Strategic Priority: Improving prediction of weather, climate, and other atmospheric phenomena

Weather Research and Forecasting/Advanced Research WRF (WRF/ARW)

The overall goal of the WRF model project is to develop a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. WRF has been developed as a collaborative effort among NCAR (ESSL, MMM Division), NOAA's National Centers for Environmental Prediction (NCEP) and Earth System Research Laboratory (ESRL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for the Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of numerous university scientists. WRF was intended to improve the forecast accuracy of significant weather features across scales ranging from cloud to synoptic, with priority emphasis on horizontal grids of 1–10 kilometers. The model incorporates advanced numerics and data assimilation techniques, a nesting capability supporting multiple and moving grids, and a range of physics options, particularly for treatment of convection and mesoscale precipitation systems. It is well-suited for a wide range of applications, from idealized simulations to operational forecasting, with the flexibility to accommodate a range of potential enhancements.

MMM scientists instigated the WRF endeavor nearly a decade ago to promote closer ties between research and operational model development. Since then, WRF has matured to become the dominant mesoscale model in the United States, with extensive worldwide use as well. MMM has had the lead role in the development of the WRF software infrastructure and the Advanced Research WRF (ARW) dynamic core and in maintaining and supporting the system for the research community. The WRF effort provides the primary facility for supporting the NCAR strategic priority of investigation of the dynamics and predictability of weather systems on time scales of 0–48 h. In addition, it furthers NCAR’s mission to provide and support state-of-the-art modeling systems for broad use in the research community.

Within MMM, project activities are distributed across three areas: 1) development and enhancement of WRF capabilities to meet the needs of MMM and community-research objectives; 2) research to advance the understanding and prediction of high-impact weather systems; and 3) model support to the research community. The effort is ongoing as the WRF system evolves to meet future requirements for advanced weather research and forecasting, while timelines attend deliverables in specific funded projects and in commitments to provide modeling capabilities for MMM and the research community.

During the past year, NCAR continued to develop new capabilities for the ARW and support it to the community. Over 1100 new users registered to download the code, bringing the total number of registered users to over 5,300. Over half of this total is non-US users, and over 90 countries are represented. In June 2007 MMM organized and conducted the 8th Annual WRF Users’ Workshop, with 220 participants attending from 26 countries. MMM personnel also conducted three user tutorials on the ARW and the WRF-VAR data assimilation system. Two of these were in Boulder, with approximately 60 persons, while another was in Seoul, Korea. Operational forecasting with the ARW continued at NCEP and AFWA (worldwide regional theatres), and new operational applications began in Korea, Taiwan, and India.

MMM manages the WRF code repository, assists community researchers in development, coordinates additions to the repository, and oversees the code integration and testing for new releases. This past year, MMM released WRF Version 2.2 (December 2006). Key features of V2.2 were:

1. the WRF Preprocessing System (WPS);
2. analysis and observation nudging capabilities;
3. positive-definite advection;
4. new and modified physics options;
5. ESMF component support;
6. I/O enhancements; and
7. updated graphics tools components.
   

The WPS is a major advancement, simpler and more computationally efficient than its predecessor. The two nudging schemes have met user needs for this data assimilation approach, and the positive-definite advection scheme in general reduces the overprediction of precipitation. A new development for the ARW is a global version of the solver, produced by scientists at the California Institute of Technology and Cornell University. This “Global ARW” is being tested now by scientists in MMM, and the intention is a release to the community in WRF Version 3.0 (described below). The evaluation of global approaches was one of MMM’s goals from last year and has been accomplished. Recent NCAR advancement of the Global ARW has included updating to the latest version of WRF, increasing code efficiency (via parallelization), and modifying pre- and post-processors to allow full-Earth NWP capabilities. Testing on the global model’s performance and scaling on precursor-to-petascale computing systems was also conducted, and benchmarking and tuning of the code on tens of thousands of processors on IBM and Cray HPC systems is underway.

Global ARW has been tested through retrospective forecasts. Figure 1 depicts a 10-d forecast of precipitable water from a 50-km run, valid 1200 UTC 22 July 2007. Initial results from such tests indicate that, qualitatively, the model is producing plausible forecasts. For operational applications, the global ARW is being considered for use by the Korean Meteorological Agency (KMA). For the research community, the global capability will allow the removal of lateral boundary constraints in both forecasting and data assimilation.

