ALBERT

Description: 〈b〉Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1〈/b〉〈br〉 Guy P. Brasseur, Ying Xie, Anna Katinka Petersen, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Jianming Xu, and Guangqiang Zhou〈br〉 Geosci. Model Dev., 12, 33-67, https://doi.org/10.5194/gmd-12-33-2019, 2019〈br〉 An operational multi-model forecasting system for air quality provides daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas in China. The paper presents an intercomparison of the different forecasts performed during a specific period of time and highlights recurrent differences between the model output. Pathways to improve the forecasts by the multi-model system are suggested.

Description: 〈b〉RandomFront 2.3: a physical parameterisation of fire spotting for operational fire spread models – implementation in WRF-SFIRE and response analysis with LSFire+〈/b〉〈br〉 Andrea Trucchia, Vera Egorova, Anton Butenko, Inderpreet Kaur, and Gianni Pagnini〈br〉 Geosci. Model Dev., 12, 69-87, https://doi.org/10.5194/gmd-12-69-2019, 2019〈br〉 Wildfires are a concrete problem and impact on human life, property and the environment. An extremely dangerous phenomenon is so-called 〈q〉fire spotting〈/q〉, i.e., the generation of secondary ignitions responsible for dangerous flare-ups during wildfires. The aim of this research was to improve the tools used for risk management through the inclusion of fire spotting in operational wildfire simulators used by forest service agencies.

Description: 〈b〉Comparison of Different Sequential Assimilation Algorithms for Satellite-derived Leaf Area Index Using the Data Assimilation Research Testbed (lanai)〈/b〉〈br〉 Xiao-Lu Ling, Cong-Bin Fu, Zong-Liang Yang, and Wei-Dong Guo〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-232,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Both observation and simulation can provide the temporal and spatial variation of vegetation characteristic, while they are not satisfactory for understanding the mechanism of the exchange between ecosystems and atmosphere. Data assimilation (DA) can combine the observation and models via mathematical statistical analysis.The results show that the Ensemble Adjust Kalman Filter (EAKF) is the optical algorithm. In addition, models perform better when the DA accept more proportion of observation.

Description: 〈b〉GemPy 1.0: open-source stochastic geological modeling and inversion〈/b〉〈br〉 Miguel de la Varga, Alexander Schaaf, and Florian Wellmann〈br〉 Geosci. Model Dev., 12, 1-32, https://doi.org/10.5194/gmd-12-1-2019, 2019〈br〉 〈i〉GemPy〈/i〉 is an open-source Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. 〈i〉GemPy〈/i〉 is implemented in the programming language Python, making use of a highly efficient underlying library, Theano, for efficient code generation that performs automatic differentiation. This enables the link to probabilistic machine-learning and Bayesian inference frameworks.

Description: 〈b〉Calibration and analysis of the uncertainty in downscaling global land use and land cover projections from GCAM〈/b〉〈br〉 Min Chen, Chris R. Vernon, Maoyi Huang, Katherine V. Calvin, and Ian P. Kraucunas〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-248,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human-Earth system models. However, Demeter has not been intensively calibrated, and we still lack a good knowledge about its sensitivity to key parameters and the parameter uncertainties. This paper aims to solve this problem.

Description: 〈b〉GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems〈/b〉〈br〉 Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise〈br〉 Geosci. Model Dev., 12, 677-698, https://doi.org/10.5194/gmd-12-677-2019, 2019〈br〉 This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM examines the future evolution of these systems through the end of the 21st century. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region’s demand for energy affect energy, water, and land in other regions.

Description: 〈b〉Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]〈/b〉〈br〉 Elias C. Massoud, Chonggang Xu, Rosie Fisher, Ryan Knox, Anthony Walker, Shawn Serbin, Bradley Christoffersen, Jennifer Holm, Lara Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel Johnson, Jeff Chambers, Charlie Koven, Nate McDowell, and Jasper Vrugt〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-6,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 2 comments)〈br〉 We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model for 5000 times with changing input parameter values, we found that 1) the photosynthetic capacity controls carbon fluxes, 2) the allometry is important for tree growth, and 3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.

Description: 〈b〉University of Warsaw Lagrangian Cloud Model (UWLCM) 1.0: a modern Large-Eddy Simulation tool for warm cloud modeling with Lagrangian microphysics〈/b〉〈br〉 Piotr Dziekan, Maciej Waruszewski, and Hanna Pawlowska〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-281,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 A new anelastic large-eddy simulation model with an Eulerian dynamical core and a Lagrangian particle-based microphysics is presented. The dynamical core uses the MPDATA advection scheme and the generalized conjugate residual pressure solver, while the microphysics scheme is based on the Super-Droplet Method. Algorithms for coupling of the Lagrangian microphysics with the Eulerian dynamics are presented, including spatial and temporal discretizations and a condensation sub-stepping algorithm. The model is free of numerical diffusion in the droplet size spectrum. Activation of droplets is modeled explicitly, making the model less sensitive to local supersaturation maxima than models in which activation is parametrised. Simulations of a drizzling marine stratocumulus give results in agreement with other LES models. Relatively low number of computational particles is sufficient to obtain the correct averaged properties of a cloud. High computational performance is achieved thanks to the use of GPU accelerators.

Description: 〈b〉The multiscale Routing Model mRM v1.0: simple river routing at resolutions from 1 to 50 km〈/b〉〈br〉 Stephan Thober, Matthias Cuntz, Matthias Kelbling, Rohini Kumar, Juliane Mai, and Luis Samaniego〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-13,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 1 comment)〈br〉 We present a model that aggregates simulated runoff along a river (i.e., a routing model). The unique feature of the model is that it can be run at multiple resolution without any modification of the input data. The model internally (dis-)aggregates all input data to the resolution given by the user. The model performance does not depend on the chosen resolution. This allows efficient model calibration at low resolution and subsequent model application at high resolution.

Description: 〈b〉Assessment of the Finite VolumE Sea Ice Ocean Model (FESOM2.0), Part I: Description of selected key model elements and comparison to its predecessor version〈/b〉〈br〉 Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-329,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice–Ocean circulation Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases, but with a remarkable performance speedup with a three times higher throughput.

Description: 〈b〉Beo v1.0: Numerical model of heat flow and low-temperature thermochronology in hydrothermal systems〈/b〉〈br〉 Elco Luijendijk〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-341,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This paper presents a new model code that can be used to date the flow of hot fluids in the crust and the age of hot springs. It does so by modeling the thermal effects of fluid flow in the subsurface and by comparing the results with low-temperature thermochronometers, which is a widely used method to quantify the temperature history of minerals and rocks. The model also demonstrates that the depth and angle of permeable faults have a strong effect on temperatures in hot springs.

Description: 〈b〉Semantic Description and Complete Computer Characterization of Structural Geological Models〈/b〉〈br〉 Xianglin Zhan, Jiandong Liang, Cai Lu, and Guangmin Hu〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-305,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We proposed the semantic descriptions for structural geological models in order to facilitate computer based processing of geological semantics. The semantic description is a complete representation of the structural model. And we use the multi-level heterogeneous network to be the computer characterization of the semantic description. Semantic descriptions can also be used to constrain structure modeling which forms a top-down modeling process. We validated the effectiveness with actual data.

Description: 〈b〉The road weather model RoadSurf driven by the HARMONIE-Climate regional climate model: evaluation over Finland〈/b〉〈br〉 Erika Toivonen, Marjo Hippi, Hannele Korhonen, Ari Laaksonen, Markku Kangas, and Joni-Pekka Pietikäinen〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-330,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We evaluated the skill of the road weather model RoadSurf to reproduce present-day road weather conditions in Finland when driven by a high-resolution regional climate model. Simulated road surface temperatures and conditions were compared to observations between 2002 and 2014 at 25 Finnish road weather stations. RoadSurf accurately captured the main characteristics of road weather conditions. Thus, this model can be used to study the future scenarios of road weather in the study area.

Description: 〈b〉IMEX_SfloW2D 1.0: a depth-averaged numerical flow model for pyroclastic avalanches〈/b〉〈br〉 Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Giacomo Lari, and Alvaro Aravena〈br〉 Geosci. Model Dev., 12, 581-595, https://doi.org/10.5194/gmd-12-581-2019, 2019〈br〉 Pyroclastic avalanches are a type of granular flow generated at active volcanoes by different mechanisms, including the collapse of steep pyroclastic deposits (e.g., scoria and ash cones) and fountaining during moderately explosive eruptions. We present IMEX_SfloW2D, a depth-averaged flow model describing the granular mixture as a single-phase granular fluid. Benchmark cases and preliminary application to the simulation of the 11 February pyroclastic avalanche at Mt. Etna (Italy) are shown.

Description: 〈b〉Computing climate-smart urban land use with the Integrated Urban Complexity model (IUCm 1.0)〈/b〉〈br〉 Roger Cremades and Philipp S. Sommer〈br〉 Geosci. Model Dev., 12, 525-539, https://doi.org/10.5194/gmd-12-525-2019, 2019〈br〉 Our results show how to halve the energy consumption of urban transportation by transforming the city.

Description: 〈b〉Global aerosol modeling with MADE3 (v3.0) in EMAC (based on v2.53): model description and evaluation〈/b〉〈br〉 J. Christopher Kaiser, Johannes Hendricks, Mattia Righi, Patrick Jöckel, Holger Tost, Konrad Kandler, Bernadett Weinzierl, Daniel Sauer, Katharina Heimerl, Joshua P. Schwarz, Anne E. Perring, and Thomas Popp〈br〉 Geosci. Model Dev., 12, 541-579, https://doi.org/10.5194/gmd-12-541-2019, 2019〈br〉 The implementation of the aerosol microphysics submodel MADE3 into the global atmospheric chemistry model EMAC is described and evaluated against an extensive pool of observational data, focusing on aerosol mass and number concentrations, size distributions, composition, and optical properties. EMAC (MADE3) is able to reproduce main aerosol properties reasonably well, in line with the performance of other global aerosol models.

Description: 〈b〉Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) v1.0: an open- source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous space-state formulations〈/b〉〈br〉 Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-332,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Computer models are used to predict river flows. A good model should represent the river basin it is applied to, so that its flow predictions are as accurate as possible. However, many different computer models exist and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrologic models into a single coding framework. This allows users to compare models in an objective way and can teach us about model differences.

