Search

Predictive skills of coupled sea-ice/ocean and atmosphere models are limited by the chaotic nature of the atmosphere. Assimilation of observational information on ocean hydrography and sea ice allows to obtain a coupled-system state that provides a basis for subseasonal-to-seasonal ocean and sea-ice forecast (Mu et al., 2022). However, if the atmosphere is not additionally constrained, the quasi-random atmospheric states within an ensemble forecast lead to a fast divergence of the ocean and sea-ice states, degrading the system’s performance with respect to the sea ice forecasts. As reported previously, imposing an additional constraint by nudging large-scale winds to the ERA5 reanalysis data (Sánchez-Benítez et al., 2021; Athanase et al., 2022) improves predictive skills of the AWI Coupled Prediction System (AWI-CPS, Mu et al. 2022) with regard to sea ice drift (Losa et al., 2023). Here we provide results based on a much more extensive set of ensemble-based data assimilation experiments spanning the time period from 2002 to 2023 and a series of long forecast experiments over 2010 – 2023, initialized in four different seasons. We compare the performance of forecasts initialized from two sets of data assimilation experiments, with and without atmospheric wind nudging. The additional relaxation of the large-scale atmospheric circulation to the ERA5 reanalysis data for the initialization leads to reasonable atmospheric forecast skill on weather timescales: Despite the simple technique, the coarse resolution compared to NWP systems, and the limited optimization efforts, 10-day forecasts of the 500 hPa geopotential height are about as skillful as the best performing NWP forecasts were about 10 –15 years ago. Among other aspects, this leads to significantly improved subseasonal-to-seasonal sea-ice concentration and thickness forecasts. Athanase, M., Schwager, M., Streffing, J., Andrés-Martínez, M., Loza, S., and Goessling, H.: Impact of the atmospheric circulation on the A

Comparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snowpack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation.

The global mean temperature has increased by ~1ºC since the preindustrial period (Allen et al., 2018). Global warming is spatially and temporally inhomogeneous, with larger increases for land and specific regions (so-called hot-spots) and seasons, such as the summer warming in the Mediterranean (García-Herrera and Barriopedro, 2018). The increasing trend of mean temperatures has been accompanied by changes in the tails of the distribution, including an increase in the frequency/duration and intensity of heat waves (Acero et al., 2018; Chapman et al., 2019) , as well as the occurrence of new emerging events, also called mega-heat waves. These extreme events, cause severe impacts in socio-economic sectors and population, like extensive crop failures (Fahad et al., 2017), devastating wildfires (Parente et al., 2018), poor air quality (Ordóñez et al., 2010; Rasilla et al., 2019), increased mortality (Kovats and Hajat, 2008), and peaks in energy demand (Newsham and Bowker, 2010)..., La temperatura media global ha aumentado ~1ºC desde la época preindustrial (Allen et al., 2018). Este calentamiento es desigual en el espacio y en el tiempo, con un mayor aumento sobre tierra y en determinadas regiones (llamadas “puntos calientes”) y estaciones de año, como en el Mediterráneo en verano (García-Herrera and Barriopedro, 2018). El aumento de la temperatura media ha venido acompañado por cambios en las colas de la distribución, provocando un incremento en la frecuencia, duración e intensidad de las olas de calor (Acero et al., 2018; Chapman et al., 2019), así como en la ocurrencia de nuevos eventos conocidos como mega-olas de calor. Éstas conllevan grandes impactos socio-económicos como pérdidas de cosechas (Fahad et al., 2017), incendios forestales (Parente et al., 2018), baja calidad del aire (Ordóñez et al., 2010; Rasilla et al., 2019), aumentos en mortalidad (Kovats and Hajat, 2008) o picos en la demanda eléctrica (Newsham and Bowker, 2010)...