In data assimilation developments, WRF-Var’s radiance assimilation capability was extended to use the JCSDA’s Community Radiative Transfer Model (CRTM), while a new satellite observation type, Special Sensor Microwave Imager/Sounder (SSMI/S) data, can now be ingested by WRF-Var. The development of 4DVAR produced the latest system (Version 2.2) that: runs as a combination of WRF (V2.2), WRF+ (WRF tangent linear and adjoint models), and WRF-Var (V2.1 with 4DVAR extensions) executables; runs on multi-processor architectures; and includes a penalty term to control noise during the minimization. Lastly, the WRF-Var system was expanded in 2007 to include an ensemble data assimilation component. This hybrid approach combines the benefits of the current 3D- and 4DVAR techniques in WRF-Var with the benefits of flow-dependent forecast error estimates.

MMM has continued to apply the ARW in the Antarctic Mesoscale Prediction System (AMPS) for real-time NWP support for the United States Antarctic Program. Over the past year MMM personnel have incorporated WRF polar modifications developed primarily at collaborator The Ohio State University into WRF V2.2. This “Polar WRF” has been run in test mode within AMPS. The modifications include fractional sea ice representation and changes to surface characteristics to better capture the conditions of ice sheets. It is found that the polar modifications improve low-level temperature predictions over Antarctica.

Last year’s goals for the ARW effort included: assisting domestic and international users of the ARW, conducting the 8th WRF Users Workshop in June 2007 and tutorials in January and July 2007, and releasing V2.2. All of these were accomplished. Capabilities listed for development in last year’s report were upper boundary gravity-wave absorption and testing of the positive definite advection scheme. The gravity wave absorption layer, involving Rayleigh damping, has been implemented into the repository, and the positive-definite scheme was released in V2.2. MMM now has a digital filter for use in ARW initialization that continues to undergo testing and development and is planned for the next release. MMM had planned to analyze past real-time convection-resolving forecasts, such as those conducted in support of the Storm Prediction Center’s (SPC) Spring experiments for the past few years. In addition to MMM scientists performing such an analysis, this year they produced real-time, 3-km, convection-permitting ARW runs for the Spring 2007 SPC Hazardous Weather Testbed experiment. These forecasts exhibited noticeable improvements over their predecessors from previous years. Figure 2 shows an accurate 25-hr ARW 3-km forecast for a tornadic squall line event of April 14, 2007. In other convection-permitting, real-time ARW applications, MMM again ran seasonal Atlantic hurricane forecasts. This year brought the highest resolution ever: 1.33-km spacing over the innermost domain of a nested, 3-grid configuration.

For the upcoming year, MMM plans a major new release— Version 3.0 (V3.0). This is slated for March 2008. The Global ARW will be further tested and included in V3.0. To improve the management of WRF contributed code, MMM has drafted procedures for the administration of the repository and of releases, and these will be finalized and published. This will also better inform the user community of the mechanisms and timetables for code submission and testing and of releases by MMM. In ARW applications, MMM will switch to using the Polar WRF in its AMPS forecasts.

The WRF modeling system will continue to serve as a tremendous scientific tool for the weather and climate research communities. It is a high-performance computational model that scales well from single-processor environments to massively-parallel petascale applications. In addition to being a state-of–the-art weather prediction model, it has been adapted to atmospheric chemistry, air quality, and nested regional climate applications. The successful migration of WRF into operational forecasting yields significant economic and societal benefits. Supporting WRF for widespread community use greatly leverages resources by allowing researchers access to a sophisticated atmospheric tool without a large resource investment, but with the opportunity to contribute to, and benefit from, the advancement of a common modeling system.

The WRF effort within MMM is supported by NCAR/NSF base funds through the MMM Division budget and USWRP resources, from the NSF Office of Polar Programs, and from outside-funded projects with AFWA, the FAA, KMA (Korea), and CWB and CAA (Taiwan).

 

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Community Climate Systems Model: Advancing Climate Science

Historical context and rationale

The development and continuous improvement of a comprehensive climate modeling system that is at the forefront of international efforts to understand and predict the behavior of the Earth's climate is a high priority of NCAR research. This includes the Community Climate System Model (CCSM) as well as its component models. The CCSM, run on some of the world's most powerful supercomputers, simulates the many interconnected events that drive Earth's climate. These include changes in the atmosphere and oceans, the ebb and flow of sea ice, and the subtle impacts of forests and rivers.

CCSM is unique among the most advanced of comprehensive global climate models. Primarily supported by the National Science Foundation (NSF) and the Department of Energy (DOE), with additional support from the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA), it belongs to the entire community of climate scientists, rather than to a single institution. Hundreds of specialists from around the world collaborate on improvements to CCSM. The model's underlying computer code is freely available on the Web. As a result, scientists throughout the world can use CCSM for their climate experiments.

