NCAR Strategic Capability projects 2014-2015

Seeking statistical convergence in large eddy simulations of tropical cyclones

Project lead: George Bryan, MMM
Yellowstone allocation: 5.1 million core-hours

A version of the CM1 numerical model has been configured for large eddy simulation (LES) of tropical cyclones (TCs), with a goal of quantifying near-surface wind gust magnitudes and variability. This project will conduct a statistical convergence test of this modeling framework in a series of simulations that vary the horizontal grid spacing from 100 m to 12.5 m. Although grid spacing of ~100 m has already been shown to produce turbulent flow in TCs, the unprecedented resolution for this study is expected to produce a better representation of near-surface conditions in the TC boundary layer by increasing the effective Reynolds number of the flow. Some existing biases with ~100 m grid spacing, such as maximum wind speeds too close to the ocean surface (compared to observations within TCs), may be mitigated at higher resolution. Post-processing of the output is expected to elucidate both vertical and horizontal turbulent processes in TCs, and can be used to improve existing boundary-layer parameterizations.

Highly-scalable Data Assimilation Research Testbed (DART)

Project lead: Nancy Collins, IMAGe
Yellowstone allocation: 5 million core-hours

The Data Assimilation Research Section (DAReS) group at NCAR develops, distributes, and supports a state-of-the-art data assimilation system, the Data Assimilation Research Testbed (DART). It works with many different models and observation types, including the NCAR community climate and weather models. The DART code has been downloaded by people at over 150 UCAR member institutions; over 400 institutions in total. DART runs on hardware that spans laptops to supercomputers.

In collaboration with researchers in CGD and MMM, DART already runs with the Community Earth System Model (CESM), the Weather Research and Forecast (WRF) model, and the Model for Prediction Across Scales (MPAS). Moving forward, the DAReS group has been redesigning the internal algorithms of DART so that it will scale to larger processor counts while requiring less memory per node, as future hardware projections show this to be the model for upcoming machines.

The redesigned code will need to be run with several large models to verify the accuracy of the new code, and it will have to be run on large processor counts to verify the scaling properties. While the DAReS group itself does not directly do atmospheric science with these systems, the use of DART enables other researchers both at NCAR and across the world to do successful data assimilation and make effective use of their computational resources.

Continuation: Fully coupled data assimilation with CESM + DART

Project lead: Gokhan Danabasoglu, CGD
Yellowstone allocation: 6.3 million core-hours

The scientific challenge of modeling the earth system with sufficient fidelity to inform society on the likelihood of climate change in the future is a formidable one for several reasons. These include the inherent complexity of the coupled earth system, the chaotic nature of its dynamical evolution, and the relative paucity of quality observations of the entire climate system. One of the most powerful methodologies that assist in tackling each of the above-mentioned limitations to scientific progress while providing useful climate information to society on seasonal to decadal time scales is data assimilation. The computer resources requested here will enable us to extend our earlier efforts in ensemble data assimilation for decadal climate predictions and begin the production of a first ever fully coupled reanalysis of CESM. Our science objectives are 1) to build from the current loosely coupled ensemble adjustment Kalman filter data assimilation that we have developed to produce our initial states for the decadal prediction activity in support of the CESM's participation in CMIP5, 2) further develop specific aspects of this system that can be improved, and 3) move all development to a fully coupled atmosphere and ocean assimilation for the purpose of producing a consistent climate system reanalysis for the 1960-2011 period. This final product will serve the dual purpose of producing i) a calibrated reanalysis data set against which we can compare climate simulation and prediction accuracy and ii) a set of ensemble initial conditions that can be used to initialize climate system forecasts of future climate anomalies on seasonal to decadal timescales.

