ALBERT

Description: Anisotropy of turbulence near the top of the stratocumulus-topped boundary layer (STBL) is studied using large-eddy simulation (LES) and measurements from the POST and DYCOMS-II field campaigns. Focusing on turbulence ∼100°m below the cloud top, we see remarkable similarity between daytime and nocturnal flight data covering different inversion strengths and free-tropospheric conditions. With λ denoting wavelength and z t cloud-top height, we find that turbulence at λ / z t ≃ 0.01 is weakly dominated by horizontal fluctuations, while turbulence at λ / z t  〉 1 becomes strongly dominated by horizontal fluctuations. Between are scales at which vertical fluctuations dominate. Typical-resolution LES of the STBL (based on POST flight 13 and DYCOMS-II flight 1) captures observed characteristics of below-cloud-top turbulence reasonably well. However, using a fixed vertical grid spacing of 5 m, decreasing the horizontal grid spacing and increasing the subgrid-scale mixing length leads to increased dominance of vertical fluctuations, increased entrainment velocity and decreased liquid water path. Our analysis supports the notion that entrainment parametrizations (e.g. in climate models) could potentially be improved by accounting more accurately for anisotropic deformation of turbulence in the cloud-top region. While LES has the potential to facilitate improved understanding of anisotropic cloud-top turbulence, sensitivity to grid spacing, grid-box aspect ratio, and subgrid-scale model needs to be addressed.

Description: Many conventional General Circulation Models (GCMs) in the Global Land–Atmosphere Coupling Experiment (GLACE) tend to produce what is now recognized as overly strong Land–Atmosphere (L–A) coupling. We investigate the effects of cloud Superparameterization (SP) on L–A coupling on timescales beyond diurnal where it has been recently shown to have a favorable muting effect hydrologically. Using the Community Atmosphere Model v3.5 (CAM3.5) and its Superparameterized counterpart SPCAM3.5, we conducted soil moisture interference experiments following the GLACE and Atmospheric Model Intercomparison Project (AMIP) protocols. The results show that, on weekly-to-subseasonal timescales, SP also mutes hydrologic L–A coupling. This is detectable globally, and happens through the evapotranspiration–precipitation segment. But on seasonal timescales, SP does not exhibit detectable effects on hydrologic L–A coupling. Two robust regional effects of SP on thermal L–A coupling have also been explored. Over the Arabian Peninsula, SP reduces thermal L–A coupling through a straightforward control by mean rainfall reduction. More counterintuitively, over the Southwestern US and Northern Mexico, SP enhances the thermal L–A coupling in a way that is independent of rainfall and soil moisture. This signal is associated with a systematic and previously unrecognized effect of SP that produces an amplified Bowen ratio, and is detectable in multiple SP model versions and experiment designs. In addition to amplifying the present-day Bowen ratio, SP is found to amplify the climate sensitivity of Bowen ratio as well, which likely plays a role in influencing climate change predictions at the L–A interface.

Description: A Single Column Model (SCM) approach is used to assess the CNRM climate model (CNRM-CM) version 6 ability to represent the properties of the apparent heat source ( Q 1 ) and moisture sink ( Q 2 ) as observed during the 3-month CINDY2011/DYNAMO field campaign, over its Northern Sounding Array (NSA). The performance of the CNRM SCM is evaluated in a constrained configuration in which the latent and sensible heat surface fluxes are prescribed, as, when forced by observed sea surface temperature, the model is strongly limited by the underestimate of the surface fluxes, most probably related to the SCM forcing itself. The model exhibits a significant cold bias in the upper troposphere, near 200 hPa, and strong wet biases close to the surface and above 700 hPa. The analysis of the Q 1 and Q 2 profile distributions emphasizes the properties of the convective parameterization of the CNRM-CM physics. The distribution of the Q 2 profile is particularly challenging. The model strongly underestimates the frequency of occurrence of the deep moistening profiles, which likely involve misrepresentation of the shallow and congestus convection. Finally, a statistical approach is used to objectively define atmospheric regimes and construct a typical convection life cycle. A composite analysis shows that the CNRM SCM captures the general transition from bottom- to mid- to top-heavy convective heating. Some model errors are shown to be related to the stratiform regimes. The moistening observed during the shallow and congestus convection regimes also requires further improvements of this CNRM-CM physics.

Description: Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012 to 2014 in which two different OICs are utilised. With respect to first experiment (CTRL) second experiment (AcSAL) differs by two aspects: usage of high resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This reduction is consistently apparent in each month and it is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulted better representation of monsoon circulation and moisture transport. This reduced bias of troposphere moisture and temperature over the Indian land mass and also produced better troposphere temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction.

Description: Atmospheric water-vapor isotopes have been proposed as a potentially powerful constraint on convection, which plays a critical role in Earth's present and future climate. It is shown here, however, that the mean tropical profile of HDO in the free troposphere does not usefully constrain the mean convective entrainment rate or precipitation efficiency. This is demonstrated using a single-column analytical model of atmospheric water isotopes. The model has three parameters: the entrainment rate, the precipitation efficiency, and the distance that evaporating condensates fall. At a given relative humidity, the possible range of HDO is small: its range is comparable to both the measurement uncertainty in the mean tropical profile and the structural uncertainty of a single-column model. Therefore, the mean tropical HDO profile is unlikely to add information about convective processes in a bulk-plume framework that cannot already be learned from relative humidity alone.

Description: A set of idealized experiments are developed using the Community Atmosphere Model (CAM) to understand the vertical velocity response to reductions in forcing scale that is known to occur when the horizontal resolution of the model is increased. The test consists of a set of rising bubble experiments, in which the horizontal radius of the bubble and the model grid spacing are simultaneously reduced. The test is performed with moisture, through incorporating moist physics routines of varying complexity, although convection schemes are not considered. Results confirm that the vertical velocity in CAM is to first-order, proportional to the inverse of the horizontal forcing scale, which is consistent with a scale-analysis of the dry equations of motion. In contrast, experiments in which the coupling time-step between the moist physics routines and the dynamical core (i.e., the ‘physics' time-step) are relaxed back to more conventional values results in severely damped vertical motion at high resolution, degrading the scaling. A set of aqua-planet simulations using different physics time-steps are found to be consistent with the results of the idealized experiments.

Description: Most regional three-dimensional chemical transport models neglect gaseous elemental mercury (GEM) oxidation by bromine (Br) radicals and Br chemistry. In this study the Community Multiscale Air Quality model with its default mercury module (CMAQ-Hg) was modified by implementing a state-of-the-art algorithm depicting Hg reactions coupled with Br chemistry (CMAQ-newHg-Br). Using CMAQ-newHg-Br with initial and boundary concentrations (ICs and BCs) from global model output, we conducted simulations for the northeastern United States over March-November 2010. Simulated GEM mixing ratios were predominantly influenced by BCs and hence reflected significant seasonal variation that was captured in the global model output as opposed to a lack of seasonal variation using CMAQ-Hg's default constant BCs. Observed seasonal percentage changes (i.e. seasonal amplitude (=maximum – minimum) in percentage of the seasonal average) of gaseous oxidized mercury (GOM) and particulate bound mercury (PBM) were 76% and 39%, respectively. CMAQ-newHg-Br significantly improved the simulated seasonal changes in GOM and PBM to 43% and 23%, respectively, from 18% and 16% using CMAQ-Hg. CMAQ-newHg-Br reproduced observed Hg wet deposition with a remarkably low fractional bias (FB) (0.4%) as opposed to a -56% – 19% FB for CMAQ-Hg simulations. Simulated Hg dry deposition using CMAQ-newHg-Br excluding the GEM+OH reaction agreed well with studies using inferential methods and litterfall/throughfall measurements, and the discrepancy varied over 13% - 42%. This study demonstrated the promising capability of CMAQ-newHg-Br to reproduce observed concentrations and seasonal variations of GEM, GOM and PBM, and Hg wet and dry deposition fluxes.

Description: Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection—such as that they adjust instantaneously to changes in resolved-scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up- and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up- and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.

Description: An explicit prognostic cloud cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low-, high- and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850hPa and above 400hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Description: In Part II of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part I. Part II provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

Description: In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part I, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode – with prescribed sea surface temperatures (SSTs) and sea ice distribution – is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part II, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.

Description: The adjoint method is used to calibrate the medium complexity climate model “Planet Simulator” through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in non-linear coupled climate models.

Description: A decadal climate prediction system named as IAP-DecPreS was constructed in the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, based on a fully coupled model FGOALS-s2 and a newly developed initialization scheme, referred to as EnOI-IAU. In this paper, we introduce the design of the EnOI-IAU scheme, assess the accuracies of initialization integrations using the EnOI-IAU and preliminarily evaluate hindcast skill of the IAP-DecPreS. The EnOI-IAU scheme integrates two conventional assimilation approaches, ensemble optimal interpolation (EnOI) and incremental analysis update (IAU). The EnOI and IAU were applied to calculate analysis increments and incorporate them into the model, respectively. Three continuous initialization (INIT) runs were conducted for the period of 1950-2015, in which observational sea surface temperature (SST) from the HadISST1.1 and subsurface ocean temperature profiles from the EN4.1.1 dataset were assimilated. Then nine-member ten-year-long hindcast runs initiated from the INIT runs were conducted for each year in the period of 1960-2005. The accuracies of the INIT runs are evaluated from the following three aspects: upper-700m ocean temperature, temporal evolution of SST anomalies and dominant interdecadal variability modes, Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO). Finally, preliminary evaluation of the ensemble mean of the hindcast runs suggests that the IAP-DecPreS has skill in the prediction of the PDO-related SST anomalies in the mid-latitude North Pacific and AMO-related SST anomalies in the tropical North Atlantic.

