Development Of Earth System Models Research Articles

Recent progresses in incorporating human land–water management into global land surface models toward their integration into Earth system models

The global water cycle has been profoundly affected by human land–water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land–water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large‐scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large‐scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land–water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human–water interactions within the Earths system. WIREs Water 2016, 3:548–574. doi: 10.1002/wat2.1150This article is categorized under: Engineering Water > Planning Water Science of Water > Water and Environmental Change

Quantifying microbial ecophysiological effects on the carbon fluxes of forest ecosystems over the conterminous United States

There is a pressing need to develop earth system models (ESMs), in which ecosystem processes are adequately represented, to quantify carbon-climate feedbacks. In particular, explicit representation of the effects of microbial activities on soil organic carbon decomposition has been slow in ESM development. Here we revised an existing Q10-based heterotrophic respiration (RH) algorithm of a large-scale biogeochemical model, the Terrestrial Ecosystem Model (TEM), by incorporating the algorithms of Dual Arrhenius and Michaelis-Menten kinetics and microbial-enzyme interactions. The microbial physiology enabled model (MIC-TEM) was then applied to quantify historical and future carbon dynamics of forest ecosystems in the conterminous United States. Simulations indicate that warming has a weaker positive effect on RH than that traditional Q10 model has. Our results demonstrate that MIC-TEM is superior to traditional TEM in reproducing historical carbon dynamics. More importantly, the future trend of soil carbon accumulation simulated with MIC-TEM is more reasonable than TEM did and is generally consistent with soil warming experimental studies. The revised model estimates that regional GPP is 2.48 Pg C year−1 (2.02 to 3.03 Pg C year−1) and NEP is 0.10 Pg C year−1 (−0.20 to 0.32 Pg C year−1) during 2000–2005. Both models predict that the conterminous United States forest ecosystems are carbon sinks under two future climate scenarios during the 21st century. This study suggests that terrestrial ecosystem models should explicitly consider the microbial ecophysiological effects on soil carbon decomposition to adequately quantify forest ecosystem carbon fluxes at regional scales.

A Performance Tool for Earth System Models Development

We present a performance tool for Earth system models development to aid in analyzing the performance of the climate modeling applications. It is difficult for existing tools to handle with the complex, coupled structure and the long execution time of models. Our performance tool implements rapid analysis based on statistical sampling and grouping aggregation the calling relationship and the actual computing resource consumption excluding waiting losses. Using this tool, we study an ocean model POP in short-term sampling and analyze its scaling bottleneck and acceleration trend. The measuring results of its entire execution prove our predictions on the scaling efficiencies.

How well do integrated assessment models simulate climate change?

Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice. There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements. This will require better communication between the IAM and ESM development communities.

Interannual Atmospheric Variability Affects Continental Ice Sheet Simulations on Millennial Time Scales

Abstract To inform the ongoing development of earth system models that aim to incorporate interactive ice, the potential impact of interannual variability associated with synoptic variability and El Niño–Southern Oscillation (ENSO) at the Last Glacial Maximum (LGM) on the evolution of a large continental ice sheet is explored through a series of targeted numerical modeling experiments. Global and North American signatures of ENSO at the LGM are described based on a multidecadal paleoclimate simulation using an atmosphere–ocean general circulation model (AOGCM). Experiments in which a thermomechanical North American ice sheet model (ISM) was forced with persistent LGM ENSO composite anomaly maps derived from the AOGCM showed only modest ice sheet thickness sensitivity to ENSO teleconnections. In contrast, very high model sensitivity was found when North American climate variations were incorporated directly in the ISM as a looping interannual time series. Under this configuration, localized transient cold anomalies in the atmospheric record instigated substantial new ice formation through a dynamically mediated feedback at the ice sheet margin, altering the equilibrium geometry and resulting in a bulk 10% growth of the Laurentide ice sheet volume over 5 kyr.

How well can we simulate past climates? Evaluating the models using global palaeoenvironmental datasets

Global syntheses of palaeoenvironmental data are required to test climate models under conditions different from the present. Data sets for this purpose contain data from spatially extensive networks of sites. The data are either directly comparable to model output or readily interpretable in terms of modelled climate variables. Data sets must contain sufficient documentation to distinguish between raw (primary) and interpreted (secondary, tertiary) data, to evaluate the assumptions involved in interpretation of the data, to exercise quality control, and to select data appropriate for specific goals. Four data bases for the Late Quaternary, documenting changes in lake levels since 30 14 C kyr BP (the Global Lake Status Data Base), vegetation distribution at 18 14 C kyr and 6 14 C kyr BP (BIOME 6000), aeolian accumulation rates during the last glacial-interglacial cycle (DIRTMAP), and tropical terrestrial climates at the Last Glacial Maximum (the LGM Tropical Terrestrial Data Synthesis) are summarised. Each has been used to evaluate simulations of Last Glacial Maximum (LGM: 21 calendar kyr BP) and/or mid-Holocene (6 cal. kyr BP) environments. Comparisons have demonstrated that changes in radiative forcing and orography due to orbital and ice-sheet variations explain the first-order, broad-scale (in space and time) features of global climate change since the LGM. However, atmospheric models forced by 6 cal. kyr BP orbital changes with unchanged surface conditions fail to capture quantitative aspects of the observed climate, including the greatly increased magnitude and northward shift of the African monsoon during the early to mid-Holocene. Similarly, comparisons with palaeoenvironmental datasets show that atmospheric models have underestimated the magnitude of cooling and drying of much of the land surface at the LGM. The inclusion of feedbacks due to changes in ocean- and land-surface conditions at both times, and atmospheric dust loading at the LGM, appears to be required in order to produce a better simulation of these past climates. The development of Earth system models incorporating the dynamic interactions among ocean, atmosphere, and vegetation is therefore mandated by Quaternary science results as well as climatological principles. For greatest scientific benefit, this development must be paralleled by continued advances in palaeodata analysis and synthesis, which in turn will help to define questions that call for new focused data collection efforts.

Predicting the Earth's future

The development of Earth system models that will simulate the past and present and provide predictions of future conditions is essential now that human activities have the potential to induce changes in the planetary environment. Critical aspects of global change include its pervasiveness and ubiquity, its distribution in several distinct time-scale bands, and the interactions between the atmosphere, ocean, land surface, and the terrestrial and marine biospheres. A model of the Earth System on the scale of decades to centuries, developed by the Earth System Science Committee (NASA) with the strategy of dividing by time scale rather than discipline, is presented and the requirements for observations to support the implementation of the model are reviewed.