Investigating the importance of climate variability on water resources in a changing climate

Project lead: Clara Deser, CGD
Yellowstone allocation: 9.1 million core-hours

Previous research in two areas has highlighted important concepts in climate research. First, the CCSM3 and CESM large ensemble experiments have illustrated the tremendous variability in climate change signal that can be due entirely to internal variability within the system. Within this ensemble individual members varied in even the sign of the climate change signal for both precipitation and temperature. Second, high-resolution WRF simulations over the Colorado Rocky Mountains have shown that proper representation of the spatio-temporal distribution of precipitation and other climate variables are key to understanding the impact of climate change on water resources. In particular, adequately resolving topography and convection explicitly within the WRF model vastly improved our ability to represent precipitation, including changes from snow to rain, and the mountain snowpack. Here we propose to investigate the combination of these two approaches with high-resolution WRF runs driven by the different runs from the CESM large ensemble. This will address key shortcomings in each of the two previous experiments. The large ensemble was necessarily performed at a resolution too low to resolve either convection or orographic processes, both of which are critical for precipitation estimates used in water resource planning. The Colorado Headwaters WRF experiments were only performed for a single idealized pseudo-global warming climate change scenario, and thus provided no guidance on the uncertainty due to internal variability or the effect of changes in storm track or interannual variability. The planned simulations will address these issues and be useful to many others in the research community.

Local and remote regional climate responses to regional forcings from short-lived climate forcers

Project lead: Jean-Francois Lamarque, ACD/CGD
Yellowstone allocation: 5.3 million core-hours

This project aims at answering the fundamental question: what are the local and remote impacts of the regional perturbations in short-lived climate forcers, as these will be key drivers of regional climate changes over the next several decades? More specifically, we will target perturbations in emissions of short-lived climate forcers or their precursors. We will use a control experiment to provide the baseline and statistical basis for significance analysis. Then we will isolate the impact of a specific region and short-lived climate forcer emissions through a series of regional perturbations (e.g., SO2 emissions from the United States) from this control state.

Study multiscale wave dynamics in the middle and upper atmosphere using high resolution WACCM simulations

Project lead: Hanli Liu, HAO
Yellowstone allocation: 7.5 million core-hours

The dynamics in the middle and upper atmosphere (20-150km, including the stratosphere, mesosphere, lower thermosphere and ionospheric E-region) play a key role in controlling the lower and upper atmosphere coupling, variability of the whole atmosphere system, and the space environment. Processes in this region are uniquely characterized by a broad range of scales and complex interactions among them. The general circulation, transport and variability are affected by wave-wave and wave-mean flow interactions. The ionospheric variability and irregularity, of great interest and importance to space weather, are likely triggered by atmospheric gravity waves originating from the lower atmosphere. Quantifying the effects of the multi-scale processes on dynamics and transport is therefore imperative for understanding the couplings between the lower-upper atmosphere and ion-neutral species. All global upper-atmosphere models, however, either quantify such effects by using parameterizations (in the case of gravity wave effects on large-scale dynamics), which is a major source of model biases and uncertainties, or do not account for such effects at all (in the case of ionosphere irregularity). This is mainly due to the insufficient spatial and temporal resolutions of the upper-atmosphere models, which in turn are constrained by the efficiency of the model algorithm and computing resources. Recently, we have demonstrated the feasibility of making global, whole-atmosphere simulations down to mesoscales using Whole Atmosphere Community Climate Model (WACCM) of the NCAR Community Earth System Model (CESM), by exploiting the high scalability of the Spectral Element (SE) dynamical core from the NCAR High-Order Method Modeling Environment (HOMME) and the computing resources made available by the NCAR Wyoming Supercomputing Center (NWSC). The primary objective of the proposed study is to carry out further and more extensive simulations of WACCM-SE, with NE120 horizontal resolution and 1/10 scale height vertical resolution (209 levels) on the Yellowstone system in order to (1) quantify the characteristics, global distribution, and temporal variability of the resolved waves from the stratosphere to the lower thermosphere; and (2) to evaluate the effects of resolved gravity waves on the large-scale flow, including the mean circulation, tides, and planetary waves.

