Summary

The goal of weather prediction is to provide information people and organizations can use to reduce weather-related losses and enhance societal benefits, including protection of life and property, public health and safety, and support of economic prosperity and quality of life. In economic terms, the benefit of the investment in public weather forecasts and warnings is substantial: the estimated annualized benefit is about $31.5 billion, compared to the $5.1 billion cost of generating the information (Lazo et al., 2009). Between 1980 and 2009, 96 weather disasters in the United States each caused at least $1 billion in damages, with total losses exceeding $700 billion (NCDC, 2010). Between 1999 and 2008, there were an average of 629 direct weather fatalities per year (NWS, 2010). The annual impacts of adverse weather on the national highway system and roads are staggering: 1.5 million weather-related crashes with 7,400 deaths, more than 700,000 injuries, and $42 billion in economic losses (BTS, 2007). In addition, $4.2 billion is lost each year as a result of weather-related air traffic delays (NOAA, 2010). Weather is also a major factor in the complex set of interactions that determine air quality; more than 60,000 premature deaths each year are attributed to poor air quality (Schwartz and Dockery, 1992).

Better forecasts and warnings are reducing these numbers, but much more can be done. The past 15 years have seen marked progress in observing, understanding, and predicting weather. At the same time, the United States has failed to match or surpass progress in operational numerical weather prediction (NWP) achieved by other nations and failed to realize its prediction potential (UCAR, 2010); as a result, the nation is not mitigating weather impacts to the extent possible.

This report represents a sense of the weather community as guided by the discussions of a Board on Atmospheric Sciences and Climate community workshop held in summer 2009. It is not a comprehensive assessment of the state of U.S. weather research and the transition of research findings



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Summary the goal of weather predcton s to provde nformaton people and organzatons can use to reduce weather-related losses and enhance soc- etal benefits, ncludng protecton of lfe and property, publc health and safety, and support of economc prosperty and qualty of lfe. In economc terms, the benefit of the nvestment n publc weather forecasts and warn- ngs s substantal: the estmated annualzed benefit s about $31.5 bllon, compared to the $5.1 bllon cost of generatng the nformaton (Lazo et al., 2009). Between 1980 and 2009, 96 weather dsasters n the Unted states each caused at least $1 bllon n damages, wth total losses exceedng $700 bllon (ncDc, 2010). Between 1999 and 2008, there were an average of 629 drect weather fataltes per year (nWs, 2010). the annual mpacts of adverse weather on the natonal hghway system and roads are staggerng: 1.5 mllon weather-related crashes wth 7,400 deaths, more than 700,000 njures, and $42 bllon n economc losses (Bts, 2007). In addton, $4.2 bllon s lost each year as a result of weather-related ar traffic delays (noAA, 2010). Weather s also a major factor n the complex set of nterac- tons that determne ar qualty; more than 60,000 premature deaths each year are attrbuted to poor ar qualty (schwartz and Dockery, 1992). Better forecasts and warnngs are reducng these numbers, but much more can be done. the past 15 years have seen marked progress n observ- ng, understandng, and predctng weather. At the same tme, the Unted states has faled to match or surpass progress n operatonal numercal weather predcton (nWP) acheved by other natons and faled to realze ts predcton potental (UcAR, 2010); as a result, the naton s not mtgatng weather mpacts to the extent possble. ths report represents a sense of the weather communty as guded by the dscussons of a Board on Atmospherc scences and clmate commu- nty workshop held n summer 2009. It s not a comprehensve assessment of the state of U.s. weather research and the transton of research findngs 1

