scholarly journals Development of a monthly to seasonal forecast framework tailored to inland waterway transport in Central Europe

2017 ◽  
Author(s):  
Dennis Meißner ◽  
Bastian Klein ◽  
Monica Ionita
Keyword(s):  
Central Europe ◽  
Lead Time ◽  
General Circulation ◽  
Statistical Approach ◽  
Empirical Relationship ◽  
Circulation Model ◽  
Lead Times ◽  
Inland Waterway ◽  
Set Up ◽  
Prediction Approach

Abstract. Traditionally, navigation-related forecasts in Central Europe cover short- to medium-range lead-times linked to the travel times of vessels to pass the main waterway bottlenecks leaving the loading ports. Without doubt, this aspect is still essential for navigational users, but in light of the growing political intention to use the free capacity of the inland waterway transport in Europe, additional lead-time supporting strategic decisions is more and more in demand. However, no such predictions offering extended lead-times of several weeks up to several months ahead currently exist for considerable parts of the European waterway network. This paper describes the set-up of a monthly to seasonal forecasting system for the German stretches of the international waterways of Rhine, Danube and Elbe rivers. Two competitive forecast approaches have been implemented: the dynamical set-up forces a hydrological model with post-processed outputs from ECMWF general circulation model System 4, whereas the statistical approach is based on the empirical relationship (teleconnection) of global oceanic, climate and regional hydro-meteorological data with river flows. The performance of both forecast methods is evaluated in relation to the climatological forecast (ensemble of historical streamflow) and the well-known Ensemble Streamflow Prediction approach (ESP, ensemble based on historical meteorology) using common performance indicators as well as an impact-based evaluation quantifying the potential economic gain. The following four key findings result from this study: (1) As former studies for other regions of Central Europe indicate, also for relevant stations along the German waterways meteorological forcings dominate initial hydrological conditions in most cases already after the first forecast month. (2) Despite the predictive limitations on longer lead-times over Central Europe, this study reveals the existence of a valuable predictability of streamflow at monthly up to seasonal time-scales along Rhine, Upper Danube and Elbe, while the Elbe achieves the highest skill and value. (3) The more physically-based as well as the statistical approach are able to improve the predictive skills compared to climatology and the ESP-approach. The specific forecast skill highly depends on the forecast location, the lead-time and the season. (4) Currently, the statistical approach seems to be most skilful for the three waterways investigated. The lagged relationship between the monthly/seasonal streamflow and the climatic/oceanic variables vary between one month (e.g. local precipitation and temperature, soil moisture) up to six months (e.g. sea surface temperature). Besides improving the forecast methodology, especially by combining the individuals approaches, the focus is on developing useful forecast products on monthly to seasonal time-scale for waterway transport and to operationalize the related forecasting service.

scholarly journals Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe

2017 ◽  
Vol 21 (12) ◽  
pp. 6401-6423 ◽  
Author(s):  
Dennis Meißner ◽  
Bastian Klein ◽  
Monica Ionita
Keyword(s):  
Central Europe ◽  
Lead Time ◽  
Statistical Approach ◽  
Empirical Relationship ◽  
Economic Value ◽  
Skill Score ◽  
Lead Times ◽  
Inland Waterway ◽  
Set Up ◽  
Prediction Approach

