Yuliya I. Troitskaya 1 values of the drag coefficient drag the of values t May from out (carried experiments field of series Russian FederationRussian 2 KuznetsovaAlexandraM. DOI: 10.15356/2071-9388_02v09_2016_02 Alexander A. KandaurovA. Alexander wind and wave prediction is discussed.is prediction wave and wind fu for need WRF.from The forcing wind heterogeneous WAVEWATCH III. Homogeneous wind forcing from the data experimental was compared with wind the using incorporated was .It Gorky considera for called directions and speeds wind the middle- a for forecasts wave correct the receive to WRF experiments are presented in [Atakturk and [Atakturk in presented are experiments these of examples Rare the data. of experimental lack the of because relevant also is km) 10–100 of size linear a (with The study of the wave regime of middle-sized areas.adjacent microclimatedefine the of overreservoir the momentum and heat and moisture exchange of inland safety navigation. the In addition, the processes determines of prediction wave correct A reservoirs. of banks the of erosion of source major a arewater the on wavesall, of First importance. practical and scientific both has reservoirs middle-sized in wave regime the of prediction the and study The The obtained parameterization of parameterization obtained The its than lower % 50 approximately are winds strong * Federation,Novgorod,RussianNizhny 603950, ABSTRACT. KEY WORDS: KEY INTRODUCTION ON THE GORKY RESERVOIR GORKY THE ON REGIME WINDWWAVE THE OF STUDY NUMERICAL AND FIELD State University, 23 Gagarina av, 60 Gagarina University,NovgorodState 23 Nizhny AcademyRussian the of PhysicsApplied of Institute Correspondingauthor

The paper describes the study of wind-wave regime a regime wind-wave of study the describes paper The reservoir, field experiment, simulation, wind-wave interaction, WAVEWATCH interaction, wind-wave simulation, experiment, III, field reservoir, 1, 2 1, ; e-mail: [email protected] e-mail: ; 1,2 1,2 C , Maxim I. I. Vdovin Maxim , D *, Georgy A. Baydakov A. Georgy *,

for a middle-sized reservoir in the range of moderate and moderate of range the in reservoir middle-sized a for C D

was implemented in the wave model WAVEWATCHmodel wave III the in implemented was and in [Sutyrina, 2011], the wave regime on regime wave the 2011], [Sutyrina, in and formulas, empirical the on based reservoirs Ivankovo and the in waves the surface of description a numerical is the for there block 2002] Sukhova, [Poddubnyi, in is based on the empirical models: for example, the of waves on description the middle-sized lakes numerical and reservoirs the Usually, forecasts.wave quality that should be taken into account in the high- of the wave regime of middle-sized reservoirs characteristics specific of number a consider the of to need the demonstrated experiments field results The Reservoir. Gorky the on experiments field carried the out of by ourseries research a groupdescribe we paper this In 2008]. Makin, and Babanin 1999; Katsaros, o October in 2012–2015) showed that the that showed 2012–2015) in October o 1,2 tion of wind field heterogeneity over the over heterogeneity field wind of tion forcing from atmospheric model WRF to model WRF atmospheric fromforcing sized reservoir. Statistical distribution of of distribution Statistical reservoir. sized values typical of the ocean conditions. ocean the of typical values , Daniil A. SergeevA. Daniil , rther improvement of the quality of quality the of improvement rther of Sciences, 46 Ulyanov st., Ulyanov 46 Sciences, of 1,2 3950, Nizhny Novgorod,Nizhny 3950, , Vladislav V.Papko t the Gorky reservoir. A A reservoir. Gorky the t 1,2 , 1 ,

