bluuebunny/crossref_metadata_2025 huggingface dataset:
Added value of assimilating surface pressure observations from personal weather stations in AROME-France
Authors: Demortier Alan , Caumont Olivier , Pourret Vivien , Mandement Marc
Published: June 2022

The rise of connected objects, such as personal weather stations (PWSs), and the availability of their data, have opened up a new field of possibilities for real-time weather observation. For instance, the Netatmo PWS network measures temperature, relative humidity and pressure near the surface at high spatial density over France with around 50,000 stations. Nevertheless, such stations have measurement errors, e.g. pressure sensor has vertical calibration and drifting issues, thus they need to be processed. The objective here is to assess the relevance of assimilating these pressure observations into an operational kilometre-scale numerical weather prediction system such as AROME-France, which uses a three-dimensional variational (3D-Var) data assimilation scheme. And, despite the rich literature describing efficient correction methods, two specific criteria have to be taken into account in our study. First the data need to be coherent with standard weather station (SWS) observations actually assimilated and secondly the processing method has to respect near-real time limitations.

In a first phase, a pre-existing correction and quality control method was adapted.  The correction is based on the interpolation of the SWS observations at PWS's locations (called reference interpolation) in order to subtract an average temporal bias. Then, a data quality control is applied in order to remove the PWS time series whose values deviate too far from the reference interpolation time series, with a non-stationary threshold. In this way, we ensured the quality of the data and the scale of their representativeness. In a second phase, two experiments assimilating the PWS observations were carried out. In a first experiment, PWS biases with respect to the model's background during a selected time window are corrected before PWS observations are quality controlled by the operational screening. In a second experiment, the pre-processing method previously described is used. A thinning at 1.3 km scale is added in order to reduce the high density in the cities which could deteriorate the analysis.
Those configurations serves as a benchmark to beat, as it is clear that some adjustments must be optimized both on the quantification of the observation error, and on the kind and scale of the thinning.

Results show that, on average over the month of August 2020, the PWSs help to bring closer the analysis to SWSs. In addition, some convective events have been studied, showing the limits of the current assimilation methods and the progress to be made.
IMPROVER overview and updates
Authors: Moseley Stephen , Mylne Ken , Wright Bruce , Jackson Simon , Rust Fiona , Evans Gavin , Ayliffe Ben , Hurst Kat , Spelman Marcus , Fitzpatrick Ben , Sampson Chris
Published: June 2022

IMPROVER (Integrated Model Post-Processing and Verification) has been developed by the Met Office as an open-source probability-based post-processing system to fully exploit our convection permitting, hourly cycling ensemble forecasts. Post-processed MOGREPS-UK model forecasts are blended with deterministic UKV model forecasts and data from the coarser resolution global ensemble, MOGREPS-G, to produce seamless probabilistic forecasts from now out to 7 days ahead. For precipitation, an extrapolation nowcast is also blended in at the start. Forecasts are converted to probabilities at the start, and all initial stages of post-processing are performed on gridded data, with site-specific forecasts extracted as a final step, helping to ensure consistency. Data are processed on a 10km global grid and on a 2km UK-centred grid.

This talk will briefly describe the post-processing sequence from raw NWP model data to fully-blended, gridded and spot forecasts as probabilities and percentiles of a broad range of meteorological diagnostics, with the application of physical and statistical post-processing techniques. The system became operational in early May 2022, and the this talk will focus on some of the work that has been undertaken in the last year to achieve this, including ensemble calibration of temperature and wind speed data at observed and non-observed sites. There will be discussion of some of the verification used to prove this system, as well as a brief look at the technical aspects of this complex system, the initial customers and collaborators and the planned future work, including the use of ECMWF forecast data to extend the range of IMPROVER out to 14 days.
Generating weather symbol data in IMPROVER
Authors: Moseley Stephen , Ayliffe Ben
Published: June 2022

IMPROVER (Integrated Model Post-Processing and Verification) has been developed by the Met Office as an open-source probability-based post-processing system to fully exploit our convection permitting, hourly cycling ensemble forecasts. Post-processed MOGREPS-UK model forecasts are blended with deterministic UKV model forecasts and data from the coarser resolution global ensemble, MOGREPS-G, to produce seamless probabilistic forecasts from now out to 7 days ahead. For precipitation, an extrapolation nowcast is also blended in at the start. Forecasts are converted to probabilities at the start, and all initial stages of post-processing are performed on gridded data, with site-specific forecasts extracted as a final step, helping to ensure consistency. Data are processed on a 10km global grid and on a 2km UK-centred grid. An overview of IMPROVER will be given in a separate talk.

