Reply on RC1

Abstract. Land cover and land management change (LCLMC) has been highlighted for its critical role in mitigation scenarios, both in terms of global mitigation and local adaptation. Yet, the climate effect of individual LCLMC options, their dependence on the background climate and the local vs. non-local responses are still poorly understood across different Earth system models (ESMs). Here we simulate the climatic effects of LCLMC using three state-of-the-art ESMs, including the Community Earth System Model (CESM), the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and the European Consortium Earth System Model (EC-EARTH). We assess the LCLMC effects using the following four idealized experiments: (i) a fully afforested world, (ii) a world fully covered by cropland, (ii) a fully afforested world with extensive wood harvesting and (iv) a full-cropland world with extensive irrigation. In these idealized sensitivity experiments, performed under present-day climate conditions, the effects of the different LCLMC strategies represent an upper bound for the potential of global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLMC, a checkerboard-like LCLMC perturbation, i.e. alternating grid boxes with and without LCLMC, is applied. The local effects of deforestation on surface temperature are largely consistent across the ESMs and the observations, with a cooling in boreal latitudes and a warming in the tropics. However, the energy balance components driving the change in surface temperature show less consistency across the ESMs and the observations. Additionally, some biases exist in specific ESMs, such as a strong albedo response in CESM mid-latitudes and a soil-thawing-driven warming in boreal latitudes in EC-EARTH. The non-local effects on surface temperature are broadly consistent across ESMs for afforestation, though larger model uncertainty exists for cropland expansion. Irrigation clearly induces a cooling effect; however, the ESMs disagree whether these are mainly local or non-local effects. Wood harvesting is found to have no discernible biogeophysical effects on climate. Overall, our results underline the potential of ensemble simulations to inform decision making regarding future climate consequences of land-based mitigation and adaptation strategies.

Abstract. Land cover and land management change (LCLMC) has been highlighted for its critical role in mitigation scenarios in terms of both global mitigation and local adaptation. Yet, the climate effect of individual LCLMC options, their dependence on the background climate, and the local vs. non-local responses are still poorly understood across different Earth system models (ESMs). Here we simulate the climatic effects of LCLMC using three state-of-the-art ESMs, including the Community Earth System Model (CESM), the Max Planck Institute for Meteorology Earth System Model (MPI-ESM), and the European Consortium Earth System Model (EC-EARTH). We assess the LCLMC effects using four idealized experiments: (i) a fully afforested world, (ii) a world fully covered by cropland, (iii) a fully afforested world with extensive wood harvesting, and (iv) a full cropland world with extensive irrigation. In these idealized sensitivity experiments performed under present-day climate conditions, the effects of the different LCLMC strategies represent an upper bound for the potential of global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLMC, a checkerboard-like LCLMC perturbation, i.e. alternating grid boxes with and without LCLMC, is applied. The local effects of deforestation on surface temperature are largely consistent across the ESMs and the observations, with a cooling in boreal latitudes and a warming in the tropics. However, the energy balance components driving the change in surface temperature show less consistency across the ESMs and the observations. Additionally, some biases exist in specific ESMs, such as a strong albedo response in CESM mid-latitudes and a soil-thawing-driven warming in boreal latitudes in EC-EARTH. The non-local effects on surface temperature are broadly consistent across ESMs for afforestation, though larger model uncertainty exists for cropland expansion. Irrigation clearly induces a cooling effect; however, the ESMs disagree regarding whether these are mainly local or non-local effects. Wood harvesting is found to have no discernible biogeophysical effects on climate. Our results overall underline the potential of ensemble simulations to inform decision-making regarding future climate consequences of land-based mitigation and adaptation strategies.