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2 2 WHen WeAtHeR MAtteRs and products nto operatons. Further, the report does not seek to address mportant ssues unquely related to clmate research nor does t touch on ntra- and nteragency organzatonal procedures and practces. Instead, the report puts forth the commttee’s judgment on the most pressng hgh- level, weather-focused research challenges and research-to-operatons (R2o) needs, and makes correspondng recommendatons. ths report addresses ssues ncludng observatons, global nonhydrostatc coupled modelng, data assmlaton, probablstc forecastng, and quanttatve precptaton and hydrologc forecastng. the report also dentfies three mportant, emergng ssues—predctons of very hgh mpact (VHI) weather, urban meteorology, and renewable en- ergy development—not recognzed or emphaszed n prevous studes. cut- tng across all of these challenges s a set of socoeconomc ssues, whose mportance and emphass, although ncreasng, has been undervalued and underemphaszed n the past and warrants greater recognton and prorty today. IMPROVE SOCIOECONOMIC RESEARCH AND CAPACITy socoeconomc consderatons are fundamental n determnng how, when, and why weather nformaton s, or s not, used. they are an extremely mportant component of weather research and R2o (and also transfers from operatons to research, o2R). Yet the weather predcton enterprse stll lacks nterdscplnary capacty to understand and address socoeconomc ssues. socoeconomc expertse s underutlzed n the weather communty. there are key gaps n the socoeconomcs of weather that, when filled, wll sub- stantally benefit the weather communty and, more mportantly, socety at large. the commttee dentfied three prorty topcs n the socoeconomcs of weather nformaton requrng attenton: estmatng ts value, understand- ng ts nterpretaton and use, and mprovng communcaton of nformaton. Untl these gaps are filled, the value of the work of the weather communty wll not be realzed n the broader context of advancng weather predcton capabltes for socetal benefit. the commttee’s vson s that by ~2025, a core group of socal scentsts and meteorologsts wll form a strong, mutu- ally benefical partnershp n whch multple areas of scence work together to ensure weather research and forecastng meet socetal needs. Recommendation: The weather community and social scientists should create partnerships to develop a core interdisciplinary capacity for weather-society research and transitioning research to operations, starting with three priority areas:

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sUMMARY 3 • estimating the societal and economic value of weather information; • understanding the interpretation and use of weather information by various audiences; and • applying this knowledge to improve communication, use, and value. to be effectve, the partnershp between the weather communty and socal scentsts should be two-way and balanced, and should n- clude a varety of socal scence perspectves. Members of the weather communty, ncludng research nsttutons, unverstes, ndvdual me- teorologsts, the natonal oceanc and Atmospherc Admnstraton (noAA), the natonal scence Foundaton, and other agences, should pursue multple mechansms for buldng research and R2o capacty n the socoeconomcs of weather, ncludng long-term nterdscplnary programs; grant-funded and drected research, R2o, and applcatons actvtes; ntegrated socal–physcal scence testbeds; msson agency programs to develop capacty; and educatonal ntatves. the requred capacty should be developed and utlzed through partnershps across agences, programs, and dscplnes, and n concert wth academa and the prvate sector. CONTINUE PURSUING ESTABLISHED WEATHER RESEARCH AND TRANSITIONAL NEEDS there are multple research and transtonal goals that have been recog- nzed for some tme as mportant and achevable but have yet to be realzed; moreover, all have sgnficant socetal benefits and needs for nput from socal scentsts. the commttee refers to these as established prortes. Four are dentfied: global nonhydrostatc coupled modelng, quanttatve precp- taton forecastng, hydrologc predcton, and mesoscale observatons. Predictability and the Need for Global Nonhydrostatic Coupled Models Global nonhydrostatc nWP models1 coupled wth ocean and land models are essental as the spatal resoluton of models contnues to n- crease, especally wth grd spacng less than 10 km. Hgh-resoluton nonhy- 1 nonhydrostatc nWP models are atmospherc models n whch the hydrostatc assumpton s not made, so that the vertcal momentum equaton s solved. As model resoluton ncreases, the model grd spacng decreases and the applcablty of the hydrostatc assumpton smlarly decreases.

