Effects of mean state of climate models on the response to prescribed forcing: Sensitivity experiments with the SPEEDY general circulation model.

2020 ◽  
Author(s):  
Emanuele Di Carlo ◽  
Paolo Ruggieri ◽  
Paolo Davini ◽  
Stefano Tibaldi ◽  
Susanna Corti
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Surface Condition ◽  
Circulation Model ◽  
Climate Simulation ◽  
Atmospheric Response ◽  
Large Ensemble ◽  
Mean State

<pre>Understanding how the general circulation of the atmosphere is affected by global warming is one of the grand challenges in climate science. Climate models are a valuable tool to: i) identifying potential mechanism for changes in general circulation, ii) recognizing signals that can be related to external forcing and iii) produce projections for future scenarios. Despite the use of large ensemble of continuosly improving climate models, uncertainty for the extratropical circulation is still large. It is therefore important to understand processes driving the variability of the circulation in climate models and how these processes are affected by model bias. To characterize the effect of models bias on the response to a given forcing, several simulations were performed with the Simplified Parameterizations, primitivE - Equation DYnamics (SPEEDY), an intermediate complexity model developed by International Center for Theoretical Physics (ICTP). Four simulations are performed with a modified orography in order to obtain an atmospheric circulation at mid-latitudes characterized by different mean states and a control climate simulation carried in standard configuration is used as baseline. For each of these experiments, we have studied the climatic response to El Niño Southern Oscillation (ENSO) and to the Atlantic Multidecadal Variability (AMV). All the <em>Sensitivity </em>simulations were performed with a large ensemble (~100 members).</pre> <pre>Results show that indeed the model response is non-negligibly influenced by its mean state and reveal geographic areas where the sensitivity is large. On the other hand, they also show large scale regions of the world where the atmospheric response to ENSO and AMV is unlikely to depend on the atmospheric mean state. We also found that the relationship between changes in the model mean state and the response to the forcing appears to be non linear. These results cam be used to interpret and understand multi-model spread in atmospheric response to aforementioned surface condition.</pre>

scholarly journals Sensitivity of boreal-summer circulation and precipitation to atmospheric aerosols in selected regions – Part 1: Africa and India

2009 ◽  
Vol 27 (10) ◽  
pp. 3989-4007 ◽  
Author(s):  
Y. C. Sud ◽  
E. Wilcox ◽  
W. K.-M. Lau ◽  
G. K. Walker ◽  
X.-H. Liu ◽  
...  
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Initial Conditions ◽  
Regional Climate ◽  
Circulation Model ◽  
Climate Simulation ◽  
Boreal Summer ◽  
Summer Circulation ◽  
Precipitation Difference

Abstract. Version-4 of the Goddard Earth Observing System (GEOS-4) General Circulation Model (GCM) was employed to assess the influence of potential changes in aerosols on the regional circulation, ambient temperatures, and precipitation in four selected regions: India and Africa (current paper), as well as North and South America (companion paper). Ensemble-simulations were carried out with the GCM to assess the aerosol direct and indirect effects, hereafter ADE and AIE. Each simulation was started from the NCEP-analyzed initial conditions for 1 May and was integrated through May-June-July-August of each year: 1982–1987 to provide an ensemble set of six simulations. In the first set, called experiment (#1), climatological aerosols were prescribed. The next two experiments (#2 and #3) had two sets of simulations each: one with 2X and other with 1/2X the climatological aerosols over each of the four selected regions. In experiment #2, the anomaly regions were advectively restricted (AR), i.e., the large-scale prognostic fields outside the aerosol anomaly regions were prescribed while in experiment #3, the anomaly regions were advectively Interactive (AI) as is the case in a normal GCM integrations, but with the same aerosols anomalies as in experiment #2. Intercomparisons of circulation, diabatic heating, and precipitation difference fields showed large disparities among the AR and AI simulations, which raised serious questions about the proverbial AR assumption, commonly invoked in regional climate simulation studies. Consequently AI simulation mode was chosen for the subsequent studies. Two more experiments (#4 and #5) were performed in the AI mode in which ADE and AIE were activated one at a time. The results showed that ADE and AIE work in concert to make the joint influences larger than sum of each acting alone. Moreover, the ADE and AIE influences were vastly different for the Indian and Africa regions, which suggest an imperative need to include them rationally in climate models. We also found that the aerosol induced increase of tropical cirrus clouds would potentially offset any cirrus thinning that may occur due to warming in response to CO2 increase.

