bluuebunny/crossref_metadata_2025 huggingface dataset:
A gridded European global dataset based on in-situ observations
Authors: van der Schrier Gerard , Knap Wouter , Dirksen Marieke , van den Besselaar Else J.M. , Klein Tank Albert M.G.
Published: June 2021

Within the EOBS project, one of the objectives is to provide an (ensemble) gridded data set of global radiation. In-situ observations of daily sums of global radiation are combined with daily sunshine duration records to construct a dataset for daily global radiation that goes back to 1950. A generalization of the commonly used Angstrom-Prescott formula is used to relate daily values of sunshine duration to global radiation, where optimal values of the parameters in this model are found by allowing for variations in the latitude and with the seasons. A quality control procedure based on the physical limits of  global radiation - latitude and yearday dependent - is applied to the data.

Based on this dataset, a gridded dataset for daily global radiation is produced with a resolution of 0.1 degree, covering Europe. The density of the combined networks of radiation and sunshine duration measurements hugely varies in space and time and this inhomogeneity is likely to give variations in space and time of the confidence of the gridded dataset. A method for enhancing the spatial analysis of daily global radiation from a sparse network is by incorporating information on the spatial covariance in the global radiation fields determined from high‐resolution measurements available in the past. Here we use satellite-based daily observations of downwards surface shortwave radiation from the CERES (Clouds and the Earth's Radiant Energy System) dataset for this purpose.

This approach is inspired by the reduced space optimal interpolation (RSOI) method, and the dominant patterns of variability are calculated using Self Organizing Maps (SOMs). Before reducing the dimension of the CERES dataset to 15 patterns, seasonal trends were removed. SOMs comprise a class of unsupervised neural networks that organize input geospatial data into a user-defined number of outputs (nodes) obtained by iteratively adjusting the nodes to resemble the input data. The training of this unsupervised artificial neural network is entirely data driven.

In the presentation, the similarity between the gridded dataset and the underlying station data is quantified, and a comparison against the CMSAF SARAH dataset is presented.
Modelling winter storm impacts on insured claim ratios of residential buildings in German administrative districts
Authors: Trojand Andreas , Becker Nico , Rust Henning
Published: June 2021

Severe winter storms are one of the most damaging natural hazards for European residential buildings. Previous studies mainly focused on the loss ratio (loss value / total insured sum) as a monetary value for damages. In this study the focus is on the claim ratio (number of claims / number of contracts), which is derived from a storm loss dataset provided by the German Insurance Association. Due to its magnitude, the claim ratio might be a more intuitive parameter for the use in impact-based warnings than the loss ratio.

In a first step, loss ratios and claim ratios in German administrative districts are compared to investigate differences and similarities between the two variables. While there is no significant change in the ratio between claim ratio and loss ratio with increasing wind speeds, a tendency for lower loss ratios in urban areas can be confirmed.

In a second step, a generalized linear model for daily claim ratios is developed using daily maximum wind gust (ERA5) and different non-meteorological indicators for vulnerability and exposure as predictor variables. The non-meteorological predictors are derived from the Census 2011. They include information about the district-average construction years, the number of apartments per buildings and others to get a better understanding of these factors concerning the number of buildings affected by windstorms. The modelling procedure is divided into two steps. First, a logistic regression model is used to model the probabilty claim ratios larger than zero. Second, generalized linear models with different link functions are compared regarding their ability to predict claim ratios larger than zero. In a cross-validation setting a criteria for model selection is implemented and the models of both steps are verified. Both steps show an improvement over the climatological forecast and in both cases the addition of data for vulnerability and exposure leads to in decrease of the mean squared error. 
Understanding complex wind fields with single Doppler Lidar techniques
Authors: Thobois Ludovic , Troiville Anselme , Pontreau Laurie
Published: June 2021

Scanning Wind Doppler lidars are more and more used for operational applications for which the retrieval of wind vectors and the turbulence quantities at specific points or at high resolution in an area of interest can bring valuable information. For retrieving volume wind data, many techniques can be used to retrieve wind vectors from the combination of radial wind data at different distances and lines of sight, as the well-known Volume Velocity Processing (VVP) technique, developed formerly for Doppler Radars. Although More sophisticated techniques based on the coupling with computational fluid dynamic models exist. e, a processing based on the VVP technique, called the Volume Wind processing (VW) has been developed. This algorithm includes a Single Value Decomposition algorithm that ensures a robust filtering of the retrieved wind data, and then high accuracy and precision. In addition, radial velocity variance (RVV) algorithm has been developped to remove the constant wind speed over a scan to provide fields of turbulent radial wind speeds. Those fields can be averaged and their variances can be computed to determine the averaged turbulent radial wind speeds as well as its deviation.