Description: Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980-2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved.

Description: Key developments have been made to the NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X). Among them the most important are the self-consistent solution of global electrodynamics, and transport of O + in the F-region. Other ionosphere developments include time-dependent solution of electron/ion temperatures, metastable O + chemistry, and high-cadence solar EUV capability. Additional developments of the thermospheric components are improvements to the momentum and energy equation solvers to account for variable mean molecular mass and specific heat, a new divergence damping scheme, and cooling by O( 3 P) fine structure. Simulations using this new version of WACCM-X (2.0) have been carried out for solar maximum and minimum conditions. Thermospheric composition, density, and temperatures are in general agreement with measurements and empirical models, including the equatorial mass density anomaly and the midnight density maximum. The amplitudes and seasonal variations of atmospheric tides in the mesosphere and lower thermosphere are in good agreement with observations. Although global mean thermospheric densities are comparable with observations of the annual variation, they lack a clear semi-annual variation. In the ionosphere, the low-latitude E×B drifts agree well with observations in their magnitudes, local time dependence, seasonal, and solar activity variations. The pre-reversal enhancement in the equatorial region, which is associated with ionospheric irregularities, displays patterns of longitudinal and seasonal variation that are similar to observations. Ionospheric density from the model simulations reproduces the equatorial ionosphere anomaly structures, and is in general agreement with observations. The model simulations also capture important ionospheric features during storms.

Description: The impacts of air–sea interactions on the representation of tropical precipitation extremes are investigated using an atmosphere–ocean-mixed-layer coupled model. The coupled model is compared to two atmosphere-only simulations driven by the coupled model sea-surface temperatures (SSTs): one with 31-day running means (31d), the other with a repeating mean annual cycle. This allows separation of the effects of inter-annual SST variability from those of coupled feedbacks on shorter timescales. Crucially, all simulations have a consistent mean state with very small SST biases against present-day climatology. 31d overestimates the frequency, intensity and persistence of extreme tropical precipitation relative to the coupled model, likely due to excessive SST-forced precipitation variability. This implies that atmosphere-only attribution and time-slice experiments may overestimate the strength and duration of precipitation extremes. In the coupled model, air–sea feedbacks damp extreme precipitation, through negative local thermodynamic feedbacks between convection, surface fluxes and SST.

Description: In mesoscale and global atmospheric simulations with large horizontal domains, strong horizontal flow across the grid is often unavoidable, but its effects on cloud-topped boundary layers has received comparatively little study. Here the effects of cross-grid flow on large-eddy simulations of stratocumulus and trade-cumulus marine boundary layers are studied across a range of grid resolutions (horizontal x vertical) between 500m x 20m and 35m x 5m. Three cases are simulated: DYCOMS nocturnal stratocumulus, BOMEX trade cumulus, and a GCSS stratocumulus-to-trade cumulus case. Simulations are performed with a stationary grid (with 4-8 m/s horizontal winds blowing through the cyclic domain) and a moving grid (equivalent to subtracting off a fixed vertically uniform horizontal wind) approximately matching the mean boundary-layer wind speed. For stratocumulus clouds, cross-grid flow produces two primary effects on stratocumulus clouds: a filtering of fine scale resolved turbulent eddies, which reduces stratocumulus cloud-top entrainment and a vertical broadening of the stratocumulus-top inversion which enhances cloud-top entrainment. With a coarse (20 m) vertical grid, the former effect dominates and leads to strong increases in cloud cover and LWP, especially as horizontal resolution is coarsened. With a finer (5m) vertical grid, the latter effect is stronger and leads to small reductions in cloud cover and LWP. For the BOMEX trade cumulus case, cross grid flow tends to produce fewer and larger clouds with higher LWP, especially for coarser vertical grid spacing. The results presented are robust to choice of advection scheme and Courant number.

Description: Precipitation changes the physiological characteristics of an ecosystem. Because land-surface models are often used to project changes in the hydrological cycle, modeling the effect of precipitation on the latent heat flux λE is an important aspect of land-surface models. Here, we contrast conditionally-sampled diel composites of the eddy-covariance fluxes from the Niwot Ridge Subalpine Forest AmeriFlux tower with the Community Land Model (CLM, version 4.5). With respect to measured λE during the warm-season: for the day following above-average precipitation, λE was enhanced at mid-day by ≈ 40 W m −2 (relative to dry conditions), and nocturnal λE increased from ≈ 10 W m −2 in dry conditions to over 20 W m −2 in wet conditions. With default settings, CLM4.5 did not successfully model these changes. By increasing the amount of time that rainwater was retained by the canopy/needles, CLM was able to match the observed mid-day increase in λE on a dry day following a wet day. Stable nighttime conditions were problematic for CLM4.5. Nocturnal CLM λE had only a small (≈ 3 W m −2 ) increase during wet conditions, CLM nocturnal friction velocity u * was smaller than observed u * , and CLM canopy air temperature was 2 °C less than those measured at the site. Using observed u * as input to CLM increased λE ; however, this caused CLM λE to be increased during both wet and dry periods. We suggest that sloped topography and the ever-present drainage flow enhanced nocturnal u * and λE . Such phenomena would not be properly captured by topographically blind land-surface models, such as CLM.

Description: A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the non-equilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a non-linear function of convective cell area, then the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of serving as a non-equilibrium closure formulations for spectral mass flux parameterizations.

Description: Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of sub-grid scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is non-commutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the inter-model spread in phase 5 of the Coupled Model Inter-comparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of K-means clustering demonstrates that the positioning of macro-/micro- physics and shallow convection plays a critical role on the model solution.

Description: By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

Description: Ocean-Waves-Atmosphere (OWA) exchanges are not well represented in current Numerical Weather Prediction (NWP) systems, which can lead to large uncertainties in tropical cyclone track and intensity forecasts. In order to explore and better understand the impact of OWA interactions on tropical cyclone modelling, a fully coupled OWA system based on the atmospheric model Meso-NH, the oceanic model CROCO and the wave model WW3 and called MSWC was designed and applied to the case of tropical cyclone Bejisa (2013-2014). The fully coupled OWA simulation shows good agreement with the literature and available observations. In particular, simulated significant wave height is within 30 cm of measurements made with buoys and altimeters. Short-term (〈 2 days) sensitivity experiments used to highlight the effect of oceanic waves coupling showlimited impact on the track, the intensity evolution and the turbulent surface fluxes of the tropical cyclone. However, it is also shown that using a fully coupled OWA system is essential to obtain consistent sea salt emissions. Spatial and temporal coherence of the sea state with the 10m-wind speed are necessary to produce sea salt aerosol emissions in the right place (in the eyewall of the tropical cyclone) and with the right size distribution, which is critical for cloud microphysics.

Description: We present non-rotating simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM) in a square limited area domain over uniform sea surface temperature. As in previous studies, convection spontaneously aggregates into humid clusters, driven by a combination of radiative and moisture-convective feedbacks. The aggregation is qualitatively independent of resolution, with horizontal grid spacing from 3 km to 110 km, with both explicit and parameterized deep convection. A budget for the spatial variance of column moist static energy suggests that longwave radiative and surface flux feedbacks help establish aggregation, while the shortwave feedback contributes to its maintenance. Mechanism denial experiments confirm that aggregation does not occur without interactive longwave radiation. Ice cloud radiative effects help support the humid convecting regions, but are not essential for aggregation, while liquid clouds have a negligible effect. Removing the dependence of parameterized convection on tropospheric humidity reduces the intensity of aggregation, but does not prevent the formation of dry regions. In domain sizes less than (5000 km)2, the aggregation forms a single cluster, while larger domains develop multiple clusters. Larger domains initialized with a single large cluster are unable to maintain them, suggesting an upper size limit. Surface windspeed increases with domain size, implying that maintenance of the boundary layer winds may limit cluster size. As cluster size increases, large boundary layer temperature anomalies develop to maintain the surface pressure gradient, leading to an increase in the depth of parameterized convective heating and an increase in gross moist stability.