The CCSM project was started in 1994, although climate modeling at NCAR has a much longer history stretching back to about 1980. The first version of CCSM was unveiled in 1998, and the most recent version, CCSM-3, was released in 2004. CCSM-3 represents a major advance over earlier versions of the model because its formulation contains far more information about Earth's physical processes. For example, it tracks the flow of major rivers that empty into the oceans and influence currents such as the Gulf Stream, and it now resolves five different thickness categories of sea ice within each grid cell, such as the thickness and the melt rate. Moreover, the finer scale of its resolution allows scientists to capture significantly greater detail about ocean currents and the mixing of salt and fresh water.

Accomplishments in FY 2007

The CCSM project continued to play a major role in the Fourth Assessment Report (AR4) by Working Group One of the Intergovernmental Panel on Climate Change (IPCC) through the completion and analysis of an extensive series of emission scenario experiments. The suite of CCSM-3 experiments is the most extensive and highest-resolution multimember ensemble of any of the international global coupled models run for the IPCC AR4. The resulting large data sets are freely available to the climate research and education community via the Earth System Grid (ESG), and a subset of the data is archived at the DOE Program for Climate Model Diagnosis and Intercomparison (PCMDI). The CCSM data are part of the Climate Model Evaluation Project (CMEP), which includes over 200 researchers from around the world who analyzed the multi-model data set for the IPCC AR4.

Many ESSL scientists have served as convening lead authors, lead authors, and contributing authors to the IPCC AR4 and the Technical Summary and Summary for Policy Makers, all of which were published during the first half of 2007. The major conclusion of the AR4 is that the observed increase in the Earth's surface temperature over the last 30 years is "almost certainly" caused by the increase in anthropogenic carbon dioxide and other greenhouse gases in the atmosphere. The report also contained the projections until 2100 from the CCSM and twenty other climate models, given different scenarios for the future increase of carbon dioxide and other greenhouse gases in the atmosphere. The publication of the IPCC AR4 completed a major project by the CCSM and many of its scientists.

Plans for FY 2008

One of the higher-priority short-term activities of the CCSM program is a concerted effort to address systematic model biases, such as the warm sea surface temperatures (SST) under the stratocumulus regions off the west coasts of North America, South America and Africa. Several hypothesis-driven activities are under way in collaboration with colleagues outside of NCAR to address such biases, which are common in other global models as well. The reduction of such biases becomes even more important as the complexity of CCSM increases, and questions about climate change focus more on regional scales of motion.

In addition, new collaborative efforts have started within ESSL to examine, in climate simulations with embedded regional models, the importance of explicitly resolving mesoscale and microscale processes that govern weather and local climate, but that may also have significant impacts on the large-scale circulation.

The current implementation plan of the CCSM project is to develop and freeze the next version of the model, CCSM-4, by the end of 2008. In addition to several other improvements, this version will have the new components for the carbon cycle and interactive atmospheric chemistry. Development activities will also be guided by the goal of including new capabilities, such as the ability to examine climate change questions at very high spatial resolution on near-term decadal time scales. This development activity will enable a whole new range of scientific questions to be asked of, and answered by, the CCSM where it is our expectation that the CCSM-4 will be the model used to contribute to the next IPCC AR5.

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U.S. Weather Research Program/Short Term Explicity Prediction Program (USWRP/STEP)

The ShortTerm Explicit Prediction (STEP) Program is a newly established multi NCAR Laboratory activity to improve the short-term forecasting of high-impact weather such as severe thunderstorms, winter storms, and hurricanes. Improving short-term forecasts of such weather can have significant societal and economic benefits, including: (1) reduced fatalities and injuries due to weather hazards; (2) reduced private, public, and industrial property damage; and (3) improved efficiency and savings for industry, transportation, and agriculture. The STEP Program is also being stimulated by the significant advancement in a number of fields that are required to make progress in this area. These include the ability to observe the four-dimensional structure of the atmosphere, the development of new data assimilation techniques, such as 3DVar/4DVar and the Ensemble Kalman Filter (EnKF), and the continuing development of numerical modeling systems, such as the Advanced Research/Weather Research and Forecasting model (WRF/ARW), that can be run at grid resolutions that properly represent the physical processes critical to the production of such hazardous weather. The program includes research into basic understanding of high-impact weather systems, development of forecast techniques, real-time testing of forecast systems, verification, and interaction with users. This collaborative effort incorporates national and international scientists, engineers, and operational personnel from universities, government institutions and the private sector.