In this study, the principle and the validation of the VW algorithm will be presented at different sites (offshore, rural, and urban) against reference anemometers will be firstly presented. The bias and precision on 10 minutes averaged wind speed obtained are both about 0.5 m/s. The results reveal that the accuracy is significantly better for winds along lidar beam and precision better for larger samples of instantaneous wind speeds in the averaging time. Finally, the Volume Wind and the Radial Velocity Variance algorithms have then been applied to datasets of several months measured with Windcube Scanning Lidars at two different sites characterized by complex terrain and buildings. The data processed by the algorithms are analyzed to better understand the heterogeneities of the wind fields and its variations in time.
Use of a Clear Sky Index to Evaluate Solar and Cloud NWP Forecasts
Authors: Gleeson Emily , Pagh Nielsen Kristian
Published: June 2021

Forecasting cloud accurately is still a challenge in numerical weather prediction (NWP) models. Detailed qualitative evaluation of such forecasts is needed in order to improve the forecasts. Cloud cover is often used for the evaluation but it is not a good metric due to inconsistency in methods for assessing the cloud cover. Global horizontal irradiance (GHI), also referred to as “global radiation”, provides an objective and quantitative measure for evaluating cloud forecasts during daytime.

Non-dimensional indices for solar energy resource assessment have been developed in recent years and decades that are very useful. One such index
is the clear sky index (CSI), which is the GHI divided by the theoretical GHI during clear sky conditions (e.g. [1,2]). We use the theoretical GHI clear sky model of [3,4], which includes coefficients that account for variable integrated atmospheric water vapour, aerosols and ozone. We have used binned CSI data computed using HARMONIE-AROME NWP forecast data and observations to identify model deficiencies in cloud and to evaluate new model physics options and settings. Sample results include the identification of consistent negative GHI biases under the thickest clouds and positive biases under Stratocumulus clouds. Such results help to pin-point deficiencies in the HARMONIE-AROME NWP model.

[1] Perez, R.; Ineichen, P.; Seals, R.; Zelenka, A. Making full use of the clearness index for parameterizing hourly insolation conditions. Sol. Energy 1990, 45, 111–114.

[2] Skartveit, A.; Olseth, J.A.; Tuft, M.E. An hourly diffuse fraction model with correction for variability and surface albedo. Sol. Energy 1998, 63, 173–183.

[3] Savijärvi, H. Fast radiation parameterization schemes for mesoscale and short-range forecast models. J. Appl. Meteorol. 1990, 437–447.

[4] Gleeson, E.; Nielsen, K.P.; Toll, V.; Rontu, L.; Whelan, E. Shortwave Radiation Experiments in HARMONIE. Tests of the cloud inhomogeneity factor and a new cloud liquid optical property scheme compared to observations. ALADIN-HIRLAM Newsl. 2015, 5, 92–106.
European heat waves: observational characterization attending to climatic zones and modelled sensitivity to spring precipitation deficit.
Authors: Khodayar Pardo Samira
Published: June 2021

In a changing climate an increase in frequency, intensity, and duration of heat extremes in Europe is predicted, accompanied by a decrease in mean precipitation, soil moisture and evapotranspiration. Over the last century, an increase in the duration of the heat waves and the number of hot days and warm nights was observed in Europe. One of the main “hot-spot” in this intensification of weather extremes is the Mediterranean due to the strong decrease in mean precipitation and increase in mean temperature. In the last two decades Europe has been frequently affected by extreme heat waves with record-breaking temperatures and large impacts on the natural, social system or on human health. During such heat-wave periods the daily mortality rate reached anomalies of about +70 %, causing for example additional 70,000 heat-related deaths in Europe in summer 2003. European cities are highly vulnerable to such events due to the urban heat effect.

Despite the significant impact of heat waves on society and the projected increase in the frequency and intensity of these phenomena in Europe, the local-to-regional characteristics and the physical processes that contribute to their occurrence are not yet sufficiently understood.

In this study, we investigate two relevant aspects of this extreme phenomena, (a) the evolution observed from the 1950-to-present in three different climatic zones in Europe, the Iberian Peninsula, France, and Central Europe, and (b) the sensitivity to preceding winter-spring precipitation and particularly spring soil moisture conditions.

Despite a general positive tendency towards higher number and intensity of heat waves in all climatic zones, relevant differences were also found. Wet winter seasons are correlated to a decrease in the number of heat days and heat wave events during summer periods. Furthermore, extreme dry/wet spring soil moisture conditions over the Iberian Peninsula contribute up to 30% to changes in summer temperature in central Europe. In this presentation, the above mentioned and additional key results will be further discussed in detail.
Experience from the RealClimate.org blog and lessons learned
Authors: Benestad Rasmus
Published: June 2021

The blog RealClimate.org was launched December 2004, and one interesting question is what came out of our involvement with climate blogging. The times have changed for sure between 2004 and 2020, with a completely level of public awareness of climate change and political landscape that was barely conceivable then. My personal involvement in RealClimate.org brought exposure but also an opportunity to learn about what questions that people outside the scientific community had. This also had an impact on my production of scientific papers, and six scientific papers originated from ideas and the engagement connected to RealClimate.org. Some of these papers have resulted in various appearances in the media, from a report in Scientific American to TV documentary.

