scholarly journals The New GFDL Global Atmosphere and Land Model AM2–LM2: Evaluation with Prescribed SST Simulations

2004 ◽  
Vol 17 (24) ◽  
pp. 4641-4673 ◽  
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Stomatal Resistance ◽  
Cold Bias ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Latent Heat Storage ◽  
Reliable Assessment ◽  
And Performance

Abstract The configuration and performance of a new global atmosphere and land model for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2–LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to E1 Niño– Southern Oscillation (ENSO). One AM2–LM2 integration was performed according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2–LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2– LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden–Julian oscillation. An ensemble of 10 AM2–LM2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2–LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO.

Korea Institute of Ocean Science & Technology Earth System Model and its simulation characteristics

2020 ◽  
Author(s):  
Young Ho Kim ◽  
Gyundo Pak ◽  
Yign Noh ◽  
Myong-In Lee ◽  
Sang-Wook Yeh ◽  
...  
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Atmospheric Temperature ◽  
Earth System Model ◽  
System Model ◽  
Superior Performance ◽  
Cold Bias ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Earth System ◽  
Ocean Science

<p>In our presentation, we will show the performance of a new earth system model developed at the Korea Institute of Ocean Science and Technology (KIOST), called the KIOST-ESM. The KIOST-ESM is based on a low-resolution version of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.5. The main changes made to the base model include using new cumulus convection and ocean mixed layer parameterization schemes, which improve the model fidelity significantly. In addition, the KIOST-ESM adopts dynamic vegetation and new soil respiration schemes in its land model component. The performance of the KIOST-ESM was assessed in pre-industrial and historical simulations that are made as part of its participation into Climate Model Intercomparison Project phase 6. The response of the earth system to increases in greenhouse gas concentrations were analyzed in the ScenarioMIP simulations. The KIOST-ESM exhibited superior performance compared to the base model in terms of the mean sea surface temperature over the Southern Ocean and over the cold tongue in the tropical Pacific. The KIOST-ESM can also simulate the dominant tropical variability in the intraseasonal (Madden-Julian Oscillation) and interannual (El Niño-Southern Oscillation) timescales more realistically than the base model. On the other hand, like many other contemporary ESMs, the KIOST-ESM showed notable cold bias in the Northern Hemisphere, and the so-called double-Intertropical Convergence Zone bias remains. The ScenarioMIP results confirm the global average surface atmospheric temperature responds to the CO<sub>2</sub> concentration.</p>

scholarly journals The Effect of a Well-Resolved Stratosphere on Surface Climate: Differences between CMIP5 Simulations with High and Low Top Versions of the Met Office Climate Model

2012 ◽  
Vol 25 (20) ◽  
pp. 7083-7099 ◽  
Author(s):  
S. C. Hardiman ◽  
N. Butchart ◽  
T. J. Hinton ◽  
S. M. Osprey ◽  
L. J. Gray
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Circulation Model ◽  
Climate Simulation ◽  
Reanalysis Dataset ◽  
Quasi Biennial Oscillation ◽  
Surface Climate ◽  
The Impact

Abstract The importance of using a general circulation model that includes a well-resolved stratosphere for climate simulations, and particularly the influence this has on surface climate, is investigated. High top model simulations are run with the Met Office Unified Model for the Coupled Model Intercomparison Project Phase 5 (CMIP5). These simulations are compared to equivalent simulations run using a low top model differing only in vertical extent and vertical resolution above 15 km. The period 1960–2002 is analyzed and compared to observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Long-term climatology, variability, and trends in surface temperature and sea ice, along with the variability of the annular mode index, are found to be insensitive to the addition of a well-resolved stratosphere. The inclusion of a well-resolved stratosphere, however, does improve the impact of atmospheric teleconnections on surface climate, in particular the response to El Niño–Southern Oscillation, the quasi-biennial oscillation, and midwinter stratospheric sudden warmings (i.e., zonal mean wind reversals in the middle stratosphere). Thus, including a well-represented stratosphere could improve climate simulation on intraseasonal to interannual time scales.