The primary activity for STEP this year was the development of an implementation plan to help coordinate research efforts across the institution (see http://www.mmm.ucar.edu/STEP) and the organization of a retrospective study using IHOP data. A workshop was conducted in October 2006 to report on progress for each project and to discuss future coordination. In order to better accomplish the STEP goal as stated in the STEP strategic plan, a process to redistribute the STEP funds for the next two-year funding cycle has been conducted and nearly completed. On the research level, a wide range of activities that are central to STEP research goals, and that involve MMM, RAL and EOL scientists have been ongoing over the past year(s). Within MMM, WRF/ARW development efforts continue to be a critical component of STEP, offering a range of new capabilities, from improved numerics and physics to new data assimilation systems that can address the short-term forecast problem. Other than the variety of basic research and development, one of the major themes in STEP is to demonstrate high resolution forecasting systems in real time. In collaboration with the Spring 2007 SPC/NSSL Hazardous Weather Testbed experiment, WRF/ARW was run at a 3-km horizontal grid resolution over the central U.S. to produce explicit 0-36 hour convective forecasts. These forecasts were evaluated by forecasters and researchers from across the country, and exhibited noticeable improvements over past years, especially as regards the representation of convective precipitation. STEP's nowcasting system and the radar data assimilation system VDRAS were demonstrated in Beijing as part of the WMO sponsored Olympics 2008 forecasting demonstration project. A number of STEP scientists were involved in the planning of future field programs that emphasize mesoscale predictability, such as VORTEX2 and TiMREX

One of the critical components of STEP is the development of advanced data assimilation systems for WRF that can assimilate high-resolution observations. Assimilation of radial velocity and reflectivity from multiple Doppler radars were further explored, using WRF 3DVar and WRF EnKF assimilation systems and a 4DVar system of a cloud-scale model (VDRAS), in a number of case studies. The objective is to improve short-term forecasting of high-impact weather by initializing the numerical models at the cloud resolving resolution. From these studies it was found that the inclusion of high-resolution radar observations significantly reduced the model spin-up problem, hence improved forecasting skills in the short range, especially in the first six hours. In the coming year, these data assimilation systems will be run on the same IHOP data for a period of one week. Comparisons will be made to evaluate strengths and weaknesses of each data assimilation system and the impact of including radar in the assimilation. The assimilation of radar refractivity will also be performed by some of the assimilation systems. Efforts at developing new techniques for verifying high-resolution forecast guidance will be continued. Future development of verification will focus on this intercomparison to understand the strengths and weaknesses of different approaches.

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Data assimilation/ensembles

Data assimilation is the process of combining observations and a previous forecast to provide a gridded estimate of the atmospheric state at a certain time. These estimates can then be used as initial conditions for subsequent forecasts or as tools to analyze and understand the atmosphere. While much progress has been made at global scales, data assimilation for scales of less than a few hundred kilometers (the "mesoscale," where most severe and damaging weather occurs) remains a significant open problem in atmospheric science. Mesoscale data assimilation is especially challenging for two reasons. First, mesoscale motions are intimately coupled to complex physical processes such as those involving moisture, cloud and rain or interaction with the land or ocean surface. These processes are difficult to represent accurately in numerical models. They also lead to distinct and strongly nonlinear dynamics at the mesoscale, so that balances between mass and wind, which pertain at large scales in the atmosphere and underlie global data assimilation schemes, are questionable at the mesoscale. Second, observations that are plentiful (e.g., Doppler radar measurements of wind and reflectivity) involve only a subset of atmospheric variables, while observing platforms that measure all relevant variables (i.e., radiosondes) are sparse and resolve mesoscale motions poorly. To overcome these difficulties, there has been substantial effort within ESSL/MMM to advance mesoscale data assimilation.

As discussed in last year's report, a significant component of these efforts has been to build, and support for the community, a data assimilation facility for WRF based on variational assimilation techniques, known as WRF-Var. The WRF-Var system continues to be widely used in research at universities and as the basis for operational assimilation system development at the U.S. Air Force Weather Agency (AFWA) and several other operational centers internationally. The capability for direct assimilation of radiances will be officially supported to the community beginning with the WRF3.0 release in Spring 2008.

In addition, the four-dimensional variational assimilation (4DVar) system within WRF-Var has been enhanced through the development of simplified physical parameterizations for use in the tangent-linear and adjoint models, the implementation of a multi-incremental approach for minimizaiton, a gravity-wave penalty term in the cost function based on a digital filter and substantial optimization and parallelization of the code. While WRF 4DVar is no longer planned for operational implementation at AFWA in 2008 owing to budget cuts, development of the system is ongoing. Support for this work includes NSF, USWRP, AFWA, KMA, CAA, NASA, CRIEPI, BMB, and USAID.