 

Weather symbols provide the general public with a simple, pictorial view of the weather for a time of interest and include sun and cloud conditions, mist and fog, hail and lightning, and three phases of precipitation, both as showers or continuous, and light or heavy. This talk describes how a deterministic most-likely weather type code is generated using a decision tree approach from probabilistic multi model IMPROVER data for 1 hour, 3 hour and day time periods that are consistent with each other. Recent work to make these weather codes representative of a time-window, rather than an instant, will be discussed. We will present some verification, comparing IMPROVER weather symbols and the current operational Met Office symbols with SYNOP present weather reports.
Vortex Merger in Shallow Water Model
Authors: Oh Tae-Jin , Sun Wen-Yih
Published: June 2022

In this presentation, an inviscid, nonlinear shallow water model is applied to study the formation of filaments and merging of potential vorticity (PV). We confirm that misalignment of vorticity with the streamlines is crucial to merger. Flow creates positive PV tendency (PVt) on the lee side of PV ridge, which increases the angle between streamlines and PV contours and the efficiency of vorticity transport along the parallel but oppositive direction in the positive quadrants of PVt . So, the vortices move closer while rotating around each other. Filamentation starts as weak vorticity shatters from the outer edge of vortex core. The filament grows and rotates around the cores, but shows little effects to positive PV advection or vortex merging in the inner core, evidenced by the steady core area integrated PV trends. Consecutive PV transfer from lower to higher interval levels are observed during merger process while elongated filamentation is dissolving into the lower level PV regime. The vortices never merge when negative PVt prevails between two vortices. Distance between the vortex cores show direct correspondence to positive PVt between them. Hence, the advance of positive PVt provides a simple mechanism of merging. The Rossby radius of deformation (LD) is confirmed to be another strong indicator for vortex pair merger where LD smaller than the initial vortex core separation length scale makes merger likely due to geostrophic adjustment. When LD to vortex core separation lengscale ratio was larger than 2, merger did not occur while mixed results showed for ratio between 1 and 2. The Rossby number (Ro) affected the overall flow interaction speed speed when LD is fixed. 
Extremes in European wind and photovoltaic power production in 2050 identifiable by weather patterns
Authors: Ho-Tran Linh , Fiedler Stephanie
Published: June 2022

Wind and photovoltaic (PV) power production vary across time and space. We aim at a first systematic assessment of anomalies in PV and wind power production associated with different synoptic-scale weather patterns with a kilometre-scale resolution for all of Europe. To that end, we have developed the University of Cologne’s Renewable Energy Model (UoC-REM). UoC-REM simulates the hourly PV and wind power production using the reanalysis data set COSMO-REA6 with a horizontal resolution of 6 km. The installed capacities of PV and wind power for 2050 are taken from gridded scenario data. The output of UoC-REM is paired with data from a classification of 29 synoptic weather patterns identified and provided by the German Weather Service. Our results reveal substantial spatio-temporal differences in PV and wind power production depending on the weather pattern. We group the PV and wind power production from individual weather patterns into three groups to facilitate a composite analysis underlining similarities for the PV and wind power production across the weather patterns. These are (1) the group with anomalously high wind power production that almost always produces above average total production, primarily associated with patterns related to westerly winds, (2) the group of moderate PV plus wind power production with weather patterns causing mostly mild anomalies in both PV and wind power, but also ‘dark doldrums’ with simultaneously low wind and PV power production during blocking high pressure systems, e.g., South-Shifted Westerly, and (3) the group with high PV power production paired with below average wind power that is mostly associated with anti-cyclonic weather patterns. We identify that the lowest 10-day production event of PV plus wind power occurs during the pattern Anticyclonic South-Easterly from Group 3, with a reduction by 41% compared to the average hourly total production for Europe. On the contrary, the highest 10-day production event occurs during the pattern Cyclonic North-Westerly from Group 1, with an increase by 18%. Our results suggest that identifying the weather pattern can be used as a quick estimate of the overall production anomaly in PV and wind power production. It would allow to monitor and issue warnings of weather conditions that pose a risk to a future energy system that relies on more weather-dependent renewable sources, without the need to perform operational simulations of the expected power production. Future work will focus on an in-depth analysis of extreme events in renewable power production considering the full spatial and temporal resolution of the new dataset of UoC-REM.
Radiative closure (simulation ↔ measurements) with a complete input/output measurement dataset of supersite Meteorological Observatory Lindenberg (Germany)
Authors: Doppler Lionel , Wacker Stefan , Mäusle Steven Joao , Riedel Janina , Balakrishnan Priji
Published: June 2022

In this paper, we apply the method of radiative closure to the measurement dataset of supersite DWD/MOL-RAO (Deutscher Wetterdienst, Meteorological Observatory Lindenberg – Richard Assmann Observatory) in Lindenberg (Tauche) Germany.

The MOL-RAO observatory is a supersite for measurements of atmospheric parameters and ground-based radiative transfer measurements. We use these measurements as input files to perform high accuracy radiative transfer simulations for cloud-free conditions. Some of the measured atmospheric parameters included in the input files are water vapour, ozone, aerosol optical depth for different wavelengths, single scattering albedo, and atmospheric pressure. For longwave simulations, water vapour and temperature profiles with good precision and estimated vertical positions of aerosol layers are provided as inputs.

We compare the results of the high accuracy simulations with ground-based radiation measurements from the highest WMO quality standards. The comparisons are conducted for every minute for broadband radiation (solar diffuse, direct and global) and every six minutes for spectral measurements (direct and global) in the range 290 - 1000 nm with a spectral resolution of 1nm.