My involvement at RealClimate has earned me both acknowledgement and enemies. Climate science was a contentious issue within the political sphere already when we started blogging, something we quickly learned through the comments on our posts. One question we discussed was how to deal with comments. We decided to moderate them fairly strictly in the start, which set the culture. All spam and ad hominem was banned. We also decided to deal with trolls was to set up a page called "The Bore Hole", where we could move false information and troll-like comments. The readers appreciated the platform as a place for discussion, so at a later stage, we established monthly threads with the title 'Unforced variations'.

Today, we may ask what difference did RealClimate make and what would the world look like without such blogs where scientists reach out.
Compiling a virtual awards ceremony
Authors: Cegnar Tanja
Published: June 2021

Due to pandemics many of our plans were corrupted and changed. The previously planned in-person events had to be carried out virtually.

Since established, the EMS Media Awards were presented live during the EMS Annual Meeting.  Everybody appreciated the opportunity for networking, informal questions and sharing of detailed backstage information.

Due to pandemic the EMS Annual Meeting in 2020 was cancelled and with this also the opportunity to present the awardees live vanished. This was a huge disappointment for the awardees. To overcome this drawback the Media and Communication Committee decided to organize a virtual media awards ceremony. Although we felt a bit uneasy at the beginning, a very positive response of all awardees encouraged us. With no previous experience in virtual awards ceremonies we compiled a scenario and gave instructions to awardees how to prepare their intervention in an appealing and sometimes entertaining way. We would be happy to share how the project developed and which technical problems we encountered.
On the Ocean Mixed Layer influence on the genesis of Mediterranean Tropical-Like cyclones
Authors: Ricchi Antonio , Liguori Giovanni , Cavicchia Leone , Miglietta Mario Marcello , Bonaldo Davide , Carniel Sandro , Ferretti Rossella
Published: June 2021

The Mediterranean basin is the formation site of a vast number and type of cyclones. Among these, we can occasionally identify intense vortices showing tropical characteristics, called Tropical-Like Cyclones (TLC). Their development has been studied in several case studies, showing the influence of synoptic scale upper level forcings and mesoscale features, such as the sea surface temperature and the characteristics of the air masses on the formation area. The importance of Sea Surface Temperature (SST) consists in modulating the intense latent and sensible heat fluxes, which control the development of the TLC. For tropical cyclones, one of the most studied factors in recent years is the ocean heat content in the formation basin of these storms. We plan here to extend this analysis to TLC. Besides innovative studies with coupled atmosphere-waves-ocean numerical models, a simpler approach for investigating the sole effect of the ocean heat content consists of adopting a simplified ocean description by varying the local characteristics of the Ocean Mixed Layer (OML). In this work we use the WRF (Weather Research and Forecasting system) model, in standalone (atmospheric) mode, with 3 km grid spacing, forced with GFS-GDAL (0.25°x0.25° horizontal resolution) and SST initialization provided by the MFS-CMEMs Copernicus dataset. Two case studies of TLC are examined here, namely ROLF (06-09/11/2011) and IANOS (14-19/09/2020). The ocean is simulated with an OML approach, with SST updated at each iteration as a function of the atmospheric heat fluxes and with an average mixed layer deph (MDL) provided by the MFS-CMEMS dataset. For each TLC studied, the MDL is modified by increasing and decreasing its depth by 10 mt, 30 mt, 50 mt . The preliminary results show how the structure of the MDL influences  the intensity of the cyclone but also the structure and precipitation both in terms of quantity and location. 
Data rescue and digitization through image recognition
Authors: Hygen Hans Olav , Elo Christoffer Artturi , Gjelten Herdis Motrøen
Published: June 2021

MET Norway has, like many other NHMS, more than a century of data, where a large portion of early measurements are not digitized. At MET Norway these data were stored on microfilm, which was smouldering away. In the autumn of 2020 were we able to scan all of these microfilms, which produced 1.3 million pictures with 1 to 6 datasheets per image. Each image contains daily data from one month. These images were produced automatic, and basically without metadata.

Moving these images towards data requires multiple steps, and a manual job in-house in MET would be too costly. In other projects at MET Norway image recognition has been applied to e.g. cloud classification. Based on this, image recognition was applied. We apply this in a multi-stage approach to ensure the quality of every stage and gain confidence in the technology. The first stage is to make a catalogue of which stations is represented in each image. The next stage is to capture the metadata such as the year and month of each image/datasheet. Stage three is to extract the data from each image and prepare it for MET Norway’s data storage and distribution. As part of this, the regular quality control from MET Norway will be performed on the dataset, thus ensuring that the quality is up to MET Norway’s regular standard.

