Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-1991-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-1991-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
07 Jul 2015
Model description paper |
| 07 Jul 2015
System for Automated Geoscientific Analyses (SAGA) v. 2.1.4
O. Conrad
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
B. Bechtel
CORRESPONDING AUTHOR
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
M. Bock
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
scilands GmbH, Goetheallee 11, 37073 Göttingen, Germany
H. Dietrich
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
E. Fischer
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
L. Gerlitz
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
J. Wehberg
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
V. Wichmann
LASERDATA GmbH, Technikerstr. 21a, 6020 Innsbruck, Austria
alpS – Center for Climate Change Adaptation, Grabenweg 68, 6020 Innsbruck, Austria
J. Böhner
Institute of Geography, University of Hamburg, Bundesstr. 55, 20146 Hamburg, Germany
Related authors
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-367, https://doi.org/10.5194/essd-2022-367, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
We present the first 1km, daily, global climate dataset for climate impact studies. We show that the high resolution data has a decreased bias, and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Michael Bock, Olaf Conrad, Andreas Günther, Ernst Gehrt, Rainer Baritz, and Jürgen Böhner
Geosci. Model Dev., 11, 1641–1652, https://doi.org/10.5194/gmd-11-1641-2018, https://doi.org/10.5194/gmd-11-1641-2018, 2018
Short summary
Short summary
We introduce the Soil and
Landscape Evolution Model (SaLEM) for the prediction of soil parent material evolution following a lithologically differentiated approach. The GIS tool is working within the software framework SAGA GIS. Weathering, erosion and transport functions are calibrated using extrinsic and intrinsic parameter data. First results indicate that our approach shows evidence for the spatiotemporal prediction of soil parental material properties.
Peter Hoffmann, Vanessa Reinhart, Diana Rechid, Nathalie de Noblet-Ducoudré, Edouard L. Davin, Christina Asmus, Benjamin Bechtel, Jürgen Böhner, Eleni Katragkou, and Sebastiaan Luyssaert
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-431, https://doi.org/10.5194/essd-2022-431, 2022
Revised manuscript under review for ESSD
Short summary
Short summary
This paper introduces the new high-resolution land-use land-cover change dataset LUCAS LUC historical and future land use and land cover change dataset for Europe (Version 1.1), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-367, https://doi.org/10.5194/essd-2022-367, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
We present the first 1km, daily, global climate dataset for climate impact studies. We show that the high resolution data has a decreased bias, and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 3835–3873, https://doi.org/10.5194/essd-14-3835-2022, https://doi.org/10.5194/essd-14-3835-2022, 2022
Short summary
Short summary
Because urban areas are key contributors to climate change but are also susceptible to multiple hazards, one needs spatially detailed information on urban landscapes to support environmental services. This global local climate zone map describes this much-needed intra-urban heterogeneity across the whole surface of the earth in a universal language and can serve as a basic infrastructure to study e.g. environmental hazards, energy demand, and climate adaptation and mitigation solutions.
Vanessa Reinhart, Peter Hoffmann, Diana Rechid, Jürgen Böhner, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 1735–1794, https://doi.org/10.5194/essd-14-1735-2022, https://doi.org/10.5194/essd-14-1735-2022, 2022
Short summary
Short summary
The LANDMATE plant functional type (PFT) land cover dataset for Europe 2015 (Version 1.0) is a gridded, high-resolution dataset for use in regional climate models. LANDMATE PFT is prepared using the expertise of regional climate modellers all over Europe and is easily adjustable to fit into different climate model families. We provide comprehensive spatial quality information for LANDMATE PFT, which can be used to reduce uncertainty in regional climate model simulations.
Peter Hoffmann, Vanessa Reinhart, Diana Rechid, Nathalie de Noblet-Ducoudré, Edouard L. Davin, Christina Asmus, Benjamin Bechtel, Jürgen Böhner, Eleni Katragkou, and Sebastiaan Luyssaert
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-252, https://doi.org/10.5194/essd-2021-252, 2021
Manuscript not accepted for further review
Short summary
Short summary
This paper introduces the new high-resolution land-use land-cover change dataset LUCAS LUC historical and future land use and land cover change dataset (Version 1.0), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
M. Bremer, V. Wichmann, M. Rutzinger, T. Zieher, and J. Pfeiffer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 943–950, https://doi.org/10.5194/isprs-archives-XLII-2-W13-943-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-943-2019, 2019
J. Pfeiffer, T. Zieher, M. Rutzinger, M. Bremer, and V. Wichmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 421–428, https://doi.org/10.5194/isprs-annals-IV-2-W5-421-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-421-2019, 2019
T. Zieher, M. Bremer, M. Rutzinger, J. Pfeiffer, P. Fritzmann, and V. Wichmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 461–467, https://doi.org/10.5194/isprs-annals-IV-2-W5-461-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-461-2019, 2019
Eva Steirou, Lars Gerlitz, Heiko Apel, Xun Sun, and Bruno Merz
Hydrol. Earth Syst. Sci., 23, 1305–1322, https://doi.org/10.5194/hess-23-1305-2019, https://doi.org/10.5194/hess-23-1305-2019, 2019
Short summary
Short summary
We investigate whether flood probabilities in Europe vary for different large-scale atmospheric circulation conditions. Maximum seasonal river flows from 600 gauges in Europe and five synchronous atmospheric circulation indices are analyzed. We find that a high percentage of stations is influenced by at least one of the climate indices, especially during winter. These results can be useful for preparedness and damage planning by (re-)insurance companies.
Michael Bock, Olaf Conrad, Andreas Günther, Ernst Gehrt, Rainer Baritz, and Jürgen Böhner
Geosci. Model Dev., 11, 1641–1652, https://doi.org/10.5194/gmd-11-1641-2018, https://doi.org/10.5194/gmd-11-1641-2018, 2018
Short summary
Short summary
We introduce the Soil and
Landscape Evolution Model (SaLEM) for the prediction of soil parent material evolution following a lithologically differentiated approach. The GIS tool is working within the software framework SAGA GIS. Weathering, erosion and transport functions are calibrated using extrinsic and intrinsic parameter data. First results indicate that our approach shows evidence for the spatiotemporal prediction of soil parental material properties.
Heiko Apel, Zharkinay Abdykerimova, Marina Agalhanova, Azamat Baimaganbetov, Nadejda Gavrilenko, Lars Gerlitz, Olga Kalashnikova, Katy Unger-Shayesteh, Sergiy Vorogushyn, and Abror Gafurov
Hydrol. Earth Syst. Sci., 22, 2225–2254, https://doi.org/10.5194/hess-22-2225-2018, https://doi.org/10.5194/hess-22-2225-2018, 2018
Short summary
Short summary
Central Asia crucially depends on water resources supplied by snow melt in the mountains during summer. To support water resources management we propose a generic tool for statistical forecasts of seasonal discharge based on multiple linear regressions. The predictors are observed precipitation and temperature, snow coverage, and discharge. The automatically derived models for 13 different catchments provided very skilful forecasts in April, and acceptable forecasts in January.
Volker Wichmann
Geosci. Model Dev., 10, 3309–3327, https://doi.org/10.5194/gmd-10-3309-2017, https://doi.org/10.5194/gmd-10-3309-2017, 2017
Short summary
Short summary
The GPP model can be used to simulate the process path and run-out area of gravitational processes based on a digital terrain model. By providing several modelling approaches, the tool can be configured for different processes such as rockfall, debris flows or snow avalanches. The tool can be applied to regional-scale studies such as natural hazard susceptibility mapping. It is implemented as tool for SAGA GIS and has been released as open source.
Ramchandra Karki, Shabeh ul Hasson, Lars Gerlitz, Udo Schickhoff, Thomas Scholten, and Jürgen Böhner
Earth Syst. Dynam., 8, 507–528, https://doi.org/10.5194/esd-8-507-2017, https://doi.org/10.5194/esd-8-507-2017, 2017
Short summary
Short summary
Dynamical downscaling of climate fields at very high resolutions (convection- and topography-resolving scales) over the complex Himalayan terrain of the Nepalese Himalayas shows promising results. It clearly demonstrates the potential of mesoscale models to accurately simulate present and future climate information at very high resolutions over remote, data-scarce mountainous regions for the development of adaptation strategies and impact assessments in the context of changing climate.
