Validation and analysis of regional present-day climate and climate change simulations over Europe

In the European Commission (EC) project "Regionalization of Anthropogenic Climate Change Simulations, RACCS, recently terminated, 11 European institutions have carried out tests of dynamical and statistical regionalization techniques. The outcome of the "dynamical part" of the project, utilizing a series of high resolution LAMs and a variable resolution global model (all of which we shall refer to as RCMs, Regional Climate Models), is presented here. The per- formance of the dqterent LAMs had first, in a preceding EC project, been tested with "perfect" boundary forcing fields (ECMWF analyses) and also multi-year present-day climate simula- tions with AMIP "perfect ocean " or mixed layer ocean GCM boundary conditions had been validated against available climatological data. The present report involves results of vali- dation and analysis of RCM present-day climate simulations and anthropogenic climate change experiments. Multi-year (5 - 30 years) present-day climate simulations have been per- formed with resolutions between 19 and 70 km (grid lengths) and with boundary conditions from the newest CGCM simulations. The climate change experiments involve various 2xCO2 - ]xCO2 transient greenhouse gas experiments and in one case also changing sulphur aerosols. A common validation and inter-comparison was made at the coordinating institution, MPIfor Meteorology. The validation of the present-day climate simulations shows the importance of systematic errors in the low level general circulation. Such errors seem to induce large errors in precipitation and surface air temperature in the RCMs as well as in the CGCMs providing boundary conditions. Over Europe the field of systematic errors in the mean sea level pressure (MSLP) usually involve an area of too low pressure, often in the form of an east-west trough across Europe with too high pressure to the north and south. New storm-track analyses confirm that the areas of too low pressure are caused by enhanced cyclonic activity and similarly that the areas of too high pressure are caused by reduced such activity. The precise location and strength of the extremes in the MSLP error field seems to be dependent on the physical param- eterization package used. In model pairs sharing the same package the area of too low pressure is deepened further in the RCM compared to the corresponding CGCM, indicating an increase of the excessive cyclonic activity with increasing resolution. From the experiments performed it seems not possible to decide to what extent the systematic errors in the general circulation are the result of local errors in the physical parameterization schemes or remote errors trans- mitted to the European region via the boundary conditions. Additional errors in precipitation and temperature seems to be due to direct local effects of errors in certain parameterization schemes and errors in the SSTs taken from the CGCMs. For all seasons many biases are fOund to be statistically significant compared to estimates of the internal model variability of the time- slice mean values. In the climate change experiments statistically significant European mean temperature changes which are large compared to the corresponding biases are found. How- ever, the changes in the deviations from the European mean temperature as well as the changes in precipitation are only partly sign wcan ce and are of the same order of magnitude or smaller than the corresponding biases found in the present-day climate simulations. Cases of an inter- action between the systematic model errors and the radiative forcing show that generally the errors are not canceling out when the changes are computed. Therefore, reliable regional cli- mate changes can only be achieved after model improvements which reduce their systematic errors sufficiently. Also in future RCM experiments sujiciently long time-slices must be used in order to obtain statistically sign ijicant climate changes on the sub-continental scale aimed at with the present regionalization technique

Validation of present-day regional climate simulations over Europe: nested LAM and variable resolution global model simulations with observed or mixed layer ocean boundary conditions

Multi-year high resolution present-day climate simulations were made with two limited area models (LAMs) at UKMO and MPI and with a global variable resolution spectral model at Meteo-France. We shall refer to these models as the regional climate models (RCMs). Together with the RCM simulations we verify the similar multi-year simulations made with the corresponding coarse resolution global models. We refer to these models as the GCMs. They are the two coarse resolution GCMs whose output were used for boundary conditions to the LAM simulations and a homogeneous coarse resolution version (T42) of the Meteo-France GCM. In the Meteo-France and the MPI simulations observed (AMIP) SST and sea-ice distributions were used whereas in the UKMO simulations we used SST and sea-ice distributions determined from a mixed layer ocean model coupled to the GCM. In the present assessment the main emphasis is put on the validation of precipitation and surface air temperature simulations. The relatively large biases or systematic errors in these parameters in both the GCM and RCM simulations seem in most cases to be explained as the result of systematic errors in the surface pressure (or the low level flow) and the cyclone activity. In most remaining cases they seem to be due to defects in specific physical parameterization schemes. The UKMO and Meteo-France simulations are 10-year integrations whereas the MPI simulations are integrations of 46-months only

