Max Planck Institute For Meteorology Research Articles

Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2

Abstract. We assess the land surface model JSBACHv4 (Jena Scheme for Biosphere Atmosphere Coupling in Hamburg version 4), which was recently developed at the Max Planck Institute for Meteorology as part of the effort to build the new Icosahedral Nonhydrostatic (ICON) Earth system model (ESM), ICON-ESM. We assess JSBACHv4 in simulations coupled with ICON-A, the atmosphere model of ICON-ESM, hosting JSBACHv4 as land component to provide the surface boundary conditions. The assessment is based on a comparison of simulated albedo, land surface temperature (LST), leaf area index (LAI), terrestrial water storage (TWS), fraction of absorbed photosynthetic active radiation (FAPAR), net primary production (NPP), and water use efficiency (WUE) with corresponding observational data. JSBACHv4 is the successor of JSBACHv3; therefore, another purpose of this study is to document how this step in model development has changed model biases. This is achieved by also assessing, in parallel, the results of coupled land–atmosphere simulations with the preceding model ECHAM6 hosting JSBACHv3. Large albedo biases appear in both models over ice sheets and in central Asia. The temperate to boreal warm bias observed in simulations with JSBACHv3 largely remained in JSBACHv4, despite the very good agreement with observed LST in the global mean. For the assessment of changes in land water storage, a novel procedure is suggested to compare the gravitational data from the Gravity Recovery And Climate Experiment (GRACE) satellites to simulated TWS. It turns out that the agreement of the changes in the seasonal cycle of TWS is sensitive to the representation of precipitation in the atmosphere model. The LAI is generally too high, which is partly caused by too high soil moisture and also by the parameterization of the phenology itself. The pattern of WUE is, for both models, largely as observed. In India, WUE is too high, probably because JSBACH does not incorporate irrigation in our simulations. WUE differences between the two models can be traced back to differences in precipitation patterns in the two coupled land–atmosphere simulations. For both models, most NPP biases can be associated with biases in water stress, LAI, and FAPAR. In particular, the NPP bias of the Eurasian steppes has switched from positive in JSBACHv3 to negative in JSBACHv4. This difference is mainly caused by weaker precipitation and lower FAPAR of ICON-A–JSBACHv4 in July, which is most probably caused by a feedback loop between too little soil moisture, evaporation, and clouds. While the size and patterns of biases in albedo and LST are largely similar between the two model versions, they are less well correlated for precipitation- and vegetation-related variables like FAPAR. Overall, the biases found in the different assessment variables are either already known from the previous implementation in the Max Planck Institute Earth System Model (MPI-ESM) or have changed because of the coupling with the new atmospheric component ICON-A. Accordingly, this study demonstrates the technically successful completion of the re-implementation of JSBACH into ICON-ESM-V1. As discussed, there is a good perspective on mitigating the biases by an improved representation of the processes.

ICON‐O: The Ocean Component of the ICON Earth System Model—Global Simulation Characteristics and Local Telescoping Capability

AbstractWe describe the ocean general circulation model Icosahedral Nonhydrostatic Weather and Climate Model (ICON‐O) of the Max Planck Institute for Meteorology, which forms the ocean‐sea ice component of the Earth system model ICON‐ESM. ICON‐O relies on innovative structure‐preserving finite volume numerics. We demonstrate the fundamental ability of ICON‐O to simulate key features of global ocean dynamics at both uniform and non‐uniform resolution. Two experiments are analyzed and compared with observations, one with a nearly uniform and eddy‐rich resolution of ∼10 km and another with a telescoping configuration whose resolution varies smoothly from globally ∼80 to ∼10 km in a focal region in the North Atlantic. Our results show first, that ICON‐O on the nearly uniform grid simulates an ocean circulation that compares well with observations and second, that ICON‐O in its telescope configuration is capable of reproducing the dynamics in the focal region over decadal time scales at a fraction of the computational cost of the uniform‐grid simulation. The telescopic technique offers an alternative to the established regionalization approaches. It can be used either to resolve local circulation more accurately or to represent local scales that cannot be simulated globally while remaining within a global modeling framework.