Shabeh Hasson, Jürgen Böhner, and Valerio Lucarini
Earth Syst. Dynam., 8, 337–355, https://doi.org/10.5194/esd-8-337-2017, https://doi.org/10.5194/esd-8-337-2017, 2017
Short summary
Short summary
A first comprehensive and systematic hydroclimatic trend analysis for the upper Indus Basin suggests warming and drying of spring and rising early melt-season discharge over 1995–2012 period. In contrast, cooling and falling or weakly rising discharge is found within summer monsoon period that coincides well with main glacier melt season. Such seasonally distinct changes, indicating dominance of snow but suppression of glacial melt regime, address hydroclimatic explanation of
Karakoram Anomaly.
Lars Gerlitz, Sergiy Vorogushyn, Heiko Apel, Abror Gafurov, Katy Unger-Shayesteh, and Bruno Merz
Hydrol. Earth Syst. Sci., 20, 4605–4623, https://doi.org/10.5194/hess-20-4605-2016, https://doi.org/10.5194/hess-20-4605-2016, 2016
Short summary
Short summary
Most statistically based seasonal precipitation forecast models utilize a small set of well-known climate indices as potential predictor variables. However, for many target regions, these indices do not lead to sufficient results and customized predictors are required for an accurate prediction.
This study presents a statistically based routine, which automatically identifies suitable predictors from globally gridded SST and climate variables by means of an extensive data mining procedure.
B. Bechtel, M. Pesaresi, L. See, G. Mills, J. Ching, P. J. Alexander, J. J. Feddema, A. J. Florczyk, and I. Stewart
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1371–1378, https://doi.org/10.5194/isprs-archives-XLI-B8-1371-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-1371-2016, 2016
B. Bechtel
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 243–250, https://doi.org/10.5194/isprs-archives-XLI-B8-243-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-243-2016, 2016
M. Klinge, J. Böhner, and S. Erasmi
Biogeosciences, 12, 2893–2905, https://doi.org/10.5194/bg-12-2893-2015, https://doi.org/10.5194/bg-12-2893-2015, 2015
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
Short summary
Short summary
Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
L. Gerlitz, O. Conrad, and J. Böhner
Earth Syst. Dynam., 6, 61–81, https://doi.org/10.5194/esd-6-61-2015, https://doi.org/10.5194/esd-6-61-2015, 2015
Short summary
Short summary
In order to assess high-resolution precipitation fields for the Tibetan Plateau and the Himalayan Arc, a novel downscaling approach is presented which integrates traditional statistical downscaling and GIS-based terrain parameterization techniques. The approach enables a detailed analysis of the precipitation heterogeinity over the complex target area.
S. Hasson, V. Lucarini, S. Pascale, and J. Böhner
Earth Syst. Dynam., 5, 67–87, https://doi.org/10.5194/esd-5-67-2014, https://doi.org/10.5194/esd-5-67-2014, 2014
Y. Wang, U. Herzschuh, L. S. Shumilovskikh, S. Mischke, H. J. B. Birks, J. Wischnewski, J. Böhner, F. Schlütz, F. Lehmkuhl, B. Diekmann, B. Wünnemann, and C. Zhang
Clim. Past, 10, 21–39, https://doi.org/10.5194/cp-10-21-2014, https://doi.org/10.5194/cp-10-21-2014, 2014
Related subject area
Climate and Earth system modeling
Differentiable programming for Earth system modeling
Evaluation of CMIP6 model performances in simulating fire weather spatiotemporal variability on global and regional scales
Data-driven aeolian dust emission scheme for climate modelling evaluated with EMAC 2.55.2
Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning
An improved method of the Globally Resolved Energy Balance model by the Bayesian networks
Assessing predicted cirrus ice properties between two deterministic ice formation parameterizations
Various ways of using empirical orthogonal functions for climate model evaluation
C-Coupler3.0: an integrated coupler infrastructure for Earth system modelling
FEOTS v0.0.0: a new offline code for the fast equilibration of tracers in the ocean
Pace v0.2: a Python-based performance-portable atmospheric model
Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water
The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework
Structural k-means (S k-means) and clustering uncertainty evaluation framework (CUEF) for mining climate data
The emergence of the Gulf Stream and interior western boundary as key regions to constrain the future North Atlantic carbon uptake
Evaluating wind profiles in a numerical weather prediction model with Doppler lidar
Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin
The impact of lateral boundary forcing in the CORDEX-Africa ensemble over southern Africa
Effects of complex terrain on the shortwave radiative balance: a sub-grid-scale parameterization for the GFDL Earth System Model version 4.1
Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project
Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1
Nudging allows direct evaluation of coupled climate models with in situ observations: a case study from the MOSAiC expedition
Importance of ice nucleation and precipitation on climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)
UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model
A New Simplified Parameterization of Secondary Organic Aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Porting the WAVEWATCH III (v6.07) wave action source terms to GPU
Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions
The Mixed Layer Depth in the Ocean Model Intercomparison Project (OMIP): Impact of Resolving Mesoscale Eddies
Analysis of systematic biases in tropospheric hydrostatic delay models and construction of a correction model
A new precipitation emulator (PREMU v1.0) for lower-complexity models
Simulating marine neodymium isotope distributions using Nd v1.0 coupled to the ocean component of the FAMOUS–MOSES1 climate model: sensitivities to reversible scavenging efficiency and benthic source distributions
CMIP6 simulations with the compact Earth system model OSCAR v3.1
Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1
The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses
AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales
Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) – refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN – Part 1: Adaptive grid refinement in an idealized double-gyre case
Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean
Developing Spring Wheat in the Noah-MP LSM (v4.4) for Growing Season Dynamics and Responses to Temperature Stress
stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1
Evaluation of native Earth system model output with ESMValTool v2.6.0
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
LandInG 1.0: A toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
Geosci. Model Dev., 16, 3123–3135, https://doi.org/10.5194/gmd-16-3123-2023, https://doi.org/10.5194/gmd-16-3123-2023, 2023
Short summary
Short summary
Differential programming is a technique that enables the automatic computation of derivatives of the output of models with respect to model parameters. Applying these techniques to Earth system modeling leverages the increasing availability of high-quality data to improve the models themselves. This can be done by either using calibration techniques that use gradient-based optimization or incorporating machine learning methods that can learn previously unresolved influences directly from data.
Carolina Gallo, Jonathan M. Eden, Bastien Dieppois, Igor Drobyshev, Peter Z. Fulé, Jesús San-Miguel-Ayanz, and Matthew Blackett
Geosci. Model Dev., 16, 3103–3122, https://doi.org/10.5194/gmd-16-3103-2023, https://doi.org/10.5194/gmd-16-3103-2023, 2023
Short summary
Short summary
This study conducts the first global evaluation of the latest generation of global climate models to simulate a set of fire weather indicators from the Canadian Fire Weather Index System. Models are shown to perform relatively strongly at the global scale, but they show substantial regional and seasonal differences. The results demonstrate the value of model evaluation and selection in producing reliable fire danger projections, ultimately to support decision-making and forest management.
Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 16, 3013–3028, https://doi.org/10.5194/gmd-16-3013-2023, https://doi.org/10.5194/gmd-16-3013-2023, 2023
Short summary
Short summary
Desert dust has significant impacts on climate, public health, infrastructure and ecosystems. An impact assessment requires numerical predictions, which are challenging because the dust emissions are not well known. We present a novel approach using satellite observations and machine learning to more accurately estimate the emissions and to improve the model simulations.
Anna Denvil-Sommer, Erik T. Buitenhuis, Rainer Kiko, Fabien Lombard, Lionel Guidi, and Corinne Le Quéré
Geosci. Model Dev., 16, 2995–3012, https://doi.org/10.5194/gmd-16-2995-2023, https://doi.org/10.5194/gmd-16-2995-2023, 2023
Short summary
Short summary
Using outputs of global biogeochemical ocean model and machine learning methods, we demonstrate that it will be possible to identify linkages between surface environmental and ecosystem structure and the export of carbon to depth by sinking organic particles using real observations. It will be possible to use this knowledge to improve both our understanding of ecosystem dynamics and of their functional representation within models.