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4 4 WHen WeAtHeR MAtteRs drostatc models (wth grd spacng around 2 km) remove the dependence of the model on convectve parameterzatons, whch has been a major barrer to progress n weather forecastng. A number of key capabltes reman to be developed for nonhydrostatc coupled models: explctly resolved convecton n global models; advanced assmlaton of convectve-scale observatons that elmnates precptaton spn-up and mproves ntal condtons; mprovements n cloud mcrophys- cs and physcs of the planetary boundary layer (PBL); atmospherc couplng to ocean and land models; and convectve-scale ensemble predcton and post-processng systems. observatons reman nadequate to optmally run and evaluate most hgh-resoluton models and determne forecast sklls at varous temporal and spatal scales. Perhaps even more challengng s the need to develop sutable and effectve verficaton and evaluaton metrcs and methods for determn- ng probablstc forecast skll at dfferent scales. Improved data assmlaton as part of the forecast system s also mportant for acqurng and mantan- ng up-to-date observng systems. Hgh-resoluton and ensemble forecasts requre sgnficant ncreases beyond the natonal centers for envronmental Predcton’s current hgh-performance computng capacty for model predc- tons but also for data assmlaton, post-processng, and vsualzaton of the unprecedented large volumes of data. there s also a pressng need for basc research to more fully understand the nherent predctablty of weather phenomena at dfferent temporal and spatal scales. Because of error growth across all scales, from cumulus con- vecton to mesoscale weather and large-scale crculatons, a hgh-resoluton (preferably cloud-resolvable) nonhydrostatc global model s crucal to ad- dress error growth and better understand the predctablty of global weather systems. Recommendation: Global nonhydrostatic coupled atmosphere–ocean– land models should be developed to meet the increasing demands for improved weather forecasts with extended timescales from hours to weeks. these modelng systems should have the capablty for dfferent configuratons: as a global model wth a unform horzontal resoluton; as a global model wth two-way nteractve finer grds over specfic re- gons; and as a regonal model wth one-way couplng to varous global models. Also requred are mproved atmospherc, oceanc, and land ob- servatons, as well as sgnficantly ncreased computatonal resources to support the development and mplementaton of advanced data assm-

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sUMMARY 5 laton systems such as four-dmensonal varatonal (4DVar), ensemble Kalman filter (enKF), and hybrd 4DVar and enKF approaches. Quantitative Precipitation Forecasting Quanttatve precptaton forecasts (QPFs2) are especally mportant for many socetal ssues but are much less skllful than forecasts of meteorolog- cal state parameters (pressure, temperature, and humdty) and wnds (Frtsch and carbone, 2004). QPF skll, although laggng progress n forecastng other varables, has nonetheless ncreased steadly but slowly over the past 30 years. Forecasts are more skllful at shorter range and lesser cumulatve precptaton amounts, whch occur much more frequently than heavy or extreme events. consderable skll has been acheved n the dynamcal pre- dcton of cool-season orographc precptaton, whch accounts for much of the skll assocated wth the wnter season. Forecast ablty for precptaton assocated wth extratropcal fronts and cyclones s ncreasngly skllful at synoptc scales. However, the least skllful predctons occur under weakly forced con- dtons when local varablty and physcal factors are more lkely to exert nfluence on precptaton occurrence and amount. General crculaton models used for operatonal weather predcton have not represented con- vectve precptaton systems explctly but rather have used parameterza- tons. the lmtatons of cumulus parameterzatons and the subsequent lack of predctve skll (Frtsch and carbone, 2004) have led to the concluson that short-range weather predcton applcatons need to explctly represent deep most convecton n forecast models. Predctng the probable locaton of convectve ranfall events s also dependent upon mprovng ntal and boundary condtons n the forecast models. Wth respect to the lower troposphere, PBL depth and hgh-resolu- ton vertcal profiles of wnd and water vapor are necessary, together wth surface analyses that are skllful n capturng mesoscale varablty on a scale of approxmately 10 km or less. Mesoscale ensemble predcton technques need to be further exploted wth respect to skll n explct predctons of most convecton and accompa- nyng precptaton. ths ncludes trade-offs between the number of members and ther spatal resoluton, and ssues related to member generaton and 2 QPF refers to forecasts of precptaton that are quanttatve (e.g., mllmeters of ran, cent- meters of snow) rather than qualtatve (e.g. lght ran, flurres), ndcatng the type and amount of precptaton that wll fall at a gven locaton durng a partcular tme perod.