19 GEOGRAPHY 20 GEOGRAPHY the tuning of the model is required. The The required. is model the of tuning the reservoir, middle-sized the of conditions the to application WAVEWATCH the III for Thus, versions.model current largest number of interactions available in the the considers model this because reservoirs, middle-sized on waves surface of simulation We 2013]. the for model WAVEWATCH chosen III [Hesser, have obtained were body water middle-sized a in waves surface the predict WAMof to use the of results first the Recently, waves 2004]. al., et [Lopatoukhin hindcast and wind for Ladoga Lake Caspian and the Sea to successfully applied were addition, 2011]. In WAVEWATCHal., et III and SWAN [Alves USA the in Lakes Great the on III was successfully used for the wave forecasts used successfully on large lakes. WAVEWATCH were models waveHowever, conditions.the ocean the to adapted are models numerical third-generation the that noted be should It interactions.wave-wave triad bottomfriction,depth-induced breakingand the of influence the account into take also and in the case of shallow water, some of them dissipation,nonlinear wave-wave interactions, wind-waveinteractions,of impact the under describethe evolution of a2D wave spectrum spectralshapes or energy levels. Thesemodels physicalprocesses explicitly, without all imposing parameterize 2006]) team, [SWANSWAN III [Tolman et al., 2014], WAM [GunterModern etthird-generation al., processes. physical1992 of models effects infer (WAVEWATCH to levels spectralshapes andsustained spectral energy second-generationand models first- use observed Outdated processes). (physical terms are classified by their treatment of the source spectra action balance equation. The models of solution numerical the on based are They models. forecast wave numerical modern meteorology. Therefore, it to is use necessary operational forthe important highly are that conditions wave extreme the of prediction averaged the characteristics, which can on not be used for the based are relationships relationships. empirical the empirical the But using studied also was reservoir Bratsk the GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. ], surface area is 1591 km 1591 is area surface water The km. 26 is width maximal its and dam, station hydroelectricNovgorod Nizhny it the to dam Rybinsk level, the from km water 430 spans normal the At River. the on Gorodets of town the near station hydroelectric Novgorod Nizhny the of dam of the reservoir Gorky which is formed by the waters the in 2012–2015 in October to May from out carried were measurements Field reservoirs. from WRF to WAVEWATCH III forcingfor middle-sized wind the of use the presents paper was realized, for example, in [Alves, 2014]. This forcingcharacterization wind the of method This (WRF). Forecasting & Research Weather model atmospheric example, for resolution, spatial high of models atmospheric use to possible is it Totask. it, challenging solve a is variability spatial high the of Consideration of experiment. source numerical the in errors possible a is temporal assumption This consider variability. that experimental measurements the from obtained was and data, experimental sufficient the of lack the to due reservoir the of area entire the over homogeneous be to assumed was speed wind the b], a, al.,2016 et [Kuznetsova works the ways to set in the wind forcing. implemented study Into used was a] 2016 al., theet [Kuznetsova tuning previous the work, this In a].2016 al., et [Kuznetsova in implemented was tuning the of step first The unchanged. remains breaking wave The to due waves. dissipation steeper by caused is linearity non- stronger a as well as intense, 2014] more al., is et [Tolman velocity wave phase the to speed) wind m 10 (or velocity friction the of relation the to proportional is which input, wind the reservoir: middle-sized a of specific the fetches by small at waves the of characteristics caused is adjusting This integral.” “collision the of adjusting the and term source input wind the of adjusting the steps: two in out carried be should tuning AT THE GORKY RESERVOIR GORKY AT THE EXPERIMENT FIELD THE OF METHODS 02 (09) 2016 (09) 02 2 , the total volume volume total the , the bank is high and steep.and high is bank the dam, station hydroelectricNovgorod Nizhny the to Chkalovsk of city the from extending but near the Sokolskoye village and ineverywhere; the almost area flat and low is bank left steep. sometimes The and high is bank right Throughoutthereservoir,ofthelakepart the on the season and the point of measurement. study area, it varies from 9 to 12 m depending ship channel varies from 4.5 to 20 m, and the in the near only city, and it is km, 3 km. 14 The depths to of the 5 main from varies reservoir the of part this of width The dam. totheNizhny Novgorod hydroelectric station lakearea fromis97 km the Elnat River mouth part of the lake area of the reservoir (Fig. 1). Th Measurements were carried out in the southernthreeriver,sections– lake.riverlake, andand into divided is reservoirnavigability, theand 0.6 km the useful volume of the navigational prism is is 8.8 km8.8 is Volzhskaya stations: weather the show circles white Zo b) data); Earth (Google reservoir Gorky The a) 1. Fig. AlexandraM. Kuznetsova FIELD AND N et al. 3 . According to the hydrological regime 3 , the useful volume is 2.8 km2.8 is volume useful the , 3 , and , e (VGMO) and Yurievets. and (VGMO) UMERICALSTUDY OF THE WIND-WAVEREGIME... reservoir and, consequently, it is necessary necessary is it consequently, and, reservoir spatial inhomogeneity of the wind above the significant shows stations weather from two the obtained distributions the between difference The intervals. same the at station the Yurievetsweather at measured direction and speed wind of distribution the shows the over 2b Fig.higher. times two to up speed is area water wind the area: water the over those from different very are shore the at velocity wind the of values the and level) high bank (about 15 meters above the water different fetches. Volzhskaya is located on the of waves and wind studying allows reservoir the of shape elongated The wide. rather is directions possible of range the direction, 2010–2015. Despite the notable31), October selected – wind 10 (May period navigational The distribution was based on the data for the station (Gorodets) close to the field study area. and direction measured at Volzhskaya weather speed wind of distribution the shows Fig.2a om view of the measurements area. Red dots in in dots Red area. measurements the of view om

21 GEOGRAPHY 22 GEOGRAPHY GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. from a vessel (Fig. 3 a) using the author's author's the using a) 3 (Fig. vessel a from water the column. The measurements in were carried out and 2014]) al., et [Bogatov in measurements similar (see characteristics well as the measurement similar of turbulent air flow (see as 2011]), et al., profile temperature, in [Bakhanov measurements velocity air current and and water waves, of surface profiles profile, velocity wind the of measurements include studies field The or prediction waves.and wind of parameters statistical accurate the determine to order in reservoir the of points different at characteristics wave and wind measure to May (from period navigational 2010–2015the over during ( directions wind the of distribution Statistical 2. Fig. top graphs) and wind speeds (low graphs) averaged averaged graphs) (low speeds wind and graphs) top in the water and held in a vertical position by The buoy represents a mast semi-submerged located. were 2015]) al., 2014]), et [Ivanov in results al., (see CTD-probe et and (Gill [Bogatov Hz) (see 50 is Instruments) rate wind (sample HS-50 three-gauge high-speed a ultrasonic 2011], al., frequency et ADCP [Bakhanov in velocity that used to similar current Instruments), RD the (Teledyne of ultrasonic an profiler vessel, the of board the On station. buoy Froude oceanographic the on based c) b, 3 (Fig. station buoy original 10 to October 31): a) Volzhskaya, b) Yurievets.b)31): Volzhskaya, a) October 10 to 02 (09) 2016 (09) 02 an equilateralan triangle with a side of 62 mm, of theresistive pairs wire sensors, three located of at the vertices consists of gauge wave The accuracy.measurement % 3 a and °C 0.01 of resolution with temperature environmental the measure sensors temperature Resistive conditions. calm in measurements includes range of wind speed measurements 0–60 m/s and accuracy velocity resolution of 0.01 measurement m/s. Operating % 4 a with sensor ultrasonic two-component a is WindSonic spectra. space-time waves the string wave gauges, which allowedwatertemperature sensor,usthree-channeland to retrieve sensor (at heights of 0.1 m [float], 0.85 m, Thebuoy1.3also wasequipped surface. m) withtemperatureair water the from cm 10 is zone m, and the height ofThe thedistance wind from speed the floatmeasurement tospeed the inbuoy’s the closemast proximityis 1 to trackingthe thewaveform water forsurface. measuring thewind 5.26 m. m, The 2.27 fifth m sensor 1.3 was m, located 0.85 of on heights the float at located were Instruments) (Gill WindSonic sensors of25 m. On the buoy’s mast, 4 ultrasonic speed 0.25isHz, which corresponds wavelengthtoa resonantThe frequencyvertical ofoscillations m, 12 is mast the length ofthe theof topsidelength total The isc). b,5.3 3 m.(Fig. depth a at load the by and surface the near float the buoy. Froude the of op the of View b) reservoir. Gorky the on Vessel a) 3. Fig. AlexandraM. Kuznetsova FIELD AND N et al. , UMERICALSTUDY OF THE WIND-WAVEREGIME... conditions of inland waters. inland of conditions the in regime wind-wave of features show and Katsaros, [Atakturk 1999; Babanin in and Makin, 2008] obtained results the example, For conditions. these different in regime expect wind-wave to fair is it therefore and banks), the by wind of shielding and waves, of steep in resulting those fetches (small from ocean the different bodies water substantially are middle-sized and small of conditions the However, winds. under hurricane interaction wind-wave the to paid is attention great the currently and ocean, open the in winds moderate and weak for flow from the wind to the waves. The The waves. the to wind dependence the from momentum flow the defines which 2012]), al., of the drag coefficient on the wind speed C speed wind the on coefficient drag dependence the of the of determination the to The particular attention in the study was paid 1996]).al., et [Donelan in described is transform wavelet the uses [Troitskaya et al., 2012] (a similarFourier algorithmtransformdescribed isdetailand inin whic thesignals received fromthedevices usesthe ( exceeds the double distanceestimating between parameters the sensorsof the wave,datasampling whichrate is length100 Hz. Thesystem allows k D max erating state of the Froude buoy. c) Schematics Schematics c) buoy. Froude the of state erating ( U

