The Atmospheric Radiation Measurement (ARM) Climate Research Facility (www.arm.gov) provides atmospheric observations from diverse climatic regimes around the world. Because it is a U.S. Department of Energy (DOE) user facility, ARM data are freely available to anyone through the ARM Data Archive. With 20 years of operations, the facility recently added two mobile facilities and an aerial facility to its network of fixed-location sites. Research using ARM data has led to advances in areas ranging from radiative transfer to cloud microphysics. The American Recovery and Reinvestment Act of 2009 allowed ARM to enhance its observational capabilities with a broad array of new instruments at its fixed and mobile sites and the aerial facility. Instruments include scanning radars; water vapor, cloud/aerosol extinction, and Doppler lidars; aerosol instruments for measuring optical, physical, and chemical properties; and aircraft probes for measuring cloud and aerosol properties. Taking full advantage of these instruments will involve the development of complex data products. This work is underway but will benefit from engagement with the broader scientific community. This article describes the current status of the ARM research capabilities with an emphasis on developments over the past eight years since ARM was designated a DOE scientific user facility, reviews some of scientific advances made using the ARM Facility over the past two decades, and describes the new measurement capabilities and adaptations of the ARM facility to make effective use of these capabilities.
DOE's Atmospheric Radiation Measurement program, which has been providing data to advance climate research for 20 years, recently added instruments to expand its capabilities for the study of clouds, aerosol, and precipitation.
The Department of Energy (DOE) created the Atmospheric Radiation Measurement (ARM) Program over 20 years ago in response to a need for observations to improve the understanding of the interaction between atmospheric radiation and clouds and their representation in global climate models (Stokes and Schwartz 1994, hereafter SS94). ARM was originally designed to include heavily instrumented observation sites in a diverse set of climatic regimes and a science team for the application of these data to climate research problems. The first ARM site began operation in 1992 in the U.S. Southern Great Plains (SGP) region (SS94). Over the next 10 years, additional sites were installed in the tropical western Pacific (TWP) and the North Slope of Alaska (NSA), with three sites in the TWP at Manus (Mather et al. 1998), Nauru, and Darwin, Australia, and two sites in the NSA at Barrow (Stamnes et al. 1999) and Atqusuk (Fig. 1). Throughout this development period, the measurement capabilities at these sites evolved to take advantage of new instruments and reflect the needs of the research community. The core set of measurements found at all these sites (with the exception of Atqusuk) is given in Table 1 and remains very close to the original design (SS94).
As originally envisioned, the ARM sites provide a broad array of measurements covering cloud properties, aerosol properties, surface properties, atmospheric thermodynamic properties, and radiative fluxes. These measurements are—with the exception of balloon sounding profiles of the atmospheric state—provided continuously with high temporal resolution (typically 1 min), although the resolution of some of the remote sensing instruments is as fine as a few seconds to capture variability in cloud properties. These continuous high-resolution data provide the means to study not only the characteristics of the atmosphere but also their detailed temporal signatures (e.g., Zhang et al. 2008).
Many papers have been written about components of ARM and analyses using ARM data. A compilation of these articles is referenced in the ARM publications database available online (at www.arm.gov/publications/db). Ackerman and Stokes (2003) provided a snapshot of the ARM measurement capabilities shortly following the installation of the tropical Darwin site in 2002, and the 2004 ARM Science Plan (Ackerman et al. 2004) provided an assessment of accomplishments as the program was on the verge of a number of changes. However, since Stokes and Schwartz described the early vision for ARM, there has not been an update of its overall capabilities. Meanwhile, there have been several major changes to ARM over the past 8 years: designation as a scientific user facility, the addition of two mobile facilities and an aerial facility, the programmatic separation of the observation facility from the science team, and, most recently, a significant expansion in the core array of instrumentation. This paper first provides a description of the ARM Facility, then overviews some of the science themes that have emerged from work with ARM data, and finally describes recent enhancements to the ARM Facility that expand its measurement capabilities.
THE ARM CLIMATE RESEARCH FACILITY.
