scholarly journals Monthly streamflow forecasting at varying spatial scales in the Rhine basin

2017 ◽  
Author(s):  
Simon Schick ◽  
Ole Rössler ◽  
Rolf Weingartner
Keyword(s):  
Land Surface ◽  
General Circulation ◽  
Initial Conditions ◽  
Spatial Scales ◽  
General Circulation Models ◽  
Surface Model ◽  
Rhine River ◽  
Streamflow Forecasting ◽  
Rhine Basin ◽  
Monthly Streamflow

Abstract. Model output statistics (MOS) methods empirically relate an environmental variable of interest to predictions from general circulation models (GCMs). This variable often belongs to a spatial scale not resolved by the GCM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the GCM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In so doing, the MOS method is tested for catchments areas covering four orders of magnitude. Using data from the period 1981–2011, the results show that skill, with respect to climatology, is restricted to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduces the mean absolute error of the former in the range of 5 to 11 percent, which is consistently reproduced at the subcatchment scale. The results further indicate that bias corrected runoff from the H-TESSEL land surface model is an interesting option when it comes to seasonal streamflow forecasting in large river basins.

scholarly journals Monthly streamflow forecasting at varying spatial scales in the Rhine basin

2018 ◽  
Vol 22 (2) ◽  
pp. 929-942 ◽  
Author(s):  
Simon Schick ◽  
Ole Rössler ◽  
Rolf Weingartner
Keyword(s):  
Initial Conditions ◽  
Spatial Scales ◽  
Surface Air Temperature ◽  
Absolute Error ◽  
Environmental Variable ◽  
Rhine River ◽  
Streamflow Forecasting ◽  
Rhine Basin ◽  
Monthly Streamflow ◽  
Model Output Statistics

Abstract. Model output statistics (MOS) methods can be used to empirically relate an environmental variable of interest to predictions from earth system models (ESMs). This variable often belongs to a spatial scale not resolved by the ESM. Here, using the linear model fitted by least squares, we regress monthly mean streamflow of the Rhine River at Lobith and Basel against seasonal predictions of precipitation, surface air temperature, and runoff from the European Centre for Medium-Range Weather Forecasts. To address potential effects of a scale mismatch between the ESM's horizontal grid resolution and the hydrological application, the MOS method is further tested with an experiment conducted at the subcatchment scale. This experiment applies the MOS method to 133 additional gauging stations located within the Rhine basin and combines the forecasts from the subcatchments to predict streamflow at Lobith and Basel. In doing so, the MOS method is tested for catchments areas covering 4 orders of magnitude. Using data from the period 1981–2011, the results show that skill, with respect to climatology, is restricted on average to the first month ahead. This result holds for both the predictor combination that mimics the initial conditions and the predictor combinations that additionally include the dynamical seasonal predictions. The latter, however, reduce the mean absolute error of the former in the range of 5 to 12 %, which is consistently reproduced at the subcatchment scale. An additional experiment conducted for 5-day mean streamflow indicates that the dynamical predictions help to reduce uncertainties up to about 20 days ahead, but it also reveals some shortcomings of the present MOS method.

Local Regimes of Atmospheric Variability: A Case Study of Southern California

2006 ◽  
Vol 19 (17) ◽  
pp. 4308-4325 ◽  
Author(s):  
Sebastien Conil ◽  
Alex Hall
Keyword(s):  
Spatial Structure ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Spatial Scales ◽  
Surface Wind ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Atmospheric Variability ◽  
Composite Surface

Abstract The primary regimes of local atmospheric variability are examined in a 6-km regional atmospheric model of the southern third of California, an area of significant land surface heterogeneity, intense topography, and climate diversity. The model was forced by reanalysis boundary conditions over the period 1995–2003. The region is approximately the same size as a typical grid box of the current generation of general circulation models used for global climate prediction and reanalysis product generation, and so can be thought of as a laboratory for the study of climate at spatial scales smaller than those resolved by global simulations and reanalysis products. It is found that the simulated circulation during the October–March wet season, when variability is most significant, can be understood through an objective classification technique in terms of three wind regimes. The composite surface wind patterns associated with these regimes exhibit significant spatial structure within the model domain, consistent with the complex topography of the region. These regimes also correspond nearly perfectly with the simulation’s highly structured patterns of variability in hydrology and temperature, and therefore are the main contributors to the local climate variability. The regimes are approximately equally likely to occur regardless of the phase of the classical large-scale modes of atmospheric variability prevailing in the Pacific–North American sector. The high degree of spatial structure of the local regimes and their tightly associated climate impacts, as well as their ambiguous relationship with the primary modes of large-scale variability, demonstrate that the local perspective offered by the high-resolution model is necessary to understand and predict the climate variations of the region.

scholarly journals Impact of possible climate changes on river runoff under different natural conditions

2018 ◽  
Vol 379 ◽  
pp. 293-300 ◽  
Author(s):  
Yeugeniy M. Gusev ◽  
Olga N. Nasonova ◽  
Evgeny E. Kovalev ◽  
Georgy V. Ayzel
Keyword(s):  
Air Temperature ◽  
River Runoff ◽  
Land Surface ◽  
General Circulation ◽  
General Circulation Models ◽  
River Basins ◽  
Annual Runoff ◽  
Surface Model ◽  
Natural Conditions ◽  
Rcp Scenarios

Abstract. The present study was carried out within the framework of the International Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) for 11 large river basins located in different continents of the globe under a wide variety of natural conditions. The aim of the study was to investigate possible changes in various characteristics of annual river runoff (mean values, standard deviations, frequency of extreme annual runoff) up to 2100 on the basis of application of the land surface model SWAP and meteorological projections simulated by five General Circulation Models (GCMs) according to four RCP scenarios. Analysis of the obtained results has shown that changes in climatic runoff are different (both in magnitude and sign) for the river basins located in different regions of the planet due to differences in natural (primarily climatic) conditions. The climatic elasticities of river runoff to changes in air temperature and precipitation were estimated that makes it possible, as the first approximation, to project changes in climatic values of annual runoff, using the projected changes in mean annual air temperature and annual precipitation for the river basins. It was found that for most rivers under study, the frequency of occurrence of extreme runoff values increases. This is true both for extremely high runoff (when the projected climatic runoff increases) and for extremely low values (when the projected climatic runoff decreases).

scholarly journals Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

scholarly journals An ensemble of AMIP simulations with prescribed land surface temperatures

2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models ◽  
Solar Constant ◽  
Surface Temperatures ◽  
Co2 Concentrations ◽  
Land Surface Temperatures ◽  
Intercomparison Project

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

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