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4 T~ r ~ . OOlS and ec 1nlques for Advancing Our Understanding The past few decades have seen the development of a multitude of new tools for measuring and modeling physical processes of cloud and storm systems. It is becoming feasible to carry out detailed studies of the chain of physical events in the evolution of a cloud system. This will lead to restore definitive assessments of the effects of seeding, refinements of physical hypotheses, and "prospecting" information about suitable seeding targets. Allis chapter identifies important developments in observational technologies and modeling and data assimilation capabilities and discusses how these new tools and techniques can best be applied to studies of enhancing atmospheric water resources and mitigating hazardous weather. MEASUREMENT AND OBSERVING TECHNOLOGIES Several large weather modification research programs were carried out in the late 1960s and early 1970s, including the National Hail Research Experiment aimed at hail suppression, the Sierra Cooperative Pilot Project aimed at snowpack enhancement, and the High Plains Experiment aimed at warm-season rainfall enhancement (among others discussed in Chapter 2 and Appendix A). These experiments contributed to the development of many new observational instruments and facilities such as the Wyoming King Air reseat ch aircraft, the NCAR CP-2 dual-wavelength radar, the CHILL dual- wavelength and Doppler radar systems, NCAR and NOAA Doppler radars, and the NCAR Portable Automated Mesonetwork. These systems defined the state of the art at the time and contributed much to our current understanding of precipitation processes. Although weather modifications research has declined since that time, observing technologies with which the field could benefit have continued to advance. Cloud- seeding research activities Carl now employ revealing measurements that were unavailable in earlier decades, particularly in terms of remote ser~sing. The new observations offer more accurate and higher resolution precipitation measurements and three-dimensional depictions of the structure, airflow, and hydrometeor composition of clouds before and after seeding. 45

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~6 CRITiCA L I~SSIJES IN AREA THEA AlODIFI(-'/ TION RESE-ARCIJ Several remote-sensing advances of great potential value to cloud seeding were fostered by urgent needs in other fields? including requirements for improved severe storm warnings, detection of aircraft icing conditions, and better understanding of the role of clouds in climate change. Some of these new observing, technologies leave had cursory initial demonstration uses in actual weather modification experiments but none have as yet been used as integral components of experiments designed to test and evaluate specific scientific hypotheses. Thanks to continuing development in other fields these technologies are reaching a level of maturity float makes their wider use in cloud-seeding research and operations feasible and attractive. The following observational tools ar likely to provide contributions to future weather modification steadies. Doppler Radars At the time of the major weather modification field studies mentioned earlier ~ the use of Doppler radar was embryonic, the performance characteristics of Doppler radars were still topics of research' and multiple Doppler networks were just emerging In the subsequent decades attendant research led to operational deployment of Doppler radars for precipitation measurement, severe weather detection and warning (the Next Generation Radar, or NEXRAD, network), and for detection and warning of hazardous wind shear at airports. Serafin and Wilson (2000) describe the status of these operational systems. These radars produce data that are of research quality and the data are becoming available in real time (for instance, through the Collaborative Radar Acquisition Field Test CRAFTY. Another major airborne instrument development has been the advent of airborne Doppler radars flown on NCAR and NOAA research aircraft as well as on the NASA ER-2. These radars have produced information of unprecedented accuracy and resolution in precipitating systems' leading to improved understanding of the structure of and air motion fields in hurricanes (Heymsfield et al, 2001), severe storms, and even in optically clear air (Wakimoto and Liu, 19983. New understanding of the genesis and evolution of tornadoes and the intensity of hurricanes has been gained from these observations. Highly mobile ground-based radars have also demonstrated their utility for high-resolution measurements in the challenging conditions prevalent in severe storm environments (Wurman and Gill, 20009. Atmospheric Profiling Much progress has been made in the arena of atmospheric profiling? and sensitive wind profilers now are available commercially. These devices measure profiles of tropospheric winds continuously and when coupled with acoustic sounders' also measure profiles of temperature (May et al., 1990~. Ground-based GPS receivers can routinely measure path-integrated water vapor. Progress has also been made in optical sensing of the atmosphere. Differential absorption and Ra~nan-scattering lidar are capable of measuring water vapor profiles (Ismail and Browell, 1994; Melfi and Whiteman, 19854. Solid-state and reliable Doppler lidars have been used very effectively for measurements of winds and turbulence (Poon and Wagoner' 1995 J. Scientists have recognized the

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TOOLS A .VD TECI-I .VIQZ;rES FOR A D VA NCIN(r OUR Z!,?~7DERSTA .VDI.INTG 47 importance of better water vapor measurement techniques and completed the most comprehensive research project ever attempted to better characterize the three- dimensional structure of water vapor (described at ~. Research interests in profiling the atmosphere have become so active that a special issue of the Journal of Atmosuhe'^ic and Oceanic Technology has been devoted to the topic (JAOT, 20024. ~ . . Microwave Radiometry In glaciogenic seeding the objective is to use a seeding agent (nuclei or dry iced to convert tipsy supercooled water droplets to ice crystals, plaice grow rapidly and precipitate out of the cloud. Thus, locating regions of high concentrations of supercooled liquid in natural clouds is of paran~ount importance. A promising tool for this "prospecting" work is the dual-channel microwave radiometer, which retrieves the patl~-integrated total amount of liquid water and water vapor along its beam by simultaneously measuring emissions from vapor and liquid at frequencies near 21 GHz or 23 GHz and 31 GHz (Westwater, 19939. Ground-based, unattended vertically pointing microwave radiometers have been used for monitoring aircraft icing conditions aloft and in atmospheric radiation climate research programs. These units' based on technology developed in the l980s, are now commercially available, as are newer ones that monitor additional frequencies to provide coarse vertical profiles of cloud liquid water content and temperature. The ability of a scanning microwave radiometer to observe cloud- seeding opportunities was demonstrated by the NOAA/ETL in the Sierra Cooperative Pilot Project orographic snowpack enhancement experiment (Snider and Rottner7 l 9824. Aircraft-~ounted microwave radiometers are also now available and Inlay be suitable for cloud-seeding activities. Polarimetric Radar Polarization-diversity (dual-polarization) radars measure signals backscattered from targets in two orthogonal orientations to discriminate between water and ice in clouds, detect hail, identify the types of particles present (see Plate 6), and attain more accurate estimates of rainfall rates using differential phase (KDp) methods (Bring) and Chandrasekar, 2001~. These capabilities are of great potential value in assessing cloud- seeding experiments For individual cloud studies, polarimetric particle classifications have the potential to reveal the transformation of supercooled liquid water droplets to ice crystals in glaciogenic seeding arid the development of large drops in hydroscopic seeding They can also follow the movement and dispersion of seeding aerosols using microwave chaff tubers as tracers (as discussed later). I hree-dimensional depictions ot these processes may be observed as they occur using ground-based or airborne r~olarimetric radars. The particle classifications also can r efine conventional ,~ .. . . . . `% .. .. . . . ~ . ~ . . ~ . .. . . retlectl~lty-based ralntall estimates by 1dentllylng regions ot echo that are not rain or contain rain with contaminations of hail, snow, ground clutter, or insects. The new differential phase estimations of rainfall rate offers a method for measuring the ground-level result of seeding that is free from several factors that have historically degraded the simple reflectivity-based estimates of precipitation. The method avoids or

