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Atmospheric flow of cold air over mountain barriers in the Alpine region often gives a rise to strong and gusty downslope wind, Bora. Such flows are often accompanied by atmospheric waves, generated by the flow passing an elevated barrier. Such phenomenon can only rarely be observed visually and can generally not be reliably reproduced by simplified numerical models. Orography‐induced atmospheric small‐scale waves were experimentally observed on 25 January 2019 during a Bora outbreak in the Vipava valley, Slovenia. A vertical scanning lidar, positioned at the lee side of the Trnovski gozd mountain and a fixed direction lidar, 5 km apart in the Vipava valley, were used to characterize the density field. The flow exhibited a stationary jump after the mountain ridge and, superimposed, an oscillatory flow pattern. High‐resolution numerical simulations complemented the observations and supported experimental results on the flow periodicity but also on the wave structures and propagation characteristics. Plain Language Summary Airflow passing over mountainous barriers often leads to the generation of atmospheric small‐scale waves. These waves play an important role in redistributing momentum and energy, impacting atmospheric dynamics on both local and regional scales. Studying mountain regions as sources of these waves has been challenging due to the highly nonlinear interactions between the airflow and often complex terrain orography, compounded by a lack of meter‐scale high‐resolution observations and efficient models. This study investigates the atmospheric waves appearing above Vipava valley, Slovenia, during a strong and gusty downslope wind event known as Bora. Using high‐resolution remote sensing observations and numerical simulations, we characterized the properties of these waves. Coordinated high‐resolution measurements of atmospheric flow were obtained using two lidar systems—one positioned at the mountain site and the other within the valley. Two‐dimensional lidar scans revealed a downslope Bora flow layer and its sudden rise after the mountain ridge, which may indicate an hydraulic jump and is associated with small‐scale waves observed further down the valley. High‐resolution numerical simulations of the atmospheric flow over the actual terrain complemented and supported the observations of atmospheric structures above the valley. Key Points Vertical and horizontal lidar measurements in and above the Vipava valley show orography‐induced atmospheric waves The horizontal propagation of such atmospheric waves is with constant speed and their wavelength is estimated High‐resolution numerical simulations of the flow over the valley support lidar measurement results on flow periodicity

Applications of weather radar data to complex orography are manifold, as are the problems. The difficulties start with the choice of suitable locations for the radar sites and their construction, which often involves long transport routes and harsh weather conditions. The next challenge is the 24/7 operation and maintenance of the remote, unmanned mountain stations, with high demands on the availability and stability of the hardware. The data processing and product generation also require solutions that have been specifically designed and optimised in a mountainous region. The reflection and shielding of the beam by the mountains, in particular, pose great challenges. This review article discusses the main problems and sources of error and presents solutions for the application of weather radar technology in complex orography. The review is focused on operational radars and practical applications, such as nowcasting and the automatic warning of thunderstorms, heavy rainfall, hail, flash floods and debris flows. The presented material is based, to a great extent, on experience collected by the authors in the Swiss Alps. The results show that, in spite of the major difficulties that emerge in mountainous regions, weather radar data have an important value for many practical quantitative applications.

Impacts of the main South American orographic structures (the Andes, the Brazilian Plateau and the Guiana shield) on the regional climate and associated global teleconnection are investigated through numerical experiments in which some of these features are suppressed. Simulations are performed with a ‘‘two-way nesting’’ system coupling interactively the regional and global versions of the LMDZ4 atmospheric general circulation model. At regional scale, the simulations confirm previous studies, showing that both the Andes and the Brazilian Plateau exert a control on the position and strength of the South Atlantic convergence zone (SACZ), mainly through their impact on the low-level jet and the coastal branch of the subtropical anticyclones. The northern topography of South America appears to be crucial to determine the leading mode of rainfall variability in eastern South America, which manifests itself as a dipole-like pattern between Southeastern South America and the SACZ region. The suppression of South America orography also shows global-scale effects, corresponding to an adjustment of the global circulation system. Changes in atmospheric circulation and precipitation are found in remote areas on the globe, being the consequences of various teleconnection mechanisms. When the Brazilian Plateau and the Andes are suppressed, there is a decrease of precipitation in the SACZ region, associated with a weakening of the large-scale ascendance. Changes are described in terms of anomalies in the Walker circulation, meridional displacements of the mid-latitude jet stream, Southern annular mode anomalies and modifications of Rossby wave train teleconnection processes.