Abstract. Traditionally, navigation-related forecasts in central Europe cover short- to medium-range lead times linked to the travel times of vessels to pass the main waterway bottlenecks leaving the loading ports. Without doubt, this aspect is still essential for navigational users, but in light of the growing political intention to use the free capacity of the inland waterway transport in Europe, additional lead time supporting strategic decisions is more and more in demand. However, no such predictions offering extended lead times of several weeks up to several months currently exist for considerable parts of the European waterway network. This paper describes the set-up of a monthly to seasonal forecasting system for the German stretches of the international waterways of the Rhine, Danube and Elbe rivers. Two competitive forecast approaches have been implemented: the dynamical set-up forces a hydrological model with post-processed outputs from ECMWF general circulation model System 4, whereas the statistical approach is based on the empirical relationship (teleconnection) of global oceanic, climate and regional hydro-meteorological data with river flows. The performance of both forecast methods is evaluated in relation to the climatological forecast (ensemble of historical streamflow) and the well-known ensemble streamflow prediction approach (ESP, ensemble based on historical meteorology) using common performance indicators (correlation coefficient; mean absolute error, skill score; mean squared error, skill score; and continuous ranked probability, skill score) and an impact-based evaluation quantifying the potential economic gain. The following four key findings result from this study: (1) as former studies for other regions of central Europe indicate, the accuracy and/or skill of the meteorological forcing used has a larger effect than the quality of initial hydrological conditions for relevant stations along the German waterways. (2) Despite the predictive limitations on longer lead times in central Europe, this study reveals the existence of a valuable predictability of streamflow on monthly up to seasonal timescales along the Rhine, upper Danube and Elbe waterways, and the Elbe achieves the highest skill and economic value. (3) The more physically based and the statistical approach are able to improve the predictive skills and economic value compared to climatology and the ESP approach. The specific forecast skill highly depends on the forecast location, the lead time and the season. (4) Currently, the statistical approach seems to be most skilful for the three waterways investigated. The lagged relationship between the monthly and/or seasonal streamflow and the climatic and/or oceanic variables vary between 1 month (e.g. local precipitation, temperature and soil moisture) up to 6 months (e.g. sea surface temperature). Besides focusing on improving the forecast methodology, especially by combining the individual approaches, the focus is on developing useful forecast products on monthly to seasonal timescales for waterway transport and to operationalize the related forecasting service.

scholarly journals A hybrid GCM paleo ice-sheet model, ANICE2.1 – [email protected]: set up and benchmark experiments

2018 ◽  
Author(s):  
Constantijn J. Berends ◽  
Bas de Boer ◽  
Roderik S. W. van de Wal
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Circulation Model ◽  
Climate Modelling ◽  
Last Glacial ◽  
Model Set ◽  
Set Up

Abstract. Fully coupled ice-sheet-climate modelling over 10,000–100,000-year time scales on high spatial and temporal resolution remains beyond the capability of current computational systems. Hybrid GCM-ice-sheet modelling offers a middle ground, balancing the need to accurately capture both long-term processes, in particular circulation driven changes in precipitation, and processes requiring a high spatial resolution like ablation. Here, we present and evaluate a model set-up that forces the ANICE 3D thermodynamic ice-sheet-shelf model calculating all ice on Earth, with pre-calculated output from several steady-state simulations with the HadCM3 general circulation model (GCM), using a so-called matrix method of coupling both components, where simulations with various levels of pCO2 and ice-sheet configuration are combined to form a time-continuous transient climate forcing consistent with the modelled ice-sheets. We address the difficulties in downscaling low-resolution GCM output to the higher-resolution grid of an ice-sheet model, and account for differences between GCM and ice-sheet model surface topography ranging from interglacial to glacial conditions. As a benchmark experiment to assess the validity of this model set-up, we perform a simulation of the entire last glacial cycle, from 120 kyr ago to present-day. The simulated eustatic sea-level drop at the Last Glacial maximum (LGM) for the combined Antarctic, Greenland, Eurasian and North-American ice-sheets amounts to 100 m, in line with many other studies. The simulated ice-sheets at LGM agree well with the ICE-5G reconstruction and the more recent DATED-1 reconstruction in terms of total volume and geographical location of the ice sheets. Moreover, modelled benthic oxygen isotope abundance and the relative contributions from global ice volume and deep-water temperature agree well with available data, as do surface temperature histories for the Greenland and Antarctic ice-sheets. This model strategy can be used to create time-continuous ice-sheet distribution and sea-level reconstructions for geological periods up to several millions of years in duration, capturing climate model driven variations in the mass balance of the ice sheet.

