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Solar panels of utility scale are a rapidly growing contribution to the renewable energy supply with increasing efficiency and steeply reducing costs of photovoltaics (PV). Although there is consensus on long term reduction of greenhouse gas emissions and advantages of avoided emissions by using PV systems, there is need to understand the climatic effects of land surface modifications of such systems.We first review studies focusing on effects of utility-scale solar farms and compare their results in accordance to their characterization of a photovoltaic and the type of model used to evaluate effects. Then, we perform simulations of larger than current utility-scale solar farms but also comparatively small localized farms which are both characterized by modified land surface properties. These regions are either identified on the basis of solar insolation and desert-like criteria (low precipitation) or are proposed in existing studies for potential deployment of solar farms. The solar farm deployments are characterized by static or gradual changes in respective boundary conditions of albedo, soil roughness and outgoing longwave thermal properties. Separate experiments are conducted with non-dynamic and dynamic vegetation components to investigate potential feedbacks originating from the interplay of vegetation and precipitation. To this end, we use a comprehensive model (MPI-ESM-LR; Mauritsen et al., 2019), and the Earth System Model of Intermediate Complexity PlaSim (Fraedrich et al., 2005) to understand, and cross-validate, the effects in two models of different complexity model.We examine the results considering changes in radiative forces and surface energy budget and, therefore, the surface temperatures which can likely lead to atmospheric circulation patterns, precipitation and vegetation feedbacks. If lower complexity models provide results in an acceptable ballpark of comprehensive ESMs, then they could be further used for future quick compute simulations with various deployment scenarios and experimentation with variable technical aspects. Spatially explicit deployment of PV with focus on parameterized thermal properties dependent on the simulated climate would also allows us to look at the complementary effect of climate on panels and could help constrain the effect of different pathways on PV technology in the future.

At the current decarbonization rate, we are set on a path towards re-shaping a substantial share of land for carbon dioxide removal (CDR) over the following decades. However, existing Earth system models which could help to quantify the character of resulting CDR side effects and their consequences for the cumulative CO2 removal do not yet resolve dynamic CDR cover in space. Here, we embark on shedding light on this CDR uncertainty space, scrutinizing CDR impacts in spatial simulations with a comprehensive Earth system model. Assuming CDR to be driven by solar irradiation in the style of photovoltaics, our model is the first to simulate an idealized approach to land-based CDR with its physical, biospheric, and land use couplings on a grid box scale. We analyze dynamic CDR simulations for spatial deployment scenarios according to the country-wise burden of past CO2 emissions, to livelihood constraints, and to optimal irradiation conditions. Shared socio-economic pathways drive the overall global CDR use for a range of potential future emission scenarios. Aside from these spatio-temporal scenarios, the simulations also cover different ways of releasing excess energy from the solar-to-carbon conversion, permitting either local cooling through carbon storage, heat dissipation resulting from system losses or co-benefits for energy production. Based on simulation ensembles for the different scenarios, we quantify Earth system impacts of CDR and their consequences for CO2 removal if grid-scale feedbacks are properly resolved. With new spatially resolved CDR representations in Earth system models we will be able to test CDR-induced Earth system dynamics and CDR promises in greater detail than with existing globally forced projections. This spatially explicit modeling strategy could also open a way toward more comprehensive modeling strategies which include consequences for land use decisions on CDR.

Recent progress in modelling the Earth system has made it possible to produce transient climate simulations longer than 10.000 years with comprehensive ESMs. These simulations improve our understanding of slow climatic feedbacks, climate state transitions, and abrupt climate changes. However, assessing the quality and reliability of such paleoclimate simulations is particularly challenging due to the inherent characteristic differences between model data and the climate reconstructions used to validate them.Here, we present a collection of software packages for inter-model and model-data comparisons called Palaeo ToolBox (PTBox). Its first intent is to evaluate transient simulations of the PalMod project (deglaciation, glacial inception, MIS3) using several proxy data syntheses. Various variables are evaluated (including temperature, precipitation, oxygen isotopes, vegetation, carbon storages and fluxes), across a range of timescales (from decadal to multi-millenial). PTBox provides integrated model-data workflows, from data pre-processing to visualisations, organised into a series of (mostly R) packages. So far, PTBox includes 1) tools for pre-processing simulations and proxy data, 2) ensemble and pseudo-proxy methods to bridge the gap between simulations and proxies and to quantify uncertainties, 3) spectral methods to analyse timescale-dependent climate variability, and 4) newly developed metrics for spatio-temporal model-data comparisons.Finally, PTBox is accompanied by a website (http://palmodapp.cloud.dkrz.de/) with examples on how to use PTBox and interactive visualisations of the datasets produced in the PalMod project.