Zhenxia Liu, Zengjie Wang, Jian Wang, Zhengfang Zhang, Dongshuang Li, Zhaoyuan Yu, Linwang Yuan, and Wen Luo
Geosci. Model Dev., 16, 2939–2955, https://doi.org/10.5194/gmd-16-2939-2023, https://doi.org/10.5194/gmd-16-2939-2023, 2023
Short summary
Short summary
This study introduces an improved method of the Globally Resolved Energy Balance (GREB) model by the Bayesian network. The improved method constructs a coarse–fine structure that combines a dynamical model with a statistical model based on employing the GREB model as the global framework and utilizing Bayesian networks as the local optimization. The results show that the improved model has better applicability and stability on a global scale and maintains good robustness on the timescale.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
Short summary
Short summary
A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
Short summary
Short summary
A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Li Liu, Chao Sun, Xinzhu Yu, Hao Yu, Qingu Jiang, Xingliang Li, Ruizhe Li, Bin Wang, Xueshun Shen, and Guangwen Yang
Geosci. Model Dev., 16, 2833–2850, https://doi.org/10.5194/gmd-16-2833-2023, https://doi.org/10.5194/gmd-16-2833-2023, 2023
Short summary
Short summary
C-Coupler3.0 is an integrated coupler infrastructure with new features, i.e. a series of parallel-optimization technologies, a common halo-exchange library, a common module-integration framework, a common framework for conveniently developing a weakly coupled ensemble data assimilation system, and a common framework for flexibly inputting and outputting fields in parallel. It is able to handle coupling under much finer resolutions (e.g. more than 100 million horizontal grid cells).
Joseph Schoonover, Wilbert Weijer, and Jiaxu Zhang
Geosci. Model Dev., 16, 2795–2809, https://doi.org/10.5194/gmd-16-2795-2023, https://doi.org/10.5194/gmd-16-2795-2023, 2023
Short summary
Short summary
FEOTS aims to enhance the value of data produced by state-of-the-art climate models by providing a framework to diagnose and use ocean transport operators for offline passive tracer simulations. We show that we can capture ocean transport operators from a validated climate model and employ these operators to estimate water mass budgets in an offline regional simulation, using a small fraction of the compute resources required to run a full climate simulation.
Johann Dahm, Eddie Davis, Florian Deconinck, Oliver Elbert, Rhea George, Jeremy McGibbon, Tobias Wicky, Elynn Wu, Christopher Kung, Tal Ben-Nun, Lucas Harris, Linus Groner, and Oliver Fuhrer
Geosci. Model Dev., 16, 2719–2736, https://doi.org/10.5194/gmd-16-2719-2023, https://doi.org/10.5194/gmd-16-2719-2023, 2023
Short summary
Short summary
It is hard for scientists to write code which is efficient on different kinds of supercomputers. Python is popular for its user-friendliness. We converted a Fortran code, simulating Earth's atmosphere, into Python. This new code auto-converts to a faster language for processors or graphic cards. Our code runs 3.5–4 times faster on graphic cards than the original on processors in a specific supercomputer system.
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottlé, and Jérôme Servonnat
Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023, https://doi.org/10.5194/gmd-16-2583-2023, 2023
Short summary
Short summary
The proposed graphs of hydrological sub-grid elements for atmospheric models allow us to integrate the topographical elements needed in land surface models for a realistic representation of horizontal water and energy transport. The study demonstrates the numerical properties of the automatically built graphs and the simulated water flows.
Magnus Hieronymus
Geosci. Model Dev., 16, 2343–2354, https://doi.org/10.5194/gmd-16-2343-2023, https://doi.org/10.5194/gmd-16-2343-2023, 2023
Short summary
Short summary
A statistical model called the sea level simulator is presented and made freely available. The sea level simulator integrates mean sea level rise and sea level extremes into a joint probabilistic framework that is useful for flood risk estimation. These flood risk estimates are contingent on probabilities given to different emission scenarios and the length of the planning period. The model is also useful for uncertainty quantification and in decision and adaptation problems.
Quang-Van Doan, Toshiyuki Amagasa, Thanh-Ha Pham, Takuto Sato, Fei Chen, and Hiroyuki Kusaka
Geosci. Model Dev., 16, 2215–2233, https://doi.org/10.5194/gmd-16-2215-2023, https://doi.org/10.5194/gmd-16-2215-2023, 2023
Short summary
Short summary
This study proposes (i) the structural k-means (S k-means) algorithm for clustering spatiotemporally structured climate data and (ii) the clustering uncertainty evaluation framework (CUEF) based on the mutual-information concept.
Nadine Goris, Klaus Johannsen, and Jerry Tjiputra
Geosci. Model Dev., 16, 2095–2117, https://doi.org/10.5194/gmd-16-2095-2023, https://doi.org/10.5194/gmd-16-2095-2023, 2023
Short summary
Short summary
Climate projections of a high-CO2 future are highly uncertain. A new study provides a novel approach to identifying key regions that dynamically explain the model uncertainty. To yield an accurate estimate of the future North Atlantic carbon uptake, we find that a correct simulation of the upper- and interior-ocean volume transport at 25–30° N is key. However, results indicate that models rarely perform well for both indicators and point towards inconsistencies within the model ensemble.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
Short summary
Short summary
We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Rubina Ansari, Ana Casanueva, Muhammad Usman Liaqat, and Giovanna Grossi
Geosci. Model Dev., 16, 2055–2076, https://doi.org/10.5194/gmd-16-2055-2023, https://doi.org/10.5194/gmd-16-2055-2023, 2023
Short summary
Short summary
Bias correction (BC) has become indispensable to climate model output as a post-processing step to render output more useful for impact assessment studies. The current work presents a comparison of different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) for climate model simulations from three initiatives (CMIP6, CORDEX, and CORDEX-CORE) for a multivariate drought index (i.e., standardized precipitation evapotranspiration index).
Maria Chara Karypidou, Stefan Pieter Sobolowski, Lorenzo Sangelantoni, Grigory Nikulin, and Eleni Katragkou
Geosci. Model Dev., 16, 1887–1908, https://doi.org/10.5194/gmd-16-1887-2023, https://doi.org/10.5194/gmd-16-1887-2023, 2023
Short summary
Short summary
Southern Africa is listed among the climate change hotspots; hence, accurate climate change information is vital for the optimal preparedness of local communities. In this work we assess the degree to which regional climate models (RCMs) are influenced by the global climate models (GCMs) from which they receive their lateral boundary forcing. We find that although GCMs exert a strong impact on RCMs, RCMs are still able to display substantial improvement relative to the driving GCMs.
Enrico Zorzetto, Sergey Malyshev, Nathaniel Chaney, David Paynter, Raymond Menzel, and Elena Shevliakova
Geosci. Model Dev., 16, 1937–1960, https://doi.org/10.5194/gmd-16-1937-2023, https://doi.org/10.5194/gmd-16-1937-2023, 2023
Short summary
Short summary
In this paper we develop a methodology to model the spatial distribution of solar radiation received by land over mountainous terrain. The approach is designed to be used in Earth system models, where coarse grid cells hinder the description of fine-scale land–atmosphere interactions. We adopt a clustering algorithm to partition the land domain into a set of homogeneous sub-grid
tiles, and for each tile we evaluate solar radiation received by land based on terrain properties.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, https://doi.org/10.5194/gmd-16-1975-2023, 2023
Short summary
Short summary
The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
Heather S. Rumbold, Richard J. J. Gilham, and Martin J. Best
Geosci. Model Dev., 16, 1875–1886, https://doi.org/10.5194/gmd-16-1875-2023, https://doi.org/10.5194/gmd-16-1875-2023, 2023
Short summary
Short summary
The Joint UK Land Environment Simulator (JULES) uses a tiled representation of land cover but can only model a single dominant soil type within a grid box; hence there is no representation of sub-grid soil heterogeneity. This paper evaluates a new surface–soil tiling scheme in JULES and demonstrates the impacts of the scheme using several soil tiling approaches. Results show that soil tiling has an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture.
Felix Pithan, Marylou Athanase, Sandro Dahlke, Antonio Sánchez-Benítez, Matthew D. Shupe, Anne Sledd, Jan Streffing, Gunilla Svensson, and Thomas Jung
Geosci. Model Dev., 16, 1857–1873, https://doi.org/10.5194/gmd-16-1857-2023, https://doi.org/10.5194/gmd-16-1857-2023, 2023
Short summary
Short summary
Evaluating climate models usually requires long observational time series, but we present a method that also works for short field campaigns. We compare climate model output to observations from the MOSAiC expedition in the central Arctic Ocean. All models show how the arrival of a warm air mass warms the Arctic in April 2020, but two models do not show the response of snow temperature to the diurnal cycle. One model has too little liquid water and too much ice in clouds during cold days.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
Short summary
Short summary
Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
Short summary
Short summary
Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-42, https://doi.org/10.5194/gmd-2023-42, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM), based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Olawale James Ikuyajolu, Luke Van Roekel, Steven R. Brus, Erin E. Thomas, Yi Deng, and Sarat Sreepathi
Geosci. Model Dev., 16, 1445–1458, https://doi.org/10.5194/gmd-16-1445-2023, https://doi.org/10.5194/gmd-16-1445-2023, 2023
Short summary
Short summary
Wind-generated waves play an important role in modifying physical processes at the air–sea interface, but they have been traditionally excluded from climate models due to the high computational cost of running spectral wave models for climate simulations. To address this, our work identified and accelerated the computationally intensive section of WAVEWATCH III on GPU using OpenACC. This allows for high-resolution modeling of atmosphere–wave–ocean feedbacks in century-scale climate integrations.