We are still in the early stages of the project. As stated are the microfilms scanned, and we have used image recognition to create a catalogue of which image belongs to which stations. We have also extracted which year is represented in each picture. This was done due to this information been in printed letters. The observations are handwritten and have so far been to be harder to extract. An internal website has been established to monitor the progress from the image recognition and limited manual corrections.
Association between COVID-19 lockdown policies and air pollution with associated mortality reduction in Europe
Authors: Schneider Rochelle , Masselot Pierre , Vicedo-Cabrera Ana Maria , Sera Francesco , Blangiardo Marta , Forlani Chiara , Douros John , Jorba Oriol , Adani Mario , Kouznetsov Rostislav , Couvidat Florian , Arteta Joaquim , Raux Blandine , Guevara Marc , Colette Augustin , Barré Jérôme , Peuch Vincent-Henri , Gasparrini Antonio
Published: June 2021

Governments were enforced to respond to SARS-CoV-2 virus spread by taking a wide range of policy measures. Several studies have reported a decrease in air pollution following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference, and did not assess the role of different policy interventions. These responses offered an unprecedented opportunity to assess the effectiveness of several interventions to reduce air pollution levels worldwide. Using an accurate representation of business-as-usual and lockdown air pollution scenarios, provided by Copernicus Atmosphere Monitoring Service (CAMS), we quantitatively evaluated the association between policies responses to the COVID-19 pandemic with changes in NO2, O3, PM2.5, and PM10 levels in 47 European cities. We also estimated the short-term mortality in the period of February-July 2020. An advanced spatio-temporal Bayesian non-linear mixed effect model was performed to determine the association between air pollutant levels and stringency indices as well as individual policy measures. The results indicate non-linear relationships, with a stronger decrease in NO2 and to a lesser extent PM10 and PM2.5 at very strict policy levels. Differences across interventions were also identified, actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements had strong effects, while restrictions on internal movement and international travels showed little impact. The observed decrease in pollution potentially resulted in hundreds of avoided deaths across the European cities. This project provides information that can help inform future policies on air pollution reduction.
Impact of SST on the NWP forecast over Adriaticduring the exceptional bura outbreak in February 2012
Authors: Tudor Martina , Janeković Ivica , Ivatek-Šahdan Stjepan
Published: June 2021

In February 2012 a strong wind event over the Adriatic Sea lead to extreme air-sea interactions. The extreme event consisted of strong to severe cold wind (bura) event that last over three weeks accompanied by accumulation of snow on the coastline in the beginning of the event. As a result, the sea surface cooled rapidly and mixed throughtout the vertical column. The ALADIN System operational forecast used the sea surface temperature (SST) available from the global meteorological model ARPEGE. It was a practical solution for an operational application, since the same source is used also for forecast lateral boundary conditions (LBCs). Here we first compare the SST available from operational global atmospheric models ARPEGE and IFS to in situ measurements, SST analyses and ocean model output. The global models underestimated the SST cooling while the available satellite based observations do not resolve the eastern Adriatic coastline due to numerous islands. Both global models overestimated SST over the Adriatic for up to 10oC when compared to in situ measurements. Afterwards, we runset of forecasts using the SST from the OSTIA and MUR analyses or the ROMS ocean model forecast. The impact of changing SST field on forecast atmospheric fields is mostly reflected on precipitation. Model forecasts more precipitation using warmer SST. Changes in fluxes of evaporation, heat and momentum through the sea surface reflect the changes in the SST. Too warm SST yields too intense fluxes. Colder SST in the Velebit Channel causes reduced momentum flux that allows stronger bura jets above the open sea away from coastlines.
CONFIDENT - Met Norway’s plan for a new quality control system
Authors: Hygen Hans Olav , Aller Abigail Louise , Borg Anette Lauen , Båserud Line , Oram Louise , Larsgård Nina Elisabeth , Kristiansen Vegar
Published: June 2021

The meteorological observation networks are in rapid change. Among other trends, these changes include: increased frequency in observations, increased spatial resolution of observations, and increased heterogeneity in observation platforms. These changes challenge the current data storage and quality control. MET Norway has implemented a new data storage, ODA, to be able to receive a significant amount more data. 

A significant challenge is that the current quality system doesn’t scale to the new world of observations. The current quality control system is not built to be modular, thus requires significant work to integrate improvements.

MET Norway is rising to the challenge of the new observation structure and storage renewing the handling of observational networks and the quality control system. Previously there have been strict criteria on how MET Norway should handle data from an observational station, this is changing with the emergence of new, cheap observational platforms. To accommodate this we are structuring the handling of the station in a hierarchical system where some stations will have fully populated metadata and be treated at the highest level, whilst others will have less information down to unknown stations with unknown setup, e.g. Netatmo.