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.

Improved Climate Simulation by MIROC5: Mean States, Variability, and Climate Sensitivity

2010 ◽  
Vol 23 (23) ◽  
pp. 6312-6335 ◽  
Author(s):  
Masahiro Watanabe ◽  
Tatsuo Suzuki ◽  
Ryouta O’ishi ◽  
Yoshiki Komuro ◽  
Shingo Watanabe ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
General Circulation ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Climate Simulation ◽  
Mean Fields ◽  
Equatorial Ocean ◽  
The Mean ◽  
The Difference

Abstract A new version of the atmosphere–ocean general circulation model cooperatively produced by the Japanese research community, known as the Model for Interdisciplinary Research on Climate (MIROC), has recently been developed. A century-long control experiment was performed using the new version (MIROC5) with the standard resolution of the T85 atmosphere and 1° ocean models. The climatological mean state and variability are then compared with observations and those in a previous version (MIROC3.2) with two different resolutions (medres, hires), coarser and finer than the resolution of MIROC5. A few aspects of the mean fields in MIROC5 are similar to or slightly worse than MIROC3.2, but otherwise the climatological features are considerably better. In particular, improvements are found in precipitation, zonal mean atmospheric fields, equatorial ocean subsurface fields, and the simulation of El Niño–Southern Oscillation. The difference between MIROC5 and the previous model is larger than that between the two MIROC3.2 versions, indicating a greater effect of updating parameterization schemes on the model climate than increasing the model resolution. The mean cloud property obtained from the sophisticated prognostic schemes in MIROC5 shows good agreement with satellite measurements. MIROC5 reveals an equilibrium climate sensitivity of 2.6 K, which is lower than that in MIROC3.2 by 1 K. This is probably due to the negative feedback of low clouds to the increasing concentration of CO2, which is opposite to that in MIROC3.2.

scholarly journals Large-Scale Controls on Atlantic Tropical Cyclone Activity on Seasonal Time Scales

2016 ◽  
Vol 29 (18) ◽  
pp. 6727-6749 ◽  
Author(s):  
Young-Kwon Lim ◽  
Siegfried D. Schubert ◽  
Oreste Reale ◽  
Andrea M. Molod ◽  
Max J. Suarez ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
North Atlantic ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Vertical Wind Shear ◽  
Circulation Model ◽  
The North ◽  
Predictive Skill ◽  
The North Atlantic

Abstract Interannual variations in seasonal tropical cyclone (TC) activity (e.g., genesis frequency and location, track pattern, and landfall) over the Atlantic are explored by employing observationally constrained simulations with the NASA Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model. The climate modes investigated are El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Atlantic meridional mode (AMM). The results show that the NAO and AMM can strongly modify and even oppose the well-known ENSO impacts, like in 2005, when a strong positive AMM (associated with warm SSTs and a negative SLP anomaly over the western tropical Atlantic) led to a very active TC season with enhanced TC genesis over the Caribbean Sea and a number of landfalls over North America, under a neutral ENSO condition. On the other end, the weak TC activity during 2013 (characterized by weak negative Niño index) appears caused by a NAO-induced positive SLP anomaly with enhanced vertical wind shear over the tropical North Atlantic. During 2010, the combined impact of the three modes produced positive SST anomalies across the entire low-latitudinal Atlantic and a weaker subtropical high, leading to more early recurvers and thus fewer landfalls despite enhanced TC genesis. The study provides evidence that TC number and track are very sensitive to the relative phases and intensities of these three modes and not just to ENSO alone. Examination of seasonal predictability reveals that the predictive skill of the three modes is limited over tropics to subtropics, with the AMM having the highest predictability over the North Atlantic, followed by ENSO and NAO.

