scholarly journals Intercomparison of Near-Surface Temperature and Precipitation Extremes in AMIP-2 Simulations, Reanalyses, and Observations

2005 ◽  
Vol 18 (24) ◽  
pp. 5201-5223 ◽  
Author(s):  
Viatcheslav V. Kharin ◽  
Francis W. Zwiers ◽  
Xuebin Zhang

Abstract The extremes of near-surface temperature and 24-h and 5-day mean precipitation rates are examined in simulations performed with atmospheric general circulation models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2). The extremes are evaluated in terms of 20-yr return values of annual extremes. The model results are validated against the European Centre for Medium-Range Weather Forecasts and National Centers for Environmental Prediction reanalyses and station data. Precipitation extremes are also validated against the pentad dataset of the Global Precipitation Climatology Project, which is a blend of rain gauge observations, satellite data, and model output. On the whole, the AGCMs appear to simulate temperature extremes reasonably well. Model disagreements are larger for cold extremes than for warm extremes, particularly in wet and cloudy regions, and over sea ice and snow-covered areas. Many models exhibit an exaggerated clustering behavior for temperatures near the freezing point of water. Precipitation extremes are less reliably reproduced by the models and reanalyses. The largest disagreements are found in the Tropics where the parameterizations of deep convection affect the simulated daily precipitation extremes.

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1594 ◽  
Author(s):  
Beatriz Garcia ◽  
Renata Libonati ◽  
Ana Nunes

The Amazon basin has experienced severe drought events for centuries, mainly associated with climate variability connected to tropical North Atlantic and Pacific sea surface temperature anomalous warming. Recently, these events are becoming more frequent, more intense and widespread. Because of the Amazon droughts environmental and socioeconomic impacts, there is an increased demand for understanding the characteristics of such extreme events in the region. In that regard, regional models instead of the general circulation models provide a promising strategy to generate more detailed climate information of extreme events, seeking better representation of physical processes. Due to uneven spatial distribution and gaps found in station data in tropical South America, and the need of more refined climate assessment in those regions, satellite-enhanced regional downscaling for applied studies (SRDAS) is used in the reconstruction of South American hydroclimate, with hourly to monthly outputs from January 1998. Accordingly, this research focuses on the analyses of recent extreme drought events in the years of 2005 and 2010 in the Amazon Basin, using the SRDAS monthly means of near-surface temperature and relative humidity, precipitation and vertically integrated soil moisture fields. Results from this analysis corroborate spatial and temporal patterns found in previous studies on extreme drought events in the region, displaying the distinctive features of the 2005 and 2010 drought events.


2010 ◽  
Vol 23 (5) ◽  
pp. 1127-1145 ◽  
Author(s):  
A. Bellucci ◽  
S. Gualdi ◽  
A. Navarra

Abstract The double–intertropical convergence zone (DI) systematic error, affecting state-of-the-art coupled general circulation models (CGCMs), is examined in the multimodel Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) ensemble of simulations of the twentieth-century climate. The aim of this study is to quantify the DI error on precipitation in the tropical Pacific, with a specific focus on the relationship between the DI error and the representation of large-scale vertical circulation regimes in climate models. The DI rainfall signal is analyzed using a regime-sorting approach for the vertical circulation regimes. Through the use of this compositing technique, precipitation events are regime sorted based on the large-scale vertical motions, as represented by the midtropospheric Lagrangian pressure tendency ω500 dynamical proxy. This methodology allows partition of the precipitation signal into deep and shallow convective components. Following the regime-sorting diagnosis, the total DI bias is split into an error affecting the magnitude of precipitation associated with individual convective events and an error affecting the frequency of occurrence of single convective regimes. It is shown that, despite the existing large intramodel differences, CGCMs can be ultimately grouped into a few homogenous clusters, each featuring a well-defined rainfall–vertical circulation relationship in the DI region. Three major behavioral clusters are identified within the AR4 models ensemble: two unimodal distributions, featuring maximum precipitation under subsidence and deep convection regimes, respectively, and one bimodal distribution, displaying both components. Extending this analysis to both coupled and uncoupled (atmosphere only) AR4 simulations reveals that the DI bias in CGCMs is mainly due to the overly frequent occurrence of deep convection regimes, whereas the error on rainfall magnitude associated with individual convective events is overall consistent with errors already present in the corresponding atmosphere stand-alone simulations. A critical parameter controlling the strength of the DI systematic error is identified in the model-dependent sea surface temperature (SST) threshold leading to the onset of deep convection (THR), combined with the average SST in the southeastern Pacific. The models featuring a THR that is systematically colder (warmer) than their mean surface temperature are more (less) prone to exhibit a spurious southern intertropical convergence zone.


2017 ◽  
Vol 8 (2) ◽  
pp. 295-312 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza

Abstract. Seasonal variability in near-surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere–ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between near-surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically, (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres, and (ii) at the annual frequency, estimates of the relative phase between near-surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1-month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3, but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterizing the cyclic response of current global atmosphere–ocean models to the external (solar) forcing that is of interest for seasonal forecasts.


