Study of the Jacobian of an extended Kalman filter for soil analysis in SURFEXv5

An externalised surface scheme like SURFEX allows computationally cheap offline runs. This is a major advantage for surface assimilation techniques such as the extended Kalman filter (EKF), where the offline runs allow a cheaper numerical estimation of the observation operator Jacobian. In the recent past an EKF has been developed within SURFEX for the initialisation of soil water content and soil temperature based on screen-level temperature and relative humidity observations. In this paper we make a comparison of the Jacobian calculated with offline SURFEX runs and with runs coupled to the atmospheric ALARO model. Comparisons are made with respect to spatial structure and average value of the Jacobian, gain values and increments. We determine the optimal perturbation size of the Jacobian for the offline and coupled approaches and compare the linearity of the Jacobian for these cases. Results show that the offline Jacobian approach gives similar results to the coupled approach and that it allows for smaller perturbation sizes that better approximate this linearity assumption. We document a new case of non-linearities that can hamper this linearity assumption and cause spurious 2 delta t oscillations in small parts of the domain for the coupled as well as offline runs. While these oscillations do not have a detrimental effect on the model run, they can introduce some noise in the Jacobian at the affected locations. The oscillations influence both the surface fluxes and the screen-level variables. The oscillations occur in the late afternoon in summer when a stable boundary layer starts to form near the surface. We propose a filter to remove the oscillations and show that this filter works accordingly

Sharing ‘Open Science’ Experiences: A Conversation on Citizen Science

In this panel session, citizen science practitioners, researchers, and facilitators share their unique responses to the question What is good citizen science, for whom, and why?, with the aim of informing and developing citizen science theory and practice

Combining an EKF soil analysis with a 3D-Var upper-air assimilation in a limited-area NWP model

In recent years, the Extended Kalman Filter (EKF) has been gaining more attention in the surface data assimilation (DA) community and has already replaced the older Optimal Interpolation (OI) scheme for the vertical component of the land surface DA system in a number of meteorological institutes. An EKF has been developed within the standalone land-surface modelling platform SURFace Externalisee (SURFEX) for the initialisation of soil temperature and soil water content based on screen-level temperature and relative humidity. In this article we present a new combination of the EKF with a basic (using conventional observations only) three-dimensional variational (3D-Var) upper-air assimilation for the limited-area model ALARO coupled to SURFEX. This new combination is compared to an Open Loop experiment where all initial conditions are interpolated from an analysis of the global numerical weather prediction model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and to an experiment where the surface is initialised using the EKF, while the upper-air initial conditions are interpolated from the ARPEGE analysis. The aim of this article is to examine whether the EKF surface assimilation coupled or not with a basic 3D-Var upper-air assimilation has an added value compared to the Open Loop, in which the more advanced upper-air data assimilation of ARPEGE with more observations used is interpolated onto the limited-area model grid. All set-ups are verified during a 1-year period 2013 against soil measurements, screen-level observations, radiosoundings and merged radar-rain-gauge precipitation observations. Results indicate that the EKF surface assimilation has positive effects on humidity scores and is able to produce similar or improved scores compared to the Open Loop. While the upper-air 3D-Var DA system of ALARO still needs improvements, the potential benefits of the combination of upper-air and surface assimilation are demonstrated through soil moisture and screen-level relative humidity verifications

Evaluating the performance of SURFEXv5 as a new land surface scheme for the ALADINcy36 and ALARO-0 models

The newly developed land surface scheme SURFEX (SURFace EXternalisee) is implemented into a limited-area numerical weather prediction model running operationally in a number of countries of the ALADIN and HIRLAM consortia. The primary question addressed is the ability of SURFEX to be used as a new land surface scheme and thus assessing its potential use in an operational configuration instead of the original ISBA (Interactions between Soil, Biosphere, and Atmosphere) scheme. The results show that the introduction of SURFEX either shows improvement for or has a neutral impact on the 2m temperature, 2m relative humidity and 10m wind. However, it seems that SURFEX has a tendency to produce higher maximum temperatures at high-elevation stations during winter daytime, which degrades the 2m temperature scores. In addition, surface radiative and energy fluxes improve compared to observations from the Cabauw tower. The results also show that promising improvements with a demonstrated positive impact on the forecast performance are achieved by introducing the town energy balance (TEB) scheme. It was found that the use of SURFEX has a neutral impact on the precipitation scores. However, the implementation of TEB within SURFEX for a high-resolution run tends to cause rainfall to be locally concentrated, and the total accumulated precipitation obviously decreases during the summer. One of the novel features developed in SURFEX is the availability of a more advanced surface data assimilation using the extended Kalman filter. The results over Belgium show that the forecast scores are similar between the extended Kalman filter and the classical optimal interpolation scheme. Finally, concerning the vertical scores, the introduction of SURFEX either shows improvement for or has a neutral impact in the free atmosphere