scholarly journals A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

2021 ◽  
Vol 14 (1) ◽  
pp. 73-90
Author(s):  
Hsi-Yen Ma ◽  
Chen Zhou ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Mark D. Zelinka ◽  
...  
Keyword(s):  
Short Range ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Heat Fluxes ◽  
Model Errors ◽  
Moist Processes ◽  
The Mean ◽  
Mean State

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

Simulations of Atmospheric Rivers, Their Variability, and Response to Global Warming Using GFDL’s New High-Resolution General Circulation Model

2020 ◽  
Vol 33 (23) ◽  
pp. 10287-10303
Author(s):  
Ming Zhao
Keyword(s):  
Global Warming ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Geographical Location ◽  
Circulation Model ◽  
Teleconnection Pattern ◽  
Width Ratio ◽  
Atmospheric Rivers ◽  
Length Width

AbstractA 50-km-resolution GFDL AM4 well captures many aspects of observed atmospheric river (AR) characteristics including the probability density functions of AR length, width, length–width ratio, geographical location, and the magnitude and direction of AR mean vertically integrated vapor transport (IVT), with the model typically producing stronger and narrower ARs than the ERA-Interim results. Despite significant regional biases, the model well reproduces the observed spatial distribution of AR frequency and AR variability in response to large-scale circulation patterns such as El Niño–Southern Oscillation (ENSO), the Northern and Southern Hemisphere annular modes (NAM and SAM), and the Pacific–North American (PNA) teleconnection pattern. For global warming scenarios, in contrast to most previous studies that show a large increase in AR length and width and therefore the occurrence frequency of AR conditions at a given location, this study shows only a modest increase in these quantities. However, the model produces a large increase in strong ARs with the frequency of category 3–5 ARs rising by roughly 100%–300% K−1. The global mean AR intensity as well as AR intensity percentiles at most percent ranks increases by 5%–8% K−1, roughly consistent with the Clausius–Clapeyron scaling of water vapor. Finally, the results point out the importance of AR IVT thresholds in quantifying modeled AR response to global warming.

scholarly journals Quantitative Sensitivity Analysis of Physical Parameterizations for Cases of Deep Convection in the NASA GEOS-5

2016 ◽  
Vol 29 (2) ◽  
pp. 455-479 ◽  
Author(s):  
Derek J. Posselt ◽  
Bruce Fryxell ◽  
Andrea Molod ◽  
Brian Williams
Keyword(s):  
General Circulation ◽  
Process Model ◽  
Large Scale ◽  
Climate Models ◽  
Deep Convection ◽  
Input Parameter ◽  
Circulation Model ◽  
Parameter Sensitivity ◽  
Global Climate Models ◽  
Simulation Code

Abstract Parameterization of processes that occur on length scales too small to resolve on a computational grid is a major source of uncertainty in global climate models. This study investigates the relative importance of a number of parameters used in the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model, focusing on cloud, convection, and boundary layer parameterizations. Latin hypercube sampling is used to generate a few hundred sets of 19 candidate physics parameters, which are subsequently used to generate ensembles of single-column model realizations of cloud content, precipitation, and radiative fluxes for four different field campaigns. A Gaussian process model is then used to create a computationally inexpensive emulator for the simulation code that can be used to determine a measure of relative parameter sensitivity by sampling the response surface for a very large number of input parameter sets. Parameter sensitivities are computed for different geographic locations and seasons to determine whether the intrinsic sensitivity of the model parameterizations changes with season and location. The results indicate the same subset of parameters collectively control the model output across all experiments, independent of changes in the environment. These are the threshold relative humidity for cloud formation, the ice fall speeds, convective and large-scale autoconversion, deep convection relaxation time scale, maximum convective updraft diameter, and minimum ice effective radius. However, there are differences in the degree of parameter sensitivity between continental and tropical convective cases, as well as systematic changes in the degree of parameter influence and parameter–parameter interaction.

