A comparison of simulated cloud radar output from the multiscale modeling framework global climate model with CloudSat cloud radar observations

2009 ◽  
Vol 114 ◽  
Author(s):  
Roger Marchand ◽  
John Haynes ◽  
Gerald G. Mace ◽  
Thomas Ackerman ◽  
Graeme Stephens
Keyword(s):  
Multiscale Modeling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Modeling Framework ◽  
Radar Observations ◽  
Cloud Radar ◽  
Multiscale Modeling Framework

scholarly journals Calibration of the 2007–2017 record of ARM Cloud Radar Observations using CloudSat

2019 ◽  
Author(s):  
Pavlos Kollias ◽  
Bernat Puigdomènech Treserras ◽  
Alain Protat
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Operating Mode ◽  
Historical Record ◽  
Department Of Energy ◽  
Radar Observations ◽  
Cloud Radar ◽  
Radar Network ◽  
The Us

Abstract. The US Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) program has been at the forefront of millimeter wavelength radar development and operations since the late 90’s. The operational performance of the ARM cloud radar network is very high; however, the calibration of the historical record is not well established. Here, we use a well-characterized spaceborne 94-GHz cloud profiling radar (CloudSat) to characterize the calibration of the different generations of the ARM cloud radars from 2007 to 2017 over a variety of climatological regimes and for fixed and mobile deployments. Over 43 years of ARM profiling cloud radar observations are compared to CloudSat and the calibration offsets are reported as a function of time using a sliding window of 6 months. The study also provides the calibration offsets for each operating mode of the ARM cloud radars. Overall, significant calibration offsets are found that exceed the uncertainty of the technique (1–2 dB). The findings of this study are critical to past, on-going and planned studies of cloud and precipitation and should assist the DOE ARM to build a legacy decadal ground-based cloud radar dataset for global climate model validation.

scholarly journals Calibration of the 2007–2017 record of Atmospheric Radiation Measurements cloud radar observations using CloudSat

2019 ◽  
Vol 12 (9) ◽  
pp. 4949-4964 ◽  
Author(s):  
Pavlos Kollias ◽  
Bernat Puigdomènech Treserras ◽  
Alain Protat
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Operating Mode ◽  
Historical Record ◽  
Department Of Energy ◽  
Atmospheric Radiation ◽  
Radar Observations ◽  
Cloud Radar ◽  
Radiation Measurements

Abstract. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurements (ARM) facility has been at the forefront of millimeter-wavelength radar development and operations since the late 1990s. The operational performance of the ARM cloud radar network is very high; however, the calibration of the historical record is not well established. Here, a well-characterized spaceborne 94 GHz cloud profiling radar (CloudSat) is used to characterize the calibration of the ARM cloud radars. The calibration extends from 2007 to 2017 and includes both fixed and mobile deployments. Collectively, over 43 years of ARM profiling cloud radar observations are compared to CloudSat and the calibration offsets are reported as a function of time using a sliding window of 6 months. The study also provides the calibration offsets for each operating mode of the ARM cloud radars. Overall, significant calibration offsets are found that exceed the uncertainty of the technique (1–2 dB). The findings of this study are critical to past, ongoing, and planned studies of cloud and precipitation and should assist the DOE ARM to build a legacy decadal ground-based cloud radar dataset for global climate model validation.

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

2021 ◽  
pp. 109434202110275
Author(s):  
Matthew R Norman ◽  
David A Bader ◽  
Christopher Eldred ◽  
Walter M Hannah ◽  
Benjamin R Hillman ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Simulation ◽  
Modeling Framework ◽  
Multi Scale ◽  
Scale Modeling ◽  
Computational Capability ◽  
Parallel Data

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

scholarly journals A single column simulation-based decomposition of the tropical upper tropospheric warming

2021 ◽  
pp. 1-36
Author(s):  
Yuwei Wang ◽  
Yi Huang
Keyword(s):  
Relative Humidity ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Dilution Effect ◽  
Lapse Rate ◽  
Modeling Framework ◽  
Single Column ◽  
Convective Adjustment

AbstractAn atmospheric global climate model (GCM) and its associated single-column model are used to study the tropical upper tropospheric warming and elucidate how different processes drive this warming. In this modeling framework, on average the direct radiative process accounts for 13% of the total warming. The radiation increases the atmospheric lapse rate and triggers more convection, which further produces 74% of the total warming. The rest 13% is attributable to the circulation adjustment. The relative importance of these processes differs in different regions. In the deep tropics, the radiative-convective adjustment produces the most significant warming and accounts for almost 100% of the total warming. In the subtropics, the radiative-convective adjustment accounts for 73% of the total warming and the circulation adjustment plays a more important role than in the deep tropics, especially at the levels above 200 hPa. When the lateral boundary conditions, i.e. the temperature and water vapor advections, are held fixed in single-column simulations, the tropospheric relative humidity significantly increases in the radiative-convective adjustment in response to the surface warming. This result, in contrast to the relative humidity conservation behavior in the GCM, highlights the importance of circulation adjustment in maintaining the constant relative humidity. The tropical upper tropospheric warming in both the full GCM and the single-column simulations is found to be less strong than the warming predicted by reference moist adiabats. This evidences that the sub-moist-adiabat warming occurs even without the dilution effect of the large-scale circulation adjustment.

