scholarly journals A Technique for Dynamically Downscaling Daily-Averaged GCM Datasets Using the Conformal Cubic Atmospheric Model

2011 ◽  
Vol 139 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Marcus Thatcher ◽  
John L. McGregor
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Coupled Model ◽  
Circulation Model ◽  
Interpolation Formula ◽  
Atmospheric Model ◽  
Order Estimate ◽  
Climate Projections ◽  
Coupled Models ◽  
Selective Filter

Abstract In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.

scholarly journals Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change

2016 ◽  
Vol 7 (3) ◽  
pp. 627-647 ◽  
Author(s):  
Minchao Wu ◽  
Guy Schurgers ◽  
Markku Rummukainen ◽  
Benjamin Smith ◽  
Patrick Samuelsson ◽  
...  
Keyword(s):  
Surface Energy ◽  
General Circulation ◽  
Hydrological Cycle ◽  
Regional Climate ◽  
Circulation Model ◽  
Future Climate ◽  
Tree Cover ◽  
Future Climate Change ◽  
Climate Projections ◽  
Area Index

Abstract. Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive vegetation–atmosphere coupling to investigate the potential role of vegetation-mediated biophysical feedbacks on climate dynamics in Africa in an RCP8.5-based future climate scenario. The model was applied at high resolution (0.44 × 0.44°) for the CORDEX-Africa domain with boundary conditions from the CanESM2 general circulation model. We found that increased tree cover and leaf-area index (LAI) associated with a CO2 and climate-driven increase in net primary productivity, particularly over subtropical savannah areas, not only imposed important local effect on the regional climate by altering surface energy fluxes but also resulted in remote effects over central Africa by modulating the land–ocean temperature contrast, Atlantic Walker circulation and moisture inflow feeding the central African tropical rainforest region with precipitation. The vegetation-mediated feedbacks were in general negative with respect to temperature, dampening the warming trend simulated in the absence of feedbacks, and positive with respect to precipitation, enhancing rainfall reduction over the rainforest areas. Our results highlight the importance of accounting for vegetation–atmosphere interactions in climate projections for tropical and subtropical Africa.

Sensitivity of the Aerosol Indirect Effect to Subgrid Variability in the Cloud Parameterization of the GFDL Atmosphere General Circulation Model AM3

2011 ◽  
Vol 24 (13) ◽  
pp. 3145-3160 ◽  
Author(s):  
Jean-Christophe Golaz ◽  
Marc Salzmann ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Yi Ming ◽  
...  
Keyword(s):  
General Circulation Model ◽  
Indirect Effect ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Radiation Balance ◽  
Cloud Drop ◽  
Aerosol Indirect Effect ◽  
Alternate Model

Abstract The recently developed GFDL Atmospheric Model version 3 (AM3), an atmospheric general circulation model (GCM), incorporates a prognostic treatment of cloud drop number to simulate the aerosol indirect effect. Since cloud drop activation depends on cloud-scale vertical velocities, which are not reproduced in present-day GCMs, additional assumptions on the subgrid variability are required to implement a local activation parameterization into a GCM. This paper describes the subgrid activation assumptions in AM3 and explores sensitivities by constructing alternate configurations. These alternate model configurations exhibit only small differences in their present-day climatology. However, the total anthropogenic radiative flux perturbation (RFP) between present-day and preindustrial conditions varies by ±50% from the reference, because of a large difference in the magnitude of the aerosol indirect effect. The spread in RFP does not originate directly from the subgrid assumptions but indirectly through the cloud retuning necessary to maintain a realistic radiation balance. In particular, the paper shows a linear correlation between the choice of autoconversion threshold radius and the RFP. Climate sensitivity changes only minimally between the reference and alternate configurations. If implemented in a fully coupled model, these alternate configurations would therefore likely produce substantially different warming from preindustrial to present day.

scholarly journals The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere

2020 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Adriana Sima
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Stratospheric Temperature ◽  
Linear Behaviour ◽  
Intercomparison Project ◽  
Stratospheric Cooling ◽  
The Uk

Abstract. We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is most appropriate where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data is available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small. From kernels available in the literature we recommend three kernels for adjustment calculations to CO2 and well-mixed greenhouse gas perturbations based on their stratospheric resolution: HadGEM3-GA7.1, ECMWF-Oslo, and ECHAM6. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

scholarly journals The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere

2020 ◽  
Vol 12 (3) ◽  
pp. 2157-2168 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Adriana Sima
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Temperature Response ◽  
Coupled Model ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Stratospheric Temperature ◽  
Linear Behaviour ◽  
Stratospheric Cooling ◽  
The Uk

Abstract. We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

scholarly journals Evaluation of Weather Noise and Its Role in Climate Model Simulations*

2013 ◽  
Vol 26 (11) ◽  
pp. 3766-3784 ◽  
Author(s):  
Hua Chen ◽  
Edwin K. Schneider ◽  
Ben P. Kirtman ◽  
Ioana Colfescu
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Forced Response ◽  
Destructive Interference ◽  
Model Framework ◽  
Climate System Model ◽  
Model Simulations ◽  
Weather Noise