Description: The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10 – 35% for typical grid sizes (Δ = 12.5 – 100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of 7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

Description: Several improvements are implemented in the Zhang-McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST) and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long-standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

Description: Reliable estimates of historical and current biogeochemistry are essential for understanding past ecosystem variability and predicting future changes. Efforts to translate improved physical ocean state estimates into improved biogeochemical estimates, however, are hindered by high biogeochemical sensitivity to transient momentum imbalances that arise during physical data assimilation. Most notably, the breakdown of geostrophic constraints on data assimilation in equatorial regions can lead to spurious upwelling, resulting in excessive equatorial productivity and biogeochemical fluxes. This hampers efforts to understand and predict the biogeochemical consequences of El Niño and La Niña. We develop a strategy to robustly integrate an ocean biogeochemical model with an ensemble coupled-climate data assimilation system used for seasonal to decadal global climate prediction. Addressing spurious vertical velocities requires two steps. First, we find that tightening constraints on atmospheric data assimilation maintains a better equatorial wind stress and pressure gradient balance. This reduces spurious vertical velocities, but those remaining still produce substantial biogeochemical biases. The remainder is addressed by imposing stricter fidelity to model dynamics over data constraints near the equator. We determine an optimal choice of model-data weights that removed spurious biogeochemical signals while benefitting from off-equatorial constraints that still substantially improve equatorial physical ocean simulations. Compared to the unconstrained control run, the optimally constrained model reduces equatorial biogeochemical biases and markedly improves the equatorial subsurface nitrate concentrations and hypoxic area. The pragmatic approach described herein offers a means of advancing earth system prediction in parallel with continued data assimilation advances aimed at fully considering equatorial data constraints.

Description: A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multi-scale approach linking constituent behavior at the microscopic level—amongst ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a 2 nd order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.

Description: Precipitation is an important climate quantity that is critically relevant to society. In spite of intense efforts, significant precipitation biases remain in most climate models. One pervasive and persistent bias found in many general circulation models occurs in the Tropical West Pacific where northern hemisphere summer-time precipitation is often underestimated compared to observations. Using the DOE-E3SM model, the inclusion of a missing process, convective gustiness, is shown to reduce those biases through a net increase in surface evaporation. Gustiness in surface wind fields is assumed to arise empirically in proportion to the intensity of convective precipitation. The increased evaporation can be treated as an increase in the moist static energy forcing into the atmosphere. A Normalized Gross Moist Stability (NGMS) framework (which characterizes the relationship between convective forcing and convective response) is used to explore the processes responsible for the precipitation bias, and the impact of the gustiness parameterization in reducing that bias. Because the NGMS of the Tropical West Pacific is less than unity in the E3SMv1 model, the increase in energy forcing amplifies the increase in precipitation to exceed that of the evaporative flux. Convective gustiness favors increased precipitation in regions where the resolved surface winds are weak and convection is present.

Description: Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Description: High resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high resolution configurations of the Community Earth System Model (CESM). We performed a suite of high resolution, multi-decadal, global scale CESM simulations in which the atmosphere (∼0.25˚ grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high resolution coupled Earth system models, with important implications for TC-climate applications.

Description: A new statistical-dynamical model is developed for estimating the long-term hazard of rare, high impact tropical cyclones events globally. There are three components representing the complete storm lifetime: an environmental index-based genesis model, a beta-advection track model and an autoregressive intensity model. All three components depend upon the local environmental conditions, including potential intensity, relative sea surface temperature, 850 and 250 hPa steering flow, deep-layer mean vertical shear, 850 hPa vorticity, and midlevel relative humidity. The hazard model, using 400 realizations of a 32-year period (approximately 3000 storms per realization), captures many aspects of tropical cyclone statistics, such as genesis and track density distribution. Of particular note, it simulates the observed number of rapidly intensifying storms, a challenging issue in tropical cyclone modeling and prediction. Using the return period curve of landfall intensity as a measure of local tropical cyclone hazard, the model reasonably simulates the hazard in the western north Pacific (coastal regions of the Philippines, China, Taiwan, and Japan) and the Caribbean islands. In other regions, the observed return period curve can be captured after a local landfall frequency adjustment that forces the total number of landfalls to be the same as that observed while allowing the model to freely simulate the distribution of intensities at landfall.

Description: The accumulation of surface meltwater on ice shelves can lead to the formation of melt lakes. Melt lakes have been implicated in ice shelf collapse; Antarctica's Larsen B Ice Shelf was observed to have a large amount of surface melt lakes present preceding its collapse in 2002. Such collapse can affect ocean circulation and temperature, cause habitat loss and contribute to sea level rise through the acceleration of tributary glaciers. We present a mathematical model of a surface melt lake on an idealised ice shelf. The model incorporates a calculation of the ice shelf surface energy balance, heat transfer through the firn, the production and percolation of meltwater into the firn, the formation of ice lenses and the development and refreezing of surface melt lakes. The model is applied to the Larsen C Ice Shelf, where melt lakes have been observed. This region has warmed several times the global average over the last century and the Larsen C firn layer could become saturated with meltwater by the end of the century. When forced with weather station data, our model produces surface melting, meltwater accumulation, and melt lake development consistent with observations. We examine the sensitivity of lake formation to uncertain parameters, and provide evidence of the importance of processes such as lateral meltwater transport. We conclude that melt lakes impact surface melt and firn density and warrant inclusion in dynamic-thermodynamic models of ice shelf evolution within climate models, of which our model could form the basis for the thermodynamic component.

Description: Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the sub-cloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection and cloud microphysics tendencies.

Description: [1] Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes non-negligible contributions to the radiation balance of the Earth. However in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global non-hydrostatic atmospheric model with a double-moment cloud microphysics scheme. An offline radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m −2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories, and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper-level clouds.

Description: Low clouds strongly impact the radiation budget of the climate system, but their simulation in most GCMs has remained a challenge, especially over the subtropical stratocumulus region. Assuming a Gaussian distribution for the subgrid-scale total water and liquid water potential temperature, a new statistical cloud scheme is proposed and tested in NCAR Community Atmospheric Model version 5 (CAM5). The subgrid-scale variance is diagnosed from the turbulent and shallow convective processes in CAM5. The approach is able to maintain the consistency between cloud fraction and cloud condensate and thus alleviates the adjustment needed in the default relative humidity based cloud fraction scheme. Short-term forecast simulations indicate that low cloud fraction and liquid water content, including their diurnal cycle, are improved due to a proper consideration of subgrid-scale variance over the southeastern Pacific Ocean region. Compared with the default cloud scheme, the new approach produced the mean climate reasonably well with improved shortwave cloud forcing (SWCF) due to more reasonable low cloud fraction and liquid water path over regions with predominant low clouds. Meanwhile, the SWCF bias over the tropical land regions is also alleviated. Furthermore, the simulated marine boundary layer clouds with the new approach extend further offshore and agree better with observations. The new approach is able to obtain the top of atmosphere (TOA) radiation balance with a slightly alleviated double ITCZ problem in preliminary coupled simulations. This study implies that a close coupling of cloud processes with other subgrid-scale physical processes is a promising approach to improve cloud simulations.

Description: A total of three binary tropical cyclone (TC) cases over the west North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6-h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g. dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g. hybrid method) can be considered to overcome these limitations. This article is protected by copyright. All rights reserved.

Description: Closed-cell mesoscale organization and its relationship to entrainment and the properties of a low, non-precipitating stratocumulus cloud is investigated. Large eddy simulations were run over 10 periodic diurnal cycles during which mesoscale organization could fully develop and approach a quasi-steady state, on five domains sized from 2.4 km × 2.4 km to 38.4 km × 38.4 km. The four smaller domains hosted a single cell with an aspect ratio that increased with domain size. On the largest domain, mesoscale organization consisted of a cell population that evolved over the course of the diurnal cycle. It is found that with increasing cell aspect ratio, entrainment weakens and the boundary layer becomes shallower, cooler, moister, and more decoupled. This causes an increase in cloud water path and cloud radiative effect up to a cell aspect ratio of 16. With further increase in cell aspect ratio, circulation on the cell scale becomes less effective in supplying moisture to the cloud and in producing turbulent kinetic energy (TKE). This mechanism can explain scale saturation in closed-cell mesoscale organization. The simulations support a maximum stable aspect ratio of closed-cell mesoscale organization between 32 and 64, consistent with the observational limit of ≈40. The simulations show furthermore that entrainment does not, in general, scale with buoyant production of TKE. Instead, entrainment correlates with the vertical component of TKE. This implies vertical motion as a driver of entrainment, and a convective velocity scale based on the vertical component of TKE rather than on buoyant production of TKE.

Description: Current conventional global climate models (GCMs) produce a weak increase in global mean precipitation with anthropogenic warming in comparison with the lower-tropospheric moisture increases. The motive of this study is to understand the differences in the hydrological sensitivity between two multiscale modeling frameworks (MMFs) that arise from the different treatments of turbulence and low clouds in order to aid to the understanding of the model spread among conventional GCMs. We compare the hydrological sensitivity and its energetic constraint from MMFs with (SPCAM-IPHOC) or without (SPCAM) an advanced higher-order turbulence closure. SPCAM-IPHOC simulates higher global hydrological sensitivity for the slow response but lower sensitivity for the fast response than SPCAM. Their differences are comparable to the spreads of conventional GCMs. The higher sensitivity in SPCAM-IPHOC is associated with the higher ratio of the changes in latent heating to those in net atmospheric radiative cooling, which is further related to a stronger decrease in the Bowen ratio with warming than in SPCAM. The higher sensitivity of cloud radiative cooling resulting from the lack of low clouds in SPCAM is another major factor in contributing to the lower precipitation sensitivity. The two MMFs differ greatly in the hydrological sensitivity over the tropical lands, where the simulated sensitivity of surface sensible heat fluxes to surface warming and CO 2 increase in SPCAM-IPHOC is weaker than in SPCAM. The difference in divergences of dry static energy flux simulated by the two MMFs also contributes to the difference in land precipitation sensitivity between the two models.