Evaluation of Hydrometeor Occurrence Profiles in the Multiscale Modeling Framework Climate Model Using Atmospheric Classification

2009 ◽  
Vol 22 (17) ◽  
pp. 4557-4573 ◽  
Author(s):  
Roger Marchand ◽  
Nathaniel Beagley ◽  
Thomas P. Ackerman
Keyword(s):  
Multiscale Modeling ◽  
Great Plains ◽  
Large Scale ◽  
Climate Model ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Modeling Framework ◽  
Neural Network Approach ◽  
Atmospheric State ◽  
Multiscale Modeling Framework

Abstract Vertical profiles of hydrometeor occurrence from the multiscale modeling framework (MMF) climate model are compared with profiles observed by a vertically pointing millimeter wavelength cloud radar (located in the U.S. southern Great Plains) as a function of the large-scale atmospheric state. The atmospheric state is determined by classifying (or clustering) the large-scale (synoptic) fields produced by the MMF and a numerical weather prediction model using a neural network approach. The comparison shows that for cold-frontal and post-cold-frontal conditions the MMF produces profiles of hydrometeor occurrence that compare favorably with radar observations, while for warm-frontal conditions the model tends to produce hydrometeor fractions that are too large with too much cloud (nonprecipitating hydrometeors) above 7 km and too much precipitating hydrometeor coverage below 7 km. It is also found that the MMF has difficulty capturing the formation of low clouds and that, for all atmospheric states that occur during June, July, and August, the MMF produces too much high and thin cloud, especially above 10 km.

scholarly journals Understanding the contributions of aerosol properties and parameterization discrepancies to droplet number variability in a global climate model

2014 ◽  
Vol 14 (9) ◽  
pp. 4809-4826 ◽  
Author(s):  
R. Morales Betancourt ◽  
A. Nenes
Keyword(s):  
Chemical Composition ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geometric Mean ◽  
Computational Cost ◽  
Activation Process ◽  
Liquid Water Path ◽  
Modeling Framework

Abstract. Aerosol indirect effects in climate models strongly depend on the representation of the aerosol activation process. In this study, we assess the process-level differences across activation parameterizations that contribute to droplet number uncertainty by using the adjoints of the Abdul-Razzak and Ghan (2000) and Fountoukis and Nenes (2005) droplet activation parameterizations in the framework of the Community Atmospheric Model version 5.1 (CAM5.1). The adjoint sensitivities of Nd to relevant input parameters are used to (i) unravel the spatially resolved contribution of aerosol number, mass, and chemical composition to changes in Nd between present-day and pre-industrial simulations and (ii) identify the key variables responsible for the differences in Nd fields and aerosol indirect effect estimates when different activation schemes are used within the same modeling framework. The sensitivities are computed online at minimal computational cost. Changes in aerosol number and aerosol mass concentrations were found to contribute to Nd differences much more strongly than chemical composition effects. The main sources of discrepancy between the activation parameterizations considered were the treatment of the water uptake by coarse mode particles, and the sensitivity of the parameterized Nd accumulation mode aerosol geometric mean diameter. These two factors explain the different predictions of Nd over land and over oceans when these parameterizations are employed. Discrepancies in the sensitivity to aerosol size are responsible for an exaggerated response to aerosol volume changes over heavily polluted regions. Because these regions are collocated with areas of deep clouds, their impact on shortwave cloud forcing is amplified through liquid water path changes. The same framework is also utilized to efficiently explore droplet number uncertainty attributable to hygroscopicity parameter of organic aerosol (primary and secondary). Comparisons between the parameterization-derived sensitivities of droplet number against predictions with detailed numerical simulations of the activation process were performed to validate the physical consistency of the adjoint sensitivities.

Evaluation of the Multiscale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program

2006 ◽  
Vol 19 (9) ◽  
pp. 1716-1729 ◽  
Author(s):  
Mikhail Ovtchinnikov ◽  
Thomas Ackerman ◽  
Roger Marchand ◽  
Marat Khairoutdinov
Keyword(s):  
Multiscale Modeling ◽  
Great Plains ◽  
Climate Model ◽  
Atmospheric Model ◽  
Atmospheric Radiation ◽  
Radiation Measurement ◽  
Modeling Framework ◽  
Atmospheric Radiation Measurement ◽  
Radiation Parameterizations ◽  
Multiscale Modeling Framework

Abstract In a recently developed approach to climate modeling, called the multiscale modeling framework (MMF), a two-dimensional cloud-resolving model (CRM) is embedded into each grid column of the Community Atmospheric Model (CAM), replacing traditional cloud and radiation parameterizations. This study presents an evaluation of the MMF through a comparison of its output with the output from the CAM and with data from two observational sites operated by the Atmospheric Radiation Measurement Program, one at the Southern Great Plains (SGP) in Oklahoma and one at the island of Nauru in the tropical western Pacific (TWP) region. Two sets of one-year-long simulations are considered: one using climatological sea surface temperatures (SSTs) and another using 1999 SST. Each set includes a run with the MMF as well as a CAM run with traditional or standard cloud and radiation treatments. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are analyzed. For the TWP site, the distributions of these variables from the MMF run are shown to be more consistent with observation than those from the CAM run. This change is attributed to the improved representation of convective clouds in the MMF compared to the conventional climate model. For the SGP, the MMF shows little to no improvement in predicting the same quantities. Possible causes of this lack of improvement are discussed.

High bit rate ACTS experiments for performing global science - Keck Telescope and global climate model

1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Bit Rate ◽  
Global Science ◽  
High Bit Rate
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