Trends and Variability of North American Cool-Season Extratropical Cyclones: 1979–2019

Extratropical cyclones are the primary driver of sensible weather conditions across the mid-latitudes of North America, often generating various types of precipitation, gusty non-convective winds, and severe convective storms throughout portions of the annual cycle. Given ongoing modifications of the zonal atmospheric thermal gradient due to anthropogenic forcing, analyzing the historical characteristics of these systems presents an important research question. Using the North American Regional Reanalysis, boreal cool-season (October–April) extratropical cyclones for the period 1979–2019 were identified, tracked, and classified based on their genesis location. Additionally, bomb cyclones—extratropical cyclones that recorded a latitude normalized pressure fall of 24 hPa in 24-hr—were identified and stratified for additional analysis. Cyclone lifespan across the domain exhibits a log-linear relationship, with 99% of all cyclones tracked lasting less than 8 days. On average, ≈ 270 cyclones were tracked across the analysis domain per year, with an average of ≈ 18 year−1 being classified as bomb cyclones. The average number of cyclones in the analysis domain has decreased in the last 20 years from 290 year−1 during the period 1979–1999 to 250 year−1 during the period 2000–2019. Spatially, decreasing trends in the frequency of cyclone track counts were noted across a majority of the analysis domain, with the most significant decreases found in Canada’s Northwest Territories, Colorado, and east of the Graah mountain range. No significant interannual or spatial trends were noted with bomb cyclone frequency.

Evaluation of wind speed estimates in reanalyses for wind energy applications

A correct spatio-temporal representation of retrospective wind speed estimates is of large interest for the wind energy sector. In this respect, reanalyses provide an invaluable source of information. However, the quality of the various reanalysis estimates for wind speed are difficult to assess. Therefore, this study compares wind measurements at hub heights from 14 locations in Central Europe with two global (ERA5, MERRA-2) and one regional reanalysis (COSMO-REA6). Employing metrics such as bias, RMSE and correlation, we evaluate the performance of the reanalyses with respect to (a) the local surface characteristics (offshore, flat onshore, hilly onshore), (b) various height levels (60 to 200 m) and (c) the diurnal cycle. As expected, we find that the reanalyses show the smallest errors to observations at offshore sites. Over land, MERRA-2 generally overestimates wind speeds, while COSMO-REA6 and ERA5 represent the average wind speed more realistically. At sites with flat terrain, ERA5 correlates better with observations than COSMO-REA6. In contrast, COSMO-REA6 performs slightly better over hilly terrain, which can be explained by the higher horizontal resolution. In terms of diurnal variation, ERA5 outperforms both other reanalyses. While the overestimation of MERRA-2 is consistent throughout the day, COSMO-REA6 significantly underestimates wind speed at night over flat and hilly terrain due to a misrepresentation of nightly low level jets and mountain and valley breezes. Regarding the representation of downtime of wind turbines due to low/high wind speeds, we find that MERRA-2 is consistently underperforming with respect to the other reanalyses. Here COSMO-REA6 performs better over the ocean, while ERA5 shows the best results over land.

BARRA v1.0: kilometre-scale downscaling of an Australian regional atmospheric reanalysis over four midlatitude domains

Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1–4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude.

Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers

The reliability of ERA5 reanalyses for directly predicting wind resources and energy production has been assessed against observations from six tall towers installed over very heterogeneous sites around the world. Scores were acceptable at the FINO3 (Germany) offshore platform for both wind speed (bias within 1%, r = 0.95−0.96) and capacity factor (CF, at worst biased by 6.70%) and at the flat and sea-level site of Cabauw (Netherlands) for both wind speed (bias within 7%, r = 0.93−0.94) and CF (bias within 6.82%). Conversely, due to the ERA5 limited resolution (~31 km), large under-predictions were found at the Boulder (US) and Ghoroghchi (Iran) mountain sites, and large over-predictions were found at the Wallaby Creek (Australia) forested site. Therefore, using ERA5 in place of higher-resolution regional reanalysis products or numerical weather prediction models should be avoided when addressing sites with high variation of topography and, in particular, land use. ERA5 scores at the Humansdorp (South Africa) coastal location were generally acceptable, at least for wind speed (bias of 14%, r = 0.84) if not for CF (biased by 20.84%). However, due to the inherent sea–land discontinuity resulting in large differences in both surface roughness and solar irradiation (and thus stability conditions), a particular caution should be paid when applying ERA5 over coastal locations.

