Enrique Sánchez

Simulations of Trade Wind Cumuli under a Strong Inversion

The fifth intercomparison of the Global Water and Energy Experiment Cloud System Studies Working Group 1 is used as a vehicle for better understanding the dynamics of trade wind cumuli capped by a strong inversion. The basis of the intercomparison is 10 simulations by 7 groups. These simulations are supplemented by many further sensitivity studies, including some with very refined grid meshes. The simulations help illustrate the turbulent dynamics of trade cumuli in such a regime. In many respects the dynamics are similar to those found in many previous simulations of trade cumuli capped by weaker inversions. The principal differences are the extent to which the cloud layer is quasi-steady in the current simulations, evidence of weak countergradient momentum transport within the cloud layer, and the development and influence of an incipient stratiform cloud layer at the top of the cloud layer. Although many elements of the turbulent structure (including the wind profiles, the evolution of cloud-base height, the statistics of the subcloud layer, and the nature of mixing in the lower and middle parts of the cloud layer) are robustly predicted, the representation of the stratiform cloud amount by the different simulations is remarkably sensitive to a number of factors. Chief among these are differences between numerical algorithms. These sensitivities persist even among simulations on relatively refined grid meshes. Part of this sensitivity is attributed to a physically realistic positive radiative feedback, whereby a propensity toward higher cloud fractions in any given simulation is amplified by longwave radiative cooling. The simulations also provide new insight into the dynamics of the transition layer at cloud base. In accord with observations, the simulations predict that this layer is most identifiable in terms of moisture variances and gradients. The simulations help illustrate the highly variable (in both height and thickness) nature of the transition layer, and we speculate that this variability helps regulate convection. Lastly the simulations are used to help evaluate simple models of trade wind boundary layers. In accord with previous studies, mass-flux models well represent the dynamics of the cloud layer, while mixing-length models well represent the subcloud layer. The development of the stratiform cloud layer is not, however, captured by the mass-flux models. The simulations indicate that future theoretical research needs to focus on interface rules, whereby the cloud layer is coupled to the subcloud layer below and the free atmosphere above. Future observational studies of this regime would be of most benefit if they could provide robust cloud statistics as a function of mean environmental conditions.

Regional changes in precipitation in Europe under an increased greenhouse emissions scenario

[1] Regional multi-model ensembles are used to both increase the spatial resolution of the global simulations and to palliate uncertainties arising from different parameterizations and dynamical cores. Here, we present the simulated current (1960-1990) and future (2070-2100) precipitation climatologies using eight Regional Climate Models (RCM) over Europe for an increased greenhouse gases scenario. Analysis of the current climate simulations in terms of the Probability Distribution Functions (PDF) shows noticeable regional differences in the type of precipitation which are in agreement with known precipitation climatologies. For future climate we observe an overall decrease of mean precipitation in most of the Mediterranean regions. A rise in high monthly precipitation amounts appear for all the regions, except for the Iberian peninsula and the Alps. As our analysis embed both spatial and temporal uncertainties in the modeling, our results provide further evidence of a variety of regional patterns within Europe under an increased greenhouse emissions scenario.

Regional climate modelling in CLARIS-LPB : a concerted approach towards twentyfirst century projections of regional temperature and precipitation over South America

Abstract The results of an ensemble of regional climate model (RCM) simulations over South America are presented. This is the first coordinated exercise of regional climate modelling studies over the continent, as part of the CLARIS-LPB EU FP7 project. The results of different future periods, with the main focus on (2071–2100) is shown, when forced by several global climate models, all using the A1B greenhouse gases emissions scenario. The analysis is focused on the mean climate conditions for both temperature and precipitation. The common climate change signals show an overall increase of temperature for all the seasons and regions, generally larger for the austral winter season. Future climate shows a precipitation decrease over the tropical region, and an increase over the subtropical areas. These climate change signals arise independently of the driving global model and the RCM. The internal variability of the driving global models introduces a very small level of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identification of the common climate change signals and their associated uncertainties for several subregions within the South American continent.

Performance of a multi-RCM ensemble for South Eastern South America

The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991–2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons.

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management.

The surface radiation budget over South America in a set of regional climate models from the CLARIS-LPB project

The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990–2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA.

Simplified nonquasi-static FET modelling approach experimentally validated up to 118.5 GHz

In this paper two similar simplified nonquasi-static approaches are applied for high-frequency large-signal FET prediction. Both account for low-frequency dispersion and use a simplified extraction process through the use of linear delays. Excellent results are obtained from dc up to the device f/sub T/ frequencies, even when f/sub T/ is 120 GHz. For low-frequency prediction a simple quasi-static extrinsic approach can produce excellent results thus further simplifying modelling. The influence of including the low-frequency dispersion modelling is also taken into account.