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~8 CRITICAL I~SSlJES IN TLEATI-IER AlODIFICATIONRESEARCH minimizes problems related to hardware calibration errors, attenuation, partial beam filling' partial beam blockage, the presence of hail, and variability of drop size distributions (Zrnic and Ryzhkov, 19964. Polarization-diverse radars are available only in the research community, but their numbers are expanding. Most dual-polarization research in the Ur~ited States has been conducted with the large S-band (3 GHz) weather surveillance radars, such as those at NCAR, NOAA's National Severe Storms Laboratory, and Colorado State University. NOAA's Environmental Technology Laboratory uses polarimetric methods with much smaller millimeter-wave radars (35 GHz) for cloud hydrometeor identifications and at X band (9 GHz) for chaff tracer tracking and differential-phase rainfall estimations. Even smaller' highly mobile polarization-diversity ~nillimeter-wave radars are operated on trucks by the University of Massachusetts and on research aircraft by the University of Wyoming. The technology now exists to inexpensively upgrade radars to multiparan~eter capability; and the national network of operational S-band weather surveillance radars (WSR-88D or NEXRAD) may be upgraded to include polarimetric capabilities by the end of this decade, depending in part on results of the Joint Polarization Experiment demonstration in Oklahoma in 2002-2003 (NRC, 20029. Millimeter-Wave Cloud Radar Millimeter-wave cloud radars use wavelengths of 8 mm or 3 mm that are more than an order of magnitude shorter than those of S-band weather surveillance radars. Lhermitte (1987, 1988) pioneered the use of 3 Alum wavelength for sensitive and high- resolution observations of developing clouds and precipitation. Use of this short wavelength offers unique opportunities for both airborne research (Leon and Vali, 1998; Pazmany et al., 1994) and ground-based studies (Martner et al., 2002~. The primary attributes of these radars are superb sensitivity and resolution (~50 m), which enable them to detect very weak targets, such as non-precipitating clouds with remarkable detail and without the need for large antennas and powerful transmitters The small size and weight of their hardware components makes mobility highly feasible. Trailer-mounted, truck-mounted, and airborne versions are now in operation arid the first space-borne cloud r adar (CloudSat) will be launched in about 2005. The main disadvantages of millimeter-wave radar are severe attenuation by liquid water clouds and rain and limited range coverage. Thus cloud radars are best suited for short-range observations of the fine-scale structure of clouds, snowstorms, arid weak rainfall. These radars can possess all the scanning' Doppler, and polarization-diversity capabilities that have been developed originally for the much larger microwave radars. A decade of research at NOAA/ETL on polarimetric identification of cloud hydrometeors with millimeter-wave radar (for the purpose of remote detection of aircraft icing) has derived hydrometeor polarimetric signatures (Figure 4.1) that have obvious applications to cloud-seeding experiments (e.g., Reinking et al., 20023. Short-wavelengtl~ cloud radars, especially airborne units, hold great promise for revealing the physical transformations in the seeded regions of clouds. Longer wavelength radars, however, are

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TOOLS A ND TECI-~.VIQ lJES FOR A D VA NCIN( r O UR UlN'DERSTA NDI.l\TG 49 w40 . :. .~ or . . +~D :~; at., . i . <^, ~ hi: Pl~3 i/ 'I, ~.~%~. ~ ~~ ~ J . . - ~ - ~~.~" s .~ ~ ^~ Is~~ ~ ~~ ^ NW ~.- . . X a! 4,,: < FIGURE 4.1 Depolarization ratio as a function of antenna elevation angle, showing signatories of various hydrometeor types obtained with scanning milJimeter-wave cloud radar. Each signature type has been matched to theoretical model simulations arid verified with in site particle sampling. SOURCE: Reinking et al. (20001. likely to restrain the primary tool for observing and assessing the ultimate desired result of seeding in terms of precipitation reaching the ground. Combining simultaneous cloud radar and radiometer observations of clouds overhead to retrieve estimated profiles of hydrometeor mass content, median size, and concentration has become a routine procedure at the U.S. DOE CART sites and in other cloud/climate research experiments. Millimeter-wave radar data are combined with microwave radiometer data for retrievals in liquid clouds, such as stratus (Frisch et al., 1 9951, and with infrared radiometer data for retrievals in optically thin fee clouds, such as cirrus (Matrosov et al. 1992). Retrievals of properties in mixed-phase clouds are more problematic. These kinds of active/passive remote sensing combinations could benefit eloud-seedi~g research' particularly if the theory and technology can be extended to scanning applications. Perhaps the most impressive demonstration of the combined use of cloud radar arid microwave radiometers in a cloud-seeding experiment is the ease described by Reinking et al. (2000~. Earlier numerical modeling simulations by Bruintjes et al. (1994) indicated that under certain wintertime stability and airflow conditions, the mountains of central Arizona initiate the development of a strong gravity wave, which produces sustained updrafts that condense vapor into significant amounts of supercooled liquid water. This orographieally induced standing wave of supercooled liquid represents an attractive target for glaciogenic seeding to increase snowpack on the downwind Mogollon Rim, which is the state's major water supply source. A field program