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6 6 WHen WeAtHeR MAtteRs selecton. ensemble predctons hold promse to mtgate and quantfy fore- cast uncertanty, especally wth respect to the detaled tme and locaton of specfic events for whch the ntrnsc lmts of predctablty are uncertan. Recommendation: To improve the skill of quantitative precipitation forecasts, the forecast process of the National Weather Service should explicitly represent deep convection in all weather forecast models and employ increasingly sophisticated probabilistic prediction techniques. Global and regonal weather forecast models should represent or- ganzed deep convecton explctly to the maxmum extent possble, even at resolutons somewhat coarser than 5 km, as may be necessary ntally, n the case of global models. explct representaton should markedly mprove forecast skll assocated wth the largest and hghest mpact precptaton events. the ntroducton of explct convecton wll lkely requre the refinement of mcrophyscal parameterzatons, boundary-layer and surface representatons and other model physcs, whch are, n themselves, formdable challenges. Probablstc predcton should be vgorously pursued through re- search and the development and use of ncreasngly sophstcated en- semble technques at all scales. new tools need to be developed for verficaton of probablstc, hgh-resoluton ensemble model forecasts, eventually supplantng equtable threat scores. Hydrologic Prediction An advanced hydrologc modelng system requres the ablty to translate precptaton forecasts nto smlarly accurate, dstrbuted runoff and stream- flow predctons by nvokng the physcal mechansms of runoff generaton, snow accumulaton, surface-groundwater exchanges, rver and floodplan routng, rver hydraulc routng, and agrcultural and other consumptve uses. these elements of an advanced hydrologc predcton system are far from beng well observed, far from beng well understood, far from beng approprately represented n numercal predcton models, and far from beng even rudmentarly verfied. Major changes n hydrologc research and nfrastructure are needed to meet the pressng socetal and economc demands of flood protecton and water avalablty. In the meteorologcal and atmospherc scences communty, advances n nWP and clmate modelng have been enabled to a large degree by the development of communty-supported and -developed models. In the hydro- logc communty, no equvalent effort exsts. Development of a robust hydro-

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sUMMARY 7 logc forecast capacty wll requre a strategc commtment to a systematc hydrologc predcton framework effort that brngs together (1) the collectve resources of the hydrologc communty n establshng a unfied hydrologc observatonal, research, and modelng agenda; (2) the atmospherc and hy- drologc communtes n developng, testng, and mprovng a fully coupled atmospherc–hydrologc predcton system; and (3) the research and opera- tons communtes to jontly dentfy research prortes that fill mportant gaps n the applcaton of hydrologc products by government agences and the prvate sector. A verfied dstrbuted model s certan to accelerate both R2o and o2R transtons and serve other user communtes. Recommendation: Improving hydrologic forecast skill should be made a national priority. Building on lessons learned, a community-based coupled atmospheric–hydrologic modeling framework should be sup- ported to accelerate fundamental understanding of water cycle dy- namics; deliver accurate predictions of floods, droughts, and water availability at local and regional scales; and provide a much needed benchmark for measuring progress. to successfully translate the nvestment n mproved weather and clmate forecasts nto mproved hydrologc forecasts at local and re- gonal scales, and meet the pressng socetal, economc, and envron- mental demands of water avalablty (floods, droughts, and adequate water supply for people, agrculture, and ecosystems), an accelerated hydrologc research and R2o strategy s needed. Fundamental research s requred on the physcal representaton of water cycle dynamcs from the atmosphere to the subsurface, probablstc predcton and uncer- tanty estmaton, assmlaton of multsensor observatons, and model verficaton over a range of scales. Integral to ths research are ntegrated observatores (from the atmosphere to the land and to the subsurface) across multple scales and hydrologc regmes. Mesoscale Observational Needs Improved observng capabltes at the mesoscale3 are an explct aspect of every weather prorty dentfied n ths study, ncludng socoeconomc 3 the Glossary of Meteorology (Glckman, 2000) defines mesoscale as “Pertanng to atmo- spherc phenomena havng horzontal scales rangng from a few to several hundred klometers, ncludng thunderstorms, squall lnes, fronts, precptaton bands n tropcal and extratropcal cyclones, and topographcally generated weather systems such as mountan waves and sea and land breezes.”