Description: 〈b〉On fluctuating air-sea-interaction in local models: linear theory〈/b〉〈br〉 Achim Wirth〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-300,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The dynamics of three local linear models of air-sea-interaction commonly employed in climate or ocean simulations is compared. The models differ by whether or not the ocean velocity is included in the shear calculation applied to the ocean and the atmosphere. Analytic calculations for the models with deterministic and random forcing (white and colored) are presented.The fluctuation-dissipation-relation, the fluctuation-dissipation-theorem and the fluctuation-theorem is discussed.

Description: 〈b〉A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)〈/b〉〈br〉 Matthew R. Hipsey, Louise C. Bruce, Casper Boon, Brendan Busch, Cayelan C. Carey, David P. Hamilton, Paul C. Hanson, Jordan S. Read, Eduardo de Sousa, Michael Weber, and Luke A. Winslow〈br〉 Geosci. Model Dev., 12, 473-523, https://doi.org/10.5194/gmd-12-473-2019, 2019〈br〉 The General Lake Model (GLM) has been developed to undertake simulation of a diverse range of wetlands, lakes, and reservoirs. The model supports the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land use change. The paper describes the science basis and application of the model.

Description: 〈b〉Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5〈/b〉〈br〉 Hocheol Seo and Yeonjoo Kim〈br〉 Geosci. Model Dev., 12, 457-472, https://doi.org/10.5194/gmd-12-457-2019, 2019〈br〉 〈p〉Fire plays an important role in terrestrial ecosystems. The burning of biomass affects carbon and water fluxes and vegetation distribution. To understand the effect of interactive processes of fire and ecological succession on surface carbon and water fluxes, this study employed the Community Land Model version 4.5 to conduct a series of experiments that included and excluded fire and dynamic vegetation processes. Results of the experiments that excluded the vegetation dynamics showed a global increase in net ecosystem production (NEP) in post-fire regions, whereas the inclusion of vegetation dynamics revealed a fire-induced decrease in NEP in some regions, which was depicted when the dominant vegetation type was changed from trees to grass. Carbon emissions from fires are enhanced by reduction in NEP when vegetation dynamics are considered; however, this effect is somewhat mitigated by the increase in NEP when vegetation dynamics are not considered. Fire-induced changes in vegetation modify the soil moisture profile because grasslands are more dominant in post-fire regions. This results in less moisture within the top soil layer than that in unburned regions, even though transpiration is reduced overall. These findings are different from those of previous fire model evaluations that ignored vegetation dynamics and thus highlight the importance of interactive processes between fires and vegetation dynamics in evaluating recent model developments.〈/p〉

Description: 〈b〉CAM6 simulation of mean and extreme precipitation over Asia: Sensitivity to upgraded physical parameterizations and higher horizontal resolution〈/b〉〈br〉 Lei Lin, Andrew Gettelman, Yangyang Xu, Chenglai Wu, Zhili Wang, and Wenjie Dong〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-1,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in 2018 with the default 1º horizontal resolution and a higher resolution simulation (approximately 0.25º), against various precipitation observational datasets over Asia. With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia.

Description: 〈b〉A high-resolution biogeochemical model (ROMS 3.4 + bio_Fennel) of the East Australian Current system〈/b〉〈br〉 Carlos Rocha, Christopher A. Edwards, Moninya Roughan, Paulina Cetina-Heredia, and Colette Kerry〈br〉 Geosci. Model Dev., 12, 441-456, https://doi.org/10.5194/gmd-12-441-2019, 2019〈br〉 Off southeast Australia, the East Australian Current (EAC) moves warm nutrient-poor waters towards the pole. In this region, the EAC and a large number of vortices pinching off it strongly affect phytoplankton’s access to nutrients and light. To study these dynamics, we created a numerical model that is able to solve the ocean conditions and how they modulate the foundation of the region’s ecosystem. We validated model results against available data and this showed that the model performs well.

Description: 〈b〉VISIR-I.b: waves and ocean currents for energy efficient navigation〈/b〉〈br〉 Gianandrea Mannarini and Lorenzo Carelli〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-292,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The VISIR ship routing model is updated in order to cope with ocean currents. Currents are employed together with waves for computing optimal ship tracks in the Atlantic Ocean. These tracks show a great seasonal and regional variability, following a variable influence of waves and currents. We assess how these tracks contribute to voyage energy efficiency gains using a standard indicator of the International Maritime Organization. The new model features are validated vs. an exact benchmark.

Description: 〈b〉FVM 1.0: a nonhydrostatic finite-volume dynamical core for the IFS〈/b〉〈br〉 Christian Kühnlein, Willem Deconinck, Rupert Klein, Sylvie Malardel, Zbigniew P. Piotrowski, Piotr K. Smolarkiewicz, Joanna Szmelter, and Nils P. Wedi〈br〉 Geosci. Model Dev., 12, 651-676, https://doi.org/10.5194/gmd-12-651-2019, 2019〈br〉 We present a novel finite-volume dynamical core formulation considered for future numerical weather prediction at ECMWF. We demonstrate that this formulation can be competitive in terms of solution quality and computational efficiency to the proven spectral-transform dynamical core formulation currently operational at ECMWF, while providing a local, more scalable discretization, conservative and monotone advective transport, and flexible meshes.

Description: 〈b〉Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): Impacts of resolution and physics〈/b〉〈br〉 Chun Zhao, Mingyue Xu, Yu Wang, Meixin Zhang, Jianping Guo, Zhiyuan Hu, Lai-Yung Leung, William Skamarock, and Michael Duda〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-340,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The global variable-resolution simulations at global uniform and variable resolutions share similar characteristics of precipitation and wind in the refined region. The experiments reveal the significant impacts of resolution on simulating the distribution and intensity of precipitation and updrafts. This study provides the evidence supporting using convection-permitting global variable-resolution simulation for studying extreme precipitation.

Description: 〈b〉CLIMADA – a global weather and climate risk assessment platform〈/b〉〈br〉 Gabriela Aznar-Siguan and David N. Bresch〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-338,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The need for assessing the risk of weather events is ever increasing. In addition to quantification of risk today, the role of aggravating factors such as population growth and changing climate conditions matter too. We present the open source software CLIMADA, which integrates hazard, exposure and vulnerability to compute metrics to assess risk and to quantify socio-economic impact, and use it to estimate and contextualise the damage of hurricane Irma through the Caribbean in 2017.

Description: 〈b〉Incorporating Wind Sheltering and Sediment Heat Flux into 1-D Models of Small Boreal Lakes: A Case Study with the Canadian Small Lake Model V2.0〈/b〉〈br〉 Murray D. MacKay〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-258,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Lakes interact with their surroundings through flux exchange at their bottom sediments and with the atmosphere at the surface, and these linkages must be represented in climate and weather prediction models in order to completely elucidate the role of lakes in the climate system. Here schemes for the inclusion of wind sheltering and sediment heat flux simple enough to be included in any one dimensional lake model are presented, along with example simulations of the Canadian Small Lake Model.

Description: 〈b〉Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets〈/b〉〈br〉 Grzegorz Muszynski, Karthik Kashinath, Vitaliy Kurlin, Michael Wehner, and Prabhat〈br〉 Geosci. Model Dev., 12, 613-628, https://doi.org/10.5194/gmd-12-613-2019, 2019〈br〉 We present the automated method for recognizing atmospheric rivers in climate data, i.e., climate model output and reanalysis product. The method is based on topological data analysis and machine learning, both of which are powerful tools that the climate science community often does not use. An advantage of the proposed method is that it is free of selection of subjective threshold conditions on a physical variable. This method is also suitable for rapidly analyzing large amounts of data.

Description: 〈b〉Limitations of the 1 % experiment as the benchmark idealized experiment for carbon cycle intercomparison in C〈sup〉4〈/sup〉MIP〈/b〉〈br〉 Andrew Hugh MacDougall〈br〉 Geosci. Model Dev., 12, 597-611, https://doi.org/10.5194/gmd-12-597-2019, 2019〈br〉 The 1 % per year exponential change in CO〈sub〉2〈/sub〉 concentration experiment is an idealized climate change scenario that has traditionally been used to facilitate comparison of different climate models and to create benchmark statistics. Here, we examine the limitations of this experiment for assessing the global carbon cycle and propose an alternative idealized experiment.

Description: 〈b〉Introducing the Probabilistic Earth-System Model: Examining The Impact of Stochasticity in EC-Earth v3.2〈/b〉〈br〉 Kristian Strommen, Hannah M. Christensen, David MacLeod, Stephan Juricke, and Tim N. Palmer〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-337,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Due to computational limitations, climate models cannot fully resolve the laws of physics below a certain scale, a large source of errors and uncertainty. Stochastic schemes aim to account for this by randomly sampling the possible unresolved states. We develop new stochastic schemes for the EC-Earth climate model and evaluate their impact on model performance. While several benefits are found, the impact is sometimes too strong, suggesting such schemes must be carefully calibrated before use.

Description: 〈b〉The INALT family – a set of high-resolution nests for the Agulhas Current system within global NEMO ocean/sea-ice configurations〈/b〉〈br〉 Franziska U. Schwarzkopf, Arne Biastoch, Claus W. Böning, Jérôme Chanut, Jonathan V. Durgadoo, Klaus Getzlaff, Jan Harlaß, Jan K. Rieck, Christina Roth, Markus M. Scheinert, and René Schubert〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-312,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 A family of nested global ocean general circulation model configurations, the INALT family, has been established with resolutions of 1/10°, 1/20° and 1/60° in the South Atlantic and western Indian oceans, covering the greater Agulhas Current (AC) system. The INALT family provides a consistent set of configurations that allows to address eddy dynamics in the AC system and their impact on the large-scale ocean circulation.

Description: 〈b〉A Lagrangian convective transport scheme including a simulation of the time air parcels spend in updrafts〈/b〉〈br〉 Ingo Wohltmann, Ralph Lehmann, Georg A. Gottwald, Karsten Peters, Alain Protat, Valentin Louf, Christopher Williams, Wuhu Feng, and Markus Rex〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-5,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We present a trajectory based model for simulating the transport of air parcels by convection. Our model extends the approach of existing models by explicitly simulating vertical updraft velocities inside the clouds and the time that an air parcel spends inside the convective event.

