9.4 National Climate Database

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Database Title	9.4 National Climate Database
Keywords Type1. Type 11.	Climate. Rainfall, temperature, sunshine, radiation, wind, meterological phenomena.
Abstract	This database stores a variety of climate information from climate stations around New Zealand as well as the Pacific and Antartica. Different climate stations report different parameters, with many just reporting rainfall. Approximately 3/5 of climate stations are closed and no longer reporting. There are many reasons for closure including increasing automation and increasing focus on weather forecasting versus long term data collection.
Geographical Coverage	New Zealand (primarily). Also sites in Antartica and the Pacific Islands.
Dataset start date.	Some records began in 1860's, some in the 1930's, and most in the 1960's. Computerization began in the mid 1960's.
Dataset end date.	Current.
Status/currency.	In progress.
Update frequency.	Ongoing.
Maintenance.	Nationally significant database funded through PGSF.

Technical Evaluation
Parameters- what is measured	Different parameters are measured at different sites. The suite of measured parameters are: cloud system earth temperature evaporation rate ice accretion on ships number of lightening bolts direction and speed of highest wind gust maximum, minimum and grass minimum extreme temperatures msl and station level pressure and change global diffuse and direction radiation precipitation amount and state of ground depth of fresh and total snow duration of bright sunshine direction and speed of wind near surface dry / dew temperature There are also observations of a variety of weather phenomena
Parameters- what is calculated	Totals, means and extremes for local month and year total rainfall - mm wet days - number of days with more than 1mm rain mean air temperature - celsius mean daily maximum air temperature - celsius mean daily minimum air temperature - celsius mean daily grass minimum temperature - celsius extreme maximum air temperature - celsius extreme minimum air temperature - celsius extreme grass minimum air temperature - celsius total sunshine- hours mean 5cm earth temperature - celsius mean 10cm earth temperature - celsius mean 20cm earth temperature - celsius mean 30cm earth temperature - celsius mean 100cm earth temperature - celsius mean daily wind run - km mean vapour pressure - hPa mean daily global radiation - MJ / sq m highest daily wind run - km total evaporation for sunken pan - mm total evaporation for raised pan - mm number of days of occurrence: thunder number of days of occurrence: ground frost number of days of occurrence: screen frost number of days of occurrence: gale number of days of occurrence: fog number of days of occurrence: hail number of days of occurrence: lightning number of days of occurrence: snow number of days of occurrence: snow lying mean MSL pressrue at 9am - hPa number of days of wind gusts >= 33 knots number of days of wind gusts >= 51 knots mean wind speed - m / sec Penman potential evapotranspiration - mm Priestly - Taylor PEM - mm Penman open water evaporation - mm Penman saturation deficit - hPa rain days - number of days with more than 0.1mm of rain maximum 1-day rainfall - mm mean cloud amount lowest maximum air temperature - celsius highest minimum air temperature - celsius wind - gust - highest speed - m / sec wind - gust - direction of highest speed - degrees mean 50cm earth temperature - celsius mean daily direct radiation - MJ / sq m mean daily diffuse radiation - MJ / sq m maximum 10-minute rainfall - mm maximum 20-minute rainfall - mm maximum 30-minute rainfall - mm maximum 1-hour rainfall - mm maximum 2-hour rainfall - mm maximum 6-hour rainfall - mm maximum 12-hour rainfall - mm maximum 24-hour rainfall - mm maximum 48-hour rainfall - mm maximum 72-hour rainfall - mm days of wind gust >= 24 knots - day standard deviation of daily mean temperature - celsius lowest daily mean temperature - celsius highest daily mean temperature - celsius mean 9am relative humidity - percent mean 9am temperature - celsius Normalised monthly and annual statistics for 30 year period
Methods used to measure parameters	Data comes from NIWA automated and manual climate stations and Meterological Service electronic data.
Scale of use.	Most data is collected hourly or daily. Some is collected at 10 minute intervals.
Number of records	There are 2,312 open climate stations which are still reporting and 3,761 closed stations that are no longer reporting.
GIS compatibility.	The climate stations are located using latitude and longitude grid references.
Available formats for users.	The data is on an Oracle database. NIWA is working on developing web access. Reports are prepared on request.
Access constraints.	Those who want to use data from the database need to be set up as users. There is a variable charge for external users who use (interpreted) data from the database. Reports prepared on request are charged for. There are staff to handle requests as well as a manual and a helpdesk for users.
Measurement Accuracy	To be completed by database manager.
Completeness of dataset	To be completed by database manager.
Positional accuracy	To be completed by database manager.
Database steward	NIWA
Database custodian	NIWA
Database custodian contact person	Allen Penney
Database custodian Contact Address Phone Fax Email	P.O. Box 14 901 Kilbirnie Wellington + 64 4 386 0300 + 64 4 386 0574 a.penney@niwa.co.nz
References	NIWA NZ Climate digest (produced monthly). Penney, A.C. 1999. Climate database (CLIDB) user's manual. Fourth edition (revised). NIWA Technical Report 59.
Date metadata record prepared.	October 1999
Author of metadata record.	Victoria Froude

Management Evaluation
Original purpose.	The database was primarily established for scientific research purposes. It was also intended that it would assist with weather forecasting.
Relationships with classification systems.	N/A
Relationships with other databases	The data from the database links to the Water Resource Archive also managed by NIWA.
Known relationships with proposed EPIP indicators.	Not known.
Database uses?	There are approximately 100 registered users. These include NIWA staff, other Crown Research Institutes, ESR, Universities, consultancies, BRANZ, Agriculture NZ, power companies. There are also many occasional requests.
Public awareness of the database	There is a large NIWA web page. A new public bulletin "The Climate Update" is being published monthly with the first issue being on 16 July 1999. Met Service refers people to this database.
Database strengths.	the database is a powerful one using Oracle the database has ISO 9002 certification data extends back to 1860's interactive web access is being developed
Database limitations.	Approximately 50% of the data is only on paper forms. This older data is being entered slowly into the electronic database as funds become available. It is often difficult to identify specific climate information for a specific time. This is because individual sites only record some data; some stations can be for a short term only; and some long term stations can be closed for various reasons. The analyses of long term trends in the data can be complicated because of the changing situations with climate stations (when they are open / closed; instrumentation changes, and changing environmental conditions around the station (eg. increase or removal of shading and shelter))

What are the Current and Emerging Uses of the Database for:
Assisting with determining historic state/baseline.	The database is primarily one of (recent) past climate. There are some difficulties with interpreting past data as, for example,. climate site conditions can change due to change in shading and shelter provided by vegetation and buildings.
Assisting with determining current state/baseline.	The database provides current climate (as opposed to weather) information.
Assisting with modeling possible future outcomes.	Intend to develop this.
Risk assessment.	Used to assess / identify climate risk, eg. drought.
Monitoring site selection and sample design.	N/A
Aggregating and reporting data locally, regionally or nationally.	Users determine how they want their data presented. As data is stored by station rather than region, or other administrative unit, it can be difficult to aggregate data because representative stations need to be selected.