2017

1. [Craig et al. 2017] Abstract. OASIS is coupling software developed primarily for use in the climate community. It provides the ability to couple different models with low implementation and performance overhead. OASIS3-MCT is the latest version of OASIS. It includes several improvements compared to OASIS3, including elimination of a separate hub coupler process, parallelization of the coupling communication and run-time grid interpolation, and the ability to easily reuse mapping weight files. OASIS3-MCT3.0 is the latest release and includes the ability to couple between components running sequentially on the same set of tasks as well as to couple within a single component between different grids or decompositions such as physics, dynamics, and I/O. OASIS3-MCT has been tested with different configurations on up to 32 000 processes, with components running on high-resolution grids with up to 1.5 million grid cells, and with over 10 000 2-D coupling fields. Several new features will be available in OASIS3-MCT-4.0, and some of those are also described.
   oasis in MPIESM

2. [Escribano and Lazaro-Touza 2022] Abstract. La dimensión geopolítica de la transición entre un régimen energético fósil y otro renovable viene recibiendo una atención académica y política creciente. Una forma de explorar las implicaciones geopolíticas de las renovables es mediante el estudio de casos en contextos tan diferentes como América Latina y el Mediterráneo, pero las dos relevantes para España. El artículo explora tres aspectos de la compleja interacción entre geopolítica y energías renovables en ambas regiones: los flujos transfronterizos de hidroelectricidad, los de otras renovables modernas, y el potencial del hidrógeno verde. Compone así un conjunto de seis historias sobre la hidroelectricidad en el Nilo y el Paraná, los intercambios eléctricos renovables México-Estados Unidos y la inexistencia de los euromediterráneos, así como el potencial del hidrógeno verde en Chile y Marruecos.
   Geopolítica, renovables

3. [Fernández-Montes et al. 2017] Abstract. Precipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonal temperature (T) and precipitation (P) across the Iberian Peninsula (IP) using regional cli- mate paleosimulations for the period 1001–1990, driven by reconstructions of external forcings. Future climate (1990–2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships. In winter, positive P-T correlations dominate west-central IP (Pearson correlation coefficient ρ = +0.43, for 1001–1990), due to prevalent cold-dry and warm-wet conditions, while this relationship weakens and become negative towards mountainous, northern and eastern regions. In autumn, negative correlations appear in similar regions as in winter, whereas for summer they extend also to the N/NW of the IP. In spring, the whole IP depicts significant negative correlations, strongest for eastern regions (ρ = − 0.51). This is due to prevalent frequency of warm-dry and cold-wet modes in these regions and seasons. At the temporal scale, regional correlation series be- tween seasonal anomalies of temperature and precipitation (assessed in 31 years running windows in 1001– 1990) show very large multidecadal variability. For winter and spring, periodicities of about 50–60 years arise. The frequency of warm-dry and cold-wet modes appears correlated with the North Atlantic Oscillation (NAO), explaining mainly co-variability changes in spring. For winter and some regions in autumn, maximum and min- imum P-T correlations appear in periods with enhanced meridional or easterly circulation (low or high pressure anomalies in the Mediterranean and Europe). In spring and summer, the Atlantic Multidecadal Oscillation shows some fingerprint on the frequency of warm/cold modes. For future scenarios, an intensification of the negative P-T relationship is generally found, as a result of an in- creased frequency of the warm-dry mode.
   Paleo regional simulations

4. [] ABSTRACT: We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2 ). We included monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970–2000, using data from between 9000 and 60 000 weather stations. Weather station data were interpolated using thin-plate splines with covariates including elevation, distance to the coast and three satellite-derived covariates: maximum and minimum land surface temperature as well as cloud cover, obtained with the MODIS satellite platform. Interpolation was done for 23 regions of varying size depending on station density. Satellite data improved prediction accuracy for temperature variables 5–15% (0.07–0.17 C), particularly for areas with a low station density, although prediction error remained high in such regions for all climate variables. Contributions of satellite covariates were mostly negligible for the other variables, although their importance varied by region. In contrast to the common approach to use a single model formulation for the entire world, we constructed the final product by selecting the best performing model for each region and variable. Global cross-validation correlations were ≥ 0.99 for temperature and humidity, 0.86 for precipitation and 0.76 for wind speed. The fact that most of our climate surface estimates were only marginally improved by use of satellite covariates highlights the importance having a dense, high-quality network of climate station data.
   Surface climate dataset

