scholarly journals ENSO Prediction in Project Minerva: Sensitivity to Atmospheric Horizontal Resolution and Ensemble Size

2015 ◽  
Vol 28 (5) ◽  
pp. 2080-2095 ◽  
Author(s):  
Jieshun Zhu ◽  
Bohua Huang ◽  
Ben Cash ◽  
James L. Kinter ◽  
Julia Manganello ◽  
...  
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Horizontal Resolution ◽  
Prediction Skill ◽  
Ensemble Size ◽  
Enso Prediction ◽  
Significant Difference ◽  
Prediction Reliability ◽  
The Impact ◽  
Probabilistic Metrics

Abstract This study examines El Niño–Southern Oscillation (ENSO) prediction in Project Minerva, a recent collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The focus is primarily on the impact of the atmospheric horizontal resolution on ENSO prediction, but the effect from different ensemble sizes is also discussed. Particularly, three sets of 7-month hindcasts performed with ECMWF prediction system are compared, starting from 1 May (1 November) during 1982–2011 (1982–2010): spectral T319 atmospheric resolution with 15 ensembles, spectral T639 with 15 ensembles, and spectral T319 with 51 ensembles. The analysis herein shows that simply increasing either ensemble size from 15 to 51 or atmospheric horizontal resolution from T319 to T639 does not necessarily lead to major improvement in the ENSO prediction skill with current climate models. For deterministic prediction skill metrics, the three sets of predictions do not produce a significant difference in either anomaly correlation or root-mean-square error (RMSE). For probabilistic metrics, the increased atmospheric horizontal resolution generates larger ensemble spread, and thus increases the ratio between the intraensemble spread and RMSE. However, there is little change in the categorical distributions of predicted SST anomalies, and consequently there is little difference among the three sets of hindcasts in terms of probabilistic metrics or prediction reliability.

scholarly journals The impact of RCM formulation and resolution on simulated precipitation in Africa

2019 ◽  
Author(s):  
Minchao Wu ◽  
Grigory Nikulin ◽  
Erik Kjellström ◽  
Danijel Belušić ◽  
Colin Jones ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Added Value ◽  
Primary Control ◽  
Model Formulation ◽  
Simulated Precipitation ◽  
Mean Climate ◽  
The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs – SMHI-RCA4 and HCLIM38-ALADIN are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100 and 200 km. Additionally to the two RCMs, two different configurations of the same RCA4 are used. Contrasting different RCMs, configurations and resolutions it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle is completely controlled by model formulation (convection scheme) while its amplitude is a function of resolution. Although higher resolution in many cases leads to smaller biases in the time mean climate, the impact of higher resolution is mixed. An improvement in one region/season (e.g. reduction of dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). The experiments confirm a pronounced and well known impact of higher resolution – a more realistic distribution of daily precipitation. Even if the time-mean climate is not always greatly sensitive to resolution, what the time-mean climate is made up of, higher order statistics, is sensitive. Therefore, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and in general cannot be considered as an added value of downscaling.

The moisture budget of tropical cyclones: large scale environmental constraints and sensitivity to model horizontal resolution

2020 ◽  
Author(s):  
Benoit Vanniere ◽  
Malcolm Roberts ◽  
Pier Luigi Vidale ◽  
Kevin Hodges ◽  
Marie-Estelle Demory
Keyword(s):  
Tropical Cyclones ◽  
Large Scale ◽  
Climate Models ◽  
Potential Temperature ◽  
Large Change ◽  
Moisture Flux ◽  
Horizontal Resolution ◽  
Moisture Budget ◽  
High Resolution Models ◽  
The Impact

<p>Previous studies have shown that, the number, intensity and structure of simulated tropical cyclones (TC) in climate models get closer to the observations as the horizontal resolution is increased. However, the sensitivity of tropical cyclone precipitation and moisture budget to changes in resolution has received less attention. In this study, we use the five-model ensemble from project PRIMAVERA/HighResMIP to investigate the systematic changes associated with the water budget of tropical cyclones in a range of horizontal resolutions from 1º to 0.25º. Our results show that despite a large change in the distribution of TC intensity with resolution, the distribution of precipitation per TC does not change significantly. This result is explained by the large scale balance which characterises the moisture budget of TCs, i.e. radii of ~15º a scale that low and high resolution models represent equally well. The wind profile is found to converge between low and high resolutions for radii > 5º, resulting in a moisture flux convergence into the TC with similar magnitude at low and high resolutions. In contrast to precipitation per TC, the larger TC intensity at higher resolution is explained by the larger surface latent heat flux near the center of the storm, which leads to an increase in equivalent potential temperature and warmer core anomalies, despite representing a negligible contribution to the moisture budget. We discuss the complication arising from the choice of the tracking algorithm when assessing the impact of model resolution and the implications of such a constraint on the TC moisture budget in the context of climate change.</p>

scholarly journals Impact of Equatorial Atlantic Variability on ENSO Predictive Skill