The Role of Mesoscale Eddies in the Rectification of the Southern Ocean Response to Climate Change

2010 ◽  
Vol 40 (7) ◽  
pp. 1539-1557 ◽  
Author(s):  
Riccardo Farneti ◽  
Thomas L. Delworth ◽  
Anthony J. Rosati ◽  
Stephen M. Griffies ◽  
Fanrong Zeng
Keyword(s):  
Climate Change ◽  
Southern Ocean ◽  
Climate Model ◽  
Coupled Model ◽  
Ekman Transport ◽  
Dynamical Response ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Climate Change Scenarios ◽  
Residual Circulation ◽  
Atmospheric Changes

Abstract Simulations from a fine-resolution global coupled model, the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.4 (CM2.4), are presented, and the results are compared with a coarse version of the same coupled model, CM2.1, under idealized climate change scenarios. A particular focus is given to the dynamical response of the Southern Ocean and the role played by the eddies—parameterized or permitted—in setting the residual circulation and meridional density structure. Compared to the case in which eddies are parameterized and consistent with recent observational and idealized modeling studies, the eddy-permitting integrations of CM2.4 show that eddy activity is greatly energized with increasing mechanical and buoyancy forcings, buffering the ocean to atmospheric changes, and the magnitude of the residual oceanic circulation response is thus greatly reduced. Although compensation is far from being perfect, changes in poleward eddy fluxes partially compensate for the enhanced equatorward Ekman transport, leading to weak modifications in local isopycnal slopes, transport by the Antarctic Circumpolar Current, and overturning circulation. Since the presence of active ocean eddy dynamics buffers the oceanic response to atmospheric changes, the associated atmospheric response to those reduced ocean changes is also weakened. Further, it is hypothesized that present numerical approaches for the parameterization of eddy-induced transports could be too restrictive and prevent coarse-resolution models from faithfully representing the eddy response to variability and change in the forcing fields.

scholarly journals The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations

2011 ◽  
Vol 24 (13) ◽  
pp. 3520-3544 ◽  
Author(s):  
Stephen M. Griffies ◽  
Michael Winton ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Stephanie M. Downes ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Atmospheric Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate Indices ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Coupled Climate Model

Abstract This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.

Did tropical precipitation improve in CMIP6 simulations?

2020 ◽  
Author(s):  
Stephanie Fiedler ◽  
Traute Crueger ◽  
Roberta D’Agostino ◽  
Karsten Peters ◽  
Tobias Becker ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Internal Variability ◽  
Atmospheric Composition ◽  
Tropical Precipitation ◽  
General Aspects

<p>Climate models are known to have biases in tropical precipitation. We assessed to what extent simulations of tropical precipitation have improved in the new Coupled Model Intercomparison Project (CMIP) phase six, using state-of-the-art observational products and model results from the earlier CMIP phases three and five. We characterize tropical precipitation with different well-established metrics. Our assessment includes (1) general aspects of the mean climatology like precipitation associated with the Intertropical Convergence Zone and shallow cloud regimes in the tropics, (2) solar radiative effects including the summer monsoons and the time of occurrence of tropical precipitation in the course of the day, (3) modes of internal variability such as the Madden-Julian Oscillation and the El Niño Southern Oscillation, and (4) changes in the course of the 20th century. The results point to improvements of CMIP6 models for some metrics, e.g., the occurrence of drizzle events and consecutive dry days. However, no improvements of CMIP6 models are identified for other aspects of tropical precipitation. These include the area and intensity of the global summer monsoon as well as the diurnal cycle of the tropical precipitation amount, frequency and intensity.</p><p>All our metrics taken together, CMIP6 models show no systematic improvement of tropical precipitation across different temporal and spatial scales. The model biases in the spatial distribution of tropical precipitation are typically larger than the changes associated with anthropogenic warming. Given the pace of climate change as compared to the pace of climate model improvements, we suggest to use novel modeling approaches to understand the responseof tropical precipitation to changes in atmospheric composition.</p>

Beyond Weather Time-Scale Prediction for Hurricane Sandy and Super Typhoon Haiyan in a Global Climate Model

2015 ◽  
Vol 143 (2) ◽  
pp. 524-535 ◽  
Author(s):  
Baoqiang Xiang ◽  
Shian-Jiann Lin ◽  
Ming Zhao ◽  
Shaoqing Zhang ◽  
Gabriel Vecchi ◽  
...  
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
The Philippines ◽  
Hurricane Sandy ◽  
False Alarms ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Super Typhoon

Abstract While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs: Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden–Julian oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential of using the GFDL coupled model for extended-range predictions of TCs.

scholarly journals The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2)

2020 ◽  
Vol 35 (4) ◽  
pp. 1317-1343 ◽  
Author(s):  
Hai Lin ◽  
William J. Merryfield ◽  
Ryan Muncaster ◽  
Gregory C. Smith ◽  
Marko Markovic ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Southern Oscillation ◽  
Weather Prediction ◽  
Coupled Model ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Boreal Winter ◽  
Prediction System ◽  
Sea Ice Concentration

AbstractThe second version of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2) was implemented operationally at Environment and Climate Change Canada (ECCC) in July 2019. Like its predecessors, CanSIPSv2 applies a multimodel ensemble approach with two coupled atmosphere–ocean models, CanCM4i and GEM-NEMO. While CanCM4i is a climate model, which is upgraded from CanCM4 of the previous CanSIPSv1 with improved sea ice initialization, GEM-NEMO is a newly developed numerical weather prediction (NWP)-based global atmosphere–ocean coupled model. In this paper, CanSIPSv2 is introduced, and its performance is assessed based on the reforecast of 30 years from 1981 to 2010, with 10 ensemble members of 12-month integrations for each model. Ensemble seasonal forecast skill of 2-m air temperature, 500-hPa geopotential height, precipitation rate, sea surface temperature, and sea ice concentration is assessed. Verification is also performed for the Niño-3.4, the Pacific–North American pattern (PNA), the North Atlantic Oscillation (NAO), and the Madden–Julian oscillation (MJO) indices. It is found that CanSIPSv2 outperforms the previous CanSIPSv1 system in many aspects. Atmospheric teleconnections associated with the El Niño–Southern Oscillation (ENSO) are reasonably well captured by the two CanSIPSv2 models, and a large part of the seasonal forecast skill in boreal winter can be attributed to the ENSO impact. The two models are also able to simulate the Northern Hemisphere teleconnection associated with the tropical MJO, which likely provides another source of skill on the subseasonal to seasonal time scale.

Distributions of Tropical Precipitation Cluster Power and Their Changes under Global Warming. Part II: Long-Term Time Dependence in Coupled Model Intercomparison Project Phase 5 Models

2017 ◽  
Vol 30 (20) ◽  
pp. 8045-8059 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Rain Rate ◽  
Climate Model ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Department Of Energy ◽  
Model Intercomparison ◽  
Intense Storm ◽  
Intercomparison Project

Abstract Distributions of precipitation cluster power (latent heat release rate integrated over contiguous precipitating pixels) are examined in 1°–2°-resolution members of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate model ensemble. These approximately reproduce the power-law range and large event cutoff seen in observations and the High Resolution Atmospheric Model (HiRAM) at 0.25°–0.5° in Part I. Under the representative concentration pathway 8.5 (RCP8.5) global warming scenario, the change in the probability of the most intense storm clusters appears in all models and is consistent with HiRAM output, increasing by up to an order of magnitude relative to historical climate. For the three models in the ensemble with continuous time series of high-resolution output, there is substantial variability on when these probability increases for the most powerful storm clusters become detectable, ranging from detectable within the observational period to statistically significant trends emerging only after 2050. A similar analysis of National Centers for Environmental Prediction (NCEP)–U.S. Department of Energy (DOE) AMIP-II reanalysis and Special Sensor Microwave Imager and Imager/Sounder (SSM/I and SSMIS) rain-rate retrievals in the recent observational record does not yield reliable evidence of trends in high power cluster probabilities at this time. However, the results suggest that maintaining a consistent set of overlapping satellite instrumentation with improvements to SSM/I–SSMIS rain-rate retrieval intercalibrations would be useful for detecting trends in this important tail behavior within the next couple of decades.