Description: 〈b〉glmGUI v1.0: an R-based Geographical User Interface and toolbox for GLM (General Lake Model) simulations〈/b〉〈br〉 Thomas Bueche, Marko Wenk, Benjamin Poschlod, Filippo Giadrossich, Mario Pirastru, and Mark Vetter〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-314,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 1 comment)〈br〉 The R-based Geographical User Interface glmGUI provides tools for pre- and postprocessing of General Lake Model (GLM) simulations, including an autocalibration, parameter sensitivity analysis, and several plot options. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The toolbox is tested for two sites (Lake Ammersee, Germany, and Lake Baratz, Italy).

Description: 〈b〉What do we do with model simulation crashes? Recommendations for global sensitivity analysis of earth and environmental systems models〈/b〉〈br〉 Razi Sheikholeslami, Saman Razavi, and Amin Haghnegahdar〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-17,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The ever-growing complexity of the Earth and Environmental Systems Models will pose many types of software development and implementation issues such as parameter-induced simulation crashes which are mainly caused by violation of the numerical stability conditions. Here, we present a new strategy to cope with crashed simulations when performing sensitivity analysis. Our results show that this strategy can scale well to the dimensionality of the model, sample size, and the number crashes.

Description: 〈b〉Mass-conserving coupling of total column CO〈sub〉2〈/sub〉 (XCO〈sub〉2〈/sub〉) from global to mesoscale models: Case study with CMS-Flux inversion system and WRF-Chem (v3.6.1)〈/b〉〈br〉 Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-342,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at 〈a href="https://github.com/psu-inversion/WRF_Boundary_Coupling" target="_blank"〉https://github.com/psu-inversion/WRF_Boundary_Coupling〈/a〉.

Description: 〈b〉PatCC1: an Efficient Parallel Triangulation Algorithm for Spherical and Planar Grids with Commonality and Parallel Consistency〈/b〉〈br〉 Haoyu Yang, Li Liu, Cheng Zhang, Ruizhe Li, Chao Sun, Xinzhu Yu, Hao Yu, Zhiyuan Zhang, and Bin Wang〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-284,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 〈p〉Graphs are commonly gridded by triangulation; i.e., the generation of a set of triangles for the points of the graph. This technique can also be used in a coupler to improve the commonality of data interpolation between different horizontal model grids. This paper proposes a new parallel triangulation algorithm, PatCC1 (Parallel triangulation algorithm with Commonality and parallel Consistency, version 1), for spherical and planar grids. Experimental evaluation results demonstrate the efficient parallelization of PatCC1 using a hybrid of MPI and OpenMP. They also show PatCC1 to have greater commonality than existing parallel triangulation algorithms (i.e., it is capable of handling more types of model grids) and that it guarantees parallel consistency (i.e., it achieves exactly the same triangulation result under different parallel settings).〈/p〉

Description: 〈b〉Land surface model photosynthesis and parameter calibration for boreal sites with adaptive population importance sampler〈/b〉〈br〉 Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-313,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We assess the differences of six stomatal conductance functions, imbedded into a land-vegetation model, on ten boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event on one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation dependent model behaviour that we are able to partially amend.

Description: 〈b〉Regionally refined capability in E3SM Atmosphere Model Version 1 (EAMv1) and applications for high-resolution modelling〈/b〉〈br〉 Qi Tang, Stephen A. Klein, Shaocheng Xie, Wuyin Lin, Jean-Christophe Golaz, Erika L. Roesler, Mark A. Taylor, Philip J. Rasch, David C. Bader, Larry K. Berg, Peter Caldwell, Scott Giangrande, Richard Neale, Yun Qian, Laura D. Riihimaki, Charles S. Zender, Yuying Zhang, and Xue Zheng〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-11,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 〈p〉Climate simulation with more accurate process-level representation at finer resolutions is a pressing need in order to provide actionable information to policy-makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building, and running high-resolution (HR, here 0.25° average grid spacing at the equator) models (HRM). A more affordable path to HRM is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low-resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations, as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces both well- and poorly simulated behaviours of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behaviour of physical parameterizations, especially for variables influencing sub-grid scale physical processes. RRM can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a testbed, and as such represents an efficient and more robust physics testbed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective approach for HRM development and hydrologic research.〈/p〉

Description: 〈b〉A simplified parameterization of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) for global chemistry and climate models〈/b〉〈br〉 Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Eloise A. Marais, Zhe Peng, Benjamin A. Nault, Weiwei Hu, Pedro Campuzano-Jost, and Jose L. Jimenez〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-9,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We developed a parameterization method for secondary organic aerosol derived from isoprene epxydiols based on the detailed chemical mechanism. Our parameterizations were tested using a box model and 3-D chemical transport model, which accurately captured the spatiotemporal distribution and response to changes on emissions, while being more computationally efficient. The method developed in this study can be applied to global climate models for long-term studies with less computational cost.

Description: 〈b〉Assessment of Sub-Shelf Melting Parameterisations Using theOcean-Ice Sheet Coupled Model NEMO(v3.6)-Elmer/Ice(v8.3)〈/b〉〈br〉 Lionel Favier, Nicolas C. Jourdain, Adrian Jenkins, Nacho Merino, Gaël Durand, Olivier Gagliardini, Fabien Gillet-Chaulet, and Pierre Mathiot〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-26,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The melting due to oceanic forcing at the base of ice shelves is the main driver of current Antarctic marine terminating glaciers. We assess various melting parameterisations ranging from simple scalings with far-field thermal driving to emulators of box and plume models, using a new Ocean-Ice Sheet coupled model. Two types of quadratic dependencies to thermal forcing show the best trade-off between the simplicity of the approach and the results accuracy in comparison to the coupled model.

Description: 〈b〉Development and evaluation of pollen source methodologies for the Victorian Grass Pollen Emissions Module VGPEM1.0〈/b〉〈br〉 Kathryn M. Emmerson, Jeremy D. Silver, Edward Newbigin, Edwin R. Lampugnani, Cenk Suphioglu, Alan Wain, and Elizabeth Ebert〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-43,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We present the first representation of grass pollen in a 3D dispersion model anywhere in Australia, tested using observations from eight counting sites in Victoria. The capability was developed in response to the severe thunderstorm asthma event which took place in Melbourne in November 2016. Ten pollen emission methodologies were developed and evaluated. The best results were obtained using statistical methods that combine elements of the satellite derived Enhanced Vegetation Index.

Description: 〈b〉How to use mixed precision in Ocean Models〈/b〉〈br〉 Oriol Tintó Prims, Mario C. Acosta, Andrew M. Moore, Miguel Castrillo, Kim Serradell, Ana Cortés, and Francisco J. Doblas-Reyes〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-20,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Mixed-precision approaches can provide substantial speed-ups for both computing- and memory-bound codes requiring little effort. A novel method to enable modern and legacy codes to benefit from a reduction of precision without sacrificing accuracy is presented. Using a precision emulator and a divide-and-conquer algorithm it identifies the parts that cannot handle reduced precision and the ones that can. The method has been proved using two ocean models, NEMO and ROMS, with promising results.

Description: 〈b〉DATeS: a highly extensible data assimilation testing suite v1.0〈/b〉〈br〉 Ahmed Attia and Adrian Sandu〈br〉 Geosci. Model Dev., 12, 629-649, https://doi.org/10.5194/gmd-12-629-2019, 2019〈br〉 This work describes DATeS, a highly extensible data assimilation package. DATeS seeks to provide a unified testing suite for data assimilation applications that allows researchers to easily compare different methodologies in different settings with minimal coding effort. The core of DATeS is written in Python. The main functionalities, such as model propagation and assimilation, can however be written in low-level languages such as C or Fortran to attain high levels of computational efficiency.

Description: 〈b〉Global tropospheric effects of aromatic chemistry with the SAPRC-11 mechanism implemented in GEOS-Chem version 9-02〈/b〉〈br〉 Yingying Yan, David Cabrera-Perez, Jintai Lin, Andrea Pozzer, Lu Hu, Dylan B. Millet, William C. Porter, and Jos Lelieveld〈br〉 Geosci. Model Dev., 12, 111-130, https://doi.org/10.5194/gmd-12-111-2019, 2019〈br〉 The GEOS-Chem model has been updated with the SAPRC-11 aromatics chemical mechanism to evaluate global and regional effects of aromatics on tropospheric oxidation capacity. Our results reveal relatively slight changes in ozone, hydroxyl radical, and nitrogen oxides on a global mean basis (1–4 %), although remarkable regional differences (5–20 %) exist near the source regions. Improved representation of aromatics is important to simulate the tropospheric oxidation.

Description: 〈b〉Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations〈/b〉〈br〉 Sergey Venevsky, Yannick Le Page, José M. C. Pereira, and Chao Wu〈br〉 Geosci. Model Dev., 12, 89-110, https://doi.org/10.5194/gmd-12-89-2019, 2019〈br〉 We present SEVER-FIRE (v1.0), incorporated into the SEVER DGVM. One of the major focuses of SEVER-FIRE is an implementation of the pyrogenic behavior of humans (timing of their activities and their willingness and necessity to ignite or suppress fire), related to socioeconomic and demographic conditions in a geographical domain of the model application. Unlike other DGVM- and ESM-based global fire models, we do not use any satellite-derived assumptions in equations of fire model development.

Description: 〈b〉Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)〈/b〉〈br〉 Chantelle Burton, Richard Betts, Manoel Cardoso, Ted R. Feldpausch, Anna Harper, Chris D. Jones, Douglas I. Kelley, Eddy Robertson, and Andy Wiltshire〈br〉 Geosci. Model Dev., 12, 179-193, https://doi.org/10.5194/gmd-12-179-2019, 2019〈br〉 Fire and land-use change are important disturbances within the Earth system, and their inclusion in models is critical to enable the correct simulation of vegetation cover. Here we describe developments to the land surface model JULES to represent explicit land-use change and fire and to assess the effects of each process on present day vegetation compared to observations. Using historical land-use data and the fire model INFERNO, overall model results are improved by the developments.

