scholarly journals Development and Evaluation of a Pan-European Multimodel Seasonal Hydrological Forecasting System

2019 ◽  
Vol 20 (1) ◽  
pp. 99-115 ◽  
Author(s):  
Niko Wanders ◽  
Stephan Thober ◽  
Rohini Kumar ◽  
Ming Pan ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
General Circulation ◽  
Hydrological Model ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Historical Period ◽  
Seasonal Forecasts ◽  
Forecasting System ◽  
Temporal And Spatial

Abstract Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.

scholarly journals Temporal and Spatial Interpolation Errors of High-Resolution Modeled Atmospheric Fields

2016 ◽  
Vol 33 (2) ◽  
pp. 303-311 ◽  
Author(s):  
N. C. Privé ◽  
R. M. Errico
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
General Circulation ◽  
Temporal Frequency ◽  
General Circulation Models ◽  
Specific Humidity ◽  
Tropospheric Temperature ◽  
Model Output ◽  
Time Step ◽  
Optimal Output

AbstractGeneral circulation models can now be run at very high spatial resolutions to capture finescale features, but saving the full-spatial-resolution output at every model time step is usually not practical because of storage limitations. To reduce storage requirements, the model output may be produced at reduced temporal and/or spatial resolutions. When this reduced-resolution output is then used in situations where spatiotemporal interpolation is required, such as the generation of synthetic observations for observing system simulation experiments, interpolation errors can significantly affect the quality and usefulness of the reduced-resolution model output. Although it is common in practice to record model output at the highest possible spatial resolution with relatively infrequent temporal output, this may not be the best option to minimize interpolation errors. In this study, two examples using a high-resolution global run of the Goddard Earth Observing System Model, version 5 (GEOS-5), are presented to illustrate cases in which the optimal output dataset configurations for interpolation have high temporal frequency but reduced spatial resolutions. Interpolation errors of tropospheric temperature, specific humidity, and wind fields are investigated. The relationship between spatial and temporal output resolutions and interpolation errors is also characterized for the example model.

scholarly journals Extreme Events Representation in CMCC-CM2 High and Very-High Resolution General Circulation Models

2021 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Daniele Peano ◽  
Silvio Gualdi ◽  
Alessio Bellucci ◽  
Tomas Lovato ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Horizontal Resolution ◽  
Historical Period ◽  
Climate Modelling ◽  
Temperature And Precipitation ◽  
Very High

Abstract. The recent advancements in climate modelling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the CMCC-CM2 model used here, adopt the highest horizontal resolutions available within the last family of the global coupled climate models de¬veloped at CMCC to participate in the CMIP6 effort. The main aim of this study is to document the ability of the CMCC-CM2 models in representing the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations (ERA5 Reanalysis and CHIRPS observations). For a more detailed evaluation we investigate both 6 hourly and daily time series for the definition of the extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The very-high resolution version (¼ degree horizontal resolution) of the atmospheric model provides better results than the high resolution one (one degree), not only in terms of means but also in terms of extreme events of temperature defined at daily and 6-hourly frequency. This is also the case of average precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

scholarly journals Hydrologic Model Evaluation and Assessment of Projected Climate Change Impacts Using Bias-Corrected Stream Flows

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2312
Author(s):  
Joseph A. Daraio
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Stream Flow ◽  
General Circulation ◽  
Model Performance ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Historical Period ◽  
Hydrologic Models ◽  
Stream Flows

Hydrologic models driven by downscaled meteorologic data from general circulation models (GCM) should be evaluated using long-term simulations over a historical period. However, simulations driven by GCM data cannot be directly evaluated using observed flows, and the confidence in the results can be relatively low. The objectives of this paper were to bias correct simulated stream flows from calibrated hydrologic models for two basins in New Jersey, USA, and evaluate model performance in comparison to uncorrected simulations. Then, we used stream flow bias correction and flow duration curves (FDCs) to evaluate and assess simulations driven by statistically downscaled GCMs for the historical period and the future time slices 2041–2070 and 2071–2099. Bias correction of stream flow from simulations increased confidence in the performance of two previously calibrated hydrologic models. Results indicated there was no difference in projected FDCs for uncorrected and bias-corrected flows in one basin, while this was not the case in the second basin. This result provided greater confidence in projected stream flow changes in the former basin and implied more uncertainty in projected stream flows in the latter. Applications in water resources can use the methods described to evaluate the performance of GCM-driven simulations and assess the potential impacts of climate change with an appropriate level of confidence in the model results.