ICTs, data and vulnerable people: a guide for citizens

ICTs, personal data, digital rights, the GDPR, data privacy, online security… these terms, and the concepts behind them, are increasingly common in our lives. Some of us may be familiar with them, but others are less aware of the growing role of ICTs and data in our lives - and the potential risks this creates. These risks are even more pronounced for vulnerable groups in society. People can be vulnerable in different, often overlapping, ways, which place them at a disadvantage to the majority of citizens; Table 3 in this guide presents some of the many forms and causes of vulnerability. As a result, vulnerable people need greater support to navigate the digital world, and to ensure that they are able to exercise their rights. This guide explains where such support can be found, and also answers the following questions: - What are the main ethical and legal issues around ICTs for vulnerable citizens? - Who is vulnerable in Europe? - How do issues around ICTs affect vulnerable people in particular? This guide is a resource for members of vulnerable groups, people who work with vulnerable groups, and citizens more broadly. It is also useful for data controllers1 who collect data about vulnerable citizens. While focused on citizens in Europe, it may be of interest to people in other parts of the world. It forms part of the Citizens’ Information Pack produced by the PANELFIT project, and is available in English, French, German, Italian and Spanish. You are welcome to translate this guide into other languages. Please send us a link to online versions in other languages, so that we can add them to the project website

The potential of an extended Kalman filter for soil analysis in conjunction with a 3D-var system in a limited area NWP model

The surface exerts an important influence on numerical weather predictions (NWP), especially for the planetary boundary layer (PBL). A good initialisation of the surface can therefore improve the short and medium-range forecast scores considerably. The link between the surface and the atmosphere is made by fluxes that transport energy and momentum between the surface and the atmosphere. The fluxes are regulated by the soil temperature and soil moisture content, that regulate the partitioning in sensible and latent heat flux. To initialise the surface, data assimilation techniques can be used. Those techniques combine observations with model data to estimate the real state of the system, or in our case the surface. Due to a lack of direct observations of soil temperature and soil moisture content, the assimilation process uses indirect observations of screen-level temperature and relative humidity. These screen-level observations are influenced by the surface fluxes and thus contain information about the state of the soil. A commonly used data assimilationt technique for the surface is Optimal Interpolation (OI). Despite its operational usage in numerous NWP-centers, it has a few important shortcomings. The OI coefficients are pre-calculated and so they do not depend on the specific location or weather situation. Moreover, these pre-calculated coefficients make it cumbersome to include new observation types, like satellite observations. Recently an EKF has been developped for surface assimilation in the surface model SURFEX that meets these shortcomings. In the EKF the coefficients are calculated in an ad hoc manner, so their values are dependent on the specific location and weather situation. Moreover, the more general and ad hoc manner of calculating these coefficients allows the EKF to be more easily extended towards new observation types. In this thesis the EKF is validated for the Numerical Weather Prediction (NWP) model ALARO coupled to the surface model SURFEX. The EKF will be combined with a three dimensional variational (3D-var) assimilation for the upper-air and the added value of this combination, with respect to surface or upper-air assimilation separatelty, is investigated. The combination of the EKF with 3D-var for a limited area model is a new one that, to our knowledge, has not been tested before. The purpose of this thesis is to find an optimal set-up for the initialisation of the operational NWP-model of the Royal Meteorological Institute (RMI) of Belgium, that is currently initialised using an interpolation of the global ARPEGE data assimilation analyses for both the surface and the atmosphere. To achieve this purpose the research is build up in in four stages. First, the importance of the surface for the planetary boundary layer and the upper atmosphere is described and the surface model SURFEX coupled to ALARO is validated above Belgium within this context. Next, data assimilation theory is discussed, with special attention for OI and the EKF as candidate assimilation techniques for the surface and 3D-var as a technique for the upper-air. The third stage is a thorough validation of the EKF, including a search for the optimal perturbation sizes for the finite differences calculation of the Jacobian of the observation operator. A comparison is made of the offline and coupled finite differences approach of calculation the Jacobian. In a fourth and final stage, the EKF is combined with a 3D-var upper-air assimilation and this combination is compared to a number of other set-ups. The comparison is made with regards to increments and validated with observation of the soil, the screen-level temperature, screen-level relative humidity, atmospheric soundings and precipitation observations. The validation of SURFEX show that SURFEX improves the forecast scores compared to the current operational ISBA surface scheme. The impact on 2m temperature, 2m relative humidity, 10m wind and precipitation is either neutral or positive. Only during Winter the daytime temperatures are too high for the stations located at higher elevations. The study of the observation operator Jacobian of the EKF shows that the offline and coupled approach have similar spatial patterns and values. Still, the offline approach has a few advantages over the coupled one. Firstly, the offline approach allows for smaller perturbation sizes due to which there is a better validity of the linearity assumption of the finite differences approach. Moreover, the offline approach is computationally much cheaper, allowing it to be used in an operational setting. A case of spurious 2∆t oscillations is documented. The oscillations arise in the late afternoon in Summer when a stable boundary layer sets in. Although they dissapear again after a while and do not have a detrimental effect on the forecast scores, they introduce considerable noise in the Jacobian of the EKF and thus in the increments. For this reason a filter was proposed to deal with these oscillations and it is shown that the filter works accordingly. Results show that the coupled, filtered approach gives the best forecast scores. Still our preference goes out to the offline, filtered approach that also improves the non-filtered EKF but is computationally much cheaper and thus more feasable for operational usage. In the final stage the EKF is combined with a 3D-var upper-air assimilation and this set-up is compared to a number of other initialisation set-ups. Experiments were performed for 1 year and for eight different set-ups. The goal of the verification is to get similar scores as the Open Loop, that uses the interpolated ARPEGE analysis as initial conditions for the surface and the atmosphere as it is done in the currect operational set-up at the RMI. Results show that the planetary boundary layer in the model is in general too cold and too wet, except during summer. The surface assimilation is capable of partly eliminating this bias. The importance of the surface assimilation is confirmed by the much larger bias and root mean square error of the free run, in which the surface is not reinitialised after each assimilation cycle but is allowed to run freely during the whole year. The combination of surface and upper-air assimilation provides better scores for soil moisture content and screen-level humidity compared to the Open Loop, especially during the first twelve hours of the forecast. Comparisons of the model values with atmospheric soundings and precipitation observations show that the 3D-var assimilation experiments are not able to reproduce the scores of the Open Loop for the upper layers of the atmosphere. This is probably due to a lack of observations, since only conventional observations are used in the assimilation so far. Only during Autumn, the 3D-var assimilation is able to improve the Open Loop scores for precipitation. The scores also show the positive effect of surface assimilation on the precipitation forecasts. In general it can be concluded that the surface assimilation, and in particular the EKF, improves the surface and boundary layer humidity compared to the Open Loop. For temperature the results are more mixed, but also in this case the surface assimilation experiments are able to achieve similar resutls as the Open Loop in most cases. The 3D-Var upper-air assimilation contains too few observation types to be able to get similar scores as the Open Loop. Adding satellite data, GNSS ZTD data and radar data will probably improve the scores of the 3D-var upper-air assimilation. The advantages of the combination of surface and upper-air assimilation are clear from the improved scores for soil moisture content and relative humidity in the lower parts of the atmosphere, compared to the runs with only surface or upper-air assimilation. As a conclusion for the operational set-up of the RMI it can be said that the surface assimilation runs, and particularly the EKF, are able to get similar or improved scores compared to the current operational initialisation set-up. The 3D-var upper-air assimilation however, should first be improved by using satellite, GNSS and/or radar observations before it can be considered for operational usage