Description: 〈b〉Reanalysis of the PacIOOS Hawaiian Island Ocean Forecast System, an implementation of the Regional Ocean Modeling System v3.6〈/b〉〈br〉 Dale Partridge, Tobias Friedrich, and Brian S. Powell〈br〉 Geosci. Model Dev., 12, 195-213, https://doi.org/10.5194/gmd-12-195-2019, 2019〈br〉 This paper demonstrates the improvements made to an operational ocean forecast model around the Hawaiian Islands by performing a reanalysis of the model over a 10-year period. Using a number of different measurements we show the role a variety of observations play in producing the forecast, in particular the contribution of high-frequency radar.

Description: 〈b〉Assimilation of SCATSAR Soil Wetness Index in SURFEX 8.0 to improve weather forecasts〈/b〉〈br〉 Stefan Schneider and Bernhard Bauer-Marschallinger〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-273,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This paper investigates the question if satellite-measured soil moisture data are useful to improve weather forecasts. To answer this question, historical forecasts are re-computed with and without this additional data source and compared against measurements from weather stations. This test shows an positive impact of using soil moisture data which indicates that they should be used operationally in regional weather forecast models.

Description: 〈b〉Quantifying uncertainties due to chemistry modeling – evaluation of tropospheric composition simulations in the CAMS model〈/b〉〈br〉 Vincent Huijnen, Andrea Pozzer, Joaquim Arteta, Guy Brasseur, Idir Bouarar, Simon Chabrillat, Yves Christophe, Thierno Doumbia, Johannes Flemming, Jonathan Guth, Béatrice Josse, Vlassis A. Karydis, Virginie Marécal, and Sophie Pelletier〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-331,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in ECMWF’s Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). This configuration of having various chemistry versions within IFS provides a quantification of uncertainties in CAMS trace gas products that are induced by chemistry modeling.

Description: 〈b〉Particle swarm optimization for the estimation of surface complexation constants with the geochemical model PHREEQC-3.1.2〈/b〉〈br〉 Ramadan Abdelaziz, Broder J. Merkel, Mauricio Zambrano-Bigiarini, and Sreejesh Nair〈br〉 Geosci. Model Dev., 12, 167-177, https://doi.org/10.5194/gmd-12-167-2019, 2019〈br〉 The paper presents a robust tool to estimate the thermodynamic surface complexation parameter for the sorption of uranium(VI) onto quartz surfaces. The optimization package hydroPSO R is coupled with the geochemical speciation code PHREEQC. hydroPSO used the m parameter estimation tool for geochemical modeling with PHREEQC. Coupled hydroPSO with PHREEQC proved to be a robust tool to estimate surface complexation constants for uranium(VI) species on quartz.

Description: 〈b〉HERMESv3, a stand-alone multiscale atmospheric emission modelling framework – Part 1: global and regional module〈/b〉〈br〉 Marc Guevara, Carles Tena, Manuel Porquet, Oriol Jorba, and Carlos Pérez García-Pando〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-324,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Atmospheric emission inventories, which describe the amounts of pollutants released into the air by different sources and for specific regions, are an essential input to numerical models that estimate air quality. This work presents the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), an open-source modelling framework that allows adapting existing global and regional emission inventories to the input requirements of air quality models in a flexible and transparent way.

Description: 〈b〉TREMOL: A stochastic rupture earthquake code based on the fiber bundle model. Application to Mexican subduction earthquakes〈/b〉〈br〉 Marisol Monterrubio-Velasco, Quetzalcóatl Rodríguez-Pérez, Ramón Zúñiga, Doreen Scholz, Armando Aguilar-Meléndez, and Josep de la Puente〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-323,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 2 comments)〈br〉 Earthquakes are the result of brittle failure within the heterogeneous crust of the Earth. In this article, we present a computer code called 〈q〉stochasTic Rupture Earthquake MOdeL〈/q〉, TREMOL, developed to investigate the rupture process of asperities on the earthquake rupture surface. According to our results, TREMOL is able to simulated magnitudes of real earthquakes, showing that can be a powerful tool which can deliver promising new insights into earthquake rupture processes.

Description: 〈b〉Description and evaluation of the Community Ice Sheet Model (CISM) v2.1〈/b〉〈br〉 William H. Lipscomb, Stephen F. Price, Matthew J. Hoffman, Gunter R. Leguy, Andrew R. Bennett, Sarah L. Bradley, Katherine J. Evans, Jeremy G. Fyke, Joseph H. Kennedy, Mauro Perego, Douglas M. Ranken, William J. Sacks, Andrew G. Salinger, Lauren J. Vargo, and Patrick H. Worley〈br〉 Geosci. Model Dev., 12, 387-424, https://doi.org/10.5194/gmd-12-387-2019, 2019〈br〉 This paper describes the Community Ice Sheet Model (CISM) version 2.1. CISM solves equations for ice flow, heat conduction, surface melting, and other processes such as basal sliding and iceberg calving. It can be used for ice-sheet-only simulations or as the ice sheet component of the Community Earth System Model. Model solutions have been verified for standard test problems. CISM can efficiently simulate the whole Greenland ice sheet, with results that are broadly consistent with observations.

Description: 〈b〉Ecological ReGional Ocean Model with vertically resolved sediments (ERGOM SED 1.0): coupling benthic and pelagic biogeochemistry of the south-western Baltic Sea〈/b〉〈br〉 Hagen Radtke, Marko Lipka, Dennis Bunke, Claudia Morys, Jana Woelfel, Bronwyn Cahill, Michael E. Böttcher, Stefan Forster, Thomas Leipe, Gregor Rehder, and Thomas Neumann〈br〉 Geosci. Model Dev., 12, 275-320, https://doi.org/10.5194/gmd-12-275-2019, 2019〈br〉 This paper describes a coupled benthic–pelagic biogeochemical model, ERGOM-SED. We demonstrate its use in a one-dimensional physical model, which is horizontally integrated and vertically resolved. We describe the application of the model to seven stations in the south-western Baltic Sea. The model was calibrated using pore water profiles from these stations. We compare the model results to these and to measured sediment compositions, benthopelagic fluxes and bioturbation intensities.

Description: 〈b〉MOMSO 1.0 - a near-global, coupled biogeochemical ocean-circulation model configuration with realistic eddy kinetic energy in the Southern Ocean〈/b〉〈br〉 Heiner Dietze, Ulrike Löptien, and Julia Getzlaff〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-297,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We present a new near-global coupled biogeochemical ocean-circulation model configuration. The configuration is cutting-edge in that it features both a relatively equilibrated oceanic carbon inventory and a realistic representation of mesoscale eddies. In this paper we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean Carbon uptake dynamics on decadal timescales and providing boundary conditions to ice-sheet models.

Description: 〈b〉The Eulerian urban dispersion model EPISODE. Part II: Extensions to the source dispersion and photochemistry for EPISODE-CityChem v1.2 and its application to the city of Hamburg〈/b〉〈br〉 Matthias Karl, Sam-Erik Walker, Sverre Solberg, and Martin O. P. Ramacher〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-325,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 A large part of the population living in cities is exposed to ozone levels above the EU air quality target value. The CityChem extension of the urban air quality model EPISODE enables a detailed treatment of the atmospheric chemistry in urban areas and the near-field dispersion close to industrial stacks and in street canyons. The application of the model in the city of Hamburg (Germany) shows good performance for ozone, nitrogen dioxide and particulate matter at air quality monitoring stations.

Description: 〈b〉A hydrological cycle model for the Globally Resolved Energy Balance (GREB) model v1.0〈/b〉〈br〉 Christian Stassen, Dietmar Dommenget, and Nicholas Loveday〈br〉 Geosci. Model Dev., 12, 425-440, https://doi.org/10.5194/gmd-12-425-2019, 2019〈br〉 In this research article, we describe the development of a new model for the water cycle (evaporation, precipitation and transport) for a simple climate model called GREB. Before this work, the water cycle in GREB was merely a dummy. We compare our simple model against more complex models and find a similar skill. The results illustrate that the new GREB model's water cycle is a useful tool to study the changes of the water cycle to external forcings like El Niño or climate change.

Description: 〈b〉The Lagrangian particle dispersion model FLEXPART version 10.3〈/b〉〈br〉 Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina Kristiansen, Massimo Cassiani, Sabine Eckhardt, Delia Arnold, Don Morton, Rona L. Thompson, Christine D. Groot Zwaaftink, Nikolaos Evangeliou, Harald Sodemann, Leopold Haimberger, Stephan Henne, Dominik Brunner, John F. Burkhart, Anne Fouilloux, Jerome Brioude, Anne Philipp, Petra Seibert, and Andreas Stohl〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-333,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We present the latest release of the Lagrangian transport model FLEXPART, which simulates the transport, diffusion, dry and wet deposition, radioactive decay and first order chemical reactions of atmospheric tracers. The model has been recently updated, both technical and in the representation of physico-chemical processes. We describe the changes, document the most recent input and output files, provide working examples and introduce testing capabilities.

Description: 〈b〉The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale〈/b〉〈br〉 Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Pia̧tek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-304,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This paper presents an overview of the ESCAPE project in which weather prediction models are broken down into smaller building blocks called dwarfs. These are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain specific languages. Different numerical techniques are compared in terms of energy efficiency and performance on a variety of computing technologies.

Description: 〈b〉Assessing bias corrections of oceanic surface conditions for atmospheric models〈/b〉〈br〉 Julien Beaumet, Gerhard Krinner, Michel Déqué, Rein Haarsma, and Laurent Li〈br〉 Geosci. Model Dev., 12, 321-342, https://doi.org/10.5194/gmd-12-321-2019, 2019〈br〉 Oceanic surface conditions coming from coupled ocean–atmosphere global climate models bear considerable biases over the historical climate. We review and present new methods for bias correcting sea surface temperatures and sea-ice concentration coming from such models in order to use them as boundary conditions for atmospheric-only GCMs. For sea ice, we propose a new analogue method which allows us to reproduce more physically consistent future bias-corrected sea-ice concentration maps.