scholarly journals Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean

2016 ◽  
Vol 20 (3) ◽  
pp. 1031-1047 ◽  
Author(s):  
Benjamin Grouillet ◽  
Denis Ruelland ◽  
Pradeebane Vaittinada Ayar ◽  
Mathieu Vrac
Keyword(s):  
High Resolution ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Hydrological Model ◽  
General Circulation Models ◽  
Western Mediterranean ◽  
Cumulative Distribution ◽  
Time Step ◽  
Stochastic Weather Generator ◽  
Precipitation And Temperature

Abstract. This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20-year period (1986&ndsh;2005) to capture different climatic conditions in the basins. The daily GR4j conceptual model was used to simulate streamflow that was eventually evaluated at a 10-day time step. Cross-validation showed that this model is able to correctly reproduce runoff in both dry and wet years when high-resolution observed climate forcings are used as inputs. These simulations can thus be used as a benchmark to test the ability of different statistically downscaled data sets to reproduce various aspects of the hydrograph. Three different statistical downscaling models were tested: an analog method (ANALOG), a stochastic weather generator (SWG) and the cumulative distribution function–transform approach (CDFt). We used the models to downscale precipitation and temperature data from NCEP/NCAR reanalyses as well as outputs from two general circulation models (GCMs) (CNRM-CM5 and IPSL-CM5A-MR) over the reference period. We then analyzed the sensitivity of the hydrological model to the various downscaled data via five hydrological indicators representing the main features of the hydrograph. Our results confirm that using high-resolution downscaled climate values leads to a major improvement in runoff simulations in comparison to the use of low-resolution raw inputs from reanalyses or climate models. The results also demonstrate that the ANALOG and CDFt methods generally perform much better than SWG in reproducing mean seasonal streamflow, interannual runoff volumes as well as low/high flow distribution. More generally, our approach provides a guideline to help choose the appropriate statistical downscaling models to be used in climate change impact studies to minimize the range of uncertainty associated with such downscaling methods.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals Annual and semiannual cycles of midlatitude surface temperature and baroclinicity: reanalysis data and AOGCMs simulations

2016 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Relative Phase ◽  
North Pacific Ocean ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Bivariate Analysis ◽  
Seasonal Forecasts ◽  
Frequency Model ◽  
Annual Frequency

Abstract. Seasonal variability of surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere-ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically: (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres; (ii) at the annual frequency, estimates of the relative phase between surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1 month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3 but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterize the cyclic response of current global atmosphere-ocean models to the external (solar) forcing that is of interest for seasonal forecasts.

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 Skillful Climate Forecasts of the Tropical Indo-Pacific Ocean Using Model-Analogs

2018 ◽  
Vol 31 (14) ◽  
pp. 5437-5459 ◽  
Author(s):  
Hui Ding ◽  
Matthew Newman ◽  
Michael A. Alexander ◽  
Andrew T. Wittenberg
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Coarse Grained ◽  
Seasonal Forecasts ◽  
Multimodel Ensemble ◽  
Initial State ◽  
The North ◽  
Eastern Equatorial Pacific ◽  
Spread Model ◽  
The Individual