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so CRITICS L I.SS(.JES IN IDEA TlIER AlODIFICA TION RESEARCH incorporating ground-based remote sensors and aircraft observations was established in 1995 to investigate the n~odel predictions. Plate 7 shows a prominent wave across the Verde Valley as observed by a scanning cloud radar and strong accentuation of liquid water content in the ascending part of the wave measured by a steerable microwave radiometer, thereby confirming the model prediction. GPS and Radar Cell Tracking Software In recent years cloud-seeding operations have relied heavily on sophisticated real-tine displays of the radar reflectivity of storms and the location of seeding aircraft to manage and assess seeding operations. Although there are many cell-tracking programs, such as the one described by Rosenfeld (1987~' the TITAN software package developed at NCAR is most used among these systems (Dixon and Wiener, 1993) This software objectively identifies discrete storm cells, follows their movement and development, and keeps statistics (Plate 84. In addition to providing guidance for real-time operations, TITAN is used extensively in subsequent analysis to examine the effects of seeding, in terms of reflectivity enhancements, on treated stolen clouds. It has become an important tool in many operational convective cJoud-seeding operations and represents a valuable aid for automating the display and analysis of radar data. TITAN has evolved since 1993 and has several features that are specifically aimed at weather modification applications. Among these are the ability to distinguish independent cells within merged cells, and the use of an altitude threshold that mitigates the effects of the Earth's curvature. In weather modification research an annulus between 15 km and 90 km is usually used as the region in which echoes are reliably tracked. For TITAN to be effective, accurate location of seeding and research aircraft is essential. This was a significant impediment to many weather modification studies in the past. The advent of the GPS now provides a superb and inexpensive tool for this purpose (Plate 7i. In addition ground-based GPS receivers, in combination with other co-located routine temperature and pressure measurements, are now available as a national network (Ware et al., 2000) for measurements of column-integrated water vapor, a necessary measurement in weather modification research. Dense networks of such measurements could be cost-effectively deployed in future experiments. Finally, GPS tracking is now used with radiosondes to provide very high-resolution vertical profiles of temperature? humidity, and winds (Hock and Franklin, 1999; Aberson and Franklin, l999~. Satellite Imagery Satellite-borne instrumentation provides horizontally contiguous observations of water vapor fields, aerosol amounts and particle sizes, cloud-top temperature, particle size and thermodynamic phase, and to a limited extent in-cloud processes and precipitation over a large aerial extent. For instance, the Tropical Rainfall Measuring Mission (TRMM) includes precipitation radar, a microwave imager, and a visible- infrared radiometer, all of wl~ich will help improve modeling and prediction of rainfall processes. CloudSat, an upcoming multisatellite, mu]tisensor mission, will utilize a millimeter-wave radar to profile the vertical structure of clouds, and measure the profiles

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7 00LS AND TECH IQZJES FOR AD VANCIN(~r OUR {!~7\~DERSTANDI.INTG 5! of cloud optical properties cloud liquid water, and ice-water content. These data can be used to evaluate and improve the way clouds are para~neterized in models. The Global Precipitation Measurement (GPM) Microwave Imager will utilize a series Ott passive microwave radiometers to provide near-global measurements of precipitation. These capabilities have opened a resew era in cloud physics and could provide many new opportunities for assessing the effects of weather modification. Satellite observations already are playing an important role in studies of inadvertent weather modification by tracking plumes of industrial pollution arid their ejects on precipitation suppression, as well as hydroscopic effects of salt aerosols that aid in restoring precipitation. Rosenfeld and Lensky (1998) developed a new methodv]ogy for using T RMM and flee Advanced Very High Resolution Radiometer sensors to infer the microstructure e of convective clouds and their precipitation-forming processes with height. 1 Ir'Situ Measurements Robert Knollenberg pioneered the development of laser based measurements of the particle size distributions in clouds. These revolutionary devices usually mounted on the tips of research aircraft wings, use laser light to image and count particles. Knollenberg probes rapidly became the tools of choice for cloud physics researchers. These Particle Measuring Systems, Inc. (PMS) probes (Knollenbe~g, 198] ~ together with hot-wire liquid water probes (King, 1978) have been the principal instruments for characterizing aerosol and cloud particle properties for the past two decades. They are useful for understanding the types and numbers of hydrometeors and their evolution. They have also been used to develop interpretative algorithms for ground-based radar measurements. I n many weather modification experiments the probes have been deployed to observe the hydrometeor evolution that takes place before and after seeding. Through the years new probe designs have evolved, and they now cover a wide range of particle sizes. Some designs use forward scattering to detect very small particles, including aerosols. At present, however' no single instrument can provide simultaneous, accurate information about cloud particle spectra and liquid water content. A combination of instruments is needed, and this situation seems unlikely to change in the near future. The Passive Cavity Aerosol Probe measures the size distribution of aerosol particles between 0.1 Em and 3 Em diameter in 15 size channels. The Forward Scattering Spectrometer Probe (FSSP-100) measures cloud droplet distributions between 0.5 Am and 47 Em diameter in 15 size bins. Anothe1 version of this probe (FSSP-300) with higher size resolution for aerosol and cloud droplet sizes between 0.3 him and 20 aim diameter has also been used extensively. The Fast-FSSP (Brenguie~ et al., 1998), an improved version of the FSSP-100, provides better sizing of the droplets and more accurate determination of the concentration of particles. Several optical array probes have been developed to measure the concentration and sizes of larger particles. The technology in use currently is the Optica] Array Probe (OAP-260X) which measures the concentrations and sizes of particles between 40 Em

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52 CRITIC.'A L I~SSlJES IN [YE-A TI--IER AIODIFICA PlON RESEARCf-f and 640 Em diameter. Optical arrant probes have also been developed to provide two- dimensional images of hydrometeors, with a resolution of 25 Bin for cloud particles and 300 Bins for larger hydrometeors such as large ice crystals and raindrops. The Cloud, Aerosol and Precipitation Spectrometer (CAPS) (Baumgardner et al., 2000) instrument consists of five sensors: the aerosol and cloud droplet spectrometer (CAS) (0 35 Am - 50 Am diameter), the cloud imaging probe (CTP) (25 M-1550 Am diameter), the liquid water detector (0.01 gm~3-3 gnat), tile air speed sensor, and a temperature probe. The CAS measures the conventional fo~ward-scattering light from single particles but also the back-scattered light that provides an estimation of the aerosol refiactive index. in addition, the sample volume is defined similar to that used in the FSSP-300X (Baumgardner et al., 1992~. These improvements provide an extended size range of particle measurement that covers much of the accumulation mode aerosols arid up to small drizzle drops in clouds. Due to the improved electronics nanny of the limitations associated with the FSSP-100 have been overcome. The principal improvements of the CIP are added stability against vibration' decreased response time, and decreased dead tickle that provides for better resolution, sizing, and more accurate particle concentrations. The liquid water content detector uses technique described by King ~ 19783. Preliminary results using the CAPS have shown increased capability compared to the conventional PMS probes. A new generation of particle spectrometers uses optical response rather than direct single-particle collection. The Gerber Particle Volume Monitor (Gerber et a]., 1994) measures the liquid water content, drop surface area, and effective radius. The light scattered in the forward direction by an ensemble of drops is optically weighted and summed on a photodetector. The Cloud Droplet Spectrometer (CDS) (Lawson and Cormack, 1995) measures the forward-scattered light from an ensemble of drops Tl~e CDS also computes drop size from the raw scattered light by inverting the measurements. The measurement has inherent advantages to overcome the limitations of single particle sizing and counting methods. Lawson et al. (1996) describe preliminary measurements with this instrument. Another instrument, the Cloud Particle Imager (CPI) uses innovative new technology to record high-definition digital images of cloud particles and measure particle size, shape, and concentration (Lawson, 1997; Lawson and Jensen, 19981. Tl~e high quality of the CPJ images supports the generation of individual size distributions for different types of particles (see Figure 4.2~. Due to varying depth of field (depending on the size of the particles), the imaging sample volume of the CPI varies from about 0.002 cm3 to 0.2 cm3. A drop-off in particle detection efficiency starts at about 25 ~m, thus the small end of narrow particle distributions (such as a typical distribution of cloud drops) will be undercounted. Research is ongoing to interpret the measurements from this instrument and its operational limitations. Korolev et al (1999) described some recent measurements using this instrument. Another important parameter is the measurement of LWC. While LWC can be calculated from the FSSP, the most widely used instruments have been the Johnson- Williams and CSIRO-King probes. The LWC is determined from the cooling effect of cloud droplets impinging on a treated sensor element thatis exposed tothe airflow

