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Many studies have focused on understanding the drivers of soil moisture droughts in Europe when the events have already intensified. Still, how atmospheric circulation changes throughout the entire life cycle of droughts, particularly during the transition periods to drought initiation and termination, has not been thoroughly investigated. Therefore, this study investigates temporal characteristics and atmospheric circulation associated with onsets (a transition period from a normal condition to drought) and terminations (a transition period from drought to a normal condition) of soil moisture droughts in Europe during 1980–2020. The typical duration, preferred seasons of occurrence, and atmospheric circulation during onsets and terminations are examined. The regions of study are central (CEU) and Mediterranean (MED) Europe, and soil moisture from ERA5-Land, GLEAM version 3, SoMo.ml, Noah-LSM, and a simulation from the Community Land Model version 5 (CLM-TRENDY) are utilized. Our findings indicate that the duration of onsets and terminations depends on the dataset: the five soil moisture datasets exhibit different mean duration of onsets and terminations, with ERA5-Land showing shorter and GLEAM longer duration across Europe. Nevertheless, within the same dataset, onsets and terminations exhibit similar durations, implying that onsets and terminations can occur at the same speed. Regarding the preferred seasons for onsets and terminations, onsets occur more during the wet seasons, specifically summer in CEU and autumn and winter in MED. Nevertheless, the frequencies of occurrence during these seasons only slightly exceed that during other seasons. Terminations tend to occur more during the driest seasons. For atmospheric circulation, onsets come with large-scale anticyclonic atmospheric circulation patterns. Terminations do not exhibit a dominant mean circulation pattern over the region where terminations occur but instead show geopotential height anomalies with reduced magnitudes in Europe and a high-pressure system over the North Atlantic. The anticyclonic circulation during onsets is anomalously persistent and shows linkages with the North Atlantic Oscillation (NAO). Positive NAO occurs much more frequently during onsets compared to other drought phases. This finding implies an important role for this large-scale mode of variability in initiating dry periods by reducing soil moisture and its potential to serve as an early warning for droughts during the period prior to the events. [ABSTRACT FROM AUTHOR]

The Mediterranean region is expected to experience significant changes in hydroclimate, reflected in increases in the duration and severity of soil moisture droughts. While numerous studies have explored Mediterranean droughts in coupled climate models under present and future scenarios, understanding droughts in past-climate simulations remains relatively underexplored. Such simulations can offer insights into long-term drought variability that observational records cannot capture. Therefore, our study investigates circulation patterns in the Euro-Atlantic domain associated with multi-year soil moisture droughts over the Mediterranean region during the last millennium (850–2005 CE) in climate simulations. For this, we use the fifth phase of the Climate Model Intercomparison Project–Paleoclimate Model Intercomparison Project Phase 3 (CMIP5–PMIP3) and the CESM Last Millennium Ensemble Project. Primarily, we examine the differences among the models in representing drought variability and related circulation patterns. For the analysis, we exclude the anthropogenic trends from 1850–2005 CE, and to detect the circulation patterns, we perform k -means clustering combined with linear correlation analyses. The findings confirm that Mediterranean drought occurrence during the last millennium is associated with internal variability in the climate system. Drought variability, the associated circulation patterns, and the frequencies of these patterns vary across the models. Some climate models exhibit a multidecadal anti-phase occurrence of some drought periods between the western and eastern Mediterranean regions, although the exact periods of coherence differ among the models. This anti-phase co-variability, which agrees with some proxy records, can be explained by the dominant circulation patterns in each region detected by the models: western Mediterranean droughts are dominated by a high-pressure system over central Europe and a North Atlantic Oscillation (NAO)-like pattern, while eastern Mediterranean droughts are linked to positive pressure anomalies in the southern and eastern Mediterranean and negative NAO, East Atlantic, and East Atlantic–western Russia-like patterns. The frequencies of these modes of climate variability are strongly model-dependent; i.e., some patterns occur more frequently or only in some models, suggesting that the main drivers of droughts differ among the models. Although it is complicated to evaluate the representation of droughts and associated circulation among the models, in general, the models with lower horizontal and vertical spatial land resolutions exhibit drought variability and patterns that distinctly differ from other models. These model differences and preferences toward some circulation patterns can be a source of uncertainties in the model–proxy comparison of Mediterranean droughts and potentially influence future climate projections. [ABSTRACT FROM AUTHOR]