Description: In this study, the environment of aggregated deep convection is investigated using a vector vorticity equation cloud-resolving model (VVM). Idealized experiments are performed under various environmental moisture with or without imposed vertical wind shear. Convective aggregation is then evaluated through diagnosing the 3-D size of an individual cloud from the model output using a six-connected segmentation method. The aggregated convection is recognized by a distinct mode with larger size in the cloud size distribution. The results suggest that aggregated convection tends to develop when column relative humidity (CRH) is larger than 80% (67%) in non-shear (shear) cases. In addition, the degree of aggregation further increases with the increase of CRH. This aggregation process may be caused by an increasing probability of multicellular cloud structure under a moister environment. The results also suggest that there are at least 5 convective cores of such system. Analyses of precipitation distribution suggest that the most extreme instantaneous grid point precipitation mainly occurs within the largest convective clusters.

Description: Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change, and while it is possible to simulate warm interglacial climates, these simulated results cannot be evaluated without the aid of geochemical proxies. One such proxy is δ 18 O , which allows for inference about both a climate state's hydrology and temperature. We utilize a stable water isotope equipped climate model to simulate three stages during the Last Interglacial (LIG), corresponding to 130, 125, and 120 kiloyears before present, using forcings for orbital configuration as well as greenhouse gases. We discover heterogeneous responses in the mean δ 18 O signal to the climate forcing, with large areas of depletion in the LIG δ 18 O signal over the tropical Atlantic, the Sahel, and the Indian Subcontinent, and with enrichment over the Pacific and Arctic Oceans. While we find that the climatology mean relationship between δ 18 O and temperature remains stable during the LIG, we also discover that this relationship is not spatially consistent. Our results suggest that great care must be taken when comparing δ 18 O records of different paleoclimate archives with the results of climate models as both the qualitative and quantitative interpretation of δ 18 O variations as a proxy for past temperature changes may be problematic due to the complexity of the signals.

Description: Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20 th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Lastly, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

Description: The behavior of tropical extreme precipitation under changes in sea surface temperatures (SSTs) is investigated with the Weather Research and Forecasting Model (WRF) in three sets of idealized simulations: small-domain tropical radiative-convective equilibrium (RCE), quasi-global “aquapatch”, and RCE with prescribed mean ascent from the tropical band in the aquapatch. We find that, across the variations introduced including SST, large-scale circulation, domain size, horizontal resolution and convective parameterization, the change in the degree of convective organization emerges as a robust mechanism affecting extreme precipitation. Higher ratios of change in extreme precipitation to change in mean surface water vapor are associated with increases in the degree of organization, while lower ratios correspond to decreases in the degree of organization. The spread of such changes is much larger in RCE than aquapatch tropics, suggesting that small RCE domains may be unreliable for assessing the temperature-dependence of extreme precipitation or convective organization. When the degree of organization doesn't change, simulated extreme precipitation scales with surface water vapor. This slightly exceeds Clausius-Clapeyron (CC) scaling, because the near-surface air warms 10-25% faster than the SST in all experiments. Also for simulations analyzed here with convective parameterizations, there is an increasing trend of organization with SST.

Description: The Superparameterized Community Atmosphere Model (SPCAM) is used to identify the dynamical and organizational properties of tropical extreme rainfall events on two scales. We compare the mesoscales resolved by General Circulation Models (GCMs) and the convective scales resolved by Cloud-Resolving Models (CRMs) to reassess and extend on previous results from GCMs and CRMs in radiative-convective equilibrium. We first show that the improved representation of subgridscale dynamics in SPCAM allows for a close agreement with the 7%/K Clausius-Clapeyron rate of increase in mesoscale extremes rainfall rates. Three contributions to changes in extremes are quantified and appear consistent in sign and relative magnitude with previous results. On mesoscales, the thermodynamic contribution (5.8%/K) and the contribution from mass flux increases (2%/K) enhance precipitation rates, while the upward displacement of the mass flux profile (-1.1%/K) offsets this increase. Convective-scale extremes behave similarly except that changes in mass flux are negligible due to a balance between greater numbers of strong updrafts and downdrafts and lesser numbers of weak updrafts. Extremes defined on these two scales behave as two independent sets of rainfall events, with different dynamics, geometries, and responses to climate change. In particular, the increases in mesoscale mass flux directly contribute to the intensification of mesoscale extreme rain, but do not seem to affect the increase in convective-scale rainfall intensities. These results motivate the need for better understanding the role of the large-scale forcing on the dynamical processes involved in the formation and intensification of heavy convective rainfall.

Description: The development of the new process-based TRIPLEX-GHG model derives from the Integrated Biosphere Simulator (IBIS), which couples nitrification and denitrification processes to quantify nitrous oxide (N 2 O) emissions from natural forests and grasslands. Sensitivity analysis indicates that the nitrification rate coefficient (COE NR ) is the most sensitive parameter to simulate N 2 O emissions. Accordingly, we calibrated this parameter using data from 29 global forest sites (across different latitudes) and grassland sites. The average nitrification rate coefficient gradually increases in the order of tropical forest to grassland to temperate forest to boreal forest, and giving means of 0.009, 0.03, 0.04, and 0.09, respectively. This study validated the mean value for each ecosystem at 52 sites globally. Calibration results both indicate the good performance of the model and its suitability in capturing seasonal variation and magnitude of N 2 O flux; however, it is limited in modeling N 2 O uptake and increments during periods of snowmelt. Additionally, validation results indicate that simulated and observed annual or seasonal N 2 O fluxes are highly correlated (R 2 =0.75; P〈0.01). Consequently, our results suggest that the model is suitable in simulating N 2 O emissions from different forest and grassland land types under varying environmental conditions on a global scale.

Description: ABSTRACT Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse-fraction-based two-leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves ( ε msh defined as a power function of the diffuse fraction ( D f )) and sunlit leaves ( ε msu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and D f . This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big-leaf GPP product. The DTEC model's explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation-dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation.

Description: A widely recognized issue found in most Earth system models is that of convective precipitation being triggered too early during the day over land, often resulting in persistent light rainfall. In an effort to address this issue, a model-consistent sub-grid convective trigger is demonstrated in the Community Earth System Model (CESM). Sub-grid convective initiation is achieved by first calculating a convective threshold within the Community Atmosphere Model (version 5.3). The convective threshold is then passed to each sub-grid land cover type within the Community Land Model (version 4.0) and convection is considered to be active if the convective threshold is exceeded and the convective available potential energy (CAPE) exceeds 70 J kg −1 (the default trigger). In total, three simulations are performed 1) a control (CTL) with the default CAPE trigger, 2) a simulation with the default CAPE trigger as well as the sub-grid trigger (HCF Trigger) applied over land and ocean and 3) a simulation the same as the HCF Trigger but only applied over land (HCF Land). By including this sub-grid trigger, convective onset time is delayed by 1-4 hours; however, the time of peak precipitation is unchanged. This diurnal shift improves the number of hours the deep convective scheme is invoked from more than 75% to less than 50%, alleviating the over-activity problem. The delayed onset time of deep convection allows for greater CAPE accumulation and a greater proportion of precipitation generated outside the convective scheme. More CAPE consequently produces an overall increase in intense precipitation events.

Description: In this study, a hybrid mass flux cumulus scheme (HYMACS) is developed for the Weather Research and Forecasting Model (WRF). Idealized experiments are performed to evaluate its effects on tropical cyclone simulations. Classical cumulus schemes assume artificial local compensation of convective mass flux. In contrast, HYMACS treats subgrid-scale mass flux convergence or divergence as parameterized mass sources or sinks. When the mass sources or sinks are introduced to the mass continuity equation in a nonhydrostatic fully compressible model, the model dynamics would resolve the mass-compensating motion, i.e., dynamic compensation of convective mass flux. A hierarchy of experiments is conducted to demonstrate the effects of the artificial local compensation. The results of the mass compensation experiment show that the amplitude of the column mass change with the artificial local compensation is more sensitive to the change of the horizontal resolution between 3 and 27 km than the dynamic compensation. The results of the piggybacking tropical cyclone simulations at 9 km resolution suggest that the artificial local compensation in the Kain-Fritsch scheme (KF) concentrates vertical exchange of dry static energy and moisture and induces secondary circulation, which could lead to sea level pressure decrease and enhanced precipitation. These results indicate that the artificial local compensation at the gray-zone resolution could cause significant effects on tropical cyclone dynamics, so it is important to avoid the artificial local compensation for cumulus parameterization at such resolution.