10 ≈ 0,5 ) (see, for example, [Troitskaya et et [Troitskaya example, for (see, ) –1 ). The algorithm of the processing of C D ( U 10 ) is rather well studied studied well rather is ) h

23 GEOGRAPHY 24 GEOGRAPHY Babanin and Makin, 2008; Fairall et al., 2003] al., et Fairall 2008; Makin, and Babanin 1999; Katsaros, and [Atakturk of results the the retrieved relationships relationships retrieved the of comparison the shows 5a Fig. analyzed. is profile resulting speed wind the the of on approximation horizons different data the from of impact the and b], 2016 al., et wind speeds observed the of direction the so seas, heavy in out the carried be not experiment, could measurements field the for used vessel the of size small the to Due direction. its by also but speed, wind by only greatly not influenced is height wave significant the that noted be should It measurement. of point the in a) (Fig.4 speeds wind of range wide a in experiments 44 included study field The peaks C coefficient drag of value The a]). 2016 al., [Kuznetsova et (see waveforms the sensor tracking speed mobile lower a of use the is and Katsaros, 1999; Babanin[Ataturk and (see Makin, 2008]) studies similar the from apart study this sets which feature important An GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. waves heights measured the of distribution the on impact significant a has stipulation This north. not is The values The [Fairall parameterization oceanic al.,et 2003]. and [Atakturk Katsaros, in 1999; Babanin and Makin, 2008], presented and results the as well as it, without and sensor lower the of use the with sensors: speed of combinations RESULTS OF THE FIELD EXPERIMENT FIELD THE OF RESULTS D is determined by profiling [Kuznetsova [Kuznetsova profiling by determined is f p

(Fig.c).4 Fig. 4. The statistical distribution of the values measu values the of distribution statistical The 4. Fig. C U D ( 10 H U S with values more than 8 m/s 10 (Fig. 4 b) and of the spectral ) are higher and closer to closer and higher are ) a) wind speed, b) significant wave height, c) peak frequenc peak c) height, wave b)significant speed, wind a) C D ( U 10 ) for two two for ) determine the accuracy of the measured measured dependence the of accuracy the determine To measurement. the of results the affects significantly only, sensors lower two the of the that use the particular sensor,in lower the of use demonstrated been has it Thus, boundary. at the water-air exactly the waves to wind the from transfer determine momentum the flow air the of parameters wherein the waves, surface the of conditions changing the to of adapts part quickly profile lower the the as wind, nonstationary the to as well as layer surface the atmospheric of stratification the to due probably difference is This one. logarithmic the from shape the profile speed by wind the of interpreted deviation be can results These winds. weak of range the in winds of retrieving the in differences significant demonstrates only only or all five sensors. The use of two sensors lower values of the drag coefficient. coefficient. drag dependencies the retrieved the of of comparison a shows 5b Fig. values lower demonstrates sensor lower the of use the while sensor lower the of use the without this, the experimental data were fitted fitted were data function:the (Fig.with 5b) experimental the do To in this, III. WAVEWATCH waves of wind framework the of simulation numerical + + .03 .009. 0.000049 0.00034 U C D + = 0.00124 red during the experiment: the during red C C D D ( ( 10 U − U 02 (09) 2016 (09) 02 1 10 10 y . U ), it was used in the the in used was it ), ) with either ) two lower with either 10 (1) AlexandraM. Kuznetsova FIELD AND N et al. UMERICALSTUDY OF THE WIND-WAVEREGIME...

C U Fig. 5. Comparison of the retrieved dependences D( 10 ): a) with and without the lower sensor: black diamondsdenote the binning of data with the lower sensor (withthe standard deviation as the error gates), redd soli circles denote the binning of the data without the lower sensorwith ( the standard deviation as the error gates),ay gr circles are the results of the field experiment [Babanin and Makin, 2008], gray crossesare the results of the field experiment [Atakturknd a Katsaros, 1999], dashed line is the empiric ocean parameterization COARE 3.0; b) using two andve sensors: fi red solid circles are the binning of five-sensors the data (with the standard deviation as error the gates), blue diamonds are the binning of the two-sensors datawith ( the standard deviation as the error gates,d soli line is an approximation of the obtained data by a function –1 CD = 0,00124·U 10 + 0,00034 + 0,000049·U10 , dashed line is the WAM 3 parameterization [Wu, 1982].