Predictability of Two Types of El Niño Assessed Using an Extended Seasonal Prediction System by MIROC

2015 ◽  
Vol 143 (11) ◽  
pp. 4597-4617 ◽  
Author(s):  
Yukiko Imada ◽  
Hiroaki Tatebe ◽  
Masayoshi Ishii ◽  
Yoshimitsu Chikamoto ◽  
Masato Mori ◽  
...  
Keyword(s):  
El Niño ◽  
Lead Time ◽  
General Circulation ◽  
El Nino ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Seasonal Prediction ◽  
Ocean General Circulation Model ◽  
Prediction System ◽  
Central Pacific

Abstract Predictability of El Niño–Southern Oscillation (ENSO) is examined using ensemble hindcasts made with a seasonal prediction system based on the atmosphere and ocean general circulation model, the Model for Interdisciplinary Research on Climate, version 5 (MIROC5). Particular attention is paid to differences in predictive skill in terms of the prediction error for two prominent types of El Niño: the conventional eastern Pacific (EP) El Niño and the central Pacific (CP) El Niño, the latter having a maximum warming around the date line. Although the system adopts ocean anomaly assimilation for the initialization process, it maintains a significant ability to predict ENSO with a lead time of more than half a year. This is partly due to the fact that the system is little affected by the “spring prediction barrier,” because increases in the error have little dependence on the thermocline variability. Composite analyses of each type of El Niño reveal that, compared to EP El Niños, the ability to predict CP El Niños is limited and has a shorter lead time. This is because CP El Niños have relatively small amplitudes, and thus they are more affected by atmospheric noise; this prevents development of oceanic signals that can be used for prediction.

scholarly journals Mid-Pliocene global climate simulation with MRI-CGCM2.3: set-up and initial results of PlioMIP Experiments 1 and 2

2012 ◽  
Vol 5 (3) ◽  
pp. 793-808 ◽  
Author(s):  
Y. Kamae ◽  
H. Ueda
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Climate Simulation ◽  
Polar Regions ◽  
The North ◽  
Set Up

Abstract. The mid-Pliocene (3.3 to 3.0 million yr ago), a globally warm period before the Quaternary, is recently attracting attention as a new target for paleoclimate modelling and data-model synthesis. This paper reports set-ups and results of experiments proposed in Pliocene Model Intercomparison Project (PlioMIP) using a global climate model, MRI-CGCM2.3. We conducted pre-industrial and mid-Pliocene runs by using the coupled atmosphere-ocean general circulation model (AOGCM) and its atmospheric component (AGCM) for the PlioMIP Experiments 2 and 1, respectively. In addition, we conducted two types of integrations in AOGCM simulation, with and without flux adjustments on sea surface. General characteristics of differences in the simulated mid-Pliocene climate relative to the pre-industrial in the three integrations are compared. In addition, patterns of predicted mid-Pliocene biomes resulting from the three climate simulations are compared in this study. Generally, difference of simulated surface climate between AGCM and AOGCM is larger than that between the two AOGCM runs, with and without flux adjustments. The simulated climate shows different pattern between AGCM and AOGCM particularly over low latitude oceans, subtropical land regions and high latitude oceans. The AOGCM simulations do not reproduce wetter environment in the subtropics relative to the present-day, which is suggested by terrestrial proxy data. The differences between the two types of AOGCM runs are small over the land, but evident over the ocean particularly in the North Atlantic and polar regions.

scholarly journals Set-up and preliminary results of mid-Pliocene climate simulations with CAM3.1

2011 ◽  
Vol 4 (4) ◽  
pp. 3339-3361 ◽  
Author(s):  
Q. Yan ◽  
Z. Zhang ◽  
H. Wang ◽  
Y. Gao ◽  
W. Zheng
Keyword(s):  
Global Warming ◽  
General Circulation ◽  
Atmospheric General Circulation Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
High Latitudes ◽  
Atmospheric General Circulation ◽  
Climate Simulations ◽  
Low Latitudes ◽  
Set Up