Abstract The relationship between coupled atmosphere–ocean general circulation model simulations and uncoupled simulations made with specified SST and sea ice is investigated using the Community Climate System Model, version 3. Experiments are carried out in a perfect model framework. Two closely related questions are investigated: 1) whether the statistics of the atmospheric weather noise in the atmospheric model are the same as in the coupled model, and 2) whether the atmospheric model reproduces the SST-forced response of the coupled model. The weather noise in both the coupled and uncoupled simulations is found by removing the forced response, as determined from the uncoupled ensemble, from the atmospheric field. The weather-noise variance is generally not distinguishable between the coupled and uncoupled simulations. However, variances of the total fields differ between the coupled and uncoupled simulations, since there is constructive or destructive interference between the SST-forced response and weather noise in the coupled model but no correlation between the SST-forced and weather-noise components in the uncoupled model simulations. Direct regression estimates of the forced response show little difference between the coupled and uncoupled simulations. Differences in local correlations are explained by weather noise because weather noise forces SST in the coupled simulation only. The results demonstrate and explain an important intrinsic difference in precipitation statistics between the coupled and uncoupled simulations. This difference could have consequences for the design of dynamical downscaling experiments and for tuning general circulation models.

scholarly journals Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state

2020 ◽  
Vol 13 (11) ◽  
pp. 5191-5209
Author(s):  
Yingxia Gao ◽  
Nicholas P. Klingaman ◽  
Charlotte A. DeMott ◽  
Pang-Chi Hsu
Keyword(s):  
General Circulation ◽  
Intraseasonal Oscillation ◽  
Phase Relationship ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Boreal Summer ◽  
Coupled Models ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Taylor Diagram ◽  
Mean State

Abstract. The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations of the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, referred to as SPA throughout). The coupled configuration is constrained to either observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean-state biases on the BSISO. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Prescribing the 31 d smoothed sea surface temperature (SST) from the SPK simulation in SPA worsens the overestimated BSISO variance. In both coupled models, the phase relationship between intraseasonal rainfall and SST is well captured. This suggests that air–sea coupling improves the amplitude of simulated BSISO and contributes to the propagation of convection. Constraining SPK to the SPCCSM3 mean state also reduces the overestimated BSISO variability but weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a 1-month delay to the BSISO seasonal cycle compared to SPK with the observed ocean mean state, which matches well with observation. Based on a Taylor diagram, both air–sea coupling and SPCCSM3 mean-state SST biases generally lead to higher simulated BSISO fidelity, largely due to their abilities to suppress the overestimated subtropical BSISO variance.

scholarly journals Estimating the Continental Response to Global Warming Using Pattern-Scaled Sea Surface Temperatures and Sea Ice

2016 ◽  
Vol 29 (24) ◽  
pp. 9125-9139 ◽  
Author(s):  
Adeline Bichet ◽  
Paul J. Kushner ◽  
Lawrence Mudryk
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
General Circulation ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Climate Projections ◽  
Western Boundary ◽  
Sea Ice Concentration ◽  
Continental Climate

Abstract Better constraining the continental climate response to anthropogenic forcing is essential to improve climate projections. In this study, pattern scaling is used to extract, from observations, the patterned response of sea surface temperature (SST) and sea ice concentration (SICE) to anthropogenically dominated long-term global warming. The SST response pattern includes a warming of the tropical Indian Ocean, the high northern latitudes, and the western boundary currents. The SICE pattern shows seasonal variations of the main locations of sea ice loss. These SST–SICE response patterns are used to drive an ensemble of an atmospheric general circulation model, the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), over the period 1980–2010 along with a standard AMIP ensemble using observed SST—SICE. The simulations enable attribution of a variety of observed trends of continental climate to global warming. On the one hand, the warming trends observed in all seasons across the entire Northern Hemisphere extratropics result from global warming, as does the snow loss observed over the northern midlatitudes and northwestern Eurasia. On the other hand, 1980–2010 precipitation trends observed in winter over North America and in summer over Africa result from the recent decreasing phase of the Pacific decadal oscillation and the recent increasing phase of the Atlantic multidecadal oscillation, respectively, which are not part of the global warming signal. The method holds promise for near-term decadal climate prediction but as currently framed cannot distinguish regional signals associated with oceanic internal variability from aerosol forcing and other sources of short-term forcing.

scholarly journals Links between Tropical Pacific SST and Cholera Incidence in Bangladesh: Role of the Eastern and Central Tropical Pacific

2008 ◽  
Vol 21 (18) ◽  
pp. 4647-4663 ◽  
Author(s):  
Benjamin A. Cash ◽  
Xavier Rodó ◽  
James L. Kinter
Keyword(s):  
El Niño ◽  
General Circulation ◽  
Physical Mechanism ◽  
El Nino ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Circulation Model ◽  
Tropical Pacific ◽  
Bacterial Disease ◽  
Monsoon Circulation

Abstract Recent studies arising from both statistical analysis and dynamical disease models indicate that there is a link between incidence of cholera, a paradigmatic waterborne bacterial disease (WBD) endemic to Bangladesh, and the El Niño–Southern Oscillation (ENSO). However, a physical mechanism explaining this relationship has not yet been established. A regionally coupled, or “pacemaker,” configuration of the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model is used to investigate links between sea surface temperature in the central and eastern tropical Pacific and the regional climate of Bangladesh. It is found that enhanced precipitation tends to follow winter El Niño events in both the model and observations, providing a plausible physical mechanism by which ENSO could influence cholera in Bangladesh. The enhanced precipitation in the model arises from a modification of the summer monsoon circulation over India and Bangladesh. Westerly wind anomalies over land to the west of Bangladesh lead to increased convergence in the zonal wind field and hence increased moisture convergence and rainfall. This change in circulation results from the tropics-wide warming in the model following a winter El Niño event. These results suggest that improved forecasting of cholera incidence may be possible through the use of climate predictions.

scholarly journals Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Climate Model ◽  
Time Window ◽  
Coupled Model ◽  
Circulation Model ◽  
Scale Interactions ◽  
Climate Signals ◽  
Coupled Data Assimilation ◽  
Climate Analysis

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

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