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20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

Measurements of the stable carbon isotope ratio ( δ 13 C) on annual tree rings offer new opportunities to evaluate mechanisms of variations in photosynthesis and stomatal conductance under changing CO 2 and climate conditions, especially in conjunction with process-based biogeochemical model simulations. The isotopic discrimination is indicative of the ratio between the CO 2 partial pressure in the intercellular cavities and the atmosphere ( c i / c a ) and of the ratio of assimilation to stomatal conductance, termed intrinsic water-use efficiency (iWUE). We performed isotope-enabled simulations over the industrial period with the land biosphere module (CLM4.5) of the Community Earth System Model and the Land Surface Processes and Exchanges (LPX-Bern) dynamic global vegetation model. Results for C3 tree species show good agreement with a global compilation of δ 13 C measurements on leaves, though modeled 13 C discrimination by C3 trees is smaller in arid regions than measured. A compilation of 76 tree-ring records, mainly from Europe, boreal Asia, and western North America, suggests on average small 20th century changes in isotopic discrimination and in c i / c a and an increase in iWUE of about 27% since 1900. LPX-Bern results match these century-scale reconstructions, supporting the idea that the physiology of stomata has evolved to optimize trade-offs between carbon gain by assimilation and water loss by transpiration. In contrast, CLM4.5 simulates an increase in discrimination and in turn a change in iWUE that is almost twice as large as that revealed by the tree-ring data. Factorial simulations show that these changes are mainly in response to rising atmospheric CO 2 . The results suggest that the downregulation of c i / c a and of photosynthesis by nitrogen limitation is possibly too strong in the standard setup of CLM4.5 or that there may be problems associated with the implementation of conductance, assimilation, and related adjustment processes on long-term environmental changes.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.

Huntzinger, D. N.↗

PandExo: A Community Tool for Transiting Exoplanet Science with JWST and HST

As we approach the James Webb Space Telescope (JWST) era, several studies have emerged that aim to (1) characterize how the instruments will perform and (2) determine what atmospheric spectral features could theoretically be detected using transmission and emission spectroscopy. To some degree, all these studies have relied on modeling of JWST's theoretical instrument noise. With under two years left until launch, it is imperative that the exoplanet community begins to digest and integrate these studies into their observing plans, as well as think about how to leverage the Hubble Space Telescope (HST) to optimize JWST observations. To encourage this and to allow all members of the community access to JWST & HST noise simulations, we present here an open-source Python package and online interface for creating observation simulations of all observatory-supported timeseries spectroscopy modes. This noise simulator, called PandExo, relies on some aspects of Space Telescope Science Institute's Exposure Time Calculator, Pandeia. We describe PandExo and the formalism for computing noise sources for JWST. Then we benchmark PandExoʼs performance against each instrument team's independently written noise simulator for JWST, and previous observations for HST. We find that PandExo is within 10% agreement for HST/WFC3 and for all JWST instruments.

Batalha, Natasha E.↗

Microbial community-level regulation explains soil carbon responses to long-term litter manipulations

Climatic, atmospheric, and land-use changes all have the potential to alter soil microbial activity, mediated by changes in plant inputs. Many microbial models of soil organic carbon (SOC) decomposition have been proposed recently to advance prediction of climate and carbon (C) feedbacks. Most of these models, however, exhibit unrealistic oscillatory behavior and SOC insensitivity to long-term changes in C inputs. Here we diagnose the source of these problems in four archetypal models and propose a density-dependent formulation of microbial turnover, motivated by community-level interactions, that limits population sizes and reduces oscillations. We compare model predictions to 24 long-term C-input field manipulations and identify key benchmarks. The proposed formulation reproduces soil C responses to long-term C-input changes and implies greater SOC storage associated with CO 2 -fertilization-driven increases in C inputs over the coming century compared to recent microbial models. This study provides a simple modification to improve microbial models for inclusion in Earth System Models.

59 BASIC BIOLOGICAL SCIENCES↗

3D Climate Simulations of Earth-Like Planets with A Range of Atmospheric Composition, Radiative Transfer, Ocean, And Resolution Configurations, Using the New Version of ROCKE-3D

Understanding the climate of terrestrial planetary atmospheres has been increasingly the focus of research worldwide, in light of the increasing amount of rocky planet discoveries orbiting other stars in or near their habitable zone. Here we present simulations with the new version of the 3D climate model ROCKE-3D, whose version 2.0 will soon become publicly available. A wide range of configurations will be supported, compared to a handful ones in its predecessor, version 1.0 (Way et al., 2017). These include two model resolutions (4x5 and 2x2.5), two radiation schemes (GISS and SOCRATES), three atmospheric configurations (Earth-like, Earth-like without O3 and aerosols, and N2-dominated), and three ocean setups (prescribed sea-surface temperatures and ice cover, q-flux, and dynamic). Simulations of all different configuration combinations have been performed and will become available for use by the community. Key results will be presented across those configurations, together of the role of the structural uncertainty in model setup in the resulting climate calculated by the model.