Abstract. The mid-Pliocene warm period (~3.3 to 3.0 Ma BP) is a potential analogue for future climate under global warming. In this study, we use an atmospheric general circulation model (AGCM) called CAM3.1 to simulate the mid-Pliocene climate with the PRISM3D boundary conditions. The simulations show that the global annual mean surface air temperature (SAT) increases by 2.0 °C in the mid-Pliocene compared with the pre-industrial temperature. The greatest warming mainly occurs in the high latitudes of both hemispheres, with little change in SAT at low latitudes. The equator-to-pole SAT gradient is reduced in the mid-Pliocene simulation. The annual mean precipitation is enhanced by 3.6% of the pre-industrial value. However, the changes in precipitation are greater in low latitudes than high latitudes.

scholarly journals Set-up and preliminary results of mid-Pliocene climate simulations with CAM3.1

2012 ◽  
Vol 5 (2) ◽  
pp. 289-297 ◽  
Author(s):  
Q. Yan ◽  
Z. S. Zhang ◽  
H. J. Wang ◽  
Y. Q. Gao ◽  
W. P. Zheng
Keyword(s):  
Global Warming ◽  
General Circulation ◽  
Atmospheric General Circulation Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
High Latitudes ◽  
Atmospheric General Circulation ◽  
Climate Simulations ◽  
Low Latitudes ◽  
Set Up

Abstract. The mid-Pliocene warm period ~3.264 to 3.025 Ma) is a potential analogue for future climate under global warming. In this study, we use an atmospheric general circulation model (AGCM) called CAM3.1 to simulate the mid-Pliocene climate with the PRISM3D boundary conditions. The simulations show that the global annual mean surface air temperature (SAT) increases by 2.0 °C in the mid-Pliocene compared with the pre-industrial temperature. The greatest warming occurs at high latitudes of both hemispheres, with little change in SAT at low latitudes. The equator-to-pole SAT gradient is reduced in the mid-Pliocene simulation. The annual mean precipitation is enhanced by 3.6% of the pre-industrial value. However, the changes in precipitation are greater at low latitudes than at high latitudes.

scholarly journals HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic

2021 ◽  
Vol 14 (4) ◽  
pp. 2057-2074
Author(s):  
Lojze Žust ◽  
Anja Fettich ◽  
Matej Kristan ◽  
Matjaž Ličer
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Circulation Model ◽  
Building Blocks ◽  
Lead Times ◽  
Atmospheric Forcing ◽  
Northern Adriatic ◽  
Set Up

Abstract. Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modelling in the Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our set-up of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2×10-6). HIDRA exhibits larger bias but lower RMSE than our set-up of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analysed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a 10-year (2006–2016) time series of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a 1-year (2019) hourly time series from a tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)−1 and at the ground-state basin seiche frequency (21.5 h)−1 is performed. The energy at the basin seiche in the HIDRA forecast is close to that observed, while our set-up of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.

scholarly journals Predictability of Seasonal Sahel Rainfall Using GCMs and Lead-Time Improvements Through the Use of a Coupled Model

2011 ◽  
Vol 24 (7) ◽  
pp. 1931-1949 ◽  
Author(s):  
Ousmane Ndiaye ◽  
M. Neil Ward ◽  
Wassila M. Thiaw
Keyword(s):  
Lead Time ◽  
General Circulation ◽  
Southern Oscillation ◽  
Boreal Summer ◽  
Circulation System ◽  
Lead Times ◽  
Tropical Atlantic ◽  
Skill Levels ◽  
Ocean Atmosphere ◽  
Sahel Rainfall