Description: 〈b〉Description and evaluation of the process-based forest model 4C at four European forest sites〈/b〉〈br〉 Petra Lasch-Born, Felicitas Suckow, Christopher O. P. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, and Jörg Schaber〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2019-2,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The process-based model 4C has been developed over the past twenty years. The objective of this paper is to give a comprehensive description of the main features of 4C and to present an evaluation of the model at four different forest sites across Europe. The evaluation was focused on growth parameters, carbon, water and heat fluxes using data from the PROFOUND database. The model's performance in simulating carbon and water fluxes was very satisfactory on daily and monthly time scales.

Description: 〈b〉Climate projections of a multi-variate heat stress index: the role of downscaling and bias correction〈/b〉〈br〉 Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-294,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely use to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical postprocessing (bias correction).

Description: 〈b〉Implementation and performance of adaptive mesh refinement in the Ice Sheet System Model (ISSM v4.14)〈/b〉〈br〉 Thiago Dias dos Santos, Mathieu Morlighem, Hélène Seroussi, Philippe Remy Bernard Devloo, and Jefferson Cardia Simões〈br〉 Geosci. Model Dev., 12, 215-232, https://doi.org/10.5194/gmd-12-215-2019, 2019〈br〉 The reduction of numerical errors in ice sheet modeling increases the results' accuracy reliability. We improve numerical accuracy by better capturing grounding line dynamics, while maintaining a low computational cost. We implement an adaptive mesh refinement (AMR) technique in the Ice Sheet System Model and compare AMR simulations with uniformly refined meshes. Our results show that the computational time with AMR is significantly shorter than for uniformly refined meshes for a given accuracy.

Description: 〈b〉The AROME-WMED re-analyses of the first Special Observation Period of the Hydrological cycle in the Mediterranean experiment〈/b〉〈br〉 Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-303,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The AROME-WMED (West-Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model which ran in real-time during the first special observation period of HYMEX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX re-analyses. The second re-analysis is found to be closer to observations than the previous AROME-WMED analyses.

Description: 〈b〉ATTILA 4.0: Lagrangian Advective and Convective Transport of Passive Tracers within the ECHAM5/MESSy (2.53.0) Chemistry Climate Model〈/b〉〈br〉 Sabine Brinkop and Patrick Jöckel〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-302,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 We have extended ATTILA (Atmospheric Tracer Transport in a LAgrangian model), a Lagrangian tracer transport scheme, which is on-line coupled to the global ECHAM/MESSy Atmospheric Chemistry (EMAC) Climate model, with a combination of newly developed and modified physical routines, and new diagnostic and infrastructure submodels. The results show an improvement of the tracer transport into and within the stratosphere due to the newly implemented diabatic vertical velocity.

Description: 〈b〉Description and evaluation of NorESM1-F: a fast version of the Norwegian Earth System Model (NorESM)〈/b〉〈br〉 Chuncheng Guo, Mats Bentsen, Ingo Bethke, Mehmet Ilicak, Jerry Tjiputra, Thomas Toniazzo, Jörg Schwinger, and Odd Helge Otterå〈br〉 Geosci. Model Dev., 12, 343-362, https://doi.org/10.5194/gmd-12-343-2019, 2019〈br〉 In this paper, we describe and evaluate a new variant of the Norwegian Earth System Model (NorESM). It is a computationally efficient model that is designed for experiments such as paleoclimate, carbon cycle, and large ensemble simulations. The model, with various recent code updates, shows improved climate performance compared to the CMIP5 version of NorESM, while the model resolution remains similar.

Description: 〈b〉Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications〈/b〉〈br〉 Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala〈br〉 Geosci. Model Dev., 12, 363-386, https://doi.org/10.5194/gmd-12-363-2019, 2019〈br〉 Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.

Description: 〈b〉RTTOV-gb v1.0 – Updates on sensors, absorption models, uncertainty, and availability〈/b〉〈br〉 Domenico Cimini, James Hocking, Francesco De Angelis, Angela Cersosimo, Francesco Di Paola, Donatello Gallucci, Sabrina Gentile, Edoardo Geraldi, Salvatore Larosa, Saverio Nilo, Filomena Romano, Elisabetta Ricciardelli, Ermann Ripepi, Mariassunta Viggiano, Lorenzo Luini, Carlo Riva, Frank S. Marzano, Pauline Martinet, Yun Young Song, Myoung Hwan Ahn, and Philip W. Rosenkranz〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-285,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The fast radiative transfer model RTTOV-gb was developed to foster ground-based microwave radiometer data assimilation into numerical weather prediction models, as introduced in a companion paper (〈a href="https://doi.org/10.5194/gmd-9-2721-2016" target="_blank"〉https://doi.org/10.5194/gmd-9-2721-2016〈/a〉). Here we present the updates and new features of the current version (v1.0), which is freely accessible online.

Description: 〈b〉The DeepMIP contribution to PMIP4: methodologies for selection, compilation and analysis of latest Paleocene and early Eocene climate proxy data, incorporating version 0.1 of the DeepMIP database〈/b〉〈br〉 Christopher J. Hollis, Tom Dunkley Jones, Eleni Anagnostou, Peter K. Bijl, Margot J. Cramwinckel, Ying Cui, Gerald R. Dickens, Kirsty M. Edgar, Yvette Eley, David Evans, Gavin L. Foster, Joost Frieling, Gordon N. Inglis, Elizabeth M. Kennedy, Reinhard Kozdon, Vittoria Lauretano, Caroline H. Lear, Kate Littler, Nele Meckler, B. David A. Naafs, Heiko Pälike, Richard D. Pancost, Paul Pearson, Dana L. Royer, Ulrich Salzmann, Brian Schubert, Hannu Seebeck, Appy Sluijs, Robert Speijer, Peter Stassen, Jessica Tierney, Aradhna Tripati, Bridget Wade, Thomas Westerhold, Caitlyn Witkowski, James C. Zachos, Yi Ge Zhang, Matthew Huber, and Daniel J. Lunt〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-309,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 The Deep-Time Model Intercomparison Project (DeepMIP) is a model-data intercomparison of the early Eocene (around 55 million years ago), the last time that Earth's atmospheric CO〈sub〉2〈/sub〉 concentrations exceeded 1000 ppm. Previously, we outlined the experimental design for climate model simulations. Here, we outline the methods used for compilation and analysis of climate proxy data. The resulting climate “atlas” will be provide insights into the mechanisms that control past warm climate states.

Description: 〈b〉Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques〈/b〉〈br〉 Dan Lu and Daniel Ricciuto〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-327,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 This work uses machine learning techniques to advance the predictive understanding of large-scale Earth systems.

Description: 〈b〉Independent perturbations for physics parametrization tendencies in a convection-permitting ensemble (pSPPT)〈/b〉〈br〉 Clemens Wastl, Yong Wang, Aitor Atencia, and Christoph Wittmann〈br〉 Geosci. Model Dev., 12, 261-273, https://doi.org/10.5194/gmd-12-261-2019, 2019〈br〉 Ensemble forecasting at the convection-permitting scale (

Description: 〈b〉Toward modular in situ visualization in Earth system models: the regional modeling system RegESM 1.1〈/b〉〈br〉 Ufuk Utku Turuncoglu〈br〉 Geosci. Model Dev., 12, 233-259, https://doi.org/10.5194/gmd-12-233-2019, 2019〈br〉 This study aims to present a novel application of the recently developed state-of-the-art modeling framework to integrate in situ visualization and a data analysis approach with a model coupling framework. The modeling framework utilizes ParaView/Catalyst to gain more insight about the vast amount of data through in situ visualizations, enabling analysis of fast-moving processes and their evolution in both time and space to support better understanding of underplaying physical mechanisms.

Description: 〈b〉The Parcels v2.0 Lagrangian framework: new field interpolation schemes〈/b〉〈br〉 Philippe Delandmeter and Erik van Sebille〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-339,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Parcels is a framework to compute how ocean currents transport 〈q〉stuff〈/q〉 such as plankton and plastic around. In the latest version 2.0 of Parcels, we focus on more accurate interpolation schemes and implement methods to seamlessly combine data from different sources (such as winds and currents, possibly in different regions). We show that this framework is very efficient to track how microplastic is transported through the North Sea into the Arctic.

Description: 〈b〉The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1〈/b〉〈br〉 Sandra L. LeGrand, Chris Polashenski, Theodore W. Letcher, Glenn A. Creighton, Steven E. Peckham, and Jeffrey D. Cetola〈br〉 Geosci. Model Dev., 12, 131-166, https://doi.org/10.5194/gmd-12-131-2019, 2019〈br〉 This paper reviews the history, code, and performance of the three dust emission schemes embedded in the WRF-Chem model, including the GOCART, AFWA, and UoC dust emission schemes, and provides the first full documentation of the AFWA scheme. A simulation case study is provided to explore differences in model output. Results highlight the relative strengths of each scheme, indicate reasons for disagreement, and demonstrate the need for improved terrain characterization in dust emission models.

Description: 〈b〉Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapo-transpiration: ACM-GPP-ETv1〈/b〉〈br〉 Thomas Luke Smallman and Mathew Williams〈br〉 Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-311,2019〈br〉 〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉 Photosynthesis and evapotranspiration are processes with global significance for carbon and water cycling. Simulating these processes and their interactions has till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement with typical R〈sup〉2〈/sup〉 ~ 0.60.

Description: Geostatistical inverse modeling (GIM) has become a common approach to estimating greenhouse gas fluxes at the Earth's surface using atmospheric observations. GIMs are unique relative to other commonly-used approaches because they do not require a single emissions inventory or a bottom-up model to serve as an initial guess of the fluxes. Instead, a modeler can incorporate a wide range of environmental, economic, and/or land use data to estimate the fluxes. Traditionally, GIMs have been paired with in situ observations that number in the thousands or tens of thousands. However, the number of available atmospheric greenhouse gas observations has been increasing enormously as the number of satellites, airborne measurement campaigns, and in situ monitoring stations continues to increase. This era of prolific greenhouse gas observations presents computational and statistical challenges for inverse modeling frameworks that have traditionally been paired with a limited number of in situ monitoring sites. In this article, we discuss the challenges of estimating greenhouse gas fluxes using large atmospheric datasets with a particular focus on GIMs. We subsequently discuss several strategies for estimating the fluxes and quantifying uncertainties, strategies that are adapted from hydrology, applied math, or other academic fields and are compatible with a wide variety of atmospheric models. We further evaluate the accuracy and computational burden of each strategy using CO2 observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. Specifically, we simultaneously estimate a full year of 3-hourly CO2 fluxes across North America in one case study – a total of 9.4 × 106 unknown fluxes using 9.9 × 104 observations. The strategies discussed here provide accurate estimates of CO2 fluxes that are comparable to fluxes calculated directly or analytically. We are also able to approximate posterior uncertainties in the fluxes, but these approximation are typically an over- or underestimate depending upon the strategy employed and the degree of approximation required to make the calculations manageable.

