The Simulation of Moisture Processes in Climate Models and Climate Sensitivity

2005 ◽  
Vol 18 (13) ◽  
pp. 2172-2193 ◽  
Author(s):  
Haijun Hu ◽  
Robert J. Oglesby ◽  
Susan Marshall
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Atmospheric Moisture ◽  
Model Sensitivity ◽  
Surface Warming ◽  
Wide Range ◽  
Modeling Techniques ◽  
Moisture Performance

Abstract General circulation models (GCMs) designed for projecting climatic change have exhibited a wide range of sensitivity. Therefore, projected surface warming with increasing CO2 varies considerably depending on which model is used. Despite notable advances in computing power and modeling techniques that have occurred over the past decade, uncertainties of model sensitivity have not been reduced accordingly. The sensitivity issue is investigated by examining two GCMs of very different modeling techniques and sensitivity, with attention focused on how moisture processes are treated in these models, how moisture simulations are affected by these processes, and how well these simulations compare to the observed and analyzed moisture field. Both GCMs predict increases of atmospheric moisture with doubled CO2, but the increment predicted by one model is substantially higher (approximately twice) than that predicted by the other. This same difference is seen in responses of the boundary layer diffusive moistening rate. Calculations with a radiative–convective model indicate that the differences in predicted equilibrium atmospheric moisture, including both column amount and vertical distribution, have contributed to the largest differences in model sensitivity between the two models. We argue that in order for climate models to be credible for prediction purposes, they must possess credible skills of simulating surface and boundary layer processes, which likely holds the key to overall moisture performance, its response to external forcing, and in turn to model sensitivity.

scholarly journals Investigation of Regional and Seasonal Variations in Marine Boundary Layer Cloud Properties from MODIS Observations

2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Test Bed ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Peak Versus

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

scholarly journals Weak Land–Atmosphere Coupling Strength in HadAM3: The Role of Soil Moisture Variability

2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Coupling Strength ◽  
General Circulation ◽  
General Circulation Models ◽  
Soil Conditions ◽  
Wide Range ◽  
The Impact ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract A recent model intercomparison, the Global Land–Atmosphere Coupling Experiment (GLACE), showed that there is a wide range of land–atmosphere coupling strengths, or the degree that soil moisture affects the generation of precipitation, amongst current atmospheric general circulation models (AGCMs). Coupling strength in the Hadley Centre atmosphere model (HadAM3) is among the weakest of all AGCMs considered in GLACE. Reasons for the weak HadAM3 coupling strength are sought here. In particular, the impact of pervasive saturated soil conditions and low soil moisture variability on coupling strength is assessed. It is found that when the soil model is modified to reduce the occurrence of soil moisture saturation and to encourage soil moisture variability, the soil moisture–precipitation feedback remains weak, even though the relationship between soil moisture and evaporation is strengthened. Composites of the diurnal cycle, constructed relative to soil moisture, indicate that the model can simulate key differences in boundary layer development over wet versus dry soils. In particular, the influence of wet or dry soil on the diurnal cycles of Bowen ratio, boundary layer height, and total heat flux are largely consistent with the observed influence of soil moisture on these properties. However, despite what appears to be successful simulation of these key aspects of the indirect soil moisture–precipitation feedback, the model does not capture observed differences for wet and dry soils in the daily accumulation of boundary layer moist static energy, a crucial feature of the feedback mechanism.

scholarly journals The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models

2018 ◽  
Vol 31 (22) ◽  
pp. 9151-9173 ◽  
Author(s):  
Richard Davy
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Seasonal Cycles ◽  
Layer Depth

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

scholarly journals Evaluating the effects of climate change on precipitation and temperature for Iran using RCP scenarios

2020 ◽  
Author(s):  
Shahab Doulabian ◽  
Saeed Golian ◽  
Amirhossein Shadmehri Toosi ◽  
Conor Murphy
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
Skill Score ◽  
Climatic Conditions ◽  
Historical Period ◽  
Rcp Scenarios ◽  
Wide Range