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TOOLS AND TECF-INIQZ,rL-S FOR ADI'ANCI.~(, OUR lJ,N'DERSTANDl.iN~G 53 :: ~~ ~~ ~~ ~ ~ ~0 ,] PleCes of ~~.~d o.~-~.~-~S I:' : ~ FIGURE 4.9 Particle images from the CPI instrument SOURCE: Lawson, et al. (19981. Outside the aircraft. Limitations exist for all instruments measuring LWC, but for the King probes, errors occur when droplet diameters become greater than 50 Em as droplets break up on the sensing element and are removed by the airflow before they evaporate completely; this causes an underestimation of liquid water. Large quantities of ice particles also are a limiting factor (FIeishauer et al., 2002~. The Gerber and CDR probes are also used to measure LWC. A comparison of more than 20 different types of probes (Strapp et al., 2000) indicated that the Nev~orov total-wate~-content probe (Korolev et a]., 1998) is the most accurate }~ot-wire estimate of LWC in water-only clouds Title large do oplets. T racers A difficult problem that has plagued matly cloud-seeding experiments and operations is the question of whether the seeding material actually reaches the targeted regions of cloud, and whether it arrives there in effective concentrations. This is especially true for g~ound-based seeding operations, but it also applies to seeding from aircraft. Tracer techniques offer valuable information on nucleant transport and

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54 CRITICAL I~S~Sl.JES IN TT'F,A TI--IER AlODIFIC,4 T10~ REtSE-ARCI! dispersion. The tracer is released together with the seeding material, and its location and concentration is subsequently measured as a proxy for the t~ucleant. The Almost widely used tracer for cloud seeding is SF6, an inert, anthropogenically produced compound that can be detected in incredibly small concentrations (Stith and Benner? 1987) but requires in situ sampling, which can be difficult. Other i'? Mu techniques include airborne ice-nuclei counters and chemical analysis of the silver content (i.e., seeding material) in snowfall. A particularly promising remote-sensing tracer method uses radar to track microwave chaff, which consists of very thin aluminum-coated glass fibers cut to half the wavelength of the observing radar. Chaff fibers released with or without seeding material show by direct measurement the actual transport and dispersion occurring within clouds. T lee fibers can be detected by radar in extremely small concentrations. Tl~e depolarization of the radar signal (the depolarization ratio) caused by the chaff allows it to be isolated from the signal of cloud intensity (reflectivity) and to be effectively tracked (partner et al., 1992; Reinking and Martner, 19961. The volume treated and the location of treatment effects thus can be identified and assessed in relation to flee total cloud volume. The concentration of chaff fibers can be computed from the radar measurements to yield information about diffusion rates. Although the chaff fibers fall faster than silver iodide aerosols (i.e., the seeding material), they provide a good approximation of the aerosol movement for several minutes after a release. This allows a polarization-diversity radar to observe and provide three-dimensional depictions of seeding aerosol movement to a treated cloud, as shown in Figure 4.3. Chaff tagging offers additional opportunities to remotely sense microphysical changes between tags. For instance, using such tagging, ice particle production arid enlargement by seeding has been followed from the source to snow on the ground (KIimowski et al., 1998; Reinking et al., 1999, 20004. 1 1 All of these tracer methods have had modest demonstrations in weather modification research experiments, such as the 1993 North Dakota Tracer Experiment, a summer convective cloud-seeding tesearch experiment that emphasized the use of a variety of tracer methods (Stith et al., 1996~. But none has yet gained widespread, routine usage. Nevertheless, tracers ale likely to be an important part of future seeding research because they offer vital observations of both the seeding material deliver>" arid else cloud r espouse. MODELING AND DATA ASSIMILATION Numerical modeling should be a lcey component of weather modification research. Computational resources are now probably sufficient to allow realistic cloud- resolving simulations with short-term predictive value. A properly constructed simulations model is internally self consistent, complete in spatial and temporal coverage, and suitable for comparison with datasets. Such a model also can be the basis for a data assimilation process, which allows incomplete observational data from various sensing systems to be used to initialize a model's predictions. To h~11;11 these needs the microphysical processes relevant to weather modification need to be carefully incorporated and tested in the models, a process that is well under way. The