Abstract. Forests are an important component in the framework of nature-based solutions for mitigating climate change. However, there are still uncertainties about the biogeophysical effects of forest cover changes affecting heat and water fluxes as captured by Earth System Models (ESMs) simulations and observations. In this study, we investigate the differences in the surface temperature response to idealized, complete deforestation and the temperature sensitivity to percentage change in forest cover in ESMs and observations. In this comparison, the separation between local (at the place of deforestation) and non-local (nearby or distant locations) effects is crucial as observations capture only the former. Here, we propose a modified methodology to separate local and non-local effects in climate models suitable for simulations with linear rate of deforestation. The local sensitivity of a climate variable per unit deforested area is represented by the slope of the linear regression, where tree cover is an explanatory variable. The non-local effect is defined as the difference between the overall change in the respective climate variable and the local effect. Our analysis of eleven ESMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) that participated in the idealized global deforestation experiment deforest-glob, reveals a coherent local temperature response among climate models characterized by warming in the tropics and cooling in the northern higher latitudes. The temperature response however varies in magnitude, space and time with ESMs showing distinctive seasonal and spatial patterns. A closer look at the albedo response to deforestation across northern latitudes shows an overestimation in the ESMs in comparison to observations that translates via an emergent constraint (i.e. resulting from the linear relationships between local albedo and surface temperature within the model ensemble) into an overestimation of the overall simulated cooling effect. The overestimation of the local albedo sensitivity cannot be explained solely by the higher percentage of snow cover in ESMs. In terms of local latent heat flux sensitivity, the ESMs ensemble mean is overestimated for the boreal region, but it is in good agreement with the observational constraint in the temperate forests and the tropics. However, the inter-model spread and the internal model variation in these regions are considerable. ESMs having higher local albedo and latent heat flux sensitivities than the current observational constraints can still exhibit a realistic temperature response due to compensatory effects between the two sensitivities. Non-local effects contribute to consistent cooling throughout the globe, which persists also during the summer when the influence of the overestimated albedo sensitivity over snow is weaker. Having a deeper understanding of how local and non-local biogeophysical effects are represented in ESMs can give us insights into the net climate impact of deforestation and help us improve next generation ESMs.

Abstract. Land cover and land management changes (LCLMCs) have a substantial impact on the global carbon budget and, consequently, on global climate via the biogeochemical (BGC) effects. The commonly considered BGC effects refer to the direct influence of LCLMCs on local carbon stocks (local BGC effects). However, LCLMCs also influence climate by altering the local surface energy balance due to changes in land surface properties, such as albedo, leaf area, and roughness (local biogeophysical (BGP) effects). Altered local air mass properties can impact regions remote from LCLMCs through advection and changes in large-scale circulation (nonlocal BGP effects). Previous studies have shown potentially substantial nonlocal BGP effects on temperature and precipitation. Given that the terrestrial carbon cycle strongly depends on climate conditions, this raises the question of whether LCLMCs can trigger remote carbon cycle changes (nonlocal BGC effects) – a currently overlooked, potentially large climate and ecosystem impact. To assess the nonlocal BGC effects, we analyze sensitivity simulations for three selected types of hypothetical large-scale LCLMCs, global cropland expansion, global cropland expansion with irrigation, and global afforestation, which were performed by three state-of-the-art Earth system models (ESMs). We separate the nonlocal BGC effect using a checkerboard-like LCLMC perturbation that has previously only been applied to BGP effects. We show that nonlocal BGC effects on vegetation and soil carbon pools persistently accumulate, exceeding natural fluctuations and typically becoming detectable within the first 40 years after LCLMCs. By the end of our 160-year simulation period, nonlocal BGC effects lead to an absolute magnitude of change in total terrestrial carbon stock by 1 to 37 GtC, with strong changes over the densely forested Amazon region (0.2 to 7 GtC) and central Congo Basin region (0.3 to 15 GtC), depending on models and LCLMCs implemented. For the irrigation scenario, the nonlocal BGC effects are comparable to the total BGC effects, with the nonlocal-to-total ratio for vegetation carbon pools commonly reaching around 90 %. Our results reveal that the nonlocal BGC effects could be substantial and call for these effects to be considered for accurate impact assessment and sound policymaking. This becomes even more relevant when LCLMCs are expected to play a pivotal role in achieving the Paris Agreement's goal of limiting global warming below 1.5 °C above pre-industrial levels.

Afforestation can impact surface temperature through local and nonlocal biophysical effects. However, the local and nonlocal effects of afforestation in China have rarely been explicitly investigated. In this study, we separate the local and nonlocal effects of idealized afforestation in China based on a checkerboard method and the regional Weather Research and Forecasting (WRF) Model. Two checkerboard pattern–like afforestation simulations (AFF1/4 and AFF3/4) with regularly spaced afforested and unaltered grid cells are performed; afforestation is implemented in one out of every four grid cells in AFF1/4 and in three out of every four grid cells in AFF3/4. The mechanisms for the local and nonlocal effects are examined through the decomposition of the surface energy balance. The results show that the local effects dominate surface temperature responses to afforestation in China, with a cooling effect of approximately −1.00°C for AFF1/4 and AFF3/4. In contrast, the nonlocal effects warm the land surface by 0.14°C for AFF1/4 and 0.41°C for AFF3/4. The local cooling effects mainly result from 1) enhanced sensible and latent heat fluxes and 2) decreases in downward shortwave radiation due to increased low cloud cover fractions. The nonlocal warming effects mainly result from atmospheric feedbacks, including 1) increases in downward shortwave radiation due to decreased low cloud cover fractions and 2) increases in downward longwave radiation due to increased middle and high cloud cover fractions. This study highlights that, despite the unexpected nonlocal warming effect, afforestation in China still has great potential in mitigating climate warming through biophysical processes.