5. [Gao et al. 2017] Abstract. The Paris Agreement proposed to keep the increase in global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels. It was thus the first international treaty to endow the 2 °C global temperature target with legal effect. The qualitative expression of the ultimate objective in Article 2 of the United Nations Framework Convention on Climate Change (UNFCCC) has now evolved into the numerical temperature rise target in Article 2 of the Paris Agreement. Starting with the Second Assessment Report (SAR) of the Intergovernmental Panel on Cli- mate Change (IPCC), an important task for subsequent assessments has been to provide scientific informa- tion to help determine the quantified long-term goal for UNFCCC negotiation. However, due to involvement in the value judgment within the scope of non-scientific assessment, the IPCC has never scientifically af- firmed the unacceptable extent of global temperature rise. The setting of the long-term goal for addressing climate change has been a long process, and the 2 °C global temperature target is the political consensus on the basis of scientific assessment. This article analyzes the evolution of the long-term global goal for addressing climate change and its impact on scientific assessment, negotiation processes, and global low- carbon development, from aspects of the origin of the target, the series of assessments carried out by the IPCC focusing on Article 2 of the UNFCCC, and the promotion of the global temperature goal at the political level.
   History of the 2C agreement

6. [González-Aparicio et al. 2017] Abstract. The growing share of electricity production from solar and mainly wind resources constantly increases the stochastic nature of the power system. Modelling the high share of renewable energy sources – and in particular wind power – crucially depends on the adequate representation of the intermittency and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these con- version methods is the selection of the spatial resolution. Although numerical weather prediction models can simulate wind speeds at higher spatial resolution (up to 1 1 km) than a reanalysis (generally, rang- ing from about 25 km to 70 km), they require high computational resources and massive storage sys- tems: therefore, the most common alternative is to use the reanalysis data. However, local wind features could not be captured by the use of a reanalysis technique and could be translated into misin- terpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bid- ding strategies for the electricity market. This study contributes to the understanding what is captured by different wind speeds spatial resolution datasets, the importance of using high resolution data for the conversion into power and the implications in power system analyses. It is proposed a methodology to increase the spatial resolution from a reanalysis. This study presents an open access renewable genera- tion time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geo- graphical aggregation levels (country, bidding zone and administrative territorial unit), for a 30 year period taking into account the wind generating fleet at the end of 2015.
   downscaling of wind

7. [Jungclaus et al. 2017] The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercompari- son Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the re- sponse to (mainly) natural forcing under background condi- tions not too different from today, and to discriminate be- tween forced and internally generated variability on interan- nual to centennial timescales. This paper describes the mo- tivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents or- bital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 ex- periments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simu- lations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Addi- tional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simula- tions. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instru- mental data).
   Forcings pmip4

8. [Knutti et al. 2017] Equilibrium climate sensitivity characterizes the Earth’s long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the ‘likely’ range for climate sensitivity of 1.5 C to 4.5 C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.
   Climate sensitivity

9. [Moreno-Chamarro et al. 2017] Abstract We assess the use of the meridional thermal- wind transport estimated from zonal density gradients to reconstruct the oceanic circulation variability during the last millennium in a forced simulation with the ECHO- G coupled climate model. Following a perfect-model approach, model-based pseudo-reconstructions of the Atlantic meridional overturning circulation (AMOC) and the Florida Current volume transport (FCT) are evaluated against their true simulated variability. The pseudo-FCT is additionally veri ed as proxy for AMOC strength and compared with the available proxy-based reconstruction. The thermal-wind component reproduces most of the simu- lated AMOC variability, which is mostly driven by inter- nal climate dynamics during the preindustrial period and by increasing greenhouse gases afterwards. The pseudo- reconstructed FCT reproduces well the simulated FCT and reasonably well the variability of the AMOC strength, including the response to external forcing. The pseudo- reconstructed FCT, however, the simulated variability at deep/shallow levels. Density changes responsible for the pseudo-reconstructed FCT are mainly driven by zonal temperature differences; salinity differences oppose but play a minor role. These results thus support the use of the thermal-wind relationship to recon- structtheoceaniccirculationpastvariability,inparticular at multidecadal timescales. Yet model-data comparison highlights important differences between the simulated and the proxy-based FCT variability. ECHO-G simulates a prominent weakening in the North Atlantic circulation that contrasts with the reconstructed enhancement. Our model results thus do not support the reconstructed FC minimum during the Little Ice Age. This points to a failure in the reconstruction, misrepresented processes in the model, or an important role of internal ocean dynamics.
   Ocean circulation, pseudoreality

10. [Matthes et al. 2017] Abstract: This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with re- spect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spec- tral irradiance (SSI), and the F10.7 index as well as parti- cle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, elec- trons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and June 2017 future (2015–2300) simulations. For the preindustrial con- trol simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder- minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.
    Solar forcing, cmip6