This paper examines the characteristics of the heatwave that affected western and central Europe in June 2017. Using a novel algorithm, we show that its extension, intensity, and persistence were comparable to those of other European mega‐heatwaves, but it occurred earlier in the summer. The most affected area was Iberia, which experienced devastating forest fires with human casualties and the warmest temperatures of the reanalysis period from daily to seasonal scales. The peak of the mega‐heatwave displayed an unprecedented warm air intrusion due to a record‐breaking subtropical ridge with signatures closer to those of July and August. The atmospheric circulation was the main triggering factor of the event. However, thermodynamical changes of the last decades made a substantial contribution to the event, by increasing the likelihood of surpassing high‐temperature thresholds. This episode could be a good example of a coming future, with high‐summer mega‐heatwaves occurring earlier.

© 2019 The Authors. We acknowledge the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing the ERA-Interim reanalysis data. NCEP/NCAR reanalysis data are provided by the Earth System Research Laboratory (ESRL) Physical Sciences Division, Boulder, Colorado (www.esrl.noaa.gov/psd). This work was supported by the Ministerio de Economía y Competitividad through the PALEOSTRAT (CGL2015-69699-R) project. A. Sánchez-Benítez was funded by grant FPU15/03958 from the Ministerio de Educación, Cultura y Deporte (MECD). The authors would like to thank J.M. Garrido-Pérez for his useful comments., This paper presents a new heatwave (HW) detection algorithm that identifies spatially coherent HW patterns on synoptic scales and their temporal evolution, yielding the main characteristics (extension, intensity or persistence) of HW events (HWEs). The algorithm has been applied to temperature data from the ERA-Interim reanalysis in order to derive a catalogue of Iberian HWEs for the extended summers (June to September) of the 1979–2017 period. The results indicate mean frequencies of five Iberian HWEs and 16 summer days with HW conditions over Iberia (Iberian HWDs), with significant positive trends in both diagnostics. The analysis of the life-cycle reveals that more than half of the HWEs correspond to events that originated within the region. Although Iberian HWEs last more than one week on average, they tend to be transient, persisting for about three days in the region (Iberian phase), where they reach maximum intensity and extension, and evolving later to other areas. In order to identify recurrent patterns of occurrence, a clustering of Iberian HWEs was performed based on their mean temperature fields. Four clusters were obtained: Atlantic, Subtropical, European and Mediterranean events, which display distinctive characteristics and spatio-temporal evolution, causing HW conditions in western, southern, northern and eastern Iberia, respectively. Interestingly, Mediterranean events largely explain the overall trends in Iberian HWEs and HWDs. The connection between Iberian HWEs and atmospheric circulation patterns as summarized in four Weather Regimes (WRs) was also investigated. During the Iberian phase, HWEs are preferentially associated with ridge conditions in western Europe, with small variations in this WR determining different regional HWEs. However, the four types of regional Iberian HWEs tend to occur under different WRs during their pre- and post-Iberian phases, and show different relationships with WRs on seasonal scales. Using an impact-oriented metri, Ministerio de Economía y Competitividad (MINECO), Ministerio de Educación, Cultura y Deportes (MECD), Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

The Canary Islands are characterized by their low availability of water resources and different studies have suggested a decrease of precipitation in the second half of the 20th century. Here, we have used the most complete precipitation data set available in the islands to create a dense high quality and homogeneous database, which was used to determine the spatio‐temporal precipitation patterns in the archipelago and the influence of oceanic and atmospheric teleconnections. We have produced a robust regionalization of the Canary Islands precipitation, with three patterns that characterizing the south of the most montainous islands and El Hierro and La Gomera, the north of the most montainous islands and the easternmost arid islands (Lanzarote and Fuerteventura), respectively. All of them show high interannual variability, with no significant trends, except in a few cases. We highlight the strong influence of weather types and teleconections, modulated by the orography, with the highest influence recorded in the first pattern. It must be stressed that the oceanic teleconnections (in special with the tropical North Atlantic surface temperature) are more important than the North Atlantic Oscillation to explain interannual variability of precipitation.