Some climate variables do not show the same response to declining atmospheric CO2 concentrations as before the preceding increase. A comprehensive understanding of this hysteresis effect and its regional patterns is, however, lacking. Here we use an Earth system model with an idealized CO2 removal scenario to show that surface temperature and precipitation exhibit globally widespread irreversible changes over a timespan of centuries. To explore the climate hysteresis and reversibility on a regional scale, we develop a quantification method that visualizes their spatial patterns. Our experiments project that 89% and 58% of the global area experiences irreversible changes in surface temperature and precipitation, respectively. Strong irreversible response of surface temperature is found in the Southern Ocean, Arctic and North Atlantic Ocean and of precipitation in the tropical Pacific, global monsoon regions and the Himalayas. These global hotspots of irreversible changes can indicate elevated risks of negative impacts on developing countries.

Land use and land cover changes (LULCCs) can influence surface temperature through local and nonlocal biophysical processes, which remain inadequately addressed. In this study, we separate the local and nonlocal effects of historical (1850–2014) LULCCs based on model outputs from the Coupled Model Intercomparison Project Phase 6. We also attempt to explore the sources of intermodel differences in the effects of LULCCs. The multimodel mean shows a cooling effect of −0.05°C (with an intermodel range of −0.24–0.06°C) at the global scale due to cropland and pastureland expansion, consisting of dominant nonlocal cooling of −0.06°C (with an intermodel range of −0.26–0.06°C) and slight local warming of 0.01°C (with an intermodel range of −0.01–0.05°C). The modeling results show some clear consistency in the effects of LULCCs despite considerable intermodel uncertainties. The local effects cause warming at low latitudes and cooling in boreal regions via changes in upward shortwave radiation and sensible and latent heat fluxes. The nonlocal effects mainly cause cooling via decreases in downward longwave radiation and increases in upward shortwave radiation. Intermodel differences in the total effects are dominated by those in the nonlocal effects, which are further attributed to divergent changes in downward longwave radiation and sensible heat flux across the models. This study highlights the importance of the nonlocal effects of LULCCs in terms of strength and intermodel uncertainty, with implications for designing land‐based solutions aimed at climate change mitigation.

Plant phenology influences both the terrestrial carbon cycle and land-atmosphere interactions, and therefore can potentially modify large-scale circulations in the atmosphere. However, considerable discrepancies are present among models and between model simulations and observations of plant phenology, adding large uncertainties to future climate projections. Here we modified plant phenology in the Northern Hemisphere in the Community Earth System Model and conducted simulations to characterize how differences in plant phenology influence land-atmosphere coupling. Plant phenology changes the land surface and land-atmosphere interactions by directly modulating absorbed solar radiation and evapotranspiration and indirectly modifying cloud feedback and snow-albedo feedback. Over the Northern Hemisphere, the largest effects occur from March to June when seasonal deciduous phenology is modified from satellite-derived values to model simulations, which results in a >3K increase in surface temperature that propagates to 500hPa (~5km height). Phenology-induced changes in canopy evapotranspiration and surface temperature depend on soil moisture availability during the growing season. Surface temperature decreases significantly due to increasing latent heat flux and cloud reflection where soil moisture is abundant, while soil moisture control over evapotranspiration increases and surface temperature remains little-changed or even increases in more arid regions. Characterizing the influence of phenology on biogeophysical processes is critical, as significant impacts are present both at the land surface and in the atmospheric layers above.

An adequate characterization of internal modes of climate variability (MoV) is a prerequisite for both accurate seasonal predictions and climate change detection and attribution. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify intermodel contrasts. In this work, these goals are pursued in four recently produced LEs: the Energy Exascale Earth System Model (E3SM) versions 1 and 2 LEs, and the Community Earth System Model (CESM) versions 1 and 2 LEs. In general, the representation of global coupled modes is found to improve across successive E3SM and CESM versions in conjunction with the fidelity of the base state climate while the patterns of extratropical modes are well simulated across the ensembles. Various persistent shortcomings for all MoV are however identified and discussed. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics. Significance Statement Modes of variability play a critical role in prediction of seasonal to decadal climate variability and detection of forced climate change, but historically many modes have been poorly simulated by coupled climate models. Using recently produced large ensembles, this work demonstrates the improved simulation of a broad range of internal modes in successive versions of the E3SM and CESM and discusses opportunities for further advances.