climate simulations of Earth-like planets↗

Numerical Modeling and Design of Gaseous Propellant Acquisition System for the Triton Hopper

Triton, the largest moon around Neptune, is a captured Kuiper Belt Object with a dynamic rarified atmosphere, active geysers, and unique “cantaloupe” like terrain. Little is known about Kuiper Belt Objects in the scientific community with most of the information coming from Pluto. Currently, NASA is designing an unmanned probe to explore the atmosphere and surface of Triton. This vehicle is unique in that it repeatedly takes off and lands (hops) using nitrogen propellant collected from its surroundings on Triton. This paper presents preliminary conceptual system design and numerical modeling of the atmospheric collection process. Four concepts are presented: a cryocooler-based system, a pump-based system, a sublimation and pump-based system, and a cryocooler and sublimation system. Numerical modeling takes into account the mass and energy transfer between all the relevant nodes in the system and is able to calculate the amount of nitrogen ice collected and ice accumulation rate as a function of time for each concept. The models are ultimately used to assess the feasibility of traversing from equator to pole in under two years using a gaseous propellant acquisition system for the Hopper.

Hopper↗

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗

Workshop on the Initialization of High-Resolution Earth System Models

From weather to climate timescales, weeks to decades, societal needs require detailed predictions of the atmosphere, ocean, and land-surface to facilitate informed planning. Central to this scientific endeavor is the ability to accurately initialize the earth system models (ESMs), since frequently the skill in forecasts, predictions, and projections depends on the quality of the initialization. However, initialization of high-resolution ESMs remains an outstanding challenge, particularly for the climate modeling community where initialization has received relatively less attention and where longer-term information is needed. This need, after a review of previous workshop outcomes, led the U.S. Department of Energy (DOE) and National Oceanic and Atmospheric Administration (NOAA) to host a workshop that focused exclusively on the opportunities that data assimilation (DA) and, specifically, coupled data assimilation (CDA) might provide to the ESM enterprise with particular attention toward initialization. The workshop was held April 9-10, 2018, at the Rockville Hilton in Rockville, Maryland, with 41 participants. It was composed of seven sessions, each with a distinct topical theme that related to the broad challenge of initializing high-resolution ESMs. The first session was used to frame the workshop challenge. Two of the sessions (2 and 7) focused the current state of the art of CDA within laboratory and operational centers at both the short-term, subseasonal and long-term, climate time scales. Three of the sessions (3, 4, and 5) addressed new algorithmic approaches to CDA at high resolution. Session 6 focused on the computational science solutions for the management of large input/output streams required to carry out the assimilation procedure.

54 ENVIRONMENTAL SCIENCES↗

Exploring the Relative Importance of the MJO and ENSO to North Pacific Subseasonal Predictability

Abstract Here we explore the relative contribution of the Madden‐Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO) to midlatitude subseasonal predictive skill of upper atmospheric circulation over the North Pacific, using an inherently interpretable neural network applied to pre‐industrial control runs of the Community Earth System Model version 2. We find that this interpretable network generally favors the state of ENSO, rather than the MJO, to make correct predictions on a range of subseasonal lead times and predictand averaging windows. Moreover, the predictability of positive circulation anomalies over the North Pacific is comparatively lower than that of their negative counterparts, especially evident when the ENSO state is important. However, when ENSO is in a neutral state, our findings indicate that the MJO provides some predictive information, particularly for positive anomalies. We identify three distinct evolutions of these MJO states, offering fresh insights into opportune forecasting windows for MJO teleconnections.

58 GEOSCIENCES↗

Effects of Southeastern Pacific Sea Surface Temperature on the Double-ITCZ Bias in NCAR CESM1

The double intertropical convergence zone (ITCZ) is a long-standing bias in the climatology of coupled general circulation models (CGCMs). The warm biases in southeastern Pacific (SEP) sea surface temperature (SST) are also evident in many CGCMs. In this study, the role of SEP SST in the double ITCZ is investigated by prescribing the observed SEP SST in the Community Earth System Model, version 1 (CESM1). Both the double ITCZ and dry equator problems are significantly improved with SEP SST prescribed. Both atmospheric and oceanic processes are involved in the improvements. The colder SST over the SEP decreases the precipitation, which enhances the southeasterly winds outside the prescribed SST region, cooling the ocean via increased evaporation. The enhanced descending motion over the SEP strengthens the Walker circulation. The easterly winds over the equatorial Pacific enhance upwelling and shoal the thermocline over the eastern Pacific. The changes of surface wind and wind curl lead to a weaker South Equatorial Countercurrent and stronger South Equatorial Current, preventing the warm water from expanding eastward, thereby improving both the double ITCZ and dry equator. The enhanced Walker circulation also increases the low-level wind convergence and reduces the wind speed in the tropical western Pacific, leading to warmer SST and stronger convection there. The stronger convection in turn leads to more cloud and reduces the incoming solar radiation, cooling the SST. These competing effects between radiative heat flux and latent heat flux make the atmospheric heat flux secondary to the ocean dynamics in the western Pacific warming.