25 GEOGRAPHY 26 GEOGRAPHY with dimensions 72dimensions with reservoir Gorky the of grid topographic the description, reservoir the for then, adjusted; as ae o be dgtzd Ti i a is This digitized. been not have maps navigational existing the area; the of considered bathymetry the about information reliable open-source no is there that noted Base Elevation (GLOBE)" (Fig. 6a). should It be One-Kilometer Land "Global data NOAA the from taken was grid The used. was 0.00833° value of a significant wave height height wave significant a minimal of the value code, open the in including: implemented, were code III WAVEWATCH the in modifications other of number a and al., 2016 a], where et adjustments body of the wind input [Kuznetsova water to model inland III adapted WAVEWATCH an the of used conditions we the study, this In introduction.the in detail in discussed are needed. The reasons and steps for the tuning model was model the of tuning the reservoir, sized prediction wave WAVEWATCH the III to the conditions of a middle- apply To GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. size of 0.00833° is shown. is 0.00833° of size WAVEW a) in reservoir Gorky the of grid Topographical 6. Fig. SIMULATION × 108 and increments of increments and 108 H S was was the frequency growth frequency the for formula logarithmic a by modeled was and simulation the in frequencies 31 in split was which range, observed experimentally the with accordance in Hz 0.2–4 to changed was range frequency The m. 9 be to chosen was depth and not calculations, was in considered bathymetry and exact m, the 4.5 therefore, than less is experiments the field in wavelength observed the addition, In water. deep it consider to sufficient was depth the that showed maps navigational these Although study. another for subject the growth rate was determined to be Typical values of wind speeds for the the for wind moderate speeds and weak wind are calculations of values Typical difference.temperaturewater-air and direction, topographicand speed wind data, specified the using parameterizations wind input different for seeding initial Gaussian given a for simulated were reservoir the in waves The considered. were field wave the [Tolman et al., 2014]; 30 angular directions of in accordance with the recommendations of ATCH III, b) WRF. Computational cell with a with cell Computational WRF.b) ATCHIII, 02 (09) 2016 (09) 02 σ N = (= δ ) N – 1– σ 1 , where , δ = 1.1 data for the lakes description “modis_lakes” description lakes the for data geographical recommended the module, data simulations was realized. For the geogrid to data prepare the the input to of the real program for real- preprocessing the system, steps were undertaken. In WRF preprocessing following the reservoir, Gorky the over field wind the of calculation the to WRF Toapply forcingfrom the atmospheric model wind WRF. the using field wind the of variability spatial the considering taking realized was It used.simulationwas the forcing insetting Fig.windthe2). secondmethodThus, ofthe wind conditions over the entire water area (see ofstudyfield thereservoirsupported bywas the overfieldwind heterogeneity the The of significantfield.windthespatial variability of the reservoir and the high banks can lead to a of shape elongated the as factors such and heterogeneous,be toexpected is field wind errors in a numerical experiment, because the wind forcing over the pond can be a source ofthe of homogeneity the of assumption This reanalysis data in a simple form is not correct. the of use regard,the this reservoir.In the of waters the over that from different is coast the on speed wind the and coast, the on are they and Yurievets), but (Volzhskaya stations weather two only are there area studied the the precise In area. this in occurs more assimilation data more are data reanalysis the addition, In (2.5°). resolution spatial low too this approach is not applicable because of its accurately. In the middle-sized inland waters, more regime wave the simulate to help can that variability spatial a has forcing.It wind a oceans, the reanalysis data is typically usedand as seas the of surface the on waves wind temperature difference. In practice, to simulate 10 m wind speed and direction, the water-air experiment: field the in measured minutes, every15 updated data input with held was simulation account. The into taken was time in variability entire reservoir; Gorky the the of surface over homogeneous and assumed experiments the in measured wind speed of value the as set was forcing wind First, studied. were data input wind of types ( AlexandraM. Kuznetsova FIELD AND N et al. U 10 = 1= ò 9 m/s) of different directions. Twodirections. different of m/s) 9 UMERICALSTUDY OF THE WIND-WAVEREGIME... The calculation of mean wave period performed by the formula:the by performed aaeeiain A 3 wih ss a the uses ocean of which dependence the linear 3, of WAM framework parameterization the ways: in two in firstly, out carried was Simulation 2012].Laboratory, Systems Information and [Computational USA the Boulder, on supercomputer, Yellowstone conducted were simulations The grid. domains the on data meteorological extracted the of interpolation horizontal a ungrib program. Metgrid program produced was extracted from the GRIB format using the was loaded. It was updated every 6 hours and from GFS) (ds083.2)” with 1 degree resolution meteorological data “NCEP Final Analysis (FNL To describe the current weather situation, the grid. given static the for information geographical the interpolate to and domains the 0.00833°) describe to III used were data These WAVEWATCH 6b). (Fig. in used data is (it arcseconds equivalent 30 to the cell size was of the topographical domain nested fourth the of size cell used.minimal was The for four nested domains in the studied region parameterization of of proposed our parameterization with secondly, and 1982], of parameterizations parameterizations of difference The 3. WAM term source input the the Fig. 5b. For of up speeds to the wind 2.5 m/s, above the the above experimental results, the calculation of of the calculation of the results, processing experimental the in and in model Both the periods. wave mean wave and heights significant output: III WAVEWATCH following the for made is comparison The below.lie they m/s, 3 greaterthan speeds wind the for and parameterization, was performed by the formula:the by performed was DISCUSSION AND SIMULATION THE OF RESULTS E H s = C . 4 D

values from the field experiment lie lie experiment field the from values (2) C D values given by the ocean ocean the by given values C C D D ( (1) in the wind wind the in (1) U 10 C D ) is shown in in shown is )