Without substantial decarbonization of the global economy, rising atmospheric carbon dioxide (CO2) levels are projected to lead to severe impacts on ecosystems and human livelihoods. Integrated assessments of economy and climate therefore favour large-scale CO2 removal to reach ambitious temperature-stabilization targets. However, most of the proposed approaches to artificially remove CO2 from the atmosphere are in conflict with planetary boundaries due to land-use needs and they may come with unintended climatic side-effects. Long-term draw-down of CO2 by photoelectrochemical (PEC) reduction is a recent and promising approach that potentially entails a very low water footprint and could offer a variety of carbon sink products for safe geological storage. For renewable hydrogen fuel production, PEC devices have already been demonstrated to deliver high solar-to-fuel efficiencies. If such devices are adjusted to deliver high solar-to-carbon efficiencies for carbon dioxide removal, they would require comparably little land for achieving annual sequestration rates that are compatible with limiting global warming to 2°C or below. Yet, no production-scale prototype exists and the climatic side-effects of such an "artificial photosynthesis'' approach for negative emissions are unknown. Here, we discuss our work towards investigating potential impacts of PEC CO2 removal on the climate and the carbon cycle in simulations with the comprehensive Earth System Model MPI-ESM. We designed a scheme to represent hypothetical PEC devices as a land surface type which is influencing land-atmosphere energy and moisture fluxes. We parameterize the irradiation-driven carbon sequestration of the devices and interactively couple their deployment area and location to a negative emission target. We plan to compare the potential side-effects between scenarios of dense, localized deployment and spread-out, decentralized application. These scenarios represent different guiding objectives for deploying hypothetical PEC systems such as maximizing the insolation per module area, or mitigating the overall impacts on climate and on carbon stocks. For the different scenarios, we intend to investigate changes in the surface balances, which could impact atmospheric circulations patterns. We further plan to quantify the amount of land-stored carbon that is relocated due to land-use change, as this affects the amount of CO2 that can effectively be withdrawn from the atmosphere. Finally, we relate theoretical expectations for area requirements and CO2 withdrawal with results from the coupled simulations which could inform the technological development. While ambitious emission reductions remain the only appropriate measure for stabilizing anthropogenic warming, our work could advance the understanding of possible benefits and side-effects of hypothetical PEC CO2 removal.M. M. May & K. Rehfeld, ESD Ideas: Photoelectrochemical carbon removal as negative emission technology. Earth Syst. Dynam. 10, 1–7 (2019).

Additional file 5: Contains supplementary Fig. S1–S5 and associated captions

Climate variability influences the probability of extreme events and is therefore of great importance for risk management. Nevertheless, changes in climate variability over time are far less studied than changes in the mean state of the climate system. Proxy records can be used to estimate the dependency of climate variability on the state and timescale, but their climate signal is perturbed by non-climatic processes and dating uncertainties. Analyzing ice cores and marine sediments, it was shown that temperature variability during the Last Glacial Maximum was larger than in the Holocene and that the magnitude of variability change depends on latitude.We estimate millennial and orbital scale variability in pollen records during the last Glacial. We draw on a global network of published pollen records, which are influenced by local temperature and moisture availability, and compare these estimates with temperature, precipitation, and vegetation variability in climate simulations of the last Glacial cycle. We discuss the regional consistency of timescale dependent estimates. Differences between Marine Isotope Stages 2, 3, and 4 are examined by comparing spatial patterns during those three periods. Then, we use spectral methods to study the scaling behavior of the pollen records. This provides additional information on the continuum of variability from centennial to orbital scales. Finally, we quantify the co-occurrence of millennial and orbital scale fluctuations across different pollen records with paleoclimate network techniques.Our work extends previous estimates to the terrestrial realm and to longer timescales. The results provide new insight on the climate variability differences between glacial and interglacial states, and on the mismatch between climate simulations and proxy data.

Globally consistent natural evidence on past climate evolution is indispensable for climate model evaluations and forecasts. However, it has rarely been investigated quantitatively whether large se...