Spatial estimation of air temperature differences for landscape-scale studies in montane environments

Lookingbill, Todd R.; Urban, Dean L.

doi:10.1016/s0168-1923(02)00196-x

Cited by 180 publications

(188 citation statements)

References 24 publications

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“…Although the interpolation algorithms and statistical models for modern climate estimation are sophisticated and high-resolution digital elevation models can be used to incorporate adiabatic lapse rates and regional climate (Randin et al 2006), they still predict meteorological (2 m above ground surface) air conditions rather than actual life conditions for alpine plants and coleopterans (Scherrer & Körner 2010. It is questionable whether such gridded or interpolated climate data reflect the actual alpine environment where the majority of organisms live in microhabitats strongly decoupled from atmospheric conditions and interacting with micro-topography at a very fine spatial scales (Lookingbill & Urban 2003;Scherrer & Körner 2010. Spatial heterogeneity in climate is a very important environmental feature and is of critical importance in the reliability and usefulness of bioclimate-envelope models that use mesoscale climate data (Ashcroft et al 2009;Ackerly et al 2010;Bennie et al 2010).…”

Section: Strengths and Weaknessesmentioning

confidence: 99%

Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies

Birks

2011

TOECOLJ

343

284

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Abstract:The importance of reconstructing past environments quantitatively in palaeoecology is reviewed by showing that many ecological questions asked of palaeoecological data commonly involve the reconstructions of past environment. Three basic approaches to reconstructing past climate from palaeoecological data are outlined and discussed in terms of their assumptions, strengths, and weaknesses. These approaches are the indicator-species approach involving bioclimateenvelope modelling; the assemblage approach involving modern analogue techniques and response surfaces; and the multivariate calibration-function approach. Topics common to all approaches are reviewed -presentation and interpretation, evaluation and validation, comparison, and general limitations of climate reconstructions. Challenges and possible future developments are presented and the potential future role of quantitative climate reconstructions in palaeoecology is summarised.

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Section: Strengths and Weaknessesmentioning

confidence: 99%

Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies

Birks

2011

TOECOLJ

343

284

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“…The catchments were divided into different elevation zones (one per 100 m) and lapse rates were used for temperature (-0.5 C per 100 m) and precipitation (+5 % per 100 m). These lapse rates were based on previous work in the region (Daly et al, 1994;Lookingbill & Urban, 2003) and analysis of data from stations in or neighbouring HJA, which were available for shorter periods. Time series of observed runoff were used for model calibration.…”

Section: Model Applicationmentioning

confidence: 99%

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

Seibert

McDonnell

2010

Hydrological Sciences Journal

106

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Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty. Hydrol. Sci. J. 55(3), 316-332. AbstractThe effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in precipitation inputs and catchment characteristics between the treatment and control catchments. This paper presents a model-based change-detection approach that includes model and parameter uncertainty as an alternative to the traditional paired-catchment method for larger catchments. We use the HBV model and data from the HJ Andrews Experimental Forest in Oregon, USA, to develop and test the approach on two small (<1 km 2 ) headwater catchments (a 100% clear-cut and a control) and then apply the technique to the larger 62 km 2 Lookout catchment. Three different approaches are used to detect changes in stream peak flows using: (a) calibration for a period before (or after) change and simulation of runoff that would have been observed without land-cover changes (reconstruction of runoff series); (b) comparison of calibrated parameter values for periods before and after a land-cover change; and (c) comparison of runoff predicted with parameter sets calibrated for periods before and after a land-cover change. Our proof-of-concept change detection modelling showed that peak flows increased in the clear-cut headwater catchment, relative to the headwater control catchment, and several parameter values in the model changed after the clear-cutting. Some minor changes were also detected in the control, illustrating the problem of false detections. For the larger Lookout catchment, moderately increased peak flows were detected. Monte Carlo techniques used to quantify parameter uncertainty and compute confidence intervals in model results and parameter ranges showed rather wide distributions of model simulations. While this makes change detection more difficult, it also demonstrated the need to explicitly consider parameter uncertainty in the modelling approach to obtain reliable results.Key words change detection; forest hydrology; forest harvesting; HJ Andrews; HBV model Impacts de l'occupation du sol sur les écoulements en rivière: une approche de détection de changement par modélisation qui inclut les incertitudes sur les paramètres Résumé L'effet de la modification de l'occupation et de la couverture du sol sur la dynamique des écoulements reste mal compris. Dans la plupart des cas, la gestion des forêts est le facteur le plus important quant à la modification de l'occupation du sol. L'approche d'analyse des bassins versants par appariement est la principale méthode pour quantifier de tels effets. Cependant, cette méthode n'est adaptée que dans le cas de petits bassins versants de tête, où les précipitations incide...

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“…Later research placed efforts on developing spatial interpolation methods using limited station data, such as the inverse distance weighted method, spline method, trends method, and kriging method. Existing interpolation methods are mainly based on the distance of nearby meteorological stations and values of measured temperature (Beek et al 1992;Lookingbill and Urban 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies have made progresses pertaining to the multivariate colinearity effect of different factors in large-scale areas (Kattel and Yao 2013;Kattel et al 2015). In most studies, latitude, longitude, and elevation were preferred factors when topography was correlated with the SAT (Brown and Comrie 2002;Goodale et al 1998;Lookingbill and Urban 2003;Ollinger et al 1995). The effect of slope and aspect on the SAT distribution has been emphasized in recent years (Weng and Luo 1990;Zhao et al 2005).…”

Section: Introductionmentioning

confidence: 99%

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Topographic effects on spatial pattern of surface air temperature in complex mountain environment

Sun

Zhang

2016

Environ Earth Sci

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Understanding topographic effects on surface air temperature (SAT) is essential in developing an accurate prediction model in complex mountain environment. A nonlinear topographic regression model is developed to predict the spatial SAT pattern using latitude, elevation, slope, and aspect. Monthly SAT data have been collected from 14 meteorological stations between 1960 and 2010 in the Daqing Mountains of China. Topographic data are acquired from a 30 m resolution digital elevation model of the study region. Results show that: (1) the SAT models are able to explain 89-95.8 % of the spatial variation in different months. Elevation has the strongest effect on the SAT variation in all months (average 84.78 %). (2) The combined contribution of slope and aspect to SAT variations is larger (average 9.14 %) than that of latitude (average 6.07 %). (3) The combined effect of slope and aspect on SAT variations is higher in winter than in summer. The introduction of slope and aspect optimizes the SAT modeling in different months. In further studies, the accuracy of SAT model might be improved by introducing alternative topographic factors to capture the vegetation and weather condition.

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Spatial estimation of air temperature differences for landscape-scale studies in montane environments

Cited by 180 publications

References 24 publications

Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies

Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

Topographic effects on spatial pattern of surface air temperature in complex mountain environment

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