An additional component of ESSL/MMM's research has been in the area of ensemble-based data assimilation. In collaboration with the Data Assimilation Research Section within CISL/IMAGe, an ensemble Kalman filter for WRF has been developed within the Data Assimilation Research Testbed; this assimilation system is known as WRF/DART. One recent application of WRF/DART has been to investigate the value of surface data assimilation for mesoscale numerical weather prediction. Through a collaborative project with the National Severe Storms Laboratory, daily WRF ensemble forecasts covering the continental U.S. were produced in the Spring and Summer of 2007. These forecasts were initialized from the NAM analyses, followed by hourly EnKF assimilation of surface observations for 6 hours. Mesoscale structures and precipitation developed in the WRF ensemble during the assimilation window, allowing subsequent very short-term precipitation forecasts to be made (Fig. 1). The forecast improvement through surface data assimilation was particularly noted in the forecasts of precipitation and low-level water vapor out to 6 hours. In Spring 2008, the effort will be expanded to include full cycling (longer assimilation windows) and assimilation of conventional upper air observations (soundings, profiler data, etc.).

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THe Observing-system Research and Predictability EXperiment (THORPEX)

One aspect of the TIIMES mission is to be the administrative home of programs that cut across the divisional and laboratory structure of NCAR. One such effort is THORPEX (The Observing-System Research and Predictability Experiment), which is a long-term effort within the World Meteorological Organization’s World Weather Research Program. The overarching goals of THORPEX are to accelerate both the forecast skill of high impact weather events on the 1 to 14-day time scale and utilization of forecast information. THORPEX research is meant to benefit society, the economy and the environment with one focus to mitigation of disasters in the developing world. While THORPEX was designed to concentrate on the 1 to 14-day time-scale, THORPEX is also developing collaborations with the World Climate Research Program for time-scales that fall between the time-scales of numerical weather prediction and climate projections. These time-scales include seasonal prediction and longer subseasonal time-scales, such as the Madden Julian Oscillations. The THORPEX and the WCRP collaboration includes research on topics of mutual interest (e.g., improving the characterization in numerical models of a variety of processes that include tropical convection, polar precipitation events and the triggering and enhancements of Rossby wave trains).

TIIMES hosts both the US THORPEX Project and the co-chair of the North American THORPEX Regional Committee. Both efforts are led by David Parsons. The THORPEX research effort in the US already has significant participation within the university community and the effort has the potential to involve weather and climate researchers within ESSL at NCAR and the activities of CISL, RAL and SERE. One aspect of THORPEX is to move the user and research community from relying on deterministic forecasts to ensemble forecast systems that better represent the uncertainty in simulations of the non-linear, partly chaotic nature of the atmosphere. During the past year, NCAR CISL initiated an archive of the ensemble members of the ensemble global forecasts of the major operational forecast centers, which when fully operational will include ~256 ensemble members produced daily for forecast periods from 1 to 14-days. The archive includes the basic model derived parameters as well as derived parameters that are of interest to researchers. This ensemble archive is called TIGGE (THORPEX Interactive Grand Global Ensemble). TIGGE is well utilized by the research community as, for example, within months of opening the beta test phase of archive there were over 50 registered users.

Parsons research activities during the past year include continuing research on a driftsonde observing system test for THORPEX during the AMMA campaign. The driftsonde system consists of a stratospheric carrier balloon that allows the deployment of dropsondes on demand. Parsons research is looking at the preconditioning of the tropical cyclone genesis environment that occurs from Africa Easterly Waves over the Atlantic showing that the waves produce favorable environment for genesis with deep moisture that extends to ~3 to 5 km. Parsons is also collaborating with Anna Agusti-Panareda at the ECMWF to determine how well these moist layers are replicated in the model initial conditions and forecast fields to assess model initial condition and forecast errors.

Parsons research activities also include significant time spent being the led Principal Investigator for two major international field experiments with accompanying numerical modeling efforts called THORPEX Pacific Asian Regional Campaign (T-PARC) and CONCORDIASI. The goals of T-PARC are to advance understanding and improve prediction of i) high impact weather over the western Pacific and east Asia with a focus tropical cyclones from genesis to extratropical transition (ET) or decay; ii) downstream high impact weather events over North America, the Arctic and Europe whose dynamical roots and forecast errors are over the western Pacific and east Asia. The tropical cyclone and ET phases of T-PARC will take place from August to early October 2008 with a winter phase planned for January to March 2009. The CONCORDIASI project will also take place from August to early October 2008. This program has multi-disciplinary goals, such as i) more accurate representation of the atmosphere over Antarctica through advancing satellite data assimilation for weather prediction and the climate record,  ii) advancing prediction of precipitation events near Antarctica and the impact of these events on lower latitude circulations; iii) more accurate prediction of ozone concentrations through Lagrangian measurements of ozone depletion and the microphysics of stratospheric NAT clouds.