54 ENVIRONMENTAL SCIENCES↗

Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.

Community Multi-scale Air Quality (CMAQ) model↗

Impacts of Climate Change and Vegetation Dynamics on Runoff in the Mountainous Region of the Haihe River Basin in the Past Five Decades

Climate and atmospheric CO2 concentration have changed significantly in the mountainous region of the Haihe River basin over the past five decades. In the study, a process-based terrestrial model, version 4 of the Community Land Model (CLM4), was used to quantify the spatiotemporal changes in runoff over the region, driven by the varying climate factors and CO2 concentration. Overall, our simulations suggest that climate-induced change in runoff in this region show a decreasing trend since 1960. Changes in precipitation, solar radiation, air temperature, and wind speed accounts for 56%, -14%, 13%, -5% of the overall decrease in annual runoff, respectively, but their relative contributions vary across the study area. Rising atmospheric CO2 concentration was found to have limited impacts on runoff. Significant decrease in runoff over the southern and northeastern portion of the region is primarily attributed to decreasing precipitation, while decreasing solar radiation and increasing air temperature are the main causes of slight runoff increase in the northern portion. Our results also suggest that the magnitude of decreasing trend could be greatly underestimated if the dynamical interactions of vegetation phenology with the environmental factors are not considered in the modeling, highlighting the importance of including dynamic vegetation phenology in the prediction of runoff in this region.

basin↗

Technical note: 3-hourly temporal downscaling of monthly global terrestrial biosphere model net ecosystem exchange

Here, the land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO 2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO 2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5° × 0.5°, 2.0° × 2.5°, and 4.0° × 5.0° (latitude × longitude).

54 ENVIRONMENTAL SCIENCES↗

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density (Fig 1). Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

Luvall, J. C.↗

Machine Learning-Based Atmospheric Phenomena Detection Platform

As the number of Earth pointing satellites has increased over the last several decades, the data volume retrieved from instruments onboard these satellites has also increased. It is expected that this trend will continue as more data intensive missions and small satellite constellations are launched. Currently, feature detection - namely atmospheric phenomena - in these datasets is performed manually and is thus not scalable with the growing data archives. Recent advancements in computational efficiency allow for the Earth science community to leverage machine learning to identify interesting atmospheric phenomena. Given the wide range of distinctive features in various atmospheric phenomena, a specialized machine learning model is required for accurate detection of these phenomena independently. The Phenomena Portal, developed at NASA IMPACT, is designed to provide visualization for the output from these machine learning models. In addition, detected events for each atmospheric phenomena are stored in a database that can be used to more easily use/subset larger spatiotemporal datasets. The user interface also incorporates additional features to enhance the user experience including spatiotemporal analysis, multiple base layer images, and a slider to filter events with lower probabilities of positive detection. Each detection supports user feedback on whether the detection is true or false that can then be stored and used to improve the machine learning model performance.

Gurung, Iksha↗

Measuring He i Stark Line Shapes in the Laboratory to Examine Differences in Photometric and Spectroscopic DB White Dwarf Masses

Abstract Accurate helium White Dwarf (DB) masses are critical for understanding the star’s evolution. DB masses derived from the spectroscopic and photometric methods are inconsistent. Photometric masses agree better with currently accepted DB evolutionary theories and are mostly consistent across a large range of surface temperatures. Spectroscopic masses rely on untested He i Stark line-shape and Van der Waals broadening predictions, show unexpected surface temperature trends, and are thus viewed as less reliable. To test this conclusion, we present in this paper detailed He i Stark line-shape measurements at conditions relevant to DB atmospheres ( T electron ≈12,000–17,000 K, n electron ≈ 10 17 cm −3 ). We use X-rays from Sandia National Laboratories’ Z -machine to create a uniform ≈120 mm long hydrogen–helium mixture plasma. Van der Waals broadening is negligible at our experimental conditions, allowing us to measure He i Stark profiles only. H β , which has been well-studied in our platform and elsewhere, serves as the n e diagnostic. We find that He i Stark broadening models used in DB analyses are accurate within errors at tested conditions. It therefore seems unlikely that line-shape models are solely responsible for the observed spectroscopic mass trends. Our results should motivate the WD community to further scrutinize the validity of other spectroscopic and photometric input parameters, like atmospheric structure assumptions and convection corrections. These parameters can significantly change the derived DB mass. Identifying potential weaknesses in any input parameters could further our understanding of DBs, help elucidate their evolutionary origins, and strengthen confidence in both spectroscopic and photometric masses.

Schaeuble, M. -A. (ORCID:0000000188695203)↗

Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Altogether, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