Knowing that internal climate variability is the principal driver of Mediterranean droughts during the last millennium, in this study, we investigate circulation patterns in the Euro-Atlantic domain associated with multi-year droughts over the Mediterranean region in CMIP5-PMIP3 and CESM-LME simulations. The focus is on the natural variability of droughts during 850-2005, thus excluding the anthropogenic trends from 1850 CE onward. The results re-confirm that Mediterranean drought occurrence during the last millennium is associated with internal variability. In terms of the temporal variability, all climate models exhibit a multi-decadal anti-phase occurrence of droughts between the western and eastern Mediterranean agreeing with some proxy records. This anti-phase occurrence of droughts can be explained by the dominant circulation patterns in each region: western Mediterranean droughts are dominated by a high-pressure system and ridge over central Europe and an NAO-like pattern, while eastern Mediterranean droughts are linked to positive pressure anomalies in the southern and eastern Mediterranean, negative NAO, negative EA and EA-WR-like patterns. However, these modes of climate variability are strongly model-dependent, i.e. each model has its preferred circulation patterns that occur more frequently during droughts, suggesting that the main drivers of droughts differ between the models. The models' preference is therefore a potential source of uncertainties in Mediterranean droughts in model-proxy comparison and may have implications for future climate projections. [ABSTRACT FROM AUTHOR]

Knowing that internal climate variability is the principal driver of Mediterranean droughts during the last millennium, in this study, we investigate circulation patterns in the Euro-Atlantic domain associated with multi-year droughts over the Mediterranean region in CMIP5-PMIP3 and CESM-LME simulations. The focus is on the natural variability of droughts during 850–2005, thus excluding the anthropogenic trends from 1850 CE onward. The results re-confirm that Mediterranean drought occurrence during the last millennium is associated with internal variability. In terms of the temporal variability, all climate models exhibit a multi-decadal anti-phase occurrence of droughts between the western and eastern Mediterranean agreeing with some proxy records. This anti-phase occurrence of droughts can be explained by the dominant circulation patterns in each region: western Mediterranean droughts are dominated by a high-pressure system and ridge over central Europe and an NAO-like pattern, while eastern Mediterranean droughts are linked to positive pressure anomalies in the southern and eastern Mediterranean, negative NAO, negative EA and EA-WR-like patterns. However, these modes of climate variability are strongly model-dependent, i.e. each model has its preferred circulation patterns that occur more frequently during droughts, suggesting that the main drivers of droughts differ between the models. The models' preference is therefore a potential source of uncertainties in Mediterranean droughts in model-proxy comparison and may have implications for future climate projections. [ABSTRACT FROM AUTHOR]

In this study, we hypothesized that shifts in the kinetic parameters of extracellular hydrolytic enzymes may occur as a consequence of seasonal environmental disturbances and would reflect the level of adaptation of the bacterial community to the organic matter of the ecosystem. We measured the activities of enzymes that play a key role in the bacterial growth (leucine aminopeptidase, β‐ and α‐glucosidases) in surface coastal waters of the Eastern Cantabrian Sea and determined their kinetic parameters by computing kinetic models of distinct complexity. Our results revealed the existence of two clearly distinct enzymatic systems operating at different substrate concentrations: a high‐affinity system prevailing at low substrate concentrations and a low‐affinity system characteristic of high substrate concentrations. These findings could be the result of distinct functional bacterial assemblages growing concurrently under sharp gradients of high‐molecular‐weight compounds. We constructed an ecological network based on contemporaneous and time‐delayed correlations to explore the associations between the kinetic parameters and the environmental variables. The analysis revealed that the recurring phytoplankton blooms registered throughout the seasonal cycle trigger the wax and wane of those members of the bacterial community able to synthesize and secrete specific enzymes. [ABSTRACT FROM AUTHOR]

The performance of the Weather Research and Forecasting (WRF) model version 3.8.1 at convection-permitting scale is evaluated by means of several sensitivity simulations over southern Peru down to a grid resolution of 1 km, whereby the main focus is on the domain with 5 km horizontal resolution. Different configurations of microphysics, cumulus, longwave radiation, and planetary boundary layer schemes are tested. For the year 2008, the simulated precipitation amounts and patterns are compared to gridded observational data sets and weather station data gathered from Peru, Bolivia, and Brazil. The temporal correlation of simulated monthly accumulated precipitation against in situ and gridded observational data show that the most challenging regions for WRF are the slopes along both sides of the Andes, i.e. elevations between 1000 and 3000 m above sea level. The pattern correlation analysis between simulated precipitation and station data suggests that all tested WRF setups perform rather poorly along the northeastern slopes of the Andes during the entire year. In the southwestern region of the domain the performance of all setups is better except for the driest period (May–September). The results of the pattern correlation to the gridded observational data sets show that all setups perform reasonably well except along both slopes during the dry season. The precipitation patterns reveal that the typical setup used over Europe is too dry throughout the entire year, and that the experiment with the combination of the single-moment 6-class microphysics scheme and the Grell–Freitas cumulus parameterization in the domains with resolutions larger than 5 km, suitable for East Africa, does not perfectly apply to other equatorial regions such as the Amazon basin in southeastern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell-Freitas cumulus parameterization tends to overestimate precipitation over the northeastern slopes of the Andes, but enforces a positive feedback between the soil moisture, air temperature, relative humidity, mid-level cloud cover and, finally, precipitation. Hence, this setup provides the most accurate results over the Peruvian Amazon, and particularly over the department of Madre de Dios, which is a region of interest because it is considered a biodiversity hotspot of Peru. The robustness of this particular configuration of the model is backed up by similar results obtained during wet climate conditions observed in 2012. [ABSTRACT FROM AUTHOR]