Abstract Climate change has caused many changes in hydrologic processes and climatic conditions globally, while extreme events are likely to occur more frequently at a global scale with continued warming. Given the importance of general circulation models (GCMs) as an essential tool for climate studies at global/regional scales, together with the wide range of GCMs available, selecting appropriate models is of great importance. In this study, six synoptic weather stations were selected as representative of different climatic zones over Iran. Utilizing monthly data for 20 years (1981–2000), the outputs of 25 GCMs for surface air temperature (SAT) and precipitation were evaluated for the historical period. The root-mean-square error and skill score were chosen to evaluate the performance of GCMs in capturing observed seasonal climate. Finally, the outputs of selected GCMs for the three Representative Concentration Pathways emission scenarios (RCPs), namely RCP2.6, RCP4.5, and RCP8.5, were downscaled using the change factor method for each station for the period 2046–2065. Results indicate that SAT in all months is likely to increase for each region, while for precipitation, large uncertainties emerge, despite the selection of climate models that best capture the observed seasonal cycle. These results highlight the importance of selecting a representative ensemble of GCMs for assessing future hydro-climatic changes for Iran.

scholarly journals Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals

2006 ◽  
Vol 19 (12) ◽  
pp. 2665-2690 ◽  
Author(s):  
Jia-Lin Lin ◽  
George N. Kiladis ◽  
Brian E. Mapes ◽  
Klaus M. Weickmann ◽  
Kenneth R. Sperber ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Intraseasonal Variability ◽  
Phase Speed ◽  
General Circulation Models ◽  
Climate Simulation ◽  
Equatorial Waves ◽  
Intergovernmental Panel ◽  
Convectively Coupled Equatorial Waves ◽  
Wide Range

Abstract This study evaluates the tropical intraseasonal variability, especially the fidelity of Madden–Julian oscillation (MJO) simulations, in 14 coupled general circulation models (GCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of daily precipitation from each model’s twentieth-century climate simulation are analyzed and compared with daily satellite-retrieved precipitation. Space–time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), and eastward inertio–gravity (EIG) and westward inertio–gravity (WIG) waves. The variance and propagation of the MJO, defined as the eastward wavenumbers 1–6, 30–70-day mode, are examined in detail. The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2–128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG–EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their “effective static stability” by diabatic heating. The MJO variance approaches the observed value in only 2 of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its westward counterpart is too small in most of the models, which is consistent with the lack of highly coherent eastward propagation of the MJO in many models. Moreover, the MJO variance in 13 of the 14 models does not come from a pronounced spectral peak, but usually comes from part of an overreddened spectrum, which in turn is associated with too strong persistence of equatorial precipitation. The two models that arguably do best at simulating the MJO are the only ones having convective closures/triggers linked in some way to moisture convergence.

Does Model Sensitivity to Changes in CO2 Provide a Measure of Sensitivity to Other Forcings?

2006 ◽  
Vol 19 (13) ◽  
pp. 3294-3306 ◽  
Author(s):  
Andrei P. Sokolov
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Cloud Feedback ◽  
Future Climate Change ◽  
Massachusetts Institute Of Technology ◽  
Model Sensitivity ◽  
Sea Ice Extent ◽  
Surface Warming

Abstract Simulation of both the climate of the twentieth century and a future climate change requires taking into account numerous forcings, while climate sensitivities of general circulation models are defined as the equilibrium surface warming due to a doubling of atmospheric CO2 concentration. A number of simulations with the Massachusetts Institute of Technology (MIT) climate model of intermediate complexity with different forcings have been carried out to study to what extent sensitivity to changes in CO2 concentration (SCO2) represent sensitivities to other forcings. The MIT model, similar to other models, shows a strong dependency of the simulated surface warming on the vertical structure of the imposed forcing. This dependency is a result of “semidirect” effects in the simulations with localized tropospheric heating. A method for estimating semidirect effects associated with different feedback mechanisms is presented. It is shown that forcing that includes these effects is a better measure of expected surface warming than a forcing that accounts for stratospheric adjustment only. Simulations with the versions of the MIT model with different strengths of cloud feedback show that, for the range of sensitivities produced by existing GCMs, SCO2 provides a good measure of the model sensitivity to other forcings. In the case of strong cloud feedback, sensitivity to the increase in CO2 concentration overestimates model sensitivity to both negative forcings, leading to the cooling of the surface and “black carbon”–like forcings with elevated heating. This is explained by the cloud feedback being less efficient in the case of increasing sea ice extent and snow cover or by the above-mentioned semidirect effects, which are absent in the CO2 simulations, respectively.

scholarly journals The Optimal Multimodel Ensemble of Bias-Corrected CMIP5 Climate Models over China

