scholarly journals Precipitation and Moisture in Four Leading CMIP5 Models: Biases across Large-Scale Circulation Regimes and Their Attribution to Dynamic and Thermodynamic Factors

2018 ◽  
Vol 31 (13) ◽  
pp. 5089-5106 ◽  
Author(s):  
Mengmiao Yang ◽  
Guang J. Zhang ◽  
De-Zheng Sun
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Frequency Of Occurrence ◽  
Upward Motion ◽  
Large Scale Circulation ◽  
Intercomparison Project ◽  
Strong Upward Motion

As key variables in general circulation models, precipitation and moisture in four leading models from CMIP5 (phase 5 of the Coupled Model Intercomparison Project) are analyzed, with a focus on four tropical oceanic regions. It is found that precipitation in these models is overestimated in most areas. However, moisture bias has large intermodel differences. The model biases in precipitation and moisture are further examined in conjunction with large-scale circulation by regime-sorting analysis. Results show that all models consistently overestimate the frequency of occurrence of strong upward motion regimes and peak descending regimes of 500-hPa vertical velocity [Formula: see text]. In a given [Formula: see text] regime, models produce too much precipitation compared to observation and reanalysis. But for moisture, their biases differ from model to model and also from level to level. Furthermore, error causes are revealed through decomposing contribution biases into dynamic and thermodynamic components. For precipitation, the contribution errors in strong upward motion regimes are attributed to the overly frequent [Formula: see text]. In the weak upward motion regime, the biases in the dependence of precipitation on [Formula: see text] and the [Formula: see text] probability density function (PDF) make comparable contributions, but often of opposite signs. On the other hand, the biases in column-integrated water vapor contribution are mainly due to errors in the frequency of occurrence of [Formula: see text], while thermodynamic components contribute little. These findings suggest that errors in the frequency of [Formula: see text] occurrence are a significant cause of biases in the precipitation and moisture simulation.

scholarly journals Precipitation in the Amazon and its relationship with moisture transport and tropical Pacific and Atlantic SST from the CMIP5 simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 671-704 ◽  
Author(s):  
G. Martins ◽  
C. von Randow ◽  
G. Sampaio ◽  
A. J. Dolman
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Regional Analysis ◽  
Coupled Model ◽  
General Circulation Models ◽  
Moisture Convergence ◽  
Cmip5 Models ◽  
Wet Season ◽  
The Pacific ◽  
Eastern Edge

Abstract. Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
South Asia ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
River Basins ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.

scholarly journals Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 723 ◽  
Author(s):  
Erzsébet Kristóf ◽  
Zoltán Barcza ◽  
Roland Hollós ◽  
Judit Bartholy ◽  
Rita Pongrácz
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Evaluation Method ◽  
Polynomial Regression ◽  
Diversity Index ◽  
Regional Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Atmospheric Teleconnections

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.

scholarly journals CMIP5 temperature biases and 21st century warming around the Antarctic coast

2016 ◽  
Vol 57 (73) ◽  
pp. 69-78 ◽  
Author(s):  
Christopher M. Little ◽  
Nathan M. Urban
Keyword(s):  
Mass Balance ◽  
21St Century ◽  
General Circulation ◽  
Large Scale ◽  
Ice Sheet ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ensemble Mean ◽  
Rcp 8.5 ◽  
Ice Sheet Mass Balance

ABSTRACTProjections of ice-sheet mass balance require regional ocean warming projections derived from atmosphere-ocean general circulation models (AOGCMs). However, the coarse resolution of AOGCMs: (1) may lead to systematic or AOGCM-specific biases and (2) makes it difficult to identify relevant water masses. Here, we employ a large-scale metric of Antarctic Shelf Bottom Water (ASBW) to investigate circum-Antarctic temperature biases and warming projections in 19 different Coupled Model Intercomparison Project Phase 5 (CMIP5) AOGCMs forced with two different ‘representative concentration pathways’ (RCPs). For high-emissions RCP 8.5, the ensemble mean 21st century ASBW warming is 0.66, 0.74 and 0.58°C for the Amundsen, Ross and Weddell Seas (AS, RS and WS), respectively. RCP 2.6 ensemble mean projections are substantially lower: 0.21, 0.26, and 0.19°C. All distributions of regional ASBW warming are positively skewed; for RCP 8.5, four AOGCMs project warming of greater than 1.8°C in the RS. Across the ensemble, there is a strong, RCP-independent, correlation between WS and RS warming. AS warming is more closely linked to warming in the Southern Ocean. We discuss possible physical mechanisms underlying the spatial patterns of warming and highlight implications of these results on strategies for forcing ice-sheet mass balance projections.

