Identification

Title

Use of daily station observations to produce high-resolution gridded probabilistic precipitation and temperature time series for the Hawaiian Islands

Abstract

It is a major challenge to develop gridded precipitation and temperature estimates that adequately resolve the extreme spatial gradients present in the Hawaiian Islands. The challenge is particularly pronounced because the available station networks are irregularly spaced and sparse, creating large uncertainties in gridded spatial meteorological estimates. Here a 100-member, daily ensemble of precipitation and temperature estimates over the Hawaiian Islands for the period 1990-2014 at 1-km grid resolution is developed. First, an intermediary ensemble estimate of the monthly climatological precipitation and temperature is created, and those climatological surfaces are used to inform daily anomaly interpolation. This climatologically aided interpolation (CAI) method extends our initial ensemble system developed for the continental United States. This study demonstrates that direct interpolation of daily precipitation values is inferior to the CAI methodology, particularly over longer time periods (from years to decades). Daily interpolation performs better for short time periods (e.g., 1 month or less) or when the precipitation distribution substantially diverges from climatology. The CAI ensemble is able to reproduce observed precipitation and temperature patterns, including precipitation occurrence. Leave-one-out cross-validation results illustrate that the ensemble has 1) minimal bias for precipitation and temperature; 2) a mean absolute error of 2.5 mm day(-1), 1.0 K, and 2.2 K for precipitation and mean and diurnal temperature, respectively; 3) a mean absolute error of 3.3 mm day(-1) for the standard deviation of precipitation; and 4) nearly unbiased probability distributions across multiple thresholds of precipitation intensity. Additionally, the ensemble provides estimates of uncertainty across the distributions with increasing uncertainty for higher percentiles.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7s185hf

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2019-03-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Copyright 2019 American Meteorological Society.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata date

2023-08-18T19:17:57.929311

Metadata language

eng; USA