Assessing the radiative impacts of precipitating clouds on winter surface air temperatures and land surface properties in general circulation models using observations

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>

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An ensemble of AMIP simulations with prescribed land surface temperatures

10.5194/gmd-2018-77 ◽

2018 ◽

Author(s):

Duncan Ackerley ◽

Robin Chadwick ◽

Dietmar Dommenget ◽

Paola Petrelli

Keyword(s):

Surface Temperature ◽

Land Surface ◽

General Circulation ◽

Global Climate ◽

General Circulation Models ◽

Solar Constant ◽

Surface Temperatures ◽

Co2 Concentrations ◽

Land Surface Temperatures ◽

Intercomparison Project

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

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The Canadian Earth System Model version 5 (CanESM5.0.3)

Geoscientific Model Development ◽

10.5194/gmd-12-4823-2019 ◽

2019 ◽

Vol 12 (11) ◽

pp. 4823-4873 ◽

Cited By ~ 58

Author(s):

Neil C. Swart ◽

Jason N. S. Cole ◽

Viatcheslav V. Kharin ◽

Mike Lazare ◽

John F. Scinocca ◽

...

Keyword(s):

Land Surface ◽

General Circulation ◽

Large Scale ◽

General Circulation Models ◽

Earth System Model ◽

System Model ◽

Historical Period ◽

Earth System ◽

Historical Climate ◽

Model Version

Abstract. The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization, and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large-scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral resolution equivalent roughly to 2.8∘) and ocean (nominally 1∘) general circulation models, a sea-ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada.

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Effect Of Eurasian Snow Cover On Summer Climate Of The Northern Hemisphere: A GCM Study

Annals of Glaciology ◽

10.1017/s0260305500009447 ◽

1990 ◽

Vol 14 ◽

pp. 364 ◽

Cited By ~ 1

Author(s):

Tetsuzo Yasunari ◽

Akio Kitoh ◽

Tatsushi Tokioka

Keyword(s):

Snow Cover ◽

Land Surface ◽

General Circulation ◽

Large Scale ◽

General Circulation Models ◽

Late Winter ◽

Hydrological Process ◽

Eurasian Snow Cover ◽

Eurasian Snow ◽

Snow Cover Extent

Observational studies have shown that Eurasian snow-cover anomalies during winter-through-spring seasons have a great effect on anomalies in atmospheric circulation and climate in the following summer season through snow albedo feedback (Hahn and Shukla, 1976; Dey and Bhanu Kumar, 1987). Morinaga and Yasunari (1987) have revealed that large-scale snow-cover extent over central Asia in late winter, which particularly has a great effect on the circulation over Eurasia in the following season, is closely related to the Eurasian pattern circulation (Wallace and Gutzler, 1981) in the beginning of winter. Some atmospheric general circulation models (GCM) have suggested that not only the albedo effect of the snow cover but also the snow-hydrological process are important in producing the atmospheric anomalies in the following seasons (Yeh and others, 1984; Barnett and others, 1988). However, more quantitative evaluations of these effects have not yet been examined. For example, it is not clear to what extent atmospheric anomalies are explained solely by snow-cover anomalies. Spatial and seasonal dependencies of these effects are supposed to be very large. Relative importance of snow cover over Tibetan Plateau should also be examined, particularly relevant to Asian summer monsoon anomalies. Moreover, these effects seem to be very sensitive to parameterizations of these physical processes (Yamazaki, 1988). This study focuses on these problems by using some versions of GCMs of the Meteorological Research Institute. The results include the evaluation of total snow-cover feedbacks as part of internal dynamics of climatic change from 12-year GCM integration, and of the effect of anomalous snow cover over Eurasia in late winter on land surface conditions and atmospheric circulations in the succeeding seasons.

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Intraurban Temperature Variability in Baltimore

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0232.1 ◽

2017 ◽

Vol 56 (1) ◽

pp. 159-171 ◽

Cited By ~ 10

Author(s):

Anna A. Scott ◽

Ben Zaitchik ◽

Darryn W. Waugh ◽

Katie O’Meara

Keyword(s):

Surface Properties ◽

Land Surface ◽

Low Cost ◽

Canopy Cover ◽

Tree Canopy ◽

Temperate Climate ◽

Weather Station ◽

Underserved Area ◽

Air Temperatures ◽

Tree Canopy Cover

AbstractHow much does minimum daily air temperature vary within neighborhoods exhibiting high land surface temperature (LST), and does this variability affect agreement with the nearest weather station? To answer these questions, a low-cost sensor network of 135 “iButton” thermometers was deployed for summer 2015 in Baltimore, Maryland (a midsized American city with a temperate climate), focusing on an underserved area that exhibits high LST from satellite imagery. The sensors were evaluated against commercial and NOAA/NWS stations and showed good agreement for daily minimum temperatures. Variability within the study site was small: mean minimum daily temperatures have a spatial standard deviation of 0.9°C, much smaller than the same measure for satellite-derived LST. The sensor-measured temperatures agree well with the NWS weather station in downtown Baltimore, with a mean difference for all measurements in time and space of 0.00°C; this agreement with the station is not found to be correlated with any meteorological variables with the exception of radiation. Surface properties are found to be important in determining spatial variability: vegetated or green spaces are observed to be 0.5°C cooler than areas dominated by impervious surfaces, and the presence of green space is found to be a more significant predictor of temperature than surface properties such as elevation. Other surface properties—albedo, tree-canopy cover, and distance to the nearest park—are not found to correlate significantly with air temperatures.

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Improving Parallel Performance of a Finite-Difference AGCM on Modern High-Performance Computers

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-13-00067.1 ◽

2014 ◽

Vol 31 (10) ◽

pp. 2157-2168 ◽

Cited By ~ 8

Author(s):

Li Liu ◽

Ruizhe Li ◽

Guangwen Yang ◽

Bin Wang ◽

Lijuan Li ◽

...

Keyword(s):

Finite Difference ◽

Land Surface ◽

General Circulation ◽

High Performance ◽

Rapid Development ◽

General Circulation Models ◽

Parallel Optimization ◽

Dynamical Core ◽

Parallel Efficiency ◽

Parallel Version

Abstract The rapid development of science and technology has enabled finer and finer resolutions in atmospheric general circulation models (AGCMs). Parallelization becomes progressively more critical as the resolution of AGCMs increases. This paper presents a new parallel version of the finite-difference Gridpoint Atmospheric Model of the Institute of Atmospheric Physics (IAP)–State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG; GAMIL) with various parallel optimization strategies, including two-dimensional hybrid parallel decomposition; hybrid parallel programming; parallel communications for coupling the physical packages, land surface, and dynamical core; and a cascading solution to the tridiagonal equations used in the dynamical core. The new parallel version under two different horizontal resolutions (1° and 0.25°) is evaluated. The new parallel version enables GAMIL to achieve higher parallel efficiency and utilize a greater number of CPU cores. GAMIL1° achieves 37.8% parallel efficiency using 960 CPU cores, while GAMIL0.25° achieves 57.5% parallel efficiency.

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