on on U 10 T m [Wu, [Wu, was H S

27 GEOGRAPHY 28 GEOGRAPHY GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. 02 (09) 2016 (09) 02

Fig. 7. On the top plots: the retrieved values of a) HS and b) Tm obtained both from the field experiment (crosses) and from the numerical experiment (red dashed line for C U the WAM 3 parameterization, red solid line for the WAM 3 parameterization with new D( 10 )). On the lower plots: the measured values of the wind used in the simulation. C parameterization proposed the of use The WAM 3 parameterizations are overestimated. with simulations in height wave significant the of values the usually Fig.from7, seen be can it As experiments. numerical and field AlexandraM. Kuznetsova FIELD AND N et al. of ones, and the use measured of the the new parameterization with discrepancy significant a has periods wave mean of prediction the However, the top graphs of Fig. 7b show that the entering accurately.more simulated was energy system of amount the that rate was defined more precisely, which means using the ocean model WAM 3 and new new and 3 parameterization WAM model ocean the using 13.06.13 day test the for measurements field and modeling the of results the Fig.shows 7 experiment.field the from data averaged the of 15 minutes from to correspond with the similarlyinterval data the over averaged were simulation output the the in experiment, measured speed wind the of value constant forcingthe wind as the set When is experimentaldatatheforcingfrom Wind point the at obtained corresponding were to the point data of the the observations. All values of values retrieved the for change a shows top the on plot the simulation, the in used wind the of values measured the show plots lower The scheme DIA [Hasselmann and Hasselmann, Hasselmann, and [Hasselmann DIA scheme nonlinear numerical of parameters specific wind input, but also in taking into account the the of function the in only not reflected was environment marine to III WAVEWATCH of Perhaps, this is due to the fact that the tuning new parameterization of of use the with experiment numerical the in field experiment. This is the expected result, as for WAM 3 parameterization compared to the fEffdf f f E df f E T T m m D C ( U = D 10 ( U ) ) reduces the standard of deviation 10 ,1 0, − ) does not have a sufficient impact. impact. sufficient a have not does ) H S         and f F i min min f f ∫ ∫ r r T ) ( ) ( m C , obtained both from the from both obtained , D ( U − 10 C 1 D ) within WAM 3. 3. WAM within ) , the wave growth − 1 . (3) H S

UMERICALSTUDY OF THE WIND-WAVEREGIME... of the predictionsof the of nonlinear scheme should not affect the quality can expect that such a tuning of the numerical wave periods will decrease. mean Consequently,At downshift. thefrequencies same time, we non-linearity, stronger which with situationshould a lead to to may a morecorresponding rapid reservoir parameters of different middle-sized adjustment requirea Steeper a of conditions. waves sea the to adjusted were DIA scheme the in proportionality of coefficients The waters. inland middle-sized the on waves the to compared slope lower of characteristics a have which conditions, ocean and wave marine the WAVEWATCH considers spectrum. III the in wind the from received energy the of redistribution because the for responsible 1985], are processes al., nonlinear et Hasselmann 1985; parameterization parameterization proposed the of use the of advantages The subsequentexperiments. numerical the intested periods.behypothesis willThis should lead to a better prediction of amountmeanof energy wavereceived by the system, but value of the wind measured in the experiment by the lower graphs in Fig. 9, which show the supported also is This 13.06.13. day test the in experiment field the in measured those values of the wind speed are much lower than the However,segment). the of direction the by (indicated direction the in and color), by the (indicated value the over in both heterogeneous is 8) (Fig. wind reservoir Gorky the the of area of water distribution The Fig.in 8.presented in the simulation for the test day 13.06.13 are wind over the water area. The results obtained showed thereservoir significant Gorky spatial variabilitythe of the containing area the to application WRF The experiment. numerical and forecast eliminating wave the possible the causes of errors in improving the in step next the was forcing wind WRF of use The WRFforcingfrom Wind a].2016 al., et [Kuznetsova in detail C D ( H U S 10 , which indicates theindicates which , ) are described in in described are )

29 GEOGRAPHY 30 GEOGRAPHY GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. simulation. o area water the over wind the of distribution The 8. Fig. f the Gorky reservoir in the test day 13.06.13,day test the in WRF reservoir Gorky f the 02 (09) 2016 (09) 02 AlexandraM. Kuznetsova FIELD AND N et al. UMERICALSTUDY OF THE WIND-WAVEREGIME...

H T C U C U Fig. 9. Top plots: a) S and b) m for: WAM 3 with new D( 10 ) with wind forcing from the experiment averaged over 15 minutes (blue dashed line), WAM 3 with new D( 10 ) C U with wind forcing from the experiment averaged over 60 minutes (blue solid line),WAM 3 with new D( 10 ) with WRF wind forcing (red solid line). Lower plots: wind measured in the experiment and averaged over 15 minutes (dashed black line), wind measured in the experiment and averaged over 60 minutes (black line), wind from WRF, averaged over 60 minutes (red line).

31 GEOGRAPHY 32 GEOGRAPHY Consequently, the resulting dependence of dependence resulting the Consequently, speed. wind of increase not reflect the local by WRF. In addition, the WRF simulation does the than wind, given was higher experiment the by given wind the average, on However, course, of of the affects the dependence wind on time. minutes, 60 over and minutes 15 over data experimental wind from the averaging of change the that shows 9 Fig. flows. turbulent of forecasts calculation the accurate incorporating highly create to help will unit this and possible, be will unit (LES) Simulation Eddy Large the of inclusion the resolution. With the increase of the precision, insufficient precision of the geographical data Second, we associate this inaccuracy with the study. future the of part is stations weather private the of Installation stations) weather needed. is pond the of perimeter the along private (e.g., sources additional the from data the Consequently, reservoir. the of different where waters the over that coast, from significantly is and the speed on wind area, the located study are the in they Yurievets) and was there (Volzhskaya stations it weather two “Simulation,” As only are section area. in test discussed the in data several of assimilated amount with small a wind with model First, of factors. WRF in inaccuracy this prediction associate We line).(red minutes 60 the with wind from WRF, comparison which was also averaged the over of convenience the for line) (black minutes 60 over and line) and averaged over 15 minutes (dashed black GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. the prediction of the mean wave periods. periods. wave mean the of prediction the for realized same is experiment the The from forcing wind output. the setting of case the the WRF in as situation the impact of inclusion quality unit LES the and assimilation data above discussed the suppose that We also peaks. it the and indicate not data, does wind the experimental the with from that than lower average, H S ( t )

with wind forcing from WRF is, on on is, WRF from forcing wind with the new proposed parameterization parameterization proposed new the WAVEWATCHtuned III, the WRF.In wind by given the under and experiment, field unsteady the of from data the on based influence field wind uniform the under both calculated tuned was and the model WAVEWATCHIII within simulated was wave process The performed. was reservoir Gorky wind wavesThe simulation of on surface the banks.by wind of stratification of the surface layer,gustiness, andwind shielding conditions: reservoir the in flow air featuresof specific the to due is This values.renderedlower significantly,also and fixed) adjacent the reduced the scatter in the data experimental and surface tracking one (the only sensors speed two of use the particular, In shown. also was sensors speed wind the of height the on speed wind the of parameters statistical the of values retrieved the of dependence strong ocean The the conditions. of typical values its than lower % 50 approximately were winds strong and drag coefficient drag the of values the that showed reservoir the period. The basic research four-year of wind flow a above over collected were conditions hydrological and meteorological of range wide a in reservoir the of in part southern column) the water the of and layer surface temperature stratification of the atmospheric wind waves (such as wind speed and direction, field experiments, the statistics parameters of of series a In reservoir. Gorky the at regime wind-wave of study a describes paper This data.” experimental the model from forcing “Wind non-linearity subsection in discussed the to adjustment includes step that tuning next WAVEWATCH III the of the period become wave should mean prediction the for solution The experiments was used. The results of the the of were experiments numerical compared with results The used. was field experiments of series the from obtained reservoir middle-sized a of conditions the for suitable CONCLUSIONS C D 02 (09) 2016 (09) 02