In 2004, ARM was designated a DOE Office of Science user facility. As a user facility, ARM is formally chartered to serve the global scientific community. ARM data have always been fully open to everyone through its archive (www.archive.arm.gov); however, key changes resulted from the user facility designation. The first notable change was the formal separation of the facility infrastructure and science components of ARM into separate programs. More recently (October 2009), the science component of ARM merged with the former DOE Atmospheric Science Program (ASP) to become the Atmospheric System Research (ASR) program (U.S. Department of Energy 2010). Today, ARM refers solely to the facility and the associated infrastructure including the observation sites, the data archive, and all the functions that process and manage the data, although there continues to be a close link between the ARM Facility and the science user community and particularly with the DOE ASR program.
In keeping with its distributed nature, the ARM Facility is managed and operated by nine DOE National Laboratories: Argonne, Berkeley, Brookhaven, Livermore, Los Alamos, Oak Ridge, National Renewable Energy, Pacific Northwest, and Sandia. These laboratories are responsible for functions including site operations, data processing and delivery, instrument maintenance and engineering, software development, and outreach. The organization of the ARM facility is described at the ARM website (www.arm.gov) but a few components that have a particularly direct impact on facility users and that were not captured in SS94 are described here.
ARM mobile facilities.
At approximately the same time that ARM became a science user facility, it developed and deployed its first ARM Mobile Facility (AMF; Miller and Slingo 2007; Fig. 2) at Point Reyes National Sea Shore in 2005. A second AMF, completed in 2010, completed its inaugural deployment in Steamboat Springs, Colorado. The AMFs include a similar suite of instruments as the fixed sites and are deployed for periods of approximately 12 months (longer and shorter periods are considered on a case-by-case basis). The second AMF was additionally designed with the intent of being deployable on a ship and is currently deployed on a commercial cargo vessel through September 2013. The AMFs provide a comprehensive array of measurements in diverse, scientifically important, but dat a-poor areas to augment the long- term fixed sites. A complete set of AMF deployments to date, including scheduled upcoming campaigns, is given in Table 2.
ARM aerial facility.
Aerial measurements have always been an important part of ARM. They have been used to augment ground-based ARM measurements for improving or testing remote sensing retrievals, evaluating processes, or measuring vertical structure. Between 2000 and 2007 routine flights were carried out over the ARM SGP site to measure aerosol optical properties (Andrews et al. 2011). Apart from these routine aerosol flights, aerial campaigns prior to 2007 were typically carried out through collaborations with other agencies (e.g., Toon and Miake-Lye 1998; Ferrare et al. 2006a) or through the DOE Unmanned Aerial Vehicle (UAV) Program (Stephens et al. 2000; Michalsky et al. 2002). In 2007, the ARM Aerial Facility (AAF) was added as a formal component of the ARM Facility (www.arm.gov/sites/aaf). The aerial component of ARM continues to support external flight operations as well as routine flights, focusing on CO2 profiles, but it now also maintains a more comprehensive internal aerial measurement capability through the DOE/Battelle G-1 aircraft. The G-1 has long supported the DOE (Molina et al. 2010; Kleinman et al. 2008) but now is primarily supported by the ARM Facility.
Field campaigns and disposition of ARM resources for intensive operations.
The ARM Mobile Facilities and the ARM Aerial Facility each provide the means to extend ARM observations beyond the fixed site's measurements. In addition, ARM supports a wide variety of field campaigns at its long-term sites, in conjunction with AMF deployments, and occasionally at off-site locations.
Major field campaigns conducted at long-term ARM sites over the past seven years have focused primarily on clouds and cloud–aerosol interactions. These have included the Mixed-Phase Arctic Cloud Experiment (M-PACE; Verlinde et al. 2007) and Indirect and Semi-Direct Arctic Cloud (ISDAC; McFarquhar et al. 2011) campaigns at the Barrow site; the Tropical Warm Pool International Cloud Experiment (TWP-ICE; May et al. 2008) at the Darwin site; and the Cloud and Land Surface Interaction Campaign (CLASIC), the Routine AAF Clouds of Low Water Depth (CLOWD) Optical Radiative Observations (RACORO; Vogelmann et al. 2012) campaign, the Small Particles in Cirrus (SPARTICUS) campaign, and the Midlatitude Continental Convective Clouds Experiment (MC3E) at the SGP site. In these experiments, cloud properties and processes were examined for a variety of cloud types.