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8 8 WHen WeAtHeR MAtteRs prortes such as reducton n vulnerablty for dense coastal populatons, and mprovements n forecasts at the scale of flash floods and routnely dsruptve local weather. observatons at the mesoscale are ncreasngly mportant to establshng ntal condtons for global models as resoluton mproves. these nclude observatons that ether resolve mesoscale atmospherc structure or unquely enable mesoscale nWP. the emphass on mesoscale observatons s motvated by the scale and phenomenology assocated wth dsruptve weather; the necessty to understand t, detect t, and warn of the potental consequences; and mproved capacty to specfically predct or otherwse antcpate t at very short to short ranges (0 to 48 hours). A natonal mesoscale observng network s needed for a wde varety of stakeholders nclusve of basc and appled researchers, ntermedate users assocated wth weather–clmate nformaton provders, and a wde varety of end users at all levels of government and numerous commercal sectors. satellte observatons are expected to assume a prmary role at alttudes above the contnental PBL. there s a pressng need for research and development leadng to mproved mesoscale data assmlaton technques n operatonal forecast systems. Improved analyses requre better knowledge of systematc errors n observatons, especally because mesoscale data are often sparse or patchy, and relatvely poorly documented compared to those from standard synoptc observatons. the structure and varablty of the lower troposphere s not well known because vertcal profiles of water vapor, temperature, and wnds are not systematcally observed at the mesoscale (schlatter et al., 2005). the senstvty to these observaton gaps s not well understood but s lkely substantal n urban (Dabberdt et al., 2000) and coastal (Droegemeer et al., 2000) regons where populaton densty s hgh and n mountanous regons, whch are a proxmate cause for major forecast errors downstream (smth et al., 1997). the relatve absence of hgh-resoluton PBL profiles mpedes progress n skllful predctons at the mesoscale over both land and coastal waters. Mesoscale predctablty s dependent, to some consderable degree, on mesoscale ntal condtons. ths s especally true wth respect to specfic predctons of deep most convecton and attendant heavy ranfall and severe weather (Frtsch and carbone, 2004). Mesoscale observatons need to be a focus of testbeds ntended to de- velop and ntroduce new paradgms n envronmental observaton. ths s partcularly mportant and urgent wth respect to fully ntegratng methods n nowcastng wth dynamcal predcton n the 0- to 6-hour range, thereby mprovng performance n severe weather, hydrologc forecasts, and rou- tnely dsruptve weather.

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sUMMARY 9 Recommendation: Federal agencies and their partners should deploy a national network of profiling devices for mesoscale weather and chemical weather prediction purposes. Such devices should incorpo- rate capabilities that extend from the subsurface to 2–3 km above the surface level. The entire system of observations in support of mesoscale predictions should be coordinated, developed, and evaluated through test-bed mechanisms. As a hgh nfrastructure prorty, optcal and rado-frequency profil- ers should be deployed natonally at approxmately 400 stes to con- tnually montor lower tropospherc meteorologcal condtons. to meet natonal needs n support of chemcal weather forecasts, a core set of atmospherc pollutant composton profiles should be obtaned at approxmately 200 urban and rural stes. to meet natonal needs for representatve land–atmosphere latent and sensble heat flux data, a natonal, real-tme network of sol mosture and temperature profile measurements should be made to a nomnal depth of 2 m and deployed natonwde at approxmately 3,000 stes. Federal agences, together wth state, prvate-sector, and nongov- ernmental organzatons, should employ mesoscale testbeds for appled research and development to evaluate and ntegrate natonal mesoscale observng systems, networks thereof, and attendant data assmlaton systems as part of a natonal 3D network of networks. INCREASE ATTENTION TO EMERGING WEATHER RESEARCH AND TRANSITIONAL NEEDS several research and R2o needs have come to be recognzed over the past 5 to 10 years as ncreasngly mportant, yet reman n the early stages of understandng or mplementaton. these are denoted as emerging weather research and transtonal needs, n contrast to establshed needs. three hgh- prorty emergng needs are dentfied: VHI weather, urban meteorology, and renewable energy development. Very High Impact Weather VHI weather s defined here as weather that endangers publc health and safety or causes sgnficant economc mpacts, ncludng 1. evere and dsruptve weather hazards that change rapdly on the s tmescale of mnutes to hours or a few days, and

