8%)、增加塑料地膜覆盖面或作物秸秆覆盖(58.2%)、调整农作物种植结构,改变作物布局(47.6%)。

Strong heatwaves with widespread urban-related hotspots over Africa in 2019

2019 was one of the hottest years in recent decades,with widespread heatwaves over many parts of the world,including Africa.However,as a developing and vulnerable region,the understanding of recent heatwave events in Africa is limited.Here,the authors incorporated different climate datasets,satellite observations,and population estimates to investigate patterns and hotspots of major heatwave events over Africa in 2019.Overall,2019 was one of the years that experienced the strongest heatwaves in terms of intensity and duration since 1981 in Africa.Heatwave hotspots were clearly identified across western-coastal,northeastern,southern,and equatorial Africa,where major cities and human populations are located.The proportion of urban agglomerations(population)exposed to extreme(99 th percentile)heatwaves in the Northern Hemisphere and Southern Hemisphere rose from 4%(5 million people)and 15%(17 million people),respectively,in the baseline period of 1981-2010 to36%(43 million people)and 57%(53 million people),respectively,in 2019.Heatwave patterns and hotspots in 2019 were related to anomalous seasonal change in atmospheric circulation and above-normal sea surface temperature.Without adaptation to minimize susceptibility to the effects of heatwave events,the risks they pose in populated areas may increase rapidly in Africa.

Accelerated rise in wildfire carbon emissions from Arctic continuous permafrost

Wildfires over permafrost put perennially frozen carbon at risk.However,wildfire emissions from biomass burning over the diverse range of permafrost regions and their share in global wildfire emissions have not been revealed.The results showed a dramatic increase in wildfire carbon emissions from permafrost regions over the period 1997–2021.The share of permafrost in global wildfire CO_(2) emissions increased from 2.42%in 1997 to 20.86%in 2021.Accelerating wildfire emissions from continuous permafrost region is the single largest contributor to increased emissions in northern permafrost regions.Fire-induced emissions from 2019 to 2021 alone accounted for approximately 40%of the 25-year total CO_(2) emissions from continuous permafrost regions.The rise in wildfire emissions from continuous permafrost regions is explained by desiccation within a 5–10 cm soil depth,where wildfires combust belowground fuel.These findings highlight the acceleration of fire-induced carbon emissions from continuous permafrost regions,which disturb the organic carbon stock and accelerate the positive feedback between permafrost degradation and climate warming,thus stimulating permafrost towards a climatic tipping point.

Contribution of high-latitude permafrost regions in the Northern Hemisphere to global wildfire carbon emissions

Wildfires are major disturbances in permafrost ecosystems, with increasing frequency and intensity in recent years. In permafrost regions, wildfires not only burn surface and subsurface organic matter but also accelerate permafrost thawing,releasing significant amounts of greenhouse gases such as carbon dioxide and methane into the atmosphere. However, the contribution of high-latitude permafrost regions in the Northern Hemisphere to global wildfire carbon emissions remains poorly understood. This study integrates remote sensing data and ground observations to analyze the contributions of aboveground and belowground fuel combustion in high-latitude permafrost regions to global wildfire carbon emissions from 2002 to 2020, as well as the spatiotemporal variations in these contributions. Our findings indicate that permafrost regions contribute approximately11.96% of global wildfire carbon emissions, with aboveground emissions accounting for approximately 3.94% of global aboveground emissions and belowground emissions contributing approximately 63.57% of global belowground emissions. The contribution of high-latitude permafrost regions to global emissions peaked in July and August, whereas the continuous permafrost zones(areas with more than 90% permafrost coverage) showed the most significant increase in June and July. The contributions of both aboveground and belowground emissions from high-latitude permafrost regions to global wildfire emissions have been increasing, primarily due to the reduction in global wildfire emissions, in contrast with the rising emissions from wildfires in high-latitude permafrost regions. This study highlights the significant role of wildfires, particularly the combustion of belowground biomass in high-latitude permafrost regions, in global carbon emissions. The decomposition and combustion of organic carbon in permafrost regions due to wildfires release more greenhouse gases into the atmosphere, potentially amplifying the positive feedback between atmospheric greenhouse gas accumulation and climate warming.

The role of big Earth data in understanding climate change

Climate-related changes have already been observed at various spatial and temporal scales,along with frequent extreme climate events and emerging issues in great complexity.Meanwhile,the impacts of climate change are expected to become increasingly more severe for more people and places as the amount of warming increases.However,great challenges and uncertainties exist in understanding climate change and its complex impacts,largely due to the limited availability and compatibility of large-scale data.