ARM field campaigns are usually colocated with ARM sites; however, several campaigns have been carried out at alternate locations to study specific processes. These include the Radiative Heating in Underexplored Bands Campaign II (RHUBC-II; Turner and Mlawer 2010) in Chile, and the Carbonaceous Aerosols and Radiative Effects Study (CARES; Zaveri et al. 2012) in California.
The selection of AMF and AAF deployments, or the dedication of resources for field campaigns, is carried out through a competitive proposal process. This process is open to the scientific community and begins each year with a call for brief preproposal ideas. Authors of ideas that are deemed feasible and relevant to programmatic goals are invited to submit full proposals. These proposals are vetted for cost and feasibility by ARM management and for scientific merit by an independent science board. Selections are made by DOE management based on these reviews.
ARM data infrastructure.
In addition to the measurement sites and associated instruments, the ARM Facility includes an array of functions to process and deliver data to the science user community (Macduff and Eagan 2004). These functions begin with the data systems at the measurement sites. These systems collect data from the individual instruments, catalog and perform status on the raw data, process the data for local use (including evaluation by on-site staff and use during field campaigns and other occasions bringing scientists on site), and send the data back to the Data Management Facility where the data are processed to a standard NetCDF format (www.unidata.ucar.edu/software/netcdf/; Brown et al. 1993) and sent to the ARM Data Archive at Oak Ridge National Laboratory. Data are made available from the data archive to the general user community, typically within a few days of collection at the sites, through user interfaces available at www.arm.gov/data.
In parallel with delivery to the ARM Data Archive, processed data at the Data Management Facility are immediately made available to the Data Quality Office, based at the University of Oklahoma, to technical leads for individual instruments (referred to as instrument mentors), and to site operations staff (Peppler et al. 2008). Guest instruments are often deployed at ARM sites as part of field campaigns or focused instrument evaluation activities. Data from these nonstandard deployments are managed by the External Data Center at Brookhaven National Laboratory.
Standard data products from ARM instruments include parameters provided through operational instrument software and simple quality checks against an expected maximum/ minimum range. When more advanced processing is required for an instrument or set of instruments, a value-added product (VAP) is developed.
VAPs are most often based on algorithms developed in the research community and then implemented for operational use within the ARM data infrastructure to serve the larger research community. There are various types of VAPs including those that derive higher-order parameters from one or more instruments, those that refine estimate of parameters and add to basic data quality checks, and those that consolidate parameters to facilitate analysis. Examples of derived higher-order parameters include retrievals of aerosol optical depth (Harrison and Michalsky 1994), cloud boundaries (Clothiaux et al. 2000), and cloud optical depths (Comstock and Sassen 2001). Examples of refined parameters include a product that provides quality assessment and control for radiation measurements (QCRAD; Long and Shi 2008) and the physically based column water retrieval from microwave radiometers (Turner et al. 2007). Finally, consolidated products include the family of ARM Best Estimate products (formerly known as the Climate Modeling Best Estimate; Xie et al. 2010), which is designed for climate model evaluation, and the Radiatively Important Parameter Best Estimate (McFarlane et al. 2011) that provides the inputs necessary to calculate radiative flux profiles.
The path for development of ARM VAPs is a multistep process requiring iterative interactions between ARM and the research community (Jensen et al. 2011). The process begins with the proposal of an algorithm for implementation. Proposals must be put into a prioritized queue pending available resources for development. Priorities are established through interactions with the science user community and particularly with DOE ASR scientists who interact with the ARM infrastructure on a regular basis. However, input from the broader user community is also encouraged and solicited through workshops, conferences, and other forms of input.
SCIENTIFIC ACCOMPLISHMENTS USING ARM DATA.
The ARM program was established to improve understanding the interaction of atmospheric radiation with clouds and the representation of these interactions in climate models (SS94). Since the beginning of ARM there has been a close connection between the collection of data and research on these and related topics. This relationship is now manifested through a close relationship between ARM and the ASR research program as well as with outreach to the broader science community. Following are a few illustrations of work done with ARM data intended to capture broad research themes from the past two decades.