in the range of moderate of range the in C D ( U 10 ) . tkuk .. Ktao KB (99 Wn Srs a Stress Wind (1999) K.B. Katsaros S.S., Atakturk 3. Opera-The (2014). G. Mann G., Lang D., Schwab TolmanA., H.L., Chawla J.-H.G.M., Alves 2. Great (2011).The G. Mann G., Lang D., Schwab H.L., Tolman A., Chawla J.-H.G.M., Alves 1. by incorporating a detailed topography and topography detailed a incorporating by of ultrahigh spatial resolution can be obtained this is due to insufficient accuracy in the the in ( accuracy topography insufficient to due is that this suppose We height. wave significant in the considered area and, as a consequence, speed wind the of value the underestimate simulation the of results the because WRF, in within simulation the improve to need application the WRF the demonstrated forcing WAVEWATCHwind of III results The 2013]).al., et Zilitinkevich 2006; al., the the stratified atmosphere to (see [Zilitinkevich et relates situation drawbacks in the simulation of in turbulence this 2015] al., et [Zilitinkevich In observed. is layer boundary resembling convective cells in a real motions turbulent large-scale artificial of appearance the circumstances, such Under resolved. nor i.e., the scales which are neither fully sub-grid used in the model was the so-called “graycaution, zone”,since the horizontal spatial resolution however, that the results should be used with using implemented WRF.noted,be should It was variability spatialfor accountingthe The models. numerical the use to necessary is it waves, and wind of prediction practical the in Moreover, a wind. of inhomogeneous case highly the accurately describe not did but experiment, fairly the a with in agreement good was experiment, field the from taken over reservoir the of speed area water entire wind the unsteady uniform The reservoir. Gorky the on experiments field the in obtained results the AlexandraM. Kuznetsova FIELD AND N et al. REFERENCES Washington // Journal of Physical Oceanography,Physical 29, of Journal Washington // Forecasting,1473–1497.29, of tional a Implementation Great Lakes Wave Forecasting System at NOAA/NCEP. // Wea. Forecasting,national and on WorkshopHawaii.Wave Hindcasting Inter-//12th Developments. Future and Challenges NOAA/NCEP: at Model Wave Lakes ≈ 1 km). The wind speed field field speed wind The km). 1 UMERICALSTUDY OF THE WIND-WAVEREGIME... by the National Science Foundation. Foundation. Science National the by and sponsored Laboratory, Systems Information Computational NCAR’s by provided support (ark:/85065/d7wd3xhc) Yellowstone computing from high-performance acknowledge to like 14-would We No. 17-00667). (Agreement Russian Foundation the by Science supported partially simulations were numerical 15-17-20009), (Agreement No. the Foundation by Science supported Russian was experiment field The 15-45-02580). 14- 15-35-20953, 05-31343, RF 14-05-91767, (13- RFBR 13-05-12093, the the Scientists 05-00865, by and Young for (MK-3550.2014.5), Grant 11.G34.31.0048), President’s Federation Russian (contract the of the of grant Government by supported was work This results.the on impact positive a with the transition to shallow water, can make the source terms in WAVEWATCH III associated the Gorky reservoir, as well as the inclusion of made. Accounting for the of real bathymetry calculations, the deep water assumption was the in made assumptions the to addition In model. non-linearity the to adjustment the includes WAVEWATCHthe that of tuning step III next the of implementation the with improved The area. be will periods wave mean the of this prediction in stations weather private from data and experiments the the from assimilation by and unit, LES the of inclusion ACKNOWLEDGEMENTS nd Surface Waves Observed on Lake Lake on Observed Waves Surface nd pp. 633–650.pp. n