Abstract The ability of several atmosphere-only and coupled ocean–atmosphere general circulation models (AGCMs and CGCMs, respectively) is explored for the prediction of seasonal July–September (JAS) Sahel rainfall. The AGCMs driven with observed sea surface temperature (SST) over the period 1968–2001 confirm the poor ability of such models to represent interannual Sahel rainfall variability. However, using a model output statistics (MOS) approach with the predicted low-level wind field over the tropical Atlantic and western part of West Africa yields good Sahel rainfall skill for all models. Skill is mostly captured in the leading empirical orthogonal function (EOF1), representing large-scale fluctuation in the regional circulation system over the tropical Atlantic. This finding has operational significance for the utility of AGCMs for short lead-time prediction based on persistence of June SST information; however, studies have shown that for longer lead-time forecasts, there is substantial loss of skill, relative to that achieved using the observed JAS SST. The potential of CGCMs is therefore explored for extending the lead time of Sahel rainfall predictions. Some of the models studied, when initialized using April information, show potential to at least match the levels of skill achievable from assuming persistence of April SST. One model [NCEP Climate Forecasting System (CFS)] was found to be particularly promising. Diagnosis of the hindcasts available for the CFS (from lead times up to six months for 1981–2008) suggests that, especially by applying the same MOS approach, skill is achieved through capturing interannual variations in Sahel rainfall (primarily related to El Niño–Southern Oscillation in the period of study), as well as the upward trend in Sahel rainfall that is observed over 1981–2008, which has been accompanied by a relative warming in the North Atlantic compared to the South Atlantic. At lead times up to six months (initialized forecasts in December), skill levels are maintained with the correlation between predicted and observed Sahel rainfall at approximately r = 0.6. While such skill levels at these long lead times are notably higher than previously achieved, further experiments, such as over the same period and with comparable AGCMs, are required for definitive attribution of the advance to the use of a coupled ocean–atmosphere modeling approach. Nonetheless, the detrended skill achieved here by the January–March initializations (r = 0.33) must require an approach that captures the evolution of the key ocean–atmosphere anomalies from boreal winter to boreal summer, and approaches that draw on persistence in ocean conditions have not previously been successful.

scholarly journals Application of [email protected] simulations of paleoclimate as forcing for an ice-sheet model, ANICE2.1: set-up and benchmark experiments

2018 ◽  
Vol 11 (11) ◽  
pp. 4657-4675 ◽  
Author(s):  
Constantijn J. Berends ◽  
Bas de Boer ◽  
Roderik S. W. van de Wal
Keyword(s):  
Sea Level ◽  
General Circulation ◽  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Circulation Model ◽  
Climate Modelling ◽  
Last Glacial ◽  
Model Set ◽  
Set Up

Abstract. Fully coupled ice-sheet–climate modelling over 10 000–100 000-year timescales at high spatial and temporal resolution remains beyond the capability of current computational systems. Forcing an ice-sheet model with precalculated output from a general circulation model (GCM) offers a middle ground, balancing the need to accurately capture both long-term processes, in particular circulation-driven changes in precipitation, and processes requiring a high spatial resolution like ablation. Here, we present and evaluate a model set-up that forces the ANICE 3-D thermodynamic ice-sheet–shelf model calculating the four large continental ice sheets (Antarctica, Greenland, North America, and Eurasia) with precalculated output from two steady-state simulations with the HadCM3 (GCM) using a so-called matrix method of coupling both components, whereby simulations with various levels of pCO2 and ice-sheet configuration are combined to form a time-continuous transient climate forcing consistent with the modelled ice sheets. We address the difficulties in downscaling low-resolution GCM output to the higher-resolution grid of an ice-sheet model and account for differences between GCM and ice-sheet model surface topography ranging from interglacial to glacial conditions. Although the approach presented here can be applied to a matrix with any number of GCM snapshots, we limited our experiments to a matrix of only two snapshots. As a benchmark experiment to assess the validity of this model set-up, we perform a simulation of the entire last glacial cycle from 120 kyr ago to present day. The simulated eustatic sea-level drop at the Last Glacial Maximum (LGM) for the combined Antarctic, Greenland, Eurasian, and North American ice sheets amounts to 100 m, in line with many other studies. The simulated ice sheets at the LGM agree well with the ICE-5G reconstruction and the more recent DATED-1 reconstruction in terms of total volume and geographical location of the ice sheets. Moreover, modelled benthic oxygen isotope abundance and the relative contributions from global ice volume and deep-water temperature agree well with available data, as do surface temperature histories for the Greenland and Antarctic ice sheets. This model strategy can be used to create time-continuous ice-sheet distribution and sea-level reconstructions for geological periods up to several million years in duration, capturing climate-model-driven variations in the mass balance of the ice sheet.

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