scholarly journals Performance Assessment of General Circulation Model in Simulating Daily Precipitation and Temperature Using Multiple Gridded Datasets

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1793 ◽  
Author(s):  
Najeebullah Khan ◽  
Shamsuddin Shahid ◽  
Kamal Ahmed ◽  
Tarmizi Ismail ◽  
Nadeem Nawaz ◽  
...  
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
General Circulation Models ◽  
Daily Maximum ◽  
Gridded Data ◽  
Max Planck ◽  
Meteorological Forcing ◽  
Temperature And Precipitation ◽  
Feature Selection Approach

The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum, minimum temperature and precipitation for Pakistan using multiple sets of gridded data, namely: Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Berkeley Earth Surface Temperature (BEST), Princeton Global Meteorological Forcing (PGF) and Climate Prediction Centre (CPC) data. An entropy-based robust feature selection approach known as symmetrical uncertainty (SU) is used for the ranking of GCM. It is known from the results of this study that the spatial distribution of best-ranked GCMs varies for different sets of gridded data. The performance of GCMs is also found to vary for both temperatures and precipitation. The Commonwealth Scientific and Industrial Research Organization, Australia (CSIRO)-Mk3-6-0 and Max Planck Institute (MPI)-ESM-LR perform well for temperature while EC-Earth and MIROC5 perform well for precipitation. A trade-off is formulated to select the common GCMs for different climatic variables and gridded data sets, which identify six GCMs, namely: ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES and MIROC5 for the reliable projection of temperature and precipitation of Pakistan.

scholarly journals Biases and Model Agreement in Projections of Climate Extremes over the Tropical Pacific

2011 ◽  
Vol 15 (24) ◽  
pp. 1-36 ◽  
Author(s):  
Sarah E. Perkins
Keyword(s):  
Minimum Temperature ◽  
General Circulation ◽  
Coupled Model ◽  
Climate Extremes ◽  
General Circulation Models ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Temperature And Precipitation ◽  
Return Levels ◽  
The Mean

Abstract Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081–2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in-20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.

scholarly journals A Comparison of Two Dust Uplift Schemes within the Same General Circulation Model

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Duncan Ackerley ◽  
Manoj M. Joshi ◽  
Eleanor J. Highwood ◽  
Claire L. Ryder ◽  
Mark A. J. Harrison ◽  
...  
Keyword(s):  
General Circulation ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
General Circulation Models ◽  
System Modelling ◽  
Global Circulation ◽  
Temperature And Precipitation ◽  
Dust Size Distribution ◽  
West African Coast ◽  
Intercomparison Project

Aeolian dust modelling has improved significantly over the last ten years and many institutions now consistently model dust uplift, transport and deposition in general circulation models (GCMs). However, the representation of dust in GCMs is highly variable between modelling communities due to differences in the uplift schemes employed and the representation of the global circulation that subsequently leads to dust deflation. In this study two different uplift schemes are incorporated in the same GCM. This approach enables a clearer comparison of the dust uplift schemes themselves, without the added complexity of several different transport and deposition models. The global annual mean dust aerosol optical depths (at 550 nm) using two different dust uplift schemes were found to be 0.014 and 0.023—both lying within the estimates from the AeroCom project. However, the models also have appreciably different representations of the dust size distribution adjacent to the West African coast and very different deposition at various sites throughout the globe. The different dust uplift schemes were also capable of influencing the modelled circulation, surface air temperature, and precipitation despite the use of prescribed sea surface temperatures. This has important implications for the use of dust models in AMIP-style (Atmospheric Modelling Intercomparison Project) simulations and Earth-system modelling.

scholarly journals Fast responses on pre-industrial climate from present-day aerosols in a CMIP6 multi-model study

2020 ◽  
Vol 20 (14) ◽  
pp. 8381-8404 ◽  
Author(s):  
Prodromos Zanis ◽  
Dimitris Akritidis ◽  
Aristeidis K. Georgoulias ◽  
Robert J. Allen ◽  
Susanne E. Bauer ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
The Arctic ◽  
Temperature And Precipitation ◽  
Model Study ◽  
Temperature Responses ◽  
Circulation Changes