After comparing the high accuracy simulation results with broadband and spectral radiation measurements for the same timestamps, we evaluate and improve both the simulation procedure and the measurement of input parameters (atmospheric composition, aerosol amount and properties). This method is called the 'radiative closure.' In the paper, we also present sensitivity analyses to investigate the influence of the different atmospheric parameters on the radiation, particularly the aerosol properties for the radiation in solar wavelengths, vertical profiles of temperature and water vapour, and aerosol properties for the thermal radiation.
North Atlantic Oscillation as a modifcator of urban climate 
Authors: Herceg-Bulic Ivana , Nimac Irena , Zuvela-Aloise Maja
Published: June 2022

Climate conditions in urban areas considerably differs from the climate of their rural surroundings manifesting as urban heat island (UHI). In addition to impacts of regional factors (such as latitude, topography, distance to large water bodies etc.), the urban climate is largely determined by effects of urbanization (the structure of the city, like height and spacing of buildings, characteristics of constructing materials etc.). However, interaction between urban climate and large-scale climate variability (e.g. heat-waves, North Atlantic Oscillation, El-Niño Southern Oscillation) may amplify UHI and therefore increase the heat stress leading to more unpleasant urban environment for its inhabitants with potential negative economic, health and social consequences. Here, we investigate the role of North Atlantic Oscillation (NAO) in modifying urban heat island of Zagreb, Croatia. Based on analyses of ground measurements and MUKLIMO_3 modelled data, it is demonstrated that both winter (wNAO) and summer (sNAO) NAO affect the summertime urban heat load. The strongest increase in the heat load is found for those summers when positive wNAO is followed by negative sNAO, while the opposite situation leads to the strongest decrease. Situations associated with wNAO and sNAO of the same polarity resulted in much weaker response due to their cancellation effect. Although the NAO is a large-scale phenomenon, its impact is not spatially uniform over the urban domain. Results indicate soil-moisture and related processes as modifying factors. Additional targeted modelling experiments based on standardized precipitation evapotranspiration index (SPEI) uphold the modifying effect of drought conditions on spatial characteristics of urban heat load. Results also imply that efficiency of green infrastructure considerably depends on soil moisture availability indicating the need of their irrigation in dry conditions together with increased water demands for irrigation in future.
The new Irish Soil Moisture Observation Network – ISMON: an Umbrella for Integrating Several Recent Soil Moisture Measurements Initiatives
Authors: Finkele Klara , Hochstrasser Tamara , Murphy Paul N.C. , Daly Eve , Jarmain Caren , Richards Karl , Fenton Owen , Cummins Thomas , Saunders Matthew , Johnston Paul M. , Bruen Michael , Byrne Kenneth A. , Delaney Declan T. , Fealy Rowan , Green Stuart , Higgins Suzanne , Hunter Williams Natalya , Lanigan Gary , McCarthy Tim , McCormack Ted , Mellander Per-Erik , Nicholson Oliver , Nugent Ciaran , O'Loughlin Fiachra , Tobin Brian , Tuohy Pat , Whetton Rebecca
Published: June 2022

Real-time soil moisture measurements are essential to manage for adaptive dynamic management of climate change adaptation and reduction of nutrient losses and greenhouse gas emissions from agriculture and forestry. Soil moisture status influences crop growth, run-off, groundwater recharge, land surface-atmospheric exchange dynamics and greenhouse gas emissions as well as the risk of forest fire danger.  Here we present the new Irish Soil Moisture Observation Network (ISMON) as an umbrella to bring together several recently established long-term environmental observational networks. These are: 1) initiative of the AGMET group (agmet.ie), 2) COSMOS UK – Northern Ireland, 3) Teagasc NASCO (National Agricultural Soil Carbon Observatory) and 4) Terrain-AI, all of which include several different methodologies for measuring soil moisture at field scale. For instance, AGMET is installing novel cosmic ray neutron sensors which can provide field averaged soil moisture estimates (400m diameter) and Teagasc NASCO and Terrain AI are using Time Domain Reflectometry probes. Such networks are seen as necessary to resolving the problem of scale between point, field-based measurements and satellite-derived soil moisture products and are important in monitoring key biogeochemical processes that vary rapidly in time and space. In the initial phase of the implementation of the ISMON network, the current distribution of the stations in relation to the other networks are presented. The ISMON aims to represent the most relevant soil types, land cover, and regional climate regimes to corroborate direct measurements of soil moisture; it will adapt its design to improve the monitoring network as required. The ISMON will make a valuable contribution to, and expand the international soil moisture monitoring network. 
The Climate Watch System in WMO RA VI
Authors: Bissolli Peter , Rösner Stefan , Roebeling Maarit , Körber Maya
Published: June 2022

The German Meteorological Service (Deutscher Wetterdienst, DWD) hosts the Regional Climate Centre Network of the WMO Regional Association (RA) VI Region (Europe and Middle East). One of its mandatory functions is the issuance of Climate Watch Advisories (CWA). These are early warning advisories on weather and climate events in the extended forecast range (2-4 weeks), such as heat and cold waves, heavy precipitation periods and drought, all within Europe / RA VI. The advisories are based on expert assessments of climate monitoring and extended forecast results. Users of these advisories are other National Meteorological and Hydrological services (NMHSs) in the RA VI Region. It is up to the NMHSs to turn CWAs into tailored national advisories or warnings to their end users.

