scholarly journals Precipitation Reproducibility over Tropical Oceans and Its Relationship to the Double ITCZ Problem in CMIP3 and MIROC5 Climate Models

2011 ◽  
Vol 24 (18) ◽  
pp. 4859-4873 ◽  
Author(s):  
Nagio Hirota ◽  
Yukari N. Takayabu ◽  
Masahiro Watanabe ◽  
Masahide Kimoto

Abstract Precipitation reproducibility over the tropical oceans in climate models is examined. Models participating in phase 3 of the Coupled Model Intercomparison Project (CMIP3) and the current (fifth) version Model for Interdisciplinary Research on Climate (MIROC5) developed by the Atmosphere and Ocean Research Institute, National Institute for Environmental Studies, and Research Institute for Global Change (AORI/NIES/RIGC) are analyzed. Scores of a pattern similarity between precipitation in the models and that in observations are evaluated. The low score models (LSMs) overestimate (underestimate) precipitation over large-scale subsidence (ascending) regions compared to the high score models (HSMs). The sensitivity of deep convection to sea surface temperature (SST) and large-scale subsidence is examined; analysis suggests that dynamical suppression of deep convection by the entrainment of environmental dry air over the subsidence region is very weak, and deep convection follows SST closely in LSMs. For example, deep convective activity is identified over the southeastern Pacific in LSMs, which corresponds to the double intertropical convergence zone (ITCZ) problem. It is suggested that the double ITCZ is associated not only with the local SST but also with the precipitation schemes that control deep convection over the entire tropical oceans. The current version, MIROC5, reproduces precipitation distributions significantly better than the older versions. Precipitation in MIROC5 has a weaker correlation with SST and a stronger correlation with environmental humidity than that in LSMs. The realistic representation of entrainment in regions with dynamical suppression is suggested to be a key factor for better reproducibility of precipitation distributions.

2012 ◽  
Vol 25 (4) ◽  
pp. 1247-1262 ◽  
Author(s):  
Hiroki Ichikawa ◽  
Hirohiko Masunaga ◽  
Yoko Tsushima ◽  
Hiroshi Kanzawa

Abstract In this study, cloud radiative forcing (CRF) associated with convective activity over tropical oceans is analyzed for monthly mean data from twentieth-century simulations of 18 climate models participating in phase 3 of the Coupled Model Intercomparison Project (CMIP3) in comparison with observational and reanalysis data. The analysis is focused on the warm oceanic regions with sea surface temperatures (SSTs) above 27°C to exclude the regions with cold SSTs typically covered by low stratus clouds. CRF is evaluated for different regimes sorted by pressure-coordinated vertical motion at 500 hPa (ω500) as an index of large-scale circulation. The warm oceanic regions cover the regime of vertical motion ranging from strong ascent to weak descent. The most notable feature found in this study is a systematic underestimation by most models of the ratio of longwave cloud radiative forcing (LWCRF) to shortwave cloud radiative forcing (SWCRF) over the weak vertical motion regime defined as −10 < ω500 < 20 hPa day−1. The underestimation of the ratio corresponds to the underestimation of LWCRF and the overestimation of SWCRF. Clouds in models seem to be lower in the amount of high clouds but more reflective than those in the observations in this regime. In the weak vertical motion regime, the lower free troposphere is dry. In the large-scale environment condition, the reproducibility of LWCRF is high in models adopting the scheme where the relative humidity–based suppression for deep convection occurrence is implemented. Models adopting the Zhang and McFarlane scheme show good performance without such a suppression mechanism.


2018 ◽  
Vol 115 (18) ◽  
pp. 4577-4582 ◽  
Author(s):  
Kathleen A. Schiro ◽  
Fiaz Ahmed ◽  
Scott E. Giangrande ◽  
J. David Neelin

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.