The land subsurface stored around 6% of the Earth’s energy imbalance in the last five decades (of around 0.5 Wm-2, equivalent to 380 ZJ), being the second contributor to the energy partitioning after the ocean (90%). Previous studies have shown that state-of-the-art Earth System Models (ESMs) remarkably underestimate the observational land heat uptake values. This underestimation stems from Land Surface Models (LSMs) within ESMs imposing too shallow zero-flux bottom boundary conditions to correctly represent the conductive propagation and land heat uptake with depth. When realistically deep boundary conditions are prescribed, land heat uptake increases by a factor of five. However, changes in ground surface temperature are negligible. The reasons for this lack of impact of the LSM depth on surface temperatures are assessed herein.An ensemble of eight historical and RCP8.5 land-only simulations with different subsurface depths was conducted with the LSM of the Max Planck Institute for Meteorology ESM (MPI-ESM), JSBACH. Simulation-derived latent (LHF), sensible (SHF), and ground heat fluxes (GHF) were compared across simulations, and GHF was additionally evaluated against estimates from a one-dimensional heat conduction forward model. Results show that, for a global warming of 1.5 ºC with respect to 1850-1900, GHF increases from 0.04 to 0.07 Wm-2 when deepening the LSM from 10 to 22 m, saturating at around 0.12 Wm-2 when the boundary condition is placed at approximately 100 m. The increase in the incoming GHF is mainly compensated by a global decrease in the outgoing SHF, a small decrease of the LHF in wet regions, and a decrease in the surface net radiation in arid and semi-arid regions. These quantities, yet small, evidence that an insufficient LSM depth induces to an inaccurate resolution of the long-term surface energy balance, which may have implications for land-atmosphere interaction. Their accumulation over time also produces biases in the terrestrial energy partitioning.

<strong class="journal-contentHeaderColor">Abstract.</strong> Molecular oxygen in our atmosphere has increased from less than a part per million in the Archean Eon, to a fraction of a percent in the Proterozoic, and finally to modern levels during the Phanerozoic. While oxygen itself has only minor radiative and climatic effects, the accompanying ozone has important consequences for Earth climate. Using the Community Earth System Model (CESM), a 3-D general circulation model, we test the effects of various levels of ozone on Earth's climate. When CO₂ is held constant, the global mean surface temperature decreases with decreasing ozone, with a maximum drop of ~3.5 K at near total ozone removal. By supplementing our GCM results with 1-D radiative flux calculations, we are able to test which changes to the atmosphere are responsible for this temperature change. We find that the surface temperature change is caused mostly by the stratosphere being much colder when ozone is absent; this makes it drier, substantially weakening the greenhouse effect. We also examine the effect of the structure of the upper troposphere and lower stratosphere on the formation of clouds, and on the global circulation. At low ozone, both high and low clouds become more abundant, due to changes in the tropospheric stability. These generate opposing short-wave and long-wave radiative forcings that are nearly equal. The Hadley circulation and tropospheric jet streams are strengthened, while the stratospheric polar jets are weakened, the latter being a direct consequence of the change in stratospheric temperatures. This work identifies the major climatic impacts of ozone, an important piece of the evolution of Earth's atmosphere.

<strong class="journal-contentHeaderColor">Abstract.</strong> Molecular oxygen in our atmosphere has increased from less than a part per million in the Archean Eon, to a fraction of a percent in the Proterozoic, and finally to modern levels during the Phanerozoic. While oxygen itself has only minor radiative and climatic effects, the accompanying ozone has important consequences for Earth climate. Using the Community Earth System Model (CESM), a 3-D general circulation model, we test the effects of various levels of ozone on Earth's climate. When CO₂ is held constant, the global mean surface temperature decreases with decreasing ozone, with a maximum drop of ~3.5 K at near total ozone removal. By supplementing our GCM results with 1-D radiative flux calculations, we are able to test which changes to the atmosphere are responsible for this temperature change. We find that the surface temperature change is caused mostly by the stratosphere being much colder when ozone is absent; this makes it drier, substantially weakening the greenhouse effect. We also examine the effect of the structure of the upper troposphere and lower stratosphere on the formation of clouds, and on the global circulation. At low ozone, both high and low clouds become more abundant, due to changes in the tropospheric stability. These generate opposing short-wave and long-wave radiative forcings that are nearly equal. The Hadley circulation and tropospheric jet streams are strengthened, while the stratospheric polar jets are weakened, the latter being a direct consequence of the change in stratospheric temperatures. This work identifies the major climatic impacts of ozone, an important piece of the evolution of Earth's atmosphere.

