ALBERT

Beschreibung: In order to evaluate whether the initialization of soil moisture has the potential to improve the prediction skill of earth system models (ESMs) on seasonal to decadal timescales, an elaborate experiment was conducted. For this task a coupled land–atmosphere model with prescribed ocean was utilized. The experiment design considered soil moisture initialization in different seasons and years and yielded information about the lifetime (memory) of extreme yet realistic soil moisture perturbations. Our analyses were focused on root zone soil moisture (RootSM) as it comprises the part of the soil that directly interacts with the atmosphere via bare-soil evaporation and transpiration. We found that RootSM memory differs not only spatially but also depends on the time of initialization. A long memory of up to 1 year is evident mostly for dry soil moisture regimes after heavy precipitation periods or prior to snow covered conditions. Short memory below 2 weeks prevails in wet soil moisture regimes and prior to distinct precipitation periods or snowmelt. Furthermore, RootSM perturbations affect other land surface states, e.g. soil temperature and leaf carbon content, and even induce anomalies with specific memory in these variables. Especially for deep-layer soil temperature, these anomalies can last for up to several years. As long as RootSM memory is evident, we found that anomalies occur periodically in other land surface states whenever climate conditions allow for interactions between that state and RootSM. Additionally, anomaly recurrence is visible for RootSM itself. This recurrence is related to the thickness of the soil layer below the root zone and can affect RootSM for several years. From our findings we conclude that soil moisture initialization has the potential to improve the predictive skill of climate models on seasonal scales and beyond. However, a sophisticated, multilayered soil hydrology scheme is necessary to allow for the interactions between RootSM and the deep-soil layer reservoir.

Beschreibung: In order to evaluate whether the initialization of soil moisture has the potential to improve the prediction skill of coupled climate models at seasonal to decadal time scales, an elaborated AMIP-type experiment was conducted. The experiment design considered soil moisture initialization in different seasons and years, and yields information about the life-time (memory) of extreme yet realistic soil moisture perturbations. Our analyses were focused on root zone soil moisture (RootSM) as it comprises the part of the soil that directly interacts with the atmosphere via bare soil evaporation and transpiration. We found that RootSM memory differs not only spatially but also depends on the time of initialization. Long memory up to one year is evident mostly for dry soil moisture regimes, after heavy precipitation periods or prior to snow covered conditions. Short memory below two weeks prevails in wet soil moisture regimes and prior to distinct precipitation periods or snow melt. Furthermore, RootSM perturbations affect other land surface states, e.g. soil temperature and leaf carbon content, and even induce anomalies with specific memory in these variables. Especially for deep layer soil temperature these anomalies can last up to several years. As long as RootSM memory is evident, we found that anomalies occur periodically in other land surface states whenever climate conditions allow for interactions between that state and RootSM. Additionally, anomaly recurrence is visible for RootSM itself. This recurrence is related to the thickness of the soil layer below the root zone and can affect RootSM for several years. From our findings we conclude that soil moisture initialization has the potential to improve the predictive skill of climate models on seasonal scales and beyond. However, a sophisticated, multi-layered soil hydrology scheme is necessary, to allow for the interactions between RootSM and the deep soil layer reservoir.

Beschreibung: The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

Beschreibung: The current version of JSBACH incorporates phenomena specific to high latitudes: freeze/thaw processes, coupling thermal and hydrological processes in a layered soil scheme, defining a multilayer snow representation and an insulating moss cover. Evaluations using comprehensive Arctic data sets show comparable results at the site, basin, continental and circumarctic scales. Such comparisons highlight the need to include processes relevant to high-latitude systems in order to capture the dynamics, and therefore realistically predict the evolution of this climatically critical biome.

Beschreibung: Droughts can have an impact on forest functioning and production, and even lead to tree mortality. However, drought is an elusive phenomenon that is difficult to quantify and define universally. In this study, we assessed the performance of a set of indicators that have been used to describe drought conditions in the summer months (June, July, August) over a 30-year period (1981–2010) in Finland. Those indicators include the Standardized Precipitation Index (SPI), the Standardized Precipitation–Evapotranspiration Index (SPEI), the Soil Moisture Index (SMI), and the Soil Moisture Anomaly (SMA). Herein, regional soil moisture was produced by the land surface model JSBACH of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM). Results show that the buffering effect of soil moisture and the associated soil moisture memory can impact on the onset and duration of drought as indicated by the SMI and SMA, while the SPI and SPEI are directly controlled by meteorological conditions. In particular, we investigated whether the SMI, SMA and SPEI are able to indicate the Extreme Drought affecting Forest health (EDF), which we defined according to the extreme drought that caused severe forest damages in Finland in 2006. The EDF thresholds for the aforementioned indicators are suggested, based on the reported statistics of forest damages in Finland in 2006. SMI was found to be the best indicator in capturing the spatial extent of forest damage induced by the extreme drought in 2006. In addition, through the application of the EDF thresholds over the summer months of the 30-year study period, the SPEI and SMA tended to show more frequent EDF events and a higher fraction of influenced area than SMI. This is because the SPEI and SMA are standardized indicators that show the degree of anomalies from statistical means over the aggregation period of climate conditions and soil moisture, respectively. However, in boreal forests in Finland, the high initial soil moisture or existence of peat often prevent the EDFs indicated by the SPEI and SMA to produce very low soil moisture that could be indicated as EDFs by the SMI. Therefore, we consider SMI is more appropriate for indicating EDFs in boreal forests. The selected EDF thresholds for those indicators could be calibrated when there are more forest health observation data available. Furthermore, in the context of future climate scenarios, assessments of EDF risks in northern areas should, in addition to climate data, rely on a land surface model capable of reliable prediction of soil moisture.