Edward C. Chan, Joana Leitão, Andreas Kerschbaumer, and Timothy M. Butler
Geosci. Model Dev., 16, 1427–1444, https://doi.org/10.5194/gmd-16-1427-2023, https://doi.org/10.5194/gmd-16-1427-2023, 2023
Short summary
Short summary
Yeti is a Handbook Emission Factors for Road Transport-based traffic emission inventory written in the Python 3 scripting language, which adopts a generalized treatment for activity data using traffic information of varying levels of detail introduced in a systematic and consistent manner, with the ability to maximize reusability. Thus, Yeti has been conceived and implemented with a high degree of data and process symmetry, allowing scalable and flexible execution while affording ease of use.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteacino Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
EGUsphere, https://doi.org/10.5194/egusphere-2023-310, https://doi.org/10.5194/egusphere-2023-310, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere, and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve "ocean eddies", which are the largest source of ocean variability and modulate the mixed layer properties. We find that the mixed layer depth is better represented in eddy-rich models, but unfortunately, not uniformly across the globe and not in all models.
Haopeng Fan, Siran Li, Zhongmiao Sun, Guorui Xiao, Xinxing Li, and Xiaogang Liu
Geosci. Model Dev., 16, 1345–1358, https://doi.org/10.5194/gmd-16-1345-2023, https://doi.org/10.5194/gmd-16-1345-2023, 2023
Short summary
Short summary
The traditional tropospheric zenith hydrostatic delay (ZHD) model's bias is usually thought negligible, yet it still reaches 10 mm sometimes and would lead to millimeter-level position errors for space geodetic observations. Therefore, we analyzed the bias’ characteristics and present a grid model to correct the traditional ZHD formula. When verifying the efficiency based on data from the ECMWF (European Centre for Medium-Range Weather Forecasts), ZHD biases were rectified by ~50 %.
Gang Liu, Shushi Peng, Chris Huntingford, and Yi Xi
Geosci. Model Dev., 16, 1277–1296, https://doi.org/10.5194/gmd-16-1277-2023, https://doi.org/10.5194/gmd-16-1277-2023, 2023
Short summary
Short summary
Due to computational limits, lower-complexity models (LCMs) were developed as a complementary tool for accelerating comprehensive Earth system models (ESMs) but still lack a good precipitation emulator for LCMs. Here, we developed a data-calibrated precipitation emulator (PREMU), a computationally effective way to better estimate historical and simulated precipitation by current ESMs. PREMU has potential applications related to land surface processes and their interactions with climate change.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
Short summary
Short summary
We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Yann Quilcaille, Thomas Gasser, Philippe Ciais, and Olivier Boucher
Geosci. Model Dev., 16, 1129–1161, https://doi.org/10.5194/gmd-16-1129-2023, https://doi.org/10.5194/gmd-16-1129-2023, 2023
Short summary
Short summary
The model OSCAR is a simple climate model, meaning its representation of the Earth system is simplified but calibrated on models of higher complexity. Here, we diagnose its latest version using a total of 99 experiments in a probabilistic framework and under observational constraints. OSCAR v3.1 shows good agreement with observations, complex Earth system models and emerging properties. Some points for improvements are identified, such as the ocean carbon cycle.
Sandra L. LeGrand, Theodore W. Letcher, Gregory S. Okin, Nicholas P. Webb, Alex R. Gallagher, Saroj Dhital, Taylor S. Hodgdon, Nancy P. Ziegler, and Michelle L. Michaels
Geosci. Model Dev., 16, 1009–1038, https://doi.org/10.5194/gmd-16-1009-2023, https://doi.org/10.5194/gmd-16-1009-2023, 2023
Short summary
Short summary
Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
Roman Brogli, Christoph Heim, Jonas Mensch, Silje Lund Sørland, and Christoph Schär
Geosci. Model Dev., 16, 907–926, https://doi.org/10.5194/gmd-16-907-2023, https://doi.org/10.5194/gmd-16-907-2023, 2023
Short summary
Short summary
The pseudo-global-warming (PGW) approach is a downscaling methodology that imposes the large-scale GCM-based climate change signal on the boundary conditions of a regional climate simulation. It offers several benefits in comparison to conventional downscaling. We present a detailed description of the methodology, provide companion software to facilitate the preparation of PGW simulations, and present validation and sensitivity studies.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
Short summary
Short summary
We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev., 16, 851–867, https://doi.org/10.5194/gmd-16-851-2023, https://doi.org/10.5194/gmd-16-851-2023, 2023
Short summary
Short summary
Cell-tracking algorithms allow for the study of properties of a convective cell across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm's criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
Short summary
Short summary
Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Yan Zhang, Xuantong Wang, Yuhao Sun, Chenhui Ning, Shiming Xu, Hengbin An, Dehong Tang, Hong Guo, Hao Yang, Ye Pu, Bo Jiang, and Bin Wang
Geosci. Model Dev., 16, 679–704, https://doi.org/10.5194/gmd-16-679-2023, https://doi.org/10.5194/gmd-16-679-2023, 2023
Short summary
Short summary
We construct a new ocean model, OMARE, that can carry out multi-scale ocean simulation with adaptive mesh refinement. OMARE is based on the refactorization of NEMO with a third-party, high-performance piece of middleware. We report the porting process and experiments of an idealized western-boundary current system. The new model simulates turbulent and temporally varying mesoscale and submesoscale processes via adaptive refinement. Related topics and future work with OMARE are also discussed.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717, https://doi.org/10.5194/gmd-16-705-2023, https://doi.org/10.5194/gmd-16-705-2023, 2023
Short summary
Short summary
To improve the numerical model predictability of monthly extended-range scales, we use the simplified slab ocean model (SOM) to restrict the complicated sea surface temperature (SST) bias from a 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have better performance than the WRF-ROMS, which has a significant impact on the atmosphere. For extreme weather events such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-311, https://doi.org/10.5194/gmd-2022-311, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Crop models incorporated in earth system models are essential to accurately simulate crop growth processes on Earth’s surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at point-scale; (2) apply dynamic planting/harvest schedules; (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Dagmawi Teklu Asfaw, Michael Bliss Singer, Rafael Rosolem, David MacLeod, Mark Cuthbert, Edisson Quichimbo Miguitama, Manuel F. Rios Gaona, and Katerina Michaelides
Geosci. Model Dev., 16, 557–571, https://doi.org/10.5194/gmd-16-557-2023, https://doi.org/10.5194/gmd-16-557-2023, 2023
Short summary
Short summary
stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
Markus Köhli, Martin Schrön, Steffen Zacharias, and Ulrich Schmidt
Geosci. Model Dev., 16, 449–477, https://doi.org/10.5194/gmd-16-449-2023, https://doi.org/10.5194/gmd-16-449-2023, 2023
Short summary
Short summary
In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
Short summary
Short summary
Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
Short summary
Short summary
More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-307, https://doi.org/10.5194/gmd-2022-307, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to >100,000 years. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate-carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
Short summary
Short summary
Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-291, https://doi.org/10.5194/gmd-2022-291, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent, so that users can make their own decisions on how to resolve these, should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
Short summary
Short summary
All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
Short summary
Short summary
The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
Short summary
Short summary
In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Cited articles
Aichner, B., Herzschuh, U., Wilkes, H., Vieth, A., and Böhner, J.: δD values of n-alkanes in Tibetan lake sediments and aquatic macrophytes – A surface sediment study and application to a 16 ka record from Lake Koucha, Org. Geochem., 41, 779–790, https://doi.org/10.1016/j.orggeochem.2010.05.010, 2010.
Asmussen, P., Conrad, O., Günther, A., Kirsch, M., and Riller, U.: Semi-automatic segmentation of petrographic thin section images using a "seeded-region growing algorithm" with an application to characterize wheathered subarkose sandstone, Comput. Geosci., https://doi.org/10.1016/j.cageo.2015.05.001, in press, 2015.
Bechtel, B.: Multitemporal Landsat data for urban heat island assessment and classification of local climate zones, in: Urban Remote Sensing Event (JURSE), 2011 Joint, Presented at the Urban Remote Sensing Event (JURSE), 2011 Joint, IEEE, 129–132, https://doi.org/10.1109/JURSE.2011.5764736, 2011a.