Assessment of multiple daily precipitation statistics in ERA-Interim driven Med-CORDEX and EURO-CORDEX experiments against high resolution observations

We assess the statistics of different daily precipitation indices in ensembles of Med-CORDEX and EURO-CORDEX experiments at high resolution (grid spacing of ~0.11°, or RCM11) and medium resolution (grid spacing of ~0.44°, or RCM44) with regional climate models (RCMs) driven by the ERA-Interim reanalysis of observations for the period 1989–2008. The assessment is carried out by comparison with a set of high resolution observation datasets for nine European subregions. The statistics analyzed include quantitative metrics for mean precipitation, daily precipitation probability density functions (PDFs), daily precipitation intensity, frequency, 95th percentile and 95th percentile of dry spell length. We assess an ensemble including all Med-CORDEX and EURO-CORDEX models together and others including the Med-CORDEX and EURO-CORDEX separately. For the All Models ensembles, the RCM11 one shows a remarkable performance in reproducing the spatial patterns and seasonal cycle of mean precipitation over all regions, with a consistent and marked improvement compared to the RCM44 ensemble and the ERA-Interim reanalysis. A good consistency with observations by the RCM11 ensemble (and a substantial improvement compared to RCM44 and ERA-Interim) is found also for the daily precipitation PDFs, mean intensity and, to a lesser extent, the 95th percentile. A general improvement by the RCM11 models is also found when the data are upscaled and intercompared at the 0.44° and 1.5° resolutions. For some regions the RCM11 ensemble overestimates the occurrence of very high intensity events while for one region the models underestimate the occurrence of the most intense extremes. The RCM11 ensemble still shows a general tendency to underestimate the dry day frequency and 95th percentile of dry spell length over wetter regions, with only a marginal improvement compared to the lower resolution models. This indicates that the problem of the excessive production of low precipitation events found in many climate models persists also at relatively high resolutions, at least in wet climate regimes. Concerning the Med-CORDEX and EURO-CORDEX ensembles we find that their performance is of similar quality over the Mediterranean regions analyzed. Finally, we stress the need of consistent and quality checked fine scale observation datasets for the assessment of RCMs run at increasingly high horizontal resolutions.

Planetary boundary layer energetics simulated from a regional climate model over Europe for present climate and climate change conditions

[1] This paper presents a description of the planetary boundary layer (PBL) for current (1960–1990) and future (2070–2100) climate periods as obtained from a regional climate model (RCM) centered on the Mediterranean basin. Vertically integrated turbulent kinetic energy (TKEZ) and boundary layer height (zi) are used to describe PBL energetics. Present climate shows a TKEZ annual cycle with a clear summer maximum for southern regions, while northern regions of Europe exhibit a smoother or even a lack of cycle. Future climate conditions exhibit a similar behaviour, with an increase in the summer maximum peaks. A detailed analysis of summer surface climate change energetics over land shows an increased Bowen ratio and decreases in the evaporative fraction. The enhanced sensible heat flux responsible for these results causes an energy surplus inside the PBL, resulting in increased convective activity and corresponding TKEZ. These results are consistent with temperature increases obtained by several other model simulations, and also indicate that changes in the turbulent transport from the PBL to the free troposphere

Simulation of medicanes over the Mediterranean Sea in a regional climate model ensemble: impact of ocean–atmosphere coupling and increased resolution

Abstract Medicanes are cyclones over the Mediterranean Sea having a tropical-like structure but a rather small size, that can produce significant damage due to the combination of intense winds and heavy precipitation. Future climate projections, performed generally with individual atmospheric climate models, indicate that the intensity of the medicanes could increase under climate change conditions. The availability of large ensembles of high resolution and ocean–atmosphere coupled regional climate model (RCM) simulations, performed in MedCORDEX and EURO-CORDEX projects, represents an opportunity to improve the assessment of the impact of climate change on medicanes. As a first step towards such an improved assessment, we analyze the ability of the RCMs used in these projects to reproduce the observed characteristics of medicanes, and the impact of increased resolution and air-sea coupling on their simulation. In these storms, air-sea interaction plays a fundamental role in their formation and intensification, a different mechanism from that of extra-tropical cyclones, where the baroclinic instability mechanism prevails. An observational database, based on satellite images combined with high resolution simulations (Miglietta et al. in Geophys Res Lett 40:2400–2405, 2013), is used as a reference for evaluating the simulations. In general, the simulated medicanes do not coincide on a case-by-case basis with the observed medicanes. However, observed medicanes with a high intensity and relatively long duration of tropical characteristics are better replicated in simulations. The observed spatial distribution of medicanes is generally well simulated, while the monthly distribution reveals the difficulty of simulating the medicanes that first appear in September after the summer minimum in occurrence. Increasing the horizontal resolution has a systematic and generally positive impact on the frequency of simulated medicanes, while the general underestimation of their intensity is not corrected in most cases. The capacity of a few models to better simulate the medicane intensity suggests that the model formulation is more important than reducing the grid spacing alone. A negative intensity feedback is frequently the result of air-sea interaction for tropical cyclones in other basins. The introduction of air-sea coupling in the present simulations has an overall limited impact on medicane frequency and intensity, but it produces an interesting seasonal shift of the simulated medicanes from autumn to winter. This fact, together with the analysis of two contrasting particular cases, indicates that the negative feedback could be limited or even absent in certain situations. We suggest that the effects of air-sea interaction on medicanes may depend on the oceanic mixed layer depth, thus increasing the applicability of ocean–atmosphere coupled RCMs for climate change analysis of this kind of cyclones.