Study of the Jacobian of an extended Kalman filter for soil analysis in SURFEXv5

status: publishe

Region-wide environmental noise monitoring in Flanders through Citizen Science : protocol to integrate surveys and measurements

Within the Program for Innovation Procurement, the Flemish government is investing in innovative methods to answer numerous societal challenges. With support of this program the Department of Environment will develop a region-wide noise monitoring protocol in a two year project, started in April 2023. To achieve this, Ghent University partnered up with Scivil, the knowledge center for Citizen Science in Flanders. The noise monitoring question fits in an environmental noise indicator evaluation designed by the Ghent University in 2019-2020. This manuscript gives an overview of the project outline. We discuss the goals, the methodology, the technical implementation and the dataflow. We explain the strategy to include citizens to achieve both the societal and the scientific goals. Since this is a government funded project, the societal aspects have priority. The first component is the technology: hardware, quality, calibration, noise surveys, event classification, privacy and data storage. The second component is the citizen engagement: how to achieve the data collection at a reasonable cost? The third component is the sampling strategy: how to reach an unbiased dataset for multiple variables: spatial characteristics, sources and population? The last component deals with applications: trends in population exposure and perception. This protocol will provide matched exposure and perception data at an unprecedented scale

Evaluating the performance of SURFEXv5 as a new land surface scheme for the ALADINcy36 and ALARO-0 models

status: publishe

Validation of the ALARO-0 model within the EURO-CORDEX framework

Using the regional climate model ALARO-0, the Royal Meteorological Institute of Belgium and Ghent University have performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979–2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44°. ALARO-0 is characterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989–2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature, some large biases, which are often also found in the ARPEGE results, persist. For precipitation, on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust, meaning independent of the period used to calculate them. Periods of 20 years are sampled from the 32-year simulation and used to construct the 95 % confidence interval for each score. For most scores, these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant