Four-Dimensional Variational Assimilation of Aerosol Data from In-situ and Remote Sensing Platforms

Die Assimilation von Aerosoldaten war bisher im Wesentlichen auf die Verwendung von Messungen der Gesamtmassenkonzentrationen von Partikeln bis zu einer bestimmten Größe und Messungen von optischer Tiefe beschränkt. Das Chemie-Transport-Modell EURAD-IM des Rheinischen Instituts für Umweltforschung (RIU) enhält ein hochentwickeltes vierdimensionales variationales (4D-var) Assimilationssystem für Gasphasenspezies, das nun um eine teilweise adjungierte Version des Aerosol-modells MADE erweitert wurde, um speziesaufgelöste Aerosolmessungen assimilieren zu können. Vorbereitend wurde bereits der äusserst rechenzeitaufwendige Mechanismus zur Lösung der Chemie der sekundären anorganischen Aerosole innerhalb des MADE mithilfe eines I/O-mapping-Verfahrens ersetzt. Der resultierende Algorithmus wurde nun adjungiert und die Funktionalität des adjungierten Aerosoltransportes sichergestellt. Desweiteren wurden verschiedene Beobachtungsoperatoren entwickelt und gleichzeitig adjungiert. Dazu gehören Integrationsroutinen für Massenkonzentrationen und Anzahldichten. Im Rahmen des AERO-SAM Projektes wurde ein Strahlungstransportmodell, Teil eines Satelliten-Retrieval-Systems, in das Modell eingebaut. Die Besonderheit liegt darin, dass das Modell speziesaufgelöste aerosoloptische Tiefen liefert. Das so konstruierte Aerosolassimilationssystem ist auf zwei Episoden angewandt worden. Als erstes auf den Sommer 2003, als ein langanhaltendes Hochdruckgebiet über Europa lag. Diese Wetterlage begünstigte Waldbrände und brachte stark erhöhte Feinstaubbelastung mit sich. In diesem Zeitraum wurde das neue Assimilationssystem getestet und der Nutzen der Assimilation von PM10 insbesondere von speziesaufgelösten Satellitendaten untersucht. Außerdem wurde die ZEPTER-2 Messkampagne aus dem Herbst 2008 ausgewählt. Ein zur Messplatform umgebauter Zeppelin, der mit einem CPC (Condensation Particle Counter) ausgestattet war, hat räumlich und zeitlich hochaufgelöste Partikelanzahldichten gemessen. In dieser Episode wurde der Fokus auf die Assimilation der Anzahldichten sowie der Leistung des Systems auf Modellgittern mit hoher Auflösung gerichtet. In beiden Fällen wurde Anfangswertoptimierung durchgeführt und das System selbst, sowie das Vermögen, die Vorhersage von Aerosolen zu verbessern, untersucht. Es hat sich herausgstellt, dass sich durch Assimilation von Aerosolen eine deutliche Verbesserung der Vorhersage insgesamt erzielen lässt, während durch die Assimilation speziesaufgelöster Retrievals zusätzlich die Zusammensetzung der Aerosole angepasst werden kann

Automating Wood Species Detection and Classification in Microscopic Images of Fibrous Materials with Deep Learning

We have developed a methodology for the systematic generation of a large image dataset of macerated wood references, which we used to generate image data for nine hardwood genera. This is the basis for a substantial approach to automate, for the first time, the identification of hardwood species in microscopic images of fibrous materials by deep learning. Our methodology includes a flexible pipeline for easy annotation of vessel elements. We compare the performance of different neural network architectures and hyperparameters. Our proposed method performs similarly well to human experts. In the future, this will improve controls on global wood fiber product flows to protect forests

State-of-the-art capabilities in LPJ-GUESS

LPJ-GUESS is an advanced DGVM including detailed forest demography and management, croplands, wetlands, specialised arctic processes, emissions of nonCO2 GHGs and a highly flexible land-use change scheme which tracks transitions between different land-uses. It is the vegetation component of the EC-Earth CMIP6 ESM, the RCA-GUESS regional ESM, and also has a European mode operating at tree species level

A stand-alone tree demography and landscape structure module for Earth system models

We propose and demonstrate a new approach for the simulation of woody ecosystem stand dynamics, demography, and disturbance-mediated heterogeneity suitable for continental to global applications and designed for coupling to the terrestrial ecosystem component of any earth system model. The approach is encoded in a model called Populations-Order-Physiology (POP). We demonstrate the behavior and performance of POP coupled to the Community Atmosphere Biosphere Land Exchange model (CABLE) applied along the Northern Australian Tropical Transect, featuring gradients in rainfall and fire disturbance. The model is able to simultaneously reproduce observation-based estimates of key functional and structural variables along the transect, namely gross primary production, tree foliage projective cover, basal area, and maximum tree height. Prospects for the use of POP to address current vegetation dynamic deficiencies in earth system modeling are discussed