Development of East Asia Regional Reanalysis based on advanced hybrid gain data assimilation method and evaluation with E3DVAR, ERA-5, and ERA-Interim reanalysis

The East Asia Regional Reanalysis (EARR) system is developed based on the advanced hybrid gain data assimilation method (AdvHG) using Weather Research and Forecasting (WRF) model and conventional observations. Based on EARR, the high-resolution regional reanalysis and reforecast fields are produced with 12 km horizontal resolution over East Asia for 2010–2019. The newly proposed AdvHG is based on the hybrid gain approach, weighting two different analysis for an optimal analysis. The AdvHG is different from the hybrid gain in that 1) E3DVAR is used instead of EnKF, 2) 6 h forecast of ERA5 is used to be more consistent with WRF, and 3) the pre-existing, state-of-the-art reanalysis is used. Thus, the AdvHG can be regarded as an efficient approach to generate regional reanalysis dataset due to cost savings as well as the use of the state-of-the-art reanalysis. The upper air variables of EARR are verified with those of ERA5 for January and July 2017 and the two-year period of 2017–2018. For upper air variables, ERA5 outperforms EARR over two years, whereas EARR outperforms (shows comparable performance to) ERA-I and E3DVAR for January in 2017 (July in 2017). EARR better represents precipitation than ERA5 for January and July in 2017. Therefore, though the uncertainties of upper air variables of EARR need to be considered when analyzing them, the precipitation of EARR is more accurate than that of ERA5 for both two seasons. The EARR data presented here can be downloaded from https://doi.org/10.7910/DVN/7P8MZT for data on pressure levels and https://doi.org/10.7910/DVN/Q07VRC for precipitation.

Regional winds over the Iberian Peninsula with COSMO-REA6 high resolution regional reanalysis: cierzo, levante and poniente

<p>Regional winds are caused by small-scale pressure differences in a way that important air flows can arise in a very small and specific region. Sometimes an orographic feature, such as a channel like the Ebro Valley or the Strait of Gibraltar, lead the wind, due to mass conservation, to acquire a certain specific range of directions and considerable speed. In the regions where they are observed, the wind is of great importance not only for the climatology and meteorology of these areas but also for their culture and identity. However, it is difficult to analyze them using the most common reanalysis products, since their spatial resolutions are not high enough to properly describe the orographic characteristics that lead to the regional winds in specific locations. Here, we will explore the application of the COSMO-REA6 high resolution reanalysis system for the assessment of the main regional winds in the Iberian Peninsula: the cierzo wind in the Ebro Valley and the levante and poniente winds in the Strait of Gibraltar, for the 2000-2018 period. COSMO-REA6 uses a spatial resolution of 6 km (0.055º), which is much larger than previous reanalysis and regional modelling databases, so it can better capture the orography of the areas and therefore the regional winds we intend to study. The cierzo, levante and poniente winds are very relevant in the Iberian Peninsula due to their intensity and their frequency. Defined with a 5 m/s threshold for each hour, and their specific direction range, around 95, 150 and 110 wind days per year are obtained, respectively. Their study may also be important for other reasons, such as the production of renewable energy in these areas. First, we conduct a preliminary assessment of wind speed and direction with hourly data from weather stations, which have been obtained from the HadISD global sub-daily dataset. Then, we compare data from stations with COSMO-REA6 reanalysis in each location and produce a spatial description of the reanalysis in the Peninsula. We also study the atmospheric patterns associated with the regional winds characterized above. Due to the few studies that have been carried out on regional winds in the Iberian Peninsula, these results can be of great interest for various fields, such as meteorology, climatology and the generation of renewable energy.</p>

Copernicus European regional reanalysis

<p>The Copernicus European regional reanalysis (https://climate.copernicus.eu/regional-reanalysis-europe) is produced as part of the Copernicus Climate Change Service (C3S). The presentation will introduce the service and its main objectives as well as it will give and overview of available data. Data quality will be demonstrated by comparison with ERA5 and other gridded datasets.</p><p>In the first phase of the service, systems inherited from the FP7 project UERRA (Uncertainties in Ensembles of Regional ReAnalyses, http://www.uerra.eu) were applied extending the UERRA-HARMONIE as well as the MESCAN-SURFEX datasets. These datasets contain analyses of the atmosphere, the surface and the soil. UERRA-HARMONIE is a full model system including a 3D-Var data assimilation scheme for upper air observations and an OI-scheme for surface observations. MESCAN-SURFEX is a complementary 2D surface analysis system interfaced to a land surface model. Data is available for entire Europe at a horizontal resolution of 11 km for UERRA-HARMONIE and at 5.5 km for MESCAN-SURFEX. The systems provide four analyses per day – at 0 UTC, 6 UTC, 12 UTC, and 18 UTC. Between the analyses ranges, forecasts of the systems are available with hourly resolution. More than fifty parameters are available on various level types. Data are available for the period 1961 – July 2019 through Copernicus Climate Data Store (CDS).</p><p>In spring 2020, the service started the production of the next generation regional reanalysis. The successor comprises three components:<br>- CERRA (5.5 km horizontal resolution)<br>- CERRA-EDA (10-member ensemble at 11 km resolution)<br>- CERRA-Land (5.5 km horizontal resolution)</p><p>In addition to the higher resolution, CERRA is more sophisticated than UERRA. For instance, more observations are assimilated into CERRA, in particular remote sensing data. CERRA is produced with 3-hourly cycling and a flow depending part of the B-matrix is derived from CERRA-EDA. The production of CERRA, CERRA-EDA and CERRA-Land will complete in September/October 2021 and data will become available in the CDS shortly thereafter.</p><p>The quality of the regional reanalysis in comparison to ERA5 will be shown with results of the standard HARMONIE-verification package as well as based on certain case studies. For instance, the winter storm Gudrun (January 2005, southern Sweden) will be investigated.</p>

