Field and Numerical Study of the Wind-Wave Regime on the Gorky Reservoir

Abstract

ABSTRACT. The paper describes the study of wind-wave regime at the Gorky reservoir. A series of field experiments (carried out from May to October in [2012][2013][2014][2015] showed that the values of the drag coefficient C D for a middle-sized reservoir in the range of moderate and strong winds are approximately 50 % lower than its values typical of the ocean conditions. The obtained parameterization of C D was implemented in the wave model WAVEWATCH III to receive the correct wave forecasts for a middle-sized reservoir. Statistical distribution of the wind speeds and directions called for consideration of wind field heterogeneity over the Gorky reservoir. It was incorporated using the wind forcing from atmospheric model WRF to WAVEWATCH III. Homogeneous wind forcing from the experimental data was compared with heterogeneous wind forcing from WRF. The need for further improvement of the quality of wind and wave prediction is discussed.

Bulk Transfer Coefficients Estimated From Eddy‐Covariance Measurements Over Lakes and Reservoirs

“…14 of 20 case between over-sea and over-land locations in terms of turbulent transfer. The lower bound for 𝐴𝐴 𝐴𝐴DN , 𝐴𝐴 𝐴𝐴HN, 𝐴𝐴EN among the water bodies at high wind speeds were within the range reported by previous studies, including for large lakes (>200 km 2 (Kuznetsova et al, 2016;Wei et al, 2016), classical open ocean measurements (Fairall et al, 2003;Large & Pond, 1981) and coastal sites under fetch-limited conditions (Lin et al, 2002). Indeed, we also considered large lakes (Figure 1b) that were expected to have the smallest drag coefficient as they had the largest fetch (e.g., Lake Erie, Lake Taihu, Lake Balaton).…”

“…As described in Section 2.4.4, we estimated drag coefficients accounting for gustiness ( 𝐴𝐴 𝐴𝐴DNG ) using gustiness factors derived from measured scalar-averaged wind speed ( 𝐴𝐴 𝐴𝐴wind ), and from the parametrization of convective velocities ( 𝐴𝐴 𝐴𝐴conv ). To test the applicability of the parametrization, we compared 𝐴𝐴 𝐴𝐴DNG estimated using both Colored lines show the results from previous studies: LK, brown line-Lake Kasumigaura, Japan (eddy covariance, Wei et al, 2016); LN, red line-Lake Neuchâtel, Switzerland (dissipation method, Simon, 1997); LG, pink line-nearshore site at Lake Geneva, Switzerland (wind profile method, Graf et al, 1984); RG, light orange color-Reservoir Gorkiy, Russia (wind profile method, Kuznetsova et al, 2016) approaches during unstable atmospheric conditions for a subset containing 11 lake data sets with all required data (Figure S8 in Supporting Information S1). The estimated 𝐴𝐴 𝐴𝐴DNG based on 𝐴𝐴 𝐴𝐴conv was slightly higher than the one based on 𝐴𝐴 𝐴𝐴wind .…”

“…The small inset in (a) shows the data beyond the scale. Vertical and horizontal black dashed lines mark a constant wind speed of 3 m s −1 and typical values of 𝐴𝐴 𝐴𝐴DN , 𝐴𝐴 𝐴𝐴HN = 𝐴𝐴EN 1.3•10 −3 , 1.1•10 −3 , respectively.Colored lines show the results from previous studies: LK, brown line-Lake Kasumigaura, Japan (eddy covariance,Wei et al, 2016); LN, red line-Lake Neuchâtel, Switzerland (dissipation method, Simon, 1997); LG, pink line-nearshore site at Lake Geneva, Switzerland (wind profile method,Graf et al, 1984); RG, light orange color-Reservoir Gorkiy, Russia (wind profile method,Kuznetsova et al, 2016); OO, dark green color-open ocean (eddy covariance, Large & Pond, 1981); OO, light green color-open ocean (eddy covariance, Fairall et al, 2003); CO, dark yellow color-coastal ocean at limited fetch conditions (eddy covariance, Lin et al, 2002). (d) Mean diel pattern of the percentage of time periods with unstable atmospheric conditions (stability parameter 𝐴𝐴 𝐴𝐴 𝐴 0 ).…”

Bulk Transfer Coefficients Estimated from Eddy-Covariance Measurements over Lakes and Reservoirs

“…As described in Section 2.4.4, we estimated drag coefficients accounting for gustiness ( 𝐴𝐴 𝐴𝐴DNG ) using gustiness factors derived from measured scalar-averaged wind speed ( 𝐴𝐴 𝐴𝐴wind ), and from the parametrization of convective velocities ( 𝐴𝐴 𝐴𝐴conv ). To test the applicability of the parametrization, we compared 𝐴𝐴 𝐴𝐴DNG estimated using both Colored lines show the results from previous studies: LK, brown line-Lake Kasumigaura, Japan (eddy covariance, Wei et al, 2016); LN, red line-Lake Neuchâtel, Switzerland (dissipation method, Simon, 1997); LG, pink line-nearshore site at Lake Geneva, Switzerland (wind profile method, Graf et al, 1984); RG, light orange color-Reservoir Gorkiy, Russia (wind profile method, Kuznetsova et al, 2016); OO, dark green color-open ocean (eddy covariance, Large & Pond, 1981); OO, light green color-open ocean (eddy covariance, Fairall et al, 2003); CO, dark yellow color-coastal ocean at limited fetch conditions (eddy covariance, Lin et al, 2002). ( d approaches during unstable atmospheric conditions for a subset containing 11 lake data sets with all required data (Figure S8 in Supporting Information S1).…”

“…The small inset in (a) shows the data beyond the scale. Vertical and horizontal black dashed lines mark a constant wind speed of 3 m s −1 and typical values of 𝐴𝐴 𝐴𝐴DN , 𝐴𝐴 𝐴𝐴HN = 𝐴𝐴EN 1.3•10 −3 , 1.1•10 −3 , respectively.Colored lines show the results from previous studies: LK, brown line-Lake Kasumigaura, Japan (eddy covariance,Wei et al, 2016); LN, red line-Lake Neuchâtel, Switzerland (dissipation method, Simon, 1997); LG, pink line-nearshore site at Lake Geneva, Switzerland (wind profile method,Graf et al, 1984); RG, light orange color-Reservoir Gorkiy, Russia (wind profile method,Kuznetsova et al, 2016); OO, dark green color-open ocean (eddy covariance,Large & Pond, 1981); OO, light green color-open ocean (eddy covariance,Fairall et al, 2003); CO, dark yellow color-coastal ocean at limited fetch conditions (eddy covariance,Lin et al, 2002). (d) Mean diel pattern of the percentage of time periods with unstable atmospheric conditions (stability parameter 𝐴𝐴 𝐴𝐴 𝐴 0 ).…”