Investigating Controls on the Isotopic Composition of Precipitation in the Continental United States using Numerical Tracers in the Community Earth System Model
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Earth Sciences↗
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Modeling microbial carbon fluxes and stocks in global soils from 1901 to 2016
Abstract. Soil microbes play a crucial role in the carbon (C) cycle; however, they have been overlooked in predicting the terrestrial C cycle. We applied a microbial-explicit Earth system model – the Community Land Model-Microbe (CLM-Microbe) – to investigate the dynamics of soil microbes during 1901 to 2016. The CLM-Microbe model was able to reproduce the variations of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR) and soil (SR) respiration, microbial (MBC) biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, and dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m during 1901–2016. During the study period, simulated C variables increased by approximately 12 PgC yr−1 for HR, 25 PgC yr−1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0–30 cm, and 1.2 PgC for FBC and 0.7 PgC for BBC in 0–1 m. Increases in microbial C fluxes and pools were widely found, particularly at high latitudes and in equatorial regions, but we also observed their decreases in some grids. Overall, the area-weighted averages of HR, SR, FBC, and BBC in the top 1 m were significantly correlated with those of soil moisture and soil temperature in the top 1 m. These results suggested that microbial C fluxes and pools were jointly governed by vegetation C input and soil temperature and moisture. Our simulations revealed the spatial and temporal patterns of microbial C fluxes and pools in response to environmental change, laying the foundation for an improved understanding of soil microbial roles in the global terrestrial C cycle.
He, Liyuan↗
Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model
Abstract. We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50° S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr-1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr-1). The contrast in contribution from the Southern Ocean, 102 Gt yr-1, is even more significant compared to the interannual variability of 35 Gt yr-1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.
54 ENVIRONMENTAL SCIENCES↗
Statistical emulation of a perturbed basal melt ensemble of an ice sheet model to better quantify Antarctic sea level rise uncertainties
Abstract. Antarctic ice shelves are vulnerable to warming ocean temperatures, and some have already begun thinning in response to increased basal melt rates. Sea level is therefore expected to rise due to Antarctic contributions, but uncertainties in its amount and timing remain largely unquantified. In particular, there is substantial uncertainty in future basal melt rates arising from multi-model differences in thermal forcing and how melt rates depend on that thermal forcing. To facilitate uncertainty quantification in sea level rise projections, we build, validate, and demonstrate projections from a computationally efficient statistical emulator of a high-resolution (4 km) Antarctic ice sheet model, the Community Ice Sheet Model version 2.1. The emulator is trained to a large (500-member) ensemble of 200-year-long 4 km resolution transient ice sheet simulations, whereby regional basal melt rates are perturbed by idealized (yet physically informed) trajectories. The main advantage of our emulation approach is that by sampling a wide range of possible basal melt trajectories, the emulator can be used to (1) produce probabilistic sea level rise projections over much larger Monte Carlo ensembles than are possible by direct numerical simulation alone, thereby providing better statistical characterization of uncertainties, and (2) predict the simulated ice sheet response under differing assumptions about basal melt characteristics as new oceanographic studies are published, without having to run additional numerical ice sheet simulations. As a proof of concept, we propagate uncertainties about future basal melt rate trajectories, derived from regional ocean models, to generate probabilistic sea level rise estimates for 100 and 200 years into the future.
97 MATHEMATICS AND COMPUTING↗
CLM5 CAMELS Basins Ensemble
Land surface models such as Community Land Model Version 5 (CLM5) are essential tools for simulating the behaviors of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrologic parameters and the implications that these uncertainties have on water resources applications. To address this long-standing issue, we conduct a comprehensive hydrologic parameter uncertainty characterization (UC) of CLM5 over the hydroclimatic gradients of the Conterminous United States using five meteorological datasets. Key datasets produced from the UC experiment include a benchmark dataset of CLM5 default hydrological performance, parameter sensitivity identified for 28 hydrological metrics, and large ensemble outputs for hydrological predictions. The presented datasets can assist CLM5 calibration and to support broad applications such as evaluating vulnerabilities to droughts and floods. The dataset can be used to identify under what hydroclimate conditions parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how land runoff uncertainties interact with other Earth system processes. Please refer to the included README.pdf for a description of the included files. Note that raw CLM5 model outputs for each forcing dataset are hosted on a Globus endpoint: https://app.globus.org/file-manager?destination_id=d22ef858-27b0-11ed-a910-fd3165076336.