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TOOLS A ND TECI-I.VIQZ;TES FOR A D I7A NCIN( r O l;R U~7~7DERSTA NDI.IN7G 55 7~-~'ng Cumulus 5~0~ Y[_'`/'J ~ ~ ~ ,X ~ I, .,, ~ I' ' OCR for page 45
56 CRITICS L I.SSZJES IN [VEA TI-~lER AlODIFICA T10N RESEARCI! establish or refine physical hypotheses. They offer the only opportunity to see the effects of cloud seeding on identical (model) cloud situations, one seeded and once not seeded. They may be used to recreate cloud-seeding experiments from the past to help in the evaluation of those cloud-seeding effects. alley can be used to simulate the dispersion trajectories of seeding material, provide r eal-time forecasting in support of field experiments and operations' examine flee potential effects of cloud seeding outside of the seeded area, and aid in the statistical analysis of weather modification experiments. The following sections review the history and methodology of modeling related to weather modification and evaluate future capabilities and needs. During flee last 20 Yeats cloud and storm modeling have been pursued most seriously tar basic research and application to prediction and warning and to a lesser extent for application to weather modification. 1~ an important review article Orville (1996) surveyed the progress of modeling related to weather modification to that date. A snore recent review has been presented by Khain et al. (2000), and a substantial account of the NASA-Goddard modeling activities is given by Tao et al. (20031. The following account is based partly on these surveys. Cloud Modeling History Old Methodology Cloud mice ophysics and dynamics have developed ghostly from different academic bases. The discipline of cloud mice ophysics was developed mainly by physicists, while cloud dynamics tended to be a blanch of fluid dynamics developed mostly by engineers, meteorologists, and oceanographers. A few scientists focusing on cloud processes have attempted the difficult task of combining these sources of knowledge. The theoretical bases of both dynamical and cloud mic~^ophysical processes have existed for some 30 to 40 years. Computing facilities and techniques, however, were much too limited to allow realistic model simulations until fairly recently. Early models of microphysical processes tended to be based on assumed particle trajectories, Title almost no dynamic contents while early cloud dynamics models contained only the most limited microphysical parameterizations. As computing hardware and numerical technology evolved, the dynamical and microphysical simulations advanced and became mutually accessible. An early but sometimes still used form of modeling is based on the plume theories for convection developed by fluid dynamicists in the 1940s and 1950s, Fist applied to prediction of nuclear bomb effects (Mo~4on et al., 1956~. A few one- dimensional equations are applied, representing the budgets of mass, buoyancy, moisture, and momentum in a cloud. These one-dimensional steady-state models ate based on ordinal y differential equations, and they have coupled microphysics and dynamics (Simpson et al, 1965; Simpson and Wiggert, 1969; Cotton, 1972) In the more modern versions a realistic environment may be assumed, with natural convection forced by condensation heating and freezing Cylindrical or slab symmetry normally is required' which limits or neglects the effects of mean shear. Microphysical processes may be simulated, but neither the distribution of seeding agents nor the trajectories of precipitation particles can be realistically followed. A list of such models' designated as

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TOOLSA~D TECIl.~[QZJESFORADVANCIN(r Ot;R ti,N'DERSTA~D{NG 57 "one-dimensional steady state" or'`one-dimensional time dependent" is given by Orville (19964. The first non-steady numerical simulations of cloud convection date front the 1960s (Ogura, 1963; Orville, 1965) and were two dimensional, usually slab symmetric. Precipitation was introduced with varying levels of sophistication in flee late 1960s' and attempts at thunderstorm simulation were made by Takeda (19713. The importance ofthe third dimension followed the clarification of the important differences between two- and thtee dimensional turbulence- by Fjortoft (1953) and Kraichnan (1967~. The first three dimensional simulations of boundary layer stratocumulus, cumulus, and deeper convection were presented in the mid-1970s. Those which produced the greatest impact, however, were the Klemp and Wilhelmson ~ 1978) and subsequent simulations (see review by Klemp, 1987), which showed how shear could contribute to convective dynamics and produce tl~understorn~s with strong rotation and other observed '~supercell" characteristics. "Bulk" microphysics were used, with just two categories of liquid water: cloud and rain. The transformation front cloud water to rainwater involved crudely simulated processes of autoconversion and collection. Models aimed at more accurate simulation of microphysical processes (usually at the expense of dynamic reality) were also being developed. These included the Orville and Kopp (1977) hailstorm model and later the Orville and Chen (1982) simulations, oriented specifically to cloud seeding. In the latter the n~ic~ophysical modulethough still confined to "bulk" processescontained four categories of cloud ice with fairly complex conversion algorithms, but the domains remained two dimensional. The correct simulation of the thermodynamic effects associated with precipitation processes- melting' evaporation, arid recycling of ice and water particles into new cloud updrafts is usually dependent on having three dimensions and fairly high resolution. Since Orville's (1996) report, it has become possible to incorporate more detailed cloud physics algorithms into three-dimensional dynamics simulations. The original single moment bulk schemes were expanded to two moment schemes (Meyers et al. 1997), allowing noose freedom for the distributions of hydrometeors to respond to ohvsical processes. A method used freoue~tlv now is to define the mass distribution of ~ 1 1 ~ particles by blnS covering size ranges, With each On larger by some factor shall the previous one. The particles in each bill ate allowed to grow or shrinl; by condensation, evaporation, deposition, and coalescence; to freeze or melt; to settle gravitationally; and to shed water or break up into smaller drops. Thus the number of particles in each bin mar increase or decrease with tinge. This method obviously requires greater computer memory and speed than for the bulk process assumptions. These simulations were first done in a zero-dimensional mode that follows a supposedly uniform parcel up or down (Berry and Reinhardt, 19741. Later the models were pursued in two or three dimensions in the context of cumulus clouds (Kogan, 1991) or shallow cloud-topped mixed layers (Kogan et al., 1995), for which the microphysics consists of purely liquid water processes. More recently simulations have been carried out for deeper clouds with large drops, freezing processes, and simulated seeding with cryogenic or hydroscopic agents (Khan et al., 2000, 2001; Khain and Sednev7 1995, 1996; Reisin et al., 1996a,b; Tao et al.' 2003; Tzivion et al., 1994; Yin et al., 200Oa,b, 2001;~. Bin models also recently have been applied to marine stratocumuli (Feingold et al., 1999; Jag et al., 2000, 2001,

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sS CRITICA L ILSSIJES IN [VEA TI-lER AlODIFICA TION RESEARCI-f 20021. As illustrated in Figure 4.4, the Goddard Cumulus Ensemble model, as well as several other cloud models, can simulate multicell convective systems and be nested in the framework of larger-scale models and observational systems (Tao, 200~. (/ Passive Radiative' \: Model ~7 \~ I inhtnino J I i;.; ~ Goddard Radiation _ LW and SW Radiation ;, O .0 en a' to an, Scale Interaction Sea Surface Fluxes TOGA COARE ~ , _ ~.~ ~ 1 ,~ 1' GCE Model T. Q. U,V,W, P. Ke c, O I . , (q, N I Call m' an at, (L, i GCM and Climate Model 2-l\Aoments Microphysics qc, qr, pi, qs, qg, qh ( - - 3 Soil/Vegetation (7 layers) J PLACE FIGURE 4.4 Schematic diagram showing the characteristics of the Goddard Cumulus Ensemble (GCE), a cloud-resolving model that includes explicit representation of warm rain and ice microphysical processes. Its main features are described in Tao et al. (20031. Arrows with solid lines indicate a two-way interaction between different physical processes and arrows with dashed lines indicate a one-way interaction. SCM stands for Single Columns Model, a one-dime~sional model with all GCM's physical processes PLACE stands for Parameterization for Land- Atmosphere Cloud Exchange, a detailed interactive process model of the heterogeneous land surface and adjacent near-surface atmosphere. The model variables include horizontal (u, v) and vertical velocities (w), potential temperature (T), perturbation pressure (p), turbulent kinetic energy (Ke), and mixing ratios of all water phases Water vapor (Qj, liquid (cloud ~vater/qc, rain drops/qr), and ice (cloud ice/qi, s~ow/qs, graupel/qg, hail/qh)~. Recently, detailed spectral-bin microphysical schemes were implemented into the GCE model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets and several types of ice particles. Due to extensive computation, this microphysical scheme can only be run on the two-dimensional version of the model SOURCE: Wei-Kuo Tao, NASA/Goddard Space Flight Center.