Assessing the spatio-temporal uncertainties in future meteorological droughts from CMIP5 models, emission scenarios and bias corrections

2020 ◽  
pp. 1-58
Author(s):  
Chuanhao Wu ◽  
Pat J.-F. Yeh ◽  
Jiali Ju ◽  
Yi-Ying Chen ◽  
Kai Xu ◽  
...  
Keyword(s):  
General Circulation ◽  
Standardized Precipitation Index ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Northern Asia ◽  
Drought Characteristics ◽  
Uncertainty Sources ◽  
Spatio Temporal ◽  
The Standardized Precipitation Index

AbstractDrought projections are accompanied with large uncertainties due to varying estimates of future warming scenarios from different modelling and forcing data. Using the Standardized Precipitation Index (SPI), this study presents a global assessment of uncertainties in drought characteristics (severity S and frequency Df) projections based on the simulations of 28 general circulation models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A hierarchical framework incorporating a variance–based global sensitivity analysis was developed to quantify the uncertainties in drought characteristics projections at various spatial (global and regional) and temporal (decadal and 30-yr) scales due to 28 GCMs, 3 Representative Concentration Pathway scenarios (RCP2.6, RCP4.5, RCP8.5), and 2 bias-correction (BC) methods. The results indicated that the largest uncertainty contribution in the globally projected S and Df is from the GCM (>60%), followed by BC (<35%) and RCP (<16%). Spatially, BC reduces the spreads among GCMs particularly in Northern Hemisphere (NH), leading to smaller GCM uncertainty in NH than Southern Hemisphere (SH). In contrast, the BC and RCP uncertainties are larger in NH than SH, and the BC uncertainty can be larger than GCM uncertainty for some regions (e.g., southwest Asia). At the decadal and 30-yr timescales, the contributions for 3 uncertainty sources show larger variability in S than Df projections, especially in SH. The GCM and BC uncertainties show overall decreasing trends with time, while the RCP uncertainty is expected to increase over time and even can be larger than BC uncertainty for some regions (e.g., northern Asia) by the end of this century.

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 An Assessment of Future Southern Hemisphere Blocking Using CMIP5 Projections from Four GCMs

2016 ◽  
Vol 29 (21) ◽  
pp. 7599-7611 ◽  
Author(s):  
Simon Parsons ◽  
James A. Renwick ◽  
Adrian J. McDonald
Keyword(s):  
Southern Hemisphere ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Southern Annular Mode ◽  
Model Intercomparison ◽  
Future Projections ◽  
South Pacific Ocean ◽  
Blocking Activity ◽  
Intercomparison Project

AbstractThis study is concerned with blocking events (BEs) in the Southern Hemisphere (SH), their past variability, and future projections. ERA-Interim (ERA-I) is used to compare the historical output from four general circulation models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5); the output of the representative concentration pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) projections are also examined. ERA-I shows that the higher latitudes of the South Pacific Ocean (SPO) are the main blocking region, with blocking occurring predominantly in winter. The CMIP5 historical simulations also agree well with ERA-I for annual and seasonal BE locations and frequencies. A reduction in BEs is observed in the SPO in the 2071–2100 period in the RCP4.5 projections, and this is more pronounced for the RCP8.5 projections and occurs predominantly during the spring and summer seasons. Preliminary investigations imply that the southern annular mode (SAM) is negatively correlated with blocking activity in the SPO in all seasons in the reanalysis. This negative correlation is also observed in the GCM historical output. However, in the RCP projections this correlation is reduced in three of the four models during summer, suggesting that SAM may be less influential in summertime blocking in the future.

scholarly journals Cloud and Water Vapor Feedbacks to the El Niño Warming: Are They Still Biased in CMIP5 Models?

2013 ◽  
Vol 26 (14) ◽  
pp. 4947-4961 ◽  
Author(s):  
Lin Chen ◽  
Yongqiang Yu ◽  
De-Zheng Sun
Keyword(s):  
Water Vapor ◽  
El Niño ◽  
Radiative Forcing ◽  
Large Scale ◽  
El Nino ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Cold Tongue ◽  
Key Factor ◽  
Intercomparison Project

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.

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