Description: This paper describes the second major release of the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). Compared to version 1.0, released in 2016, ESMValTool version 2.0 (v2.0) features a brand new design, with an improved interface and a revised preprocessor. It also features a significantly enhanced diagnostic part that is described in three companion papers. The new version of the ESMValTool has been specifically developed to target the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex ESMs. The new version takes advantage of state-of-the-art computational libraries and methods to deploy an efficient and user-friendly data processing. Common operations on the input data (such as regridding or computation of multi-model statistics) are centralized in a highly optimized preprocessor, which allows applying a series of preprocessing functions before diagnostics scripts are applied for in-depth scientific analysis of the model output. Performance tests conducted on a set of standard diagnostics show that the new version is faster than its predecessor by about a factor of three. The performance can be further improved, up to a factor of more than 30, when the newly-introduced task-based parallelization options are used, which enable the efficient exploitation of much larger computing infrastructures. ESMValTool v2.0 also includes a revised and simplified installation procedure, setting of user configurable options based on modern language formats, and high code quality standards following the best practices for software development.

Description: Irrigation is one of the land managements that can affect the local climate. Recent literature shows that it affects mostly the near-surface variables and it is associated with an irrigation cooling effect. However, there is no common parameterization that also accounts for a realistic water amount, and these factors could be ascribed as causes of different impacts found in previous studies. This work aims to develop three new surface irrigation parameterizations within the WRF-ARW model (V3.8.1) that consider different evaporative processes. The parameterizations are tested on one of the regions where global studies disagree on the signal of irrigation: the Mediterranean area, and in particular the Po Valley. Three sets of experiments are performed using the same irrigation water amount of 5.7 mm/d, derived from Eurostat data. Two complementary validations are performed for July 2015: monthly mean, minimum and maximum temperature with ground stations and potential evapotranspiration with the MODIS product. All tests show that both mean and maximum temperature, as well as potential evapotranspiration, simulated fields approximate better the measures when using the irrigation parameterizations. This study addresses the sensitivity of the results to the parameterizations' human-decision assumptions: start time, length and frequency. The main impact of irrigation on surface variables such as soil moisture is due to the parameterization choice itself, rather than the timing. Moreover, on average, the atmosphere and soil variables are not very sensitive to the parameterizations assumptions for realistic timing and length.

Description: Accurate predictions of future sea level rise require numerical models that capture the complex thermomechanical feedbacks in rapidly deforming ice. Shear margins, grounding zones and the basal sliding interface are locations of particular interest where the stress-field is complex and fundamentally three-dimensional. These transition zones are prone to thermomechanical localisation, which can be captured numerically only with high temporal and spatial resolution. Thus, better understanding the coupled physical processes that govern these boundaries of localised strain necessitates a non-linear, full Stokes model that affords high resolution and scales well in three dimensions. This paper’s goal is to contribute to the growing toolbox for modelling thermomechanical deformation in ice by levering GPU accelerators’ parallel scalability. We propose a numerical model that relies on pseudo-transient iterations to solve the implicit thermomechanical coupling between ice motion and temperature involving shear-heating and a temperature-dependant ice viscosity. Our method is based on the finite-difference discretisation, and we implement the pseudo-time integration in a matrix-free way. We benchmark the mechanical Stokes solver against the finite-element code Elmer/Ice and report good agreement among the results. We showcase a parallel version of the solver to run on GPU-accelerated distributed memory machines, reaching a parallel efficiency of 93 %. We show that our model is particularly useful for improving our process-based understanding of flow localisation in the complex transition zones bounding rapidly moving ice.

Description: Here, we present the implementation of the freshwater carbon (C) cycle in the Dynamic In-stream Chemistry module (CARBON-DISC), which is part of the Integrated Model to Assess the Global Environment-Dynamic Global Nutrient Model (IMAGE-DGNM). A coupled hydrology-biogeochemistry approach with 0.5 by 0.5-degree resolution accounts for the spatial and temporal variability in dynamic conditions in the aquatic continuum using independent global databases. This process-based model resolves the concentrations, transformations and transfer fluxes of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC) and terrestrial and autochthonous particulate organic carbon (POC) from headwaters to river mouth with a time step of 1 month for the period 1950–2000. This is a major step forward in basin scale modelling of the C processing in freshwater systems, since simulated results can be validated at every location and point in time, and the model can be applied for retrodiction and to analyse future scenarios. Validation of the model with long-term measurement data shows a fair agreement, considering that this is a global model. To analyse the performance of the full production-respiration DISC module, two other schemes are presented, including an abiotic system excluding any in-stream processing of DOC and allochthonous production, and an extended abiotic system including heterotrophic respiration, but excluding production. Furthermore, a sensitivity analysis shows that many parameters, such as temperature, solar radiation, organic sediment mineralization rate and C inputs, including particulate organic carbon from terrestrial vegetation and dissolved inorganic carbon from groundwater, strongly affect atmosphere-freshwater exchange of CO2.

Description: The biogeochemical dynamics of Hg, and specifically of its three species Hg0, HgII, and MeHg (elemental, inorganic, and organic, respectively) in the marine coastal area of Augusta Bay (southern Italy) have been explored by the high resolution 3D Hg (HR3DHG) model, namely an advection-diffusion-reaction model for the dissolved mercury in the seawater compartment coupled with i) a diffusion-reaction model for dissolved mercury in the pore water of sediments and ii) a sorption/de-sorption model for total mercury in the sediments. The spatio-temporal variability of dissolved and total mercury concentration both in seawater ([HgD] and [HgT]) first layers of bottom sediments ([HgsedD] and [HgsedT]), and the Hg fluxes at the boundaries of the 3D model domain have been theoretically reproduced, showing an excellent agreement with the experimental data, collected in multiple field observations during six different oceanographic cruises. The mass-balance of the different Hg species in seawater has been calculated for the Augusta Harbor, improving previous estimations. The HR3DHG model includes modules that can be implemented for specific and detailed exploration of the effects of climate change on the spatio-temporal distribution of Hg in highly contaminated coastal-marine areas.

Description: The full Stokes equations are solved by a finite element method for simulation of large ice sheets and glaciers. The simulation is particularly sensitive to the discretization of the grounding line which separates the ice resting on the bedrock and the ice floating on water and is moving in time. The boundary conditions at the ice base are enforced by Nitsche's method and a subgrid treatment of the elements in the discretization close to the grounding line. Simulations with the method in two dimensions for an advancing and a retreating grounding line illustrate the performance of the method. It is implemented in the two dimensional version of the open source code Elmer/ICE.

Description: Up-to-date and accurate emission inventories for air pollutants are essential for understanding their role in the formation of tropospheric ozone and particulate matter at various temporal scales, for anticipating pollution peaks and for identifying the key drivers that could help mitigate their emissions. This paper describes the Bayesian variational inverse system PYVAR-CHIMERE, which is adapted to the inversion of reactive species. Complementarily with bottom-up inventories, this system aims at updating and improving the knowledge on the high spatio-temporal variability of emissions of air pollutants and their precursors. The system is designed to use any type of observations, such as satellite observations or surface stations. The potential of PYVAR-CHIMERE is illustrated with one-day inversions of CO and NO2 emissions in Europe, using the MOPITT and OMI satellite observations (for CO and for NO2, respectively).

Description: Over the last years, we have seen growing concerns on the need to publish computer code as an integral part of the research process. This has been reflected on improved publishing policies by scientific journals, addressing the relevant issues such as repositories or licensing. Here we explore the state-of-the-art of code availability and sharing for climate models, using as testbed the models from the Climate Model Intercomparison Project 5 and make some reflections on it. Our results show that there are great limitations in the access to the code of these climate models and that the climate modelling community needs to greatly improve their code sharing practices in order to comply with the best scientific practices and the most up to date editorial publishing policies.

Description: A new cloud microphysical scheme including a detailed parameterization for aerosol-driven ice formation in cirrus clouds is implemented in the global chemistry climate model EMAC and coupled to the aerosol submodel MADE3. The new scheme is able to consistently simulate three regimes of stratiform clouds (liquid, mixed- and ice-phase (cirrus) clouds), considering the impact of aerosol on the activation of cloud droplets and the nucleation of ice crystals. In the cirrus regime, it accounts for the competition between homogeneous and heterogeneous freezing for the available supersaturated water vapor, taking into account different types of ice-nucleating particles, whose specific ice-nucleating properties can be flexibly varied in the model setup. The new model configuration was tuned using satellite data to find the optimal set of parameters that reproduces the observations. A detailed evaluation is also performed comparing the model results for standard cloud and radiation variables with a comprehensive set of observations from satellite retrievals and in situ measurements. The performance of EMAC-MADE3 in this new coupled configuration is in line with similar global coupled models and with other global aerosol models featuring ice cloud parameterizations. Some remaining discrepancies, especially with regard to ice crystal number concentrations in cirrus, which are a common problem of this kind of models, need to be the subject of future investigations. To further demonstrate the readiness of the new model system for application studies, an estimate of the global anthropogenic aerosol radiative forcing is provided and discussed in the context of the CMIP5 results for the IPCC.