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TOOLSAND TECHNI QUES FORADVANCI NG OUR UNDER~ANDI NG Cur r ent Status and Pr aspects 59 The most fully reported cloud simulation model relevant to nucleation, preci pi tati on, and weather modi f i cati on studi es are the model s of the two I srael i groups, one at the University of Tel Aviv developed by Tzivion and associates, the other at the Hebrew University of ~Jerusalem, developed by Khain and associates. The group at Tel Aviv focused more on the hydroscopic seedi ng agents, whereas at Jerusalem they focused more on the effect of variations in the natural and anthropogenic aerosol on the precipitation formation process. Yin et al (2001) found that seeding with hydroscopic flares produces changes in the hydrometeor distribution, with resulting changes in the radar reflectivity-rat nfal I rate relationshi p. Such changes are significant si nce radar is the primary evaluation tool for precipitation enhancement projects. Khain et al. (1999) report on si mulations of cold season clouds over an eastern M editerranean coastal zone i n conditions of large-scale convergence that lead to significant precipitation. They concentrate attention on the effects of varyi ng amounts (100, 500, and 1000 CCN cm~3), verti cal di stri buti ons (uniform or decreasi ng upward), and types (sodi urn chl ori de and ammonium sulfate) of condensation nuclei. They found that although most of the rain forms from melted snow or graupel, the larder droo sizes Generated bv the cleaner air , .. . . . . . . _ - _ _ , , _ . _ , smear cc~x counts' produced rain much faster and that the total amount of rain was sensitive to the nucleus type (greater for ammonium sulfate). Neither of the results of the two groups coul d have been obtai ned by exi sti ng bul k model approaches. Other model i ng groups have adopted approaches to mi crophysi cal model i ng similar to that of the Israelis. A m for contributor is the NASA Goddard group, whose cl oud-model i ng results were recently summari zed by Tao et al . (2003~. The pri mary emphasi s of the Goddard group i s cl ouds and preci pi tati on as mat or i nputs to gl obal and regional climatology, but here too the microphysical interactions are often crucial . For exampl e, the f ormati on of I ong-l i ved real dual ci rrus sheets i s cri ti cal to the radi ati on budget, which then feeds back into the cloud dynamics. Also precipitation efficiencya the fraction of cloud liquid water that reaches the ground as rains is important both for climatological and weather-forecasting purposes, and it apparently is strongly dependent on mi crophysi cal processes. Tao et al . (2003) report on three versi ons of mi crophysi cal si mul ati on, i ncl udi ng i ce processes, two of them rather sophi sti cat ed bul k model s and one a hi n model . M ost of the results shown are compari sons of model s with each other, rather than with observati ons. Compari sons of hi n model results wi th hi gh and I ow CCN counts, in this case for entirely liquid clouds, indicate considerably greater rainfall for the clean al r case. Despite the progress that has been made, model predictions of hydrometeor evolution are not sufficiently accurate to inspire great confidence. Errors arise from I i mited revel ution, i Insufficiently accurate physics, and i nadequate observati ons. Bryan et al. (2003) point out that thetypical resolution of simulated cloud and storm models, about 1 km, is insufficient to resolve the inertial range and predict dissipation. This is important because condensation, freezing, and coalescence appear to be dependent on at least the statistical structure of small-scale turbulence as principally defined by the dissipation rate. Resolution of order 100 m is found to be necessary for fairly accurate dynamical simulations, which stretches computer capabilities close to the limit, even without the best treatment of hydrometeors. Obs~vati onal I i mitati ons i ncl ude the revel uti on of

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60 CRITI CAL I S9UES I N WEATHER MODI Fl CATI ON RESEARCH humidity measurements and the very li mited observational knowledge of the size and compost ti on di stri buti on of condensati on nucl ei and the di stri buti on of temperatures at which freezing nuclei become effective. New methods of remote sensing may significantly i mprove the humidity observations, but the nuclei are only observable i n situ from i Instrumentation at ground stations or on a few research al rcraft, although alternative methods of nuclei retrieval are being explored. The model physics are again subject to computer I i mi tati ons (and cl everness of desi gn), but model i ng of the i nteracti on between ice and water speciesO and even between water drops themselves, whether the same size or notOrestson largely untested hypotheses.4 Accurateprediction of the hydrometeor distri button development is critical to getti ng the dynamics-mi crophysics i nteracti on correct, since hydrometoors determine (through sedi mentation) the location and ti mi ng of latent heat release and precipitation loading impacts on cloud dynamics. It is exactly these detai I s of the hydrometeor di stri buti on devel opment that cl oud seedi ng tri es to alter. Thus, while bin models have many degrees of freedom and thus can simulate many physical situations realistically, much of the knowledge necessary to specify parameters needed i n thei r i mpl ementati on i s sti 11 1 acki ng. Data Assi mi ration, M odel I nitial ization, and Advanced Forecasti ng Systems Methods of optimally assimilating observed data and generating a series of fields sui tabl e f or i ni ti al i zi ng a predi cti on model have al ways been cri ti cal parts of I arge-scal e numerical weather prediction, but at the convective scaJ es, models have been under development for only 10 to 15 years. The potential for assimilation of fin~scale Doppler radar data, and from it establishing the dynamic and thermodynamic fields, was a major el ement of the proposal for the Center for Anal ysi s and Predi cti on of Storms, one of the first of the NSF science and technology centers. Most of the methods developed or adapted by the Center~; scientists and others are variational in nature, involving minimization of the integral of an error function. Among the most sophisticatecl is the adj oi nt method. The adj oi nt of a set of predi cti ve equati ons i s a si mi I ar set whi ch predi cts backwards the weightings of variables at a previous time which contribute to the change of a variable at a given position and current ti me. This al lows, i n pri nci pie, opti mal utilization of current and previous data to produce an initial state for a future prediction. The adjoins method has shown fairly good success in obtaining three-dimensional i nitialization from single Doppler radar data (Sun and Crook, 1997, 2001; Xu et al ., 1994), but it is rather expensive, often requiring the equivalent of 50 to 100 time integrations for a few minutes each. Methods for speeding the convergence are under active devel opment. ~For example, in a model with many different bins of ice and water species, the rate at which ice particles (of size 1 mm to 2 mm) combine with water droplets (of 1/8 mm to 1/4 mm) is a parameter that must be specified. This is a function of drop-size distributions, turbulence, temperature, the hydrodynamics of sedimentation, and, to a lesser extent, electrification of the cloud. Similar rate constants must be specified for all pairs of particle bins.