2020 ◽  
Author(s):  
Baijun Tian

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>


2020 ◽  
Author(s):  
Liang Wu

<p><span>Two high-resolution climate models (the HiRAM and MRI-AGCM3.2) are used to simulate present-day western North Pacific (WNP) tropical cyclone (TC) activity and investigate </span><span>the </span><span>projected changes for the late 21<sup>st</sup> century. Compared </span><span>to</span><span>observation</span><span>s</span><span>, the models </span><span>are</span><span> able to realistically simulate many basic features of </span><span>the WNP</span><span> TC activity </span><span>climatolog</span><span>y. Future projections </span><span>with the coupled model inter-comparison project phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 8.5 scenario</span><span> show a tendency for decreases in the number of WNP TCs</span><span>,</span> <span>and of</span><span> increase</span><span>s</span> <span>in the</span> <span>more intense </span><span>TCs. It is unknown to what cause this inverse variation with number and intensity should be generally linked to similar large-scale environmental conditions. To examine the WNP TC genesis and intensity with environmental variables, we show that most of the current trend of decreasing genesis of TCs can be attributed to weakened dynamic environments and the current trend of increasing intensity of TCs might be linked to increased thermodynamic environments. Thus, the future climate warms under RCP 8.5 will likely lead to strong reductions in TC genesis frequency over the WNP, with project decreases of 36-63% by the end of the twenty-first century, but lead to greater TC intensities with rapid development of thermodynamic environments.</span></p>


2016 ◽  
Vol 29 (2) ◽  
pp. 455-479 ◽  
Author(s):  
Derek J. Posselt ◽  
Bruce Fryxell ◽  
Andrea Molod ◽  
Brian Williams

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.


2020 ◽  
Author(s):  
Pedro Herrera-Lormendez ◽  
Nikolaos Mastrantonas ◽  
Jörg Matschullat ◽  
Hervé Douville

<p>Circulation classifications are a simple tool given their ability to portray aspects of day-to-day weather. As we start facing a dynamical response in general circulation patterns due to anthropogenic global warming, circulation changes can enhance or mitigate regional and local behaviour of extreme weather events.</p> <p>A weather type (WT) automatic classification, developed by Jenkinson-Collison (JC), is used to evaluate past and future changes in the seasonal frequencies of synoptic weather patterns over central and western Europe. A set of three reanalyses and four Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used, based on daily Sea Level Pressure (SLP) data.</p> <p>Discrepancies are found in the model outputs as they fall short of capturing interannual variabilities when compared to the reanalyses. Cyclonic and westerly circulations tend to be overestimated, whereas anticyclonics are underestimated.</p> <p>The projected frequencies, based on the Shared Socioeconomic Pathway 5 (SSP5) experiment, suggest significant increasing trends for unclassified WT (characterized by weak pressure gradients) during their summer half-year persistency for the coming 21<sup>st</sup> century. Winter trends indicate a surge in westerlies and a reduction in the events of cyclonic circulations and easterly flows. The results of this study support evidence of emergent changes in the occurrence of major synoptic configurations over Europe.</p>


2016 ◽  
Vol 29 (4) ◽  
pp. 1477-1496 ◽  
Author(s):  
Penelope Maher ◽  
Steven C. Sherwood

Abstract Expansion of the tropics will likely affect subtropical precipitation, but observed and modeled precipitation trends disagree with each other. Moreover, the dynamic processes at the tropical edge and their interactions with precipitation are not well understood. This study assesses the skill of climate models to reproduce observed Australian precipitation variability at the tropical edge. A multivariate linear independence approach distinguishes between direct (causal) and indirect (circumstantial) precipitation drivers that facilitate clearer attribution of model errors and skill. This approach is applied to observed precipitation and ERA-Interim reanalysis data and a representative subset of four models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and their CMIP3 counterparts. The drivers considered are El Niño–Southern Oscillation, southern annular mode, Indian Ocean dipole, blocking, and four tropical edge metrics (position and intensity of the subtropical ridge and subtropical jet). These models are skillful in representing the covariability of drivers and their influence on precipitation. However, skill scores have not improved in the CMIP5 subset relative to CMIP3 in either respect. The Australian precipitation response to a poleward-located Hadley cell edge remains uncertain, as opposing drying and moistening mechanisms complicate the net response. Higher skill in simulating driver covariability is not consistently mirrored by higher precipitation skill. This provides further evidence that modeled precipitation does not respond correctly to large-scale flow patterns; further improvements in parameterized moist physics are needed before the subtropical precipitation responses can be fully trusted. The multivariate linear independence approach could be applied more widely for practical model evaluation.