Bechtel, B.: Multisensorale Fernerkundungsdaten zur mikroklimatischen Beschreibung und Klassifikation urbaner Strukturen, Photogramm.-Fernerkund.-Geoinformation, 2011, 325–338, 2011b.
Bechtel, B.: Robustness of Annual Cycle Parameters to Characterize the Urban Thermal Landscapes, IEEE Geosci. Remote Sens. Lett., 9, 876–880, https://doi.org/10.1109/LGRS.2012.2185034, 2012.
Bechtel, B.: A New Global Climatology of Annual Land Surface Temperature, Remote Sens., 7, 2850–2870, https://doi.org/10.3390/rs70302850, 2015.
Bechtel, B. and Daneke, C.: Classification of Local Climate Zones Based on Multiple Earth Observation Data, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 5, 1191–1202, https://doi.org/10.1109/JSTARS.2012.2189873, 2012.
Bechtel, B. and Schmidt, K. J.: Floristic mapping data as a proxy for the mean urban heat island, Clim. Res., 49, 45–58, https://doi.org/10.3354/cr01009, 2011.
Bechtel, B., Ringeler, A., and Böhner, J.: Segmentation for Object Extraction of Trees using MATLAB and SAGA, in: SAGA – Seconds Out, Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie. Univ. Hamburg, Inst. für Geographie, 1–12, 2008.
Bechtel, B., Langkamp, T., Ament, F., Böhner, J., Daneke, C., Günzkofer, R., Leitl, B., Ossenbrügge, J., and Ringeler, A.: Towards an urban roughness parameterisation using interferometric SAR data taking the Metropolitan Region of Hamburg as an example, Meteorol. Z., 20, 29–37, https://doi.org/10.1127/0941-2948/2011/0496, 2011.
Bechtel, B., Daneke, C., Langkamp, T., Oßenbrügge, J., and Böhner, J.: Classification of Local Climate Zones from multitemporal remote sensing data, in: Proceedings ICUC8 – 8th International Conference on Urban Climates. Presented at the 8th International Conference on Urban Climates, 06–10 August 2012, UCD, Dublin Ireland, 2012a.
Bechtel, B., Langkamp, T., Böhner, J., Daneke, C., Oßenbrügge, J., and Schempp, S.: Classification and modelling of urban micro-climates using multitemporal remote sensing data, ISPRS – Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XXXIX-B8, 463–468, https://doi.org/10.5194/isprsarchives-XXXIX-B8-463-2012, 2012b.
Bechtel, B., Zakšek, K., and Hoshyaripour, G.: Downscaling Land Surface Temperature in an Urban Area: A Case Study for Hamburg, Germany, Remote Sens., 4, 3184–3200, https://doi.org/10.3390/rs4103184, 2012c.
Bechtel, B., Böhner, J., Zakšek, K., and Wiesner, S.: Downscaling of diurnal land surface temperature cycles for urban heat island monitoring, in: Urban Remote Sensing Event (JURSE), 2013 Joint, Presented at the Urban Remote Sensing Event (JURSE), 2013 Joint, IEEE, 2013.
Bechtel, B., Wiesner, S., and Zaksek, K.: Estimation of Dense Time Series of Urban Air Temperatures from Multitemporal Geostationary Satellite Data, J. Sel. Top. Appl. Earth Obs. Remote Sens., 7, 4129–4137, https://doi.org/10.1109/JSTARS.2014.2322449, 2014.
Bechtel, B., Alexander, P. J., Böhner, J., Ching, J., Conrad, O., Feddema, J., Mills, G., See, L., and Stewart, I.: Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities, ISPRS Int. J. Geo-Inf., 4, 199–219, https://doi.org/10.3390/ijgi4010199, 2015.
Behrens, T. and Scholten, T.: Digital soil mapping in Germany – a review, J. Plant Nutr. Soil Sci., 169, 434–443, 2006.
Bernardini, F., Sgambati, A., Montagnari Kokelj, M., Zaccaria, C., Micheli, R., Fragiacomo, A., Tiussi, C., Dreossi, D., Tuniz, C., and De Min, A.: Airborne LiDAR application to karstic areas: the example of Trieste province (north-eastern Italy) from prehistoric sites to Roman forts, J. Archaeol. Sci., 40, 2152–2160, https://doi.org/10.1016/j.jas.2012.12.029, 2013.
Bivand, R. S.: 14 GeoComputation and Open-Source Software, in: GeoComputation, CRC Press, 329 pp., 2014.
Blaschke, T.: Object based image analysis for remote sensing, ISPRS J. Photogramm. Remote Sens., 65, 2–16, 2010.
Bock, M. and Köthe, R.: Predicting the Depth of Hydromorphic Soil Characteristics Influenced by Ground Water, 2008.
Bock, M., Böhner, J., Conrad, O., Köthe, R., and Ringeler, A.: Methods for creating Functional Soil Databases and applying Digital Soil Mapping with SAGA GIS, JRC Sci. Tech. Rep. EUR 22646 EN, 2007a.
Bock, M., Conrad, O., Köthe, R., and Ringeler, A.: Methods for creating functional soil databases and applying digital soil mapping with SAGA GIS, in: Status and Prospect of Soil Information in South-Eastern Europe: Soil Databases, Projects and Applications, European Communities, Luxembourg, 149–162, 2007b.
Bock, M., Böhner, J., Conrad, O., Köthe, R., and Ringeler, A.: Methods for creating Functional Soil Databases and applying Digital Soil Mapping with SAGA GIS, 2007c.
Bock, M., Günther, A., Ringeler, A., Baritz, R., and Böhner, J.: Assessment of soil parent material formation in periglacial environments through medium scale landscape evolution modelling, Geophys. Res. Abstr., p. 8796, EGU2012-8796, EGU General Assembly 2012, Vienna, Austria, 2012.
Böhner, J.: Regionalisierung bodenrelevanter Klimaparameter für das Niedersächsische Landes-amt für Bodenforschung (NLfB) und die Bundesanstalt für Geowissenschaften und Rohstoffe (BGR), Arbeitshefte Boden, 4, 17–66, 2004.
Böhner, J.: Advancements and new approaches in climate spatial prediction and environmental modelling, Arbeitsberichte Geogr. Inst. HU Zu Berl., 109, 49–90, 2005.
Böhner, J.: General climatic controls and topoclimatic variations in Central and High Asia, Boreas, 35, 279–295, https://doi.org/10.1080/03009480500456073, 2006.
Böhner, J. and Antonic, O.: Land surface parameters specific to topo-climatology, Geomorphometry-Concepts Softw. Appl., 195–226, 2009.
Böhner, J. and Kickner, S.: Woher der Wind weht, GeoBit, 5, 22–25, 2006.
Böhner, J. and Köthe, R.: Bodenregionalisierung und Prozeßmodellierung: Instrumente für den Bodenschutz, Petermann. Geogr. Mitt., 147, 72–82, 2003.
Böhner, J. and Langkamp, T.: Klimawandel und Landschaft – Regionalisierung, Rekonstruktion und Projektion des Klima- und Landschaftswandels Zentral- und Hochasiens, Hambg. Symp. Geogr., 2, 27–49, 2010.
Böhner, J. and Lehmkuhl, F.: Climate and Environmental Change Modelling in Central and High Asia, Boreas, 34, 220–231, 2005.
Böhner, J. and Selige, T.: Spatial prediction of soil attributes using terrain analysis and climate regionalisation, in: SAGA – Analysis and Modelling Applications, Göttinger Geographische Abhandlungen, Göttingen, 13–28, 2006.
Böhner, J., Köthe, R., Conrad, O., Gross, J., Ringeler, A., and Selige, T.: Soil regionalisation by means of terrain analysis and process parameterisation, Soil Classif., European Soil Bureau, Research Report 7, 213–222, 2002.
Böhner, J., Schäfer, W., Conrad, O., Gross, J., and Ringeler, A.: The WEELS model: methods, results and limitations, Catena, 52, 289–308, 2003.
Böhner, J., Dietrich, H., Fraedrich, K., Kawohl, T., Kilian, M., Lucarini, V., and Lunkeit, F.: Development and Implementation of a Hierarchical Model Chain for Modelling Regional Climate Variability and Climate Change over Southern Amazonia, in: Interdisciplinary Analysis and Modeling of Carbon-Optimized Land Management Strategies for Southern Amazonia, edite by: Gerold, G., Jungkunst, H. F., Wantzen, K. M., Schönenberg, R., Amorim, R. S. S., Couto, E. G., Madari, B., and Hohnwald, S., Universitätsdrucke Göttingen, Göttingen, 174 pp., 2014.