Abstract. In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014. In response to the pattern of all aerosols effective radiative forcing (ERF), the fast temperature responses are characterized by cooling over the continental areas, especially in the Northern Hemisphere, with the largest cooling over East Asia and India, sulfate being the dominant aerosol surface temperature driver for present-day emissions. In the Arctic there is a warming signal for winter in the ensemble mean of fast temperature responses, but the model-to-model variability is large, and it is presumably linked to aerosol-induced circulation changes. The largest fast precipitation responses are seen in the tropical belt regions, generally characterized by a reduction over continental regions and presumably a southward shift of the tropical rain belt. This is a characteristic and robust feature among most models in this study, associated with weakening of the monsoon systems around the globe (Asia, Africa and America) in response to hemispherically asymmetric cooling from a Northern Hemisphere aerosol perturbation, forcing possibly the Intertropical Convergence Zone (ITCZ) and tropical precipitation to shift away from the cooled hemisphere despite that aerosols' effects on temperature and precipitation are only partly realized in these simulations as the sea surface temperatures are kept fixed. An interesting feature in aerosol-induced circulation changes is a characteristic dipole pattern with intensification of the Icelandic Low and an anticyclonic anomaly over southeastern Europe, inducing warm air advection towards the northern polar latitudes in winter.

scholarly journals Using Different Formulations of the Transformed Eulerian Mean Equations and Eliassen–Palm Diagnostics in General Circulation Models

2010 ◽  
Vol 67 (6) ◽  
pp. 1983-1995 ◽  
Author(s):  
Steven C. Hardiman ◽  
David G. Andrews ◽  
Andy A. White ◽  
Neal Butchart ◽  
Ian Edmond
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Circulation Model ◽  
General Circulation Models ◽  
Primitive Equations ◽  
Model Output ◽  
Vertical Coordinate ◽  
Order Of Magnitude ◽  
Transformed Eulerian Mean

Abstract Transformed Eulerian mean (TEM) equations and Eliassen–Palm (EP) flux diagnostics are presented for the general nonhydrostatic, fully compressible, deep atmosphere formulation of the primitive equations in spherical geometric coordinates. The TEM equations are applied to a general circulation model (GCM) based on these general primitive equations. It is demonstrated that a naive application in this model of the widely used approximations to the EP diagnostics, valid for the hydrostatic primitive equations using log-pressure as a vertical coordinate and presented, for example, by Andrews et al. in 1987 can lead to misleading features in these diagnostics. These features can be of the same order of magnitude as the diagnostics themselves throughout the winter stratosphere. Similar conclusions are found to hold for “downward control” calculations. The reasons are traced to the change of vertical coordinate from geometric height to log-pressure. Implications for the modeling community, including comparison of model output with that from reanalysis products available only on pressure surfaces, are discussed.

scholarly journals The HAMMONIA Chemistry Climate Model: Sensitivity of the Mesopause Region to the 11-Year Solar Cycle and CO2 Doubling

2006 ◽  
Vol 19 (16) ◽  
pp. 3903-3931 ◽  
Author(s):  
H. Schmidt ◽  
G. P. Brasseur ◽  
M. Charron ◽  
E. Manzini ◽  
M. A. Giorgetta ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Solar Cycle ◽  
General Circulation ◽  
Climate Model ◽  
Temperature Response ◽  
Circulation Model ◽  
Max Planck ◽  
Dynamical Processes ◽  
Mesopause Region ◽  
Height Range