scholarly journals Simulation of ENSO in the New NCEP Coupled Forecast System Model (CFS03)

2005 ◽  
Vol 133 (6) ◽  
pp. 1574-1593 ◽  
Author(s):  
Wanqiu Wang ◽  
Suranjana Saha ◽  
Hua-Lu Pan ◽  
Sudhir Nadiga ◽  
Glenn White
Keyword(s):  
Southern Oscillation ◽  
Coupled Model ◽  
Forecast Model ◽  
Seasonal Prediction ◽  
Ocean Model ◽  
System Model ◽  
Enso Cycle ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Forecast System ◽  
Enso Events

Abstract A new global coupled atmosphere–ocean forecast system model (CFS03) has recently been developed at the National Centers for Environmental Prediction (NCEP). The new coupled model consists of a T62L64 version of the operational NCEP Atmospheric Global Forecast System model and the Geophysical Fluid Dynamics Laboratory Modular Ocean Model version 3, and is expected to replace the current NCEP operational coupled seasonal forecast model. This study assesses the performance of the new coupled model in simulating El Niño–Southern Oscillation (ENSO), which is considered to be a desirable feature for models used for seasonal prediction. The diagnoses indicate that the new coupled model simulates ENSO variability with realistic frequency. The amplitude of the simulated ENSO is similar to that of the observed strong events, but the ENSO events in the simulation occur more regularly than in observations. The model correctly simulates the observed ENSO seasonal phase locking with the peak amplitude near the end of the year. On average, however, simulated warm events tend to start about 3 months earlier and persist longer than observed. The simulated ENSO is consistent with the delayed oscillator, recharge oscillator, and advective–reflective oscillator theories, suggesting that each of these mechanisms may operate at the same time during the ENSO cycle. The diagnoses of the simulation indicate that the model may be suitable for real-time prediction of ENSO.

Physical interactions within a coupled climate model over the last glacial–interglacial cycle

1990 ◽  
Vol 81 (4) ◽  
pp. 357-369 ◽  
Author(s):  
A. Berger ◽  
Th. Fichefet ◽  
H. Gallée ◽  
I. Marsiat ◽  
C. Tricot ◽  
...  
Keyword(s):  
Sea Ice ◽  
Land Surface ◽  
Climate Model ◽  
Ice Sheets ◽  
Coupled Model ◽  
Greenland Ice Sheet ◽  
Atmospheric Model ◽  
Climate System ◽  
Last Glacial ◽  
The Last Glacial

ABSTRACTA two-dimensional (2-D) seasonal model has been developed for simulating the transient response of the climate system to the astronomical forcing. The atmosphere is represented by a zonally averaged quasi-geostrophic model which includes accurate treatment of radiative transfer. The atmospheric model interacts with the other components of the climate system (ocean, sea-ice and land surface covered or not by snow and ice) through vertical fluxes of momentum, heat and humidity. The model explicitly incorporates surface energy balances and has snow and sea-ice mass budgets. The vertical profile of the upper-ocean temperature is computed by an interactive mixed-layer model which takes into account the meridional turbulent diffusion of heat. This model is asynchronously coupled to a model which simulates the dynamics of the Greenland, the northern American and the Eurasian ice sheets. Over the last glacial–interglacial cycle, the coupled model simulates climatic changes which are in general agreement with the low frequency part of deep-sea, ice and sea-level records. However, after 6000 yBP, the remaining ice volume of the Greenland and northern American ice sheets is overestimated in the simulation. The simulated climate is sensitive to the initial size of the Greenland ice sheet, to the ice-albedo positive feedback, to the precipitation-altitude negative feedback over the ice sheets, to the albedo of the aging snow and to the insolation increase, particularly at the southern edge of the ice sheets, which is important for their collapse or surge.

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