Abstract. Modeling fire as an integral part of an Earth system model (ESM) is vital for quantifying and understanding fire–climate–vegetation interactions on a global scale and from an Earth system perspective. In this study, we introduce to the Community Earth System Model (CESM) the new global fire parameterization proposed by Li et al. (2012a, b), now with a more realistic representation of the anthropogenic impacts on fires, with a parameterization of peat fires, and with other minor modifications. The improved representation of the anthropogenic dimension includes the first attempt to parameterize agricultural fires, the economic influence on fire occurrence, and the socioeconomic influence on fire spread in a global fire model – also an alternative scheme for deforestation fires. The global fire parameterization has been tested in CESM1's land component model CLM4 in a 1850–2004 transient simulation, and evaluated against the satellite-based Global Fire Emission Database version 3 (GFED3) for 1997–2004. The simulated 1997–2004 average global totals for the burned area and fire carbon emissions in the new fire scheme are 338 Mha yr−1 and 2.1 Pg C yr−1. Its simulations on multi-year average burned area, fire seasonality, fire interannual variability, and fire carbon emissions are reasonable, and show better agreement with GFED3 than the current fire scheme in CESM1 and modified CTEM-FIRE. Moreover, the new fire scheme also estimates the contributions of global fire carbon emissions from different sources. During 1997–2004, the contributions are 8% from agricultural biomass burning, 24% from tropical deforestation and degradation fires, 6% from global peat fires (3.8% from tropical peat fires), and 62% from other fires, which are close to previous assessments based on satellite data, government statistics, or other information sources. In addition, we investigate the importance of direct anthropogenic influence (anthropogenic ignitions and fire suppression) on global fire regimes during 1850–2004, using CESM1 with the new fire scheme. Results show that the direct anthropogenic impact is the main driver for the long-term trend of global burned area, but hardly contributes to the long-term trend of the global total of fire carbon emissions.

A detailed examination is made in both observations and the Community Earth System Model (CESM) of relationships among top‐of‐atmosphere radiation, water vapor, temperatures, and precipitation for 2000–2014 to assess the origins of radiative perturbations and climate feedbacks empirically. The 30‐member large ensemble coupled runs are analyzed along with one run with specified sea surface temperatures for 1994 to 2005 (to avoid volcanic eruptions). The vertical structure of the CESM temperature profile tends to be top heavy in the model, with too much deep convection and not enough lower stratospheric cooling as part of the response to tropospheric heating. There is too much absorbed solar radiation (ASR) over the Southern Oceans and not enough in the tropics, and El Niño–Southern Oscillation (ENSO) is too large in amplitude in this version of the model. However, the covariability of monthly mean anomalies produces remarkably good replication of most of the observed relationships. There is a lot more high‐frequency variability in radiative fluxes than in temperature, highlighting the role of clouds and transient weather systems in the radiation statistics. Over the Warm Pool in the tropical western Pacific and Indian Oceans, where nonlocal effects from the Walker circulation driven by the ENSO events are important, several related biases emerge: in response to high SST anomalies there is more precipitation, water vapor, and cloud and less ASR and outgoing longwave radiation in the model than observed. Different model global mean trends are evident, however, possibly hinting at too much positive cloud feedback in the model.

Simulating mass changes and ice dynamics for mountain glaciers using Earth System Models (ESMs) is challenging due to their small size, sheer number, and spatial discontinuities in the ground ice coverage. This has resulted in a knowledge and representational gap in ESMs. However, there is a need for scaling ESMs from global to regional domains for comprehensive glacio-hydrological and hydroclimatic assessments. We introduce new developments for simulating the mass balance and dynamic evolution of mountain glaciers within the Community Earth System Model (CESM). We provide an overview of this work across two spatiotemporal scales related to: (1) the dynamic evolution of the Central European glaciers under the GlacierMIP3 protocol using the Community Ice Sheet Model (CISM) and (2) the energy and water balance of the Upper Indus glaciated basins at daily-monthly timescales using the Hillslope Hydrology configuration of the Community Land Model (CLM).