Yan, Hongxiang↗
CLM5 CAMELS Basins Ensemble
Land surface models such as Community Land Model Version 5 (CLM5) are essential tools for simulating the behaviors of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrologic parameters and the implications that these uncertainties have on water resources applications. To address this long-standing issue, we conduct a comprehensive hydrologic parameter uncertainty characterization (UC) of CLM5 over the hydroclimatic gradients of the Conterminous United States using five meteorological datasets. Key datasets produced from the UC experiment include a benchmark dataset of CLM5 default hydrological performance, parameter sensitivity identified for 28 hydrological metrics, and large ensemble outputs for hydrological predictions. The presented datasets can assist CLM5 calibration and to support broad applications such as evaluating vulnerabilities to droughts and floods. The dataset can be used to identify under what hydroclimate conditions parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how land runoff uncertainties interact with other Earth system processes. Please refer to the README.pdf for a description of the included files. Note that raw CLM5 model outputs for each forcing dataset are hosted on a Globus endpoint: https://app.globus.org/file-manager?destination_id=d22ef858-27b0-11ed-a910-fd3165076336.
Yan, Hongxiang↗
Forced Patterns of Sea Level Rise in the Community Earth System Model Large Ensemble From 1920 to 2100
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John T. Fasullo↗
Characteristics of stratosphere-troposphere exchange in a general circulation model
In this study we examine mass exchange, water vapor exchange, and the behavior of idealized tracers and parcels to diagnose Stratosphere-Troposphere Exchange (STE) in the National Center for Atmospheric Research (NCAR) General Circulation Model (GCM), the Community Climate Model (CCM2). The CCM2 correctly represents the seasonality of mass exchange across 100 hPa, but values are uniformly too strong. Water vapor, however, indicates that tropical STE is not well represented in the CCM2; even though mean tropopause temperatures are colder than observed, the lower stratosphere is too moist. Most net mass flux occurs at water vapor mixing ratios of about 4-5 parts per million by volume (ppmv), about 1 ppmv too moist. Vertical resolution has little impact on the nature of tropical STE. In midlatitudes, CCM2 more successfully represents STE, which occurs in developing baroclinic waves and stationary anticyclones. Exchange from troposphere to stratosphere does occur but only influences the lowest few kilometers of the extratropical stratosphere, even for tracers with large vertical gradients.
Mote, Philip W.↗
Sensitivity of the Tropical Atmospheric Energy Balance to ENSO-Related SST Changes: Comparison of Climate Model Simulations to Observed Responses
This paper focuses on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. While this natural perturbation to climate is quite distinct from possible anthropogenic changes in climate, adjustments in the tropical water and energy budgets during ENSO may give insight into feedback processes involving water vapor and cloud feedbacks. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). In a companion paper we have presented observational analyses, based principally on space-based measurements which document systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes. Here we analyze several contemporary climate models run with observed SSTs over recent decades and compare SST-induced changes in radiation, precipitation, evaporation, and energy transport to observational results. Among these are the NASA / NCAR Finite Volume Model, the NCAR Community Climate Model, the NCEP Global Spectral Model, and the NASA NSIPP Model. Key disagreements between model and observational results noted in the recent literature are shown to be due predominantly to observational shortcomings. A reexamination of the Langley 8-Year Surface Radiation Budget data reveals errors in the SST surface longwave emission due to biased SSTs. Subsequent correction allows use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative heating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 W/sq m per K of SST change. Model results agree reasonably well with this estimate of sensitivity. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. There remain, however, significant quantitative uncertainties in cloud forcing changes in the models as compared to observations. These differences are examined in relationship to model convection and cloud parameterizations Analysis of the possible sampling and measurement errors compared to systematic model errors is also presented.