During the early years of the program there was an emphasis on understanding the clear-sky radiation problem that required improvement in radiation measurement methods (e.g., Michalsky et al. 1999e.g., Michalsky et al. 2007) and the measurement of water vapor (Revercomb et al. 2003; Turner et al. 2003) and aerosol optical properties (Michalsky et al. 2010; Kassianov et al. 2007; Andrews et al. 2011). In addition to improved measurements of these atmospheric components, this work was also coupled with radiation modeling and led to the development of more accurate and faster radiation models. The culmination of that work has been the development of the Rapid Radiation Transfer Model (RRTM; Mlawer et al. 1997; Clough et al. 2005) that has now been integrated into several global models including the Community Earth System Model (CESM; Neale et al. 2010) and the European Centre for Medium-Range Weather Forecasts (ECMWF) model (Morcrette et al. 2001).
There has also been a lot of work done on understanding cloud properties using ARM data through work done by members of the ASR science team and the larger research community. This work was significantly enabled by the deployment of the vertically pointing Millimeter Cloud Radar (MMCR) beginning in 1996 (Moran et al. 1998) but also has made use of observations from lidars, radiometers, and airborne cloud probes. The cloud radar alone and in combination with other instruments has led to greater understanding of the distribution of clouds (Mace and Benson 2008; Mather and McFarlane 2009; Kollias et al. 2009) and many techniques have been used to study the variety of cloud types observed at the diverse ARM sites. Cloud microphysics work has included studies of low liquid water stratus clouds (e.g., Dong and Mace 2003; McComiskey et al. 2009), cirrus clouds (e.g., McFarquhar et al. 2007; Deng and Mace 2008; Protat et al. 2010), and mixed-phase clouds (e.g., de Boer et al. 2009; Luke et al. 2010).
While the improvement in understanding of radiation and clouds is critical, the primary goal for the ARM program has been to transfer this improved understanding to the improvement of climate models. The transfer of information from raw measurements to improvements in atmospheric models has been aided by the model-oriented field campaigns and by several value-added products geared to model assessment.
An important attribute of many ARM field campaigns is the operation of an expanded radiosonde array around the central observation locale. From these sounding array data, value-added products are developed that provide constraints for running model simulations over the ARM site (Zhang and Lin 1997). When a model is constrained in this way, simulations of clouds and radiation fields can be directly compared to measurements within the experiment domain (Randall et al. 2003). Field campaigns that have incorporated sounding arrays include MC3E, TWP-ICE (e.g., Fridlind et al. 2011), and M-PACE (Klein et al. 2009). These field campaigns tend to draw a lot of attention from the modeling community because of this mechanism to directly compare simulations with local observations. This type of model to observation comparison has led to model improvements such as the Modal Aerosol Model (Liu et al. 2011) that predicts aerosol distributions as well as liquid and ice nucleation and has been incorporated in the most recent update to the Community Atmosphere Model (CAM5; Neale et al. 2010). A similar mechanism that has been used to evaluate climate models with ARM data that does not require a field campaign is the Cloud Associated Parameterization Testbed (CAPT; Phillips et al. 2004). In the CAPT framework, a climate model is run like a numerical weather prediction model in terms of global forcing and then the model is evaluated over an ARM site (e.g., Zhao et al. 2012).
An important set of ARM data products for model evaluation is the family of ARM Best Estimate products (Xie et al. 2010; Fig. 3). These products merge data from variety of ARM instruments, average parameters to a time resolution of 1 h, and include additional quality checking. These data have proved to be very useful to the climate modeling community because of the convenience they represent for accessing a lot of information directly relevant to testing models. As an illustration, the ARM Best Estimate products have been included in the test data suite for the NCAR Community Earth System Model.
As briefly illustrated by these examples, there has been much work done over the past two decades with ARM data spanning a range of disciplines. In the mid-2000s, however, there were discussions going on with the ARM science community about what additional measurements were needed, for example, to better determine cloud microphysical properties and three-dimensional cloud distributions. The active remote sensors to that time were zenith-pointing with a narrow field of view, restricting the measurement of cloud fields to a narrow column directly over the ARM sites and there was interest in applying radar capabilities such as dual polarization to improve measurements of cloud properties. With the merging of the ARM science program with the aerosol-oriented ASP program, there was a need to expand the measurement capabilities for aerosol properties. And there was also a growing interest in using ARM data to study not only a static view of the atmosphere, but the processes associated with cloud evolution (e.g., Zhang and Klein 2010). As discussed below, the combination of two workshops and subsequent funding through American Recovery and Reinvestment Act has enabled ARM to significantly expand in recent years to address this expanded set of scientific goals.