The representation of orographic drag remains a major source of uncertainty for numerical weather prediction (NWP) and climate models. Its accuracy depends on contributions from both the model grid‐scale orography and the subgrid‐scale orography (SSO). Different models use different source orography data sets and different methodologies to derive these orography fields. This study presents the first comparison of orography fields across several operational global NWP models. It also investigates the sensitivity of an orographic drag parameterization to the intermodel spread in SSO fields and the resulting implications for representing the Northern Hemisphere winter circulation in a NWP model. The intermodel spread in both the grid‐scale orography and the SSO fields is found to be considerable. This is due to differences in the underlying source data set employed and in the manner in which this data set is processed (in particular how it is smoothed and interpolated) to generate the model fields. The sensitivity of parameterized orographic drag to the intermodel variability in SSO fields is shown to be considerable and dominated by the influence of two SSO fields: the standard deviation and the mean gradient of the SSO. NWP model sensitivity experiments demonstrate that the intermodel spread in these fields is of first‐order importance to the intermodel spread in parameterized surface stress, and to current known systematic model biases. The revealed importance of the SSO fields supports careful reconsideration of how these fields are generated, guiding future development of orographic drag parameterizations and reevaluation of the resolved impacts of orography on the flow. Plain Language Summary Mountains play a governing role in global atmospheric circulation via the aerodynamic drag they exert on the atmosphere. At smaller scales they influence winds and weather, for example, instigating damaging downslope windstorms in their lee; generating winds which power onshore wind farms; and causing clear‐air turbulence, which affects commercial aviation. Consequently, it is important that mountains (or “orography”) and their effects are represented accurately in global weather and climate models. While broad mountains are well resolved by these models, smaller mountains and steep slopes are poorly resolved or unresolved. To approximate the drag exerted on the atmosphere by this “subgrid‐scale” orography (SSO), “missing” hills or mountains are assumed in each grid box, whose height, steepness, and shape are defined by data fields derived from the SSO. In this study, it is found that both model grid‐scale orography and SSO fields vary significantly across currently operational models. These differences have a profound effect on the resultant drag, and consequently on the atmospheric circulation. The implication of these results is that changes in how orography is represented in our models have the capacity to bring significant improvements in our ability to model atmospheric circulations across a range of spatial and temporal scales. Key Point Differences in orography data fields are a principal cause of variation in atmospheric drag and circulation among weather and climate models

A recently launched project under the auspices of the World Climate Research Program’s (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both “weather-like” (WL, initialized just before the event in question) and “climate” (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes.

In July 2015, the New Horizons spacecraft flew through the Pluto system at high speed, humanity's first close look at this enigmatic system on the outskirts of our solar system. In a series of papers, the New Horizons team present their analysis of the encounter data downloaded so far: Moore et al. present the complex surface features and geology of Pluto and its large moon Charon, including evidence of tectonics, glacial flow, and possible cryovolcanoes. Grundy et al. analyzed the colors and chemical compositions of their surfaces, with ices of H 2 O, CH 4 , CO, N 2 , and NH 3 and a reddish material which may be tholins. Gladstone et al. investigated the atmosphere of Pluto, which is colder and more compact than expected and hosts numerous extensive layers of haze. Weaver et al. examined the small moons Styx, Nix, Kerberos, and Hydra, which are irregularly shaped, fast-rotating, and have bright surfaces. Bagenal et al. report how Pluto modifies its space environment, including interactions with the solar wind and a lack of dust in the system. Together, these findings massively increase our understanding of the bodies in the outer solar system. They will underpin the analysis of New Horizons data, which will continue for years to come. Science , this issue pp. 1284 , 10.1126/science.aad9189 , 10.1126/science.aad8866 , 10.1126/science.aae0030 , & 10.1126/science.aad9045 Pluto’s atmosphere is cold, rarefied, and made mostly of nitrogen and methane, with layers of haze. Observations made during the New Horizons flyby provide a detailed snapshot of the current state of Pluto’s atmosphere. Whereas the lower atmosphere (at altitudes of less than 200 kilometers) is consistent with ground-based stellar occultations, the upper atmosphere is much colder and more compact than indicated by pre-encounter models. Molecular nitrogen (N 2 ) dominates the atmosphere (at altitudes of less than 1800 kilometers or so), whereas methane (CH 4 ), acetylene (C 2 H 2 ), ethylene (C 2 H 4 ), and ethane (C 2 H 6 ) are abundant minor species and likely feed the production of an extensive haze that encompasses Pluto. The cold upper atmosphere shuts off the anticipated enhanced-Jeans, hydrodynamic-like escape of Pluto’s atmosphere to space. It is unclear whether the current state of Pluto’s atmosphere is representative of its average state—over seasonal or geologic time scales.