Bolch, T.: GIS- und fernerkundungsgestützte Analyse und Visualisierung von Klima- und Gletscheränderungen im nördlichen Tien Shan (Kasachstan/Kyrgyzstan): mit einem Vergleich zur Bernina-Gruppe, Alpen, Dissertation, Faculty of Science of the Friedrich-Alexander-Universität Erlangen-Nuernberg, Germany, 210 pp., 2006.
Bolch, T.: Climate change and glacier retreat in northern Tien Shan (Kazakhstan/Kyrgyzstan) using remote sensing data, Glob. Planet. Change, 56, 1–12, https://doi.org/10.1016/j.gloplacha.2006.07.009, 2007.
Bolch, T. and Kamp, U.: Glacier Mapping in High Mountains Using DEMs, Landsat and ASTER Data, Grazer Schriften Geogr. Raumforsch., Grazer Schriften der Geographie und Raumforschung 41, 37–48, 2006.
Boettinger, J. L.: Digital Soil Mapping: Bridging Research, Environmental Application, and Operation, Springer Science & Business Media, 2010.
Brenning, A.: Statistical geocomputing combining R and SAGA: The example of landslide susceptibility analysis with generalized additive models, SAGA–Seconds Hambg, Beitr. Zur Phys. Geogr. Landschaftsökologie 19, 23–32, 2008.
Brenning, A.: Benchmarking classifiers to optimally integrate terrain analysis and multispectral remote sensing in automatic rock glacier detection, Remote Sens. Environ., 113, 239–247, 2009.
Brenning, A., Long, S., and Fieguth, P.: Detecting rock glacier flow structures using Gabor filters and IKONOS imagery, Remote Sens. Environ., 125, 227–237, 2012.
Chang, C.-C. and Lin, C.-J.: LIBSVM: a library for support vector machines, ACM Transa. Int. Sys. Technol. (ACM TIST), 2, 1–27, 2011.
Conrad, O.: SAGA – Entwurf, Funktionsumfang und Anwendung eines Systems für Automatisierte Geowissenschaftliche Analysen, Dissertation, Faculties Natural Sciences, Mathematics and Informatics, Faculty of Geosciences and Geography, 221 pp., 2007.
Conrad, O., Jens-Peter, K., Michael, B., Gerhard, G., and Bohner, J.: Soil degradation risk assessment integrating terrain analysis and soil spatial prediction methods, GEOOKO-Bensh., 27, 165–174, 2006.
Czech, A.: GIS-gestützte morphometrische Analyse von Okklusalflächen mit SAGA GIS, Unpublished BSc thesis, University of Hamburg, Faculty of Earth Sciences, Institute of Geographie, Sect. Physical Geography, Hamburg, 2010.
Czegka, W. and Junge, F. W.: The use of SAGA as a mobile Field-Tool in the environmental Geochemistry, in: SAGA – Seconds Out, Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie, Univ. Hamburg, Inst. für Geographie, Hamburg, 33–36, 2008.
Dietrich, H. and Böhner, J.: Cold Air Production and Flow in a Low Mountain Range Landscape in Hessia (Germany), in: SAGA – Seconds Out, Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie, Univ. Hamburg, Inst. für Geographie, Hamburg, 37–48, 2008.
Enea, A., Romanescu, G., and Stoleriu, C.: Quantitative considerations concerning the source-areas for the silting of the red lake (Romania) lacustrine basin, in: Water Resources and Wetlands, Tulcea, Romania, 14–16, 2012.
ESRI: The ArcGIS Platform, available at: http://www.esri.com/software/arcgis, last access: 05 June 2015.
Fader, M., Böhner, J., and Gerold, G.: Precipitation Variability and Landscape Degradation in Rio Negro (Argentina), Geo-Öko, 33, 5–33, 2012.
Fenoy, G., Bozon, N., and Raghavan, V.: ZOO-Project: the open WPS platform, Appl. Geomat., 5, 19–24, 2013.
Fey, C., Zangerl, C., Wichmann, V., and Prager, C.: Back-Calculation of Medium-Scale Rockfalls Using an Empirical GIS Model, Int. Symp. Rock Slope Stab. Open Pit Min. Civ. Eng. Vancover Can, 2011.
Free Software Foundation: Licenses, available at: http://www.gnu.org/licenses/licenses.html, last access: 04 June 2015.
Gerlitz, L.: Using fuzzified regression trees for statistical downscaling and regionalization of near surface temperatures in complex terrain, Theor. Appl. Climatol., 118, 1–16, https://doi.org/10.1007/s00704-014-1285-x, 2014.
Gerlitz, L., Conrad, O., Thomas, A., and Böhner, J.: Assessment of Warming Patterns for the Tibetan Plateau and its adjacent Lowlands based on an elevation- and bias corrected ERA-Interim Data Set, Clim. Res., 58, 235–246, https://doi.org/10.3354/cr01193, 2014.
Gerlitz, L., Conrad, O., and Böhner, J.: Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach, Earth Syst. Dynam., 6, 61–81, https://doi.org/10.5194/esd-6-61-2015, 2015.
Goetz, J. N., Guthrie, R. H., and Brenning, A.: Integrating physical and empirical landslide susceptibility models using generalized additive models, Geomorphology, 129, 376–386, 2011.
Grabs, T. J., Jencso, K. G., McGlynn, B. L., and Seibert, J.: Calculating terrain indices along streams: A new method for separating stream sides, Water Resour. Res., 46, W12536, https://doi.org/10.1029/2010WR009296, 2010.
Günther, A.: SLOPEMAP: programs for automated mapping of geometrical and kinematical properties of hard rock hill slopes, Comput. Geosci., 29, 865–875, 2003.
Günther, A., Carstensen, A., and Pohl, W.: Automated sliding susceptibility mapping of rock slopes, Nat. Hazards Earth Syst. Sci., 4, 95–102, https://doi.org/10.5194/nhess-4-95-2004, 2004.
Haas, F.: Fluviale Hangprozesse in alpinen Einzugsgebieten der nördlichen Kalkalpen: Quantifizierung und Modellierungsansätze, Eichstätter Geographische Arbeiten, Profil-Verlag, München, Wien, 2008.
Haas, F., Heckmann, T., Wichmann, V., and Becht, M.: Quantification and Modeling of Fluvial Bedload Discharge from Hillslope Channels in two Alpine Catchments (Bavarian Alps, Germany), Z. Geomorphol. Suppl., 55, 147–168, https://doi.org/10.1127/0372-8854/2011/0055S3-0056, 2011.
Haas, F., Heckmann, T., Wichmann, V., and Becht, M.: Runout analysis of a large rockfall in the Dolomites/Italian Alps using LIDAR derived particle sizes and shapes, Earth Surf. Process. Landf., 37, 1444–1455, https://doi.org/10.1002/esp.3295, 2012.
Hartemink, A. E., McBratney, A. B., and de Lourdes Mendoncca-Santos, M.: Digital soil mapping with limited data, Springer, 2008.
Heckmann, T.: Untersuchungen zum Sedimenttransport durch Grundlawinen in zwei Einzugsgebieten der Nördlichen Kalkalpen: Quantifizierung, Analyse und Ansätze zur Modellierung der geomorphologischen Aktivität, Eichstätter Geographische Arbeiten, Profil-Verlag, München, 2006.
Heckmann, T. and Becht, M.: Statistical disposition modelling of mass movements, in: SAGA – Analysis and Modelling Applications, Göttinger Geographische Abhandlungen, Göttingen, 61–74, 2006.
Heckmann, T., Wichmann, V., and Becht, M.: Sediment transport by avalanches in the Bavarian Alps revisited – a perspective on modelling, Z. Geomorphol. Suppl. Issues, 138, 11–25, 2005.
Heckmann, T., Bimböse, M., Krautblatter, M., Haas, F., Becht, M., and Morche, D.: From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany, Earth Surf. Process. Landf., 37, 119–133, 2012.
Heinrich, R. and Conrad, O.: Diffusion, Flow and Concentration Gradient Simulation with SAGA GIS using Cellular Automata Methods, in: SAGA – Seconds Out, Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie, Univ. Hamburg, Inst. für Geographie, Hamburg, 59–70, 2008.
Hengl, T. and Reuter, H. I.: Geomorphometry: Concepts, Software, Applications, Newnes, 2009.
