GloSVeT: a global 0.05° monthly mean surface soil and vegetation component temperature dataset (2003–2023)

IF 13.6 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Xiangyang Liu,Zhao-Liang Li,Chen Ru,Si-Bo Duan,Pei Leng
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引用次数: 0

Abstract

Current satellite-derived land surface temperature (LST) products represent a mixed radiative signal that integrates soil and vegetation contributions, obscuring the physical mechanisms controlling surface energy partitioning and ecosystem functioning. To overcome this limitation, this study developed the Global Soil and Vegetation Temperature dataset (GloSVeT), the first global product that simultaneously provides surface soil and vegetation component temperatures at 0.05° spatial resolution for the period 2003–2023. GloSVeT was generated using the multisource data fusion-based global surface soil and vegetation temperature retrieval (FuSVeT) method, which integrates multi-temporal MODIS observations with ERA5-Land reanalysis to improve spatial completeness, retrieval accuracy, and computational efficiency. Its performance was extensively assessed through a comprehensive evaluation framework combining internal closure check, flux-tower validation at 72 representative sites, triple collocation (TC) analysis, and physical consistency assessments. Results show that GloSVeT largely preserves the original MODIS mixed-pixel LST constraint, and achieves reliable accuracy with coefficients of determination mostly at or above 0.9 and root mean square errors generally around 2 K for both components. TC analysis further demonstrates globally consistent performance, with advantages in humid tropics and transitional ecosystems compared with reanalysis products. In addition, soil temperature anomalies are predominantly negatively correlated with soil moisture whereas vegetation temperature aligns with solar-induced fluorescence along a clear gradient from energy-limited to water-limited biomes, indicating the physical consistency of GloSVeT. Over pixels where soil and vegetation temperatures are simultaneously available, both components exhibit evident warming trends during 2003–2023, with rates of 0.44 ± 0.04 K per decade for soil temperature and 0.39 ± 0.04 K per decade for vegetation temperature. In summary, GloSVeT provides a physically consistent, observation-driven depiction of surface thermal dynamics, offering new opportunities for quantifying land–atmosphere energy exchange, monitoring ecosystem hydrothermal responses, and improving the representation of land surface processes in Earth system models. GloSVeT is publicly available at https://doi.org/10.11888/RemoteSen.tpdc.303317 (Liu and Li, 2026a) and https://doi.org/10.5281/zenodo.22724289 (Liu and Li, 2026b).
GloSVeT: 2003-2023年全球0.05°月平均地表土壤和植被成分温度数据集
目前的卫星地表温度(LST)产品代表了一个混合的辐射信号,整合了土壤和植被的贡献,模糊了控制地表能量分配和生态系统功能的物理机制。为了克服这一限制,本研究开发了全球土壤和植被温度数据集(GloSVeT),这是第一个同时提供2003-2023年0.05°空间分辨率的地表土壤和植被成分温度的全球产品。GloSVeT采用基于多源数据融合的全球地表土壤和植被温度检索(FuSVeT)方法生成,该方法将多时相MODIS观测数据与ERA5-Land再分析相结合,提高了空间完整性、检索精度和计算效率。通过综合评估框架对其性能进行了广泛评估,该评估框架结合了内部关闭检查、72个代表性站点的通量塔验证、三重配置(TC)分析和物理一致性评估。结果表明,GloSVeT在很大程度上保留了原始MODIS混合像元LST约束,并且在两个分量的决定系数大多在0.9以上,均方根误差一般在2 K左右的情况下获得了可靠的精度。TC分析进一步展示了全球一致的性能,与再分析产品相比,在潮湿热带和过渡生态系统中具有优势。此外,土壤温度异常主要与土壤湿度呈负相关,而植被温度与太阳诱导荧光沿着从能量限制到水限制的明显梯度一致,表明GloSVeT的物理一致性。2003-2023年,在土壤温度和植被温度同时存在的像元上,土壤温度和植被温度的升温速率分别为0.44±0.04 K / 10年和0.39±0.04 K / 10年。总之,GloSVeT提供了一个物理上一致的、观测驱动的地表热动力学描述,为量化陆地-大气能量交换、监测生态系统热液响应以及改善地球系统模型中地表过程的表征提供了新的机会。GloSVeT的公开网址为https://doi.org/10.11888/RemoteSen.tpdc.303317 (Liu and Li, 2026a)和https://doi.org/10.5281/zenodo.22724289 (Liu and Li, 2026b)。
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来源期刊
Earth System Science Data
Earth System Science Data GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍: Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.
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