Description: Ice and mixed-phase cloud representation and simulation in global climate models are challenging with large uncertainties and biases. Sharing similar growth paths, no distinct separation exists in nature between cloud ice and snow. Different from conventional microphysics schemes separating cloud ice from snow, a single prognostic category is used to represent the whole spectrum of solid hydrometeors. Instead of using fixed physical properties for separate ice classes, e.g. the mass, area, and fall velocity, we consider the particle shape and riming impacts on ice properties. This approach simplifies several ice-related microphysical processes and eliminates the ambiguity and uncertainty associated with parameterizing cloud ice to snow conversion. The modifications were implemented in the Morrison-Gettelman (MG08) scheme and tested in Community Atmosphere Model. Evaluation using single column simulations indicated that the new approach increased the ice water content (IWC) in high clouds during dry period, which is improved compared to available retrievals. Global atmospheric simulations using the new approach give an overall comparable mean climate with notable improvement in terms of clouds and their radiative forcing. Both longwave and shortwave cloud forcing are closer to observations due to more realistic IWC, liquid water content, and cloud top height. Furthermore, the new approach yields slightly better representation of mixed-phase clouds when a smaller capacitance for non-spherical particles is used in the ice depositional growth parameterization. Overall, the physically-based single-ice approach is a promising direction for future GCM microphysics development given its simplified representation of microphysical processes and flexible description of ice particle properties.

Description: Convective dust storms have significant impacts on atmospheric conditions and air quality and are a major source of dust uplift in summertime. However, regional-to-global models generally do not accurately simulate these storms, a limitation that can be attributed to (1) using a single mean value for wind speed per grid box, i.e. not accounting for subgrid wind variability, and (2) using convective parametrizations that poorly simulate cold pool outflows. This study aims to improve the simulation of convective dust storms by tackling these two issues. Specifically, we incorporate a probability distribution function for surface wind in each grid box to account for subgrid wind variability due to dry and moist convection. Furthermore, we use lightning assimilation to increase the accuracy of the convective parameterization and simulated cold pool outflows. This updated model framework is used to simulate a massive convective dust storm that hit Phoenix, AZ on 6 July, 2011. The results show that lightning assimilation provides a more realistic simulation of precipitation features, including timing and location, and the resulting cold pool outflows that generated the dust storm. When those results are combined with a dust model that accounts for subgrid wind variability, the prediction of dust uplift and concentrations are considerably improved compared to the default model results. This modeling framework could potentially improve the simulation of convective dust storms in global models, regional climate simulations, and retrospective air quality studies.

Description: We quantify the biases in the diurnal cycle of temperature in ERA-Interim for both warm and cold season using hourly climate station data for four stations in Saskatchewan from 1979-2006. The warm season biases increase as opaque cloud cover decreases, and change substantially from April to October. The bias in mean temperature increases almost monotonically from small negative values in April to small positive values in the fall. Under clear skies, the bias in maximum temperature is of the order of -1°C in June and July, and -2°C in spring and fall; while the bias in minimum temperature increases almost monotonically from +1°C in spring to +2.5°C in October. The bias in the diurnal temperature range falls under clear skies from -2.5°C in spring to -5°C in fall. The cold season biases with surface snow have a different structure. The biases in maximum, mean and minimum temperature with a stable BL reach +1°C, +2.6°C and +3°C respectively in January under clear skies. The cold season bias in diurnal range increases from about -1.8°C in the fall to positive values in March. These diurnal biases in 2-m temperature and their seasonal trends are consistent with a high bias in both the diurnal and seasonal amplitude of the model ground heat flux, and a warm season daytime bias resulting from the model fixed leaf area index. Our results can be used as bias corrections in agricultural modeling that use these reanalysis data, and also as a framework for understanding model biases.

Description: The spatial pattern of sea surface temperature (SST) changes has a large impact on the magnitude of cloud feedback. In this study, we seek a basic understanding of the dependence of cloud feedback on the spatial pattern of warming. Idealized experiments are carried out with an AGCM to calculate the change in global mean cloud-induced radiation anomalies (ΔR cloud ) in response to imposed surface warming/cooling in 74 individual localized oceanic “patches”. Then the cloud feedback in response to a specific warming pattern can be approximated as the superposition of global cloud feedback in response to a temperature change in each region, weighted by the magnitude of the local temperature changes. When there is a warming in the tropical subsidence or extratropical regions, the local decrease of LCC results in a positive change in R cloud . Conversely, warming in tropical ascent regions increases the free-tropospheric temperature throughout the tropics, thereby enhancing the inversion strength over remote regions and inducing positive global low cloud cover (LCC) anomalies and negative R cloud anomalies. The Green's function approach performs reasonably well in predicting the response of global mean ΔLCC and net ΔR cloud , but poorly for shortwave and longwave components of ΔR cloud due to its ineffectiveness in predicting middle and high cloud cover changes. The approach successfully captures the change of cloud feedback in response to time-evolving CO 2 -induced warming, and captures the interannual variations in ΔR cloud observed by CERES. The results highlight important non-local influences of SST changes on cloud feedback.

Description: Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one-dimensional process-based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area-weighted CO 2 fluxes from yedoma thermokarst lakes, non-yedoma thermokarst lakes and glacial lakes are 29.5 g C m −2 yr −1 , 13.0 g C m −2 yr −1 and 21.4 g C m −2 yr −1 , respectively, close to the observed values (31.2 g C m −2 yr −1 , 17.2 g C m −2 yr −1 and 16.5±7.7 g C m −2 yr −1 , respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight-induced organic carbon degradation is more important for shallow non-yedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM model can simulate the whole-lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.

Description: We describe how convective vertical velocities w c vary in the ‘gray zone’ of horizontal resolution, using both hydrostatic and non-hydrostatic versions of GFDL's FV 3 dynamical core, as well as analytical solutions to the equations of motion. We derive a simple criterion (based on parcel geometries) for a model to resolve convection, and find that O (100m) resolution can be required for convergence of w c . We also find, both numerically and analytically, that hydrostatic systems over-estimate w c , by a factor of 2 - 3 in the convection-resolving regime. This over-estimation is simply understood in terms of the ‘effective buoyancy pressure’ of Jeevanjee and Romps (2015, 2016).

Description: Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset and the annual cycle.

Description: This paper presents analytical solutions of large-scale, zonally symmetric overturning circulations in the tropical free troposphere forced by transient diabatic heating in the off-equatorial intertropical convergence zone (ITCZ). The dynamics are discussed in the context of the time dependent meridional circulation equation arising in an equatorial $\beta$-plane model. The solutions of these differential equations contain terms for the slow, quasi-balanced part of the response and terms for the transient, zonally symmetric, inertia-gravity wave part of the response. When the off-equatorial (north of the equator) ITCZ diabatic heating is switched on at various rates, both parts of the response reveal a basic asymmetry between the southern and northern hemispheres, with the southern hemisphere side containing most of the quasi-balanced compensating subsidence and transient inertia-gravity wave activity. The inertia-gravity waves travel in wave packets that bounce off a spectrum of turning latitudes, and are analyzed in the context of an average conservation law approach. These traveling wave packets cause the mass flux in the southern and northern Hadley cells to pulsate on timescales of about one, two, and three days for diabatic heating of the external, first internal, and second internal vertical modes, respectively. The spectral characteristics of the vertical motion in the ITCZ and subsidence regions are slightly more complicated and depend on ITCZ location. This article is protected by copyright. All rights reserved.

Description: A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6 and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that, Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed Soil Moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression. This article is protected by copyright. All rights reserved.

Description: Multi-scale atmospheric simulations can be computationally prohibitive, as they require large domains and fine spatio-temporal resolutions. Grid-nesting can alleviate this by bridging mesoscales and microscales, but one turbulence scheme must run at resolutions within a range of scales known as the terra incognita (TI). TI grid-cell sizes can violate both mesoscale and microscale subgrid-scale parametrization assumptions, resulting in unrealistic flow structures. Herein we assess the impact of unrealistic lateral boundary conditions from parent mesoscale simulations at TI resolutions on nested large eddy simulations (LES), to determine whether parent domains bias the nested LES. We present a series of idealized nested mesoscale-to-LES runs of a dry convective boundary layer (CBL) with different parent resolutions in the TI. We compare the nested LES with a stand-alone LES with periodic boundary conditions. The nested LES domains develop ∼20% smaller convective structures. While potential temperature profiles are nearly identical for both the mesoscales and LES simulations. The horizontal wind speed and surface wind shear in the nested simulations closely resemble the reference LES. Heat fluxes are overestimated by up to ∼0.01 K m s −1 in the top half of the PBL for all nested simulations. Overestimates of turbulent kinetic energy (TKE) and Reynolds stress in the nested domains are proportional to the parent domain's grid-cell size, and are almost eliminated for the simulation with the finest parent grid-cell size. Based on these results, we recommend that LES of the CBL be forced by mesoscale simulations with the finest practical resolution.

Description: In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah-MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions — two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah-MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, the amount of GPP and ER in the growing season. Furthermore, the augmented Noah-MP performed reasonably well in simulating the spatial distributions of LAI, GPP and NPP in East Asia, consistent with the satellite observations.

Description: We describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES), which includes the coupling between the atmosphere, ocean and land surface, as well as an hydrological and ocean biogeochemistry model, with the capability of using a variety of physical parameterizations. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains and more regional settings featuring climatically important coupled phenomena. Regional coupled ocean-atmosphere models can be especially useful tools to provide information on the mechanisms of air-sea interactions and feedbacks occurring at fine spatial and temporal scales. RegCM-ES shows a good representation of precipitation and SST fields over the domains tested, as well as realistic simulations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source, making it suitable for usage by the broad scientific community.

