BILO Climate Relative Error Grids V01

## **Abstract** \n\nThe dataset was derived by the Bioregional Assessment Programme from multiple datasets. The source dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.\n\nThe dataset has following components:\n\n\n\n1. average monthly grids of BAWAP rain, Tmax and Tmin of last 3 decades (1980- 2009), and every decade (1980-1989, 1990-1999, 2000 - 2009)\n\n\n\nThis includes the climate variable grids (rainfall and temperature), associated rmse grids and relative error grids.\n\n\n\n2. Max, Min, Mean and Stdev values of the average grid, rmse grid and relative error grid of last 3 decades for each BA subregion.\n\n## **Purpose** \n\nTo display the climatology of BA subregions\n\n## **Dataset History** \n\nThis dataset was created from BoM 5km grids using IDL scripts to create mean monthly and decadal and longterm relative errors for each subregion.\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2015) BILO Climate Relative Error Grids V01. Bioregional Assessment Derived Dataset. Viewed 10 December 2018, http://data.bioregionalassessments.gov.au/dataset/c0c139f5-3648-4e0f-9acf-a884b7cc859b.\n\n## **Dataset Ancestors** \n\n* **Derived From** [Bioregional Assessment areas v02](https://data.gov.au/data/dataset/e414b1b3-c42e-42e9-9cc4-2093054aa35f)\n\n* **Derived From** [Natural Resource Management (NRM) Regions 2010](https://data.gov.au/data/dataset/1d54e38f-4051-4f0c-a350-c7dbd8eba65b)\n\n* **Derived From** [BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012](https://data.gov.au/data/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14)\n\n* **Derived From** [Bioregional Assessment areas v01](https://data.gov.au/data/dataset/0fd0d820-30b3-451f-a126-a50040426999)\n\n* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)\n\n* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)\n\n* **Derived From** [NSW Catchment Management Authority Boundaries 20130917](https://data.gov.au/data/dataset/0dc4272e-c081-4ed4-9645-aa336ffacd85)\n\n* **Derived From** [Geological Provinces - Full Extent](https://data.gov.au/data/dataset/0a064b3b-2a1e-4672-80d9-03333be67aad)\n\n

**摘要**
本数据集由生物区域评估项目（Bioregional Assessment Programme）基于多源数据集衍生得到。本元数据声明的「谱系（Lineage）」字段已标注源数据集信息，而生成该衍生数据集的具体处理流程则记载于元数据的「历史（History）」字段中。

本数据集包含以下组成部分：
1. 近30年（1980-2009年）及各年代（1980-1989年、1990-1999年、2000-2009年）的BAWAP降雨、最高气温（Tmax）与最低气温（Tmin）月度平均格网数据。该部分包含气候变量格网（降雨与气温）、配套的均方根误差（Root Mean Square Error, RMSE）格网以及相对误差格网。
2. 各生物地理亚区（BA subregion）近30年的平均格网、RMSE格网与相对误差格网的最大值、最小值、平均值以及标准差（Standard Deviation, Stdev）数值。

**用途**
用于展示生物地理亚区的气候学特征。

**数据集历史**
本数据集基于澳大利亚气象局（Bureau of Meteorology, BoM）的5公里分辨率格网数据制作，通过交互式数据语言（Interactive Data Language, IDL）脚本生成各亚区的月度、年代际及长期相对误差数据。

**数据集引用**
生物区域评估项目（Bioregional Assessment Programme）(2015) 《BILO气候相对误差格网V01》，生物区域评估衍生数据集。查阅日期：2018年12月10日，来源链接：http://data.bioregionalassessments.gov.au/dataset/c0c139f5-3648-4e0f-9acf-a884b7cc859b。

**数据集溯源**
* **数据溯源自** [生物区域评估区域v02](https://data.gov.au/data/dataset/e414b1b3-c42e-42e9-9cc4-2093054aa35f)
* **数据溯源自** [2010年自然资源管理区域（Natural Resource Management Regions 2010）](https://data.gov.au/data/dataset/1d54e38f-4051-4f0c-a350-c7dbd8eba65b)
* **数据溯源自** [BILO格网气候数据：1900-2012年逐年逐日气候数据集](https://data.gov.au/data/dataset/7aaf0621-a0e5-4b01-9333-53ebcb1f1c14)
* **数据溯源自** [生物区域评估区域v01](https://data.gov.au/data/dataset/0fd0d820-30b3-451f-a126-a50040426999)
* **数据溯源自** [GEODATA TOPO 250K系列3 文件地理数据库格式（.gdb）](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)
* **数据溯源自** [GEODATA TOPO 250K系列3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)
* **数据溯源自** [新南威尔士州流域管理局边界 20130917](https://data.gov.au/data/dataset/0dc4272e-c081-4ed4-9645-aa336ffacd85)
* **数据溯源自** [全域地质省](https://data.gov.au/data/dataset/0a064b3b-2a1e-4672-80d9-03333be67aad)