The spatio-temporal characteristic of rainfall in the Beles Basin of Ethiopia is poorly understood, mainly due to lack of data. With recent advances in remote sensing, satellite derived rainfall products have become alternative sources of rainfall data for such poorly gauged areas. The objectives of this study were: (i) to evaluate a multi-source rainfall product (Climate Hazards Group Infrared Precipitation with Stations: CHIRPS) for the Beles Basin using gauge measurements and (ii) to assess the spatial and temporal variability of rainfall across the basin using validated CHIRPS data for the period 1981–2017. Categorical and continuous validation statistics were used to evaluate the performance, and time-space variability of rainfall was analyzed using GIS operations and statistical methods. Results showed a slight overestimation of rainfall occurrence by CHIRPS for the lowland region and underestimation for the highland region. CHIRPS underestimated the proportion of light daily rainfall events and overestimated the proportion of high intensity daily rainfall events. CHIRPS rainfall amount estimates were better in highland regions than in lowland regions, and became more accurate as the duration of the integration time increases from days to months. The annual spatio-temporal analysis result using CHIRPS revealed: a mean annual rainfall of the basin is 1490 mm (1050–2090 mm), a 50 mm increase of mean annual rainfall per 100 m elevation rise, periodical and persistent drought occurrence every 8 to 10 years, a significant increasing trend of rainfall (~5 mm year−1), high rainfall variability observed at the lowland and drier parts of the basin and high coefficient of variation of monthly rainfall in March and April (revealing occurrence of bimodal rainfall characteristics). This study shows that the performance of CHIRPS product can vary spatially within a small basin level, and CHIRPS can help for better decision making in poorly gauged areas by giving an option to understand the space-time variability of rainfall characteristics.

We introduce a set of global high-resolution (0.05°) precipitation (P) climatologies corrected for bias using streamflow (Q) observations from 9372 stations worldwide. For each station, we inferred the “true” long-term P using a Budyko curve, which is an empirical equation relating long-term P, Q, and potential evaporation. We subsequently calculated long-term bias correction factors for three state-of-the-art P climatologies [the “WorldClim version 2” database (WorldClim V2); Climatologies at High Resolution for the Earth’s Land Surface Areas, version 1.2 (CHELSA V1.2 ); and Climate Hazards Group Precipitation Climatology, version 1 (CHPclim V1)], after which we used random-forest regression to produce global gap-free bias correction maps for the P climatologies. Monthly climatological bias correction factors were calculated by disaggregating the long-term bias correction factors on the basis of gauge catch efficiencies. We found that all three climatologies systematically underestimate P over parts of all major mountain ranges globally, despite the explicit consideration of orography in the production of each climatology. In addition, all climatologies underestimate P at latitudes >60°N, likely because of gauge undercatch. Exceptionally high long-term correction factors (>1.5) were obtained for all three P climatologies in Alaska, High Mountain Asia, and Chile—regions characterized by marked elevation gradients, sparse gauge networks, and significant snowfall. Using the bias-corrected WorldClim V2, we demonstrated that other widely used P datasets (GPCC V2015, GPCP V2.3, and MERRA-2) severely underestimate P over Chile, the Himalayas, and along the Pacific coast of North America. Mean P for the global land surface based on the bias-corrected WorldClim V2 is 862 mm yr−1 (a 9.4% increase over the original WorldClim V2). The annual and monthly bias-corrected P climatologies have been released as the Precipitation Bias Correction (PBCOR) dataset, which is available online (http://www.gloh2o.org/pbcor/).