One of the main criteria for issuing CWAs is the existence of any expected impact, and the advisories should also contain impact information (e.g. flooding, impact on health or agriculture). In such a large area like Europe / the RA VI Region, the impact can be very different from country to country due to the very heterogeneous climate within the Region, different infrastructure and different level of vulnerability.

To gather the impact information, an appropriate geodatabase has been established at DWD, the so-called KRONER (Knowledge Database on EuROpeaN Climate ExtRemes). Taken from various sources in the web and especially from data and reports of NMHSs, the following event information is archived as data base records: start and end time of the event, event category (flood, landslide, heat wave, etc.), related low- or high-pressure system, place (country, various administrative levels), description of the event and related impact. The data base is filled daily, and the content is checked for relevance for Climate Watch purposes by applying specific warning criteria (sufficient duration, spatial extension, extreme intensity and impact).

For the future, it is planned to transform this subjective Climate Watch system (based on expert assessment) into an objective automatized system. This new system will contain the check of warning criteria based on gridded data of preselected forecast models, the automatized generation of CWAs using text modules, automatic inclusion of impact information taken from the KRONER database, automatic visualisation of warned areas using geodata layers and automatic distribution to the users (the NMHSs).
FESSTVaL: connecting dense surface networks, supersites and citizen to catch atmospheric variability at kilo- and subkilo-meter scales
Authors: Hohenegger Cathy
Published: June 2022

FESSTVaL, the Field Experiment on Submeso Spatio-temporal Variability in Lindenberg took place in summer 2021 in Germany. Initially proposed by modellers to peer into the lifecycle of convective cold pools, it led observationalists design new instruments and new retrieval algorithms to catch variability at kilometer scales. Those included self-designed autonomous cold pool loggers (APOLLOs), self-built weather stations (MESSIs) and novel gust wind retrievals. FESSTVaL connected cheap, numerous surface observations, with a network of 182 instruments deployed in a 15-km radius around Lindenberg, with expansive vertically profiling instruments, deployed at three supersites. To augment the spatial coverage of the surface network, FESSTVaL connected to citizen and involved them in the measurement process. With its focus on observing the summertime boundary layer and its variability at kilometer scale, FESSTVaL also bridged between the numerous past field campaigns on either micro- or meso-scale phenomena. Not to forget that FESSTVaL took place around the supersite of the German Weather Service and benefitted from the connection between basic research and operational application, both on the observational and modelling side. In this talk, I’ll show how FESSTVaL connected communities and, from a process point of view, scales and which results were achieved. In particular FESSTVaL provided for the first time unprecedented highly-resolved spatio-temporal cold-pool structures, both in the horizontal and in the vertical dimension, associated with overpassing convective systems. FESSTVaL also captured the effects of the atmosphere on cold pool characteristics as well as the effects of cold pools on land surface properties.
An upper bound for extreme temperatures over midlatitude land
Authors: Zhang Yi , Boos William
Published: June 2022

Heatwaves damage societies globally and are intensifying with global warming. Several mechanistic drivers of heatwaves, such as atmospheric blocking and soil moisture-atmosphere feedback, are well-known for their ability to raise surface air temperature. However, what limits the maximum surface air temperature in heatwaves remains unknown; this became evident during recent Northern Hemisphere heatwaves which achieved temperatures far beyond the upper tail of the observed statistical distribution. Here, we present the hypothesis, with corroborating evidence, that convective instability limits annual maximum surface air temperatures (TXx) over midlatitude land. We provide a theory for the upper bound of midlatitude temperatures, which accurately describes the observed relationship between temperatures at the surface and in the mid-troposphere. Known heatwave drivers shift the position of the atmospheric state in the phase space described by the theory, changing its proximity to the upper bound.Our theory suggests that the upper bound for midlatitude TXx should increase 1.9 times as fast as 500-hPa temperatures. Using empirical 500-hPa warming, we project that the upper bound of TXx over Northern Hemisphere midlatitude land (40°N-65°N) will increase about twice as fast as global mean surface air temperature, and TXx will increase faster than this bound over regions that dry on the hottest days. Our results identify two factors that must be constrained for accurate projection of midlatitude extreme temperatures: i) the amount of midlatitude free-tropospheric warming, and ii) surface air specific humidity changes on the hottest days. Understanding the physical processes controlling these factors should be priority in future research on midlatitude extreme temperatures.