The performance of the Weather Research and Forecasting (WRF) model version 3.8.1 at convection-permitting scale is evaluated by means of several sensitivity simulations over southern Peru down to a grid resolution of 1 km, whereby the main focus is on the domain with 5 km horizontal resolution. Different configurations of microphysics, cumulus, longwave radiation and planetary boundary layer schemes are tested. For the year 2008, the simulated precipitation amounts and patterns are compared to gridded observational data sets and weather station data gathered from Peru, Bolivia and Brazil. The temporal correlation of simulated monthly precipitation sums against in-situ and gridded observational data show that the most challenging regions for WRF are the slopes along both sides of the Andes, i.e., elevations between 1000 and 3000 m above sea level. The pattern correlation analysis between simulated precipitation and station data suggests that all tested WRF setups perform rather poorly along the northeastern slopes of the Andes during the entire year. In the southwestern region of the domain the performance of all setups is better except for the driest period (May-September). The results of the pattern correlation to the gridded observational data sets show that all setups perform reasonably well except along both slopes during the dry season. The precipitation patterns reveal that the typical setup used over Europe is too dry throughout the entire year, and that the experiment with the combination of the single-moment 6-class microphysics scheme and the Grell-Freitas cumulus parameterization in the domains with resolutions larger than 5 km, suitable for East Africa, does not perfectly apply to other equatorial regions such as the Amazon basin in southeastern Peru. The experiment with the Stony-Brook University microphysics scheme and the Grell-Freitas cumulus parameterization tends to overestimate precipitation over the northeastern slopes of the Andes, but allows to enforce a positive feedback between the soil moisture, air temperature, relative humidity, mid-level cloud cover and finally, also precipitation. Hence, this setup is the one providing the most accurate results over the Peruvian Amazon, and particularly over the department of Madre de Dios, which is a region of interest because it is considered the biodiversity hotspot of Peru. The robustness of this particular parameterization option is backed up by similar results obtained during wet climate conditions observed in 2012. [ABSTRACT FROM AUTHOR]

The ability of two downscaling experiments to correctly simulate the instability conditions that can trigger thunderstorms over the Iberian Peninsula is compared in this paper. To do so, three instability indices are evaluated: TT index, CAPE and CIN. The WRF model is used for the simulations. The N experiment is driven by ERA-Interim's initial and boundary conditions; The D experiment has the same configuration as N, but the 3DVAR data assimilation step is additionally run at 00, 06, 12 and 18 UTC. Eight radiosondes are available over the IP, and the values for these indices calculated from the University of Wyoming were chosen as reference in the validation of both simulations. Additionally, measured variables at different pressure levels from the radiosondes provided byWyoming were used to calculate the three instability indices by our own methodology using the R package aiRthermo. According to the validation, the correlation, SD and RMSE obtained by the experiment D for all the indices in most of the stations are better than those for N. The different methodologies produce small discrepancies between the values for TT, but these are larger for CAPE and CIN due to the dependency of these indices on the initial conditions assumed for the calculation of an air parcel's vertical evolution. Similar results arise from the seasonal analysis concerning both WRF experiments: N tends to overestimate or underestimate (depending on the index) the variability of the reference values, but D is able to capture it in most of the seasons. The heterogeneity of the indices is highlighted in the mean maps over the Iberian Peninsula. According to those from D, the ingredients for the development of convective precipitation during winter are found along the entire Atlantic coast, but in summer they are located particularly in the Mediterranean coast. The chances of developing thunderstorms in those areas at 12 UTC is much higher than at 00 UTC; The convective inhibition is more extended towards inland at 00 UTC in those areas, which prevents storms from developing. However, high values are observed near Murcia also at 12 UTC. [ABSTRACT FROM AUTHOR]