HydroPy (v1.0): a new global hydrology model written in Python

Abstract. Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can – at least to some extent – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy.

Holocene vegetation transitions and their climatic drivers in MPI-ESM1.2

Abstract. We present a transient simulation of global vegetation and climate patterns of the mid- and late Holocene using the MPI-ESM (Max Planck Institute for Meteorology Earth System Model) at T63 resolution. The simulated vegetation trend is discussed in the context of the simulated Holocene climate change. Our model captures the main trends found in reconstructions. Most prominent are the southward retreat of the northern treeline that is combined with the strong decrease of forest in the high northern latitudes during the Holocene and the vast increase of the Saharan desert, embedded in a general decrease in precipitation and vegetation in the Northern Hemisphere monsoon margin regions. The Southern Hemisphere experiences weaker changes in total vegetation cover during the last 8000 years. However, the monsoon-related increase in precipitation and the insolation-induced cooling of the winter climate lead to shifts in the vegetation composition, mainly between the woody plant functional types (PFTs). The large-scale global patterns of vegetation almost linearly follow the subtle, approximately linear, orbital forcing. In some regions, however, non-linear, more rapid changes in vegetation are found in the simulation. The most striking region is the Sahel–Sahara domain with rapid vegetation transitions to a rather desertic state, despite a gradual insolation forcing. Rapid shifts in the simulated vegetation also occur in the high northern latitudes, in South Asia and in the monsoon margins of the Southern Hemisphere. These rapid changes are mainly triggered by changes in the winter temperatures, which go into, or move out of, the bioclimatic tolerance range of individual PFTs. The dynamics of the transitions are determined by dynamics of the net primary production (NPP) and the competition between PFTs. These changes mainly occur on timescales of centuries. More rapid changes in PFTs that occur within a few decades are mainly associated with the timescales of mortality and the bioclimatic thresholds implicit in the dynamic vegetation model, which have to be interpreted with caution. Most of the simulated Holocene vegetation changes outside the high northern latitudes are associated with modifications in the intensity of the global summer monsoon dynamics that also affect the circulation in the extra tropics via teleconnections. Based on our simulations, we thus identify the global monsoons as the key player in Holocene climate and vegetation change.

Ocean Model Formulation Influences Transient Climate Response

AbstractThe transient climate response (TCR) is 20% higher in the Alfred Wegener Institute Climate Model (AWI‐CM) compared to the Max Planck Institute Earth System Model (MPI‐ESM) whereas the equilibrium climate sensitivity (ECS) is by up to 10% higher in AWI‐CM. These results are largely independent of the two considered model resolutions for each model. The two coupled CMIP6 models share the same atmosphere‐land component ECHAM6.3 developed at the Max Planck Institute for Meteorology (MPI‐M). However, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice‐ocean model developed at MPI‐M and the FESOM sea ice‐ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is related to ocean heat uptake in response to greenhouse gas forcing. Specifically, AWI‐CM simulations show stronger surface heating than MPI‐ESM simulations while the latter accumulate more heat in the deeper ocean. The vertically integrated ocean heat content is increasing slower in AWI‐CM model configurations compared to MPI‐ESM model configurations in the high latitudes. Weaker vertical mixing in AWI‐CM model configurations compared to MPI‐ESM model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell and Ross Gyres and the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI‐CM model configurations and the presence of a warming hole in MPI‐ESM model configurations. All these differences occur largely independent of the considered model resolutions.

The German Climate Forecast System: GCFS

AbstractSeasonal prediction is one important element in a seamless prediction chain between weather forecasts and climate projections. After several years of development in collaboration with Universität Hamburg and Max Planck Institute for Meteorology, the Deutscher Wetterdienst performs operational seasonal forecasts since 2016 with the German Climate Forecast System, now in Version 2 (GCFS2.0). Here, the configuration of the previous system GCFS1.0 and the current GCFS2.0 are described and the performance of the two systems is compared over the common hindcast period of 1990–2014. In GCFS2.0, the forecast skill is improved compared to GCFS1.0 during boreal winter, especially for the Northern Hemisphere where the Pearson correlation has increased for the North Atlantic Oscillation index. Overall, a similar performance of GCFS2.0 in comparison to GCFS1.0 is assessed during the boreal summer. Future developments for climate forecasts need a stronger focus on the performance of interannual variability in a model system.