Seasonal forecasts made by coupled atmosphere–ocean general circulation models (CGCMs) undergo strong climate drift and initialization shock, driving the model state away from its long-term attractor. Here we explore initializing directly on a model’s own attractor, using an analog approach in which model states close to the observed initial state are drawn from a “library” obtained from prior uninitialized CGCM simulations. The subsequent evolution of those “model-analogs” yields a forecast ensemble, without additional model integration. This technique is applied to four of the eight CGCMs comprising the North American Multimodel Ensemble (NMME) by selecting from prior long control runs those model states whose monthly tropical Indo-Pacific SST and SSH anomalies best resemble the observations at initialization time. Hindcasts are then made for leads of 1–12 months during 1982–2015. Deterministic and probabilistic skill measures of these model-analog hindcast ensembles are comparable to those of the initialized NMME hindcast ensembles, for both the individual models and the multimodel ensemble. In the eastern equatorial Pacific, model-analog hindcast skill exceeds that of the NMME. Despite initializing with a relatively large ensemble spread, model-analogs also reproduce each CGCM’s perfect-model skill, consistent with a coarse-grained view of tropical Indo-Pacific predictability. This study suggests that with little additional effort, sufficiently realistic and long CGCM simulations provide the basis for skillful seasonal forecasts of tropical Indo-Pacific SST anomalies, even without sophisticated data assimilation or additional ensemble forecast integrations. The model-analog method could provide a baseline for forecast skill when developing future models and forecast systems.

Atmospheric response to Gulf Stream SST front shifting: impact of horizontal resolution in an ensemble of global climate models

2021 ◽  
Author(s):  
Luca Famooss Paolini ◽  
Alessio Bellucci ◽  
Paolo Ruggieri ◽  
Panos Athanasiadis ◽  
Silvio Gualdi
Keyword(s):  
High Resolution ◽  
Gulf Stream ◽  
General Circulation ◽  
Diabatic Heating ◽  
Storm Track ◽  
General Circulation Models ◽  
Horizontal Resolution ◽  
Atmospheric Response ◽  
Sst Front ◽  
Pressure Anomaly

<p>Western boundary currents transport a large amount of heat from the Tropics toward higher latitudes; furthermore they are characterized by a strong sea surface temperature (SST) gradient, which anchors zones of intense upward motion extending up to the upper-troposphere and shapes zones of intense baroclinic eddy activity (storm tracks). For such reasons they have been shown to be fundamental in influencing the climate of the Northern Hemisphere and its variability, and a potentially relevant source of atmospheric predictability. </p><p> </p><p>General circulation models show deficiencies in simulating the observed atmospheric response to SST front variability. The atmospheric horizontal resolution has been recently proposed as a key element in understanding such differences. However, the number of studies on this subject is still limited. Furthermore, a multi-model analysis to systematically investigate differences between low-resolution and high-resolution atmospheric response to oceanic forcing is still lacking. </p><p> </p><p>The present work has the objective to fill this gap, analysing the atmospheric response to Gulf Stream SST front shifting using data from recent High Resolution Model Intercomparison Project (HighResMIP). This project was designed with the specific objective of investigating the impact of increased model horizontal resolution on the representation of the observed climate. Ensembles of historical simulations performed with three atmospheric general circulation models (AGCMs) have been analysed, each conducted with a low-resolution (LR, about 1°) and a high-resolution (HR, about 0.25°) configuration. AGCMs have been forced with observed SSTs (HadISST2 dataset), available at daily frequency on a 0.25° grid, during 1950–2014. </p><p><br>Results show atmospheric responses to the SST-induced diabatic heating anomalies that are strongly resolution dependent. In LR simulations a low-pressure anomaly is present downstream of the SST anomaly, while the diabatic heating anomaly is mainly balanced by meridional advection of air coming from higher latitudes, as expected for an extra-tropical shallow heat source. In contrast, HR simulations generate a high-pressure anomaly downstream of the SST anomaly, thus driving positive temperature advection from lower latitudes (not balancing diabatic heating). Along the vertical direction, both in LR and HR simulation, the diabatic heating in the interior of the atmosphere is balanced by upward motion south of GS SST front and downward motion north and further south of the Gulf Stream. Finally, LR simulations show a reduction in storm-track activity over the North Atlantic, whereas HR simulations show a meridional displacement of the storm-track considerably larger (yet in the same direction) than that of the SST front. HR simulations reproduce the atmospheric response obtained from observations, albeit weaker. This is a hint for the existence of a positive feedback between ocean and atmosphere, as proposed in previous studies. These findings are qualitatively consistent with previous results in literature and, leveraging on recent coordinated modelling efforts, shed light on the effective role of atmospheric horizontal resolution in modelling the atmospheric response to extra-tropical oceanic forcing.</p>

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