Description: The increasing demand for high-resolution climate information has attracted a growing attention for statistical downscaling methods (SD), due in part to their relative advantages and merits as compared to dynamical approaches (based on regional climate model simulations), such as their much lower computational cost and their fitness-for-purpose for many local-scale applications. As a result, a plethora of SD methods is nowadays available for climate scientists, which has motivated recent efforts for their comprehensive evaluation, like the VALUE Project (http://www.value-cost.eu). The systematic intercomparison of a large number of SD techniques undertaken in VALUE, many of them independently developed by different authors and modeling centers in a variety of languages/environments, has shown a compelling need for new tools allowing for their application within an integrated framework. With this regard, downscaleR is an R package for statistical downscaling of climate information which covers the most popular approaches (Model Output Statistics – including the so called 'bias correction' methods – and Perfect Prognosis) and state-of-the-art techniques. It has been conceived to work primarily with daily data and can be used in the framework of both seasonal forecasting and climate change studies. Its full integration within the climate4R framework (Iturbide et al. 2019) makes possible the development of end-to-end downscaling applications, from data retrieval to model building, validation and prediction, bringing to climate scientists and practitioners a unique comprehensive framework for SD model development. In this article the main features of downscaleR are showcased through the replication of some of the results obtained in the VALUE Project, making an emphasis in the most technically complex stages of perfect-prog model calibration (predictor screening, cross-validation and model selection) that are accomplished through simple commands allowing for extremely flexible model tuning, tailored to the needs of users requiring an easy interface for different levels of experimental complexity. As part of the open-source climate4R framework, downscaleR is freely available and the necessary data and R scripts to fully replicate the experiments included in this paper are also provided as a companion notebook.

Description: Atmospheric inversions are commonly used for estimating large-scale (continental to regional) net sources and sinks of CO2 and other stable atmospheric tracers from their observed concentrations. Recently, there has been an increasing demand from stakeholders for robust estimates of greenhouse gases at country-scale (or higher) resolution, in particular in the framework of the Paris agreement. This increase in resolution is in theory enabled by the growing availability of observations from surface in-situ networks (such as ICOS in Europe) and from remote sensing products (OCO-2, GOSAT-2). The increase in the resolution of inversions is also a necessary step to provide efficient feedback to the process-based (bottom-up) modelling community (vegetation models, fossil fuel emission inventories). This, however, calls for new developments in the inverse modelling systems, mainly in terms of diversification of the inversion approaches, shift from global to regional inversions, and improvement in the computational efficiency, We have developed the Lund University Modular Inversion Algorithm (LUMIA) as a tool to address some of these new developments. LUMIA is meant to be a platform for inverse modelling developments at Lund University. It aims at being a flexible, yet simple and easy to maintain set of tools that modellers can combine to build inverse modelling experiments. It is in particular designed to be transport model agnostic, which should facilitate isolating the transport model errors from those introduced by the inversion setup itself. Here, we briefly describe the motivations for developing LUMIA as well as the underlying development principles, current status and future prospects. We present a first LUMIA inversion setup for a regional CO2 inversions over Europe, based on a new coupling between the Lagrangian FLEXPART (high resolution foreground transport) and the global coarse resolution TM5 transport models, using in-situ data from surface and tall tower observation sites.

Description: Coasts are among the most intensely used environments on the planet, but they also present dynamic and unique hazards including flooding and erosion. Sea level rise and changing wave climates will alter patterns of erosion and deposition, but some existing coastline evolution models are unable to simulate these effects due to their one-dimensional representation of the systems, or of sediment transport processes. In this paper, the development and application of the Coastline Evolution Model 2D (CEM2D) is presented, that incorporates these influences. The model has been developed from the established CEM model and is capable of simulating fundamental cause-effect relationships in coastal systems. The two-dimensional storage and transport of sediment in CEM2D, which is only done in one-dimension in CEM, means it is also capable of exploring the influence of a variable water level on sediment transport and the formation and evolution of morphological features and landforms at the meso-scale, from 10 to 100 years and over 10 to 100 kilometres. The model sits between one-dimensional and three-dimensional models, with the advantage of increased complexity and detail in model outputs compared to the former, but with more efficiency and less computational expense than the latter.

Description: We revisit Cloud Vertical Structure (CVS) classes we have previously employed to classify the planet’s cloudiness. The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an Atmospheric Global Climate Model (AGCM), specifically NASA’s GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Determination of CVS and associated radiation in the model is possible thanks to the implementation of a subcolumn cloud generator which is paired with the model’s radiative transfer algorithm. We assess GEOS-5 cloudiness in terms of the statistics and geographical distributions of the CVS classes, as well as features of their associated Cloud Radiative Effect (CRE). We decompose the model’s CVS-specific CRE errors into component errors stemming from biases in the frequency of occurrence of the CVSs, and biases in their internal radiative characteristics. Our framework sheds additional light into the verisimilitude of cloudiness in large scale models and can be used to complement cloud evaluations that take advantage of satellite simulator implementations.

Description: Increasing urbanization is likely to intensify the urban heat island effect, decrease outdoor thermal comfort and enhance runoff generation in cities. Urban green spaces are often proposed as a mitigation strategy to counteract these adverse effects and many recent developments of urban climate models focus on the inclusion of green and blue infrastructure to inform urban planning. However, many models still lack the ability to account for different plant types and oversimplify the interactions between the built environment, vegetation, and hydrology. In this study, we present an urban ecohydrological model, Urban Tethys-Chloris (UT&C), that combines principles of ecosystem modelling with an urban canopy scheme accounting for the biophysical and ecophysiological characteristics of roof vegetation, ground vegetation and urban trees. UT&C is a fully coupled energy and water balance model that calculates 2 m air temperature, 2 m humidity, and surface temperatures based on the infinite urban canyon approach. It further calculates all urban hydrological fluxes, including transpiration as a function of plant photosynthesis. Hence, UT&C accounts for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements of eddy covariance towers located in three cities in different climates (Singapore, Melbourne, Phoenix). A sensitivity analysis, performed as a proof of concept for the city of Singapore, shows a mean decrease in 2 m air temperature of 1.1 °C for fully grass covered ground, 0.2 °C for high values of leaf area index (LAI), and 0.3 °C for high values of Vc,max (an expression of photosynthetic activity). These reductions in temperature were combined with a simultaneous increase in relative humidity by 6.5 %, 2.1 %, and 1.6 %, for fully grass covered ground, high values of LAI, and high values of Vc,max, respectively. Furthermore, the increase of pervious vegetated ground is able to significantly reduce surface runoff. These results show that urban greening can lead to a decrease in urban air temperature and surface runoff, but this effect is limited in cities characterized by a hot, humid climate.

Description: Surface and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs is dynamically evolving with improvement in technology and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves Richards’ equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite difference scheme and a conservative finite volume method for subsurface flow and transport, respectively. ParFlow uses multigrid preconditioned Krylov and Newton-Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g. Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and the atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.

Description: Upcoming telescopes such as the James Webb Space Telescope (JWST), the European Extremely Large Telescope (E-ELT), the Thirty Meter Telescope (TMT) or the Giant Magellan Telescope (GMT) may soon be able to characterize, through transmission spectroscopy, the atmospheres of rocky exoplanets orbiting nearby M dwarfs. One of the most promising candidates is the late M dwarf system TRAPPIST-1 which has seven known transiting planets for which Transit Timing Variation (TTV) measurements suggest that they are terrestrial in nature, with a possible enrichment in volatiles. Among these seven planets, TRAPPIST-1e seems to be the most promising candidate to have habitable surface conditions, receiving ~ 66 % of the Earth's incident radiation, and thus needing only modest greenhouse gas inventories to raise surface temperatures to allow surface liquid water to exist. TRAPPIST-1e is therefore one of the prime targets for JWST atmospheric characterization. In this context, the modeling of its potential atmosphere is an essential step prior to observation. Global Climate Models (GCMs) offer the most detailed way to simulate planetary atmospheres. However, intrinsic differences exist between GCMs which can lead to different climate prediction and thus observability of gas and/or cloud features in transmission and thermal emission spectra. Such differences should preferably be known prior to observations. In this paper we present a protocol to inter-compare planetary GCMs. Four testing cases are considered for TRAPPIST-1e but the methodology is applicable to other rocky exoplanets in the Habitable Zone. The four test cases included two land planets composed of pure N2 and pure CO2, respectively, and two aqua planets with a modern Earth and a CO2 rich composition. Currently there are 4 participating models (LMDG, ROCKE3D, ExoCAM, UM), however this protocol is intended to let other teams participate as well.

Description: The Bosphorus exchange is of critical importance for hydrodynamics of the Black Sea. In this study, we report on the development of a medium resolution circulation model of the Black Sea, making use of up-to-date topography, atmospheric forcing with high space and time resolution, climatic river fluxes and strait exchange enabled by adding the Bosphorus Strait with an artificial box on the Marmara Sea side. Particular attention is given to circulation, mixing, convective water mass formation processes compared with observations. The present formulation with temperature and salinity relaxed to the observed seasonal climatology of the Marmara box and open boundary conditions are found to enable Bosphorus exchange with upper, lower layer and net fluxes comparable to the observed range. This in turn enables to capture the trend of rapid climatic change observed in the Black Sea in the last decade.

Description: A new module has been implemented in the ECHAM5/MESSy Atmospheric Chemistry (EMAC) Model that simulates cloud related processes on a much smaller grid. This so called superparametrisation acts as a replacement for the convection parametrisation and large-scale cloud scheme. The concept of embedding an ensemble of cloud resolving models (CRMs) inside of each grid box of a general circulation model leads to an explicit representation of cloud dynamics. The new model component is evaluated against observations and the conventional usage of EMAC using a convection parametrisation. In particular, effects of applying different configurations of the superparametrisation are analyzed in a systematical way. Consequences of changing the CRMs orientation, cell size and number of cells range from regional differences in cloud amount up to global impacts on precipitation distribution and its variability. For some edge case setups the analysed climate state of superparametrised simulations even deteriorates from the mean observed energy budget. In the current model configuration different climate regimes can be formed that are mainly driven by some of the parameters of the CRM. Presently, the simulated cloud cover is at the lower edge of the CMIP5 model ensemble indicating that the hydrological overturning is too efficient. However, certain "tuning" of the current model configuration could improve the currently underestimated cloud cover, which will result in a shift of the climate. The simulation results show that especially tropical precipitation is better represented with the superparamerisation in the EMAC model configuration. Furthermore, the diurnal cycle of precipitation is heavily affected by the choice of the CRM parameters. However, despite an improvement of the representation of the continental diurnal cycle in some configurations, other parameter choices result in a deterioration compared to the reference simulation using a conventional convection parameterisation. The ability of the superparametrisation to represent latent and sensible heat flux climatology is dependent on the chosen CRM setup. Further interactions of the planetary boundary layer and the free troposphere can significantly influence cloud development on the large-scale. Therefore a careful selection of the CRM setup is recommended to compensate for computational expenses.