Description: Lateral and lower boundary conditions derived from a suitable global reanalysis dataset forms the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis datasets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational datasets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias corrected WRF simulations are, however, found to be marginally better than mean only bias corrected WRF simulations and raw ERA-I reanalysis driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.

Description: Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global- or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis dataset. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a 〉3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

Description: Global aerosol simulations are conducted by using the Community Atmosphere Model version 5 with the Aerosol Two-dimensional bin module for foRmation and Aging Simulation version 2 (CAM5-chem/ATRAS2) which was developed in part 1. The model uses a two-dimensional (2-D) section representation with 12 size bins from 1 nm to 10 μm and 8 black carbon (BC) mixing state bins, and it can calculate detailed aerosol processes and their interactions with radiation and clouds. The simulations have similar or better agreement with aerosol observations (e.g., aerosol optical depth, absorption aerosol optical depth (AAOD), aerosol number concentrations, mass concentrations of each species) compared with the simulations using the Modal Aerosol Model with three modes. Sensitivity simulations show that global mean AAOD is reduced by 15% by resolving BC mixing state as a result of two competing effects (optical and lifetime effects). AAOD is reduced by 10-50% at low- and mid-latitudes in the 2-D sectional simulation because BC absorption enhancement by coating species is reduced by resolving pure BC, thinly coated BC, and BC-free particles in the model (optical effect). In contrast, AAOD is enhanced by 5-30% at high-latitudes because BC concentrations are enhanced by 40-200% over the regions by resolving less CCN active particles (lifetime effect). The simulations also suggest a model which resolves more than 3 BC categories (including BC-free particles) is desirable to calculate the optical and lifetime effects accurately. The complexity of aerosol representation is shown to be especially important for simulations of BC and CCN concentrations and AAOD.

Description: This study develops an aerosol module, the Aerosol Two-dimensional bin module for foRmation and Aging Simulation version 2 (ATRAS2), and implements the module into a global climate model, Community Atmosphere Model. The ATRAS2 module uses a two-dimensional (2-D) sectional representation with 12 size bins for particles from 1 nm to 10 μm in dry diameter and 8 black carbon (BC) mixing state bins. The module can explicitly calculate the enhancement of absorption and cloud condensation nuclei activity of BC-containing particles by aging processes. The ATRAS2 module is an extension of a 2-D sectional aerosol module ATRAS used in our previous studies within a framework of a regional three-dimensional model. Compared with ATRAS, the computational cost of the aerosol module is reduced by more than a factor of 10 by simplifying the treatment of aerosol processes and 2-D sectional representation, while maintaining good accuracy of aerosol parameters in the simulations. Aerosol processes are simplified for condensation of sulfate, ammonium, and nitrate, organic aerosol formation, coagulation, and new particle formation processes, and box model simulations show that these simplifications do not substantially change the predicted aerosol number and mass concentrations and their mixing states. The 2-D sectional representation is simplified (the number of advected species is reduced) primarily by the treatment of chemical compositions using two interactive bin representations. The simplifications do not change the accuracy of global aerosol simulations. In part 2, comparisons with measurements and the results focused on aerosol processes such as BC aging processes are shown.

Description: Large tabular icebergs calved from Antarctic ice shelves have long lifetimes (due to their large size), during which they drift across large distances, altering ambient ocean circulation, bottom-water formation, sea-ice formation, and biological primary productivity in the icebergs' vicinity. However, despite their importance, the current generation of ocean circulation models usually do not represent large tabular icebergs. In this study we develop a novel framework to model large tabular icebergs submerged in the ocean. In this framework, tabular icebergs are represented by pressure-exerting Lagrangian elements that drift in the ocean. The elements are held together and interact with each other via bonds. A breaking of these bonds allows the model to emulate calving events (i.e. detachment of a tabular iceberg from an ice shelf) and tabular icebergs breaking up into smaller pieces. Idealized simulations of a calving tabular iceberg, its drift, and its breakup demonstrate capabilities of the developed framework.

Description: To understand Earth's climate, climate modelers employ a hierarchy of climate models spanning a wide spectrum of complexity and comprehensiveness. This essay, inspired by the World Climate Research Programme's recent ‘Model Hierarchies Workshop’, attempts to survey and synthesize some of the current thinking on climate model hierarchies, especially as presented at the workshop. We give a few formal descriptions of the hierarchy, and survey the various ways it is used to generate, test, and confirm hypotheses. We also discuss some of the pitfalls of contemporary climate modeling, and how the ‘elegance’ advocated for by Held [2005] has (and has not) been used to address them. We conclude with a survey of current activity in hierarchical modeling, and offer suggestions for its continued fruitful development.

Description: Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here, concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such tradeoffs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which tradeoffs in GCM performance occur. This approach allows the modeler to visualize tradeoffs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that tradeoffs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

Description: The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals scheme (CLUBB) and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled sub-grid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud. Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: 1) a parameterized relationship between rain evaporation and CLUBB's sub-grid spatial variance of moisture and heat that induces an extra cooling in the lower PBL; and 2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.

Description: Having a clear multi-dimensional picture of Earth's oceans is crucial for understanding ocean processes and how they are evolving with climate change. Ocean knowledge is currently limited by relying on in situ data. A possible source of remote data is using the electromagnetic fields produced by the ocean and detected by geomagnetic satellites. Marine electromagnetic signals largely depend on three factors: oceanic transport, the local main magnetic field, and the electrical conductivity produced by the local salinity and temperature. Thus, how can marine electromagnetic signals be utilized to enhance the multi-dimensional picture of Earth's ocean circulation and state?

Description: The diurnal cycle of sea surface temperature (SST) plays an important role in the upper ocean and climate system. One way to represents the diurnal variation of SST in Ocean General Circulation Models (OGCMs) with coarse vertical resolution is to parameterize the diurnal cycle of SST without considering detailed dynamic processes within the mixed layer. In this study, a diagnostic sublayer parameterization scheme following Schiller and Godfrey [2005] was incorporated into a global OGCM (NEMO), for the first time, to simulate the diurnal cycle of SST. Moreover, three different sublayer temperature profiles (constant, linear and exponential) were evaluated. Comparison with satellite SST and mooring temperature data indicated that the parameterization scheme with an exponential temperature profile showed the most reasonable diurnal warming simulation results, significantly improving the probability of (from 1.7% with constant temperature profile to 13.4%) diurnal SST amplitude larger than 1.0°C. Furthermore, the mean biases in each season were all reduced to less than 0.16°C, in good agreement with observations.

Description: In energetic equilibrium, the atmosphere's net radiative divergence ( ) is balanced by sensible ( ) and latent ( ) heat fluxes, i.e. . Radiative forcing from increasing CO 2 reduces , and the surface warming following an increase in CO 2 is largely due to the reduction in atmospheric energy demand in and , with only a smaller surface radiative budget perturbation. With an idealized General Circulation Model, we show that the fast atmospheric adjustment at fixed surface temperature produces the required decrease in the sum of and through changes in the near-surface temperature and specific humidity. In layers near the surface, the reduced radiative cooling forces a temperature increase that leads to a negative Planck radiative feedback and, because of the reduced surface-atmosphere temperature difference, also to a reduction in sensible heat flux. In the free troposphere, the reduced radiative cooling leads to a weakening of the tropospheric circulation. Consequently, there is a decrease in the water flux exported from the layers near the surface, and as such in precipitation. By mass conservation, the near-surface specific humidity increases and surface evaporation decreases until it balances the reduced export flux. Other processes can amplify or dampen the responses in and and change the partitioning between these two fluxes, but by themselves do not ensure .

Description: The Earth's climate is changing due to the existence of multiple radiative forcing agents. It is under question whether different forcing agents perturb the global climate in a distinct way. Previous studies have demonstrated the existence of similar climate response patterns in response to aerosol and greenhouse gas (GHG) forcings. In this study, the sensitivity of tropospheric temperature response patterns to surface heating distributions is assessed by forcing an atmospheric general circulation model coupled to an aquaplanet slab ocean with a wide range of possible forcing patterns. We show that a common climate pattern emerges in response to localized forcing at different locations. This pattern, characterized by enhanced warming in the tropical upper troposphere and the polar lower troposphere, resembles the historical trends from observations and models as well as the future projections. Atmospheric dynamics in combination with thermodynamic air-sea coupling are primarily responsible for shaping this pattern. Identifying this common pattern strengthens our confidence in the projected response to GHG and aerosols in complex climate models.

Description: Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195 Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated by Xu et al . [2014]. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). However, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.

Description: The General Circulation Model ECHAM is used to study the effects of three refined vertical resolutions on convection in the tropics and on the structure of the intertropical convergence zone (ITCZ). Additional vertical resolutions have 76, 134 or 192 levels, which is over four times the default resolution of 47 levels. New levels are placed in the troposphere only. The simulations are conducted on an aqua-planet with equator symmetrical, time and zonal independent sea surface temperature and without a yearly solar cycle. Whereas the default vertical resolution shows a double ITCZ, refining the vertical resolution yields an equatorward shift of the ITCZ. The ITCZ converges to its equatorial position with 134 levels. The sensitivity of the ITCZ to the vertical resolution is traced back first and foremost to the mixing formulation in the convection scheme. Here, a higher number of vertical levels leads to a stronger mixing between the updraft and its environment by design, which favors an equatorward position of the ITCZ. Differences in the relative humidity profiles explain the remaining differences in the ITCZ location. Differences that can be masked by making clouds transparent.

Description: The numerical simulation of atmospheric blocking, in particular over the Euro-Atlantic region, still represents a main concern for the climate modeling community. We discuss the Northern Hemisphere winter atmospheric blocking representation in a set of 30-year atmosphere-only simulations using the EC-Earth Earth System Model with several ensemble members at five different horizontal resolutions (from 125 km to 16 km). Results show that the negative bias in blocking frequency over Europe becomes negligible at resolutions of about 40 km and 25 km. A combined effect by the more resolved orography and by a change in tropical precipitation is identified as the source of an upper tropospheric planetary wave. At the same time, a weakening of the meridional temperature gradient reduces the upper level baroclinicity and the zonal mean winds. Following these changes, in the high resolution configurations the Atlantic eddy-driven jet stream is weakened favoring the breaking of synoptic Rossby waves over the Atlantic ridge and thus increasing the simulated European blocking frequency. However, at high-resolution the Atlantic jet stream is too weak and the blocking duration is still underestimated. This suggests that the optimal blocking frequencies are achieved through compensation of errors between eddies found at upper levels (too strong) and eddies at lower levels (too weak). This also implies that eddies are not necessarily better represented at higher resolutions.

Description: Threshold wind speed for snow movement is one of the most important parameters describing the wind-transport snow process. A majority of previous studies used empirical and constant threshold wind speeds while the variations of atmosphere condition and snow age seem to greatly affect the snow settlement process. This study tested the hypothesis that the threshold wind speed for snow transport increases as deposition time passed since last snowfall by introducing a new formula of the threshold wind speed for snow movement. It was theoretically derived based on the sintering process modeling and the moment balance of a snow particle. Through this formula, the influences of snow particle size, temperature, and deposition time on the threshold wind speed were explicitly taken into consideration. However, two empirical parameters in the sintering process modeling remained in the new formula, and they were determined by a calibration-validation procedure using the field observed snow flux data. The snow flux and meteorological data collected at the ISAW stations ( http://www.iav.ch ) including large number of snow transport events during five winter seasons were used to test this formula. It was shown that the new formula qualitatively described the threshold wind speed required for the incipient motion of snow under various conditions in the natural environment of the Alps.

Description: A new paradigm of simulating suspended sediment load (SSL) with a Land Surface Model (LSM) is presented here. Five erosion and SSL algorithms were applied within a common LSM framework to quantify uncertainties and evaluate predictability in two steep, forested catchments (〉 1,000 km 2 ). The algorithms were chosen from among widely-used sediment models, including empirically-based: monovariate rating curve (MRC), and the Modified Universal Soil Loss Equation (MUSLE); stochastically-based: the Load Estimator (LOADEST); conceptually-based: the Hydrologic Simulation Program—Fortran (HSPF); and physically-based: the Distributed Hydrology Soil Vegetation Model (DHSVM). The algorithms were driven by the hydrologic fluxes and meteorological inputs generated from the Variable Infiltration Capacity (VIC) LSM. A multi-objective calibration was applied to each algorithm and optimized parameter sets were validated over an excluded period, as well as in a transfer experiment to a nearby catchment to explore parameter robustness. Algorithm performance showed consistent decreases when parameter sets were applied to periods with greatly differing SSL variability relative to the calibration period. Of interest was a joint calibration of all sediment algorithm and streamflow parameters simultaneously, from which tradeoffs between streamflow performance and partitioning of runoff and baseflow to optimize SSL timing were noted, decreasing the flexibility and robustness of the streamflow to adapt to different time periods. Parameter transferability to another catchment was most successful in more process-oriented algorithms, the HSPF and the DHSVM. This first-of-its-kind multi-algorithm sediment scheme offers a unique capability to portray acute episodic loading while quantifying tradeoffs and uncertainties across a range of algorithm structures.

Description: The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

Description: Offline chemical transport models (CTMs) have traditionally been used to perform studies of atmospheric chemistry in a fixed dynamical environment. An alternative to using CTMs is to constrain the flow in a general circulation model using winds from meteorological analyses. The Goddard Earth Observing System (GEOS) “replay” approach involves reading in analyzed fields every six hours and recomputing the analysis increments, which are applied as a forcing to the meteorology at every model time step. Unlike in CTM, all of the subgrid-scale processes are recalculated on-line so that they are consistent with the large-scale analysis fields, similar in spirit to “nudged” simulations, in which the online meteorology is relaxed to the analysis. Here we compare the transport of idealized tracers in different replay simulations constrained with meteorological fields taken from The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). We show that there are substantial differences in their large-scale stratospheric transport, depending on whether analysis fields or assimilated fields are used. Replay simulations constrained with the instantaneous analysis fields produce stratospheric mean age values that are up to 30\% too young relative to observations; by comparison, simulations constrained with the time-averaged assimilated fields produce more credible stratospheric transport. Our study indicates that care should be taken to correctly configure the model when the replay technique is used to simulate stratospheric composition.

Description: The ORCHIDEE land surface model has recently been updated to improve the representation of high latitude environments. The model now includes improved soil thermodynamics and the representation of permafrost physical processes (soil thawing and freezing), as well as a new snow model to improve the representation of the seasonal evolution of the snow pack and the resulting insulation effects. The model was evaluated against data from the experimental sites of the WSibIso-Megagrant project ( www.wsibiso.ru ). ORCHIDEE was applied in stand-alone mode, on two experimental sites located in the Yamal Peninsula in the northwestern part of Siberia. These sites are representative of circumpolar-arctic tundra environments and differ by their respective fractions of shrub/tree cover and soil type. After performing a global sensitivity analysis to identify those parameters that have most influence on the simulation of energy and water transfers, the model was calibrated at local scale and evaluated against in situ measurements (vertical profiles of soil temperature and moisture, as well as active layer thickness) acquired during summer 2012. The results show how sensitivity analysis can identify the dominant processes and thereby reduce the parameter space for the calibration process. We also discuss the model performance at simulating the soil temperature and water content (i.e., energy and water transfers in the soil-vegetation-atmosphere continuum) and the contribution of the vertical discretization of the hydro-thermal properties. This work clearly shows, at least at the two sites used for validation, that the new ORCHIDEE vertical discretization can represent the water and heat transfers through complex cryogenic arctic soils — soils which present multiple horizons sometimes with peat inclusions. The improved model allows us to prescribe the vertical heterogeneity of the soil hydro-thermal properties.

Description: Cumulus elements generated by detraining convective condensate - detrained cumulus - are added to the Community Atmosphere Model Version 5 (CAM5) combined with a Unified Convection Scheme (UNICON). Instead of evaporating convective liquids detrained into clear portions, we diagnosed a new detrained cumulus that is horizontally nonoverlapped with cumulus and stratus in each layer by assuming a steady state balance between the detrainment rate of cumulus condensates and the dissipation rate of detrained condensates by entrainment mixing with environmental air. The addition of detrained cumulus was found to substantially improve the simulation of low-level clouds and the associated shortwave cloud radiative forcing, particularly in the subtropical trade cumulus regime. In addition to the mean climate, successful simulations of the diurnal cycle of precipitation, Madden-Julian Oscillation, and Kelvin wave were also well maintained.

Description: Changes in the Madden-Julian Oscillation (MJO) with increasing CO2 concentrations are examined using the Goddard Institute for Space Studies Global Climate Model (GCM). Four simulations performed with fixed CO2 concentrations of 0.5, 1, 2 and 4 times pre-industrial levels using the GCM coupled with a mixed layer ocean model are analyzed in terms of the basic state, rainfall, moisture and zonal wind variability, and the structure and propagation of the MJO. The GCM simulates basic state changes associated with increasing CO2 that are consistent with results from earlier studies: column water vapor increases at ∼7.1 % K-1, precipitation also increases but at a lower rate (∼3 % K-1), and column relative humidity shows little change. Moisture and rainfall variability intensify with warming while zonal wind variability shows little change. Total moisture and rainfall variability increases at a rate that is similar to that of the mean state change. The intensification is faster in the MJO-related anomalies than in the total anomalies, though the ratio of the MJO band variability to its westward counterpart increases at a much slower rate. On the basis of linear regression analysis and space-time spectral analysis, it is found that the MJO exhibits faster eastward propagation, faster westward energy dispersion, a larger zonal scale and deeper vertical structure in warmer climates.

Description: Modeled wintertime precipitation over the Atlantic Gulf Stream region is shown to be sensitive to the horizontal resolution of the driving Global Circulation Model (GCM). By contrasting simulations with the EC-Earth GCM over a range of horizontal resolutions (T159, T319, T799), it is shown that especially the precipitation extremes become more populated if resolution is higher. Higher resolution also appears to strengthen the communication from the sea surface toward the troposphere. With increasing resolution, deep convection over the Gulf Stream region, diagnosed via wind-convergence and vertical motion, occurs more frequently and the former is in better agreement with observations. Likewise the frequency increase of the precipitation extremes over the region for increasing resolution makes them agree better with observations, despite large natural variability and discrepancies between different observational sources.