In 2007 and again in 2008, DOE sponsored workshops to solicit feedback on the ARM Facility. Each of these workshops included representation from both ARM and ASR and the larger climate research community. The goals of the first workshop were fourfold: to identify high-priority locales for future observations, to identify important characteristics for a new mobile facility, to identify aerial measurement priorities, and to identify needs for data processing and handling (U.S. Department of Energy 2007). The mobile facility is now in operation, there have been numerous improvements to the aerial facility and the computing infrastructure, and, as discussed below, ARM is now developing two new long-term sites.
The goals of the second workshop were to consider science applications for the ARM Facility and whether the current array of sites was appropriate and whether there were gaps in the measurement capabilities (U.S. Department of Energy 2008).
The major findings from the second workshop were suggestions for additional measurements that would benefit the scientific goals of ARM. These followed the themes mentioned at the end of the previous section and included expanded remote sensing capabilities with an emphasis on advanced radar systems, improved boundary layer measurements, and sensors for probing cloud–aerosol interactions. At the time, there was not an expectation that ARM would be able to pursue more than a small subset of these ideas in the short term. However, the American Recovery and Reinvestment Act of 2009 made it possible to significantly bolster the measurement capabilities of the ARM sites in a very short time.
NEW MEASUREMENT CAPABILITIES.
In 2009, the ARM program was awarded a facility upgrade and expansion project through the American Recovery and Reinvestment Act (hereafter simply Recovery Act). The Recovery Act project plan included upgrades to facility infrastructure and investments in new and existing instrumentation. The instrument selections were based on input from the 2007 and 2008 ARM Facility workshops and on priorities expressed at user meetings over the previous few years. Over 140 instruments were purchased. A summary list of these instruments is provided in Table 3 and a complete list is available at www.arm.gov/about/recovery-act. The instruments can be broken into several major categories: radars, lidars, radiometers, surface flux systems, and instruments that measure a variety of aerosol properties. The list also includes aircraft probes for measuring cloud properties, aerosol optical and chemical properties, and atmospheric state parameters. In addition to the existing sites, many of these instruments will be deployed at two new ARM sites.
One of the key elements of the ARM instrument suite has been the vertically pointing millimeter cloud radar since it was first deployed at the SGP site in 1996 (Moran et al. 1998; Kollias et al. 2007). The continuously operating cloud radars provide detailed profiles of vertical cloud structure with high temporal and vertical resolution. The largest component of the Recovery Act investment expanded the ARM array of radars to include additional transmission frequencies, dual polarization, and scanning capabilities. The compliment of radars includes two types of instruments intended primarily for cloud detection, two for precipitation, and two radar wind profilers.
The cloud-detecting millimeter-wavelength radars include six dual-frequency scanning radars (with frequency combinations of 35/94 GHz or 35/10 GHz; Figs. 4 and 5) and upgrades to the original 35-GHz zenith-pointing cloud radars. The precipitation-detecting, centimeter-wavelength radars include a network of three 10-GHz radars at the SGP site modeled after the CASA network (McLaughlin et al. 2009), a 10-GHz radar at Barrow configured to sample area precipitation, and 5-GHz radars at SGP and Manus to sample area precipitation (Keenan et al. 1998). Finally, there are two radar wind profilers, one operating at 915 MHz and the other at 1,290 MHz.
Collectively, this array of radars distributed across the ARM Facility is intended to provide enhanced information for deriving microphysical properties of clouds and precipitation, and to take cloud sampling from one spatial dimension to three. Microphysical retrievals will be enhanced by dual frequency sampling (Sekelsky et al. 1999), dual polarization, and scanning (Matrosov et al. 2005a,b). Making the best use of the millimeter-wavelength scanning has been an iterative process and is likely to continue to evolve. It is not feasible to sample clouds in the full hemisphere because of both the radar's narrow beamwidth (0.19°–0.31°) and limitations to scan rate driven by the low signal reflected from clouds. The current scan strategy for all the radars is described in Bharadwaj et al. (2012). This array of radars is expected to provide a remarkable dataset because of both this combination of physical capabilities and the merging of cloud and precipitation observations.