Herzschuh, U., Birks, H. J. B., Mischke, S., Zhang, C., and Böhner, J.: A modern pollen–climate calibration set based on lake sediments from the Tibetan Plateau and its application to a Late Quaternary pollen record from the Qilian Mountains, J. Biogeogr., 37, 752–766, 2010.
Herzschuh, U., Ni, J., Birks, H. J. B., and Böhner, J.: Driving forces of mid-Holocene vegetation shifts on the upper Tibetan Plateau, with emphasis on changes in atmospheric CO2 concentrations, Quaternary Sci. Rev., 30, 1907–1917, 2011.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas, Int. J. Climatol., 25, 1965–1978, 2005.
Jansen, P.: Flächenhafte Berechnung der Hangkinematik und Stabilitätsmodellierung im Bereich des Göttinger Waldes Unpublished MSc thesis, University of Hamburg, Faculty of Earth Sciences, Institute for Geology, Hamburg, 2014.
Jürgens, N., Oldeland, J., Hachfeld, B., Erb, E., and Schultz, C.: Ecology and spatial patterns of large-scale vegetation units within the central Namib Desert, J. Arid Environ., 93, 59–79, https://doi.org/10.1016/j.jaridenv.2012.09.009, 2013.
Kamlun, K. U., Goh, M. H., Teo, S. P., and Phua, M. H.: Monitoring of Deforestation and Fragmentation in Sarawak, Malaysia between 1990 and 2009 using Landsat and SPOT Images, J. Forest Sci., 28, 152–157, 2012.
Kaye, S.: Finding the site of Boudica's last battle: Roman logistics empowered the sword, bandaarcgeophysics, available at: http://www.bandaarcgeophysics.co.uk/arch/boudica logistics.pdf (last access: 03 December 2014), 2013.
Kessler, M., Böhner, J., and Kluge, J.: Modelling tree height to assess climatic conditions at tree lines in the Bolivian Andes, Ecol. Model., 207, 223–233, https://doi.org/10.1016/j.ecolmodel.2007.05.001, 2007.
Kidd, D. and Viscarra Rossel, R.: ACLEP-Tasmanian Digital Soil Mapping Project – a component of the Wealth from Water Land Suitability Project, available at: http://www.clw.csiro.au/aclep/documents/TAS_ACLEP_DSM_Project_Report.pdf (last access: 28 June 2015), 2011.
Klinge, M., Böhner, J., and Lehmkuhl, F.: Climate Patterns, Snow- and Timberline in the Altai Mountains, Central Asia, Erdkunde, 57, 296–308, 2003.
Klinge, M., Böhner, J., and Erasmi, S.: Modeling forest lines and forest distribution patterns with remote-sensing data in a mountainous region of semiarid central Asia, Biogeosciences, 12, 2893–2905, https://doi.org/10.5194/bg-12-2893-2015, 2015.
Köthe, R. and Bock, M.: Preprocessing of Digital Elevation Models–derived from Laser Scanning and Radar Interferometry–for Terrain Analysis in Geosciences, Proc. Geomorph., 155–161, 2009.
Köthe, R., Gehrt, E., and Böhner, J.: Automatische Reliefanalyse für geowissenschaftliche Kartierungen, Arbeitshefte Boden, 1, 31–37, 1996.
Köthe, U.: Generische Programmierung für die Bildverarbeitung, BoD–Books on Demand, 2000.
Kühn, J., Brenning, A., Wehrhan, M., Koszinski, S., and Sommer, M.: Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture, Precis. Agric., 10, 490–507, 2009.
Lado, L. R., Hengl, T., and Reuter, H. I.: Heavy metals in European soils: a geostatistical analysis of the FOREGS Geochemical database, Geoderma, 148, 189–199, 2008.
Lal, R. and Stewart, B. A.: Soil Management of Smallholder Agriculture, CRC Press, 2014.
Lehmkuhl, F., Böhner, J., and Stauch, G.: Geomorphologische Formungs-und Prozessregionen in Zentralasien, Petermanns Geogr. Mitteilungen, 147, 6–13, 2003.
Lehrling, M.: Klimaentwicklung in Alaska: Eine GIS-gestützte Erfassung und Analyse der raumzeitlichen Entwicklung von Temperatur und Niederschlag, ibidem-Verlag, 2006.
Leopold, M., Gannaway, E., Völkel, J., Haas, F., Becht, M., Heckmann, T., Westphal, M., and Zimmer, G.: Geophysical prospection of a bronze foundry on the southern slope of the acropolis at athens, Greece, Archaeol. Prospect., 18, 27–41, https://doi.org/10.1002/arp.402, 2011.
Liersch, S. and Volk, M.: A rainfall-runoff database to support flood risk assessment, in: Proceedings of the iEMSs Fourth Biennial Meeting, Presented at the International Congress on Environmental Modelling and Software, Barcelona, Catalonia, 494–502, 2008.
Mantovani, F., Gracia, F. J., de Cosmo, P. D., and Suma, A.: A new approach to landslide geomorphological mapping using the Open Source software in the Olvera area (Cadiz, Spain), Landslides, 7, 69–74, https://doi.org/10.1007/s10346-009-0181-4, 2010.
Marini, L., Scotton, M., Klimek, S., Isselstein, J., and Pecile, A.: Effects of local factors on plant species richness and composition of Alpine meadows, Agric. Ecosyst. Environ., 119, 281–288, 2007.
Marini, L., Fontana, P., Klimek, S., Battisti, A., and Gaston, K. J.: Impact of farm size and topography on plant and insect diversity of managed grasslands in the Alps, Biol. Conserv., 142, 394–403, https://doi.org/10.1016/j.biocon.2008.10.034, 2009.
McBratney, A. B., Mendoncca Santos, M. L., and Minasny, B.: On digital soil mapping, Geoderma, 117, 3–52, 2003.
Miehe, G., Miehe, S., Böhner, J., Kaiser, K., Hensen, I., Madsen, D., Liu, J. Q., and Opgenoorth, L.: How old is the human footprint in the world's largest alpine ecosystem? A review of multiproxy records from the Tibetan Plateau from the ecologists' viewpoint, Quaternary Sci. Rev., 86, 190–209, 2014.
Milevski, I.: Estimation of soil erosion risk in the upper part of bregalnica watershed-republic of macedonia, based on digital elevation model and satellite imagery, Proceedings from the 5th international conference on geographic information systems, Fatih University, Istanbul, 2008.
Milevski, I., Dragicevic, S., and Kostadinov, S.: Digital elevation model and satellite images an assessment of soil erosion potential in the Pcinja catchment, Glas. Srp. Geogr. Drustva, 87, 11–20, https://doi.org/10.2298/GSGD0702011M, 2007.
Morche, D., Haas, F., Baewert, H., Heckmann, T., Schmidt, K.-H., and Becht, M.: Sediment transport in the proglacial Fagge River (Kaunertal/Austria), Eros. Sediment Yields Chang. Environ, IAHS Press Wallingford IAHS Publ., 356, 72–81, 2012
Muenchow, J., Brenning, A., and Richter, M.: Geomorphic process rates of landslides along a humidity gradient in the tropical Andes, Geomorphology, 139–140, 271–284, 2012.
National Research Council (Ed.): Basic Research Opportunities in Earth Science. Washington, D.C., National Academy Press, 154 pp., 2001.
Neteler, M., Bowman, M. H., Landa, M., and Metz, M.: GRASS GIS: A multi-purpose open source GIS, Environ. Model. Softw., 31, 124–130, https://doi.org/10.1016/j.envsoft.2011.11.014, 2012.
Nothdurft, A., Wolf, T., Ringeler, A., Böhner, J., and Saborowski, J.: Spatio-temporal prediction of site index based on forest inventories and climate change scenarios, Forest Ecol. Manage., 279, 97–111, 2012.
Olaya, V. and Conrad, O.: Chapter 12 Geomorphometry in SAGA, in: Developments in Soil Science, edited by: Hengl, T. and Reuter, H. I., Elsevier, 293–308, 2009.
Patriche, C. V., P\^irnuau, R. G., Rocsca, B., and Stoica, D. L.: Assessment of Soil Erosion and its Impact on Humus Spatial and Temporal Dynamics, Bull. Univ. Agric. Sci. Vet. Med. Cluj-Napoca Agric., 69, 185–194, 2012.
Peters-Walker, D., Krause, K.-H., Strellen, T., Kleindienst, H., Petrini-Monteferri, F., and Wichmann, V.: Modellierung von Abfluss und Geschiebetransport in alpinen Wildbacheinzugsgebieten mit SimAlp/HQsim, Wildbach-Lawinenverbau, 76, 154–166, 2012.