2020 ◽  
Vol 21 (4) ◽  
pp. 845-863 ◽  
Author(s):  
Xiaoli Yang ◽  
Xiaohan Yu ◽  
Yuqian Wang ◽  
Xiaogang He ◽  
Ming Pan ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Multimodel Ensemble ◽  
Hydrological Impacts ◽  
Optimal Ensemble ◽  
Wide Range ◽  
Precipitation And Temperature ◽  
Impacts Of Climate Change

AbstractA multimodel ensemble of general circulation models (GCM) is a popular approach to assess hydrological impacts of climate change at local, regional, and global scales. The traditional multimodel ensemble approach has not considered different uncertainties across GCMs, which can be evaluated from the comparisons of simulations against observations. This study developed a comprehensive index to generate an optimal ensemble for two main climate fields (precipitation and temperature) for the studies of hydrological impacts of climate change over China. The index is established on the skill score of each bias-corrected model and different multimodel combinations using the outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results show that the optimal ensemble of the nine selected models accurately captures the characteristics of spatial–temporal variabilities of precipitation and temperature over China. We discussed the uncertainty of subset ensembles of ranking models and optimal ensemble based on historical performance. We found that the optimal subset ensemble of nine models has relative smaller uncertainties compared with other subsets. Our proposed framework to postprocess the multimodel ensemble data has a wide range of applications for climate change assessment and impact studies.

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals Exploiting the weekly cycle as observed over Europe to analyse aerosol indirect effects in two climate models

2009 ◽  
Vol 9 (21) ◽  
pp. 8493-8501 ◽  
Author(s):  
J. Quaas ◽  
O. Boucher ◽  
A. Jones ◽  
G. P. Weedon ◽  
J. Kieser ◽  
...  
Keyword(s):  
Indirect Effects ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Large Variability ◽  
Aerosol Indirect Effects ◽  
Weekly Cycle ◽  
Model Control

Abstract. A weekly cycle in aerosol pollution and some meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloud-radiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol processes and cloud microphysics. It is found that the simulated weekly cycles in sulfur dioxide, sulfate, and aerosol optical depth in both models agree reasonably well with those observed indicating model skill in simulating the aerosol cycle. A distinct weekly cycle in cloud droplet number concentration is demonstrated in both observations and models. For other variables, such as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation fluxes, precipitation, and surface temperature, large variability and contradictory results between observations, model simulations, and model control simulations without a weekly cycle in emissions prevent us from reaching any firm conclusions about the potential aerosol impact on meteorology or the realism of the modelled second aerosol indirect effects.

scholarly journals The faint young Sun problem revisited with a 3-D climate–carbon model – Part 1

2014 ◽  
Vol 10 (2) ◽  
pp. 697-713 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Freezing Point ◽  
Climatic Factors ◽  
General Circulation Models ◽  
Companion Paper ◽  
One Dimensional ◽  
Carbon Dioxide Concentrations ◽  
Wide Range ◽  
High Concentrations

Abstract. During the Archaean, the Sun's luminosity was 18 to 25% lower than the present day. One-dimensional radiative convective models (RCM) generally infer that high concentrations of greenhouse gases (CO2, CH4) are required to prevent the early Earth's surface temperature from dropping below the freezing point of liquid water and satisfying the faint young Sun paradox (FYSP, an Earth temperature at least as warm as today). Using a one-dimensional (1-D) model, it was proposed in 2010 that the association of a reduced albedo and less reflective clouds may have been responsible for the maintenance of a warm climate during the Archaean without requiring high concentrations of atmospheric CO2 (pCO2). More recently, 3-D climate simulations have been performed using atmospheric general circulation models (AGCM) and Earth system models of intermediate complexity (EMIC). These studies were able to solve the FYSP through a large range of carbon dioxide concentrations, from 0.6 bar with an EMIC to several millibars with AGCMs. To better understand this wide range in pCO2, we investigated the early Earth climate using an atmospheric GCM coupled to a slab ocean. Our simulations include the ice-albedo feedback and specific Archaean climatic factors such as a faster Earth rotation rate, high atmospheric concentrations of CO2 and/or CH4, a reduced continental surface, a saltier ocean, and different cloudiness. We estimated full glaciation thresholds for the early Archaean and quantified positive radiative forcing required to solve the FYSP. We also demonstrated why RCM and EMIC tend to overestimate greenhouse gas concentrations required to avoid full glaciations or solve the FYSP. Carbon cycle–climate interplays and conditions for sustaining pCO2 will be discussed in a companion paper.

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