Changes of air quality during the pandemic and airborne transmission issues.

The COVID-19 pandemic has killed more than 1 000 000 people within nine months in 2020. The world is changed as the cities were locked down, the traffic reduced, and people forced to work from home and keep social distance. These controlling measures also resulted in drastic reduction of the emission of many air pollutants, providing researchers an unprecedented large-scale natural experiment in examining how the air quality would respond to a strong forcing. In this panel discussion held on 22 September 2020, five experts gathered to discuss their observations and analyses, as well as the current understanding and misconception about airborne transmission.This Forum article is dedicated to Prof. Martin Williams of the Imperial College London, who intended to join the panel discussion but passed away one day before it. Guy Brasseur Professor of Max Planck Institute for Meteorology, Germany Junji Cao Professor of Institute of Earth Environment, Chinese Academy of Sciences, China Aijun Ding Dean and Professor of School of Atmospheric Sciences, Nanjing University, China Lidia Morawska Professor of Queensland University of Technology, Australia Tong Zhu (Chair) Dean and Professor of College of Environmental Sciences and Engineering, Peking University, China

Selection of the Optimum Global Circulation Model that Mimics the Circumstances of Egypt

Egyptian researchers in the field of climatic changes and their effects on various sectors, such as agriculture, water resources, health and social usually operate one of the Global Circulation Models (GCMs) and rely on its results. They considered its results as facts and real and they study the impact without reference to the uncertainty in their results. This is a major drawback to study the effect of climate changes on different sectors since there is a persuasive variation in the results of different models. Therefore, the impact analysis may result in building policies and develop alternatives in a way that is related to the real situation of the area under study. It has been found that the best global model or recycling models for the case of Egypt must be neutralized. It is an imperative component for building future policies to study the impact of climate change properly. The current study focuses on assessing the results of GCMs in Egypt. Previous reviews showed that there is no study to address this issue on Egypt. Thus, the following methodology was followed. Forty GCMs in Coupled Model Inter-comparing Project (CMIP5), are analyzed for the variable’s precipitation and temperature. These GCMs were Evaluated for Egypt for the climate variable precipitation rate through dividing the entire Egypt area to 110 cells each cell is square 100 km x 100 km. The precipitation and temperature were evaluated through applying five performance indicators. These indicators are listed as follow: i) coefficient of correlation (CoC) , ii) normalized root mean (NRMSE), absolute normalized mean bias error (ANMBE), average absolute relative error (AARE) and skill score (SS).The Payoff matrix (40 GCMs versus 5 indicators) is developed and then the entropy technique for determination of the performance indicators’ weights is applied. The Normalization technique was applied for each season out of 4 seasons that are winter, spring, summer and autumn on the performance indicators. These weights are applied to assist for ranking the 40 GCMs. The Ranking of these GCMs were obtained through a multi-criterion decision-making outranking method (PROMETHEE-2). Finally, it is proven that the “MPI-ESM-LR” GCM is found to be the best model for predicting the climate change parameters, (precipitation and temperature), all over Egypt compared to the other 39 models. The MPI-ESM-LR GCM model is developed by the Max Planck Institute for Meteorology in Germany. It is recommended that the results of climate change projects for Egypt up until year 2100 has to apply the output results of the GCM named MPI-ESM-LR rather than other GCMs as long as it gives the most proper results for climate change projection of Egypt.

