In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.

To support the instrument deployment during HyMeX, aiming at studying the high precipitation in the Mediterranean area, a dedicated version of the operational convective-scale AROME-France model was developed: the AROME-WMED model. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. The forecast skill of the model is then assessed during the HyMeX special observation periods and compared to the operational AROME-France.

This work describes a new type of observational simulator for directly comparing measurements and models that takes advantage of all of the information in spectrally resolved top-of-atmosphere data. It describes how to model how the spectrum of the Earth, both in the shortwave and the long wave, changes in response to climate forcings, and provides a path towards inline observational simulation for the upcoming Coupled Model Intercomparison Project – Phase 6.

A model for predicting the timing of activation of rainfall-induced landslides is presented. Calibration against real events is based on genetic algorithms, and provides a family of optimal solutions (kernels) that maximize a fitness function. Accordingly, a set of mobility functions is obtained through convolution with rainfall. Once properly validated, the model allows one to estimate future landslide activations in the same study area, by employing either recorded or forecasted rainfall.

The System for Automated Geoscientific Analyses (SAGA) is a comprehensive and globally established open source geographic information system (GIS) for scientific analysis and modeling. The current version 2.1.4 offers more than 700 tools that represent the broad scopes of SAGA in numerous fields of geoscientific endeavor. In this paper, we inform about the system’s architecture and functionality and highlight the wide spectrum of scientific applications of SAGA in a review of published studies.

This paper introduces the Spatial Processes in HYdrology (SPHY) model (v2.0), its underlying concepts, and some example applications. SPHY has the flexibility to be applied in a wide range of hydrologic applications, on various scales, and can easily be implemented. The most relevant hydrologic processes integrated in the SPHY model are rainfall--runoff, cryosphere processes, evapotranspiration processes, the dynamic evolution of evolution of vegetation cover, and lake/reservoir outflow.

Despite the potential of forest management to mitigate climate change, none of today's predictions of future climate accounts for the impact of forest management. To address this gap in modelling capability, we developed and parametrised a land-surface model to simulate biogeochemical and biophysical effects of forest management. Comparison of model output against data showed an increased model performance in reproducing large-scale spatial patterns and inter-annual variability over Europe.

Three practical meteorological applications with different characteristics highlight the core computer science aspects and applicability of distributed computing to meteorology. Presenting cloud and grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts.

The natural abundance of 14C in CO2 dissolved in seawater is often used to evaluate circulation and age in the ocean and in ocean models. We study limitations of using natural 14C to determine the time elapsed since water had contact with the atmosphere. We find that, globally, bulk 14C age is dominated by two equally important components, (1) the time component of circulation and (2) the “preformed 14C-age”. Considering preformed 14C-age is critical for an assessment of circulation in models.

The application of WRF/Chem to North America shows that it can reproduce most observations and their variation trends from 2006 to 2010. The inclusion of chemical feedbacks reduces biases in meteorological predictions in 2010 but increases errors in comparison to WRF. The net changes in meteorology from 2006 to 2010 are mostly influenced by changes in meteorology and those of ozone and fine particles are influenced by changes in emissions and chemical BCONs, and to a lesser extent meteorology.

An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). This work presents a novel spatiotemporal source apportionment method that generates source impacts for the continental USA. Key sources presented include fossil fuel combustion, biomass burning, dust, sea salt, as well as agricultural activities, biogenics, and aircraft.

The paper examines the coupled thermo-hydro-mechanical (THM) processes that develop in a fractured rock region within a fluid-saturated rock mass due to loads imposed by an advancing glacier. This scenario needs to be examined in order to assess the suitability of potential sites for the location of deep geologic repositories for the storage of high-level nuclear waste. The THM processes are examined using a computational multiphysics approach.

Biogeochemical models are increasingly used in forecasting systems. They provide parameter fields such as nutrients, chlorophyll and oxygen for scientific use and for marine management. This paper describes a model currently used for forecasting the North Atlantic and Arctic oceans on a weekly basis and the evaluation of this model against observations. The model provides reliable fields of nutrients, while the predicted phytoplankton fields are still connected with large uncertainties.

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human-climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. By introducing heretofore-omitted feedbacks between natural and societal drivers in iESM, we can improve scientific understanding of the human-Earth system dynamics.

The paper presents a new sea ice configuration, GSI6.0, in the Met Office coupled atmosphere-ocean-ice model. Differences in the sea ice from a previous configuration (GSI4.0) are explained in the context of a previously published sensitivity study. In summer, Arctic sea ice is thicker and more extensive than in GSI4.0, bringing it closer to the observationally derived data sets. In winter, the Arctic ice is thicker but less extensive than in GSI4.0.

Ecosystem models provide a powerful tool for simulating ocean biology. Care must be exercised when selecting appropriate equations and parameter values to represent chosen marine ecosystems. Here, we present an efficient plankton model testbed, using simplified physics and coded in the freely available language R. Multiple runs can be undertaken for different ocean sites, permitting thorough evaluation of ecosystem model performance. The testbed also serves as an excellent resource for teaching.

This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.

Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.

This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions.

Land cover is an essential variable in earth system models and determines conditions driving biogeochemical, energy and water exchange between ecosystems and the atmosphere. A methodology is presented for mapping plant functional types used in global vegetation models from a updated land cover classification system and open-source conversion tool, resulting from a consultative process among map producers and modelers engaged in the European Space Agency’s Land Cover Climate Change Initiative.

This article presents "Met.3D", a new open-source tool for the interactive 3D visualization of numerical ensemble weather predictions. Met.3D builds a bridge from proven 2D visualization methods commonly used in meteorology to 3D visualization and implements approaches to using the ensemble to allow the user to assess forecast uncertainty. The article is the first part of a two-paper study discussing how 3D and ensemble visualization can be used in a meaningful way suited to weather forecasting.

This article presents the application of interactive 3D visualization of ensemble weather predictions to forecasting warm conveyor belt situations during aircraft-based atmospheric research campaigns. A method to predict 3D probabilities of the spatial occurrence of WCBs is developed and integrated into the 3D visualization tool "Met.3D", introduced in the first part of this two-paper study. A case study demonstrates the use of 3D and uncertainty visualization for weather forecasting.