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TOOLS A ND TECHNIQI J,ES FOR A D I7A NCirN( r O UR Z>Tl\7DERSTA NDI.iNtG Future Prospects 61 Models and data assimilation offer the possibility of greatly ameliorating the difficulties of past statistical verification described in this report. With today's itnproved statistical techniques and sophisticated models sources of uncertainty can be explicitly accounted for' and treatment and control experiments can now be compared spatially and temporally. The computational facilities and human resources necessary for work in these areas exist and can be rapidly developed at a number of governmental (e.g. NCAR, NOAA' NASA) and non-governmental laboratories and university groups for application to weather modification. Development of a cloud and precipitation model suitable for planning and testing seeding experiments may be feasible using the cutting edge of current simulation modeling. However? for real-time modeling studies that run coincidentally with field experiments a model would need to run faster (and therefore nary be confined to a spatially coarser mesh and have less physical complexity) and would require data assimilation and initialization techniques that include microphysical paran~eters. Again, the techniques used for storm analysis and experimental prediction help point the way, although they have not been applied to the newer methods for observing water substance and please, and methods need to be developed for rapid assimilation of these data types. Model forecasts are always uncertain. Increasingly, predictions of large-scale models are presented as probabilities or ensembles. These probabilistic forecasts attempt to account for the uncertainties inherent in initial conditions, boundary conditions' and in the models themselves (especially the model parameterizations of subgrid-scale }physical processes). Similar approaches should be used to quantify the uncertainty in simulations of weather modification experiments, including uncertainties related to the experimental treatment. LABORATORY STUDIES Laboratory investigations play an integral role in advancing the understanding of cloud physical processes. The high degree of measurement capability? repeatability, and control over experimental conditions in the laboratory allows r esearch on detai led processes that is not possible in the free atmosphere. Rogers and DeMott (1991) provide an excellent overview of the state of cloud physics laboratory work as of 1990. The most significant development in cloud physics laboratory studies since the early 1990s is the successful use of electrody~amic levitation chambers, in which nucleation and vapor deposition properties of individual, freely suspended hydrometeors earl be studied in a fully controlled environment (Straw et al., 2000; Swanson et al., 19994. Other important reseal ch continues on drop-drop interactions (Beard et al., 2001), on primaty fee crystal habits arid the impacts of growth and evaporation cycles (Bailey and Hallett, 2002), on nucleation coefficients of liquid and ice phases (Bailey and Hallett, 2002; Shaw and Lamb, 1999; Xue and Lamb, 2002), and on the growth of ice crystals in a water-saturated environment (Fukuta and Takahashi, 19991.

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62 CRIT1C,4L i`SSIJES IN [YF,A TI--IER A1ODIFIC,4 TION RE5~EARCIT BOX 4.1 Hurricane Modeling and Prediction As noted in DeMaria and Gross (2002), hurricanes present a particularly difficult modeling challenge in which a fairly sn~all-scale, circularly symmetric disturbance (the storm) is embedded in a larger-scale surrounding flow. The lack of computer power and adequate observations, especially over the oceans' needed to properly represent initial conditions have been among the greatest difficulties in hurricane modeling More than 20 different types of hurricane models have been developed since 1959. Current hurricane simulations are limited to a resolution of about ] 0 km. with highly parameterized convection schemes. Using nested grid techniques, higl~er-resolution (~1 km), mixed-phase bulk microphysics models can be applied to small, critical regions ifs a hurricane, but until these high-resolution models can be applied to the entire domain of the storm system, only very basic aspects of hurricane modification theories can be tested. Since the 1950s hurricane modeling has been divided into track-forecast models aimed at predicting where the storm will strike land, and intensity- forecast models aimed at predicting the strength and extent of the storm's winds and consequent effects on the ocean (i.e., storm surge). Accurate track predictions require three-dimensional models that can account for the full range of interactions between the storm and its environment. Despite considerable advances in modeling hurricanes, the skill of track forecasts frown a numerical model have only very recently overtaken that of statistical Precast methods (Emanuel, 20029. Average (24-hour) track errors remain above 70 miles for all models (DeMaria and Gross, 2002~. Modeling and forecasting the intensity of a hurricane remains art unresolved challenge The present generation of models may not have enough horizontal resolution to capture the fu]] intensity of extreme storms. However' new three- dimensional storm models (coupled to upper ocean models) should lead to better understanding of the factors that control hurricane intensity (Emanuel, 19999. Many other aspects of the hurricane system are not yet adequately modeled, including the areal extent of storm wields, the storm surge, and precipitation especially flooding rainfall. Improvement in theoretical and numerical modeling of hurricanes will undoubtedly remain a high national priority because of the value of predicting their behavior with increasing accuracy. Whether or not we can learn enough to consider modifying hurricanes to mitigate damage remains to be seen. Certainly any attempt to modify hurricanes must be dependent upon whether their behavior with and without modification can be predicted accurately and reliably. Even alien, any serious consideration of l~urricane modification will raise grave arid far reaching issues of public policy with both ethical and economic implications.

