This research examines how stable stratifications occur and influence energy production predictions along Brazil's Southeast offshore region. The investigation focuses on a notable stable condition on July 3, 2019, detailed in a spatiotemporal analysis using the reanalysis dataset and a numerical atmospheric model. Moreover, we analyze reanalysis data of the air temperature at 2 m and the sea surface temperature (SST) to investigate the influence of atmospheric stability in the surface layer. We also measured the wind up to a height of 150 m using a wind profiler at a floating production storage and offloading vessel located about 190 km off the coast in the pre-salt oil extraction region. Stable conditions arise when warm air in the vanguard of the cold front passes over a relatively colder sea surface. An important finding reveals that air and sea are locally decoupled, where the wind profile is modified before the air surface temperature surpasses the sea surface temperature at the vessel due to the stable upstream conditions associated with the upwelling of cold water near the coast. Finally, we assess the stable stratification effects on annual energy production using three methods to extrapolate wind speeds from reanalysis data at a reference altitude of 100 m to the hub height of 150 m for a reference 15 MW wind turbine. Our results indicate that extrapolation methods for stable conditions may lead to overprediction in annual energy production projections ranging from 1.2% to 9.7%.

1.
International Energy Agency
, see https://www.iea.org/ for “
Analysis and forecast to 2030
” (
2024
).
2.
Agência Nacional do Petróleo, Gás Natural e Biocombustíveis
, see https://www.gov.br/anp for “
Exploração e produção de Óleo e gás - segurança operacional
” (
2024
).
3.
S. A.
Hsu
,
Coastal Meteorology
(
Academic Press
,
1988
).
4.
R. J.
Barthelmie
,
J.
Badger
,
S. C.
Pryor
,
C. B.
Hasager
,
M. B.
Christiansen
, and
B. H.
Jørgensen
, “
Offshore coastal wind speed gradients: Issues for the design and development of large offshore windfarms
,”
Wind Eng.
31
,
369
382
(
2007
).
5.
S. T. K.
Miller
,
B. D.
Keim
,
R. W.
Talbot
, and
H.
Mao
, “
Sea breeze: Structure, forecasting, and impacts
,”
Rev. Geophys.
41
,
3
, https://doi.org/10.1029/2003RG000124 (
2003
).
6.
R.
Floors
,
A. N.
Hahmann
, and
A.
Peña
, “
Evaluating mesoscale simulations of the coastal flow using lidar measurements
,”
J. Geophys. Res. Atmos.
123
,
2718
2736
, https://doi.org/10.1002/2017JD027504 (
2018
).
7.
D.
Borvarán
,
A.
Peña
, and
R.
Gandoin
, “
Characterization of offshore vertical wind shear conditions in Southern New England
,”
Wind Energy
24
,
465
480
(
2021
).
8.
I. C. D. V.
Dragaud
,
M.
Soares da Silva
,
L. P. d F.
Assad
,
M.
Cataldi
,
L.
Landau
,
R. N.
Elias
, and
L. C. G.
Pimentel
, “
The impact of SST on the wind and air temperature simulations: A case study for the coastal region of the Rio de Janeiro state
,”
Meteorol. Atmos. Phys.
131
,
1083
1097
(
2019
).
9.
F. N. D.
Ribeiro
,
J.
Soares
, and
A. P.
Oliveira
, “
Sea-breeze and topographic influences on the planetary boundary layer in the coastal upwelling area of Cabo Frio (Brazil)
,”
Boundary. Layer Meteorol.
158
,
139
150
(
2016
).
10.
Y.
Sakagami
,
W. C.
Radünz
,
P.
Santos
,
R.
Haas
,
J. C.
Passos
, and
F. F.
Taves
, “
Power curve performance of coastal turbines subject to low turbulence intensity offshore winds
,”
J. Braz. Soc. Mech. Sci. Eng.
45
,
24
(
2023
).
11.
F.
Pimenta
,
W.
Kempton
, and
R.
Garvine
, “
Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil
,”
Renewable Energy
33
,
2375
2387
(
2008
).
12.
L. F.
de Assis Tavares
,
M.
Shadman
,
L. P.
de Freitas Assad
, and
S. F.
Estefen
, “
Influence of the WRF model and atmospheric reanalysis on the offshore wind resource potential and cost estimation: A case study for Rio de Janeiro state
,”
Energy
240
,
122767
(
2022
).
13.
P.
Tuchtenhagen
,
G. G.
De Carvalho
,
G.