Evaluating the GECCO3 1948–2018 ocean synthesis – a configuration for initializing the MPI‐ESM climate model

AbstractThe paper describes an update of the GECCO (German contribution to the Estimating the Circulation and Climate of the Ocean project) ocean synthesis, now in its version 3, and provides an evaluation of the results with assimilated and independent data. GECCO3 covers the 71‐year period 1948–2018 and differs from its predecessor by returning to a single assimilation window instead of partitioning the period in 5‐year‐long overlapping windows which was previously necessary to yield convergence. A solution to the convergence problem is presented. GECCO3 is intended to be used for the initialization of coupled climate models and is configured for the higher‐resolution version of the earth system model (MPI‐ESM) developed at the Max Planck Institute for Meteorology. It uses the bathymetry and grid of the MPI‐ESM with quasi‐uniform resolution of 0.4°, thereby providing the first global eddy‐permitting synthesis based on the adjoint method. The synthesis additionally features the estimation of various mixing parameters and can regionally choose between explicit or parametrized eddy fluxes. Except for the altimeter data in tropical regions, GECCO3 is in better agreement with the assimilated data than GECCO2. The improvements relative to the in situ data partly result from the much larger amount of Argo data, which show lower model–data differences. Global heat content changes are in good agreement with recent estimates, but show uptake almost exclusively in the top 700 m. An alternative version of GECCO3, created by starting from different first‐guess control parameters, was used to evaluate the uncertainty of the estimated parameters and state due to lack of convergence. This estimate suggests a large uncertainty related to the uptake of heat into the lower layers, while estimates of mean meridional transport of heat and freshwater are not affected.

The impact of future climate change on bean cultivation in the Prespa Lake catchment, northern Greece

Local impact projections for the Prespa Lake catchment (northern Greece) were generated using the regional climate model RCA4 of the Swedish Meteorological and Hydrological Institute, as driven by the global climate model MPI-ESM-LR of the Max Planck Institute for Meteorology under two RCP future emissions scenarios: RCP 4.5 (some mitigating measures applied) and RCP 8.5 (business as usual). These projections indicate that temperatures in this region will rise statistically significantly—by 1–3 °C (RCP 4.5) and 3–6 °C (RCP 8.5)—by the end of the century. Future wet season precipitation is not projected to change, but precipitation variability and maximum dry spell (P 16 °C during the seed stage (15/04–15/05) will increase, while days with maximum temperatures that fall within the optimum range (21 °C < Tmax < 26 °C) during the growth and blossoming stages (15/05–30/08) will decrease. Current irrigation methods using lake water will become more difficult to sustain in the future, as very low lake levels will become more frequent. Based on these simulations, we recommend that heat- and drought-resistant varieties of bean crops that do not require (much) irrigation should be prioritized and promoted for climate-proof agriculture. Sustainable irrigation methods, such as drip irrigation and the use of recycled wastewater, should be selected in the future. These recommendations will be integrated into local farming practice and policy recommendations for regional agricultural adaptation measures.

Climate-mode initialization for decadal climate predictions

In the context of decadal climate predictions, a climate-mode initialization method is being tested by which ocean ORAS4 reanalysis is projected onto dominant modes of variability of the Earth System Model from the Max Planck Institute for Meteorology (MPI-ESM). The method aims to improve the prediction skill of the model by filtering out dynamically unbalanced noise during the initialization step. Used climate modes are calculated as statistical 3-D modes based on the bivariate empirical orthogonal function (EOF) analysis applied to temperature and salinity anomalies from an ensemble of historical simulations from the MPI-ESM. The climate-mode initialization method shows improved surface temperature skill, particularly over the tropical Pacific Ocean at seasonal-to-interannual timescales associated with the improved zonal momentum balance. There, the new initialization somewhat outperforms the surface temperature skill of the anomaly initialization also for lead years 2–5. In other parts of the world ocean, both initialization methods currently are equivalent in skill. However, only 44% of variance in the original ORAS4 reconstruction remains after the projection on model modes, suggesting that the ORAS4 modes are not fully compatible with the model modes. Moreover, we cannot dismiss the possibility that model modes are not sufficiently sampled with the data set underlying the EOF analysis. The full potential of the climate-mode initialization method for future decadal prediction systems therefore still needs to be quantified based on improved modal representation.

