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At least 217 records · Page 12

Constraints and Opportunities in GCM Model Development

Over the past 30 years climate models have evolved from relatively simple representations of a few atmospheric processes to complex multi-disciplinary system models which incorporate physics from bottom of the ocean to the mesopause and are used for seasonal to multi-million year timescales. Computer infrastructure over that period has gone from punchcard mainframes to modern parallel clusters. Constraints of working within an ever evolving research code mean that most software changes must be incremental so as not to disrupt scientific throughput. Unfortunately, programming methodologies have generally not kept pace with these challenges, and existing implementations now present a heavy and growing burden on further model development as well as limiting flexibility and reliability. Opportunely, advances in software engineering from other disciplines (e.g. the commercial software industry) as well as new generations of powerful development tools can be incorporated by the model developers to incrementally and systematically improve underlying implementations and reverse the long term trend of increasing development overhead. However, these methodologies cannot be applied blindly, but rather must be carefully tailored to the unique characteristics of scientific software development. We will discuss the need for close integration of software engineers and climate scientists to find the optimal processes for climate modeling.

Schmidt, Gavin↗

Comparison of Satellite-Derived TOA Shortwave Clear-Sky Fluxes to Estimates from GCM Simulations Constrained by Satellite Observations of Land Surface Characteristics

Clear-sky, upwelling shortwave flux at the top of the atmosphere (S(sub TOA raised arrow)), simulated using the atmospheric and land model components of the Community Climate System Model 3 (CCSM3), is compared to corresponding observational estimates from the Clouds and Earth's Radiant Energy System (CERES) sensor. Improvements resulting from the use of land surface albedo derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to constrain the simulations are also examined. Compared to CERES observations, CCSM3 overestimates global, annual averaged S(sub TOA raised arrow) over both land and oceans. However, regionally, CCSM3 overestimates S(sub TOA raised arrow) over some land and ocean areas while underestimating it over other sites. CCSM3 underestimates S(sub TOA raised arrow) over the Saharan and Arabian Deserts and substantial differences exist between CERES observations and CCSM3 over agricultural areas. Over selected sites, after using groundbased observations to remove systematic biases that exist in CCSM computation of S(sub TOA raised arrow), it is found that use of MODIS albedo improves the simulation of S(sub TOA raised arrow). Inability of coarse resolution CCSM3 simulation to resolve spatial heterogeneity of snowfall over high altitude sites such as the Tibetan Plateau causes overestimation of S(sub TOA raised arrow) in these areas. Discrepancies also exist in the simulation of S(sub TOA raised arrow) over ocean areas as CCSM3 does not account for the effect of wind speed on ocean surface albedo. This study shows that the radiative energy budget at the TOA is improved through the use of MODIS albedo in Global Climate Models.

Anantharaj, Valentine G.↗

The Continual Intercomparison of Radiation Codes (CIRC) Assessing Anew the Quality of GCM Radiation Algorithms

The simulation of changes in the Earth's climate due to solar and thermal radiative processes with global climate models (GCMs) is highly complex, depending on the parameterization of a multitude of nonlinearly coupled physical processes. In contrast, the germ of global climate change, the radiative forcing from enhanced abundances of greenhouse gases, is relatively well understood. The impressive agreement between detailed radiation calculations and highly resolved spectral radiation measurements in the thermal infrared under cloudless conditions (see, for example, Fig. 1) instills confidence in our knowledge of the sources of gaseous absorption. That the agreement spans a broad range of temperature and humidity regimes using instruments mounted on surface, aircraft, and satellite platforms not only attests to our capability to accurately calculate radiative fluxes under present conditions, but also provides confidence in the spectroscopic basis for computation of fluxes under conditions that might characterize future global climate (e.g., radiative forcing). Alas, the computational costs of highly resolved spectral radiation calculations cannot be afforded presently in GCMs. Such calculations have instead been used as the foundation for approximations implemented in fast but generally less accurate algorithms performing the needed radiative transfer (RT) calculations in GCMs. Credible climate simulations by GCMs cannot be ensured without accurate solar and thermal radiative flux calculations under all types of sky conditions: pristine cloudless, aerosol-laden, and cloudy. The need for accuracy in RT calculations is not only important for greenhouse gas forcing scenarios, but is also profoundly needed for the robust simulation of many other atmospheric phenomena, such as convective processes.