The new quality control system will be modular to ensure the ability to change and upgrade different parts. One major module of the system is an in-house developed library for spatial quality control, Titan (presented at EMS 2019).

Unlike the present quality control, which is a separate entity to the data storage, CONFIDENT will be built to use ODA as data storage to ensure the best information is available for users and CONFIDENT at all times. We are also working on how we can integrate other software performing quality control of the data, e.g. for assimilation.

The project is planned to start in the autumn of 2021 for three years. Spring of 2021 was used to map relevant activities and modules as the foundation of the planned development of the new system. The plan is not to change the current quality system in one go, but to start implementing the different modules in 2022, and phasing out the current system throughout the project period of three years.
Temperature scaling of extreme precipitation events – an application of the new DWD event catalogue
Authors: Winterrath Tanja , Walawender Ewelina , Lengfeld Katharina , Weigl Elmar , Becker Andreas
Published: June 2021

According to the Clausius-Clapeyron equation on saturation vapour pressure a temperature increase of 1 K allows an atmospheric air mass to hold approximately 7 % more water vapour thus increasing its potential for heavy precipitation. Several published measurement studies on the relation between precipitation intensity and temperature, however, revealed an increase of even up to twofold the CC rate for short-term precipitation events. Model conceptions explain this scaling behaviour with increasing temperature by different intensification pathways of convective processes and/or a transition between stratiform and convective precipitation regimes that both can hardly be verified by point measurements alone. In this presentation, we present first results of the correlation between ambient air temperature and different attributes of the Catalogue of Radar-based Heavy Rainfall Events (CatRaRE) recently published by Deutscher Wetterdienst (DWD). This object-oriented event catalogue files and characterizes extreme precipitation events that have occurred on German territory since 2001. It is based on the high-resolution precipitation climate data set RADKLIM of DWD, i.e. contiguous radar-based reflectivity measurements adjusted to hourly station-based precipitation totals and corrected for typical measurement errors applying specific climatological correction methods. Our analysis gives new insights into potential explanations of the observed temperature scaling relating not only precipitation intensity but characteristic event properties like area, duration, and extremity indices with ambient temperature data. With this approach, extreme precipitation events can be analysed in a comprehensive way that is significant in the context of potential impact. The presented analysis moreover allows testing the hypothesis of regime changing based on objective precipitation event criteria that are typical for different precipitation types. We will briefly present the methodological background of CatRaRE with special focus on the event attributes used in the analysis of Clausius-Clapeyron scaling and give first results on the retrieved temperature dependencies of extreme precipitation events.
Analysis and evaluation of the CORDEX simulations and derived extreme precipitation characteristics in European lowlands
Authors: Berényi Alexandra , Bartholy Judit , Pongrácz Rita
Published: June 2021

As the effects of climate change become more severe, the possible shifts in precipitation patterns can cause severe natural hazards, such as extended drought periods, floods and flash floods, therefore, appropriate risk management is essential. The future adaptation strategies and decisions should definitely consider the results of physically-based climate model simulations, that is why the validation and analysis of these results play a key role in climate change issues.

            The main goal of this study is to analyse the spatio-temporal changes in main and extreme precipitation indices, and validate the Euro-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) simulations from this specific point of view. For the evaluation and analysis, we use the current version of E-OBS database. Both the simulations and the database are available in a 0.11° grid with daily temporal resolution.

            Since plain regions play an important role in agricultural economy and are more exposed to floods due to their geographic features, our primary goals are (i) to examine temporal and spatial changes in extreme precipitation events, and (ii) to explore possible connections between the different lowlands across Europe. Altogether 14 plain regions were selected with an objective multi-step methodology where the selected plains have to fulfil several criteria. These target regions represent different climatic types within Europe and cover different geographical areas (e.g. near the sea, surrounded by mountains, etc.). More specifically, five plain regions are parts of the East European Plain, two regions are located in the Scandinavian basin, five regions are located in Western Europe, one in Southern Europe, and finally, the Pannonian Plain (including mostly Hungary) is also selected.

            To analyse and validate the simulations, we calculated 17 climate indices (most of them defined by the Expert Team of Climate Change Indices, ETCCD). These indices are capable to represent the differences and similarities between and within the plains, and measure the changes in the occurrence an intensity of main and extreme precipitation, the lack of precipitation, and dry spells. The validation results serve as a basis of selecting the most suitable simulations for subsequent analysis of extreme conditions predicted for lowlands within Europe under different future scenarios.
Cloud effect on the Ultraviolet index
Authors: Pokorná Lucie , Tomanová Helena
Published: June 2021

Ultraviolet (UV) radiation is essential for many biological processes even its intensity near the surface is weak in comparison with visible and infrared sun radiation. Plants, animals and humans adopted to common UV radiation intensity. However higher doses pose an increased risk for all organisms. The UV index (UVI) defined in early 90s is recently used to express possible harm to the human body.