2021 ◽  
Author(s):  
Eleftheria Exarchou ◽  
Pablo Ortega ◽  
Maria Belén Rodrıguez de Fonseca ◽  
Teresa Losada Doval ◽  
Irene Polo Sanchez ◽  
...  
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Sensitivity Study ◽  
Tropical Pacific ◽  
Climate Impacts ◽  
Equatorial Atlantic ◽  
Predictive Capacity ◽  
Predictive Skill ◽  
The Impact ◽  
The Tropical Pacific

<p>El Niño–Southern Oscillation (ENSO) is a key mode of climate variability with worldwide climate impacts. Recent studies have highlighted the impact of other tropical oceans on its variability. In particular, observations have demonstrated that summer Atlantic Niños (Niñas) favor the development of Pacific Niñas (Niños) the following winter, but it is unclear how well climate models capture this teleconnection and its role in defining the seasonal predictive skill of ENSO. Here we use an ensemble of seasonal forecast systems to demonstrate that a better representation of equatorial Atlantic variability in summer and its lagged teleconnection mechanism with the Pacific relates to enhanced predictive capacity of autumn/winter ENSO. An additional sensitivity study further shows that correcting SST variability in equatorial Atlantic improves different aspects of forecast skill in the Tropical Pacific, boosting ENSO skill. This study thus emphasizes that new efforts to improve the representation of equatorial Atlantic variability, a region with long standing systematic model biases, can foster predictive skill in the region, the Tropical Pacific and beyond, through the global impacts of ENSO.</p>

Testing robustness of co-existing climate states

2021 ◽  
Author(s):  
Charline Ragon ◽  
Valerio Lembo ◽  
Valerio Lucarini ◽  
Christian Vérard ◽  
Jérôme Kasparian ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Water Mass ◽  
Hydrological Cycle ◽  
Initial Conditions ◽  
Frictional Heating ◽  
Horizontal Resolution ◽  
Climate Dynamics ◽  
Mechanical Work ◽  
The Impact

<p><span>The climate can be regarded as a stationary non-equilibrium statistical system (Gallavotti 2006): a continuous and spatially inhomogeneous input of solar energy enters at the top-of-atmosphere and compensates the action of non-conservative forces, mainly occurring at small scales, to give rise to a statistically steady state (or attractor) for the whole climate. </span></p><p><span>Depending on the initial conditions and the range of forcing, all other parameters being the same, some climate models have the property to settle down on different attractors. </span><span>Multi-stability reflects how energy, water mass and entropy can be re-distributed in multiple ways among the climate components, such as the atmosphere, the ocean or the ice, through a different balance between nonlinear mechanisms. </span></p><p><span>Starting from a configuration where competing climate attractors occur under the same forcing, we have explored their robustness performing two kinds of numerical experiment. </span><span>First, we have investigated the impact of frictional heating on the overall energy balance and we have shown that such contribution, generally neglected in the atmospheric component of climate models, has crucial </span><span>consequences on conservation properties: it improves the energy imbalance at top-of-atmosphere, typically non negligible in coarse simulations (Wild et al. 2020), strengthens the hydrological cycle, </span><span>mitigates the mechanical work associated to atmospheric circulation intensity </span><span>and reduces the heat transport peaks in the ocean. </span><span>Second, we have compared two bulk formulas for the cloud albedo, one where it is constant everywhere and the other where it increases with latitude, as implemented in the new version of the atmospheric module SPEEDY in order to improve comparisons with observational data (Kucharski 2013). We have che</span><span>cked that this new parameterization does not affect energy and water-mass imbalances, while reduces global temperature and water-mass transport on the attractor, giving rise to a larger conversion of heat into mechanical work in the atmosphere.</span></p><p><span>In order to perform such studies, we have run the climate model MITgcm on coupled aquaplanets at 2.8 horizontal resolution until steady states are reached (Brunetti el al. 2019) and we have applied the Thermodynamic Diagnostic Tool (<em>TheDiaTo</em>, Lembo et al. 2019). </span></p><p> </p><p><span>References: </span></p><p><span>Brunetti, Kasparian, Vérard, Climate Dynamics 53, 6293 (2019)</span></p><p><span>Gallavotti, </span>Math. Phys. 3, 530<span> (2006)</span></p><p>Kucharski<span> et al.</span>, Bulletin of the American Meteorological Society 94, 25<span> (2013)</span></p><p>Lembo, Lunkeit, Lucarini, Geoscientific Model Development 12, 3805<span> (2019)</span></p><p><span>Wild, </span>Climate Dynamics 55, 553<span> (2020)</span></p>