 

 

 

 

 

 

 

 

 

 
Assessment of land energy uptake in the industrial period from observational and model products
Authors: García Pereira Félix , González Rouco Jesús Fidel , Melo Aguilar Camilo , Steinert Norman , García Bustamante Elena , de Vrese Philipp , Jungclaus Johann , Lorenz Stephan , Hagemann Stefan
Published: June 2022

Land-air interaction occurs at the ground surface at a wide range of time scales in the form of mass, momentum, and energy exchange. As a result of the water and heat fluxes, the land acts as a water and mostly energy storehouse for the climate system. Last estimates based on multimodel comparisons quantify the land contribution to terrestrial energy budget at about 2 % in the last four decades, whilst other studies based on borehole temperature profiles (BTPs) scale it up to be a 6 %. This uncertainty makes it necessary to explore other data sources to determine the land energy uptake, mostly under the increasing energy imbalance due to the ongoing anthropogenic-induced climate change.

State-of-the-art land surface models (LSMs) resolve a subsurface whose bottom boundary condition placement (BBCP) is not deep enough to correctly represent its thermal structure. This results both in a constrained capability to store energy, and an overestimation of temperature variability and industrial trends with increasing depth. A 2000-year-long forced simulation using a version of the Max Planck Institute (MPI) Earth System Model (ESM), MPI-ESM, including a very deep version of the LSM (BBCP at 1417 m), allows for assessing the behavior of subsurface temperatures and heat storage at long term scales, with a particular focus on the land response to the last century global warming. The analysis also allows for extending the assessment to CMIP6 historical simulations and climate reanalysis data.

Preliminary results show the energy uptaken by the MPI-ESM simulation with a deep version of the LSM is well above the range of values provided by CMIP6 model-based estimates and much closer to the observations. This underlines the great importance of BBCP depth in correctly representing the role of the land component in the terrestrial energy budget.
The role of Rossby wave breaking for extreme and annual mean precipitation in (semi)arid regions
Authors: De Vries Andries Jan , Armon Moshe , Klingmüller Klaus , Portmann Raphael , Domeisen Daniela I.V.
Published: June 2022

Precipitation can have large dual societal impacts in regions with a dry climate. On the one hand, extreme precipitation can induce catastrophic floods, and on the other hand, replenish scarce freshwater resources. In contrast to wet (extra)tropical regions, the atmospheric processes that govern the precipitation formation in dry subtropical and extratropical regions are often overlooked by the scientific community. In this study we investigate the role of Rossby wave breaking for precipitation in (semi)arid regions at the global scale. To this end, we quantify the contribution of Rossby wave breaking to extreme precipitation days and annual precipitation amounts in regions with different degrees of aridity. Rossby wave breaking is represented by potential vorticity (PV) streamers and cutoffs on isentropic surfaces using ECMWF reanalysis data, while for precipitation we also use an observational product. We show that the relevance of Rossby wave breaking for precipitation increases from humid to hyper-arid regions. Equatorward breaking Rossby waves contribute to a large fraction of precipitation extremes and annual amounts in regions on the poleward-westward flanks of the world’s most arid regions where most precipitation occurs in the cool season. In contrast, precipitation in the equatorward-eastward parts of these arid regions has a negative association with Rossby wave breaking, implying that the tropical forcing governs the precipitation formation which occurs in these regions predominantly in the warm season. Overall, this study shows that Rossby wave breaking is of key importance for precipitation in (semi)arid regions that are exposed to both flood hazards and drying under global warming.
Estimation of planetary boundary layer height (PBLH) from profile data at Bosung site
Authors: Song Yunyoung , Ahn Myoung Hwan , Lee Su Jeong
Published: June 2022

The planetary boundary layer (PBL) is the lowest part of the atmosphere and it is directly influenced by its contact with a planetary surface and the PBL height (PBLH) varies with time, season and topography. In this study, PBLH is estimated from atmospheric profiles utilizing the parcel method, the bulk Richardson method and the temperature inversion method using the potential temperature, turbulence and temperature gradients, respectively. Additionally, the theta gradient profile and the mixing ratio gradient profile are used to estimate PBL discontinuity in the previous methods. The ERA5 reanalysis is used as reference data in order to develop the PBLH estimation algorithm. During the day, the PBLH is first estimated by the parcel method. If the estimated PBLH is less than 3000 m, it is final PBLH. If not, secondly, calculate the bulk Richardson number to find the height below criteria (0.25) as the final PBLH. When these conditions are not satisfied, finally, the height of the maximum theta gradient subtracts the difference between the height obtained from the bulk Richardson number and the height of the maximum theta gradient. These differences are hourly averaged over the duration of the study. During the nighttime (from evening to morning), PBLH is estimated by the temperature inversion method, and if it greater than 1500 m or not calculated, PBLH is calculated using the theta gradient method and the mixing ratio gradient method. The algorithm is applied to Ground-based microwave radiometer (MWR) profiles, the one-dimensional variational (1D-VAR) retrieval profiles based on the optimal estimation by combining MWR brightness temperatures and a priori information from Local Data Assimilation and Prediction System model. The PBLH difference between MWR and ERA5 shows a large correlation coefficient (0.59) than between 1D-VAR and ERA5. On contrary, the statistical error of 1D-VAR is lower than MWR. Compared to MWR, The RMSE is reduced to 12 % and bias is reduced to 82.5 %. Detailed methods and results in this study will be presented at the conference.
Characteristics of the Low-Level Jets Observed over Dunkerque (North Sea French coast) using 4 years of wind lidar data
Authors: Dieudonné Elsa , Delbarre Hervé , Sokolov Anton , Ebojie Felix , Augustin Patrick , Fourmentin Marc
Published: June 2022