Martins
,
P. E.
Da Silva
,
C. P.
De Oliveira
,
L. D. M. B.
Andrade
,
J. M.
De Araújo
,
P. R.
Mutti
,
P. S.
Lucio
, and
C. M. S.
e Silva
, “
WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil
,”
Energy
190
,
116341
(
2020
).
14.
N. N.
Davis
,
J.
Badger
,
A. N.
Hahmann
,
B. O.
Hansen
,
N. G.
Mortensen
,
M.
Kelly
,
X. G.
Larsén
,
B. T.
Olsen
,
R.
Floors
,
G.
Lizcano
,
P.
Casso
,
O.
Lacave
,
A.
Bosch
,
I.
Bauwens
,
O. J.
Knight
,
A.
Potter van Loon
,
R.
Fox
,
T.
Parvanyan
,
S. B.
Krohn Hansen
,
D.
Heathfield
,
M.
Onninen
, and
R.
Drummond
, “
The global wind atlas: A high-resolution dataset of climatologies and associated web-based application
,”
Bull. Am. Meteorol. Soc.
104
,
E1507
E1525
(
2023
).
15.
Q.
Guo
,
R.
Huang
,
L.
Zhuang
,
K.
Zhang
, and
J.
Huang
, “
Assessment of China's offshore wind resources based on the integration of multiple satellite data and meteorological data
,”
Remote Sens.
11
,
2680
(
2019
).
16.
A. M.
Sempreviva
,
R. J.
Barthelmie
, and
S. C.
Pryor
, “
Review of methodologies for offshore wind resource assessment in European seas
,”
Surv. Geophys.
29
,
471
497
(
2008
).
17.
S.
Yang
,
H.
Yuan
, and
L.
Dong
, “
Offshore wind resource assessment by characterizing weather regimes based on self-organizing map
,”
Environ. Res. Lett.
17
,
124009
(
2022
).
18.
N.
Chacko
, “
Exploring the offshore wind resource potential of India based on remotely sensed wind field data
,”
J. Indian Soc. Remote Sens.
50
,
1689
1700
(
2022
).
19.
K. S.
Klemmer
,
E. P.
Condon
, and
M. F.
Howland
, “
Evaluation of wind resource uncertainty on energy production estimates for offshore wind farms
,”
J. Renewable Sustainable Energy
16
,
013302
(
2024
).
20.
N.
Svensson
,
J.
Arnqvist
,
H.
Bergström
,
A.
Rutgersson
, and
E.
Sahlée
, “
Measurements and modelling of offshore wind profiles in a Semi-Enclosed Sea
,”
Atmosphere
10
,
194
(
2019
).
21.
H.
Li
,
B.
Claremar
,
L.
Wu
,
C.
Hallgren
,
H.
Körnich
,
S.
Ivanell
, and
E.
Sahlée
, “
A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea
,”
Geosci. Front.
12
,
101229
(
2021
).
22.
H.
Hersbach
,
B.
Bell
,
P.
Berrisford
,
S.
Hirahara
,
A.
Horányi
,
J.
Muñoz-Sabater
,
J.
Nicolas
,
C.
Peubey
,
R.
Radu
,
D.
Schepers
,
A.
Simmons
,
C.
Soci
,
S.
Abdalla
,
X.
Abellan
,
G.
Balsamo
,
P.
Bechtold
,
G.
Biavati
,
J.
Bidlot
,
M.
Bonavita
,
G.
De Chiara
,
P.
Dahlgren
,
D.
Dee
,
M.
Diamantakis
,
R.
Dragani
,
J.
Flemming
,
R.
Forbes
,
M.
Fuentes
,
A.
Geer
,
L.
Haimberger
,
S.
Healy
,
R. J.
Hogan
,
E.
Hólm
,
M.
Janisková
,
S.
Keeley
,
P.
Laloyaux
,
P.
Lopez
,
C.
Lupu
,
G.
Radnoti
,
P.
de Rosnay
,
I.
Rozum
,
F.
Vamborg
,
S.
Villaume
, and
J.-N.
Thépaut
, “
The ERA5 global reanalysis
,”
Q. J. R. Meteorol. Soc.
146
,
1999
2049
(
2020
).
23.
G.
Gualtieri
, “
Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review
,”
Renewable Sustainable Energy Rev.
167
,
112741
(
2022
).
24.
J.
Santos
,
Y.
Sakagami
,
R.
Haas
,
J.
Passos
,
M.
Machuca
,
W.
