|
Products
Data Sets
Publications
Protocols
Images
Contribution Series
CAP LTER Symposia
|
|
Average precipitation in June in Central Arizona
Identifier:335_1
Publication date:2007
Author(s):
Alexander Buyantuyev
Abstract:
The dataset is part of the effort to provide the most detailed climate data for CAPLTER and related projects. This dataset represents average monthly rainfall derived from spatial interpolation of daily rainfall data from a dense network of precipitation sensors for the period of 5 years (2000-2005).
Keywords:
Phoenix, Arizona, Sonoran Desert, caplter, Central Arizona Phoenix Longterm Ecological Research, urban, metropolitan area, climate, weather, rainfall, rain, precipitation, Geosciences, Climate Ecosystem Interactions, caplter created, gis, Project id 1, Project id 79
Temporal Coverage:
2000-02-01 - 2005-12-31
Geographic Coverage:
Geographic Description:Central Arizona Phoenix
Bounding Coordinates:
Longitude:-112.860109 to -111.487525
Latitude:33.894016 to 33.010982
Contact:
Data Manager,
Global Institute of Sustainability,Arizona State University,POB 875401,TEMPE
caplter.data@asu.edu
Methods used in producing this dataset:
Meteorological data acquisition and preprocessing
Precipitation data were obtained from different sources including the Flood Control Disctrict of Maricopa County (ALERT), the National Weather Service (NWS), the Arizona Meteorological Network (AZMET), and the Phoenix Real-time Instrumentation for Surface Meteorological Studies (PRISMS) Network. Instrument locations were first geocoded using the station descriptions from each network. Daily measurements were then aggregated to bi-weekly periods to match the temporal resolution of MODIS (The Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index (NDVI) images. MODIS is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites designed for global monitoring of key biophysical parameters including vegetation. Tables with aggregated precipitation were then joined to the shapefile of precipitaiton sensors.
Spatial interpolation
I performed ordinary kriging to create precipitaion surfaces. The maps were created using Geostatistical Analyst, the ArcGIS 9.1 extension. Spherical models were used in all semivariogram models and predictions were checked interactively using the built-in tools. Standard Error maps were also produced along with prediction surfaces that were all rasterized to a 250 meter resolution grid.
Temporal aggregations
Biweekly precipitation surfaces were aggregated to monthly time step. In turn monthly surfaces were summed up to derive annual precipitation grids. For each month I computed the average 6-year precipitaion. Finally the average annual precipitation was also computed for the period of 2000-2006.
Entities:
Raster: Band_1
download
Attributes:
Attribute:ObjectID
Description:Internal feature number.
Attribute:Value
Description:Amount of average monthly rainfall in millimeters
Measurement Unit:number
|
