An Integrated Meteorological Surface Observation System 

ByWan 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.

Integrated Meteorological Surface Observation System

108 Stesen Meteorologi Auksiliari

Central Data

Retrieval &Ingest Module

NetworkAnd

InstrumentMonitoring

Module

DataAggregation,

andQC

Module

ApplicationModule

SensorsSuite

AcquisitionElectronics

LoggingProcessing

QCTransmission

WAN(Internet)

CLIMATOLOGICAL DATABASE(MAKLIM)

FORECAST APPLICATIONSPORTAL

RESEARCH

User AccessSystem

ConfigurationData Viewing

MaintenanceEquipment

Non-VolatileStorage

WANInterface

&Communications

Equipment 1-minuteData

Repository

SYSTEM LAYOUT AND DATA FLOW

PowerSupply

Power Supply

Stabilised ACwith backup

Solar powerwith accessories

On-Site

Central

Data FromOther

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)

WANInterface

&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

Databasereal-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