The UVI is computed from the spectral intensity of UV–B radiation. Its magnitude is thus related to sun elevation, cloud cover, stratospheric ozone concentration, altitude and air pollution. Important factor is also snow cover which increases the UVI due to high reflectivity. The UVI usually attains values between 0 and 9 in middle latitudes; the higher value of the UVI indicates a higher risk of the human body harm. The highest values are generally reached in sunny days around the noon in June and July in mid-latitudes. The cloudiness usually decreases the UVI and the Cloud modification factor defined for the UV-B radiation reduction is usually applied for the UVI forecast.

The aim of the contribution is to quantify effect of clouds on the UVI and revise the values of the CMF for the UVI. Different types of clouds, the base height and cloud structure are considered. The study is based on station measurement of the UVI, global radiation and sun duration in 10 minutes intervals from four stations in the Czechia during the period 2011–2017. The parameters of clouds were extracted from the SYNOP reports from the nearest stations. The results show a weak effect of high- level clouds on the UVI (decrease of 15 %) even under cover 8/8. The mid- and low-level clouds reduce the UVI with factor 0,7 to 0,35 according to its amount. However, clouds with vertical evolution (cumulus and cumulonimbus) cause in specific cases even increase of the UVI. Complete table of cloud effect on the UVI for the sun elevation between 35° and 50° will be introduced in presentation.
Mitigating urban heat island effect through integrated climate-sensitive planning framework: a study based in Singapore
Authors: Zhang Liqing , Yuan Chao
Published: June 2021

Background

Urban heat island (UHI) is known as one of the severe environmental problems, and thus, research on UHI mitigation from the perspective of urban morphology is indispensable, especially in tropical regions like Singapore.

Objectives

While studies were carried out to evaluate and relieve UHI effect in urban areas, research that conducted through integrated assessment of urban aerodynamic and long wave radiation is limited. This research aims to provide an integrated climate-sensitive planning framework to UHI mitigation by understanding urban morphology.

Methods

A district-scale case study in Paya Lebar Air Base (PLAB) was conducted to illustrate how the urban morphological study contributes to the initial planning by an integrated analysis of climate information. Two urban morphological indices, frontal area density (FAD) and sky view factor (SVF), were calculated to depict aerodynamic and long wave radiation, i.e., pedestrian-level wind speed and air temperature, respectively.

Results

The SVF modelling results indicate that the UHI intensity at surrounding areas could be 2℃ to 3℃. With future development, there is a potential risk to create a spreading and more intensive UHI. Aiming at this problem, the FAD map indicates the importance of linking open spaces to create air paths, while the ΔT map implies the necessity of separating building clusters with intensive UHI. Integrated planning strategies are then developed based on the balance between link and separation, focusing on site layout and building geometry. For site layout, open spaces, e.g., major roads, building setbacks, low-rise built areas, and green corridor, should be linked to form the potential breezeways. At the same time, buffer zones like secondary forest should be arranged between site and surrounding areas to prevent new and existing UHI clusters from merging together. As for the building geometry, as the important design parameters, building height, footprint area, and building height to width ratio (H/W) should be carefully decided. Accordingly, a multi-step workflow is developed as an integrated climate-sensitive planning framework.

Conclusions

Urban morphology makes an important contribution to UHI effect. Integrated UHI mitigations can be developed by balancing the strategies for spatial link and separation in urban planning and design, based on climate information, e.g., aerodynamics and heat. The integrated climate-sensitive planning framework is generally applicable to tropical regions with cooling needs, as the key is to minimize temperature rise due to long wave radiation while introduce cool air to the site.
A spectral analysis of near-surface wind speed and possible sources of predictability in the Iberian Peninsula
Authors: Utrabo-Carazo Eduardo , Azorin-Molina Cesar , Aguilar Enric , Brunet Manola
Published: June 2021

Conventional time series analysis of observed near-surface wind speed (SWS) have focused both on mean values and on the sign, magnitude and statistical significance of trends. Specifically, a decrease in the SWS has been detected in continental surfaces of the planet's mid-latitudes from 1979 to 2010 approximately, the so-called stilling phenomenon; and an increase from 2010 until now, the reversal phenomenon. However, although various hypotheses have been proposed in the scientific literature, the mechanisms behind these phenomena and what evolution this parameter will follow in the future are still understudied, mainly because the response of a variable dependent on atmospheric circulation, such as wind speed, to a warming climate is uncertain. This study aims to use spectral analysis (Fourier and wavelet) to determine the most significant frequency modes associated with the SWS time series in the Iberian Peninsula (IP), for both mean wind speed and daily peak wind gusts, as well as its temporal evolution for 1961-2019. Subsequently, this study will also attempt to relate these modes to those corresponding to various modes of ocean-atmosphere variability such as the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) or, due to the influence of sudden stratospheric warming (SSW) in the European troposphere, the polar vortex. The ultimate goal will be to explore possible sources of predictability in the medium-long term for SWS across the IP, which would have direct applications in areas such as: wind-power generation, agriculture, air quality, insurance and fishing industries, among many others socioeconomic and environmental issues. 
Empirical statistical downscaling with EPISODES in an Alpine territory
Authors: Schellander-Gorgas Theresa , Lorenz Philip , Kreienkamp Frank , Matulla Christoph
Published: June 2021

