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Title: Evaluation of Greenland near surface air temperature datasets

Abstract

Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT from different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.

Authors:
ORCiD logo [1];  [1]
  1. Univ. of Arizona, Tucson, AZ (United States). Department of Hydrology and Atmospheric Sciences
Publication Date:
Research Org.:
Univ. of Arizona, Tucson, AZ (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1367939
Alternate Identifier(s):
OSTI ID: 1429318
Grant/Contract Number:
SC0016533
Resource Type:
Journal Article: Published Article
Journal Name:
The Cryosphere (Online)
Additional Journal Information:
Journal Name: The Cryosphere (Online); Journal Volume: 11; Journal Issue: 4; Journal ID: ISSN 1994-0424
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Reeves Eyre, J. E. Jack, and Zeng, Xubin. Evaluation of Greenland near surface air temperature datasets. United States: N. p., 2017. Web. doi:10.5194/tc-11-1591-2017.
Reeves Eyre, J. E. Jack, & Zeng, Xubin. Evaluation of Greenland near surface air temperature datasets. United States. doi:10.5194/tc-11-1591-2017.
Reeves Eyre, J. E. Jack, and Zeng, Xubin. Wed . "Evaluation of Greenland near surface air temperature datasets". United States. doi:10.5194/tc-11-1591-2017.
@article{osti_1367939,
title = {Evaluation of Greenland near surface air temperature datasets},
author = {Reeves Eyre, J. E. Jack and Zeng, Xubin},
abstractNote = {Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT from different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.},
doi = {10.5194/tc-11-1591-2017},
journal = {The Cryosphere (Online)},
number = 4,
volume = 11,
place = {United States},
year = {Wed Jul 05 00:00:00 EDT 2017},
month = {Wed Jul 05 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.5194/tc-11-1591-2017

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  • Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements (~1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2°C in all months. Ice sheet-average annual mean SATmore » from different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach ~5°C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.« less
  • In central Greenland, near-surface air temperatures can be estimated from long-term satellite passive microwave brightness temperatures supported by limited air-temperature data from automatic weather stations. In this region, brightness temperature depends on snow emissivity, which varies slowly over time, and on snow temperature, which varies more rapidly and is controlled by air temperature. The air temperature and brightness temperature data define an emissivity trend which can be modeled as an annual sinusoid. An air temperature trend can then be derived from the brightness temperature and modeled emissivity information. The estimated air temperature values represent an integrated near-surface value that definesmore » the overall temperature trend at the Greenland Summit. The modeled emissivity cycle allows daily-average air temperatures to be estimated across significant gaps in weather station records, as well as quality control of their temperature data. The technique also generates annual trends of emissivity which can be used to evaluate radiative transfer models of microwave emissivity from dry firn.« less
  • Simulations with the UCLA atmospheric general circulation model (AGCM) using two different global sea surface temperature (SST) datasets for January 1979 are compared. One of these datasets is based on COADS (SSTs) at locations where they are ship reports, and climatology elsewhere; the other is derived from measurements by instruments onboard NOAA satellites. In the former dataset (COADS SST), data are concentrated along shipping routes in the Northern Hemisphere; in the latter dataset (HIRS SST), data cover the global domain. Ensembles of five 30-day mean fields are obtained from integrations performed in the perpetual-January mode. The results are presented asmore » anomalies, that is, departures of each ensemble mean from that produced in a control simulation with climatological SSTs. Large differences are found between the anomalies obtained using COADS and HIRS SSTs, even in the Northern Hemisphere when the datasets are most similar to each other. The internal variability of the circulation in the control simulation and the simulated atmospheric response to anomalous forcings appear to be linked in that the pattern of geopotential height anomalies obtained using COADS SSTs resembles the first empirical orthogonal function (EOF 1) in the control simulation. The corresponding pattern obtained using HIRS SSTs is substantially different and somewhat resembles EOF 2 in the sector from central North America to central Asia. 16 refs., 7 figs.« less