Description: Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modelling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modelled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m 3 /s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a one-to two-month wet season lag and a negative baseflow bias. Accounting for this two-month lag yields a hydrograph RMSE of 270 m 3 /s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modelling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

Description: NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM) and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth-System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace-gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This manuscript describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.

Description: The quasi-geostrophic omega equation has been used extensively to examine the large-scale vertical velocity patterns of atmospheric systems. It is derived from the quasi-geostrophic equations, a balanced set of equations based on the partitioning of the horizontal wind into a geostrophic and an ageostrophic component. Its use is limited to higher latitudes, however, as the geostrophic balance is undefined at the equator. In order to derive an omega equation which can be used at all latitudes, a new balanced set of equations is developed. Three key steps are used in the formulation. First, the horizontal wind is decomposed into a nondivergent and an irrotational component. Second, the Coriolis parameter is assumed to be slowly varying, such that it may be moved in and out of horizontal derivative operators as necessary to simplify the derivation. Finally, the mass field is formulated from the nondivergent wind field. The resulting balanced set of equations and the omega equation derived from them take a similar form to the quasi-geostrophic equations, yet are valid over the whole sphere. A method of solution to the global omega equation using vertical normal modes and spherical harmonics is presented, along with a middle- and low-latitude example.

Description: Grasslands play an important role in feeding the growing human population by supporting dairy and livestock production. The purpose of this paper was to improve the representation of carbon (C) allocation processes in ecosystem models, and to understand the sensitivity of simulated grass biomass to model parameters, providing guidance for future environmental change research. We used the Regional Hydro-Ecologic Simulation System to compare estimates of above and belowground biomass for C allocation strategies based on plant growth, resource use, and a newly developed HYBRID approach that integrates the first two allocation schemes. Observed values of biomass at seven grassland sites are used to compare performance of these three allocation strategies. Partial ranked correlation coefficients are then calculated to assess parameter importance and sensitivity under current and future climate conditions. We found that both resource use and plant growth play a role in simulating dynamic C allocation in grass biomass over time, indicating the need for the HYBRID approach to capture grassland C allocation. Parameter importance was site-specific under increased temperatures, enhanced carbon dioxide, and changed precipitation. Site-specific parameter importance also yielded insight into limiting resources (i.e. energy, moisture) at sites and subsequent effects on ecological processes like photosynthesis and allocation. This work increases our understanding of C allocation in ecosystem models related to grasses, and guides what model parameters may require further research.

Description: Mammalian herbivores are an essential component of grassland and savanna ecosystems, and with feedbacks to the climate system. To date, the response and feedbacks of mammalian herbivores to changes in both abiotic and biotic factors are poorly quantified and not adequately represented in the current global land modeling framework. In this study, we coupled herbivore population dynamics in a global land model (the Dynamic Land Ecosystem Model, DLEM3.0) to simulate populations of horses, cattle, sheep and goats, and their responses to changes in multiple environmental factors at the site level across different continents during 1980-2010. Simulated results show that the model is capable of reproducing observed herbivore populations across all sites for these animal groups. Our simulation results also indicate that during this period, climate extremes led to a maximum mortality of 27% of the total herbivores in Mongolia. Across all sites, herbivores reduced aboveground net primary productivity (ANPP) and heterotrophic respiration (Rh) by 14% and 15%, respectively ( p  〈 0.05). With adequate parameterization, the model can be used for historical assessment and future prediction of mammalian herbivore populations and their relevant impacts on biogeochemical cycles. Our simulation results demonstrate a strong coupling between primary producers and consumers, indicating that inclusion of herbivores into the global land modeling framework is essential to better understand the potentially large effect of herbivores on carbon and water cycles in grassland and savanna ecosystems.

Description: The processes that lead to changes in the propagation and maintenance of the Madden-Julian oscillation (MJO) as a response to increasing CO 2 are examined by analyzing moist static energy budget of the MJO in a series of NASA GISS model simulations. It is found changes in MJO propagation is dominated by several key processes. Horizontal moisture advection, a key process for MJO propagation, is found to enhance predominantly due to an increase in the mean horizontal moisture gradients. The terms that determine the strength of the advecting wind anomalies, the MJO horizontal scale and the dry static stability, are found to exhibit opposing trends that largely cancel out. Furthermore, reduced sensitivity of precipitation to changes in column moisture, i.e. a lengthening in the convective moisture adjustment timescale, also opposes enhanced propagation. The dispersion relationship of Adames and Kim, which accounts for all these processes, predicts an acceleration of the MJO at a rate of ∼3.5%K -1 , which is consistent with the actual phase speed changes in the simulation. For the processes that contribute to MJO maintenance, it is found that damping by vertical MSE advection is reduced due to the increasing vertical moisture gradient. This weaker damping is nearly cancelled by weaker maintenance by cloud-radiative feedbacks, yielding the growth rate from the linear moisture mode theory nearly unchanged with the warming. Furthermore, the estimated growth rates are found to be a small, negative values, suggesting that the MJO in the simulation is a weakly damped mode.

Description: Runoff and river routing schemes play important roles in land surface models (LSMs) because they regulate the soil moisture, heat flux and vegetation dynamics of land surface processes and account for the carbon and nutrient transport in river channels. However, these schemes are often simplistic and conceptual. Hence, in this study, we focused on (1) evaluating these schemes in the Community Land Model (CLM) and (2) altering the model representations using physically based schemes based on a study of the Yellow River basin. For runoff simulation, CLM exhibits limitations in water-limited areas, especially areas with aridity index values greater than 2. Additionally, CLM greatly overestimates runoff, and produces negative Nash-Sutcliffe efficiency (NSE) coefficients, few quick flow variations, high quick flow index values and large root mean square errors of total water storage. These issues were greatly improved by implementing schemes of physically based overland flow, lateral soil water flow and interchange between groundwater and river water. Furthermore, for the river routing scheme, the use of 1D kinematic wave routing improved previously unrealistic aspects of the flood hydrographs (e.g., incorrect flood peak values and times) of the original CLM. Moreover, compared with using the grid element-based river routing approach in CLM, the computational costs were reduced by up to 45% by implementing the flow interval element method. Finally, our results indicate that parameter calibration in CLM minimally improved the simulation performance in water-limited areas, while physically based schemes generated better results.

Description: This paper presents the development and application of a physically based hydrological data assimilation system (HDAS) using the gridded and parallelized Soil and Water Assessment Tool (SWATGP) distributed hydrological model. This SWAT-HDAS software integrates remotely sensed data, including the leaf area index (LAI), snow cover fraction, snow water equivalent, soil moisture and ground-based observational data (e.g., from discharge and ground sensor networks), with SWATGP and the Parallel Data Assimilation Framework (PDAF) to accurately characterize watershed hydrological states and fluxes. SWAT-HDAS employs high performance computational technologies to address the computational challenges of high-resolution and/or large area modeling. Multiple observational system simulation experiments (OSSEs), including soil moisture assimilation experiments, snow water equivalent assimilation experiments and streamflow assimilation experiments, were designed to validate the assimilation efficiency of various types of observations within SWAT-HDAS using an ensemble Kalman filter (EnKF) algorithm. Both the temporal and spatial correlations in the trend/pattern and the magnitudes of improvement between the simulated and “true” states (i.e., for soil moisture, snow water equivalent and discharge) were satisfactory using the integrated assimilation, which suggests the reliability of SWAT-HDAS for regional hydrology studies. The streamflow assimilation experiment also showed that the observation location dramatically influences the assimilation efficiency. The quantity and quality of observations have effects of varying degrees on the streamflow predictions. SWAT-HDAS is a promising tool for hydrological studies and applications under climate and environmental change scenarios.

Description: State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO 2 . Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the 'true' physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between sub-models that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent and it does not introduce artificial error interactions between sub-models. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning.

Description: Stratocumulus topped boundary layers (STBL) are notoriously difficult to parameterize in single column models due to the strong inversion layer across which entrainment mixing plays an important role in modulating the boundary layer mass, energy, and moisture balances. We compare three different WRF planetary boundary layer (PBL) schemes (Yonsei University – YSU, Asymmetric Convective Model - ACM2, Mellor Yamada Nakanishi Niino - MYNN) against Large Eddy Simulations (LES) to find out that they underestimate entrainment flux in stratocumulus over both ocean and coastal land. Hence, the PBL schemes produce a cooler, moister STBL with higher liquid water content. In order to improve the entrainment parameterization, we propose a modification to the YSU scheme that takes into account the in-cloud turbulence flux contribution to cloud top entrainment through the formulation of a velocity scale based on the in-cloud buoyancy flux. A revised top-down mixing profile is also implemented to model mixing due to turbulence generated by long-wave cooling at the cloud top. The modified YSU simulates stronger entrainment flux, resulting in a STBL that matches LES results. Similar modifications were made to ACM2 in addition to implementing explicit entrainment, and while the results also showed good agreement with LES, discretization issues and conflicts with its original design prevent immediate implementation, as the contribution from the modifications and the original scheme are difficult to correctly modulate.