EPISODES is an empirical statistical downscaling method which has been developed at the German national weather service, DWD (Kreienkamp et al. 2019). Its main aim is the downscaling of climate projections and climate predictions (seasonal to decadal) from global climate models (GCMs) to regional scale. A specific aim is to enhance ensembles based on dynamical downscaling and to improve robustness of deduced indices and statements.

The methodology involves two main steps, first, analogue downscaling in connection with linear regression and, second, a sort of weather generator. An important precondition is the availability of long-term observation data sets of high quality and resolution. The synthetic time-series resulting from EPISODES are multivariate and consistent in space and time. The data provide daily values for selected surface variables and can be delivered on grid or station representation. As such, they meet the main requirements for applications in climate impact research. Thanks to low computational needs, EPISODES can provide climate projections within short time. This enables early insights in the local effects of climate change as projected by GCMs and allows flexibility in the selection of ensembles.

While good results for EPISODES projections have already been achieved for Germany, the methodology needs to be adapted for the more complex terrain of the Alpine region. This is done in close collaboration of DWD and ZAMG (Austria). Among other tasks, the adaptions include a regionalization of the selection of relevant weather regimes, optimal fragmentation of the target region into climatic sub-zones and correction of precipitation class frequencies.

The presentation will refer to the progress of the adaption process. In doing so the quality of downscaled climate projections is shown for a test ensemble in comparison with existing projections of the Austrian ÖKS15 data set and EURO-CORDEX. 

Reference: Kreienkamp, F., Paxian, A., Früh, B., Lorenz, P., Matulla, C.: Evaluation of the empirical–statistical downscaling method EPISODES. Clim Dyn 52, 991–1026 (2019). https://doi.org/10.1007/s00382-018-4276-2
New profiling capability for operational ceilometer networks
Authors: Tuononen Minttu , Lehtinen Raisa , Kallio Jukka , Tuominen Pekko , Roininen Reijo
Published: June 2021

Ceilometers are known to be robust, stand-alone and cost-effective lidar-based remote sensing instruments. Typically, ceilometers are used in aviation to detect cloud base heights. Ceilometers are also used for atmospheric profiling, however, and the applications of profile information are increasing. The focus of this presentation is on potential new developments for operational ceilometer networks, such as the use of depolarization ratio profiles.

High-quality vertical profiles of total attenuated backscatter enable the detailed observation of cloud, boundary-layer, and elevated aerosol layer structures. Further developments in conventional ceilometers, such as the addition of the depolarization ratio profile measurement capability, allow more effective atmospheric sensing and new application areas can be more accurately covered.  Depolarization ratio profiles enable the differentiation of hydrometeors – differentiation of liquid droplets, drizzle and raindrops, snow and ice crystals. These are important to a wide range of applications in the fields of aviation, meteorology, and air quality.

In this presentation we demonstrate depolarization ratio profile measurements using a new Vaisala CL61 Lidar Ceilometer with depolarization ratio profiling capability. We show measurements collected with 910.55 nm wavelength in different field campaigns and the comparison results with research grade lidars in varying weather and climate. The results correlate well and the depolarization ratio measurements show the physical characteristics of liquid and ice clouds, as well as the effects of multiple scattering in liquid cloud layers. This new depolarization capability in ceilometers allows multiple applications to be served, and enables the buildup of operational networks that provide improved vertical profiling in all weather conditions.
Development of downscaled Climate Change Scenarios for Central America. Lessons learned and next steps
Authors: Tamayo Jorge , Rodriguez-Camino Ernesto , Covaleda Sara
Published: June 2021

The intersectoral workshop held in December 2016 among the Ibero-American networks on water (CODIA), climate change (RIOCC) and meteorology (CIMHET) identified the need to dispose of downscaled climate change scenarios for Central America. Such scenarios would be developed by National Meteorological and Hydrological Services (NMHS) in the region, based on a common methodology, allowing the assessment of climate change impacts on water resources and extreme hydro-meteorological events.

One final outcome of the project has been a freely accessible web viewer, installed on the Centro Clima webpage (https://centroclima.org/escenarios-cambio-climatico/), managed by CRRH-SICA, where all information generated during the project is available for consultation and data downloading by the different sectors of users.

A key element in this project has been to integrate many downscaled projections based on different methods (dynamical and statistical), totalizing 45 different projections, and aiming at estimating the uncertainty coming from different sources in the best possible way.