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TOOLS AND TECI-~.VIQl;TES FOR ADI'ANCIN(, Ot;R Zi,N'DERSrTANDI.IN:G ~3 List et al. (1986) and Rogers arid DeMott (1991) identified the need for a large national laboratory facility to study difficult simulation experiments such as the interactions between particles in the presence of aerosols or gases and electric fields. Suel~ a facility has not yet been created, nor is fleece even any ~neel~anism for long-term planning and funding of laboratory cloud physics research. As a result the number of cloud physics laboratory facilities in the nation has decreased in recent years and there has been little influx of new talent. There is currently no coordinated etfott to address the overall process of precipitation Coronation; rather? individual researchers address parts of the problem as permitted by their existing taeilities. In particular, there appears to be no on:,oi~g investigation of fee or fee interactions, and only limited facilities to study n~ixed- phase processes. There are, of courser constraints on the types of problems that can be addressed through laboratory steadies; thus flee greatest progress can be made when laboratory studies are linlced to theoretical and numerical modeling studies and observational world. D ~ ~ ~ ~ _ ~ _ _ J , FIELD STUDIES Physical concepts, laboratory findings, and n~nerical models must ultimately be tested in the field. Field studies have the unique capability of concentrating analytical and technical tools on a specific problem in a given time and space domain. Progress in understanding the chain of physical processes leading to precipitation or underlying severe weather has isolated key uncertainties, as identified in earlier sections. These uncertainties constitute goals that can be addressed in a hierarchy of field studies. Such studies progress from limited activities that can build on othet at~nospherie field programs to dedicated large-scale weather mo~eat~on experiments. Ordeal uncertainties inherent in the exploitation of atmospheric resources and mitigation of weather hazards (Box 2.2) need to be addressed if larger-scale dedicated weather modification experiments are to make substantial advances. Such field studies must be founded upon testable physical hypotheses and must advance stepwise from the si~nplif~ed to the more complex. It should be noted that scientists at the Mazatlan workshop (discussed in Appendix A) identified a number of specific, testable hypotheses that could form a useful basis for fixture field experiments (WMO, 2000 J. Because many of the roadblocks impeding progress in weather modification are part of the wider research problems facing atmospheric science as a whole, these studies may be pursued on a broad front. Cloud formation, precipitation generation, and the dynamics of severe weather are all of interest to a large number of atmospheric scientists Opportunities thus abound for the pursuit of basic studies of critical concern to weather modification What is lacking is a centralized program to coordinate this research as a national elfin in atmospheric resource enhancement and weather hazard mitigation. Such a program could coordinate modeling? Iaborato~y, and field studies that range from modest "piggyback" experiments to full-blown, dedicated field studies for testing and demonstrating weather modification procedures. These field studies need to be sustained arid would benefit from centralized long- lived facilities. Such centralized and essentially permanent facilities exist at NCAR,

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64 CRITICA L ISSUES IN AREA TlIER AIODIFICA TION RESE-ARCI! NOAA/ETL~ and the U.S. Southern Great Plains CART established on the Oklahoma/Kansas border by the DOE ARM Program. NCAR has a long history of basic and applied research in weather modification with advanced compute and observing facilities designed to serve the atmospheric research community. Similarly, NOAA/ETL has contributed significant funding toward weather modification research efforts in the past. Else CART/ARM site has an extensive array of observing systems detailed in Table 4.1. NASA is planning as part of the GPM to significantly enhance the CART/ARM site. This array of observing systems with its attendant ir~frastructure presents an unprecedented opportunity to pursue fundamental questions facing the weather modification community. While the Oklahoma/Kansas location will not address all problems of weather modification research, fundamental questions involving flee formation of precipitation, the distribution and nature of cloud liquid water and ice in large convective storms, and a host of other more sophisticated experiments, which could involve actual treatment, are among important problems that can be tackled. The combined capabilities at NCAR, NOAA/ETL, and the CART/ARM/GPM site constitute an opportunity that may only require financial and logistical coordination by a central agency to provide a powerful base for weather modification field studies. A number of other operational networks and facilities are available that can advance studies in weather modification; for instance, operational facilities of the National Weather Service (NWS) could be used to conduct comparative, parallel climatological studies in different geographic regions; the national operational Doppler weather radar network (NEXRAD) might be useful in characterizing cloud and precipitation climatologies in neighboring treated and untreated regions in operational weather modification programs; . the Oklahoma Mesonet (Brock et al., 1995) provides l~igh-resolution meteorological data for research, educational, operational' and commercial purposes; and the Automated Surface Observing System? operated by the NWS and the Federal Aviation Administration, is a highly sophisticated surface network that provides high- . ... . .. . . . ~ . . , . . . . . ~ ~ . . quality data routinely at approx1rmately 1,()()~) sites (mostly at alrpo1^ts) across the United States. Ongoing operational programs in weather modification can be improved by the addition of research components. Ultimately, however, major issues of atmospheric resource use and hazard mitigation must be addressed by a sustained research effort. Such a sustained effort ideally rests on an infrastructure of administrative, logistical, numerical, laboratory, and field support coordinated under a single program

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TOOLS AND TECI-I.VIQUES FOR AD VANCIN(.7 OUR l.),N'DERSTANDING TABLE 4.1 ARM/CART Site Instruments 65 Purpose or parameter measured System (if applicable) Instrument Aerosols Aerosol observation n/a system Additional systems Cimel sunphoton~eter Multifilter rotating sl~adowband Radiometer Raman lidar Atmospheric profiling Balloon-borne sounding system Microwave radiometer Radars lidar 50 MHz r adar wind profiler and radio acoustic sounding system MASSE 915 MHz radar wind profiler and RASS Clouds Belfort laser ceilometer Micropulse lidar MilJimeter-wavelength cloud radar Microwave radiometer Video time-lapse camera Whole-sky invader Narrow field-of-view sensor Raman lidar Atmospheric emitted radiance interferometer Absolute solar transmittance interferometer Cimel sunphotometer Infrared thermometer Microwave radiometer Narrow field-of-view sensor Rotating shadowband spectrometer Shortwave spectrometer Solar radiance transmission interferometer Multifilter rotating shadowband radiometer MFR (upwelling) Pyranometers Radiometers MFRSR-related Broad-band instruments Radion~etric instrument systems Pyrgeometers Pyrhe]iometers UV-B radiometer UV spectroradiometer Solar infrared radiation station

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66 CRJ7~(-~,4 L ISSlJES IN IDEA TI-IER AlODIFR-A TIO.V RESEARCI-f Surface energy flux Eddy con elation system Energy balance Bowen ratio station Infrared thermometer Soil waters and temperature system Surface meteorology Chilled mirror Surface meteorological observation system instruments 60-m tower: temperature and humidity sensors Temperature, humidity, wind, and pressure sensors Instruments of Radiometers Solarinfrared radiation station extended facilities of Multifilter rotating shadowband the CART/ARM site radiometer Surface energy flux Eddy correlation systems Energy balance Bowen ratio stations Soil water and temperature system Surface n/a meteor ological observation system instruments Instruments at Balloon-borne sounding system boundary facilities of the CART/ARM site Microwave radiometer Vaisala ceilometer Atmospheric emitted radiance interferometer Temperature, humidity, wind, and pressure sensors Instep uments at 91 5-MHz radar wind pi ofiler intermediate facilities Radio acoustic sounding system of the CART/ARM site