Previous observational studies about Low-Level Jet (LLJs) in the North Sea area provided insight about LLJs occurring above offshore and inland sites. The present work completes this corpus by adding a statistical study performed above a coastal site, relying on four years of wind profiles recorded by a small Doppler lidar installed in Dunkerque port (northern coast of France, southernmost North Sea). The instrument, a Leosphere Windcube v2, had a range of 280 m allowing the detection of LLJs up to 244 m above mean sea-level. LLJs were found on 4.74 % (9,649) of the 10-minute average wind profiles, laying the basis for a robust statistical analysis of the jet core height, speed and direction, and for the study of the seasonal, annual and daily cycles of the LLJs occurrence. The altitude of the jet core (wind peak) was typically 114 m above mean sea-level, with a core speed around 7-8 m.s-1. The core wind direction exhibited a dominant mode in the NE direction (onshore coastwise) that occurred mostly during the afternoon (11:00 to 18:00 UTC), and a secondary mode in the ESE direction (offshore cross-coast) that occurred mostly during the late night (00:00 to 07:00 UTC). The months with the highest LLJ frequency were April, May and August, following the annual cycle of the dominant NE mode. The conditions of occurrence and possible formation mechanisms of the LLJs over Dunkerque were investigated using three parameters computed from the ERA5 reanalyzes data: the land-sea thermal contrast, the bulk Richardson number and the geostrophic flow. The dominant NE LLJ mode was associated with anticyclonic conditions (easterly geostrophic flow, warmer land, unstable atmosphere), this mode likely gathering local sea breeze events and regional circulations generated by the wind channeling at the entrance of the English Channel.
Intercomparing the quality of recent reanalyses for offshore wind farm planning
Authors: Spangehl Thomas , Borsche Michael , Niermann Deborah , Kaspar Frank , Schimanke Semjon , Brienen Susanne , Möller Thomas , Brast Maren
Published: June 2022

The German energy transition demands the increasing usage of renewable energy resources. Following current plans of the German government, the proportion of renewable energy in total electricity needs shall rise to more than 80 percent until 2030 and reach 100 percent in 2035. One important contribution to reach these goals is the increased setting up of wind farms within the German Exclusive Economic Zone (EEZ). Here, the effective usage of the available space and the economic and environmental planning require knowledge on the meteorological and climatological conditions. A crucial factor is the spatial and temporal variability of the wind over the North Sea and Baltic Sea. Additional insight is gained by the representation of the atmospheric boundary layer.

Global and regional atmospheric reanalyses provide detailed information of the wind speed and wind direction at hub heights of modern wind turbines. In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany’s national meteorological service) provides reanalysis data and quality assessments to Bundesamt für Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency). Currently, the regional reanalysis COSMO-REA6, maintained by DWD, is used besides the global reanalysis ERA5, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF).

At present, new reanalyses and derived products become available. One example is the Copernicus European Regional Re-Analysis (deterministic system, CERRA-DET and ensemble of data assimilations, CERRA-EDA). Moreover, a successor of COSMO-REA6, R6G2 (COSMO-REA6 Generation 2), is currently produced by DWD. Furthermore, a convection-resolving climate simulation for Germany with COSMO-CLM, as a regional downscaling of ERA5, was recently produced by DWD.

The quality of the reanalysis data for offshore wind energy application is assessed on the basis of a consistent evaluation approach. Different types of observations are used as reference. In-situ measurements of the wind speed and wind direction at heights between 30 m and 100 m are available from FINO (Research platforms in the North Sea and Baltic Sea, https://www.fino-offshore.de/en/index.html). Moreover, near surface wind speed and wind direction, retrieved from ASCAT scatterometers onboard METOP-A and METOP-B satellites, are used (satellite data provided by CMEMS, Copernicus Marine Environment Monitoring Service). Results are presented for the 100 m wind speed and wind direction at FINO1 and near surface wind fields over the North Sea. Uncertainties of the different products are addressed by carefully intercomparing the reanalyses.
Clustering possibilities of weather patterns associated with winter cold and warm spells in Hungary
Authors: Mikes Márk Zoltán , Dezső Zsuzsanna
Published: June 2022

