Altura significativa de onda (m)

≤ 0,51,52,53,54,5≥ 5,5

Starting Guaecast

Full forecast

WAVES AND WIND

Significant wave heightSignificant swell height at the beach Mean period at the beachOffshore swell period ➤ Direção do swell offshore Night

Wind at 10 m (knots)

Altura (m)Período (s)

WAVE ENERGY

Low Moderate High Very high Extreme

Potência (kW/m)

TIDE AND SEA LEVEL

Total level (astronomical tide + atmospheric effect)Astronomical tide

Nível do mar (m)

ATMOSPHERE

Air temperature Chuva por intervalo (1 h / 3 h) ☀ / ☾ Nebulosidade e chuva Night

Temp. (°C)Chuva (mm)

Selected time in detail

Beach conditions

At the beach

Waves and swell

GFS · 10 m

Wind

Swell offshore

Directional spectrum

0run maximum

GFS

Atmosphere

Sea level

Tide and total level

Ressacast

Coastal conditions

Conheça o Ressacast ↗

All data

Forecast by time

Click a time to select it on the map and in the hourly details.

Day

DateTime in Brasília (UTC−3)	At the beach				Offshore		Wind		Tide			Weather				Ressacast
DateTime in Brasília (UTC−3)	Significant wave heightm	Significant swell heightm	Mean periods	PowerkW/m	Swell periods	Swell direction°	Speedknots	Direction°	Total levelm	Astronomicalm	Meteorologicalm	Temperature°C	Clouds%	Rainfall in 3 hoursmm	PressurehPa	RessacastCategory

Wave, wind and tide forecasts for the São Paulo coast

GUAECAST provides forecasts for 88 beaches in 13 municipalities, from Paraty (RJ) to Peruíbe (SP), Brazil. Explore wave height, period and direction, swell, wind, tides and weather in maps and charts up to 16 days ahead.

Coastal forecasts for surfing and ocean activities

Eight nested SWAN grids represent how waves change near the coast. Select a city and beach to explore forecasts for Guaecá, Barequeçaba, Maresias, Ilhabela, Ubatuba, Santos, Guarujá and other covered locations.

How to read the beach conditions

Read wave height together with swell period and direction, wind and sea level. Forecasts come from numerical models; they are not live observations or a guarantee of breaking-wave conditions. Maps and time series show how the predicted conditions evolve.