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A. S. Alhumaima and S. M. Abdullaev

climate classifications are the basis to indicating climate change (e.g., Phillips and Bonfils 2015 ; Fernandez et al. 2017 ) and assessing the ecology (e.g., Baker et al. 2010 ). The second question is as follows: Is it possible to find a dataset with time series of precipitation and temperatures that best reflects (is correlated with) the space–time variability of primary biological productivity of landscapes (NDVI)? This question is more complex than finding a measure of similarity between some

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Farhat Abbas, Nida Sarwar, Muhammad Ibrahim, Muhammad Adrees, Shafaqat Ali, Farhan Saleem, and Hafiz Mohkum Hammad

. , and G. Rasul , 2004 : Agro-climatic classification of Pakistan . Sci. Vision , 9 , 59 – 66 , http://www.sciencevision.org.pk/BackIssues/Vol9/8.agro_climate.pdf . Choi , G. , and Coauthors , 2009 : Changes in means and extreme events of temperature and precipitation in the Asia-Pacific Network region, 1955–2007 . Int. J. Climatol. , 29 , 1906 – 1925 , https://doi.org/10.1002/joc.1979 . 10.1002/joc.1979 Donat , M. G. , and Coauthors , 2013 : Updated analyses of temperature and

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Jay Golden, W. C. Chuang, and W. L. Stefanov

residential areas, which included criteria of capacity, type, and permanency of residence as the discriminating factors among classes: 111) single-family units, 112) multifamily units, 113) group quarters, 114) residential hotels, 115) mobile home parks, 116) transient lodgings, 117) other. Their work provided a significant contribution to classifying land cover and land use from remotely sensed data. However, greater refinement is necessary to adequately adapt these classifications for modeling climate

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Forrest M. Hoffman, William W. Hargrove Jr., David J. Erickson III, and Robert J. Oglesby

itself, the common climate regimes defined for the entire ensemble were used as centroids for a single-pass clustering or classification of the ensemble average time series. As a result, the ensemble average regime changes can be directly compared to those of the individual runs since they share a common set of basis states. MSTC serves as a transform between geographic space and phase space through simulation time, and climate regimes derived in one phase space may be transplanted into another to

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T. Scott Rupp, Xi Chen, Mark Olson, and A. David McGuire

. 1992 ; Lamontagne et al. 2000 ; Schindler et al. 1980 ). A more frequent fire regime also has the potential to release carbon to the atmosphere from high-latitude soils that are rich in carbon ( McGuire et al. 2004 ). Therefore, it is important to couple ecological models of fire regime into climate models to better understand how future responses of the fire regime in high latitudes may influence hydrologic and trace gas feedbacks to the climate system. Global climate models (GCMs) agree that

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Charles W. Lafon and Steven M. Quiring

spatial variations in disturbance regimes may influence geographic patterns of vegetation ( Parker et al. 2001 ; Bond and Keeley 2005 ). Here, we investigate how climate, specifically moisture, influences geographic patterns of wildfire in the eastern United States. Fire is an influential disturbance agent and major natural hazard that presents complex management challenges. Many factors, such as vegetation and land use, affect fire occurrence ( Pyne 1982 ; Alaback et al. 2003 ), but climate is of

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Gregory T. Pederson, Stephen T. Gray, Daniel B. Fagre, and Lisa J. Graumlich

1. Introduction Evidence from an increasingly rich paleoproxy record demonstrates that over the last millennium decadal to multidecadal precipitation anomalies have been a substantial, if not defining, component of western North America’s climates. As in the twentieth century, the last 1000 yr has experienced sporadic episodes of both persistent (>10 yr) droughts and wet regimes, though the magnitude and duration of many paleodroughts surpass those captured by the instrumental record

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M. P. Calef, A. D. McGuire, and F. S. Chapin III

region ( Calef et al. 2005 ). Additionally, we used vegetation types separated into black spruce forest, white spruce forest, deciduous forest, and tundra. The four-class vegetation land cover was developed with algorithms designed to reduce a commonly used classification with 23 land-cover classes ( Fleming 1997 ) to the four major types using topography and climate ( Calef et al. 2005 ; Rupp et al. 2007 ). Tundra is delineated from deciduous forest based on low growing season temperature and

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Brent M. Lofgren, Andrew D. Gronewold, Anthony Acciaioli, Jessica Cherry, Allison Steiner, and David Watkins

GCMs. Air temperature is often used within indices that classify climatic regimes according to their level of aridity. Rubel and Kottek ( Rubel and Kottek 2010 ) determined Köppen classifications at different time periods using climatic variables simulated under the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (SRES) A1FI scenario. They show that, in comparing the 2075–2100 time period to 1975–2000, a net of 9.6% of the area originally classified under C (warm

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Peiyun Zhu, Susan J. Cheng, Zachary Butterfield, Gretchen Keppel-Aleks, and Allison L. Steiner

Y-2010-v1.6.1. European Space Agency Climate Change Initiative (ESA-CCI)-Land Cover, accessed May 2016, https://www.esa-landcover-cci.org/?q=node/158 . Gobron , N. , and Coauthors , 2006 : Evaluation of fraction of absorbed photosynthetically active radiation products for different canopy radiation transfer regimes: Methodology and results using Joint Research Center products derived from SeaWiFS against ground-based estimations . J. Geophys. Res. , 111 , D13110 , https://doi.org/10

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