Oreopoulos, Lazaros↗

Extensive MRO CRISM Observations of 1.27 micron O2 Airglow in Mars Polar Night and Their Comparison to MRO MCS Temperature Profiles and LMD GCM Simulations

The Martian polar night distribution of 1.27 micron (0-0) band emission from O2 singlet delta [O2(1Delta(sub g))] is determined from an extensive set of Mars Reconnaissance Orbiter (MRO) Compact Reconnaissance Imaging Spectral Mapping (CRISM) limb scans observed over a wide range of Mars seasons, high latitudes, local times, and longitudes between 2009 and 2011. This polar nightglow reflects meridional transport and winter polar descent of atomic oxygen produced from CO2 photodissociation. A distinct peak in 1.27 micron nightglow appears prominently over 70-90NS latitudes at 40-60 km altitudes, as retrieved for over 100 vertical profiles of O2(1Delta(sub g)) 1.27 micron volume emission rates (VER). We also present the first detection of much (x80+/-20) weaker 1.58 micron (0-1) band emission from Mars O2(1Delta(sub g)). Co-located polar night CRISM O2(1Delta(sub g)) and Mars Climate Sounder (MCS) (McCleese et al., 2008) temperature profiles are compared to the same profiles as simulated by the Laboratoire de Météorologie Dynamique (LMD) general circulation/photochemical model (e.g., Lefèvre et al., 2004). Both standard and interactive aerosol LMD simulations (Madeleine et al., 2011a) underproduce CRISM O2(1Delta(sub g)) total emission rates by 40%, due to inadequate transport of atomic oxygen to the winter polar emission regions. Incorporation of interactive cloud radiative forcing on the global circulation leads to distinct but insufficient improvements in modeled polar O2(1Delta(sub g)) and temperatures. The observed and modeled anti-correlations between temperatures and 1.27 mm band VER reflect the temperature dependence of the rate coefficient for O2(1Delta(sub g)) formation, as provided in Roble (1995).

Atmosphere↗

Diagnosing Warm Frontal Cloud Formation in a GCM: A Novel Approach Using Conditional Subsetting

This study analyzes characteristics of clouds and vertical motion across extratropical cyclone warm fronts in the NASA Goddard Institute for Space Studies general circulation model. The validity of the modeled clouds is assessed using a combination of satellite observations from CloudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The analysis focuses on developing cyclones, to test the model's ability to generate their initial structure. To begin, the extratropical cyclones and their warm fronts are objectively identified and cyclone-local fields are mapped into a vertical transect centered on the surface warm front. To further isolate specific physics, the cyclones are separated using conditional subsetting based on additional cyclone-local variables, and the differences between the subset means are analyzed. Conditional subsets are created based on 1) the transect clouds and 2) vertical motion; 3) the strength of the temperature gradient along the warm front, as well as the storm-local 4) wind speed and 5) precipitable water (PW). The analysis shows that the model does not generate enough frontal cloud, especially at low altitude. The subsetting results reveal that, compared to the observations, the model exhibits a decoupling between cloud formation at high and low altitudes across warm fronts and a weak sensitivity to moisture. These issues are caused in part by the parameterized convection and assumptions in the stratiform cloud scheme that are valid in the subtropics. On the other hand, the model generates proper covariability of low-altitude vertical motion and cloud at the warm front and a joint dependence of cloudiness on wind and PW.

cyclones↗

CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations

We have identified several errors in the calculations that were performed to create Fig. 3 of Del Genio et al. (2012). These errors affect the composite evolution of precipitation and column water vapor versus lag relative to the Madden-Julian oscillation (MJO) peak presented in that figure. The precipitation and column water vapor data for the April and November 2009 MJO events were composited incorrectly because the date of the MJO peak at a given longitude was assigned to the incorrect longitude band. In addition, the precipitation data for all MJO events were first accumulated daily and the daily accumulations averaged at each lag to create the composite, rather than the averaging of instantaneous values that was used for other composite figures in the paper. One poorly sampled day in the west Pacific therefore biases the composite precipitation in that region at several lags after the MJO peak. Finally, a 4-day running mean was mistakenly applied to the precipitation and column water vapor data rather than the intended 5-day running mean. The results of the corrections are that an anomalous west Pacific precipitation maximum510 days after the MJO peak is removed and the maximum in west Pacific precipitation one pentad before the MJO peak is now more evident; there is now a clear maximum in precipitation for the entire warm pool one pentad before the MJO peak; west Pacific column water vapor now varies more strongly as a function of lag relative to the peak; and precipitation, and to a lesser extent column water vapor, in general vary more smoothly with time. The corrections do not affect any other parts of the paper nor do they change the scientific conclusions we reached. The 4-day running mean error also affects Figs. 1 and 2 therein, with almost imperceptible impacts that do not affect any results or necessitate major changes to the text.

