Monthly Average of Daily Maximum Near-Surface Air Temperature
units :
K
grid_mapping :
crs
standard_name :
air_temperature
height :
2 m
cell_methods :
time: maximum(interval: 24 hours);mean over days
_ChunkSizes :
[ 10 44 107]
[544864320 values with dtype=float32]
description :
Multivariate Adaptive Constructed Analogs (MACA) method, version 2.3,Dec 2013.
id :
MACAv2-METDATA
naming_authority :
edu.uidaho.reacch
Metadata_Conventions :
Unidata Dataset Discovery v1.0
Metadata_Link :
cdm_data_type :
FLOAT
title :
Monthly aggregation of downscaled daily meteorological data of Monthly Average of Daily Maximum Near-Surface Air Temperature from College of Global Change and Earth System Science, Beijing Normal University (BNU-ESM) using the run r1i1p1 of the historical scenario.
summary :
This archive contains monthly downscaled meteorological and hydrological projections for the Conterminous United States at 1/24-deg resolution. These monthly values are obtained by aggregating the daily values obtained from the downscaling using the Multivariate Adaptive Constructed Analogs (MACA, Abatzoglou, 2012) statistical downscaling method with the METDATA (Abatzoglou,2013) training dataset. The downscaled meteorological variables are maximum/minimum temperature(tasmax/tasmin), maximum/minimum relative humidity (rhsmax/rhsmin),precipitation amount(pr), downward shortwave solar radiation(rsds), eastward wind(uas), northward wind(vas), and specific humidity(huss). The downscaling is based on the 365-day model outputs from different global climate models (GCMs) from Phase 5 of the Coupled Model Inter-comparison Project (CMIP3) utlizing the historical (1950-2005) and future RCP4.5/8.5(2006-2099) scenarios.
keywords :
monthly, precipitation, maximum temperature, minimum temperature, downward shortwave solar radiation, specific humidity, wind velocity, CMIP5, Gridded Meteorological Data