Data product development for these new radars is underway. The top priorities for the scanning millimeter-wavelength radars are to provide radial and gridded Doppler moments and a gridded cloud mask. The latter will provide a three-dimensional analog to the Active Remotely-Sensed Cloud Locations (ARSCL) cloud mask (Clothiaux et al. 2000) that has been applied to zenith-pointing radars for many years. The top priority for the centimeter-wavelength radars is to implement algorithms for the Quantitative Precipitation Estimation (QPE; e.g., Doviak and Zrnic 1993; Bringi and Chandrasekar 2001; Matrosov 2010). In addition to QPE, much work has been done with centimeter-wavelength radars to derive various properties of precipitating cloud systems including hydrometeor types (Liu and Chandrasekar 2000; Keenan 2003), latent heating profiles (Tao et al. 2006), and dynamic structure (Wurman et al. 1994; Protat and Zawadzki 1999). It is expected that all of these techniques will ultimately be applied to the ARM data; however, the relative priorities among these parameters will be established through dialog with the research community.
Prior to the Recovery Act upgrade, the core set of ARM lidars included ceilometers with a maximum range of 7 km and micropulse lidars (Spinhirne 1993; Campbell et al. 2002) that gave an extended range (through the tropical tropopause) and higher sensitivity for the detection of aerosol and thin cirrus (Comstock et al. 2002). In addition, a Raman lidar has operated at the SGP since 1998 (Goldsmith et al. 1998). The Raman lidar provides profiles of water vapor and aerosol extinction (Turner et al. 2002; Ferrare et al. 2006b; Schmid et al. 2009) and received a significant upgrade in 2004 (Turner and Goldsmith 2005).
The Recovery Act expansion included replacement of the aging Vaisala CT25K ceilometers with next-generation CL31 ceilometers, the deployment of a second Raman lidar (essentially identical to the SGP unit) to Darwin, two high spectral resolution lidars for the retrieval of aerosol and cloud optical properties (Eloranta and Razenkov 2006, and references therein), and three Doppler lidars. The Doppler lidars are capable of scanning but are currently deployed primarily in a vertically pointing mode to emphasize measurements of vertical velocity below cloud base (Fig. 6; Pearson et al. 2009).
The ARM Facility has always included a variety of broadband and spectrally resolved radiometers in accordance with the research emphasis on the effects of clouds and aerosols on the surface radiation budget. The Recovery Act enabled the procurement of two types of radiometers: replacements of the Atmospheric Emitted Radiance Interferometers (AERIs; Knuteson et al. 2004a,b) at all sites, and the development of a pair of new shortwave spectrometers, the Solar Array Spectroradiometer—zenith-viewing (SAS-Ze) and -hemisphere viewing (SAS-He).
The AERIs measure zenith radiance over the range 500 to 3,000 cm−1 except in the arctic where an extended range detector pushes the low wavenumber limit to 400 cm−1. The spectral radiance measured by the AERI can be used for various applications including improvement of radiation parameterizations (Turner et al. 2004), derivation of water vapor profiles (Feltz et al. 2003), the detection and quantification of mixed phase clouds (Turner 2005), and improved liquid water path retrievals when the liquid water path is small (Turner et al. 2007). The SAS-Ze measures zenith radiance over the range 300 to 1,700 nm with a resolution of 2.4 to 3.5 nm (full width at half maximum) while the SAS-He uses a shadowband to measure hemispheric, direct-beam, and diffuse solar irradiance with the same spectral characteristics. The SAS-Ze and SAS-He are new instruments and are expected to provide constraints for radiative transfer models as well as retrievals of gaseous constituents, aerosol properties, and cloud optical properties (e.g., Bergstrom et al. 2007).
Prior to the Recovery Act project, three ARM sites—SGP, Barrow (also part of the NOAA Baseline Observatory), and the first mobile facility—included integrated aerosol observing systems. These aerosol systems included a variety of instruments that provide measurements of aerosol number concentration, aerosol scattering and absorption, cloud condensation number concentration, and ozone concentration (Sheridan et al. 2001). The Recovery Act provided the opportunity to add two additional aerosol observing systems (Darwin and the second mobile facility) and to develop a more comprehensive suite of instruments, the Mobile Aerosol Observing System (MAOS), so named because it is intended to be deployed as needed at any of the mobile or fixed sites or on its own. The MAOS includes the capabilities of the Aerosol Observing System with additional instrumentation for measuring particle size distributions and chemical composition.