Another essential element has been the strong involvement of the different user sectors through national workshops, first, at the beginning of the project for the identification and definition of viewer features the project, and then for the presentation of results and planning of its use by prioritized sectors.

In a second phase of the project, a regional working group made up of experts from the NMHSs will be in charge of viewer maintenance and upgrade, including new sectoral parameters, developed in collaboration with interested users, and computation and addition of new downscaled projections from CMIP 6 in collaboration with AEMET.

Finally, following the request of CIMHET, the possibility of replicating this project for other areas of Ibero-America is being evaluated.
Performance of the Adriatic Sea and Coast (AdriSC) climate component – a COAWST V3.3-based coupled atmosphere-ocean modelling suite: ocean part
Authors: Pranić Petra , Denamiel Cléa , Vilibić Ivica
Published: June 2021

Abstract. In this study, the Adriatic Sea and Coast (AdriSC) kilometre-scale atmosphere-ocean climate model covering the Adriatic and northern Ionian Seas is presented. The AdriSC ocean results of a 31-year long (i.e. 1987–2017) climate simulation, derived with the Regional Ocean Modeling System (ROMS) 3-km and 1-km models, are evaluated with respect to a comprehensive collection of remote-sensing and in situ observational data. In general, it is found that the AdriSC model is capable to reproduce the observed sea-surface properties, daily temperatures and salinities and the hourly ocean currents with good accuracy. In particular, the AdriSC ROMS 3-km model demonstrates skill in reproducing the main variabilities of the sea-surface height as well as the sea-surface temperature, despite a persistent negative bias within the Adriatic Sea. Furthermore, the AdriSC ROMS 1-km model is found to be more capable to reproduce the observed thermohaline and dynamical properties than the AdriSC ROMS 3-km model. For the temperature and salinity, better results are obtained in the deeper parts than in the shallow shelf and coastal parts, particularly for the surface layer of the Adriatic Sea. The AdriSC ROMS 1-km model is also found to perform well in reproducing the seasonal thermohaline properties of the water masses over the entire Adriatic-Ionian domain. The evaluation of the modelled ocean currents revealed better results at locations along the eastern coast and especially the north-eastern shelf than in the middle-eastern coastal area and the deepest part of the Adriatic Sea. Finally, the AdriSC climate component is found to be a more suitable modelling framework to study the dense water formation and long-term thermohaline circulation of the Adriatic-Ionian basin than the available Mediterranean regional climate models.
Atmospherically-forced sea-level variability in western Hudson Bay, Canada
Authors: Dmitrenko Igor , Volkov Denis , Stadnyk Tricia , Tefs Andrew , Babb David , Kirillov Sergei , Crawford Alex , Sydor Kevin , Barber David
Published: June 2021

Abstract. In recent years, significant trends toward earlier breakup and later freeze‐up of sea-ice in Hudson Bay have led to a considerable increase in shipping activity through the Port of Churchill, which is located in western Hudson Bay and is the only deep-water ocean port in the province of Manitoba. Therefore, understanding sea level variability at the Port is an urgent issue crucial for safe navigation and coastal infrastructure. Using tidal gauge data from the Port along with an atmospheric reanalysis and Churchill River discharge, we assess environmental factors impacting synoptic to seasonal variability of sea-level at Churchill. An atmospheric vorticity index used to describe the wind forcing was found to correlate with sea level at Churchill. Statistical analyses show that, in contrast to earlier studies, local discharge from the Churchill River can only explain up to 5 % of the sea level variability. The cyclonic wind forcing contributes from 22 % during the ice-covered winter-spring season to 30 % during the ice-free summer-fall season due to cyclone-induced storm surge generated along the coast. Multiple regression analysis revealed that wind forcing and local river discharge combined can explain up to 32 % of the sea level variability at Churchill. Our analysis further revealed that the seasonal cycle of sea level at Churchill appears to be impacted by the seasonal cycle in atmospheric circulation rather than by the seasonal cycle in local discharge from the Churchill River, particularly post-construction of the Churchill River diversion in 1977. Sea level at Churchill shows positive anomalies for September–November compared to June–August. This seasonal difference was also revealed for the entire Hudson Bay coast using satellite-derived sea level altimetry. This anomaly was associated with enhanced cyclonic atmospheric circulation during fall, reaching a maximum in November, which forced storm surges along the coast. Complete sea-ice cover during winter impedes momentum transfer from wind stress to the water column, reducing the impact of wind forcing on sea level variability. Expanding our observations to the bay-wide scale, we confirmed the process of wind-driven sea-level variability with (i) tidal-gauge data from eastern Hudson Bay and (ii) satellite altimetry measurements. Ultimately, we find that cyclonic winds generate sea level rise along the western and eastern coasts of Hudson Bay at the synoptic and seasonal time scales, suggesting an amplification of the bay-wide cyclonic geostrophic circulation in fall (October–November), when cyclonic vorticity is enhanced, and Hudson Bay is ice-free.