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Climate change and regional air quality implications

Globally, secondary organic aerosol (SOA) from biogenic precursors surpasses those from anthropogenic sources. These organic particles impact climate directly by scattering and absorbing of radiation, and indirectly through the modification of clouds and precipitation. These processes exert a substantial influence back upon the earth system through links to the terrestrial carbon and water cycles (e.g., precipitation regulates plant growth and thus emissions of organic compounds). Understanding the feedbacks between the atmosphere and terrestrial environment is key to estimating the impact of climate change on regional air quality.

In 2007, ACD scientists collaborated with Jack Chen, Jeremey Avise, and Brian Lamb (Wash. State U.), Cliff Mass (U. Washington), Donald McKenzie and Susan Fergusen (US Forest Service) to investigate the impact of future climate and land cover on regional air quality in the Pacific Northwest and North Central U.S. The results indicate that U.S. regional air quality (e.g., ozone and particles) will degrade even if U.S. anthropogenic emissions remain the same. The changes are due to a combination of pollutant transport from other countries (primarily China, Mexico and Canada), changes in wildfire emissions, and changes in biogenic emissions. The increased pollution transport is due to predicted increases in emissions in these countries. Wildfire activity is predicted to increase due to a warming and drying climate. Biogenic VOC emissions are expected to increase in response to higher temperatures. Land use change (i.e. tree plantations, agriculture, and urbanization) scenarios result in dramatic increases in some regions and decreases in other areas.

Researchers from ACD, TIIMES, and ASP have teamed with Robert Griffin (U. New Hampshire) to study the impact of climate change on the formation of secondary organic aerosol from biogenic precursors. These studies are being conducted in the Biosphere-Atmosphere Interactions Chamber, a new facility located in the Atmospheric Chemistry Laboratory at NCAR. The two primary components of the facility are a biogenic emissions enclosure and an aerosol growth chamber. Experiments are initiated by continuously passing clean, dry air over a live branch in the biogenic emissions enclosure. This sample air is fed to the aerosol growth chamber, where it is mixed with clean air containing ozone at approximately ambient concentrations; the reaction between the biogenic VOCs and ozone can lead to new particle formation and growth. The most important accomplishment in 2007 was the expansion of the aerosol growth chamber to a volume of 10 m3. This allows for average residence times of ~8 hours at 20 lpm sampling flow rates, which will gives sufficient time for aerosol growth to occur to a size that is pertinent to the study of cloud formation processes. To complement these process-level investigations, ACD and TIIMES researchers have been performing continuous measurements of ultrafine particle size distribution and some trace gases like O3 and SO2 in a coniferous forest at the Manitou Experimental Forest near Woodland Park, CO. This research, which commenced in March 2007, is motivated by the need to characterize and understand interactions between biogeochemical and water cycles across scales and their response to climate and land-use change. Preliminary results indicate that new particle formation, such as the event shown in the figure, occurs regularly at this site. This "scoping study" is showing that there exist distinct periods where urban air is transported to the site and interacts with local biogenic emissions, as well as periods where the air masses are primarily biogenic in origin.

Future plans for 2008 using the Biosphere-Atmosphere Interactions chamber include investigating the role that nitrogen species play in BSOA formation (Jose Jimenez, U. Colorado) and the impact of environmental factors on biogenic SOA formation and cloud condensation nuclei (Athanasios Nenes, Georgia Tech). Measurements at Manitou Experimental Forest will continue through March 2008 in order to capture seasonal variations in aerosol size distributions. Future plans there may include expanding the measurements to include fluxes of aerosols, water vapor, nitrogen species, and organic compounds as well as characterizations of soil and plant biological activity.

This work was funded by NSF, DOE, NOAA and USEPA.