2017 ◽  
Vol 30 (12) ◽  
pp. 4527-4545 ◽  
Author(s):  
F. Hugo Lambert ◽  
Angus J. Ferraro ◽  
Robin Chadwick

A compositing scheme that predicts changes in tropical precipitation under climate change from changes in near-surface relative humidity (RH) and temperature is presented. As shown by earlier work, regions of high tropical precipitation in general circulation models (GCMs) are associated with high near-surface RH and temperature. Under climate change, it is found that high precipitation continues to be associated with the highest surface RH and temperatures in most CMIP5 GCMs, meaning that it is the “rank” of a given GCM grid box with respect to others that determines how much precipitation falls rather than the absolute value of surface temperature or RH change, consistent with the weak temperature gradient approximation. Further, it is demonstrated that the majority of CMIP5 GCMs are close to a threshold near which reductions in land RH produce large reductions in the RH ranking of some land regions, causing reductions in precipitation over land, particularly South America, and compensating increases over ocean. Recent work on predicting future changes in specific humidity allows the prediction of the qualitative sense of precipitation change in some GCMs when land surface humidity changes are unknown. However, the magnitudes of predicted changes are too small. Further study, perhaps into the role of radiative and land–atmosphere feedbacks, is necessary.


2011 ◽  
Vol 24 (4) ◽  
pp. 1053-1070 ◽  
Author(s):  
Tianjun Zhou ◽  
Jie Zhang

Abstract Recent studies have identified different modes associated with two flavors of El Niño in terms of the three-dimensional structure of atmospheric temperature. The first is a deep-warm mode, which features a coherent zonal mean warming throughout the troposphere from 30°N to 30°S with cooling aloft. The second is a shallow-warm mode, which features strong wave signatures in the troposphere with warmth (coolness) over the central Pacific (western Pacific). The ability to simulate these two modes is a useful metric for evaluating climate models. To understand the reproducibility of these two modes, the authors analyzed the multimodel ensemble mean (MMEM) of 11 atmospheric general circulation models (AGCMs) that participated in the second phase of the Atmospheric Model Intercomparison Project (AMIP II). Each model was run in an AGCM-alone mode forced by historical sea surface temperatures covering the period 1980–99. The authors find that atmospheric temperature variability is generally well captured in the MMEM of AMIP II models, demonstrating that the observational changes documented here are driven by SST changes during the El Niño events and the variety of vertical temperature structures associated with two flavors of El Niño are highly reproducible. The model skill for the first mode is slightly higher than the second mode. The skill in the upper troposphere–lower stratosphere is lower than for the tropospheric counterpart, especially at high latitudes. The performances of individual models are also assessed. The authors also show some differences from previous data analyses, including the variance accounted for by the two modes, as well as the lead–lag relationship of the shallow-warm mode with the Niño-3.4 index.


2019 ◽  
Vol 15 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Marina Suzuki

Abstract. There remain substantial uncertainties in future projections of Arctic climate change. There is a potential to constrain these uncertainties using a combination of paleoclimate simulations and proxy data, but such a constraint must be accompanied by physical understanding on the connection between past and future simulations. Here, we examine the relevance of an Arctic warming mechanism in the mid-Holocene (MH) to the future with emphasis on process understanding. We conducted a surface energy balance analysis on 10 atmosphere and ocean general circulation models under the MH and future Representative Concentration Pathway (RCP) 4.5 scenario forcings. It is found that many of the dominant processes that amplify Arctic warming over the ocean from late autumn to early winter are common between the two periods, despite the difference in the source of the forcing (insolation vs. greenhouse gases). The positive albedo feedback in summer results in an increase in oceanic heat release in the colder season when the atmospheric stratification is strong, and an increased greenhouse effect from clouds helps amplify the warming during the season with small insolation. The seasonal progress was elucidated by the decomposition of the factors associated with sea surface temperature, ice concentration, and ice surface temperature changes. We also quantified the contribution of individual components to the inter-model variance in the surface temperature changes. The downward clear-sky longwave radiation is one of major contributors to the model spread throughout the year. Other controlling terms for the model spread vary with the season, but they are similar between the MH and the future in each season. This result suggests that the MH Arctic change may not be analogous to the future in some seasons when the temperature response differs, but it is still useful to constrain the model spread in the future Arctic projection. The cross-model correlation suggests that the feedbacks in preceding seasons should not be overlooked when determining constraints, particularly summer sea ice cover for the constraint of autumn–winter surface temperature response.


2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.


2014 ◽  
Vol 10 (2) ◽  
pp. 697-713 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot

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.


2016 ◽  
Author(s):  
Valerio Lembo ◽  
Isabella Bordi ◽  
Antonio Speranza

Abstract. Seasonal variability of surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere-ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically: (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres; (ii) at the annual frequency, estimates of the relative phase between surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1 month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3 but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterize the cyclic response of current global atmosphere-ocean models to the external (solar) forcing that is of interest for seasonal forecasts.


2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.


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