Robertson, Franklin R.↗
A Two-Habit Ice Cloud Optical Property Parameterization for GCM Application
We present a novel ice cloud optical property parameterization based on a two-habit ice cloud model that has been proved to be optimal for remote sensing applications. The two-habit ice model is developed with state-of-the-art numerical methods for light scattering property calculations involving individual columns and column aggregates with the habit fractions constrained by in-situ measurements from various field campaigns. Band-averaged bulk ice cloud optical properties including the single-scattering albedo, the mass extinction/absorption coefficients, and the asymmetry factor are parameterized as functions of the effective particle diameter for the spectral bands involved in the broadband radiative transfer models. Compared with other parameterization schemes, the two-habit scheme generally has lower asymmetry factor values (around 0.75 at the visible wavelengths). The two-habit parameterization scheme was widely tested with the broadband radiative transfer models (i.e. Rapid Radiative Transfer Model, GCM version) and global circulation models (GCMs, i.e. Community Atmosphere Model, version 5). Global ice cloud radiative effects at the top of the atmosphere are also analyzed from the GCM simulation using the two-habit parameterization scheme in comparison with CERES satellite observations.
Yi, Bingqi↗
Evaluating the Uncertainties in the Electron Temperature and Radial Speed Measurements Using White Light Corona Eclipse Observations
We examine the uncertainties in two plasma parameters from their true values in a simulated asymmetric corona. We use the Corona Heliosphere (CORHEL) and Magnetohydrodynamics Around the Sphere (MAS) models in the Community Coordinated Modeling Center (CCMC) to investigate the differences between an assumed symmetric corona and a more realistic, asymmetric one. We were able to predict the electron temperatures and electron bulk flow speeds to within +/-0.5 MK and +/-100 km s(exp−1), respectively, over coronal heights up to 5.0 R from Sun center.We believe that this technique could be incorporated in next-generation white-light coronagraphs to determine these electron plasma parameters in the low solar corona. We have conducted experiments in the past during total solar eclipses to measure the thermal electron temperature and the electron bulk flow speed in the radial direction in the low solar corona. These measurements were made at different altitudes and latitudes in the low solar corona by measuring the shape of the K-coronal spectra between 350 nm and 450 nm and two brightness ratios through filters centered at 385.0 nm/410.0 nm and 398.7 nm/423.3 nm with a bandwidth of is approximately equal to 4 nm. Based on symmetric coronal models used for these measurements, the two measured plasma parameters were expected to represent those values at the points where the lines of sight intersected the plane of the solar limb.
corona↗
The Signature of Ozone Depletion in Recent Antarctic Precipitation Change: A Study with the Community Earth System Model
Although precipitation is a primary control on Antarctic ice sheet (AIS) mass balance, long-term historical AIS precipitation trends and their underlying external climate drivers remain inconclusive. In this study, we use a novel pair of climate model ensembles to identify a simulated spatial signature of ozone depletion-forced AIS precipitation change. Distinct areas of little change or precipitation decrease, arising from interaction between ozone depletion-forced atmospheric circulation changes and ice sheet topography, are outweighed by large-scale precipitation increases. This signature bears notable similarities to a new ice core-based reconstruction of AIS accumulation change and yields a significant increase in annual integrated precipitation (38 ± 10 Gt/year over the 1986–2005 period or 51 ± 11 Gt/year over the 1991–2005 period). Remarkably, this simulated ozone depletion-forced precipitation change is of a similar absolute magnitude to recent observed AIS mass loss trends and as a consequence, it may play a role in dampening recent AIS sea level rise contributions.
Lenaerts, Jan T. M.↗
Impact of Dust Aerosols on Simulated Infrared Radiances Within the Community Radiative Transfer Model (CRTM)
No abstract available
Naeger, Aaron↗
Influence of Sea-Ice Anomalies on Antarctic Precipitation Using Source Attribution in the Community Earth System Model
We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50∘ S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr−1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr−1). The contrast in contribution from the Southern Ocean, 102 Gt yr−1, is even more significant compared to the interannual variability of 35 Gt yr−1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.