Mediterranean Sea response to climate change in an ensemble of twenty first century scenarios

The Mediterranean climate is expected to become warmer and drier during the twenty-first century. Mediterranean Sea response to climate change could be modulated by the choice of the socio-economic scenario as well as the choice of the boundary conditions mainly the Atlantic hydrography, the river runoff and the atmospheric fluxes. To assess and quantify the sensitivity of the Mediterranean Sea to the twenty-first century climate change, a set of numerical experiments was carried out with the regional ocean model NEMOMED8 set up for the Mediterranean Sea. The model is forced by air–sea fluxes derived from the regional climate model ARPEGE-Climate at a 50-km horizontal resolution. Historical simulations representing the climate of the period 1961–2000 were run to obtain a reference state. From this baseline, various sensitivity experiments were performed for the period 2001–2099, following different socio-economic scenarios based on the Special Report on Emissions Scenarios. For the A2 scenario, the main three boundary forcings (river runoff, near-Atlantic water hydrography and air–sea fluxes) were changed one by one to better identify the role of each forcing in the way the ocean responds to climate change. In two additional simulations (A1B, B1), the scenario is changed, allowing to quantify the socio-economic uncertainty. Our 6-member scenario simulations display a warming and saltening of the Mediterranean. For the 2070–2099 period compared to 1961–1990, the sea surface temperature anomalies range from +1.73 to +2.97 °C and the SSS anomalies spread from +0.48 to +0.89. In most of the cases, we found that the future Mediterranean thermohaline circulation (MTHC) tends to reach a situation similar to the eastern Mediterranean Transient. However, this response is varying depending on the chosen boundary conditions and socio-economic scenarios. Our numerical experiments suggest that the choice of the near-Atlantic surface water evolution, which is very uncertain in General Circulation Models, has the largest impact on the evolution of the Mediterranean water masses, followed by the choice of the socio-economic scenario. The choice of river runoff and atmospheric forcing both have a smaller impact. The state of the MTHC during the historical period is found to have a large influence on the transfer of surface anomalies toward depth. Besides, subsurface currents are substantially modified in the Ionian Sea and the Balearic region. Finally, the response of thermosteric sea level ranges from +34 to +49 cm (2070–2099 vs. 1961–1990), mainly depending on the Atlantic forcing

Measures of Model Performance Based On the Log Accuracy Ratio

Quantitative assessment of modeling and forecasting of continuous quantities uses a variety of approaches. We review existing literature describing metrics for forecast accuracy and bias, concentrating on those based on relative errors and percentage errors. Of these accuracy metrics, the mean absolute percentage error (MAPE) is one of the most common across many fields and has been widely applied in recent space science literature and we highlight the benefits and drawbacks of MAPE and proposed alternatives. We then introduce the log accuracy ratio and derive from it two metrics: the median symmetric accuracy and the symmetric signed percentage bias. Robust methods for estimating the spread of a multiplicative linear model using the log accuracy ratio are also presented. The developed metrics are shown to be easy to interpret, robust, and to mitigate the key drawbacks of their more widely used counterparts based on relative errors and percentage errors. Their use is illustrated with radiation belt electron flux modeling examples.Peer reviewe

ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions: Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs

A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4–6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data

How realistic are air quality hindcasts driven by forcings from climate model simulations?

Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O<sub>3</sub>, NO<sub>x</sub>, SO<sub>2</sub> and, with some bias that can be explained by the set-up, PM<sub>10</sub>. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality

Predictability of soil moisture and river flows over France for the spring season

Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960–2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 880 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifers. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Soil moisture and river flow skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened