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Despite recurrent emphasis on their ecological and economic roles, the importance of high-trophic levels on ocean carbon dynamics, through passive (fecal pellet production, carcasses) and active (vertical migration) processes, is still largely unexplored, notably under climate change scenarios. Additionally, high trophic levels impact the ecosystem dynamics through top-down effects on lower trophic levels, which might change under anthropogenic influence. Here we compare two simulations of a global biogeochemical-ecosystem model with and without feedbacks from large marine animals. We show that these large marine animals affect the evolution of low-trophic level biomasses, hence net primary production and most certainly ecosystem equilibrium, but seem to have little influence on the 21st century anthropogenic carbon uptake under the RCP8.5 scenario. These results provide new insights regarding the expectations for trophic amplification of climate change through the marine trophic chain and regarding the necessity to explicitly represent marine animals in Earth System Models.

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change and broadening the impact of ecological research. Accepted version

Computational models of the Earth System are critical tools for modern scientific inquiry. Efforts toward evaluating and improving errors in representations of physical and chemical processes in th...

For decades, the Arctic has been warming at least twice as fast as the rest of the globe. As a first step towards quantifying parametric uncertainty in Arctic feedbacks, we perform a variance-based...

The present study examines the characteristics of the MJO events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistic...

We report the results of two Earth System Model (ESM) configurations which only differ in the physical representation of the ocean around New Zealand. The first model is a global low-resolution con...

Floodplain inundation links river and land systems through significant water, sediment, and nutrient exchanges. However, these two-way interactions between land and river are currently missing in m...

The ability of an observationally-constrained cloud-system resolving model (Weather Research and Forecasting; WRF, 4-km grid spacing) and a global climate model (Energy Exascale Earth System Model;...

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmosphere Model version 4.1 (AM4.1), which builds on developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation as part of the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's AM4.0 development effort, which focused on physical and aerosol interactions and which is used as the atmospheric component of CM4.0, AM4.1 focuses on comprehensiveness of Earth system interactions. Key features of this model include doubled horizontal resolution of the atmosphere (~200 to ~100 km) with revised dynamics and physics from GFDL's previous‐generation AM3 atmospheric chemistry‐climate model. AM4.1 features improved representation of atmospheric chemical composition, including aerosol and aerosol precursor emissions, key land‐atmosphere interactions, comprehensive land‐atmosphere‐ocean cycling of dust and iron, and interactive ocean‐atmosphere cycling of reactive nitrogen. AM4.1 provides vast improvements in fidelity over AM3, captures most of AM4.0's baseline simulations characteristics, and notably improves on AM4.0 in the representation of aerosols over the Southern Ocean, India, and China—even with its interactive chemistry representation—and in its manifestation of sudden stratospheric warmings in the coldest months. Distributions of reactive nitrogen and sulfur species, carbon monoxide, and ozone are all substantially improved over AM3. Fidelity concerns include degradation of upper atmosphere equatorial winds and of aerosols in some regions.

For simulations intended to study the influence of anthropogenic forcing on climate, temporal stability of the Earth's natural heat, freshwater, and biogeochemical budgets is critical. Achieving such coupled model equilibration is scientifically and computationally challenging. We describe the protocol used to spin‐up the UK Earth system model (UKESM1) with respect to preindustrial forcing for use in the sixth Coupled Model Intercomparison Project (CMIP6). Due to the high computational cost of UKESM1's atmospheric model, especially when running with interactive full chemistry and aerosols, spin‐up primarily used parallel configurations using only ocean/land components. For the ocean, the resulting spin‐up permitted the carbon and heat contents of the ocean's full volume to approach equilibrium over 5,000 years. On land, a spin‐up of 1,000 years brought UKESM1's dynamic vegetation and soil carbon reservoirs toward near‐equilibrium. The end‐states of these parallel ocean‐ and land‐only phases then initialized a multicentennial period of spin‐up with the full Earth system model, prior to this simulation continuing as the UKESM1 CMIP6 preindustrial control (piControl). The realism of the fully coupled spin‐up was assessed for a range of ocean and land properties, as was the degree of equilibration for key variables. Lessons drawn include the importance of consistent interface physics across ocean‐ and land‐only models and the coupled (parent) model, the extreme simulation duration required to approach equilibration targets, and the occurrence of significant regional land carbon drifts despite global‐scale equilibration. Overall, the UKESM1 spin‐up underscores the expense involved and argues in favor of future development of more efficient spin‐up techniques.

Biological processes in Southern Ocean surface waters have widespread impacts on global productivity and oceanic CO2 storage. Here, we demonstrate that biological calcification in the Southern Ocean exerts a strong control on the global distribution of alkalinity. The signature of Southern Ocean calcification is evident in observations as a depletion of potential alkalinity within portions of Subantarctic Mode and Intermediate Water. Experiments with an ocean general circulation model indicate that calcification and subsequent sinking of biogenic carbonate in this region effectively transfers alkalinity between the upper and lower cells of the meridional overturning circulation. Southern Ocean calcification traps alkalinity in the deep ocean; decreasing calcification permits more alkalinity to leak out from the Southern Ocean, yielding increased alkalinity in the upper cell and low-latitude surface waters. These processes have implications for atmosphere-ocean partitioning of carbon. Reductions in Southern Ocean calcification increase the buffer capacity of surface waters globally, thereby enhancing the ocean's ability to absorb carbon from the atmosphere. This study highlights the critical role of Southern Ocean calcification in determining global alkalinity distributions, demonstrating that changes in this process have the potential for widespread consequences impacting air-sea partitioning of CO2.

A regional Earth System Model has been implemented for the South Asia region. We investigate the effect of the marine biogeochemical feedback which affects the attenuation of the short-wave radiati...

Representing climate‐crop interactions is critical to Earth system modeling. Despite recent progress in modeling dynamic crop growth and irrigation in land surface models (LSMs), transitioning these models from field to regional scales is still challenging. This study applies the Noah‐MP LSM with dynamic crop‐growth and irrigation schemes to jointly simulate the crop yield and irrigation amount for corn and soybean in the central United States. The model performance of crop yield and irrigation amount are evaluated at county‐level against the USDA reports and USGS water withdrawal data, respectively. The bulk simulation (with uniform planting/harvesting management and no irrigation) produces significant biases in crop yield estimates for all planting regions, with root‐mean‐square‐errors (RMSEs) being 28.1% and 28.4% for corn and soybean, respectively. Without an irrigation scheme, the crop yields in the irrigated regions are reduced due to water stress with RMSEs of 48.7% and 20.5%. Applying a dynamic irrigation scheme effectively improves crop yields in irrigated regions and reduces RMSEs to 22.3% and 16.8%. In rainfed regions, the model overestimates crop yields. Applying spatially varied planting and harvesting dates at state‐level reduces crop yields and irrigation amount for both crops, especially in northern states. A “nitrogen‐stressed” simulation is conducted and found that the improvement of irrigation on crop yields is limited when the crops are under nitrogen stress. Several uncertainties in modeling crop growth are identified, including yield‐gap, planting date, rubisco capacity, and discrepancies between available data sets, pointing to future efforts to incorporating spatially varying crop parameters to better constrain crop growing seasons.

On interannual to decadal time scales, memory in the Earth's climate system resides to a large extent in the slowly varying heat content of the ocean, which responds to fast atmospheric variability and in turn sets the frame for large-scale atmospheric circulation patterns. This large-scale coupled atmosphere–ocean feedback is generally well represented in today's Earth system models. This may fundamentally change when data assimilation is used to bring such models close to an observed state to initialize interannual to decadal climate predictions. Here, we review how the large-scale coupled atmosphere–ocean feedback is preserved in common approaches to construct such initial conditions, with the focus on the initialized ocean state. In a set of decadal prediction experiments, ranging from an initialization of atmospheric variability only to full-field nudging of both atmosphere and ocean, we evaluate the variability and predictability of the Atlantic meridional overturning circulation, of the Atlantic multidecadal variability and North Atlantic subpolar gyre sea surface temperatures. We argue that the quality of initial conditions for decadal predictions should not purely be assessed by their closeness to observations, but also by the closeness of their respective predictions to observations. This prediction quality may depend on the representation of the simulated large-scale atmosphere–ocean feedback. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models