Toward Effective Collaborations between Regional Climate Modeling and Impacts-Relevant Modeling Studies in Polar Regions

What: The aim of this workshop was to discuss the needs and challenges in using high-resolution climate model outputs for impacts-relevant modeling. Development of impacts-relevant climate projections in the polar regions requires effective collaboration between regional climate modelers and impacts-relevant modelers in the design stage of high-resolution climate projections for the polar regions. When: 8 November 2021 Where: Online

Toward Effective Collaborations between Regional Climate Modeling and Impacts-Relevant Modeling Studies in Polar Regions

The aim of this workshop was to discuss the needs and challenges in using high-resolution climate model outputs for impacts-relevant modeling. Development of impacts-relevant climate projections in the polar regions requires effective collabora-tion between regional climate modelers and impacts-relevant modelers in the design stage of high-resolution climate projections for the polar regions

Impact of Changes to the Atmospheric Soluble Iron Deposition Flux on Ocean Biogeochemical Cycles in the Anthropocene

Iron can be a growth‐limiting nutrient for phytoplankton, modifying rates of net primary production, nitrogen fixation, and carbon export ‐ highlighting the importance of new iron inputs from the atmosphere. The bioavailable iron fraction depends on the emission source and the dissolution during transport. The impacts of anthropogenic combustion and land use change on emissions from industrial, domestic, shipping, desert, and wildfire sources suggest that Northern Hemisphere soluble iron deposition has likely been enhanced between 2% and 68% over the Industrial Era. If policy and climate follow the intermediate Representative Concentration Pathway 4.5 trajectory, then results suggest that Southern Ocean (>30°S) soluble iron deposition would be enhanced between 63% and 95% by 2100. Marine net primary productivity and carbon export within the open ocean are most sensitive to changes in soluble iron deposition in the Southern Hemisphere; this is predominantly driven by fire rather than dust iron sources. Changes in iron deposition cause large perturbations to the marine nitrogen cycle, up to 70% increase in denitrification and 15% increase in nitrogen fixation, but only modestly impacts the carbon cycle and atmospheric CO2 concentrations (1–3 ppm). Regionally, primary productivity increases due to increased iron deposition are often compensated by offsetting decreases downstream corresponding to equivalent changes in the rate of phytoplankton macronutrient uptake, particularly in the equatorial Pacific. These effects are weaker in the Southern Ocean, suggesting that changes in iron deposition in this region dominates the global carbon cycle and climate response

The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.Peer reviewe

Inverse Modelling and Combined State-Source Estimation for Chemical Weather

Air quality data assimilation aims to find a best estimate of the control parameters (see theory chapter) for those processes of the atmosphere which govern the chemical evolution of biologically relevant height levels, typically located in the the lowermost atmosphere. As in data assimilation (see theory chapters), we have to resort to numerical models to complement usually sparse observation networks; these models serve as system constraints. Several research groups are developing data assimilation methods similar to those applied to meteorological applications. Techniques range from nudging to advanced spatio-temporal methods such as four-dimensional variational (4D-Var) data assimilation and various simplifications of the Kalman filter (KF)

Fire Dynamics in Boreal Forests Over the 20th Century : A Data-Model Comparison

Fire regimes across the world are expected to be altered by continuing variations in socio-economic conditions and climate. Current global fire-vegetation models are able to represent the present-day fire activity, but it is unclear how well they can simulate past or future scenarios. Here we use sedimentary charcoal-based biomass burning reconstructions to evaluate fire probability and total carbon flux emitted to the atmosphere per year simulated by the dynamic global vegetation model LPJ-GUESS with its incorporated fire model SIMFIRE-BLAZE across the boreal region during the last century. The analyses were run for the whole time period (1900–2000 CE), as well as for the intervals 1900–1950 CE and 1950–2000 CE. The data–model comparison for the 20th century reveals a general disagreement in trends between charcoal reconstructions (with decreasing or stable trends) and simulations (showing an overall increase) at both global (boreal forests) and continental scales (North America and Fennoscandia), as well as for most of the regional sub-areas (Canada, Norway and Sweden). The only exceptions are Alaska and Finland/Russia Karelia, where all the variables increase. Negative correlations between observations and model outputs are also recorded for the two different sub-periods, except for Alaska and North America during the time interval 1900–1950 CE, and Norway and Finland/Russia Karelia between 1950 and 2000 CE. Despite several uncertainties in charcoal records, main differences between modeled and observed fire activity are probably due to limitations in the representation of the human impact on fire regime (especially connected to forest management and landscape fragmentation) in the model simulations