Petrini-Montferri, F., Wichmann, V., Georges, C., Mantovani, D., and Stötter, J.: Erweiterung der GIS Software SAGA zur Verarbeitung von Laserscanning-Daten der Autonomen Provinz Bozen – Südtirol, in: Angewandte Geoinformatik, edited by: Strobl., J., Blaschke, T., and Griesebner, G., Beiträge zum 21. AGIT-Symposium, Salzburg, 618–623, 2009.
Phua, M.-H., Conrad, O., Kamlun, K. U., Fischer, M., and Böhner, J.: Multitemporal Fragmentation Analysis of Peat Swamp Forest in the Klias Peninsula, Sabah, Malaysia using GIS and Remote Sensing Techniques, in: SAGA – Seconds Out, Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie, Univ. Hamburg, Inst. für Geographie, Hamburg, 81–90, 2008.
Prouza, Z., Beckova, V., Cespirova, I., Helebrant, J., Hulka, J., Kuca, P., Michalek, V., Rulik, P., Skrkal, J., and Hovorka, J.: Field Tests Using Radioactive Matter, Radiat. Prot. Dosimetry, ncp299, https://doi.org/10.1093/rpd/ncp299, 2010.
QGIS Development Team: QGIS Geographic Information System. Open Source Geospatial Foundation Project, 2014.
Rieg, L., Wichmann, V., Rutzinger, M., Sailer, R., Geist, T., and Stötter, J.: Data infrastructure for multitemporal airborne LiDAR point cloud analysis – Examples from physical geography in high mountain environments, Comput. Environ. Urban Syst., 45, 137–146, 2014.
Roecker, S. M., Howell, D. W., Haydu-Houdeshell, C. A., and Blinn, C.: A Qualitative Comparison of Conventional Soil Survey and Digital Soil Mapping Approaches, in: Digital Soil Mapping, Progress in Soil Science, edited by: Boettinger, D. J. L., Howell, D. W., Moore, A. C., Hartemink, P. D. A. E., and Kienast-Brown, S., Springer Netherlands, 369–384, 2010.
Russ, A. and Riek, W.: Methode zur Ableitung des Grundwasserflurabstandes aus Karten der forstlichen Standortskartierung und digitalen Geländemodellen in Brandenburg, in: Waldökologie, Landschaftsforschung und Naturschutz, 12, 85–92, 2011.
Sass, O., Haas, F., Schimmer, C., Heel, M., Bremer, M., Stöger, F., and Wetzel, K.-F.: Impact of Forest Fires on Geomorphic Processes in the Tyrolean Limestone Alps, Geogr. Ann. Ser. Phys. Geogr., 94, 117–133, https://doi.org/10.1111/j.1468-0459.2012.00452.x, 2012.
Schauppenlehner, T.: Geostatistische Analysen zur Integration von Geländemodellen und Bodenschätzungsdaten für verbesserte digitale Bodenkarten am Beispiel einer alluvialen Landschaft (Dissertation), University of natural resources and life sciences, 2008.
Setiawan, M. A.: Integrated Soil Erosion Risk Management in the upper Serayu Watershed, Wonosobo District, Central Java Province, Indonesia, Faculty of Geo- and Atmospheric Sciences of the Universität Innsbruck, Innsbruck, 2012.
Smart, J., Hock, K., and Csomor, S.: Cross-platform GUI programming with wxWidgets, Prentice Hall Professional, 2005.
Soria-Auza, R. W.: Diversität und Biogeographie der Farne und Vögel Boliviens, Niche Modellierung GIS Applicationen, 2010.
Soria-Auza, R. W., Kessler, M., Bach, K., Barajas-Barbosa, P. M., Lehnert, M., Herzog, S. K., and Böhner, J.: Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia, Ecol. Model., 221, 1221–1229, 2010.
Steiniger, S. and Bocher, E.: An overview on current free and open source desktop GIS developments, Int. J. Geogr. Inf. Sci., 23, 1345–1370, https://doi.org/10.1080/13658810802634956, 2009.
Stötter, J. and Sailer, R.: Permafrost in Südtirol, Innsbrucker Geographische Studien, 2012.
Stroustrup, B.: Programming: principles and practice using C++, Pearson Education, 2014.
Sun, Z.: MicroCity – A Spatial Analysis and Simulation Framework, available at: http://microcity.sourceforge.net/, 2015.
Vanselow, K. and Samimi, C.: GIS und statistische Modelle im Weidemanagement: Ein Beispiel anhand der Hochgebirgsweiden im Ostpamir (Tadschikistan), Angewandte Geoinformatik, 23, 625–634, 2011.
Varga, K., Becht, M., and Damm, B.: Ansätze der GIS-gestützten räumlichen Modellierung von Rutschgefahren in Buntsandsteingebieten Nordhessens und Südniedersachsens (BRD), in: Angewandte Geoinformatik, edited by: Strobl, J., Blaschke, T., and Griesebner, G., Beiträge zum 21. AGIT-Symposium, Salzburg, 679–684, 2006.
Wang, Y., Herzschuh, U., Shumilovskikh, L. S., Mischke, S., Birks, H. J. B., Wischnewski, J., Böhner, J., Schlütz, F., Lehmkuhl, F., Diekmann, B., Wünnemann, B., and Zhang, C.: Quantitative reconstruction of precipitation changes on the NE Tibetan Plateau since the Last Glacial Maximum – extending the concept of pollen source area to pollen-based climate reconstructions from large lakes, Clim. Past, 10, 21–39, https://doi.org/10.5194/cp-10-21-2014, 2014.
Wehberg, J., Bock, M., Weinzierl, T., Conrad, O., Böhner, J., Stellmes, M., and Landschreiber, L.: Terrain-based Landscape Structure Classification in Relation to Remote Sensing Products and Soil Data for the Okavango Catchment, Biodivers. Ecol., 5, 221–233, 2013.
Weinzierl, T., Conrad, O., Böhner, J., and Wehberg, J.: Regionalization of baseline climatologies and time series for the Okavango Catchment, Biodivers. Ecol., 5, 235–245, 2013.
Wichmann, V.: Modellierung geomorphologischer Prozesse in einem alpinen Einzugsgebiet – Abgrenzung und Klassifizierung der Wirkungsräume von Sturzprozessen und Muren mit einem GIS, Eichstätt. Geogr. Arb., 15, 231 pp., 2006.
Wichmann, V. and Becht, M.: Spatial modelling of debris flows in an alpine drainage basin, IAHS-AISH P., 288, 370–376, 2004.
Wichmann, V. and Becht, M.: Modelling Of Geomorphic Processes In An Alpine Catchment, GeoDynamics, 151–167, 2005.
Wichmann, V. and Becht, M.: Modelling Of Geomorphic Processes In An Alpine Catchment, in: Geodynamics, edited by: Atkinson, P. M., Foody, G. M., Darby, S. E., and Wu, F., CRC Press, Boca Raton, 151–167, 2005.
Wichmann, V., Rutzinger, M., and Vetter, M.: Digital Terrain Model Generation from airborne Laser Scanning Point Data and the Effect of grid-cell size on the Simulation Results of a Debris Flow Model, in: Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie (SAGA – Seconds Out), Hamburger Beiträge Zur Physischen Geographie Und Landschaftsökologie, edited by: Böhner, J., Blaschke, T., and Montanarella, L., Univ. Hamburg, Inst. für Geographie, 103–113, 2008.
Willer, J., Baritz, R., Eberhardt, E., Milbert, G., and Jahn, R.: Projekt SIAM – Entwicklung eines Boden-Landschaftsmodells zur Datenharmonisierung und Qualitätssicherung für Bodenübersichtskarten, available at: http://eprints.dbges.de/477/ (last access: 13 February 2013), 2009.
Wilson, J. P. and Gallant, J. C.: Terrain analysis: principles and applications. John Wiley & Sons, 2000.
Wischmeier, W. H. and Smith, D. D.: Predicting rainfall erosion losses-a guide to conservation planning, Agriculture Handbook, 537 pp., 1978.
Short summary
The System for Automated Geoscientific Analyses (SAGA) is a comprehensive and globally established open source geographic information system (GIS) for scientific analysis and modeling. The current version 2.1.4 offers more than 700 tools that represent the broad scopes of SAGA in numerous fields of geoscientific endeavor. In this paper, we inform about the system’s architecture and functionality and highlight the wide spectrum of scientific applications of SAGA in a review of published studies.
The System for Automated Geoscientific Analyses (SAGA) is a comprehensive and globally...