Mesoscale control of the biological pump

Project lead: Matthew Long, CGD 
Yellowstone allocation: 13.5 million core-hours

Ocean biogeochemical processes are tightly coupled to physics across a range of scales. The oceanic sink for anthropogenic CO2, for instance, is regulated by the rate at which the large-scale overturning circulation exposes deep water. On smaller scales, ocean turbulence regulates the upper-ocean habitat, governing phytoplankton's light and nutrient supply and yielding physical-biological interactions with exceptionally rich structure. As a result of this tight coupling, ocean biogeochemical solutions are intimately tied to the resolution of physical models. We are using global eddy-resolving integrations, enabled with an ocean biogeochemistry model, to investigate the impact of interannual climate forcing and intrinsic ocean variability on ocean biogeochemical dynamics.

A coherent treatment of stratospheric aerosol forcing for climate and chemistry-climate models from 1850 to present

Project lead: Ryan R. Neely, ACD/ASP
Yellowstone allocation: 5.4 million core-hours

This project aims to create an original stratospheric aerosol database for use by NCAR’s CESM and the wider climate and chemistry-climate modeling communities. Current data sets provided for the CESM, as well as most other state-of-the-art models used for inter-comparison projects, tend to lead to overestimations of the impact of large volcanic eruptions and underestimation of the impact of small aerosol loadings that result from moderate volcanic eruptions and background emissions. As such, significant errors are introduced by the current stratospheric aerosol forcings into the simulated climate system. We aim to improve the current generation of forcing files by individually simulating each of the 96 significant volcanic eruptions between 1850 and present and the background periods in between with CESM1(WACCM) coupled to a sectional microphysical model, CARMA. The results of these snapshots will be then combined to create a continuous stratospheric aerosol database. Though CESM1(WACCM/CARMA) has been used extensively for the accurate simulation of individual large volcanic eruptions and short background periods, this work will also be the first application to the entirety of the historical record due to the significant costs associated with running such a detailed aerosol model. The main outcome of this proposal will be the first prescribed stratospheric aerosol forcing file that provides coherent information to both the radiation and chemistry schemes of the CESM over the full historical period.

Continuation: A detailed evaluation of the water cycle over the contiguous United States including potential climate change scenarios

Project lead: Roy Rasmussen, RAL
Yellowstone allocation: 16.5 million core-hours

Recent high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations. A subsequent sensitivity experiment consistent with expected climate change resulted in an enhanced hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and increased total runoff. A total increase of precipitation on the order of 10-25% was found in the pseudo-global-warming experiment, but the enhancement was less pronounced in the core of the Colorado Headwaters due to a rain-shadow effect from upstream mountains. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we expanded our prior modeling study to encompass most of North America. A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western U.S., as well as the very dominant role of convection in the eastern half of the U.S. The planned simulations will leverage many other RAL and NCAR-wide imperatives and frontiers including: applications to wind and solar energy, surface and air transportation issues, predictability of severe weather, quantification of aerosol-cloud interactions, discovery of model biases, and advancement of state of the art numerical models. The WRF-downscaled climate change data will become a valuable community resource for many university groups who are interested in studying regional climate changes and impacts but unable to perform such long-duration and high-resolution WRF-based downscaling simulations of their own.

Investigation of solar dynamo models and magnetic flux emergence

Project lead: Matthias Rempel, HAO
Yellowstone allocation: 11.2 million core-hours

The Sun as a magnetic star exhibits a wide variety of activity, ranging from the fairly regular 11-year cycles of major sunspot eruptions with orderly patterns on the global scales to the intense and more chaotic magnetic fields on the small scales. The Sun shows that magnetism in stars involves both beauty and complexity. The large-scale fields seen as sunspots and active regions follow orderly and systematic cyclic patterns that have long been studied. Both the large-scale and small-scale components contribute to the total magnetic activity of the Sun, which is the primary driver for solar variability. A clear challenge is to understand how solar dynamo action within the interior can yield such diverse and evolving magnetic fields. In this project we will address two key components of this grand challenge: cyclic dynamo action in the solar convection zone and magnetic flux emergence leading to the formation of active regions (sunspot groups).

