Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

Rasmussen, Søren Højmark; Christensen, Jens Hesselbjerg; Drews, Martin; Gochis, David; Refsgaard, Jens Christian

doi:10.1175/jhm-d-12-07.1

Cited by 27 publications

(25 citation statements)

References 80 publications

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“…The long-term and high-resolution tree-ring records presented here can provide useful proxy information addressing this data gap. In addition, the low-frequency variability from the 11-year smoothed series is important for local climate change research, since this would be the foundation for sound regional climate modeling and for more reliable forecasts of trends in future precipitation variability in the cold and arid Qilian Mountains, similarly to equivalent studies in different regions [72]–[74].…”

Section: Discussionmentioning

confidence: 99%

Climate Control on Tree Growth at the Upper and Lower Treelines: A Case Study in the Qilian Mountains, Tibetan Plateau

Yang

Melvin

et al. 2013

PLoS ONE

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It is generally hypothesized that tree growth at the upper treeline is normally controlled by temperature while that at the lower treeline is precipitation limited. However, uniform patterns of inter-annual ring-width variations along altitudinal gradients are also observed in some situations. How changing elevation influences tree growth in the cold and arid Qilian Mountains, on the northeastern Tibetan Plateau, is of considerable interest because of the sensitivity of the region’s local climate to different atmospheric circulation patterns. Here, a network of four Qilian juniper (Sabina przewalskii Kom.) ring-width chronologies was developed from trees distributed on a typical mountain slope at elevations ranging from 3000 to 3520 m above sea level (a.s.l.). The statistical characteristics of the four tree-ring chronologies show no significant correlation with increasing elevation. All the sampled tree growth was controlled by a common climatic signal (local precipitation) across the investigated altitudinal gradient (520 m). During the common reliable period, covering the past 450 years, the four chronologies have exhibited coherent growth patterns in both the high- and low-frequency domains. These results contradict the notion of contrasting climate growth controls at higher and lower elevations, and specifically the assumption that inter-annual tree-growth variability is controlled by temperature at the upper treeline. It should be stressed that these results relate to the relatively arid conditions at the sampling sites in the Qilian Mountains.

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Section: Discussionmentioning

confidence: 99%

Climate Control on Tree Growth at the Upper and Lower Treelines: A Case Study in the Qilian Mountains, Tibetan Plateau

Yang

Melvin

et al. 2013

PLoS ONE

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“…Model domains and analysis area. Figure from Rasmussen et al () ©American Meteorological Society, used with permission…”

Section: Examplesmentioning

confidence: 99%

Where are the limits of model predictive capabilities?

Refsgaard

Højberg

et al. 2016

Hydrological Processes

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Distributed hydrological models can make predictions with much finer spatial resolution than the supporting field data. They will, however, usually not have a predictive capability at model grid scale due to limitations of data availability and uncertainty of model conceptualizations. In previous publications, we have introduced the Representative Elementary Scale (RES) concept as the theoretically minimum scale at which a model with a given conceptualization has a potential for obtaining a predictive accuracy corresponding to a given acceptable accuracy. The new RES concept has similarities to the 25‐year‐old Representative Elementary Area concept, but it differs in the sense that while Representative Elementary Area addresses similarity between subcatchments by sampling within the catchment, RES focuses on effects of data or conceptualization uncertainty by Monte Carlo simulations followed by a scale analysis. In the present paper, we extend and generalize the RES concept to a framework for assessing the minimum scale of potential predictability of a distributed model applicable also for analyses of different model structures and data availabilities. We present three examples with RES analyses and discuss our findings in relation to Beven's alternative blueprint and environmental modeling philosophy from 2002. While Beven here addresses model structural and parameter uncertainties, he does not provide a thorough methodology for assessing to which extent model predictions for variables that are not measured possess opportunities to have meaningful predictive accuracies, or whether this is impossible due to limitations in data and models. This shortcoming is addressed by the RES framework through its analysis of the relationship between aggregation scale of model results and prediction uncertainties and for considering how alternative model structures and alternative data availability affects the results. We suggest that RES analysis should be applied in all modeling studies that aim to use simulation results at spatial scales smaller than the support scale of the calibration data.

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“…To achieve this, we apply a convolution procedure that smooths the field before thresholding the data. For unforced convection, Rasmussen et al (2012) studied how well spatial correlation patterns of summer precipitation for the central United States were simulated by two RCMs. They showed that the models and observations were more strongly correlated when compared on larger scales, and their main conclusion was that model precipitation should be compared with observations on scales of at least around 100 km.…”

Section: Evaluation Datamentioning

confidence: 99%

A new regional climate model operating at the meso-gamma scale: performance over Europe

Lindstedt¹,

Lind²,

Kjellström

et al. 2015

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C TThere are well-known difficulties to run numerical weather prediction (NWP) and climate models at resolutions traditionally referred to as 'grey-zone' ( Â3Á8 km) where deep convection is neither completely resolved by the model dynamics nor completely subgrid. In this study, we describe the performance of an operational NWP model, HARMONIE, in a climate setting (HCLIM), run at two different resolutions (6 and 15 km) for a 10-yr period (1998Á2007). This model has a convection scheme particularly designed to operate in the 'grey-zone' regime, which increases the realism and accuracy of the time and spatial evolution of convective processes compared to more traditional parametrisations. HCLIM is evaluated against standard observational data sets over Europe as well as high-resolution, regional, observations. Not only is the regional climate very well represented but also higher order climate statistics and smaller scale spatial characteristics of precipitation are in good agreement with observations. The added value when making climate simulations at Â5 km resolution compared to more typical regional climate model resolutions is mainly seen for the very rare, high-intensity precipitation events. HCLIM at 6 km resolution reproduces the frequency and intensity of these events better than at 15 km resolution and is in closer agreement with the high-resolution observations.

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Spatial-Scale Characteristics of Precipitation Simulated by Regional Climate Models and the Implications for Hydrological Modeling

Cited by 27 publications

References 80 publications

Climate Control on Tree Growth at the Upper and Lower Treelines: A Case Study in the Qilian Mountains, Tibetan Plateau

Climate Control on Tree Growth at the Upper and Lower Treelines: A Case Study in the Qilian Mountains, Tibetan Plateau

Where are the limits of model predictive capabilities?

A new regional climate model operating at the meso-gamma scale: performance over Europe

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