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10 10 WHen WeAtHeR MAtteRs 2. persstent weather hazards that occur on longer tmescales of days to weeks or even years (e.g., drought). Advancng the understandng, montorng, and predcton of VHI phe- nomena and mpacts requres mprovng the accuracy and tmelness of ob- servatons, forecasts, and warnngs n order to develop an efficent response system that helps mnmze and mtgate hazardous weather mpacts. A new paradgm for the comng decades s the expanson n emphass from weather predcton alone to the predcton of weather and related mpacts. ths expanson necesstates development of new modelng and observatonal tools, nnovatve forecast gudance products, and methods of nformaton and warnng dssemnaton. ths shft also demands full ntegra- ton of the physcal and socoeconomc scences. one major challenge for such an expanson s to explot ensemble modelng more fully to produce quanttatve probablstc forecasts of at- mospherc quanttes wth estmates of uncertanty, and for these to then be used to generate probablstc forecasts of the mpacts and rsks of pendng VHI weather stuatons, thereby enablng mproved decson makng. teams of physcal scentsts, socal scentsts, and professonals from user groups wll need to work together to define the needed observatons and mpact parameters. Recommendation: The federal agencies and their state and local gov- ernment partners, along with private-sector partners, should place high priority on providing not only improved weather forecasts but also explicit impact forecasts. An effective integrated weather im- pacts prediction system should utilize high-quality and high-resolution meteorological analysis and forecast information as part of coupled prediction systems for VHI weather situations. ths wll requre • fundamental research n both the physcal and socal scences to mprove understandng and predcton of VHI weather phenomena, and the provson of warnngs and rsk assessments n support of dec- son makng; • development of mpact parameters and representatons for mul- tple applcatons (e.g., morbdty, electrc grd vulnerablty, storm surge and flood nundaton areas); • research to determne and obtan crtcal and tmely observatons; • end-to-end partcpaton by multple sectors and dscplnes (n- cludng modelers, observatonalsts, forecasters, socal scentsts, and

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sUMMARY 11 end users) to jontly desgn and mplement mpact-forecastng systems; and • multdscplnary undergraduate and graduate programs that can address the emergng field of VHI weather–mpacts predcton, rsk as- sessment and management, and communcaton through fully ntegrated research, educaton, and tranng for the new generaton of scentsts, forecasters, emergency managers, and decson makers. Urban Meteorology Urbanzaton of the world’s populaton has gven rse to more than 450 ctes around the world wth populatons n excess of 1 mllon and more than 25 so-called megactes wth populatons over 10 mllon (Brnkhoff, 2010). the Unted states today has a total resdent populaton of more than 308,500,000,4 wth 81 percent resdng n ctes and suburbs as of md-2005 (Un, 2008). Urban meteorology s the study of the physcs, dynamcs, and chem- stry of the nteractons of earth’s atmosphere and the urban bult envron- ment, and the provson of meteorologcal servces to the populatons and nsttutons of metropoltan areas. Although the detals of such servces are dependent on the locaton and the synoptc clmatology of each cty, there are common themes, such as enhancng qualty of lfe and respondng to emergences. experence elsewhere (e.g., shangha, Helsnk) shows urban meteorologcal support s a key part of an ntegrated or multhazard warn- ng system that consders the full range of envronmental challenges and provdes a unfied response from muncpal leaders. A natonal ntatve to enhance urban meteorologcal servces s a hgh- prorty need for a wde varety of stakeholders, ncludng the general publc, commerce and ndustry, and all levels of government. some of the actvtes of such an ntatve nclude conductng basc research and development; proto- typng and other R2o actvtes to enable very short- and short-range predc- tons; supportng and mprovng productvty and efficency n commercal and ndustral sectors; and urban plannng for long-term sustanablty. Urban testbeds are an effectve means for developng, testng, and fos- terng the necessary basc and appled meteorologcal and socoeconomc research, and transtonng research findngs to operatons. An extended, multyear perod of contnuous effort, punctuated wth ntensve observng and forecastng perods, s envsoned. Recommendation: The federal government, led by the National Oce- anic and Atmospheric Administration, in concert with multiple public 4 ee http://www.census.gov/man/www/popclock.html. s