High resolution ensemble analyses and forecasts of severe convective weather with NCAR’s DART facility and WRF model

Project lead: Glenn Romine, MMM/IMAGe
Yellowstone allocation: 8.3 million core-hours

Forecasts of convective precipitation systems remain a considerable challenge for the weather community, but recent progress in convection-permitting ensemble forecasting methods provide a path forward by providing guidance on convective forecast uncertainty. Ensemble data assimilation serves as a foundation for ensemble forecast systems, differentiating locations with the greatest initial condition uncertainty, while ensemble forecasts evolve this uncertainty and can map how the limited information in the initial state impacts forecast outcomes. The proposed project aims to continue foundational progress in ensemble prediction of high-impact convective weather using NCAR’s Data Assimilation Research Testbed (DART) facility and Advanced Research Weather Research and Forecast (WRF) model. During this allocation period we will investigate 1) the impact of ensemble size on analysis system performance, 2) performance differences between hybrid and pure ensemble analysis approaches, 3) long-term continuous versus partial cycling for high-resolution analysis, 4) mesoscale predictability experiment (MPEX) observation impact studies, and 5) real-time analysis and forecast exercises.

Global forecasts experiments using MPAS

Project lead: William Skamarock, MMM
Yellowstone allocation: 7.2 million core-hours

We propose to further test, develop, and apply the nonhydrostatic atmospheric component of the Model for Prediction Across Scales (MPAS-A) to problems in (i) atmospheric prediction and dynamics involving tropical cyclones, (ii) midlatitude convection, and (iii) tropical convection, including MJO dynamics and scale interactions associated with precipitation processes in the tropical western Pacific with extratropical waves. We will also test the ability of MPAS-A, coupled with the ensemble Kalman filter assimilation system in the Data Assimilation Research Testbed (DART), to produce high-resolution global analyses to support these applications.

A large-eddy simulation study of Southern Ocean boundary layers

Project lead: Peter Sullivan, MMM 
Yellowstone allocation: 6.5 million core-hours

Climate models exhibit large persistent unexplained bias in the Southern Ocean mainly because of their parameterization of the ocean boundary layer (OBL); generally the depth of the modeled boundary layers is quite shallow compared to observations. The objective of this NSC project is to shed light on this bias by isolating key dynamical processes missing in the parameterizations that control turbulent mixing and scalar transport in the Southern Ocean OBL. The scientific approach relies on analyzing fine resolution large-eddy simulation (LES) forced by winds, surface heating-cooling, and surface waves representative of observations collected at the Southern Ocean Flux Station (SOFS). The LES model includes time varying phase-averaged wave-current interactions and surface forcings, and larger scale oceanic submesoscale activity (temperature fronts and filaments). All simulations use at least 109 gridpoints and a typical simulation utilizes 106 core-hours running on 2048 processors.

First decadal assimilation of satellite carbon monoxide observations for quantifying pollutant emission trends and interannual variability and for future atmospheric composition satellite mission planning

Project lead: Helen Worden, ACD 
Yellowstone allocation: 6.7 million core-hours

Atmospheric carbon monoxide (CO) provides a signature for anthropogenic combustion-related pollution emissions, and also serves as the reference for the emissions of many difficult-to-measure pollutants. Recent results from satellite total column CO measurements showed decreasing global CO values in time series of over the past decade. All of the satellite instruments showed consistent inter-annual variability due to fires and possibly the global recession in late 2008. The longer MOPITT (Measurements of Pollution in the Troposphere) data record shows around 1%/year decrease in the northern hemisphere. Observed decreases in CO over North America and Europe are consistent with decreases expected from emissions inventories. However, the decrease in total column CO observed by the satellite data for eastern China is not indicated by most of these inventories. Explaining the observed inter-annual variability and long-term trends for CO is of critical importance for atmospheric chemistry and climate modeling. This project aims to assimilate the 13-year MOPITT record of satellite CO observations into CAM-Chem v4 with DART (Data Assimilation Research Testbed) in order to estimate CO emissions globally and into WRF-Chem to study finer scales in regions of special interest. This assimilation framework also applies to OSSE (Observation Simulation System Experiment) activities that support planning for future satellite missions being considered for a geostationary satellite constellation for air quality observations.