The upper-atmosphere extension of the ICON general circulation model (version: ua-icon-1.0)

Abstract. How the upper-atmosphere branch of the circulation contributes to and interacts with the circulation of the middle and lower atmosphere is a research area with many open questions. Inertia–gravity waves, for instance, have moved in the focus of research as they are suspected to be key features in driving and shaping the circulation. Numerical atmospheric models are an important pillar for this research. We use the ICOsahedral Non-hydrostatic (ICON) general circulation model, which is a joint development of the Max Planck Institute for Meteorology (MPI-M) and the German Weather Service (DWD), and provides, e.g., local mass conservation, a flexible grid nesting option, and a non-hydrostatic dynamical core formulated on an icosahedral–triangular grid. We extended ICON to the upper atmosphere and present here the two main components of this new configuration named UA-ICON: an extension of the dynamical core from shallow- to deep-atmosphere dynamics and the implementation of an upper-atmosphere physics package. A series of idealized test cases and climatological simulations is performed in order to evaluate the upper-atmosphere extension of ICON.

Implementation of snow albedo schemes of varying complexity and their performances in offline Noah and Noah coupled with NCEP CFSv2

The representation of snow albedo in global models is recognized as one of the key sources of uncertainty in the simulation of mean and variability of climate. The Climate Forecast System version 2 (CFSv2), which is used for subseasonal-to-seasonal forecast of weather and climate, also suffers from large overestimation of surface albedo, particularly over the snow region. In order to improve the snow albedo biases, performances of three snow albedo schemes: the existing ‘maximum snow albedo’ (MSA) scheme of land surface model Noah, temperature dependent scheme of Roeckner et al. (The atmospheric general circulation model ECHAM5—part 1. Technical Report 349, Max Planck Institute for Meteorology, 2003) (RK03) and prognostic albedo scheme of Dutra et al. (J Hydrometeor 11:899–916, 2010) (DU10) are evaluated in offline mode. While offline Noah performs better with MSA scheme as compared to RK03 and DU10 in simulating climatological mean albedo, DU10 scheme shows a better skill in simulating monthly albedo and also captures the interannual variability with high fidelity. Therefore, MSA and DU10 schemes are also evaluated in coupled model along with the existing albedo scheme of Briegleb (J Geophys Res 97:7603–7612, 1992) (BR92) in CFSv2. The performance of MSA scheme is found to be better in simulating surface albedo, snow water equivalent and 2 m air temperature as compared to those using DU10 and BR92 schemes. Furthermore, the improved albedo have positive impact in the simulation of Indian summer monsoon rainfall, that reduces the dry bias over the Indian subcontinent, and cold bias in sea surface temperature and improves rainfall teleconnection. Thus, among four schemes (MSA, RK03, DU10 and BR92) evaluated here, MSA appears to be the most suitable snow albedo scheme for CFSv2.

Characterizing uncertainties in the ESA-CCI land cover map of the epoch 2010 and their impacts on MPI-ESM climate simulations

Limitations of mapping land surface properties and their conversion into climate model boundary conditions are major sources of uncertainty in climate simulations. In this paper, the range of the largest possible uncertainty in satellite-derived land cover (LC) map is estimated and its impact on climate simulations is quantified with the Earth System Model of the Max-Planck Institute for Meteorology utilizing prescribed sea surface temperature and sea ice. Two types of uncertainty in the LC map are addressed: (i) uncertainty due to classification algorithm of spectral reflectance into LC classes, and (ii) uncertainty due to conversion of LC classes into the climate model vegetation distribution. For forest cover, each of them is about the same order of magnitude as the uncertainty range in recent observations (∼± 700 Mha). Superposing two sources of uncertainty results in LC maps that feature the range of vegetation deviation that is about the same order of magnitude as the recent (since year 1700) forest loss due to agriculture (forest cover uncertainty range ∼± 1700 Mha). These uncertainties in vegetation distribution lead to noticeable variations in near-surface climate variables, local, regional, and global climate forcing. Temperature does not show significant uncertainty in global mean, but rather exhibits regional deviations with an opposite response to LC uncertainty that compensate each other in the global mean (e.g., albedo feedback controls temperature in boreal North America resulting in cooling (warming) with decrease (increase) of vegetation while evaporative cooling controls temperature in South America and sub-Saharan Africa resulting in cooling (warming) with increase (decrease) of vegetation). Large-scale circulation is also affected by the LC uncertainty, and consequently precipitation pattern as well. It is demonstrated that precipitation uncertainty in the monsoonal regions are about the same order of magnitude as in previous studies with idealized perturbations of vegetation. These findings indicate that the range of uncertainty in satellite-derived vegetation maps for climate models is about the same order of magnitude as the uncertainty in recent observations of forest cover or as the forest lost due to agriculture. Consequently, climate simulations have a similar range of uncertainty in variables representing near-surface climate as the observed climate change due to land use. Hence, more accurate methods are needed for mapping and converting LC properties into model vegetation in order to increase reliability of climate model simulations.