Radünz
,
E.
Dias
, and
M.
Lima
, “
Wind speed evaluation of MERRA-2, ERA-interim and ERA-5 reanalysis data at a wind farm located in Brazil
,” in
Proceedings of the ISES Solar World Congress 2019, SOLAR 2019/SHC 2019
(
International Solar Energy Society
,
2019
), pp.
1
10
.
25.
X.
Sun
,
K. H.
Cook
, and
E. K.
Vizy
, “
The South Atlantic subtropical high: Climatology and interannual variability
,”
J. Clim.
30
,
3279
3296
(
2017
).
26.
P.
Satyamurty
,
C. A.
Nobre
, and
P. L.
Silva Dias
, “
South America
,” in
Meteorology of the Southern Hemisphere
, edited by
D. J.
Karoly
and
D. G.
Vincent
(
American Meteorological Society
,
Boston, MA
,
1998
), pp.
119
139
.
27.
L. M. V.
Carvalho
,
C.
Jones
, and
B.
Liebmann
, “
The South Atlantic convergence zone: Intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall
,”
J. Clim.
17
,
88
108
(
2004
).
28.
W. L. F.
Correia Filho
,
P. H. D. A.
Souza
,
J. F. D.
Oliveira-Júnior
,
D. D. B.
Santiago
,
G. B.
Lyra
,
M.
Zeri
, and
G.
Cunha-Zeri
, “
The wind regime over the Brazilian southeast: Spatial and temporal characterization using multivariate analysis
,”
Int. J. Climatol.
42
,
1767
1788
(
2022
).
29.
A.
Lapworth
, “
The diurnal variation of the marine surface wind in an offshore flow
,”
Q. J. R. Meteorol. Soc.
131
,
2367
2387
(
2005
).
30.
J.
Gottschall
,
G.
Wolken-Möhlmann
,
T.
Viergutz
, and
B.
Lange
, “
Results and conclusions of a floating-lidar offshore test
,”
Energy Proc.
53
,
156
161
(
2014
).
31.
G.
Wolken-Möhlmann
,
O.
Bischoff
, and
J.
Gottschall
, “
Analysis of wind speed deviations between floating LIDARS, fixed lidar and cup anemometry based on experimental data
,”
J. Phys. Conf. Ser.
2362
,
012042
(
2022
).
32.
F.
Kelberlau
and
J.
Mann
, “
Quantification of motion-induced measurement error on floating LIDAR systems
,”
Atmos. Meas. Tech.
15
,
5323
5341
(
2022
).
33.
W. C.
Skamarock
,
J. B.
Klemp
,
J.
Dudhia
,
D. O.
Gill
,
Z.
Liu
,
J.
Berner
,
W.
Wang
,
J. G.
Powers
,
M. G.
Duda
,
D. M.
Barker
, and
X.-Y.
Huang
, “
A description of the advanced research WRF model version 4.3
,” Report No. NCAR/TN–556+STR (
UCAR/NCAR
,
2021
).
34.
A. N.
Hahmann
,
T.
Sile
,
B.
Witha
,
N. N.
Davis
,
M.
Dörenkämper
,
Y.
Ezber
,
E.
Garciá-Bustamante
,
J.
Fidel González-Rouco
,
J.
Navarro
,
B. T.
Olsen
, and
S.
Söderberg
, “
The making of the new European Wind Atlas - Part 1: Model sensitivity
,”
Geosci. Model Dev.
13
,
5053
5078
(
2020
).
35.
W. C.
Radünz
,
E.
de Almeida
,
A.
Gutiérrez
,
O. C.
Acevedo
,
Y.
Sakagami
,
A. P.
Petry
, and
J. C.
Passos
, “
Nocturnal jets over wind farms in complex terrain
,”
Appl. Energy
314
,
118959
(
2022
).
36.
J. J.
Danielson
and
D. B.
Gesch
, “
Global multi-resolution terrain elevation data 2010 (GMTED2010)
,” Report No. 2011-1073, (
U.S. Department of the Interior, U.S. Geological Survey
,
2011
).
37.
S.-Y.
Hong
,
J.
Dudhia
, and
S.-H.
Chen
, “
A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation
,”
Mon. Weather Rev.
132
,
103
120
(
2004
).
38.
M. J.
Iacono
,
J. S.
Delamere
,
E. J.
Mlawer
,
M. W.
Shephard
,
S. A.
Clough
, and
W. D.
Collins
, “
Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models
,”
J. Geophys. Res.
113
,
D13103
, https://doi.org/10.1029/2008JD009944 (
2008
).