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Model physics

The Weather Research and Forecasting (WRF) Model is being used in an increasingly wider set of applications as computing power improves. WRF was developed as a community mesoscale model for numerical weather prediction, case study, and idealized simulations, and as a tool for related applications such as air quality research and forecasting. Some examples of newer applications that have resulted from improved computing resources are real-time cloud-resolving forecasting, including moving-nest hurricane forecasting, and nested regional climate modeling in the whole tropical belt (see other sections). With these applications come new priorities in physics development to enable better hurricane and regional climate modeling. These priorities fit with several of ESSL's priorities, including those of weather prediction and simulation across scales. Furthermore the aim of providing the university research community with a relevant up-to-date modeling system is met by continually updating the model to make use of the new capabilities in the current computing era, and improvements in model physics form one critical aspect of this development.

WRF already has a large set of physics options designed for its range of uses, from fast physics packages for operational uses, to more complex packages for scientific studies. The table shown summarizes the current WRF physics options available to the ARW dynamical core as of its last release (Version 2.2) in December 2006.Version 2.2 also included nudging techniques for dynamical analysis applications. These were developed by scientists at MMM, RAL, and Penn State University.

Ongoing physics collaborations exist with NCEP, NASA Goddard, the EPA, NRL, NOAA/ESRL, the Pacific Northwest National Laboratory, Colorado State University, UCLA, the University of South Florida, University of New Mexico, and YonSei University (Seoul, Korea), as well as across the NCAR Divisions and Laboratories. These are all likely to reach fruition with more options for the WRF user community in the next few years including in the planned Version 3.0 release in March 2008. Support for this work includes NSF, KMA, AFWA, ARO, and the FAA.

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Chemistry-climate coupling: Past and future

Methane clathrate is an ice-like structure of water and methane that form under conditions of low temperatures, high pressure and sufficient methane concentrations; at present times, methane clathrates are located along many outer continental margins of the world. They represent a very large methane reservoir and their destabilization is hypothesized to be the main reason for the isotopic carbon excursion observed in the benthic foraminifera record at the Paleocene-Eocene Thermal Maximum. Outside the stable zone, e.g., for warmer temperatures or lower pressures, the clathrate destabilizes and the methane can be released into the ocean water. Under a climate change scenario, one mechanism for the destabilization is a warming of the deep ocean, in response to external forcing such as the release of greenhouse gases (and CO2 in particular) in the atmosphere. A wide variety of coupled climate models from around the world have participated in the recent IPCC (Intergovernmental Panel on Climate Change) AR-4 simulations; this collection can be seen as representing the state-of-the-science climate models. ACD scientists used the 1%-CO2 increase (over present-day conditions) per year simulations to estimate if, by the time a doubling of CO2 (with 1%/year increase, doubling occurs approximately after 70 years) is simulated, significant areas of the global ocean have become unstable with respect to methane clathrate.

The analysis (see Figure) shows that slightly less than half of the models indicate that a region between Canada and Greenland and another South of New Zealand will be potentially unstable by the time atmospheric CO2 doubles. In addition, coastal regions in the vicinity of Iceland (but also to the Northeast), Northern Japan, Kamchatka and Northern Russia exhibit a model agreement between 30-40%. Furthermore, coastal regions around Florida (and the Gulf of Mexico in general), Scotland/Ireland, Japan and Kamchatka are shown by more than 20% of the models to be unstable. This work is submitted for publication in Geophysical Research Letters. Follow on studies in FY2008 will expand on this study by focusing on the global distribution of methane clathrates. This work is funded by DOE and NSF/NCAR.

The last decades of the 20th century have seen profound shifts in atmospheric composition, from the surface to the upper atmosphere. Among these changes, the decrease of ozone in the Polar Regions has been one of the most spectacular; it is now well-established that the disappearance of ozone is due to heterogeneous chemistry on polar stratospheric clouds and requires the presence of chlorine- and bromine-containing compounds in sufficient quantities. Most of those compounds, mainly the chlorofluorocarbons (CFCs) and their replacements, are man-made and have seen a dramatic increase in the release into the atmosphere, especially since the 1970s. The Montreal Protocol in 1989 has led to the regulation and subsequent decrease in emissions and concentrations of some of those compounds.

In order to simulate the evolution of the atmospheric composition over the last 35 years, we use the Community Atmosphere Model version 3 (CAM3) modified to include interactive chemistry, including aerosols. The chemical mechanism used in this study is formulated to provide an accurate representation of both tropospheric and stratospheric chemistry. The model is forced at the surface by the observed concentration of long-lived greenhouse gases and halocarbons. As a display of chemistry-climate coupling, we show (Figure) the vertical distribution of the temperature linear trend for 1979-1998, averaged between 70oS and 70oN. We can see that the model is quite able to reproduce the observed (from radiosondes and satellite data) linear trend; our results are actually remarkably similar to equivalent simulations by WACCM, even in the details such as the larger (more negative) than observed trend between 5 and 10 hPa. This indicates that this version of CAM-chem, even with its low lid at 4hPa, can adequately representing stratospheric chemistry-climate couplings; this work is under review for publication in the Journal of Geophysical Research. We are planning to expand in FY2008 this analysis to simulations relevant to future conditions. This work is funded by DOE and NSF/NCAR.