ICON‐A, The Atmosphere Component of the ICON Earth System Model: II. Model Evaluation

AbstractWe evaluate the new icosahedral nonhydrostatic atmospheric (ICON‐A) general circulation model of the Max Planck Institute for Meteorology that is flexible to be run at grid spacings from a few tens of meters to hundreds of kilometers. A simulation with ICON‐A at a low resolution (160 km) is compared to a not‐tuned fourfold higher‐resolution simulation (40 km). Simulations using the last release of the ECHAM climate model (ECHAM6.3) are also presented at two different resolutions. The ICON‐A simulations provide a compelling representation of the climate and its variability. The climate of the low‐resolution ICON‐A is even slightly better than that of ECHAM6.3. Improvements are obtained in aspects that are sensitive to the representation of orography, including the representation of cloud fields over eastern‐boundary currents, the latitudinal distribution of cloud top heights, and the spatial distribution of convection over the Indian Ocean and the Maritime Continent. Precipitation over land is enhanced, in particular at high‐resolution ICON‐A. The response of precipitation to El Niño sea surface temperature variability is close to observations, particularly over the eastern Indian Ocean. Some parameterization changes lead to improvements, for example, with respect to rain intensities and the representation of equatorial waves, but also imply a warmer troposphere, which we suggest leads to an unrealistic poleward mass shift. Many biases familiar to ECHAM6.3 are also evident in ICON‐A, namely, a too zonal SPCZ, an inadequate representation of north hemispheric blocking, and a relatively poor representation of tropical intraseasonal variability.

Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

Abstract. To improve the aeolian dust budget calculations with the global ECHAM/MESSy atmospheric chemistry–climate model (EMAC), which combines the Modular Earth Submodel System (MESSy) with the ECMWF/Hamburg (ECHAM) climate model developed at the Max Planck Institute for Meteorology in Hamburg based on a weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), we have implemented new input data and updates of the emission scheme. The data set comprises land cover classification, vegetation, clay fraction and topography. It is based on up-to-date observations, which are crucial to account for the rapid changes of deserts and semi-arid regions in recent decades. The new Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover and vegetation data are time dependent, and the effect of long-term trends and variability of the relevant parameters is therefore considered by the emission scheme. All input data have a spatial resolution of at least 0.1∘ compared to 1∘ in the previous version, equipping the model for high-resolution simulations. We validate the updates by comparing the aerosol optical depth (AOD) at 550 nm wavelength from a 1-year simulation at T106 (about 1.1∘) resolution with Aerosol Robotic Network (AERONET) and MODIS observations, the 10 µm dust AOD (DAOD) with Infrared Atmospheric Sounding Interferometer (IASI) retrievals, and dust concentration and deposition results with observations from the Aerosol Comparisons between Observations and Models (AeroCom) dust benchmark data set. The update significantly improves agreement with the observations and is therefore recommended to be used in future simulations.

Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4

In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010–2040, 2040–2070 and 2070–2100 with respect to the control period of 1970–2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070–2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain.