A new diagram is proposed for the verification of vector quantities generated by multiple models against a set of observations. It has been designed with the idea of extending the Taylor diagram to two dimensional quantities such as currents, wind, or horizontal fluxes of water vapour, salinity, energy and other geophysical variables. The diagram is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations. This matrix is separated in a part corresponding to the bias and the relative rotation of the empirical orthogonal functions of the data. We test the performance of this new diagram to identify the differences amongst the reference dataset and the different model outputs by using examples with wind, current, vertically integrated moisture transport and wave energy flux time series. An alternative setup is shown in the last examples, where the spatial average of surface wind in the Northern and Southern Hemispheres according to different reanalyses and realizations of CMIP5 models are compared. The examples of use of the Sailor diagram presented show that it is a tool which helps in identifying errors due to the bias or the orientation of the simulated vector time series or fields. The R implementation of the diagram presented together with this paper allows also to easily retrieve the individual diagnostics of the different components of the mean squared error. [ABSTRACT FROM AUTHOR]

In this paper, we have estimated the spatiotemporal distribution of moisture recycling over the Iberian Peninsula (IP). The recycling ratio was computed from two simulations over the IP using the Weather Research and Forecasting (WRF) model with a horizontal resolution of 15 km spanning the period 2010–2014. The first simulation (WRF N) was nested inside the ERA-Interim with information passed to the domain through the boundaries. The second run (WRF D) is similar to WRF N, but it also includes 3DVAR data assimilation every six hours (12:00 a.m., 6:00 a.m., 12:00 p.m. and 6:00 p.m. UTC). It was also extended until 2018. The lowest values of moisture recycling (3%) are obtained from November to February, while the highest ones (16%) are observed in spring in both simulations. Moisture recycling is confined to the southeastern corner during winter. During spring and summer, a gradient towards the northeastern corner of the IP is observed in both simulations. The differences between both simulations are associated with the dryness of the soil in the model and are higher during summer and autumn. WRF D presents a lower bias and produces more reliable results because of a better representation of the atmospheric moisture. [ABSTRACT FROM AUTHOR]

The use of the Noah Land Surface Model (LSM) in regional modeling has increased during the last decades, while data assimilation is not so commonly used. Thus, this study focuses on the impact of both options on WRF simulations, and how they affect the summer surface temperature bias and energy balance over the Iberian Peninsula (IP). For that purpose, a numerical downscaling exercise over the IP was run nesting the WRF model inside ERA-Interim. Four different configurations of the model were run during 2010-2014 after a one-year spin-up (2009). In the first experiment (N), including the Noah LSM for the calculation of the soil temperature and moisture, the boundary conditions drive the model after the initialization. The second experiment (D) includes also the LSM, but the 3DVAR data assimilation step is run every six hours (00Z, 06Z, 12Z and 18Z). The third and fourth experiments (S and C respectively) present the same configurations as the previous experiments, but without the Noah LSM. The domain covers the IP with a 15x15 km2 grid and 51 vertical levels. The sea surface temperature is updated daily and observations from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) are assimilated inside a 120-minute window centered at the analysis times in the 3DVAR assimilated runs (C and D). Results show that the experiment including the data assimilation and the Noah LSM (D) produces the best correlations and the smallest RMSE. Both experiments including the Noah LSM (D and N) showed similar biases, but the RMSE obtained by N is not as good as that from D. A larger bias is obtained by the C experiment (with data assimilation but without the LSM), but not as remarkable as that from the experiment without both options (S). However, the correlations obtained by C are comparable to those from D. According to these results, the effect of the Noah LSM in temperature is similar to that derived from the data assimilation scheme for temperature bias. Conversely, for day-to-day variations (correlation coefficient), data assimilation performs much better. Thus, in terms of mean square error, the combination of land surface model and data assimilation yields the optimum combination. The spatial distribution of the Bowen ratio was also calculated for each experiment. Those experiments including the Noah LSM are the ones obtaining the most similar results to those obtained by previous studies, particularly the N experiment. The mean Bowen Ratio value for the experiments without the Noah LSM is around 0.5, while for D is 1.48 and for N 3.78. If we focus on the energy balance, the experiments including Noah LSM are those able to better close the balance (residual below 25 W/m2 – mean value for the entire IP). The residual of the experiments without Noah LSM can reach values of 200 W/m2 because the estimation of Ground Flux is severely affected by the use of a diffusive soil scheme. [ABSTRACT FROM AUTHOR]