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 ◽  
...  

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.

2013 ◽  
Vol 26 (17) ◽  
pp. 6185-6214 ◽  
Author(s):  
Meng-Pai Hung ◽  
Jia-Lin Lin ◽  
Wanqiu Wang ◽  
Daehyun Kim ◽  
Toshiaki Shinoda ◽  
...  

Abstract This study evaluates the simulation of the Madden–Julian oscillation (MJO) and convectively coupled equatorial waves (CCEWs) in 20 models from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and compares the results with the simulation of CMIP phase 3 (CMIP3) models in the IPCC Fourth Assessment Report (AR4). The results show that the CMIP5 models exhibit an overall improvement over the CMIP3 models in the simulation of tropical intraseasonal variability, especially the MJO and several CCEWs. The CMIP5 models generally produce larger total intraseasonal (2–128 day) variance of precipitation than the CMIP3 models, as well as larger variances of Kelvin, equatorial Rossby (ER), and eastward inertio-gravity (EIG) waves. Nearly all models have signals of the CCEWs, with Kelvin and mixed Rossby–gravity (MRG) and EIG waves being especially prominent. The phase speeds, as scaled to equivalent depths, are close to the observed value in 10 of the 20 models, suggesting that these models produce sufficient reduction in their effective static stability by diabatic heating. The CMIP5 models generally produce larger MJO variance than the CMIP3 models, as well as a more realistic ratio between the variance of the eastward MJO and that of its westward counterpart. About one-third of the CMIP5 models generate the spectral peak of MJO precipitation between 30 and 70 days; however, the model MJO period tends to be longer than observations as part of an overreddened spectrum, which in turn is associated with too strong persistence of equatorial precipitation. Only one of the 20 models is able to simulate a realistic eastward propagation of the MJO.


2005 ◽  
Vol 18 (13) ◽  
pp. 2172-2193 ◽  
Author(s):  
Haijun Hu ◽  
Robert J. Oglesby ◽  
Susan Marshall

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.


2004 ◽  
Vol 85 (12) ◽  
pp. 1903-1916 ◽  
Author(s):  
Thomas J. Phillips ◽  
Gerald L. Potter ◽  
David L. Williamson ◽  
Richard T. Cederwall ◽  
James S. Boyle ◽  
...  

To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework. To further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.


2008 ◽  
Vol 21 (23) ◽  
pp. 6119-6140 ◽  
Author(s):  
Nicholas P. Klingaman ◽  
Peter M. Inness ◽  
Hilary Weller ◽  
Julia M. Slingo

Abstract While the Indian monsoon exhibits substantial variability on interannual time scales, its intraseasonal variability (ISV) is of greater magnitude and hence of critical importance for monsoon predictability. This ISV comprises a 30–50-day northward-propagating oscillation (NPISO) between active and break events of enhanced and reduced rainfall, respectively, over the subcontinent. Recent studies have implied that coupled general circulation models (CGCMs) were better able to simulate the NPISO than their atmosphere-only counterparts (AGCMs). These studies have forced their AGCMs with SSTs from coupled integrations or observations from satellite-based infrared sounders, both of which underestimate the ISV of tropical SSTs. The authors have forced the 1.25° × 0.83° Hadley Centre Atmospheric Model (HadAM3) with a daily, high-resolution, observed SST analysis from the United Kingdom National Center for Ocean Forecasting that contains greater ISV in the Indian Ocean than past products. One ensemble of simulations was forced by daily SSTs, a second with monthly means, and a third with 5-day means. The ensemble with daily SSTs displayed significantly greater variability in 30–50-day rainfall across the monsoon domain than the ensemble with monthly mean SSTs, variability similar to satellite-derived precipitation analyses. Individual ensemble members with daily SSTs contained intraseasonal events with a strength, a propagation speed, and an organization that closely matched observed events. When ensemble members with monthly mean SSTs displayed power in intraseasonal rainfall, the events were weak and disorganized, and they propagated too quickly. The ensemble with 5-day means had less intraseasonal rainfall variability than the ensemble with daily SSTs but still produced coherent NPISO-like events, indicating that SST variability at frequencies higher than 5 days contributes to but is not critical for simulations of the NPISO. It is concluded that high-frequency SST anomalies not only increased variance in intraseasonal rainfall but helped to organize and maintain coherent NPISO-like convective events. Further, the results indicate that an AGCM can respond to realistic and frequent SST forcing to generate an NPISO that closely resembles observations. These results have important implications for simulating the NPISO in AGCMs and coupled climate models, as well as for predicting tropical ISV in short- and medium-range weather forecasts.