Abstract This paper introduces the three-dimensional Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), which treats atmospheric dynamics, radiation, and chemistry interactively for the height range from the earth’s surface to the thermosphere (approximately 250 km). It is based on the latest version of the ECHAM atmospheric general circulation model of the Max Planck Institute for Meteorology in Hamburg, Germany, which is extended to include important radiative and dynamical processes of the upper atmosphere and is coupled to a chemistry module containing 48 compounds. The model is applied to study the effects of natural and anthropogenic climate forcing on the atmosphere, represented, on the one hand, by the 11-yr solar cycle and, on the other hand, by a doubling of the present-day concentration of carbon dioxide. The numerical experiments are analyzed with the focus on the effects on temperature and chemical composition in the mesopause region. Results include a temperature response to the solar cycle by 2 to 10 K in the mesopause region with the largest values occurring slightly above the summer mesopause. Ozone in the secondary maximum increases by up to 20% for solar maximum conditions. Changes in winds are in general small. In the case of a doubling of carbon dioxide the simulation indicates a cooling of the atmosphere everywhere above the tropopause but by the smallest values around the mesopause. It is shown that the temperature response up to the mesopause is strongly influenced by changes in dynamics. During Northern Hemisphere summer, dynamical processes alone would lead to an almost global warming of up to 3 K in the uppermost mesosphere.

scholarly journals Multi-model dynamic climate emulator for solar geoengineering

2016 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ben Kravitz
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Circulation Model ◽  
Nonlinear Effects ◽  
Accurate Estimate ◽  
Natural Variability ◽  
Sea Ice Extent ◽  
Temperature And Precipitation ◽  
Solar Geoengineering

Abstract. Climate emulators trained on existing simulations can be used to project the climate effects that would result from different possible future pathways of anthropogenic forcing, without relying on general circulation model (GCM) simulations for every possible pathway. We extend this idea to include different amounts of solar geoengineering in addition to different pathways of green-house gas concentrations by training emulators from a multi-model ensemble of simulations from the Geoengineering Model Intercomparison Project (GeoMIP). The emulator is trained on the abrupt 4 x CO2 and a compensating solar reduction simulation (G1), and evaluated by comparing predictions against a simulated 1 % per year CO2 increase and a similarly smaller solar reduction (G2). We find reasonable agreement in most models for predicting changes in temperature and precipitation (including regional effects), and annual-mean Northern hemisphere sea ice extent, with the difference between simulation and prediction typically smaller than natural variability. This verifies that the linearity assumption used in constructing the emulator is sufficient for these variables over the range of forcing considered. Annual-minimum Northern hemisphere sea ice extent is less-well predicted, indicating the limits of the linearity assumption. For future pathways involving relatively small forcing from solar geoengineering, the errors introduced from nonlinear effects may be smaller than the uncertainty due to natural variability, and the emulator prediction may be a more accurate estimate of the forced component of the models' response than an actual simulation would be.

scholarly journals Do Downscaled General Circulation Models Reliably Simulate Historical Climatic Conditions?

2018 ◽  
Vol 22 (10) ◽  
pp. 1-22 ◽  
Author(s):  
Andrew R. Bock ◽  
Lauren E. Hay ◽  
Gregory J. McCabe ◽  
Steven L. Markstrom ◽  
R. Dwight Atkinson
Keyword(s):  
General Circulation ◽  
Statistical Tests ◽  
Circulation Model ◽  
General Circulation Models ◽  
Climatic Conditions ◽  
Low Flow ◽  
Balance Model ◽  
Monthly Precipitation ◽  
Significance Level ◽  
Ks Test

Abstract The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

scholarly journals Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Climate Model ◽  
Time Window ◽  
Coupled Model ◽  
Circulation Model ◽  
Scale Interactions ◽  
Climate Signals ◽  
Coupled Data Assimilation ◽  
Climate Analysis

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

scholarly journals Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  
Keyword(s):  
General Circulation ◽  
Bayesian Model Averaging ◽  
Mean Squared Error ◽  
Radiant Energy ◽  
Coupled Model ◽  
Model Averaging ◽  
Longwave Radiation ◽  
Energy System ◽  
General Circulation Models ◽  
The Individual

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).

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.

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