Whirlwinds were photographically captured in Stok, Choglamsar, and Nubra valleys in Ladakh, India, in June 2018. It is estimated that the spatial extent of these whirlwinds was 50 m2, vertical extent 0.5–1 km, and lasted for 15 min. To assess the meteorological setup that could have contributed to the occurrence of the whirlwinds, Advanced Research Weather Research and Forecasting (ARW) model (v4.3) was run in a three nested domain setup with 3 km, 1 km, and 333 m resolution. The model could simulate the whirlwinds at finer grid spacing ( 333 m). The whirlwinds are formed in a strongly sheared environment of 22 m s−1, and the storm‐relative shear direction is 80°. These events appear to be initiated as feedback of localized heterogeneity in a convective setting with increased winds and directional change with height. The surface wind convergence due to the temperature gradient at the surface also contributes to whirlwind initiation. The temperature gradient aligns with recently developed landscape heterogeneity and could be due to increasing urbanization. This study reports on the first evidence of whirlwinds in the Himalayan region and demonstrates the ability of the ARW model in representing/simulating whirlwinds in the complex orography of the Himalayan region. First‐ever visual evidence of whirlwinds in the Himalayan Ladakh region is presented. Whirlwinds were photographically captured in Stok, Choglamsar, and Nubra valleys in Ladakh, India, in June 2018. It is estimated that the spatial extent of these whirlwinds was 50 m2, vertical extent 0.5–1 km, and lasted for 15 min. Local communities were concerned about the occurrence of such hitherto never witnessed whirlwinds in recent years and are reported as for the first time. To assess the meteorological setup that could have contributed to the occurrence of the whirlwinds, the Advanced Research Weather Research and Forecasting (ARW) model was run. The model could simulate the whirlwinds at finer grid spacing ( 333 m). These events appear to be initiated as feedback of localized heterogeneity in a convective setting with increased winds and directional change with height. The surface wind convergence due to the temperature gradient at the surface also contributes to whirlwind initiation. Interestingly, the temperature gradient aligns with recently developed landscape heterogeneity due to increasing urbanization.

We investigate the effect of using convection-permitting models (CPMs) spanning a pan-European domain on the representation of precipitation distribution at a climatic scale. In particular we compare two 2.2 km models with two 12 km models run by ETH Zürich (ETH-12 km and ETH-2.2 km) and the Met-Office (UKMO-12 km and UKMO-2.2 km). The two CPMs yield qualitatively similar differences to the precipitation climatology compared to the 12 km models, despite using different dynamical cores and different parameterization packages. A quantitative analysis confirms that the CPMs give the largest differences compared to 12 km models in the hourly precipitation distribution in regions and seasons where convection is a key process: in summer across the whole of Europe and in autumn over the Mediterranean Sea and coasts. Mean precipitation is increased over high orography, with an increased amplitude of the diurnal cycle. We highlight that both CPMs show an increased number of moderate to intense short-lasting events and a decreased number of longer-lasting low-intensity events everywhere, correcting (and often over-correcting) biases in the 12 km models. The overall hourly distribution and the intensity of the most intense events is improved in Switzerland and to a lesser extent in the UK but deteriorates in Germany. The timing of the peak in the diurnal cycle of precipitation is improved. At the daily time-scale, differences in the precipitation distribution are less clear but the greater Alpine region stands out with the largest differences. Also, Mediterranean autumnal intense events are better represented at the daily time-scale in both 2.2 km models, due to improved representation of mesoscale processes.