correction↗

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Climate model↗

High altitude smoke in the NASA GISS GCM

High altitude smoke-plumes from large, explosive fires were discovered in the late 1990sThey can now be observed with unprecedented detail from space-borne instruments with high vertical resolution in the UTLS such as CALIOP, MLS and ACE. These events inject large quantities of pollutants into a relatively clean and dry environment They serve as unique natural experiments with which to understand, using chemical transport and composition-climate models, the chemical and radiative impacts of long-lived biomass burning emissions. We are currently studying the Black Saturday bushfires in Australia during February 2009

high altitude↗

Application of the CERES Flux-by-Cloud Type Simulator to GCM Output

The CERES Flux By CloudType data product produces CERES top-of-atmosphere (TOA) fluxes by region and cloud type. Here, the cloud types are defined by cloud optical depth (t) and cloud top pressure (pc), with bins similar to those used by ISCCP (International Satellite Cloud Climatology Project). This data product has the potential to be a powerful tool for the evaluation of the clouds produced by climate models by helping to identify which physical parameterizations have problems (e.g., boundary-layer parameterizations, convective clouds, processes that affect surface albedo). Also, when the flux-by-cloud type and frequency of cloud types are simultaneously used to evaluate a model, the results can determine whether an unrealistically large or small occurrence of a given cloud type has an important radiative impact for a given region. A simulator of the flux-by-cloud type product has been applied to three-hourly data from the year 2008 from the UK Met Office HadGEM2-A model using the Langley Fu-Lour radiative transfer model to obtain TOA SW and LW fluxes.

Eitzen, Zachary↗

Equilibrium Temperatures and Albedos of Habitable Earth-Like Planets in a Coupled Atmosphere-Ocean GCM

The potential habitability of detected exoplanets is typically assessed using the concept of equilibrium temperature (T[subscript] e) based on cloud-free 1-D models with assumed albedo equal to Earth's (0.3) to determine whether a planet lies in the habitable zone. Incident stellar flux appears to be a better metric for stars unlike the Sun. These estimates, however, ignore the effect of clouds on planetary albedo and the fact that the climates of synchronously rotating planets are not well predicted by 1-D models. Given that most planet candidates that will be detected in the next few years will be tidally locked and orbiting M stars, how might the habitable zone e tailored to better in-form characterization with scarce observing resources?

Del Genio, Anthony↗

Including a Cold Pool Representation in a Convection Parameterization and Simulating Its Impacts on the Spatial and Temporal Variability of the Precipitation in the NASA GEOS GCM

We developed and implemented a simple representation of a cold pool in the Grell-Freitas (GF) convection parameterization. The cold pool parameterization is based on the observation that convective-scale downdrafts produce a local ‘deficit’ of the moist static energy (MSE). This information is advected and becoming downwind available to trigger and intensify new convection. The cold pool is dissipated by a simple exponential decay using a lifetime of a few hours, or by interacting with the underneath surface by exchanging latent and sensible heat fluxes. Preliminary results show some improvement of the simulation of the diurnal cycle of the precipitation over the land, mainly during the nighttime.

Cold pools↗

LongRunMIP - Motivation and Design for a Large Collection of Millennial-Length AO-GCM Simulations

LongRunMIP is the first collection of millennial-length simulations of complex coupled climate models and enables investigations of how these models equilibrate in response to radiative perturbations.We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1000+ year) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time-and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1000 years. LongRunMIP is a MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields, and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of summer 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submission of more simulations in the future.

Maria Rugenstein↗

Continuous Habitable Zones: Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

In the near-future, new space telescopes like JWST, LUVOIR, and HabEx will begin attempting to explore the properties of atmospheres of potentially habitable planets. This will require a significant amount of time and resources for even a single planet, which makes it essential to prioritize observations by those most-likely to have detectable life. Here we present a statistical method to estimate the probabilities that specific exoplanets have been continuously in the habitable zone of their host stars for more than 2 billion years, the approximate time it took life on Earth to significantly increase the oxygen content of the atmosphere. We introduce the use of statistics of an ensemble of 3D planetary general circulation models to estimate these probabilities, replacing prior 1D model estimates.

habitable planets↗

Simulating the Martian Middle and Upper Atmosphere with the NASA Ames Mars GCM.