33 GEOGRAPHY 34 GEOGRAPHY 7. Computational and Information Systems Laboratory. Systems Information and Computational 7. . oao NA, ahnv .. Emskn .. Kaz A.V., Ermoshkin V.V., Bakhanov N.A., Bogatov 6. . ahnv .. Bgtv .. Emskn .. Iva A.V., Ermoshkin N.A., Bogatov V.V., Bakhanov 5. . aai AV, ai VK (08 Efcs f wind of Effects (2008) V.K. Makin A.V., Babanin 4. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. 1 . untoa .. Byao GA, ak .. Kan V.V., Papko G.A., Baydakov A.M., Kuznetsova 15. 14. Ivanov A.V.,Troitskaya V.V.,PapkoYu.I., Ivanov Serg 14. 1 . Hesser T.J., Cialone M.A., Anderson M.E. (2013) 13. and Computations (1985) T.P. Barnett J.H., Allender K., Hasselmann S., Hasselmann 12. the of parameterizations and Computations (1985) K. Hasselmann and S. Hasselmann 11. Technical 4. cycle model WAM The (1992) P.A.E.M. Janssen S., Hasselmann H., Gunter 10. (2 al. et J.E. Hare E.F., Bradley C.W., Fairall 9. M.A., Drennan Donelan W.M., analysis of the direc- (1996) Nonstationary Magnusson A.K. 8. doi:10.1117/12.2067403. L and Waters,Coastal Ice, Sea Ocean, the of water Sensing a of parame layer determination near-surface foratmosphere an radar and surface marine standard of Using (2014) Yu.I. Troitskaya doi:10.1117/12.898364. L and Waters, Coastal Ice, Sea Ocean, the of Sensing S White the in waves wind the on currents mogeneous o investigations Full-scale (2011) V.I.Titov O.N., rg Lk Gog suy / ora o Gohscl R Geophysical of Journal // study doi:10.1029/2007JC004233. George Lake drag: rology, vol. 2016, Article ID 8539127, 13 pages. doi:10.1155/2016/8539127.pages. 13 8539127, ID Article rology,2016, vol. the watermiddle-sized body on the basis of the field experiment. // Advances in Meteo- in WAVEWATCH term source input wind Troitskayaof Adjusting (2016) Yu.forI. model III 34, с.149–156 (In Russian) (In с.149–156 34, tor of influence on water of quality a plane // reservoir) Privolzhsky Nauchnyy Journal, № poverkhnost na vody kachestvo na vliyaniya factor kak O.A Donskova I.M., Afanasieva A.A., Kandaurov V.I., Modeling. // The US Army Research and Development Center (ERDC), 156 pp.156 (ERDC), Center Development and Research Army US // Modeling.The // COARE and Algorithm the UpdatesforVerification http://n2t.net/ark:/85065/d7wd3xh Research. spheric C Boulder, Computing). Community (University System Oceanogr., vol. 15, pp. 1378–1391.pp.Oceanogr., 15, vol. J.Phys.// wavemodels in transferforenergyapplication nonlinear of parameterizations II: Part spectrum, gravity-wave a in transfer energy nonlinear the of parameterizations 1369–1377. pp. 15, vol. Oceanogr., Phys. J. // integral transfer nonlinear exact the of computations spectrum, gravity-wave a in transfer energy nonlinear pp.Hamburg.//DKRZ 101 WAM 4. No.Documentation. Model report Phys.J.Oceanogr., waves.// propagating of V.26,P.1901–1914. N.9., properties tional 003) Bulk Parameterization of Air–Sea. Fluxes: Air–Sea. of Parameterization Bulk 003) eev D.A., Baydakov G.A., Vdovin M.I., Kazakov Kazakov M.I., VdovinG.A., Baydakov D.A., eev Lake St. Clair: Storm St. Clair: Lake Wave and Water Level f the action of internal waves and inho-and waves internal of action the f arv .. dvn .. Srev D.A., Sergeev M.I., Vdovin A.A., daurov ., Shuvalova N.M. (2015) Stratifikaciya Stratifikaciya (2015) N.M. Shuvalova ., kv .. Kmrky ON, io V.I., Titov O.N., Kemarskaya V.I., akov nov A.Y., Lobanov V.N., Kemarskaja Kemarskaja V.N., Lobanov A.Y., nov trend and gustiness on the sea sea the on gustiness and trend Journal of Climate, of V.16, Journal P.571–591. c. arge Water Regions 2014, 924013; 924013; 2014, Regions Water arge arge Water Regions 2011, 81750L, 81750L, 2011, Regions Water arge Part I: A new method for efficient efficient for method new A I: Part (2012) Yellowstone: IBM iDataPlex IBM Yellowstone:(2012) i vodoema (Stratification as a fac-a as (Stratification vodoema i ters // Proc. SPIE 9240, Remote 9240, SPIE Proc. // ters : ainl etr o Atmo- for Center National O: ea // Proc. SPIE 8175, Remote 8175, SPIE Proc. // ea 02 (09) 2016 (09) 02 esearch, V.113, C02015, C02015, V.113, esearch, 2 . risaaY. . Srev .. Knarv A.A Kandaurov D.A., Sergeev I., Yu. Troitskaya 22. Tolman H. and WAVEWATCH III Development Group. User manual and system documen-21. of Technology,University //Delft SWAN(2006) manual.SWANEnvironmen- team.user – 20. 1 . odby SA, uhv EV (02 Modelirova (2002) E.V. Sukhova S.A., Poddubnyi 18. 19. SutyrinaE.N. (2011) Opredeleniye SutyrinaE.N. kharakteristi 19. 2 . WuJ. (1982) Wind-stressovers coefficients sea 23. 17. Lopatoukhin L.J., Boukhanovsky A.V.,Chernysho Boukhanovsky L.J., Lopatoukhin 17. 25. Zilitinkevich S.S., Elperin Elperin R S.S., N., T., Zilitinkevich Kleeorin 25. to models refining – Megacities (2015) A. Baklanov I., Esau M., Kulmala S., Zilitinkevich 24. 26. Zilitinkevich S.S., Hunt J.C.R., Grachev A.A., Grachev J.C.R., Hunt S.S., Zilitinkevich 26. 1. untoa .. Byao GA, ak .. Kan V.V., Papko G.A., Baydakov A.M., Kuznetsova 16. AlexandraM. Kuznetsova FIELD AND N et al. Received01.12.2015 Modeling and Analysis Branch. 282 pp. + Appendices.+ pp. 282 Branch. Analysis and Modeling Marine Center, Modeling //Environmental WAVEWATCH(2014) of 4.18. tation version III pp. 129 Section. Mechanics Fluid tal Russian). (In Univ.,216-226. vol.4,State Irkutsk Izv. the of characteristics of estimation (The nilishcha wind conditions // J. Geophys. Res.,Geophys.J. V.117, // C11, Is. conditions wind air-stheoretical of and modeling Laboratory (2012) Waves Hindcasting and Forecasting,and Hawaii.Waves Hindcasting wind and wave climate of seas around // Proc. Vod. im. I.D.Papanina, 116 pp. (In Russian). I.D.Papanina,Vod.(In pp.im. 116 BiologiiVn. //Institut Manual). User’s reservoirs: in hydrobionts of distribution on factors h of effect the (Modeling polzovatelej. dlya vodstvo raspredeleniyegidrobionna faktorov antropogennykh rologiya i Gidrologiya,vol. 41, issue 2, pp. 136 – 145 (In Russian). (In 145 – 136 pp. 2, issue Gidrologiya,vol.41, i rologiya // Meteo- reservoir). waves on the middle-size ment and simulation of wind and surface sredn vodoyemakh vnutrennikh c na voln i poverkhnostnykh issledovaniya Naturnye (2016) I. Yu. Troitskaya personal environment. // WMO Bulletin 64 (1), 20–22.(1), 64 Bulletin // environment.WMO personal 9704–9706.pp. 87, vol.Res.,phys. flows. // Boundary-Layer Meteorol. 146, 341–373.146, Meteorol. Boundary-Layer // flows. geophysical stratified stably for models closure turbulence (EFB) flux-budget and ergy- eddies on the surface layer turbulence. // Quart. J Quart. // turbulence. layer surface the on eddies C.W.,rall Fernando JoffreA., S.M. H.J.S., Baklanov ogachevskii I., Esau I.N. (2013) A hierarchy of en- hierarchy of A (2013) I.N. Esau I., ogachevskii UMERICALSTUDY OF THE WIND-WAVEREGIME... Esau I.N., Lalas D.P., Lalas I.N., Esau E., Tombrou Fai-Akylas M., k volnovogo rezhima vodokhra- Bratskogo ., Baidakov G.A., Vdovin M.A., Kazakov V.I. Kazakov M.A., Vdovin G.A., Baidakov ., urface from J.breeze // Geo- to hurricane urface (2006) largeof influence The convective va E.S., Ivanov S.V. (2004) Hindcasting of Hindcasting S.V.(2004) Ivanov E.S., va arv .. dvn .. Srev D.A., Sergeev M.I., Vdovin A.A., daurov C00J21. . Roy. Met. Soc. 132, 1423–1456. 132, Soc. Roy. Met. . ie lyny gdoiaihsih i gidrodinamicheskikh vliyaniya niye Bratskoye Reservoir wave regime). //regime). wave Reservoir Bratskoye ea momentum transfer momentum severe ea under ilnoe oeioaie er i vetra modelirovaniye hislennoye The 8th International Workshop on ydrodynamical and anthropogenic and ydrodynamical tov v vodokhranilishchakh: Ruko- vodokhranilishchakh: v tov k rzeo (il experi- (Field razmerov ikh Accepted05.05.2016