Two aerosol instruments receiving early attention are the Single Particle Soot Photometer (SP2; Stephens et al. 2003; Schwarz et al. 2006) and the Aerosol Chemical Speciation Monitor (ACSM; Ng et al. 2011). The SP2 uses laser ablation photometry to determine information about aerosol particles including size, amount of absorbing material, and layered structure (Fig. 7). This combination of information provides insights into the chemical processing of a population of aerosol particles. A data product is under development to extract this information from raw photometric time series (Sedlacek et al. 2012).
High-resolution Aerosol Mass Spectrometers (AMSs) provide detailed information about the size, composition, and oxidative state of nonrefractory aerosol populations (Canagartna et al. 2007). The ACSM is a comparatively low-resolution instrument but with the significant advantage that it is designed to operate continuously with relatively little oversight. The ACSM cannot provide such specific information about size-resolved composition, but work is underway to provide components of organic aerosol from ACSM measurements using positive matrix factorization that will provide a long-term time series of aerosol class distributions.
Airborne probes for measuring cloud, aerosol, and atmospheric state parameters.
ARM frequently carries out field campaigns that utilize airborne measurements. Until recently, the aircraft component of these campaigns was deployed primarily through collaborative partnerships (Ferrare et al. 2006a; Verlinde et al. 2007; May et al. 2008). While ARM will continue to work with other programs to deploy aircraft, through the Recovery Act the facility has also developed a flexible in-house capability. The diverse nature of these campaigns requires a variety of instrumentation and DOE-sponsored G1 aircraft can now be deployed with either cloud or aerosol probes. Cloud probes include sensors for particle size and shape as well as total water while aerosol measurement capabilities are very similar to those found in the ground-based MAOS (Tomlinson et al. 2011).
New long-term sites.
In early 2012, ARM was directed to develop two new sites: a fixed site in the Azores and an extended-term mobile site at Oliktok, Alaska. Each of these sites will have a comparable set of measurements as are found at other ARM fixed sites. The Azores site builds on the 2009–10 AMF deployment on Graciosa Island and will again focus on the life cycle and characteristics of marine stratocumulus clouds. The Oliktok site also represents a return to a previous campaign locale; Oliktok was one of several auxiliary sites used during the 2004 M-PACE campaign (Verlinde et al. 2007). The Federal Aviation Administration (FAA) has granted DOE authorization for a 4-mile-radius Restricted Airspace zone centered over Oliktok Point, and that airspace has been used by DOE for operations of tethered balloons since 2004. DOE is currently in discussion with FAA regarding extending this region for the operation of moored balloons, dropsondes, and Unmanned Aerial Vehicles. These technologies would provide the means to obtain measurements of atmospheric quantities over the sea ice in conjunction with a full set of ARM measurements on the shore. The Azores and Oliktok sites are expected to begin operations in 2013.
ADAPTING THE ARM FACILITY TO THE NEW MEASUREMENT SYSTEMS.
The Recovery Act instruments and the anticipated new sites represent a significant expansion in measurement capabilities. The combination of radars and lidars will provide improved microphysical measurements while also providing information about atmospheric motion and cloud evolution. Aerosol measurements from the MAOS and the aerial facility will provide the means to study aerosol evolution and better study aerosol–cloud interactions. Scanning precipitation radars will complete the view of cloud evolution from nucleation to precipitation and cloud decay. This integrated information including spatial information about clouds and precipitation will be valuable for process studies and for evaluating processes in cloud-resolving models. However, these facility additions also present operational challenges with increases in the number of instruments, the complexity of instruments, data volume, data flow rate, and the complexity of new multisensor value-added products. Much has already been done to address these challenges but more work remains and strategies to effectively manage this expanded measurement suite must be developed in close concert with the scientific community that will be making use of these new capabilities. Ongoing efforts include staffing, developing an integrated radar operations strategy, developing tools to more clearly communicate data quality information, and development of a community workspace for accessing, working with, and sharing results using ARM data.
The first steps taken to manage the expanded instrument suites were taken before any of the instruments had been purchased. Staff resources were brought onboard to define the specifications of new instruments and oversee their implementation. This effort was targeted at the areas of largest growth: radars, lidars, and aerosol instruments. ARM continues to increase investment in these areas as we evaluate operational performance.