This paper describes the development of New Zealand's Earth System Model (NZESM) and evaluates its performance against its parent model (United Kingdom Earth System Model, UKESM) and observations. The main difference between the two earth system models is an embedded high‐resolution (1/5°) nested region over the oceans around New Zealand in the NZESM. Due to this finer ocean model mesh, currents such as the East Australian Current, East Australian Current Extension, Tasman Front, and Tasman Leakage, and their volume and heat transports are better simulated in the NZESM. The improved oceanic transports have led to a reduction in upper ocean temperature and salinity biases over the nested region. In addition, net transports through the Tasman Sea of volume, heat and salt in the NZESM agree better with previously reported estimates. A consequence of the increased cross‐Tasman Sea transports in the NZESM is increased temperatures and salinity west of Australia and in the Southern Ocean reducing the meridional sea surface temperature gradient between the subtropics and sub‐Antarctic. This also leads to a weakening of the westerly winds between 60°S and 45°S over large parts of the Southern Ocean, which reduces the northward Ekman transport, reduces the formation of Antarctic Intermediate Water, and allows for a southward expansion of the Super‐Gyre in all ocean basins. Connecting an improved oceanic circulation around New Zealand to a basin‐wide Super‐Gyre response is an important step forward in our current understanding of how local scales can influence global scales in a fully coupled earth system model.

Including the parameterization of land management practices into Earth System Models has been shown to influence the simulation of regional climates, particularly for temperature extremes. However, recent model development has focused on implementing irrigation where other land management practices such as conservation agriculture (CA) has been limited due to the lack of global spatially explicit datasets describing where this form of management is practiced. Here, we implement a representation of CA into the Community Earth System Model and show that the quality of simulated surface energy fluxes improves when including more information on how agricultural land is managed. We also compare the climate response at the subgrid scale where CA is applied. We find that CA generally contributes to local cooling (~1°C) of hot temperature extremes in mid-latitude regions where it is practiced, while over tropical locations CA contributes to local warming (~1°C) due to changes in evapotranspiration dominating the effects of enhanced surface albedo. In particular, changes in the partitioning of evapotranspiration between soil evaporation and transpiration are critical for the sign of the temperature change: a cooling occurs only when the soil moisture retention and associated enhanced transpiration is sufficient to offset the warming from reduced soil evaporation. Finally, we examine the climate change mitigation potential of CA by comparing a simulation with present-day CA extent to a simulation where CA is expanded to all suitable crop areas. Here, our results indicate that while the local temperature response to CA is considerable cooling (>2°C), the grid-scale changes in climate are counteractive due to negative atmospheric feedbacks. Overall, our results underline that CA has a nonnegligible impact on the local climate and that it should therefore be considered in future climate projections. ispartof: GLOBAL CHANGE BIOLOGY vol:24 issue:10 pages:4758-4774 ispartof: location:England status: published

An estimate of permafrost extent and thickness in the northern hemisphere during the Last Glacial Maximum (LGM, ~ 21 ka) has been produced using the VU University Amsterdam Permafrost Snow (VAMPERS) model, forced by iLOVECLIM, an Earth System Model of Intermediate Complexity. We present model results that give both permafrost thickness and extent. In the northern hemisphere, permafrost is estimated to have extended southwards to approximately 50°N in Asia and have achieved 1500 m thickness in Russia. The simulated distribution is compared with a reconstruction of northern hemisphere permafrost extent (Vandenberghe et al., 2014). We contend that the areas which agree with Vandenberghe et al. (2014) are the approximate areas of continuous permafrost during the LGM. In Asia, the model results agree well until approximately 50°N, which is also the approximate 0°C mean annual ground temperature isotherm estimated by iLOVECLIM. South of this limit, therefore, were likely the areas of discontinuous, sporadic and isolated permafrost during the LGM. However, it becomes difficult to model these more sensitive areas of permafrost extent since formation is dependent on local factors that are too fine for our grid's spatial resolution. In Europe, the model results disagree with the reconstruction but this was to be expected since iLOVECLIM is known to carry a warm bias in this region. For permafrost thickness, we compare our estimates with previous research and find that we have reasonably close approximations but there is a wide range of uncertainty since the subsurface parameters of lithology and water content are generalised. Copyright © 2015 John Wiley & Sons, Ltd.

The ocean occupies 95% of the Caribbean's area and plays a leading role in the region's climate, thus making the sea surface temperature (SST) a very important regional climate index. This, in conjunction with the lack of a regionally consistent, quality-controlled surface temperature dataset increases the scientific value of using SST to characterize the regional climate and its trends. This study determines the magnitudes of the long-term SST trends in the Wider Caribbean (WC) and the Antilles. We overcome the presence of discontinuity points in the SST time series using the change point statistical technique. Annual mean SST trends combining the subperiods 1906–1969 and 1972–2005 are 1.32 ± 0.41 °C per century for the Antilles and 1.08 ± 0.32 °C per century for the WC. For the same regions during the subperiod 1972–2005, the corresponding trends are 1.41 ± 0.68 °C per century and 1.18 ± 0.49 °C per century, illustrating the warming intensification during the last four decades. A significant correlation is found between the SSTs in the Caribbean and Atlantic Multidecadal Oscillation (AMO) index, suggesting a potential link between Caribbean SSTs and the mechanisms governing the Atlantic basin-wide SSTs. Finally, the capabilities of two state-of-the-art coupled climate models, the Norwegian Earth System Model (NorESM1-M) and the Bergen Climate Model (BCM), to simulate SST in the Caribbean were tested. Both models produce an adequate simulation of the annual mean SST anomalies and SST seasonal cycle for the WC and the Antilles. The simulated annual and monthly mean SSTs are colder in the two models compared to the observations, a common feature among the majority of general circulation models participating in the Coupled Model Intercomparison Project Phase 5. However, despite these minor deficiencies both BCM and NorESM1-M are considered adequate for conducting SST simulations relevant for future climate change research in the Caribbean.

Soil Sci. Soc. Am. J. 78:894–902 doi:10.2136/sssaj2013.11.0484 Received 15 Nov. 2013. *Corresponding author (umishra@anl.gov). © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Active-Layer Thickness across Alaska: Comparing Observation-Based Estimates with CMIP5 Earth System Model Predictions Pedology

The evolution of past permafrost since the Last Glacial Maximum (LGM) is simulated using the Vrije Universiteit Amsterdam Permafrost (VAMPER) model. This method is different from a proxy-based approach which translates reconstructed air temperatures to estimate past permafrost extent and thickness. First, a sensitivity analysis was performed to assess the behaviour of the model. Then five case studies within Eurasia were performed using mean annual ground surface temperatures derived from an Earth system model as the surface forcing. In Central and West Siberia, the simulated LGM permafrost thicknesses of 730–940 m and 365–445 m, respectively, agree well with previous estimates. The LGM and present-day estimates for South Russia (9–15 m) are underestimated, which is likely due to a highly simplified land-atmosphere coupling. In West and Central Europe, however, the VAMPER model was not able to produce permafrost during LGM conditions, which is due to previously recognised biases of the Earth system model. A supplementary simulation was then performed, resulting in an LGM permafrost thickness estimate of 260–320 m. Average thawing rates are on the order of 1 to 3 cm/yr except for Central Siberia, where permafrost thawed at rates of 0.3 to 0.4 cm/yr. Overall results of these simulations provide a basis for future improvement in modelling the permafrost-climate relationship over millennia. Copyright © 2013 John Wiley & Sons, Ltd.