35 GEOGRAPHY 36 GEOGRAPHY GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. GEOGRAPHY. ENVIRONMENT. SUSTAINABILITY. VailvV Papko V. Vladislav Alexandra M. Kuznetsova Georgy A. Baydakov Alexander KandaurovA. and atmospheric models. atmospheric and layer,surface layer, boundary planetary simulation, wave models, hydrosphere, and atmosphere include interests main Her RAS). Sci of Academy Russian the of (IAP) Insti Physics the Applied at works now then and degree She D. Ph. degree. her M.Sc. obtained a with Novgorod) Lobachevsk (Nizhny of University Physics Applied and General of School 25 journal articles. including journal 25 papers, scientific 60 nearly published He ocean. the in processes hydro-physical study to expeditions numerous in participated He technique. electronic measuring and modeling, laboratory experiments, field solitons, degreewaves, nonlinear to relate D. Ph. his Novg received (Radiophysics) in the IAP RAS main in research1982. His Nizhny interests He 1965. the in of University Faculty Technical Radioelectronic the from He RAS. IAP the of Processes Geophysical Nonlinear under severe wind conditions. wind severe under layer boundary turbulent the of modeling laboratory and layer o boundary atmospheric the in investigation processes transfer and interaction field includes interests scientific The RAS. IAP the at works and degree D. Ph. a holds i Novgorod) (Nizhny University State Lobachevsky of measurements, laboratory modeling, and visualization.and modeling, laboratory measurements, in 2015. RAS His IAP main in research hydrosphere) interests and are atmosphere hydrophysics, of hydrodynamics (physics D. Ph. his received and 2011 in degreeM.Sc. a with Novgorod) (Nizhny State Lobachevsky of Physics Applied and General of is Senior Researcher at the Department of of Department the at Researcher Senior is graduated from the Radiophysics Department graduatedfrom Advanced the School graduated in 2013 from the Advanced 02 (09) 2016 (09) 02 wind-wave f 21. He 2012. n ences (IAP (IAP ences University University graduated area of his of area State y ue of tute orod orod AlexandraM. Kuznetsova FIELD AND N et al. supervised a number of Ph.D. students at the IAP RAS Lobachevskywho AppliedGeneralsuccessfully thePhysicsdefendedand oftheir ofS theses. best publication in 2008. From 1998 to present, she uia . Troitskaya I. Yuliya I. Vdovin Maxim ail . Sergeev A. Daniil the turbulent boundary layer under severe wind condit wind severe under layer boundary turbulent the of modeling laboratory and layer boundary atmospheric the in scientific his of area The transferprocessesand wind-waveinterests interactions includes RAS. IAP the at Researcher Junior is He 2012. Novgorodin Nizhny of University State Lobachevsky of Shewasrecognized bythePublishing House MAIK-Sci international symposiums, many conferences, at and published more than 200 scientific papers, and made hydrosphere,satellite methods forstudying watthe hy atmoturbulence arewaves,dynamicstheand interestsflows of in research main Her 1998. in RAS d IAP D. Ph. Sc.D.degree her theat her and 1987 in RAS receivedIAP the at (geophysics) She 1983. in Novgorod) (Nizhny Un State Lobachevsky the of Department Radiophysics graduated She RAS. IAP the of Processes Geophysical MedalofRussian Academy ofSciences in2009. awar was Heworkshops. conferences,symposiums,and journal30articles, presentationsmadeand manyat scientificvisualization.publishedp 100nearly He mode hydrodynamics measurements, laboratorylayers, researchinterests are physics of atmosphere and oc ofatmosphere andhydrosphere) attheIAP RAS in20 with a M. Sc. degree in 2003 and received his Ph. D Applied Physics of Lobachevsky State University (Ni IAPRAS.graduatedHe from theAdvanced School G of TechnicalEnvironmentalHydrodynamicand in Methods graduated from the Radiophysics Department Department Radiophysics the from graduated UMERICALSTUDY OF THE WIND-WAVEREGIME... s ed f h Lbrtr o Experimental of Laboratory the of Head is is has been Professor of the Advanced School

ed f h Dprmn o Nonlinear of Department the of Head tate Universitytate(Nizhny Novgorod). She . degree (physics apers,including zhny Novgorod) er surface.er She presentations eanboundary international encefor the sphere and 06.mainHis workshops. drophysics, from the the from eneraland ions. ig and ling, iversity iversity ded the ded s of the of s egree

37 GEOGRAPHY