Other changes in atmospheric composition that impact climate are a result of biomass burning. For example, the dense tropical rainforests of Sumatra, Kalimantan, and Malaysia only burn in years with below average rainfall when significant drying occurs. The fires normally originate in agricultural activities and often spread out of control. In Sumatra and Kalimantan, there is an added concern that significant forest clearing and drainage threatens the stability of peat deposits - thick layers of extremely flammable partially decayed vegetation matter that build up at the forest floor. This makes them particularly susceptible to fire during periods of drought and a smoldering burn that releases large amounts of carbon into the atmosphere and often continues until the onset of the monsoon rains at the end of the year. Drought periods over Indonesia are often brought on by the shift in the atmospheric circulation over the topical Pacific associated with El Nino conditions. Significant El Nino conditions closely match the occurrence of high CO pollutant loadings as measured by the MOPITT satellite instrument in 2002, 2004, and 2006. Even though the 2006 El Nino is considered mild, it led to significant pollution over Indonesia and neighboring countries. In addition to CO, the fires also produce significant amounts of the greenhouse gas carbon dioxide (CO2). This suggests that not only is there a direct link between climate variability and the deterioration of regional air quality, but a potential for further climate impact.

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Prediction across scales

The Prediction Across Scales initiative is a collaborative effort between CGD and MMM to coordinate research and system development activities across weather and climate scales. Recent major advances in petascale computing coupled with rapid advances in scientific understanding are enabling advances in simulating a wide range of physical and dynamical phenomena with associated physical, biological and chemical feedbacks that collectively cross the traditional weather-climate divide. Such simulations and predictions are essential to a society that is becoming much more sophisticated in its requirements for weather, air quality and climate predictions and that is able to make useful economic and social use of such improvements. Moreover, fundamental barriers to advancing such prediction on time scales from days to years, as well as long-standing systematic errors in weather and climate models, are partly attributable to our limited understanding and capability to simulate the complex, multiscale interactions intrinsic to atmospheric and oceanic fluid motions. The scientific and societal questions and issues to be addressed are many. A limited sample includes better understanding of:

• The water cycle and its predictability, particularly the limitations of available water and the impacts on food production;
• The limits of weather, air quality and climate predictability including the impacts of mega-cities and the stressed Earth’s capacity to sustain quality of life;
• The interaction of hydrological, chemical and biogeochemical cycles and their feedback on weather/climate processes;
• The mechanisms by which solar variations influence the chemistry and dynamics of the upper atmosphere, and how these effects are manifested in the lower atmosphere;
• The interactions between climate change, ENSO and other natural modes of variability, including changes to the behavior of phenomena like hurricanes;
• The mechanisms of abrupt climate change and potential tipping points.

Our plans for 2007 were to complete a series of simulations with the Advanced Research WRF model reconfigured as a Nested Regional Climate Model (NRCM), and to commence the analysis of the outcomes.

We have completed a 10-year simulation of the tropical circulation with the NRCM configured in a channel mode using NCEP/NCAR reanalysis data on the poleward boundaries and specified surface conditions. A set of comparative simulations were also made using the CAM at T170 resolution and configured in a similar channel mode with relaxation towards reanalysis in the polar regions. These simulations were run on the Blue Vista and the NASA Columbia computers. The base simulation was made at 36 km, with one year simulation using a 2-way nest over the Maritime Continent at 4 km resolution. A set of high-resolution simulations were made off the west coast of North and South America for use in determining oceanic simulation issues there. And a full simulation of the 2005 hurricane season was accomplished with a 12 km nest over the North Atlantic. A subset of the data has been analyzed for tropical modes, hurricanes and the East Asian monsoon. This has shown a range of successes, with good simulation of tropical cyclones and tropical modes, but some failures with the East-Asian monsoon. Several university groups have joined the program to conduct research on the data.

Our immediate plans are:

• To diagnose the problems that have arisen and how they can be removed in future simulations;
• To continue the analysis of the previous simulations in collaboration with our university colleagues;
• To nest the NRCM inside CAM and advance development of a full nested configuration including atmospheric and oceanic components;
• To conduct high-resolution simulations with both the CCSM and WRF Global models

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