Details:

Journal Title:
Geoscientific Model Development
Personal Author:
Brunke, Michael A. ; Cassano, John J. ; Dawson, Nicholas ; DuVivier, Alice K. ; Gutowski Jr., William J. ; ... More +
Brunke, Michael A. ; Cassano, John J. ; Dawson, Nicholas ; DuVivier, Alice K. ; Gutowski Jr., William J. ; Hamman, Joseph ; Maslowski, Wieslaw ; Nijssen, Bart ; Reeves Eyre, J. E. Jack ; Renteria, José C. ; Roberts, Andrew ; Zeng, Xubin Less -
NOAA Program & Office:
CIRES (Cooperative Institute for Research in Environmental Sciences)
Description:
The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere–ocean–sea ice–land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990–2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea ice–atmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do.
Keywords:
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Atmospheric Science Mathematical Models
Source:
Geosci. Model Dev., 11, 4817–4841, 2018
DOI:
https://doi.org/10.5194/gmd-11-4817-2018
Document Type:
Journal Article
Rights Information:
CC BY
Compliance:
Submitted
Main Document Checksum:
[+]
urn:sha256:7b230c5efb3a9865c846deec678ac5488bdedcbb9816093faf15f6bef3368d4e
Download URL:
https://repository.library.noaa.gov/view/noaa/26415/noaa_26415_DS1.pdf
File Type:

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