2010 ◽  
Vol 23 (21) ◽  
pp. 5755-5770 ◽  
Author(s):  
Thomas M. Smith ◽  
Phillip A. Arkin ◽  
Mathew R. P. Sapiano ◽  
Ching-Yee Chang

Abstract A monthly reconstruction of precipitation beginning in 1900 is presented. The reconstruction resolves interannual and longer time scales and spatial scales larger than 5° over both land and oceans. Because of different land and ocean data availability, the reconstruction combines two separate historical reconstructions. One analyzes interannual variations directly by fitting gauge-based anomalies to large-scale spatial modes. This direct reconstruction is used for land anomalies and interannual oceanic anomalies. The other analyzes annual and longer variations indirectly from correlations with analyzed sea surface temperature and sea level pressure. This indirect reconstruction is used for oceanic variations with time scales longer than interannual. In addition, a method of estimating reconstruction errors is also presented. Over land the reconstruction is a filtered representation of the gauge data with data gaps filled. Over oceans the reconstruction gives an estimate of the atmospheric response to changing temperature and pressure, combined with interannual variations. The reconstruction makes it possible to evaluate global precipitation variations for periods much longer than the satellite period, which begins in 1979. Evaluations show some large-scale similarities with coupled model precipitation variations over the twentieth century, including an increasing tendency over the century. The reconstructed land and sea trends tend to be out of phase at low latitudes, similar to the out-of-phase relationship for interannual variations. This reconstruction may be used for climate monitoring, for statistical climate studies of the twentieth century, and for helping to evaluate dynamic climate models. In the future the possibility of improving the reconstruction will be explored by further improving the analysis methods and including additional data.


2013 ◽  
Vol 26 (14) ◽  
pp. 4947-4961 ◽  
Author(s):  
Lin Chen ◽  
Yongqiang Yu ◽  
De-Zheng Sun

Abstract Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.


2010 ◽  
Vol 23 (8) ◽  
pp. 2030-2046 ◽  
Author(s):  
Yukari N. Takayabu ◽  
Shoichi Shige ◽  
Wei-Kuo Tao ◽  
Nagio Hirota

Abstract Three-dimensional distributions of the apparent heat source (Q1) − radiative heating (QR) estimated from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) utilizing the spectral latent heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated Q1 − QR averaged over the tropical oceans is estimated as ∼72.6 J s−1 (∼2.51 mm day−1) and that over tropical land is ∼73.7 J s−1 (∼2.55 mm day−1) for 30°N–30°S. It is shown that nondrizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems: deep systems and congestus. A rough estimate of the shallow-heating contribution against the total heating is about 46.7% for the average tropical oceans, which is substantially larger than the 23.7% over tropical land. Although cumulus congestus heating linearly correlates with SST, deep-mode heating is dynamically bounded by large-scale subsidence. It is notable that a substantial amount of rain, as large as 2.38 mm day−1 on average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that, even in the region with SSTs warmer than 28°C, large-scale subsidence effectively suppresses the deep convection, with the remaining heating by congestus clouds. The results support that the entrainment of mid–lower-tropospheric dry air, which accompanies the large-scale subsidence, is the major factor suppressing the deep convection. Therefore, a representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and the resultant large-scale circulation.


Sign in / Sign up

Export Citation Format

Share Document