SAWS: Met-Ocean Data & Infrastructure in Support of Industry, Research & Public Good. South Africa-Norway Science Week, 2016
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1 SAWS: Met-Ocean Data & Infrastructure in Support of Industry, Research & Public Good South Africa-Norway Science Week, 2016 Marc de Vos, November 2016
2 South Africa: Context mshare-show-note-asset/859_fdoc.pdf
3 SAWS: An Introduction Met-ocean data are required for a number of purposes: For the preparation of marine forecasts and warnings For the preparation of forecasts and warnings for offshore industries For marine consultancy For global computer models of the future state of the ocean/atmosphere To monitor the state of the oceans using delayed-mode data in weekly and monthly analyses For climatological data banks for many purposes, e.g. design of ships and structures at sea, determination of economic shipping routes; and To build long-term records to monitor changes in JCOMM, the 2015 climate of the earth.
4 SAWS: An Introduction 25 Weather Offices 3 Remote Stations 205 Automatic Weather Stations 165 Automatic Rainfall Stations all 11 stations, Climate Stations but for selected 1159 Rainfall Stations stations 11 Upper since Air Facilities SST Sites wind ~ 60 Drifting speed, Weather temperature, Buoys 24 Lightning Detection Stations humidity, pressure and 14 Meteorological Radar (C-, S- and X- sunshine band) from 1950 onwards 17 Air Quality Measuring and Monitoring 1961 Stations 2 Dobson Spectrophotometer 3 Aircraft 1 Baseline Surface Radiation Network radar Station data in De since Aar Global Atmosphere Watch Station at Cape Point 12 Voluntary Observing Ships 13 Solar Radiation Sensors Daily rainfall values since 1836 Daily surface observations for Hourly data of wind direction, Upper-air sounding data since Marine data from 1975 onwards Forecasting data since 1990, and
5 SAWS: An Introduction
6 SAWS: Coastal AWSs
7 SAWS: Coastal AWSs Wind (speed & direction) Pressure Temperature Humidity Rainfall
8 SAWS: Coastal AWSs
9 SAWS: Radar Currently: 14 Radar Systems (total) 11 S-band (8-15 cm) 3 C-band (4-8 cm) 10 Doppler 1 Dual Polarization
10 SAWS: Radar Coastal HF Radar WMO GEO Group Earth Observations, Work Plan: Specific Recommendations - Development of HFR network: coastal surface currents and surface waves - Pollutant tracking, SAR, HABs, navigation, coastal management, emergency response - Marine science: DA à better forecasting of extreme weather events, climate projections and seasonal monitoring; augment current in-situ & numerical modelling Mantovanelli et al., 2010
11 SAWS: Radar Coastal HF Radar Operation Phakisa - Marine Transport & manufacturing (coastal shipping, boat building, repair & refurbishment) - Offshore oil & gas - Aquaculture - Marine protection services & ocean governance
12 SAWS: Radar Coastal HF Radar Integration with other data & information systems - OCIMS - SAMSA: SASSN (MDA)
13 SAWS: Ship-Based Infrastructure SA Agulhas II - AWS - Upper Air - Visual Observations data/assets/image/0023/413069/agulhas_j aakoe_iso.jpg RV Algoa - AWS - Visual Observations
14 SAWS: Ship-Based Infrastructure
15 SAWS: Ship-Based Infrastructure WMO IOC JCOMM SOT VOS
16 SAWS: Ship-Based Infrastructure
17 SAWS: Drifting Weather Buoys Maintain a global 5x5 degree array of 1250 satellite-tracked surface drifting buoys to meet the need for an accurate and globally dense set of in-situ observations of mixed layer currents, sea surface temperature, atmospheric pressure, winds and salinity.
18 SAWS: Drifting Weather Buoys WMO/IOC JCOMMOPS DBCP GDP SAWS
19 SAWS: Drifting Weather Buoys
20 SAWS: Drifting Weather Buoys ~ 5.4 km
21 SAWS: Drifting Weather Buoys
22 SAWS: SST Smit et al., 2013
23 SAWS: SST Figure 2. (a) Interpolated summertime inshore in situ temperature data for the entire coast between measurement sites 1-87 (Port Nolloth to Sodwana Bay). These same data are also plotted in the lower panel (b) to further highlight the alongshore gradients. The middle and upper panels in (b) show the seasonal mean monthly in situ temperature for August and February respectively representing winter and summer. Smit et al., 2013
24 Thank You
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