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12 12 WHen WeAtHeR MAtteRs and private partners, should identify the resources needed to provide meteorological services that focus on where people live, beginning with a high-priority urban meteorology initiative to create infrastruc- ture, products, and services tailored to the special needs of cities. Although noAA should be the lead agency n such an ntatve, ts success wll requre effectve partnershps wth other federal, state, and local government agences, academa, and the prvate sector, as well as wth all sectors of the user communty, both publc and prvate. Under the leadershp of noAA, a consortum of natonal and local partners should establsh a small number of urban testbeds for the purpose of determnng urban user needs for talored meteorologcal nformaton and then developng, testng, and evaluatng varous observng, model- ng, and communcaton strateges for provdng those end users wth an effectve sute of socetally relevant and cost-effectve products and servces to meet those needs. the goal of such testbeds would be to con- duct or foster the necessary basc and appled research and then trans- ton the research findngs together wth the practcal lessons learned nto operatons, and to extend these capabltes, approprately scaled, to ctes across the naton. Renewable Energy Development the producton of energy from renewable sources—hydro, bomass, geothermal, muncpal waste, wnd, and solar—s an ntegral part of the challenge to reduce relance on fossl fuels, acheve a meanngful measure of energy ndependence, and mnmze anthropogenc clmate change. elec- trcty generaton from renewable resources represents a small yet rapdly growng fracton that s projected to produce 14 percent of total domestc generaton n 2030. However, there are sgnficant weather dependences and uncertantes that challenge the use of renewable energes—especally wnd and solar—n a producton and dstrbuton system that must provde stable and relable electrc power where and when t s needed. there are a host of weather-related research and operatonal challenges that wll need to be met to provde relable and predctable wnd power. these challenges pertan to wnd turbne desgn and operaton, wnd en- ergy exploraton, wnd plant stng and desgn, wnd ntegraton, and the effects of a changng clmate. Lke so many other weather research and R2o prortes, those pertanng to wnd energy nvolve both observatons and modelng and nclude