Beschreibung: In this study we present the development of the dynamical wetland extent scheme (DWES) and evaluate its skill to represent the global wetland distribution. The DWES is a simple, global scale hydrological scheme that solves the water balance of wetlands and estimates their extent dynamically. The extent depends on the balance of water flows in the wetlands and the slope distribution within the grid cells. In contrast to most models, the DWES is not directly calibrated against wetland extent observations. Instead, wetland affected river discharge data are used to optimise global parameters of the model. The DWES is not a complete hydrological model by itself but implemented into the Max Planck Institute – Hydrology Model (MPI-HM). However, it can be transferred into other models as well. For present climate, the model evaluation reveals a good agreement for the spatial distribution of simulated wetlands compared to different observations on the global scale. The best results are achieved for the Northern Hemisphere where not only the wetland distribution pattern but also their extent is simulated reasonably well by the DWES. However, the wetland fraction in the tropical parts of South America and Central Africa is strongly overestimated. The simulated extent dynamics correlate well with monthly inundation variations obtained from satellites for most locations. Also, the simulated river discharge is affected by wetlands resulting in a delay and mitigation of peak flows. Compared to simulations without wetlands, we find locally increased evaporation and decreased river flow into the oceans due to the implemented wetland processes. In summary, the evaluation demonstrates the DWES' ability to simulate the distribution of wetlands and their seasonal variations for most regions. Thus, the DWES can provide hydrological boundary conditions for wetland related studies. In future applications, the DWES may be implemented into an Earth system model to study feedbacks between wetlands and climate.

Beschreibung: It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However the improvements to the statistical properties of the data are limited to the specific time scale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made of persistence of the bias over the largest timescales. We examine the effects of mixing fluctuations on different time scales and suggest an improved statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.

Beschreibung: In this study we present the development of the dynamical wetland extent scheme (DWES) and its validation against present day wetland observations. The DWES is a simple, global scale hydrological scheme that solves the water balance of wetlands and estimates their extent dynamically. The extent depends on the balance of water flows in the wetlands and the slope distribution within the grid cells. In contrast to most models, the DWES is not directly calibrated against wetland extent observations. Instead, wetland affected river discharge data are used to optimize global parameters of the model. The DWES is not a complete hydrological model by itself but implemented into the Max Planck Institute – Hydrology Model (MPI-HM). However, it can be transferred into other models as well. For present climate, the model validation reveals a good agreement between the occurrence of simulated and observed wetlands on the global scale. The best result is achieved for the northern hemisphere where not only the wetland distribution pattern but also their extent is simulated reasonably well by the DWES. However, the wetland fraction in the tropical parts of South America and Central Africa is strongly overestimated. The simulated extent dynamics correlate well with monthly inundation variations obtained from satellite for most locations. Also, the simulated river discharge is affected by wetlands resulting in a delay and mitigation of peak flows. Compared to simulations without wetlands, we find locally increased evaporation and decreased river flow into the oceans due to the implemented wetland processes. In summary, the validation analysis demonstrates the DWES' ability to simulate the global distribution of wetlands and their seasonal variations. Thus, the dynamical wetland extent scheme can provide hydrological boundary conditions for wetland related studies. In future applications, the DWES should be implemented into an earth system model to study feedbacks between wetlands and climate.

Beschreibung: We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2-D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.

Beschreibung: An adapted Earth system model is used to investigate the limitations that future climate and water availability impose on the potential expansion and productivity of croplands. The model maximises the cropland area under prevailing climate conditions and accounts for an optimized, sustainable irrigation practice, thus allowing to consider the two-way feedback between climate and agriculture. We show that the total cropland area could be extended substantially throughout the 21st century, especially in South America and sub-Saharan Africa, where the rising water demand resulting from increasing temperatures can largely be met by increasing precipitation and irrigation rates. When accounting for the CO2 fertilization effect, only few agricultural areas have to be abandoned, while increasing temperatures allow to expand croplands even into high northern latitudes. Without the CO2 fertilization effect there is no increase in the overall cropland fraction during the second half of the century but areal losses in increasingly water-stressed regions can be compensated by an expansion in regions, previously too cold. However, global yields are more sensitive and, without the benefits of CO2 fertilization, they may decrease when green house gas concentrations exceed the RCP4.5 scenario. For certain regions the situation is even more concerning and guaranteeing food security in dry areas in Northern Africa, the Middle East and South Asia will become increasingly difficult, even under the most optimistic assumptions.