Prediction of Indian Summer Monsoon Onset Using Dynamical Subseasonal Forecasts: Effects of Realistic Initialization of the Atmosphere

2015 ◽  
Vol 143 (3) ◽  
pp. 778-793 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Annalisa Cherchi ◽  
Stefano Materia ◽  
Antonio Navarra ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
General Circulation ◽  
Large Scale ◽  
Initial Conditions ◽  
Intraseasonal Oscillation ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Monsoon Onset ◽  
Mean State

Abstract Ensembles of retrospective 2-month dynamical forecasts initiated on 1 May are used to predict the onset of the Indian summer monsoon (ISM) for the period 1989–2005. The subseasonal predictions (SSPs) are based on a coupled general circulation model and recently they have been upgraded by the realistic initialization of the atmosphere with initial conditions taken from reanalysis. Two objective large-scale methods based on dynamical-circulation and hydrological indices are applied to detect the ISM onset. The SSPs show some skill in forecasting earlier-than-normal ISM onsets, while they have difficulty in predicting late onsets. It is shown that significant contribution to the skill in forecasting early ISM onsets comes from the newly developed initialization of the atmosphere from reanalysis. On one hand, atmospheric initialization produces a better representation of the atmospheric mean state in the initial conditions, leading to a systematically improved monsoon onset sequence. On the other hand, the initialization of the atmosphere allows some skill in forecasting the northward-propagating intraseasonal wind and precipitation anomalies over the tropical Indian Ocean. The northward-propagating intraseasonal modes trigger the monsoon in some early-onset years. The realistic phase initialization of these modes improves the forecasts of the associated earlier-than-normal monsoon onsets. The prediction of late onsets is not noticeably improved by the initialization of the atmosphere. It is suggested that late onsets of the monsoon are too far away from the start date of the forecasts to conserve enough memory of the intraseasonal oscillation (ISO) anomalies and of the improved representation of the mean state in the initial conditions.

scholarly journals Global atmospheric response to specific linear combinations of the main SST modes. Part I: numerical experiments and preliminary results

1996 ◽  
Vol 14 (10) ◽  
pp. 1066-1077 ◽  
Author(s):  
S. Trzaska ◽  
V. Moron ◽  
B. Fontaine
Keyword(s):  
Numerical Experiments ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Equatorial Atlantic ◽  
Preliminary Results ◽  
The Impact

Abstract. This article investigates through numerical experiments the controversial question of the impact of El Niño-Southern Oscillation (ENSO) phenomena on climate according to large-scale and regional-scale interhemispheric thermal contrast. Eight experiments (two considering only inversed Atlantic thermal anomalies and six combining ENSO warm phase with large-scale interhemispheric contrast and Atlantic anomaly patterns) were performed with the Météo-France atmospheric general circulation model. The definition of boundary conditions from observed composites and principal components is presented and preliminary results concerning the month of August, especially over West Africa and the equatorial Atlantic are discussed. Results are coherent with observations and show that interhemispheric and regional scale sea-surface-temperature anomaly (SST) patterns could significantly modulate the impact of ENSO phenomena: the impact of warm-phase ENSO, relative to the atmospheric model intercomparison project (AMIP) climatology, seems stronger when embedded in global and regional SSTA patterns representative of the post-1970 conditions [i.e. with temperatures warmer (colder) than the long-term mean in the southern hemisphere (northern hemisphere)]. Atlantic SSTAs may also play a significant role.

scholarly journals A multi-year short-range hindcast experiment for evaluating climate model moist processes from diurnal to interannual time scales

2020 ◽  
Author(s):  
Hsi-Yen Ma ◽  
Chen Zhou ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Mark D. Zelinka ◽  
...  
Keyword(s):  
Time Scales ◽  
Short Range ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Model Errors ◽  
Moist Processes ◽  
The Mean ◽  
Mean State

Abstract. We present a multi-year short-range hindcast experiment and its experiment procedure for better evaluating both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual time scales to facilitate model development. We use the Community Earth System Model version 1 as the based model and performed a suite of 3-day long hindcasts every day starting at 00Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the Central U.S., precipitation and diabatic heating associated with the Madden-Julian Oscillation propagation, and the response of moist processes to sea surface temperature anomalies associated with the El Niño-Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment design to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment. Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model’s climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated parameterized moist processes usually develop within a few days, and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

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