Understanding the spring phenology of Arctic tundra using multiple satellite data products and ground observations

The Arctic is highly sensitive to climate change,and the rise in its near-surface air temperatures has been almost twice the global average.The increased growth of the Arctic tundra and its changing seasonality have been observed,largely in response to the impacts of climate change.In this study,we investigated the temporal and spatial variations of the start of the growing season(SOS)using various remote sensing indices,including Normalized Difference Vegetation Index,Normalized Difference Water Index,and Normalized Difference Snow Index from 2000 to 2018 in Arctic tundra regions.The SOS was derived at 29 sites from ground observations,including CO2 flux data,phenological images,and field records that were used to validate the SOS from remote sensing indices.Our results revealed that the SOS was delayed by approximately 3.86 days per degree of latitude along the northward latitudinal gradient.From 2000 to 2018,the start of the growing season and the interannual variability differed greatly among tundra types.Although the overall trends were not significant from 2000 to 2018,the start of the growing season in different plant communities was consistently delayed after 2016.High Arctic vegetation,including(1)low wetland complexes(5–10 cm)dominated by sedges,grasses,and mosses,and(2)slightly higher prostrate and hemi-prostrate shrubs(<15 cm),experienced a delayed start of the growing season.The start of the growing season of Low Arctic vegetation,comprising(1)wetland complexes(10–40 cm)dominated by sedges,grasses,mosses,and dwarf shrubs,(2)moist tundra(20–50 cm)dominated by tussock cottongrass and dwarf shrubs,and(3)transition zones containing tundra and taiga,displayed no obvious trend.

A global terrestrial ecosystem respiration dataset(2001-2010)estimated with MODIS land surface temperature and vegetation indices

This paper describes how a validated semi-empirical,but physiologically based,remote sensing model-Ensemble_all-was upscaled using MODIS land surface temperature data(MOD11C2),enhanced vegetation indices(MOD13C1)and land-cover data(MCD12C1)to produce a global terrestrial ecosystem respiration data set(Reco)for January 2001-December 2010.The temporal resolution of this data set is 1 month,the spatial resolution is 0.05°,and the range is from 55°S to 65°N and 180°W to 180°E(crop and natural vegetation mosaic is not included).After crossvalidating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model,a LPJ_S1 process model and a machine learning method model,we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world.This data set can be found at http://www.dx.doi.org/10.11922/sciencedb.934.

Heterogeneous Trends of Precipitation Extremes in Recent Two Decades over East Africa

East Africa is so vulnerable to the impacts of precipitation extremes varying from frequent floods to prolonged droughts.However,systematic regional assessment of precipitation extremes across seasons has received little attention,and most previous studies of precipitation extremes have employed many indices and sparse gauge observations giving marginalized details.In this study,we use three precipitation extreme indices to examine the intensity of the highest single-day rainfall record(rx1day),prevalence of very heavy rainfalls(r30mm),and persistence of successive wet days(cwd)at both annual and seasonal scales over recent two decades(1998-2018)based on the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis data.The results show that the most intensive and frequent precipitation extremes are noticeable from January to May across the areas extending from Madagascar to the Tanzanian coastal zone.These areas also exhibit patches of significant increasing trends in frequency,duration,and intensity of precipitation extremes annually and seasonally.However,significant declines in frequency and intensity of precipitation extremes are observed from western Ethiopia to Congo-Uganda,especially in June-September.The October-December season witnesses higher interannual variability amounting to overall weak and less significant trends.Further subregional assessment shows overall declining intensity and frequency of precipitation extremes in northern part of the study areas.Mean wetness duration increased,with persistence of moderate wet days and slight reduction of severe events.This study unveils higher susceptibility of the East African region to the widely observed hotspots of precipitation extremes posing threats to food security,water resource,and human well-being.The region should consider upscaling irrigation schemes in addition to planning resilient and supportive infrastructures to withstand the upsurging precipitation extremes,especially along the coastal zone.

Identifying and Quantifying Pixel-Level Uncertainty among Major Satellite Derived Global Land Cover Products

Accurate global land cover(GLC), as a key input for scientific communities, is important for a wide variety of applications. In order to understand the current suitability and limitation of GLC products, the discrepancy and pixellevel uncertainty in major GLC products in three epochs are assessed in this study by using an integrated uncertainty index(IUI) that combines the thematic uncertainty and local classification accuracy uncertainty. The results show that the overall spatial agreements(Ao values) between GLC products are lower than 58%, and the total areas of forests are very consistent in major GLC products, but significant differences are found in different forest classes.The misclassification among different forest classes and mosaic types can account for about 20% of the total disagreements. The mean IUI almost reaches 0.5, and high uncertainty mostly occurs in transition zones and heterogeneous areas across the world. Further efforts are needed to make in the land cover classifications in areas with high uncertainty. Designing a classification scheme for climate models, with explicit definitions of land cover classes in the threshold of common attributes, is urgently needed. Information of the pixel-level uncertainty in major GLC products not only give important implications for the specific application, but also provide a quite important basis for land cover fusion.