scholarly journals Copula-based statistical refinement of precipitation in RCM simulations over complex terrain

2011 ◽  
Vol 15 (7) ◽  
pp. 2401-2419 ◽  
Author(s):  
P. Laux ◽  
S. Vogl ◽  
W. Qiu ◽  
H. R. Knoche ◽  
H. Kunstmann
Keyword(s):  
Time Series ◽  
Complex Terrain ◽  
Large Scale ◽  
Extreme Values ◽  
Regional Climate ◽  
Tail Dependence ◽  
Copula Models ◽  
Climate Simulations ◽  
Weather Situation ◽  
The Common

Abstract. This paper presents a new Copula-based method for further downscaling regional climate simulations. It is developed, applied and evaluated for selected stations in the alpine region of Germany. Apart from the common way to use Copulas to model the extreme values, a strategy is proposed which allows to model continuous time series. As the concept of Copulas requires independent and identically distributed (iid) random variables, meteorological fields are transformed using an ARMA-GARCH time series model. In this paper, we focus on the positive pairs of observed and modelled (RCM) precipitation. According to the empirical copulas, significant upper and lower tail dependence between observed and modelled precipitation can be observed. These dependence structures are further conditioned on the prevailing large-scale weather situation. Based on the derived theoretical Copula models, stochastic rainfall simulations are performed, finally allowing for bias corrected and locally refined RCM simulations.

scholarly journals Copula-based statistical refinement of precipitation in RCM simulations over complex terrain

2011 ◽  
Vol 8 (2) ◽  
pp. 3001-3045 ◽  
Author(s):  
P. Laux ◽  
S. Vogl ◽  
W. Qiu ◽  
H. R. Knoche ◽  
H. Kunstmann
Keyword(s):  
Time Series ◽  
Complex Terrain ◽  
Large Scale ◽  
Extreme Values ◽  
Regional Climate ◽  
Copula Models ◽  
Climate Simulations ◽  
Weather Situation ◽  
The Common ◽  
The Impact

Abstract. This paper presents a new Copula-based method for further downscaling regional climate simulations. It is developed, applied and evaluated for selected stations in the alpine region of Germany. Apart from the common way to use Copulas to model the extreme values, a strategy is proposed which allows to model continous time series. In this paper, we focus on the positive pairs of observed and modelled (RCM) precipitation. As the concept of Copulas requires independent and identically distributed (iid) random variables, meteorological fields are transformed using an ARMA-GARCH time series model. The dependence structures between modelled and observed precipitation are conditioned on the prevailing large-scale weather situation. The impact of the altitude of the stations and their distance to the surrounding modelled grid cells is analyzed. Based on the derived theoretical Copula models, stochastic rainfall simulations are performed, finally allowing for bias corrected and locally refined RCM simulations.

scholarly journals Improving runoff estimates from regional climate models: a performance analysis in Spain

2012 ◽  
Vol 16 (6) ◽  
pp. 1709-1723 ◽  
Author(s):  
D. González-Zeas ◽  
L. Garrote ◽  
A. Iglesias ◽  
A. Sordo-Ward
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Aridity Index ◽  
Regional Climate Models ◽  
Hydrologic Model ◽  
Direct Runoff ◽  
Interpolation Methods ◽  
Basin Scale

Abstract. An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results.

Large-scale drivers of the Mediterranean climate change hot-spot

2021 ◽  
Author(s):  
Roman Brogli ◽  
Silje Lund Sørland ◽  
Nico Kröner ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Hot Spot ◽  
Regional Climate ◽  
Lapse Rate ◽  
Summer Climate ◽  
Climate Simulations ◽  
Summer Warming ◽  
The Mediterranean ◽  
Circulation Changes

<div> <p><span>It has long been recognized that the Mediterranean is a ‘hot-spot’ of climate change. The model-projected year-round precipitation decline and amplified summer warming are among the leading causes of the vulnerability of the Mediterranean to greenhouse gas-driven warming. We investigate large-scale drivers influencing both the Mediterranean drying and summer warming in regional climate simulations. To isolate the influence of multiple large-scale drivers, we sequentially add the respective drivers from global models to regional climate model simulations. Additionally, we confirm the robustness of our results across multiple ensembles of global and regional climate simulations.</span></p> </div><div> <p><span>We will present in detail how changes in the atmospheric stratification are key in causing the amplified Mediterranean summer warming. Together with the land-ocean warming contrast, stratification changes also drive the summer precipitation decline. Summer circulation changes generally have a surprisingly small influence on the changing Mediterranean summer climate. In contrast, changes in the circulation are the primary driver for the projected winter precipitation decline. Since land-ocean contrast and stratification changes are more robust in global climate simulations than circulation changes, we argue that the uncertainty associated with the projected climate change patterns should be considered smaller in summer than in winter.</span></p> </div><div> <p><span>References:</span></p> </div><div> <p><span>Brogli, R., S. L. Sørland, N. Kröner, and C. Schär, 2019: Causes of future Mediterranean precipitation decline depend on the season. Environmental Research Letters, 14, 114017, doi:10.1088/1748-9326/ab4438.</span></p> </div><div> <p><span>Brogli, R., N. Kröner, S. L. Sørland, D. Lüthi and C. Schär, 2019: The Role of Hadley Circulation and Lapse-Rate Changes for the Future European Summer Climate. Journal of Climate, 32, 385-404, doi:10.1175/JCLI-D-18-0431.1</span></p> </div>

scholarly journals Improving runoff estimates from regional climate models: a performance analysis in Spain