39.
P. A.
Jiménez
,
J.
Dudhia
,
J. F.
González-Rouco
,
J.
Navarro
,
J. P.
Montávez
, and
E.
García-Bustamante
, “
A revised scheme for the WRF surface layer formulation
,”
Mon. Weather Rev.
140
,
898
918
(
2012
).
40.
Y. N. S.-Y.
Hong
and
J.
Dudhia
, “
A new vertical diffusion package with an explicit treatment of entrainment processes
,”
Mon. Weather Rev.
134
,
2318
2341
(
2006
).
41.
F.
Chen
and
J.
Dudhia
, “
Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model description and implementation
,”
Mon. Weather Rev.
129
,
569
585
(
2001
).
42.
J. S.
Kain
, “
The Kain-Fritsch convective parameterization: An update
,”
J. Appl. Meteorol. Climatol.
43
,
170
181
(
2004
).
43.
J. S.
Kain
and
J. M.
Fritsch
, “
A one-dimensional entraining/detraining plume model and its application in convective parameterization
,”
J. Appl. Meteorol. Climatol.
47
,
2784
2802
(
1990
).
44.
E.
Gaertner
,
J.
Rinker
,
L.
Sethuraman
,
F.
Zahle
,
B.
Anderson
,
G.
Barter
,
N.
Abbas
,
F.
Meng
,
P.
Bortolotti
,
W.
Skrzypinski
,
G.
Scott
,
R.
Feil
,
H.
Bredmose
,
K.
Dykes
,
M.
Shields
,
C.
Allen
, and
A.
Viselli
,
Definition of the IEA 15-Megawatt Offshore Reference Wind Turbine
(
National Renewable Energy Laboratory (NREL)
,
2020
).
45.
International Electrotechnical Commission
,
Wind Energy Generation systems - Part 12-1: Power Performance Measurements of Electricity Producing Wind turbines- IEC 61400-12-1:2017
, 2nd ed. (
International Electrotechnical Commission
,
Geneva, Switzerland
,
2017
), p.
558
.
46.
T.
Foken
,
Micrometeorology
(
Springer
,
Berlin, Heidelberg
,
2017
).
47.
M.
Schwartz
,
D.
Heimiller
,
S.
Haymes
, and
W.
Musial
, “
Assessment of offshore wind energy resources for the United States
,” Report No. NREL/TP-500-45889, (
Office of Scientific and Technical Information (OSTI)
,
2010
).
48.
U.
Högström
, “
Non-dimensional wind and temperature profiles in the atmospheric surface layer: A re-evaluation
,”
Boundary-Layer Meteorol.
42
,
55
(
1988
).
49.
T.
Foken
, “
50 years of the Monin–Obukhov Langua
,”
Boundary-Layer Meteorol.
119
,
431
447
(
2006
).
50.
Y.
Sakagami
,
R.
Haas
, and
J. C.
Passos
, “
Generalized non-dimensional wind and temperature gradients in the surface layer
,”
Boundary-Layer Meteorol.
175
,
441
451
(
2020
).
51.
A. S.
Monin
and
A. M.
Obukhov
, “
Basic laws of turbulent mixing in the surface layer of the atmosphere
,” in
Trudy Geofiz
, (
Akademia nauk SSSR
,
1954
), Vol.
24
, pp.
163
187
.
52.
S.
Redfern
,
M.
Optis
,
G.
Xia
, and
C.
Draxl
, “
Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic
,”
Wind Energy Sci.
8
,
1
23
(
2023
).
53.
M. S.
Reboita
,
M. A.
Gan
,
R. P. d
Rocha
, and
T.
Ambrizzi
, “
Regimes de precipitação na América do Sul: Uma revisão bibliográfica
,”
Rev. Bras. Meteorol.
25
,
185
204
(
2010
).
54.
R.
Stull
,
Practical Meteorology: An Algebra-Based Survey of Atmospheric Science
,(
University of British Columbia
,
2016
).
55.
D.
Vickers
,
L.
Mahrt
,
J.
Sun
, and
T.
Crawford
, “
Structure of offshore flow
,”
Mon. Weather Rev.
129
,
1251
1258
(
2001
).
56.
A. K.
Blackadar
, “
Boundary layer wind maxima and their significance for the growth of nocturnal inversions
,”
Bull. Am. Meteorol. Soc.
38
,
283
290
(
1957
).
You do not currently have access to this content.