Spectrally resolved OLR from IASI measurements

2020 ◽  
Author(s):  
Simon Whitburn ◽  
Lieven Clarisse ◽  
Sophie Bauduin ◽  
Steven Dewitte ◽  
Maya George ◽  
...  
Keyword(s):  
Spectral Range ◽  
Climate Models ◽  
Southern Oscillation ◽  
Radiation Budget ◽  
Retrieval Algorithm ◽  
Distribution Models ◽  
Reanalysis Dataset ◽  
The Earth ◽  
Spectrally Resolved ◽  
The Impact

<p>The Earth’s Outgoing Longwave Radiation (OLR) is a key component in the study of climate feedbacks and processes. As part of the Earth’s radiation budget, it reflects how the Earth-atmosphere system compensates the incoming solar radiation at the top of the atmosphere. It can be retrieved from the radiance intensities measured by satellite sounders and integrated over all the zenith angles of observation. Since satellite instruments generally acquire the radiance at a limited number of viewing angle directions and because the radiance field is not isotropic, the conversion is however not straightforward. This problem is usually overcome by the use of empirical angular distribution models (ADMs) developed for different scene types that directly link the directional radiance measurement to the corresponding OLR.</p><p>OLR estimates from dedicated broadband instruments are available since the mid-1970s; however, such instruments only provide an integrated OLR estimate over a broad spectral range. They are therefore not well suited for tracking separately the impact of the different parameters affecting the OLR (including greenhouse gases), making it difficult to track down deficiencies in climate models. Currently, several hyperspectral instruments in space acquire radiances in the thermal infrared spectral range, and in principle, these should allow to better constrain the OLR. However, as these instruments were not specifically designed to measure the OLR, there are several challenges to overcome. Here we propose a new retrieval algorithm for the estimation of the spectrally resolved OLR from measurements made by the IASI sounder on board the Metop satellites. It is based on a set of spectrally resolved ADMs developed from synthetic spectra for a large selection of scene types associated with different states of the atmosphere and the surface. Atmospheric and surface parameters are derived from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset and selected using a dissimilarity-based subset selection algorithm. These spectral ADMs are then used to convert the measured IASI radiances into spectral OLR.</p><p>We then evaluate how the IASI OLR compare with the CERES and the AIRS integrated and spectral OLR. We analyze the interannual variations in OLR over 10 years of IASI measurements for selected spectral channels using EOF analysis and we connect them with well-known climate phenomena such as El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Atlantic Multidecadal Oscillation (AMO).</p>

scholarly journals Seasonal-to-Interannual Prediction Skills of Near-Surface Air Temperature in the CMIP5 Decadal Hindcast Experiments

2016 ◽  
Vol 29 (4) ◽  
pp. 1511-1527 ◽  
Author(s):  
Jung Choi ◽  
Seok-Woo Son ◽  
Yoo-Geun Ham ◽  
June-Yi Lee ◽  
Hye-Mi Kim
Keyword(s):  
Air Temperature ◽  
Climate Models ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Equatorial Pacific ◽  
Prediction Skill ◽  
Good Opportunity ◽  
Near Surface ◽  
Global Mean

Abstract This study explores the seasonal-to-interannual near-surface air temperature (TAS) prediction skills of state-of-the-art climate models that were involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) decadal hindcast/forecast experiments. The experiments are initialized in either November or January of each year and integrated for up to 10 years, providing a good opportunity for filling the gap between seasonal and decadal climate predictions. The long-lead multimodel ensemble (MME) prediction is evaluated for 1981–2007 in terms of the anomaly correlation coefficient (ACC) and mean-squared skill score (MSSS), which combines ACC and conditional bias, with respect to observations and reanalysis data, paying particular attention to the seasonal dependency of the global-mean and equatorial Pacific TAS predictions. The MME shows statistically significant ACCs and MSSSs for the annual global-mean TAS for up to two years, mainly because of long-term global warming trends. When the long-term trends are removed, the prediction skill is reduced. The prediction skills are generally lower in boreal winters than in other seasons regardless of lead times. This lack of winter prediction skill is attributed to the failure of capturing the long-term trend and interannual variability of TAS over high-latitude continents in the Northern Hemisphere. In contrast to global-mean TAS, regional TAS over the equatorial Pacific is predicted well in winter. This is mainly due to a successful prediction of the El Niño–Southern Oscillation (ENSO). In most models, the wintertime ENSO index is reasonably well predicted for at least one year in advance. The sensitivity of the prediction skill to the initialized month and method is also discussed.

