An Integrated Meteorological Surface Observation System By Wan Mohd. Nazri Wan Daud Malaysian Meteorological Department Due to the increasing and evolving demands for local weather information the Malaysian Meteorological Department embarked on a program to integrate the diverse AWS and manual systems existing in the observing program. This process was started in 2008 starting with the installation of 108 new unmanned AWS stations culminating in the design and implementation of the server cluster which now acts as the end point for both manual and automatic stations be they manned Principal or unmanned climatological. Moreover meteorological surface observations associated with other systems such as Marine or GAW can now be included in this “first step” action plan. For the purposes of the project surface observations refers to terrestrial based in-situ (direct measurements) surface observing systems that measure the common near-surface atmospheric parameters. The system includes three main modules, two of which are new innovations used for the first time in any observing system. With the increasing demand for real-time data increases, the system has been designed to work with a myriad of communication methods and protocols.

Central Data Retrieval & Ingest Module Network And Instrument Monitoring Module Data Aggregation, and QC Module Application Module Sensors Suite Acquisition Electronics Logging Processing QC Transmission WAN (Internet) CLIMATOLOGICAL DATABASE (MAKLIM) FORECAST APPLICATIONS PORTAL RESEARCH User Access System Configuration Data Viewing Maintenance Equipment Non-Volatile Storage WAN Interface & Communications Equipment 1-minute Data Repository SYSTEM LAYOUT AND DATA FLOW Power Supply Power Supply Stabilised AC with backup Solar power with accessories On-Site Central Data From Other Systems National Integrated Surface Meteorological Observing System (NISMOS)

Communication breakdowns which are normal over cheaper GPRS networks, can cause breaks in data sets which would be flagged as missing or would have to be retrieved via manual downloads. These methods are costly. With the innovative data synchronization method over VPN all data is now available over the same link once communications resume. Central Data Retrieval & Ingest Module WAN (Internet) WAN Interface & Communications Equipment VPN Tunnel Real-time TCP Stream Keeps track of missing data due to comms break, and requests missing data when comms returns

QC2 HQC QC1 QC0 Database real-time & non real-time Real-time QC (use rule-set to find errors) Station Standards Data Retrieval in real time Non real-time QC (use rule-set to correct errors) Non real- time data Human QC (decision on data that auto QC is unable to correct) Quality Control of Meteorological Observations Data While timely data is important, the requirements for quality data is also a prerequisite. These requirements are handled by an innovative rule-set based quality control module which has the ability to accept data from both automatic as well manual sources. Therefore a single point of entry into the database allows for QC rules to be homogenous throughout the dataset whatever the temporal frequency of the dataset. The use of rule-sets enables differing rules for differing purposes and gives a better view of actual weather phenomena with the inclusion of range, temporal and spatial rules. Manually entered into database