The most significant need lies with the greatly expanded radar network. Prior to the Recovery Act, ARM operated six vertically pointing radars and had just recently implemented a single scanning radar. With the Recovery Act, ARM now has in the field six vertically pointing radars and 19 scanning radars. To support this complex measurement network, ARM is implementing a multifaceted operational strategy (U.S. Department of Energy 2012; Voyles 2012). The operations plan includes a dedicated core group of radar engineers who work closely with on-site operations staff, visiting technicians, the data quality office, and the radar vendors. The plan also explicitly identifies a radar science group that is formed from the ARM science user community. This group represents the perspective of the user community to provide feedback to the radar operations group. This radar organizational structure is new and is expected to be effective at optimizing radar operations, data quality, and data product delivery. This includes the broad range of issues related to the radar network including day-to-day operations and maintenance, calibration, and data quality assessment and control. It is also expected to serve as an example for other instrument groups.
Data quality assessment for the radars and most of the new instruments will be completed in unison with the ARM Data Quality Office. The Data Quality Office was established in 2000 to provide consistent data reviews, provide feedback to operations staff, and communicate data quality to the user community in conjunction with instrument mentors and other operations staff (Peppler et al. 2008). One of the most important tools for communicating data quality to the user community is through data quality reports. These reports identify suspect or problem data and are currently delivered in text format along with any data ordered through the ARM archive. These data quality reports are stored in a database and work is underway to provide this quality information in machine-readable form and to use this information as a filter in the data-ordering process.
As noted above, the data volume and flow rate of some of the new instruments, and in particular the radars, is significantly greater than previously deployed ARM instruments. The increased data volume poses challenges to data delivery, processing, and analysis. To mitigate this issue, a data processing system, The ARM Data Cluster, has been established at Oak Ridge National Laboratory in association with the ARM data archive. The data cluster provides a workspace for algorithm development and data evaluation that removes the barrier of transporting large volumes of data over the network. This workspace is also intended to serve as a community software development and tool sharing area.
Continuous atmospheric observations from the ARM Facility are entering their second decade, with the first instruments having been deployed at the SGP site in 1992 (SS94). The ARM mission has always been to provide atmospheric measurements for the improved understanding of the atmosphere and the translation of that improved understanding into better representation of physical processes in climate models but the scope of the program has evolved and grown over time (SS94; Ackerman et al. 2004; U.S. Department of Energy 2010).
Since ARM was designated a DOE science user facility eight years ago, it has grown to include two mobile facilities, an aerial facility, and a broadened set of measurement capabilities. The mobile facilities provide the means to sample an annual cycle in diverse climate regimes to aid in the resolution of complex science issues such as the formation and maintenance of marine stratocumulus clouds while the aerial facilities provide detailed in situ measurements. Application of data from the ARM Facility has led to a wide variety of science advances in areas ranging from radiation measurements to cloud microphysics. The advanced understanding of atmospheric processes from this work is now being implemented in climate models. With the 2009 Recovery Act, the measurement capabilities of each site and the aerial facility have grown significantly. These new instruments provide the means to measure cloud properties more accurately, to study the spatial distribution of clouds and precipitation, and to expand the types of aerosol parameters observed. Together, these measurements provide a comprehensive data set for studying a broad array of atmospheric processes including the interaction of clouds and aerosols.
Fully exploiting these new measurements requires changes to the facility infrastructure and the development of advanced data products. Changes to infrastructure including a new radar operating strategy are underway, as is the development of new data products. Data product development is being done primarily within the ARM infrastructure so far and there is a need to engage with a broader community to accelerate the application of these data. Users of ARM data are encouraged to engage with the facility infrastructure to share their advances in retrieval development and to communicate development needs.
The ARM Climate Research Facility is funded through the DOE Office of Science and is managed through the Biological and Environmental Research (BER) Division. ARM is supported by a large number of dedicated individuals, far too many to mention here. The authors would like to specifically thank Wanda Ferrell, Rick Petty, and Ashley Williamson at DOE headquarters as well as the members of the joint ARM/ASR Science and Infrastructure Steering Committee (www.arm.gov/about/contacts) for their guidance and support.