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sUMMARY 13 • Exploration: Assessng the wnd energy resource requres observa- tons to quantfy the dstrbuton of wnd speed as a functon of locaton, tme, and heght. • Wind turbine design: Because of ther large span, wnd turbnes are ex- posed to varable atmospherc stresses, whch place demands on ther desgn that requre detaled knowledge of mean and turbulent flow condtons. • Wind plant architecture: the desgn of wnd parks and ther power generatng efficency heavly depend on wake nteractons and nterferences among neghborng turbnes, and the effects of local topography. • Operations: Wnd forecasts on the 6- to 48-hour tmescale are m- portant for projectng wnd energy producton, but wnd park operatons are also susceptble to “wnd ramp” events—abrupt, major changes n wnd speed. Managng wnd power ntegraton on the 30-mnute to 6-hour tme- scale requres accurate very short range nWP and nowcasts. the current state of mesoscale observatons s nadequate to support the hgh-resoluton modelng needs of the wnd energy ndustry. Meteorologcal observatons—prmarly wnd and turbulence, but also temperature—are requred to ad n wnd park assessment, stng, and desgn and to assess the performance of ndvdual wnd turbnes. Because of the sgnficant vertcal extent of large wnd turbnes and the effects of wnd shear and turbulence, t s essental to have detaled wnd structure nformaton up to heghts of ~0.5 km above ground level. A herarchy of models, each smulatng a cascade of spatal scales, s requred to address varous wnd-dependent aspects of wnd turbne and wnd park desgn and operaton, ncludng computatonal flud dynamcs models; very hgh resoluton atmospherc (ncludng large-eddy smulaton) models; hgh-resoluton mesoscale models, and nowcastng methods. solar energy systems produce electrcty, drectly or ndrectly, from ambent sunlght. Lke wnd, the avalablty of solar power s also hghly varable n space and tme. Developers of large solar plants and utltes usng dstrbuted photovoltac systems have common needs for relable ob- servatons of solar radaton, hstorcal and real-tme databases, and accurate forecasts on a varety of scales. exstng hstorcal, natonal databases are based on n stu measurements from a few tens of surface-based radometers together wth satellte cloud magery and analytcal nterpolaton algorthms. However, the accuracy of the hourly estmates of surface solar rradance from satellte magery s nadequate (only ±20 percent), and the spatal database resoluton of ≥10 km does not meet many users’ needs for 1-km data.

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14 14 WHen WeAtHeR MAtteRs Utlty operators requre hstorcal data and solar resource forecasts on several tmescales: ≤3 hours for “dspatchng” to enable a steady power supply to the grd; 24 to 72 hours for system operatons plannng; and sea- sonal to nterannual forecastng for economc analyses and system plannng. there s currently no exstng operatonal solar forecastng capablty that meets user needs. these needs nclude hghly resolved (15 mnutes and sometmes less) short-range forecasts that, n turn, requre more ste-specfic n stu downwellng solar and nfrared radaton measurements, mproved satellte estmates, better extrapolaton methods, and relable, operatonal solar forecastng not avalable today. Improved observatons, smulatons, and predctons of wnd and tur- bulence, and solar radaton, are needed wth hgh spatal and temporal resoluton and accuracy to optmally locate, desgn, and operate wnd and solar energy facltes. these efforts wll requre a focused, hgh-prorty natonal research and R2o program that s carefully and closely ntegrated wth the mesoscale observng and predctng ntatves and socoeconomc actons recommended throughout ths report. to be successful, these efforts wll requre effectve collaboratons and partnershps among power system desgners, operators, grd managers, observatonalsts, researchers, forecast- ers, and modelers. Recommendation: The effective design and operation of wind and so- lar renewable energy production facilities requires the development, evaluation, and implementation of improved and new atmospheric observing and modeling capabilities, and the decision support sys- tems they enable. The federal agencies should prioritize and enhance their development and support of the relevant observing and mod- eling methods, and facilitate their transfer to the private sector for implementation. CONCLUSION An actve dalogue s needed among stakeholders representng a wde range of dscplnes and organzatons. one approach that has been effectve n the past s for the federal agences to ntate and lead such a dalogue through a communty “weather summt” that brngs the partes together to dentfy prortes and define specfic actons to establsh a cohesve ap- proach to the plannng of weather research and R2o. As our naton’s weather challenges have changed, so must our scentfic research and operatonal prortes change. the varous socoeconomc,

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sUMMARY 15 establshed, and emergng ssues dentfied n ths report requre ncreased attenton. ths nvolves undertakng the needed research and transferrng the mportant research results nto operatons. the communty also needs to establsh and nurture effectve partnershps among government, academa, and ndustry. As such, ths report and ts recommendatons are relevant to all partes n the weather enterprse: agency decson makers, polcy makers, research scentsts, prvate-sector applcatons specalsts, teachers, publc and prvate user groups and organzatons, and the general publc.

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