Climate, weather, space weather: model development in an operational context

Aspects of operational modeling for climate, weather, and space weather forecasts are contrasted, with a particular focus on the somewhat conflicting demands of “operational stability” versus “dynamic development” of the involved models. Some common key elements are identified, indicating potential for fruitful exchange across communities. Operational model development is compelling, driven by factors that broadly fall into four categories: model skill, basic physics, advances in computer architecture, and new aspects to be covered, from costumer needs over physics to observational data. Evaluation of model skill as part of the operational chain goes beyond an automated skill score. Permanent interaction between “pure research” and “operational forecast” people is beneficial to both sides. This includes joint model development projects, although ultimate responsibility for the operational code remains with the forecast provider. The pace of model development reflects operational lead times. The points are illustrated with selected examples, many of which reflect the author’s background and personal contacts, notably with the Swiss Weather Service and the Max Planck Institute for Meteorology, Hamburg, Germany. In view of current and future challenges, large collaborations covering a range of expertise are a must − within and across climate, weather, and space weather. To profit from and cope with the rapid progress of computer architectures, supercompute centers must form part of the team.

Uncertainties in modelling the climate impact of irrigation

Irrigation-based agriculture constitutes an essential factor for food security as well as fresh water resources and has a distinct impact on regional and global climate. Many issues related to irrigation’s climate impact are addressed in studies that apply a wide range of models. These involve substantial uncertainties related to differences in the model’s structure and its parametrizations on the one hand and the need for simplifying assumptions for the representation of irrigation on the other hand. To address these uncertainties, we used the Max Planck Institute for Meteorology’s Earth System model into which a simple irrigation scheme was implemented. In order to estimate possible uncertainties with regard to the model’s more general structure, we compared the climate impact of irrigation between three simulations that use different schemes for the land-surface–atmosphere coupling. Here, it can be shown that the choice of coupling scheme does not only affect the magnitude of possible impacts but even their direction. For example, when using a scheme that does not explicitly resolve spatial subgrid scale heterogeneity at the surface, irrigation reduces the atmospheric water content, even in heavily irrigated regions. Contrarily, in simulations that use a coupling scheme that resolves heterogeneity at the surface or even within the lowest layers of the atmosphere, irrigation increases the average atmospheric specific humidity. A second experiment targeted possible uncertainties related to the representation of irrigation characteristics. Here, in four simulations the irrigation effectiveness (controlled by the target soil moisture and the non-vegetated fraction of the grid box that receives irrigation) and the timing of delivery were varied. The second experiment shows that uncertainties related to the modelled irrigation characteristics, especially the irrigation effectiveness, are also substantial. In general the impact of irrigation on the state of the land surface is more than three times larger when assuming a low irrigation effectiveness than when a high effectiveness is assumed. For certain variables, such as the vertically integrated water vapour, the impact is almost an order of magnitude larger. The timing of irrigation also has non-negligible effects on the simulated climate impacts and it can strongly alter their seasonality.

Ocean Modeling on a Mesh With Resolution Following the Local Rossby Radius

AbstractWe discuss the performance of the Finite Element Ocean Model (FESOM) on locally eddy‐resolving global unstructured meshes. In particular, the utility of the mesh design approach whereby mesh horizontal resolution is varied as half the Rossby radius in most of the model domain is explored. Model simulations on such a mesh (FESOM‐XR) are compared with FESOM simulations on a smaller‐size mesh, where refinement depends only on the pattern of observed variability (FESOM‐HR). We also compare FESOM results to a simulation of the ocean model of the Max Planck Institute for Meteorology (MPIOM) on a tripolar regular grid with refinement toward the poles, which uses a number of degrees of freedom similar to FESOM‐XR. The mesh design strategy, which relies on the Rossby radius and/or the observed variability pattern, tends to coarsen the resolution in tropical and partly subtropical latitudes compared to the regular MPIOM grid. Excessive variations of mesh resolution are found to affect the performance in other nearby areas, presumably through dissipation that increases if resolution is coarsened. The largest improvement shown by FESOM‐XR is a reduction of the surface temperature bias in the so‐called North‐West corner of the North Atlantic Ocean where horizontal resolution was increased dramatically. However, other biases in FESOM‐XR remain largely unchanged compared to FESOM‐HR. We conclude that resolving the Rossby radius alone (with two points per Rossby radius) is insufficient, and that careful use of a priori information on eddy dynamics is required to exploit the full potential of ocean models on unstructured meshes.