Model-simulated hydroclimate in the East Asian summer monsoon region during past and future climate: a pilot study with a moisture source perspective

Here we present a pilot study of the sensitivity of summer monsoon precipitation in the Yangtze River Valley (YRV; 110–122∘ E and 27–33∘ N, eastern China) to climatic boundary conditions from the Last Glacial Maximum (LGM), pre-industrial conditions, and the Representative Concentration Pathway 6 emission scenario from two different climate models. Using a quantitative Lagrangian moisture source diagnostic based on backward trajectories, we are able to interpret changes in precipitation amount and seasonality in terms of processes at the source regions and during transport that contribute to YRV precipitation. Thereby, we gain insight into influential processes and characteristics related to precipitation variability and the sensitivity of the summer monsoon hydroclimate in East Asia to boundary-condition changes in models. Comparing 10-year time slices similar to present-day conditions from the NorESM1-M and CAM5.1 models to reanalysis data reveals overall similar moisture source regions, albeit with a tendency for a more local precipitation origin in the climate models. The general characteristics of the moisture sources and moisture transport in the YRV are relatively stable across different climate forcings, both concerning the mean location of source regions, transport distance, and the relative contributions of moisture from land and ocean areas. Changes regarding regional precipitation contributions from the East Asian continent indicate that precipitation recycling responds to different climate forcings. We interpret these findings such that models to first order respond with a scaling rather than reorganisation of the hydroclimate to climatic forcing, while land–atmosphere interactions play an important, but secondary, role. If the model simulations are accurate, the moisture source regions and thus the general processes of precipitation in the YRV could remain relatively stable across different climates. However, some differences in moisture source conditions are larger between the different climate models than between different climatic boundary conditions in the same model. It may therefore be possible that current climate models underestimate the potential for non-linear responses to changing boundary conditions, for example due to precipitation recycling. Although limited by the relatively short analysis period, our findings demonstrate that the diagnosis of moisture sources provides a useful additional perspective for understanding and quantifying precipitation mechanisms and the hydroclimate simulated by models and enables more detailed evaluation of model simulations, for example using paleoclimate records.publishedVersio

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are madeIn this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT=±0.03±0.05·AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer.Peer reviewe

Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2)

The ocean carbon cycle is a key player in the climate system through its role in regulating the atmospheric carbon dioxide concentration and other processes that alter the Earth's radiative balance. In the second version of the Norwegian Earth System Model (NorESM2), the oceanic carbon cycle component has gone through numerous updates that include, amongst others, improved process representations, increased interactions with the atmosphere, and additional new tracers. Oceanic dimethyl sulfide (DMS) is now prognostically simulated and its fluxes are directly coupled with the atmospheric component, leading to a direct feedback to the climate. Atmospheric nitrogen deposition and additional riverine inputs of other biogeochemical tracers have recently been included in the model. The implementation of new tracers such as “preformed” and “natural” tracers enables a separation of physical from biogeochemical drivers as well as of internal from external forcings and hence a better diagnostic of the simulated biogeochemical variability. Carbon isotope tracers have been implemented and will be relevant for studying long-term past climate changes. Here, we describe these new model implementations and present an evaluation of the model's performance in simulating the observed climatological states of water-column biogeochemistry and in simulating transient evolution over the historical period. Compared to its predecessor NorESM1, the new model's performance has improved considerably in many aspects. In the interior, the observed spatial patterns of nutrients, oxygen, and carbon chemistry are better reproduced, reducing the overall model biases. A new set of ecosystem parameters and improved mixed layer dynamics improve the representation of upper-ocean processes (biological production and air–sea CO2 fluxes) at seasonal timescale. Transient warming and air–sea CO2 fluxes over the historical period are also in good agreement with observation-based estimates. NorESM2 participates in the Coupled Model Intercomparison Project phase 6 (CMIP6) through DECK (Diagnostic, Evaluation and Characterization of Klima) and several endorsed MIP simulations.publishedVersio

The influence of remote aerosol forcing from industrialised economies on the future evolution of East and West African rainfall

Past changes in global industrial aerosol emissions have played a significant role in historical shifts in African rainfall and yet assessment of the impact on African rainfall of near term (10-40 year) potential aerosol emission pathways remains largely unexplored. Whilst existing literature links future aerosol declines to a northward shift of Sahel rainfall, existing climate projections rely on RCP scenarios that do not explore the range of air quality drivers. Here we present projections from two emission scenarios that better envelope the range of potential aerosol emissions. More aggressive emission cuts results in northward shifts of the tropical rain-bands whose signal can emerge from expected internal variability on short, 10-20 year, time horizons. We also show for the first time that this northward shift also impacts East Africa, with evidence of delays to both onset and withdrawal of the Short Rains. However, comparisons of rainfall impacts across models suggest that only certain aspects of both the West and East African model responses may be robust, given model uncertainties. This work motivates the need for wider exploration of air quality scenarios in the climate science community to assess the robustness of these projected changes and to provide evidence to underpin climate adaptation in Africa. In particular, revised estimates of emission impacts of legislated measures every 5-10 years would have a value in providing near term climate adaptation information for African stakeholders

Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models

Terrestrial isoprene, a biogenic volatile organic compound emitted by many plants, influences atmospheric chemistry and the Earth’s radiative balance. Elucidating its historical changes is therefore important for predicting climate change and air quality. Isoprene emissions can respond to climate (e.g., temperature, shortwave radiation, precipitation), land use and land cover change (LULCC), and atmospheric CO2 concentrations. However, historical trends of isoprene emissions and the relative influences of the respective drivers of those trends remain highly uncertain. This study addresses uncertainty in historical isoprene emission trends and their influential factors, particularly the roles of climate, LULCC, and atmospheric CO2 (via fertilization and inhibition effects). The findings are expected to reconcile discrepancies among different modelling approaches and to improve predictions of isoprene emissions and their climate change effects. To investigate isoprene emission trends, controlling factors, and discrepancies among models, we analyzed long-term (1850–2014) global isoprene emissions from online simulations of CMIP6 Earth System Models and offline simulations using the VISIT dynamic vegetation model driven by climate reanalysis data. Mean annual global present-day isoprene emissions agree well among models (434–510 TgC yr⁻¹) with a 5 % inter-model spread (24 TgC yr⁻¹), but regional emissions differ greatly (9–212 % spread). All models show an increasing trend in global isoprene emissions in recent decades (1980–2014), but their magnitudes vary (+1.27 ± 0.49 TgC yr⁻², 0.28 ± 0.11 % yr⁻¹). Long-term trends of 1850–2014 show high uncertainty among models (–0.92 to +0.31 TgC yr⁻²). Results of emulated sensitivity experiments indicate meteorological variations as the main factor of year-to-year fluctuations, but the main drivers of long-term isoprene emission trends differ among models. Models without CO2 effects implicate climate change as the driver, but other models with CO2 effects (fertilization only/and inhibition) indicate CO2 and LULCC as the primary drivers. The discrepancies arise from how models account for CO2 and LULCC alongside climate effects on isoprene emissions. Aside from LULCC-induced reductions, differences in CO2 inhibition representation (strength and presence or absence of thresholds) were able to mitigate or reverse increasing trends because of rising temperatures or in combination with CO2 fertilization. Net CO2 effects on global isoprene emissions show the highest inter-model variation (σ = 0.43 TgC yr⁻²), followed by LULCC effects (σ = 0.17 TgC yr⁻²), with climate change effects exhibiting more or less variation (σ = 0.06 TgC yr⁻²). The critical drivers of isoprene emission trends depend on a model’s emission scheme complexity. This dependence emphasizes the need for models with accurate representation of CO2 and LULCC effects alongside climate change influences for robust long-term predictions. Important uncertainties remain in understanding the interplay between CO2, LULCC, and climate effects on isoprene emissions, mainly for CO2. More long-term observations of isoprene emissions across various biomes are necessary, along with improved models with varied CO2 responses. Moreover, instead of reliance on the current models, additional emission schemes can better capture isoprene emissions complexities and their effects on climate

Event-to-event intensification of the hydrologic cycle from 1.5 °C to a 2 °C warmer world

Abstract The Paris agreement was adopted to hold the global average temperature increase to well below 2 °C and pursue efforts to limit it to 1.5 °C. Here, we investigate the event-to-event hydroclimatic intensity, where an event is a pair of adjacent wet and dry spells, under future warming scenarios. According to a set of targeted multi-model large ensemble experiments, event-wise intensification will significantly increase globally for an additional 0.5 °C warming beyond 1.5 °C. In high latitudinal regions of the North American continent and Eurasia, this intensification is likely to involve overwhelming increases in wet spell intensity. Western and Eastern North America will likely experience more intense wet spells with negligible changes of dry spells. For the Mediterranean region, enhancement of dry spells seems to be dominating compared to the decrease in wet spell strength, and this will lead to an overall event-wise intensification. Furthermore, the extreme intensification could be 10 times stronger than the mean intensification. The high damage potential of such drastic changes between flood and drought conditions poses a major challenge to adaptation, and the findings suggest that risks could be substantially reduced by achieving a 1.5 °C target

NorCPM1 and its contribution to CMIP6 DCPP

The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It combines the Norwegian Earth System Model version 1 (NorESM1) – which features interactive aerosol-cloud schemes and an isopycnic-coordinate ocean component with biogeochemistry – with anomaly assimilation of SST and T/S-profile observations using the Ensemble Kalman Filter (EnKF).publishedVersio

ClimateBench v1.0: A benchmark for data-driven climate projections

Many different emission pathways exist that are compatible with the Paris climate agreement, and many more are possible that miss that target. While some of the most complex Earth System Models have simulated a small selection of Shared Socioeconomic Pathways, it is impractical to use these expensive models to fully explore the space of possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate response to a given scenario. Here we present ClimateBench - a benchmarking framework based on a suite of CMIP, AerChemMIP and DAMIP simulations performed by a full complexity Earth System Model, and a set of baseline machine learning models that emulate its response to a variety of forcers. These emulators can predict annual mean global distributions of temperature, diurnal temperature range and precipitation (including extreme precipitation) given a wide range of emissions and concentrations of carbon dioxide, methane and aerosols, allowing them to efficiently probe previously unexplored scenarios. We discuss the accuracy and interpretability of these emulators and consider their robustness to physical constraints such as total energy conservation. Future opportunities incorporating such physical constraints directly in the machine learning models and using the emulators for detection and attribution studies are also discussed. This opens a wide range of opportunities to improve prediction, consistency and mathematical tractability. We hope that by laying out the principles of climate model emulation with clear examples and metrics we encourage others to tackle this important and demanding challenge

Evaluating stratospheric ozone and water vapour changes in CMIP6 models from 1850 to 2100

Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here, we evaluate long-term changes in these species from the pre-industrial period (1850) to the end of the 21st century in Coupled Model Intercomparison Project phase 6 (CMIP6) models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ∼300 DU in 1850 to ∼ 305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone-depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼ 10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer-Dobson circulation under other Shared Socioeconomic Pathways (SSPs). In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ∼ 0.5 ppmv at 70 hPa. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼ 0.5 ppmv from the pre-industrial to the present-day period and are projected to increase further by the end of the 21st century. The largest increases (∼ 2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapour, and to a lesser extent TCO, shows large variations following explosive volcanic eruptions. © Author(s) 2021