Dataset Information

Seasonal spatial heterogeneity of warming rates on the Tibetan Plateau over the past 30 years.

ABSTRACT: Based on temperature data from 79 meteorological stations, we estimate the warming rate by season on the Tibetan Plateau (TP) during 1984-2013. The warming rate was spatially heterogeneous across seasons over the past 30 years. The northern TP (NTP) experienced more warming than the southern TP (STP) (divided near 33 °N) in all seasons. The greatest north-south difference in warming was 0.70 ± 0.11 °C for summer (June-August), while the smallest difference was 0.27 ± 0.14 °C for the cold season (November-April). Such seasonal and spatial heterogeneity in the warming rate is consistent with the seasonal precipitation patterns of the NTP and the STP. One possible cause for this phenomenon is that more precipitation occurs in the STP than in the NTP (especially for summer), accompanied by more low cloud cover, which may have slowed the warming rate. Our results imply that dry regions on the TP will possibly experience greater temperature increase than wet regions under future global warming, and this will be more prominent in summer.

SUBMITTER: Duan J

PROVIDER: S-EPMC4481825 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Seasonal spatial heterogeneity of warming rates on the Tibetan Plateau over the past 30 years.

Duan Jianping J Li Lun L Fang Yongjie Y

Scientific reports 20150626

Based on temperature data from 79 meteorological stations, we estimate the warming rate by season on the Tibetan Plateau (TP) during 1984-2013. The warming rate was spatially heterogeneous across seasons over the past 30 years. The northern TP (NTP) experienced more warming than the southern TP (STP) (divided near 33 °N) in all seasons. The greatest north-south difference in warming was 0.70 ± 0.11 °C for summer (June-August), while the smallest difference was 0.27 ± 0.14 °C for the cold season ...[more]

PMID: 26114895

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Project description:The northeastern margin of the Tibetan Plateau (NE Tibetan Plateau) exhibits active geological structures and has experienced multiple strong earthquakes, with M ≥ 7, throughout history. Particularly noteworthy is the 1920 M81/2 earthquake in the Haiyuan region that occurred a century ago and is documented as one of the deadliest earthquakes. Consequently, analyzing seismic risks in the northeastern margin of the Tibetan Plateau holds significant importance. The b value, a crucial parameter for seismic activity, plays a pivotal role in seismic hazard analyses. This study calculates the spatial b values in this region based on earthquake catalogs since 1970. The study area encompasses several major active faults, and due to variations in b values across different fault types, traditional grid-search methods may introduce significant errors in calculating the spatial b value within complex fault systems. To address this, we employed the hierarchical space-time point-process (HIST-PPM) method proposed by Ogata. This method avoids partitioning earthquake samples, optimizes parameters using Akaike's Bayesian Information Criterion (ABIC) with entropy maximization, and theoretically allows for a higher spatial resolution and more accurate b value calculations. The results indicate a high spatial heterogeneity in b values within the study area. The northwestern and southeastern regions exhibit higher b values. Along the Haiyuan fault zone, the central rupture zone of the Haiyuan earthquake has relatively higher b values than other regions of this fault zone, which is possibly related to the sufficient release of stress during the main rupture of the Haiyuan earthquake. The b values vary from high in the west to low in the east along the Zhongwei fault. On the West Qinling fault zone, the epicenter of the recent Minxian-Zhangxian earthquake is associated with a low b value. In general, regions with low b values correspond well to areas with moderate-strong seismic events in the past 50 years. The spatial differences in b values may reflect variances in seismic hazards among fault zones and regions within the same fault zone.

Project description:BackgroundMonitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate.Methodology/principal findingsGrassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity.Conclusions/significanceShortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.

Dataset Information

Seasonal spatial heterogeneity of warming rates on the Tibetan Plateau over the past 30 years.

Publications

Seasonal spatial heterogeneity of warming rates on the Tibetan Plateau over the past 30 years.

Similar Datasets

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