2012 ◽  
Vol 9 (1) ◽  
pp. 175-214
Author(s):  
D. González-Zeas ◽  
L. Garrote ◽  
A. Iglesias ◽  
A. Sordo-Ward
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Hydrologic Model ◽  
Direct Runoff ◽  
Interpolation Methods ◽  
Basin Scale ◽  
The Impact

Abstract. An important aspect to assess the impact of climate change on water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimize the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of naturalised runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behavior of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evaporation and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber also gives good results.

scholarly journals Transport Catastrophe Analysis as an Alternative to a Monofractal Description: Theory and Application to Financial Crisis Time Series

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Sergey A. Kamenshchikov
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Large Scale ◽  
Extreme Values ◽  
Phase Diffusion ◽  
Description Theory ◽  
Mortgage Crisis ◽  
Memory Measure ◽  
Short Memory ◽  
Scale Failure

The goal of this investigation was to overcome limitations of a persistency analysis, introduced by Benoit Mandelbrot for monofractal Brownian processes: nondifferentiability, Brownian nature of process, and a linear memory measure. We have extended a sense of a Hurst factor by consideration of a phase diffusion power law. It was shown that precatastrophic stabilization as an indicator of bifurcation leads to a new minimum of momentary phase diffusion, while bifurcation causes an increase of the momentary transport. An efficiency of a diffusive analysis has been experimentally compared to the Reynolds stability model application. An extended Reynolds parameter has been introduced as an indicator of phase transition. A combination of diffusive and Reynolds analyses has been applied for a description of a time series of Dow Jones Industrial weekly prices for the world financial crisis of 2007–2009. Diffusive and Reynolds parameters showed extreme values in October 2008 when a mortgage crisis was fixed. A combined R/D description allowed distinguishing of market evolution short-memory and long-memory shifts. It was stated that a systematic large scale failure of a financial system has begun in October 2008 and started fading in February 2009.

scholarly journals CECILIA Regional Climate Simulations for Future Climate: Analysis of Climate Change Signal

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Michal Belda ◽  
Petr Skalák ◽  
Aleš Farda ◽  
Tomáš Halenka ◽  
Michel Déqué ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Global Scale ◽  
Climate Change Signal ◽  
Northwestern Part ◽  
Climate Simulations ◽  
Climate Analysis

Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021–2050 and 2071–2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3°C in the first period and 2 and 5°C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to −1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models.

scholarly journals Causes of future Mediterranean precipitation decline depend on the season

2020 ◽  
Author(s):  
Roman Brogli ◽  
Silje Lund Sørland ◽  
Nico Kröner ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Lapse Rate ◽  
Environmental Research ◽  
Economic Sectors ◽  
Climate Simulations ◽  
The Mediterranean ◽  
Circulation Changes

<p>The Mediterranean is among the global 'hot-spots' of climate change, where severe consequences of climate change are expected. Changes in the atmospheric water cycle are among the leading causes of the vulnerability of the Mediterranean to greenhouse gas-driven warming. Specifically, precipitation is projected to decrease year-round, which is expected to have major impacts on hydrology, biodiversity, agriculture, hydropower, and further economic sectors that rely on sufficient water supply.</p><p>We investigate possible causes of the Mediterranean drying in regional climate simulations. To isolate the influence of multiple large-scale drivers on the drying, we sequentially add the respective drivers from global models to regional climate model simulations. We show that the causes of the Mediterranean drying depend on the season. We will present in detail how the summer drying is driven by the land-ocean warming contrast, lapse-rate and other thermodynamic changes, while it only weakly depends on circulation changes. In contrast, changes in the circulation are the primary driver for the projected winter precipitation decline. Since land-ocean contrast, thermodynamic and lapse-rate changes are more robust in climate simulations than circulation changes, the uncertainty associated with the projected drying should be considered smaller in summer than in winter.</p><p>Reference: Brogli, R., S. L. Sørland, N. Kröner, and C. Schär, 2019: Causes of future Mediterranean precipitation decline depend on the season. Environmental Research Letters, 14, 114017, doi:10.1088/1748-9326/ab4438.</p>

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