Water Policy ◽  
2013 ◽  
Vol 15 (S1) ◽  
pp. 26-50 ◽  
Author(s):  
Marc Jeuland ◽  
Nagaraja Harshadeep ◽  
Jorge Escurra ◽  
Don Blackmore ◽  
Claudia Sadoff

This paper presents the first basin-wide assessment of the potential impact of climate change on the hydrology and production of the Ganges system, undertaken as part of the World Bank's Ganges Strategic Basin Assessment. A series of modeling efforts – downscaling of climate projections, water balance calculations, hydrological simulation and economic optimization – inform the assessment. We find that projections of precipitation across the basin, obtained from 16 Intergovernmental Panel on Climate Change-recognized General Circulation Models are highly variable, and lead to considerable differences in predictions of mean flows in the main stem of the Ganges and its tributaries. Despite uncertainties in predicted future flows, they are not, however, outside the range of natural variability in this basin, except perhaps at the tributary or sub-catchment levels. We also find that the hydropower potential associated with a set of 23 large dams in Nepal remains high across climate models, largely because annual flow in the tributary rivers greatly exceeds the storage capacities of these projects even in dry scenarios. The additional storage and smoothing of flows provided by these infrastructures translates into enhanced water availability in the dry season, but the relative value of this water for the purposes of irrigation in the Gangetic plain, and for low flow augmentation to Bangladesh under climate change, is unclear.


Author(s):  
Shahab Doulabian ◽  
Saeed Golian ◽  
Amirhossein Shadmehri Toosi ◽  
Conor Murphy

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.


2020 ◽  
Vol 21 (4) ◽  
pp. 845-863 ◽  
Author(s):  
Xiaoli Yang ◽  
Xiaohan Yu ◽  
Yuqian Wang ◽  
Xiaogang He ◽  
Ming Pan ◽  
...  

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.


2008 ◽  
Vol 21 (5) ◽  
pp. 883-909 ◽  
Author(s):  
Jia-Lin Lin ◽  
Myong-In Lee ◽  
Daehyun Kim ◽  
In-Sik Kang ◽  
Dargan M. W. Frierson

Abstract This study examines the impacts of convective parameterization and moisture convective trigger on convectively coupled equatorial waves simulated by the Seoul National University (SNU) atmospheric general circulation model (AGCM). Three different convection schemes are used, including the simplified Arakawa–Schubert (SAS) scheme, the Kuo (1974) scheme, and the moist convective adjustment (MCA) scheme, and a moisture convective trigger with variable strength is added to each scheme. The authors also conduct a “no convection” experiment with deep convection schemes turned off. Space–time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the Madden–Julian oscillation (MJO), Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), and eastward inertio-gravity (EIG) and westward inertio-gravity (WIG) waves. The results show that both convective parameterization and the moisture convective trigger have significant impacts on AGCM-simulated, convectively coupled equatorial waves. The MCA scheme generally produces larger variances of convectively coupled equatorial waves including the MJO, more coherent eastward propagation of the MJO, and a more prominent MJO spectral peak than the Kuo and SAS schemes. Increasing the strength of the moisture trigger significantly enhances the variances and slows down the phase speeds of all wave modes except the MJO, and usually improves the eastward propagation of the MJO for the Kuo and SAS schemes, but the effect for the MCA scheme is small. The no convection experiment always produces one of the best signals of convectively coupled equatorial waves and the MJO.


2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke

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.


2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz

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.


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