Wang, Hailong↗
Long Term Stability Monitoring of Aqua MODIS Thermal Emissive Bands through Radiative Transfer Modeling
Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua has been in operation providing continuous global observations for science research and applications since 2002. The long-term stability of thermal emissive bands (TEBs) of Aqua MODIS was monitored through inter-comparisons with measurements by hyperspectral infrared sensors, such as AIRS on Aqua and IASI on MetOp satellite, or through long term vicarious monitoring over cold targets, such as Dome- C and deep convective clouds (DCC). In this paper, a radiative transfer modeling-based simulation model using Community Radiative Transfer Model (CRTM) is developed to perform the long-term monitoring of the stability of TEBs of Aqua MODIS. CRTM is a fast-radiative transfer model for calculations of radiances for satellite infrared radiometers and is able to output infrared radiance and brightness temperature at spectral bands of MODIS. Long term European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis data, such as temperature and humidity profiles, are used as inputs to the CRTM simulation. By confining the area of interest to be over low to middle latitude ocean, the long-term stabilities of selected Aqua MODIS TEBs are monitored through Observation–Background (O-B) brightness temperature (BT) bias between MODIS measurements and BT retrieval from CRTM simulation. The consistency and relative stability between Aqua MODIS and ECMWF reanalysis data for surface channels of MODIS are evaluated. In addition, the radiative transfer modeling with CRTM enables us to evaluate the impacts of long term variation of global CO2 distribution on the O-B BT biases for CO2 channels of Aqua MODIS through comparison of simulations with constant or long term variable CO2 as inputs. The O-B analysis with RTM show that Aqua MODIS surface channels are all radiometrically stable with yearly BT bias drift less than 0.004K/year for B20, B22, B23 and ~0.01K/year for B31 and B32. The CO2 absorption channels of Aqua MODIS, e.g. B33-B36, are stable with BT bias drift < 0.005K/year.
MODIS↗
Implementation of a New Scattering Database and a Radar Simulator into Community Radiative Transfer Model
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Isaac Moradi↗
Community Radiative Transfer Model: Implementing A New Cloud Scattering Database and Developing the Forward Radar Module
The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promises in calculating the scattering properties of particles with different shapes in the microwave frequencies. The goal of the research was to enhance the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. Given that such optical properties cannot be practically calculated on the fly, pre-computed look-up tables need to be implemented into the fast RT models to calculate the scattering properties of these particles using the DDA technique and the inputs provided by the users. Therefore, we implemented such pre-computed DDA databases into CRTM. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system will be used to evaluate the scattering improvements. Additionally, we used the backscattering information from the DDA database to implement a radar simulator into CRTM. The radar operators takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.
Isaac Moradi↗
An Evaluation of A Physics-Based Firn Model and A Semi-Empirical Firn Model Across the Greenland Ice Sheet (1980–2020)
The Greenland Ice Sheet's (GrIS) firn layer buffers the ice sheet's contribution to sea level rise by storing meltwater in its pore space. However, available pore space and meltwater retention capability is lost due to ablation of the firn layer and refreezing of meltwater as near-surface ice slabs in the firn. Understanding how firn properties respond to climate is important for constraining the GrIS's future contribution to sea level rise in a warming climate. Observations of firn density provide detailed information about firn properties, but they are spatially and temporally limited. Here we use two firn models, the physics-based SNOWPACK model and the Community Firn Model configured with a semi-empirical densification equation (CFM-GSFC), to quantify firn properties across the GrIS from 1980 through 2020. We use an identical forcing (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) atmospheric reanalysis) for SNOWPACK and the CFM-GSFC in order to isolate firn model differences. To evaluate the models, we compare simulated firn properties, including firn air content (FAC), to measurements from the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset of snow and firn density. Both models perform well (mean absolute percentage errors of 14 % in SNOWPACK and 16 % in the CFM-GSFC), though their performance is hindered by the spatial resolution of the atmospheric forcing. In the ice-sheet-wide simulations, the 1980–1995 average spatially integrated FAC (i.e., air volume in the firn) for the upper 100 m is 34 645 km 3 from SNOWPACK and 28 581 km 3 from the CFM-GSFC. The discrepancy in the magnitude of the modeled FAC stems from differences in densification with depth and variations in the sensitivity of the models to atmospheric forcing. In more recent years (2005–2020), both models simulate substantial depletion of pore space. During this period, the spatially integrated FAC across the entire GrIS decreases by 3.2 % (−66.6 km 3 yr −1 ) in SNOWPACK and 1.5 % (−17.4 km 3 yr −1 ) in the CFM-GSFC. These differing magnitudes demonstrate how model differences propagate throughout the FAC record. Over the full modeled record (1980–2020), SNOWPACK simulates a loss of pore space equivalent to 3 mm of sea level rise buffering, while the CFM-GSFC simulates a loss of 1 mm. The greatest depletion in FAC is along the margins and especially along the western margin where observations and models show the formation of near-surface, low-permeability ice slabs that may inhibit meltwater storage.
Megan Thompson-Munson↗