In this rapidly changing climate weather extremes get even more attention since they are occurring more frequently around the world. Even when global temperatures are rising, both extremely cold and warm periods impact our economy, agriculture, and our daily life. Using weather station data from Hungary we found that cold and warm spells (CSPs and WSPs) are more intense and have greater variability in the winter months compared to events in the transition or summer months. We also experienced that temperature extremes have recently become more frequent in March, so we used this month additionally to the three winter months in this research. Our results show that various weather patterns may be associated with CSPs/WSPs, so we investigate the macro-synoptic circulation in the background of these events over a 30-year timespan (1991-2020) using the ERA-5 reanalysis database. This will give us a picture of the weather patterns causing both cold and warm extremes in this part of Europe. In this research, we investigate CSPs/WSPs for each month separately and for the whole winter period combined to gather more information about the meteorological background of these extremes. Our main goal is to group events with similar synoptic background, combining wind, temperature, pressure, and geopotential fields (and anomalies) at various pressure levels during the start, peak and end of the events. Then we analyse these clusters more closely, associating them with well-known synoptic situations in Europe. Furthermore, we would like to increase our investigated timespan to weekly anomalies in the future, as it is easier to compare these anomalies with operational long-range forecasts.
Copernicus European regional reanalysis
Authors: Schimanke Semjon , Isaksson Ludvik , Edvinsson Lisette , Ridal Martin , Hopsch Susanna , Dahlgren Per , Bazile Eric , Le Moigne Patrick , Verrelle Antoine
Published: June 2022

The Copernicus European regional reanalysis (https://climate.copernicus.eu/regional-reanalysis-europe) was 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 an overview on available data. Data quality will be demonstrated by comparison with ERA5 and other gridded datasets.

The Copernicus European Regional ReAnalysis (CERRA) is produced with a setup of the HARMONIE-ALADIN model system including a 3D-Var data assimilation scheme for upper air observations and an OI-scheme for surface observations. The model domain covers entire Europe at a horizontal resolution of 5.5 km. The system provides eight analyses per day – at 0 UTC, 3 UTC, 6 UTC, … and 21 UTC. Between the analyses, data are available with hourly resolution from the forecast model. More than fifty parameters are available on various level types including surface parameters and data up to 1 hPa. Data are available for the period September 1984 – June 2021 through Copernicus Climate Data Store (CDS).

In addition to CERRA, the service produced a reanalysis with an ensemble of data assimilation (EDA) system, called CERRA-EDA. CERRA-EDA consists of 10 members and is produced with a horizontal resolution of 11 km. Uncertainty information from the ensemble system is used as a flow depending part of the B-matrix for CERRA. Another product of the service is CERRA-Land. CERRA-Land provides daily precipitation analyses as well as parameters from the surface/soil model SURFEX, which is driven with CERRA data.

In the presentation, the production chain will be illustrated and the availability of data will be clarified. The focus will be on CERRA. The quality of the regional reanalysis will be demonstrated in comparison to the global reanalysis ERA5. For instance, investigations of the winter storm Gudrun (January 2005, southern Sweden) will be presented. 
Assessment of direct normal irradiance assessment from cloud optical depth of geostationary meteorological satellites in Germany
Authors: Turpin Mathieu , Kurzrock Frederik , Schmutz Nicolas
Published: June 2022

The assessment of Direct Normal Irradiance (DNI) is essential for the solar power industry. Satellite estimations offer many advantages over ground-based measurements with immediate and affordable installation (no hardware installation), inexistant operation and maintenance of sensors, and efficient detection of any malfunction by comparing the production measured on the meter with the satellite estimation. In this work, we compare two estimations models of DNI from geostationary meteorological satellites in Germany.

The first model is provided by Copernicus Atmosphere Monitoring Service (CAMS) solar radiation services. In its latest v4 update, this model uses the APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme that is a probabilistic interpretation of the original APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) method to infer the Cloud Optical Depth (COD).

The second model is based on COD of the “Satellite Application Facility on support to NoWCasting and very short range forecasting” (SAFNWC) with the version 2018.1. The algorithm is based on a multispectral threshold technique applied to each pixel of the satellite image and uses Numerical Weather Prediction (NWP) input data for surface temperature and total atmospheric water vapour content.

Both models use a Cloud Mask (CMA) product to delineate all cloud-free pixels in a satellite scene with a high confidence, then DNI is forced to the value obtained by the McClear clear sky model when CMA indicates "cloud free". Otherwise, the COD is combined with the clear sky model in order to compute the effective DNI.

Moreover, we take into account the circumsolar radiation to avoid underestimation of the forward scattered radiation in DNI when compared to ground observations.

The model outputs are compared to 10-minute solar radiation measurements from Deutscher Wetterdienst (DWD) stations located in Germany over the period 2021-04-01 and 2022-03-31. This network measures the Global Horizontal Irradiance (GHI) and Diffuse Horizontal Irradiance (DHI). DNI is computed out of the quality-checked measurements of GHI and DHI. The results are expressed for all available measurement data in terms of relative Root Mean Scare Error (RMSE), RMSE Skill Score, Mean Absolute Error (MAE), MAE Skill Score, and mean bias error.

We conclude that the two models offer similar performances with a MAE between 25% and 35% for Germany.
Combinational Optimization of Physical Parameterization Schemes to Improve Air Quality Prediction Using Intelligent Optimization System
Authors: Yoon Ji Won , Lee Ebony , Lim Sujeong , Lee Seungyeon , Park Seon  Ki
Published: June 2022

  The environmental problems related to air pollution have been increasing, especially in East Asia, due to human activities, including high energy consumption and rapid economic growth. In order to address the air pollution problems, it is essential not only to improve the national and local air pollution control measures but also to enhance the air quality forecast skill through a numerical prediction system. The performance of numerical air quality prediction is significantly dependent on the land surface and the PBL parameterization schemes in a coupled atmosphere-chemistry prediction system, such as the Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-Chem).

