DOI: 10.1002/joc.5857
论文题名: Influence of source and scale of gridded temperature data on modelled spring onset patterns in the conterminous United States
作者: Mehdipoor H. ; Zurita-Milla R. ; Izquierdo-Verdiguier E. ; Betancourt J.L.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 14 起始页码: 5430
结束页码: 5440
语种: 英语
英文关键词: climate change
; cloud computing
; gridded time series analysis
; scale theory
; spatio-temporal trend analysis
; spring phenology
; volunteered geographic information
Scopus关键词: Climate models
; Cloud computing
; Computation theory
; Image resolution
; Input output programs
; Time series analysis
; Climate variability and change
; Gridded temperatures
; Phenological observations
; Scale theory
; Spatio temporal
; Temperature regimes
; Volunteered geographic information
; Western United States
; Climate change
英文摘要: Gridded time series of climatic variables are key inputs to phenological models used to generate spatially continuous indices and explore the influence of climate variability and change on plant development at broad scales. To date, there have been few efforts to evaluate how the particular source and spatial resolution (i.e., scale) of the input data might affect how phenological models and associated indices track variations and shifts at the continental scale. This study represents the first such assessment, based on cloud computing and volunteered phenological observations. It focuses on established extended spring indices (SI-x) that estimate day of year (DOY) for first leaf (FL) emergence and first bloom (FB) emergence in plants particularly sensitive to accumulation of warmth in early to mid-spring. We compared and validated gridded SI-x products obtained using Daymet (at 1, 4, 35, and 100 km spatial resolution) and gridMET (at 4, 35, and 100 km) temperature data. These products were used to estimate temporal trends in DOY for FL and FB in the coterminous United States (CONUS) from 1980 to 2016. The SI-x products, and their resulting patterns and trends across CONUS, affected more by the source of input data than their spatial resolution. SI-x estimates DOY of FL and FB are about 3 and 4 weeks more accurate, respectively, using Daymet than gridMET. This leads to significant differences, and even contradictory, rates of change in DOY driven by Daymet versus gridMET temperatures, even though both data sources exhibit advancement in DOY of FL and FB across most regions in CONUS. SI-x products generated from gridMET poorly estimate the timing of spring onset, whereas Daymet SI-x products and actual volunteered observations are moderately correlated (r = 0.7). Daymet better captures temperature regimes, particularly in the western United States, and is more appropriate for generating high-resolution SI-x indices at continental scale. © 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116716
Appears in Collections: 气候减缓与适应
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作者单位: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands; Science and Decisions Center, U.S. Geological Survey, Reston, VA, United States; Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States
Recommended Citation:
Mehdipoor H.,Zurita-Milla R.,Izquierdo-Verdiguier E.,et al. Influence of source and scale of gridded temperature data on modelled spring onset patterns in the conterminous United States[J]. International Journal of Climatology,2018-01-01,38(14)