scholarly journals Assessment of the Canary current upwelling system in a regionally coupled climate model

2021 ◽  
Author(s):  
Ruben Vazquez ◽  
Ivan Parras-Berrocal ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Rafael Mañanes ◽  
...  
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Climate Change Signal ◽  
Climate Modelling ◽  
Near Surface ◽  
Upwelling System ◽  
The Impact ◽  
Mesoscale Processes

AbstractThe Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere–ocean regionally coupled model. The regional coupled model presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. The coupled system reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. Moreover, it shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields, showing the impact of the higher resolution and coupling for CCUS climate modelling. The model is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of the regionally coupled model to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence.

scholarly journals Impact of equatorial Atlantic variability on ENSO predictive skill

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eleftheria Exarchou ◽  
Pablo Ortega ◽  
Belén Rodríguez-Fonseca ◽  
Teresa Losada ◽  
Irene Polo ◽  
...  
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Sensitivity Study ◽  
Tropical Pacific ◽  
Climate Impacts ◽  
Equatorial Atlantic ◽  
Predictive Capacity ◽  
Predictive Skill ◽  
The Impact ◽  
The Tropical Pacific

AbstractEl Niño-Southern Oscillation (ENSO) is a key mode of climate variability with worldwide climate impacts. Recent studies have highlighted the impact of other tropical oceans on its variability. In particular, observations have demonstrated that summer Atlantic Niños (Niñas) favor the development of Pacific Niñas (Niños) the following winter, but it is unclear how well climate models capture this teleconnection and its role in defining the seasonal predictive skill of ENSO. Here we use an ensemble of seasonal forecast systems to demonstrate that a better representation of equatorial Atlantic variability in summer and its lagged teleconnection mechanism with the Pacific relates to enhanced predictive capacity of autumn/winter ENSO. An additional sensitivity study further shows that correcting SST variability in equatorial Atlantic improves different aspects of forecast skill in the Tropical Pacific, boosting ENSO skill. This study thus emphasizes that new efforts to improve the representation of equatorial Atlantic variability, a region with long standing systematic model biases, can foster predictive skill in the region, the Tropical Pacific and beyond, through the global impacts of ENSO.

scholarly journals A statistical and process oriented evaluation of cloud radiative effects in high resolution global models

2018 ◽  
Author(s):  
Manu Anna Thomas ◽  
Abhay Devasthale ◽  
Torben Koenigk ◽  
Klaus Wyser ◽  
Malcolm Roberts ◽  
...  
Keyword(s):  
High Resolution ◽  
Southern Oscillation ◽  
Global Climate Model ◽  
Radiant Energy ◽  
Horizontal Resolution ◽  
Radiative Effects ◽  
Resolution Model ◽  
High Resolution Model ◽  
Cloud Radiative Effects ◽  
The Impact

Abstract. This study evaluates the impact of atmospheric horizontal resolution on the representation of cloud radiative effects (CREs) in an ensemble of global climate model simulations following the protocols of the High Resolution Model Intercomparison Project (HighResMIP). We compare results from four European modelling centres, each of which provides data from "standard" and "high" resolution model configurations. Simulated radiative fluxes are compared with observation-based estimates derived from the Clouds and Earth's Radiant Energy System (CERES) dataset. Model CRE biases are evaluated using both conventional statistics (e.g. time and spatial averages) and after conditioning on the phase of two modes of internal climate variability, namely the El Niño and Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Simulated top-of-atmosphere (TOA) and surface CREs show large biases over the polar regions, particularly over regions where seasonal sea-ice variability is strongest. Increasing atmospheric resolution does not significantly improve these biases. The spatial structure of the cloud radiative response to ENSO and NAO variability is simulated reasonably well by all model configurations considered in this study. However, it is difficult to identify a systematic impact of atmospheric resolution on the associated CRE errors. Mean absolute CRE errors conditioned on ENSO phase are relatively large (5–10 W/m2) and show differences between models. We suggest this is a consequence of differences in the parameterization of SW radiative transfer and the treatment of cloud optical properties rather than a result of differences in resolution. In contrast, mean absolute CRE errors conditioned on NAO phase are generally smaller (0–2 W/m2) and more similar across models. Although the regional details of CRE biases show some sensitivity to atmospheric resolution within a particular model, it is difficult to identify patterns that hold across all models. This apparent insensitivity to increased atmospheric horizontal resolution indicates that physical parameterizations play a dominant role in determining the behaviour of cloud-radiation feedbacks. However, we note that these results are obtained from atmosphere-only simulations and the impact of changes in atmospheric resolution may be different in the presence of coupled climate feedbacks.

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