  In this study, to improve the air quality prediction performance in East Asia, we built an intelligent optimization system by coupling the micro-genetic algorithm (μGA) and the WRF-Chem model --- the WRF-Chem-μGA system. This system can find an optimal set of physical parameterization schemes in WRF-Chem to improve the air quality forecasting.

 Before optimization, we selected several cases by considering the synoptic weather patterns according to the sources and the transport routes of the sand dust storms that affected Korea. As a preliminary study, we aim to obtain the optimal set of the land surface and PBL schemes via the intelligent optimization system for each case, which is the most suitable for predicting some Asian sand dust storm (SDS) events over Korea. Overall, our preliminary results show that the WRF-Chem with the optimized set of parameterization schemes produces better results than that with non-optimized scheme sets in forecasting the selected SDS events in East Asia.
Towards a data-driven nowcasting of severe weather based on geostationary satellite data
Authors: Küçük Çağlar , Giannakos Apostolos , Schneider Stefan , Jann Alexander
Published: June 2022

Nowcasting severe weather is crucial not only to mitigate the effects of extreme weather events like storms and flash floods but also to support decision-makers on weather-dependent operations like aviation and outdoor events. Stunning pace of developments in Artificial Intelligence (AI) and increasing availability of high resolution data from different sensors motivate using AI in weather prediction, particularly in nowcasting due to its rapidly changing dynamics in short timescales.

Meteosat Third Generation (MTG) will greatly improve our capacity on nowcasting with its high resolution sensors on board. However, data-driven algorithms are needed to use the information stored within large volumes of MTG data for nowcasting in an efficient way. Therefore, we are developing AI based nowcasting algorithms fusing remote sensing data with ground based radar mosaics for nowcasting severe weather. 

As MTG data are not available yet (expected to be launched in late 2022), we use data from GOES satellites as the primary data source, which have comparable sensors with MTG. Specifically, we use the Storm Event ImageRy (SEVIR) dataset in the initial phase of the study which contains more than 10000 image sequences, 20 % of which contain storm events reported by NOAA. Each of these image sequences cover 384 x 384 km in space and 4-hour in time, containing three bands from the visible and infrared spectrums, and the lightning mapper data from GOES-16 with Vertically Integrated Liquid (VIL) mosaics derived from ground-based radar. We obtained promising results to reproduce spatial variations of VIL with Generative Adversarial Network (GAN) as a baseline. We are currently developing Recurrent Neural Network (RNN) based models to reproduce temporal variations of VIL to incorporate temporal information in GAN models. Furthermore, we are using European Weather Cloud, which not only provides a strong computation infrastructure but also fosters collaboration across projects. Development of efficient AI algorithms for nowcasting severe weather using GOES data will enable the opportunity to fully use MTG data on nowcasting severe weather.
Analyzing precipitation distribution and intensity related to floods in the Spanish Mediterranean basin since 1960
Authors: Cuixart Mercè , Peña Juan Carlos , Gil-Guirado Salvador , Pérez-Morales Alfredo , Serrano-Notivoli Roberto , Pino David
Published: June 2022

The Spanish Mediterranean Basin (SMB) have experienced an increase of urbanization resulting from the socioeconomic growth of the last five decades. Consequently, flood prone areas have been intensively occupied and have become more vulnerable to this hazard. In this framework, we analyze the intensity and distribution of precipitation associated to floods occurred in the coastal municipalities of the region between 1960 and 2012, according to the SMC-Flood database (https://doi.org/10.5194/nhess-19-1955-2019).

Our study uses this database and a Principal Component Analysis technique to identify significant patterns and correlations between the damage produced by the floods, the main synoptic patterns during those days (https://doi.org/10.1016/j.scitotenv.2021.150777) obtained from the 20th Century Reanalysis V3 project and the precipitation from the SPREAD database (https://doi.org/10.5194/essd-9-721-2017).

Regarding the synoptic analysis, 12 different patterns explain most of the variance of the surface pressure. Additionally, the provinces from Girona to Almería are more commonly affected by eastern airflows in autumn, mainly owing to the warm and moist Mediterranean air transportation; whereas the prevailing wind in the most southwestern provinces (Cádiz, Málaga and Granada) is from the south and it is frequently associated to Atlantic low-pressure centres. Yet, it is found that the northern provinces of the SMB can be also affected by the latter configuration.

Regarding the precipitation, 9 different patterns associated to different regions along the SMB are obtained. The matching between both types of patterns (synoptic and precipitation) is performed according to the flood events statistically related to each of them.

Finally, from the analysis it can be concluded that the provinces of Granada, Almería and Barcelona are more exposed to this hazard, as low average rainfall values and high mean severity indexes are identified; and also, that the patterns presenting an Atlantic trough tend to provide more precipitation and more severe events.