A novel approach to surface reanalysis

<p>Reanalysis is a procedure to merge numerical model integrations and observations to obtain a synergetic representation of the past climatological state of a system, e.g., of the atmosphere. An alternative to running a full reanalysis scheme is a so-called surface reanalysis. Here, an existing reanalysis is used as prior information (for the near-surface state). This first guess is then corrected in a data assimilation step preferrably by applying observations not used in the original assimilation. In such a scheme, an additional downscaling is often performed to enhance the spatial representation of the surface reanalysis.</p><p>We present here the development of a new approach aiming to establish such a data set based on the COSMO-REA6 regional reanalysis of the Hans-Ertel-Centre and Deutscher Wetterdienst (DWD). The data assimilation step is based on the operational Local Ensemble Transform Kalman Filter (LETKF) of DWD. While the data assimilation is often performed univariately in such surface reanalysis schemes, here we apply it to various parameters at once thus conserving the covariances among the parameters and allowing for a consistent multivariate utilization of the data. Further, this reanalysis will not be restricted to the ground level and near-surface parameters. Instead, it will be extended to the lower part of the boundary layer aiming at an improved representation of wind speeds in wind turbine hub heights especially relevant for renewable energy applications. The envisaged resolution is approximately 1km and therefore enables an enhanced representation of spatial variability and heterogeneity on small scales. In addition, the LETKF is an ensemble-based data assimilation scheme which also provides uncertainty estimates through an ensemble of the re-analyzed parameters which can also be used as input for downstream applications.</p>

The new Italian regional reanalysis SPHERA: benefits of the convection-permitting resolution in detecting severe-weather events

<p>In recent years the interest towards the development of limited-area atmospheric reanalysis datasets has been growing more and more. Regional reanalyses in fact, as a consequence of the restricted domain that they cover, provide a data distribution displaced on a much finer grid compared to a coarser global dataset. This permits to better resolve those patterns related to rapid and high-impact weather events, first and foremost convection. Furthermore, with a finer horizontal resolution, a consistent increase in the level of detail in the description of the orography is also gained, that is a crucial point to achieve especially in a very complex territory such as Italy. This study presents the first application of the novel regional reanalysis dataset developed at ARPAE-SIMC: the High rEsolution ReAnalysis over Italy (SPHERA). SPHERA is a high-resolution convection-permitting reanalysis over the Italian domain and the surrounding seas covering 25 years, from 1995 to 2020, at hourly temporal frequency. SPHERA is based on the non-hydrostatic limited-area model COSMO, and produced by a dynamical downscaling of the global reanalysis ERA5, developed at ECMWF. A nudging data assimilation scheme is applied in order to steer the model outcomes towards the surface and upper-air observations. All the available conventional observations have been used.</p><p>The added value of SPHERA in representing severe-weather and convective events is evident from its preliminar validation, which was performed on the multidecadal period against various datasets of surface observations, joined with the comparison against the global reanalysis ERA5. In fact, a clear advantage of SPHERA on its driver ERA5 is found for the detection of events with moderate to intense daily and sub-daily rainfalls, which are characterized by a strong seasonal and geographical component, that is further investigated. We report also the preliminary sensitivity analysis on the dimension of the box used to operate the upscaling for the validation of SPHERA, a process necessary to reduce the errors caused by geographical mismatches between observed and simulated events localizations, which are particularly frequent in case of strongly-localized and rapid processes. Furthermore, in order to give a quantitative evaluation of the performance of the new reanalysis in particular conditions, the results of the simulations for specific case studies involving the occurrence of severe-precipitation events in recent years was performed, focusing on events having different dynamical genesis, but interrelated by the important damages they caused. From this analysis, for which also a comparison with other regional reanalyses is performed, the advantage of SPHERA in representing the most intense rainfall occurrences, in terms of location, intensity and timing, clearly emerges.</p>