Description: Simulating ensembles of extreme events is a necessary task to evaluate their probability distribution and analyse their meteorological properties. Algorithms of importance sampling have provided a way to simulate trajectories of dynamical systems (like climate models) that yield extreme behavior, like heatwaves. Such algorithms also give access to the return periods of such events. We present an adaptation based on circulation analogues of importance sampling to provide a data-based algorithm that simulates extreme events like heatwaves in a realistic way. This algorithm is a modification of a stochastic weather generator, which gives more weight to trajectories with higher temperatures. This presentation outlines the methodology on European heatwaves and illustrates the spatial and temporal properties of simulations.

Description: The square conservation theory is widely used on latitude–longitude grids, but it is rarely implemented on quasi-uniform grids, given the difficulty involved in constructing anti-symmetrical spatial discrete operators on these grids. Increasingly more models are developed on quasi-uniform grids, such as arbitrarily structured C-grids. Thuburn–Ringler–Skamarock–Klemp (TRiSK) is a shallow water dynamic core on an arbitrarily structured C-grid. The spatial discrete operator of TRiSK is able to naturally maintain the conservation properties of total mass, total absolute vorticity and instantaneous total energy. The first 2 integral invariants are entirely conserved during integration, but the total energy dissipates when using the dissipative temporal integration schemes, i.e., Runge-Kutta. The method of strictly conserving the total energy simultaneously uses both an anti-symmetrical spatial discrete operator and square conservative temporal integration scheme. In this study, we demonstrate that square conservation is equivalent to energy conservation in both a continuous shallow water system and a discrete shallow water system of TRiSK, attempting to extend the square conservation theory to the TRiSK framework. To overcome the challenge of constructing an anti-symmetrical spatial discrete operator, we unify the unit of evolution variables of shallow water equations by Institute of Atmospheric Physics (IAP) transformation, expressing the temporal trend of the evolution variable by using the original operators of TRiSK. Using the square conservative Runge-Kutta scheme, the total energy is completely conserved, and there is no influence on the properties of conserving total mass and total absolute vorticity. In the standard shallow water numerical test, the square conservative scheme not only helps maintain total conservation of the three integral invariants but also creates less simulation error norms.

Description: This paper describes a new satellite simulator for the Satellite Application Facility on Climate Monitoring (CM SAF) cLoud, Albedo and RAdiation dataset (CLARA), Advanced Very High Resolution Radiometer (AVHRR)-based, version 2 (CLARA-A2) Climate Data Record (CDR). This simulator takes into account the variable skill in cloud detection in the CLARA-A2 CDR by using a different approach to other similar satellite simulators to emulate the ability to detect clouds. In particular, the paper describes three methods to filter out clouds from climate models undetectable by observations. The first method, compared to the simulators in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), relies on one global visible cloud optical depth at 550nm (τc) threshold to delineate cloudy and cloud-free conditions. Method two and three apply long/lat -gridded values separated by day and nighttime conditions. Method two uses gridded varying τc as opposed to method one that uses just a single τc threshold, and method three uses a cloud Probability of Detection (POD) depending on the model τc. Method two and three replicate the relative ease or difficulty for cloud retrievals depending on the region and illumination by increasing the cloud sensitivity where the cloud retrievals are relatively straightforward, such as over mid-latitude oceans, and by decreasing the sensitivity where cloud retrievals are notoriously tricky, such as over the Arctic region during the polar night. Method three has the added advantage that it indirectly takes into account that cloud retrievals in some areas are more likely than others to miss some clouds. This situation is common in cold regions where even thick clouds may be inseparable from cold, snow-covered surfaces and also in areas with an abundance of broken and small scale cumulus clouds such as the atmospheric subsidence regions over the ocean. The simulator, together with the International Satellite Cloud Climatology Project (ISCCP) simulator of COSP, is used to assess Arctic clouds in the EC-Earth climate model compared to the CLARA-A2 and ISCCP-H CDRs. Compared to CLARA-A2, EC-Earth is shown to underestimate cloudiness in the Arctic generally. However, compared to ISCCP and its simulator, the opposite conclusion is reached. Previous studies have found that the CLARA-A2 CDR performs well in the Arctic during the summer months, and this paper shows that the simulated cloud mask of CLARA-A2 using method three is more representative of the CDR than method one used in COSP, using a global τc threshold to simulate clouds. Therefore, the conclusion that EC-Earth underpredicts clouds in the Arctic is the more likely one. The simulator substantially improves the simulation of the CLARA-A2 detected clouds, especially in the polar regions, by accounting for the variable cloud detection skill over the year. The approach to cloud simulation based on the POD of clouds depending on their cloud optical depth, location, and illumination is the preferred one as it reduces cloudiness over a range of cloud optical depths. Climate model comparisons with satellite-derived information can be significantly improved by this approach, mainly by reducing the risk of misinterpreting problems with satellite retrievals as cloudiness features.

Description: BCC-ESM1 is the first version of a fully-coupled Earth System Model with interactive atmospheric chemistry and aerosols developed by Beijing Climate Center, China Meteorological Administration. Major aerosol species (including sulfate, organic carbon, black carbon, dust and sea salt) and greenhouse gases are interactively simulated with a whole panoply of processes controlling emission, transport, gas-phase chemical reactions, secondary aerosol formation, gravitational settling, dry deposition, and wet scavenging by clouds and precipitation. Effects of aerosols on radiation, cloud, and precipitation are fully treated. The performance of BCC-ESM1 in simulating aerosols and their optical properties is comprehensively evaluated as required by the Aerosol Chemistry Model Intercomparison Project (AerChemMIP), covering the preindustrial mean state and time evolution from 1850 to 2014. The simulated aerosols from BCC-ESM1 are quite coherent with CMIP5-recommended data and in-situ measurements from surface networks (such as IMPROVE in the U.S. and EMEP in Europe). A comparison of the aerosol optical depth (AOD) at 550 nm for all aerosols with the satellite AOD observations retrieved from MODIS and MISR and surface AOD observations from AERONET shows reasonable agreement between simulated and observed AOD. However, BCC-ESM1 seems to show weaker upward transport of aerosols from the surface to the middle and upper troposphere, likely reflecting the deficiency of representing deep convective transport of chemical species in BCC-ESM1. With an overall good agreement between BCC-ESM1 simulated and observed aerosol properties, it demonstrates a success of the implementation of interactive aerosol chemistry in BCC-ESM1.

Description: We present a new capability of the ice sheet model SICOPOLIS that enables flexible adjoint code generation via source transformation using the open-source algorithmic differentiation (AD) tool OpenAD. The adjoint code enables efficient calculation of sensitivities of a scalar-valued objective function or quantity of interest (QoI) to a range of important, often spatially varying model input variables, including initial and boundary conditions, as well as model parameters. Compared to earlier work on adjoint code generation of SICOPOLIS, our work is based on several important advances: (i) it is embedded within the up-to-date trunk of the SICOPOLIS repository – accounting for one and a half decades of code development and improvements – and is readily available to the wider community; (ii) the AD tool used, OpenAD, is an open-source tool; (iii) the adjoint code developed is applicable to both Greenland and Antarctica, including grounded ice as well as floating ice shelves, and with an extended choice of thermodynamical representations. A number of code refactorization steps were required. They are discussed in detail in an Appendix as they hold lessons for application of AD to legacy codes at large. As an example application, we examine the sensitivity of the total Antarctic Ice Sheet volume to changes in initial ice thickness, summer precipitation, and basal and surface temperatures across the ice sheet. Simulations of Antarctica with floating ice shelves show that over 100 years of simulation the sensitivity of total ice sheet volume to the initial ice thickness and precipitation is almost uniformly positive, while the sensitivities to surface and basal temperature are almost uniformly negative. Sensitivity to summer precipitation is largest on floating ice shelves from Queen Maud to Queen Mary Land. The largest sensitivity to initial ice thickness is at outlet glaciers around Antarctica. Comparison between total ice sheet volume sensitivities to surface and basal temperature shows that surface temperature sensitivities are higher broadly across the floating ice shelves, while basal temperature sensitivities are highest at the grounding lines of floating ice shelves and outlet glaciers. A uniformly perturbed region of East Antarctica reveals that, among the four control variables tested here, total ice sheet volume is most sensitive to variations in summer precipitation as formulated in SICOPOLIS. Comparison between adjoint- and finite-difference-derived sensitivities shows good agreement, lending confidence that the AD tool is producing correct adjoint code. The new modeling infrastructure is freely available at www.sicopolis.net under the development trunk.

Description: Air pollution is a serious and urgent problem in China, and it has a great impact on the lives of residents and urban development. The particulate matter (PM) value is usually used to indicate the degree of air pollution. In addition to PM2.5 and PM10, the use of the PM2.5 / PM10 ratio as an indicator and assessor of air pollution has also become more widespread. This ratio reflects the air pollution conditions and pollution sources. In this paper, a better composite prediction system was proposed that aimed at improving the accuracy and spatio-temporal applicability of PM2.5 / PM10. First, the aerosol optical depth (AOD) in 2017 in Wuhan was obtained based on Moderate Resolution Imaging Spectroradiometer images, with a 1 km spatial resolution, by using the Dense Dark Vegetation method. Second, the AOD was corrected by calculating the planetary boundary layer height and relative humidity. Third, the coefficient of determination of the optimal subset selection was used to select the factor with the highest correlation with PM2.5 / PM10 from meteorological factors and gaseous pollutants. Then, PM2.5 / PM10 predictions based on time, space, and random patterns were obtained by using 9 factors (the corrected AOD, meteorological data and gaseous pollutant data) with the long short-term memory (LSTM) neural network method, which is a dynamic model that remembers historical information and applies it to the current output. Finally, the LSTM model prediction results were compared and analysed with the results of other intelligent models. The results showed that the LSTM model had significant advantages in the average, maximum and minimum accuracies and the stability of PM2.5 / PM10 prediction.