11. [REN21 2017] The 2017 edition of the REN21 Renewables Global Status Report (GSR) reveals a global energy transition well under way, with record new additions of installed renewable energy capacity, rapidly falling costs, particularly for solar PV and wind power, and the decoupling of economic growth and energy-related carbon dioxide emissions for the third year running. Innovative and more sustainable ways of meeting our energy needs are accelerating the paradigm shift away from a world run on fossil fuels. Despite these positive trends, the pace of the transition is not on track to achieve the goals established in the Paris Agreement to keep global temperature rise well below 2 degrees Celsius. So how can we speed up the energy transition with renewables? It is clear that policy is essential. Policy support for renewables in 2016, as in past years, focused mostly on power generation, whereas policies for the heating and cooling and transport sectors have remained virtually stagnant. This has to change. A systems approach is also needed across all sectors. There is a need to broaden the definition of a renewables-based energy system to one that moves beyond the traditional, narrow construct of renewable energy sources to one that looks at the role of supporting infrastructure, supply and demand balancing measures, e iciency measures and sector coupling, as well as a wide range of enabling technologies. The systems approach should become the norm in energy and infrastructure planning, financing and policy development...
    wind power

12. [Sanz Rodrigo et al. 2017b] Abstract: The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.
    Meso-micro

13. [Sanz Rodrigo et al. 2017a] Abstract. The GEWEX Atmospheric Boundary Layer Studies (GABLS) 1, 2 and 3 are used to develop a methodology for the design and testing of Reynolds-averaged Navier–Stokes (RANS) atmospheric boundary layer (ABL) models for wind energy applications. The first two GABLS cases are based on idealized boundary conditions and are suitable for verification purposes by comparing with results from higher-fidelity models based on large-eddy simulation. Results from three single-column RANS models, of 1st, 1.5th and 2nd turbulence closure order, show high consistency in predicting the mean flow. The third GABLS case is suitable for the study of these ABL models under realistic forcing such that validation versus observations from the Cabauw meteorological tower are possible. The case consists on a diurnal cycle that leads to a nocturnal low-level jet and addresses fundamental questions related to the definition of the large-scale forcing, the interaction of the ABL with the surface and the evaluation of model results with observations. The simulations are evaluated in terms of surface-layer fluxes and wind energy quantities of interest: rotor equivalent wind speed, hub-height wind direction, wind speed shear and wind direction veer. The characterization of mesoscale forcing is based on spatially and temporally averaged momentum budget terms from Weather Research and Forecasting (WRF) simulations. These mesoscale tendencies are used to drive single-column models, which were verified previously in the first two GABLS cases, to first demonstrate that they can produce similar wind profile characteristics to the WRF simulations even though the physics are more simplified. The added value of incorporating different forcing mechanisms into microscale models is quantified by systematically removing forcing terms in the momentum and heat equations. This mesoscale-to-microscale modeling approach is affected, to a large extent, by the input uncertainties of the mesoscale tendencies. Deviations from the profile observations are reduced by introducing observational nudging based on measurements that are typically available from wind energy campaigns. This allows the discussion of the added value of using remote sensing instruments versus tower measurements in the assessment of wind profiles for tall wind turbines reaching heights of 200 m.
    Advection and gradient terms

14. [Simpkins 2017] Progress in climate modelling Development and planning for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been years in the making. Nature Climate Change speaks to the Chair of the CMIP Panel, Veronika Eyring, about the aims and projected outcomes of the project.
    cmips

15. [Steiger and Smerdon 2017] Abstract. Because of the relatively brief observational record, the climate dynamics that drive multiyear to centennial hydroclimate variability are not adequately charac- terized and understood. Paleoclimate reconstructions based on data assimilation (DA) optimally fuse paleoclimate prox- ies with the dynamical constraints of climate models, thus providing a coherent dynamical picture of the past. DA is therefore an important new tool for elucidating the mecha- nisms of hydroclimate variability over the last several mil- lennia. But DA has so far remained untested for global hy- droclimate reconstructions. Here we explore whether or not DA can be used to skillfully reconstruct global hydroclimate variability along with the driving climate dynamics. Through a set of idealized pseudoproxy experiments, we find that an established DA reconstruction approach can in principle be used to reconstruct hydroclimate at both annual and sea- sonal timescales. We find that the skill of such reconstruc- tions is generally highest near the proxy sites. This set of re- construction experiments is specifically designed to estimate a realistic upper bound for the skill of this DA approach. Importantly, this experimental framework allows us to see where and for what variables the reconstruction approach may never achieve high skill. In particular for tree rings, we find that hydroclimate reconstructions depend critically on moisture-sensitive trees, while temperature reconstruc- tions depend critically on temperature-sensitive trees. Real- world DA-based reconstructions will therefore likely require a spatial mixture of temperature- and moisture-sensitive trees to reconstruct both temperature and hydroclimate variables. Additionally, we illustrate how DA can be used to elucidate the dynamical mechanisms of drought with two examples: tropical drivers of multiyear droughts in the North American Southwest and in equatorial East Africa. This work thus pro- vides a foundation for future DA-based hydroclimate recon- structions using real-proxy networks while also highlighting the utility of this important tool for hydroclimate research.
    Data Assimilation Hidroclimate

16. [Zhao et al. 2017] Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multi- method analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region- specific adaptation strategies to ensure food security for an increas- ing world population.
    food production