The NASA Ames Mars Global Climate Model (MGCM) continues to be utilized to examine the dynamical coupling between the lower atmosphere and middle/upper atmosphere. This coupling impacts the transport of water, dust, and chemistry which augments the thermal structure and circulation. The interactions and coupling within the atmosphere are important for understanding the present-day and past atmosphere and climate. MGCM simulations are compared with observations from recent Mars missions to provide model constraints, and in turn, the simulations can then provide context to the observations. This cycle is important to move us forward in our understanding of planetary atmospheres. We will present on one of the fundamental atmospheric features, the thermal structure, and how the physics in the MGCM can elucidate the observed diurnal and seasonal behavior. Additionally, we will focus on the distribution of chemical species which influences the thermal structure and provides additional information on the coupling between the lower and middle/upper atmosphere. Lastly, we will provide a summary of the model capabilities, as the MGCM continues to be improved upon to properly simulate Mars’ atmosphere from the ground to ~250 km.

Amanda Susanne Brecht↗

Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

In the near-future, new space telescopes like JWST, LUVOIR, and HabEx will begin attempting to explore the properties of atmospheres of potentially habitable planets. This will require a significant amount of time and resources for even a single planet, which makes it essential to prioritize observations by those most-likely to have detectable life. Here we present a statistical method to estimate the probabilities that specific exoplanets have been continuously in the habitable zone of their host stars for more than 2 billion years, the approximate time it took life on Earth to significantly increase the oxygen content of the atmosphere. We introduce the use of statistics of an ensemble of 3D planetary general circulation models to estimate these probabilities, replacing prior 1D model estimates.

habitable planets↗

Comment on “Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5-T2m” by N. Scafetta (2022)

Scafetta (2022, https://doi.org/10.1029/2022gl097716) purports to test Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models through a comparison of temperature changes over three decades. Unfortunately, the paper contains numerous conceptual and statistical errors that undermine all of the conclusions. First, no uncertainty is given for the observational temperature difference, making it impossible to assess compatibility with any model result. Second, the CMIP6 data are the ensemble means for each model, but the metric being tested is sensitive to the internal variability and so the full ensemble for each model must be used. When this is corrected, the conclusion that “all models with ECS > 3.0°C overestimate the observed global surface warming” is not sustained. Third, the statistical test in Section 2 would reject all models even in a perfect model setup given sufficient ensemble members, thus the second conclusion “that spatial t-statistics rejects the data-model agreement” is also not sustainable.

CMIP6↗

The B Regional Dust Storm in the New NASA Ames Mars GCM

Introduction The Thermal Emission Spectrometer (TES) and the Mars Climate Sounder (MCS) instruments have been ob- serving global dust and temperature on Mars twice daily for a combined ∼12 Mars Years (MYs). Analysis of these data by [5] reveal three highly repeatable, regional scale dust events occurring annually during years lack- ing a global dust storm (GDS). Named the "A," "B," and "C" storms in seasonal order, these recurring dust storms develop in the southern hemisphere of Mars during the perihelion season(Ls =180°–360°)when Mars is closest to the sun and the southern hemisphere experiences sum- mer [5]. The "A" and "C" storms occur in the southern midlatitudes where they amplify the Hadley circulation causing dynamical warming in the northern hemisphere. In contrast, the "B" storm (hereafter, B storm) and its ef- fects are entirely confined to the south pole [5]. All three storms are large enough to inject dust above the boundary layer [8]. As a result, the annually-recurring regional storms produce significant temperature perturbations in the middle atmosphere, raising zonal mean 50 Pa ( 25 km) temperatures above 200 K (Figure 1) [5]. In this work, we seek to identify the mechanisms responsible for lofting dust into the middle atmosphere during the B storm by simulating the storm with the new NASA Ames Mars Global Climate Model (MGCM). We find that the simulated B storm is driven by a series of dust plumes that form in the high southern latitudes during southern summer solstice. We also find that radiative-dynamic feedbacks between airborne dust and incoming shortwave radiation are crucial for the pluming mechanism.

C M L Batterson↗