The representation of winds in the lower troposphere in ECMWF forecasts and reanalyses during the EUREC4A field campaign

The characterization of systematic forecast errors in lower-tropospheric winds over the ocean is a primary need for reforming models. Winds are among the drivers of convection, thus an accurate representation of winds is essential for better convective parameterizations. We focus on the temporal variability and vertical distribution of lower-tropospheric wind biases in operational medium-range weather forecasts and ERA5 reanalyses produced with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Thanks to several sensitivity experiments and an unprecedented wealth of measurements from the 2020 EUREC4A field campaign, we show that the wind bias varies greatly from day to day, resulting in RSME's up to 2.5 m s−1, with a mean wind speed bias up to −1 m s−1 near and above the trade-inversion in the forecasts and up to −0.5 m s−1 in reanalyses. The modeled zonal and meridional wind exhibit a too strong diurnal cycle, leading to a weak wind speed bias everywhere up to 5 km during daytime, turning into a too strong wind speed bias below 2 km at nighttime. The biases are fairly insensitive to the assimilation of sondes and likely related to remote convection and large scale pressure gradients. Convective momentum transport acts to distribute biases throughout the lowest 1.5 km, whereas at higher levels, other unresolved or dynamical tendencies play a role in setting the bias. Below 1 km, modelled friction due to unresolved physical processes appears too strong, but is (partially) compensated by dynamical tendencies, making this a challenging coupled problem.

A Relaxed Eddy Accumulation (REA) LOPAP-System for Flux Measurements of Nitrous Acid (HONO)

In the present study a Relaxed Eddy Accumulation (REA) system for the quantification of vertical fluxes of nitrous acid (HONO) was developed and tested. The system is based on a three-channel-LOPAP instrument, for which two channels are used for the updrafts and downdrafts, respectively, and a third one for the correction of chemical interferences. The instrument is coupled to a REA gas inlet, for which an ultrasonic anemometer controls two fast magnetic valves to probe the two channels of the LOPAP instrument depending on the vertical wind direction. A software (PyREA) was developed, which controls the valves and measurement cycles, which regularly alternates between REA-, zero- and parallel ambient measurements. In addition, the assignment of the updrafts and downdrafts to the physical LOPAP channels is periodically alternated, to correct for differences in the interferences of the different air masses. During the study, only small differences of the interferences were identified for the updrafts and downdrafts excluding significant errors when using only one interference channel. In laboratory experiments, high precision of the two channels and the independence of the dilution corrected HONO concentrations on the length of the valve switching periods were demonstrated. A field campaign was performed in order to test the new REA-LOPAP system at the TROPOS monitoring station in Melpitz, Germany. HONO fluxes in the range of −4·1013 molecules m−2 s−1 (deposition) to +1.0·1014 molecules m−2 s−1 (emission) were obtained. A typical diurnal variation of the HONO fluxes was observed with low, partly negative fluxes during night-time and higher positive fluxes around noon. After an intensive rain period the positive HONO emissions during daytime were continuously increasing, which was explained by the drying of the upper most ground surfaces. Similar to other campaigns, the highest correlation of the HONO flux was observed with the product of the NO2 photolysis frequency and the NO2 concentration (J(NO2)·[NO2]), which implies a HONO formation by photosensitized conversion of NO2 on organic surfaces, like e.g. humic acids. Other postulated HONO formation mechanisms are also discussed, but are ranked being of minor importance for the present field campaign.

Role of upwind precipitation in transboundary pollution and secondary aerosol formation: A case study during the KORUS-AQ field campaign

Clouds and precipitation play critical roles in wet removal of aerosols and soluble gases in the atmosphere, and hence their accurate prediction largely influences accurate prediction of air pollutants. In this study, the impacts of clouds and precipitation on wet scavenging and long-range transboundary transport of pollutants are examined during the 2016 Korea-United States Air Quality (KORUS-AQ) field campaign using the Weather Research and Forecasting model coupled with chemistry. Two simulations in which atmospheric moisture is constrained vs. it is not are performed and evaluated against surface and airborne observations. The simulation with moisture constraints is found to better reproduce precipitation as well as surface PM2.5, whereas the areal extent and amount of precipitation are overpredicted in the simulation without moisture constraints. As a results of overpredicted clouds and precipitation and consequently overpredicted wet scavenging, PM2.5 concentration is generally underpredicted across the model domain in the simulation without moisture constraints. The effects are significant not only in the precipitating region (upwind region, southern China in this study) but also in the downwind region (South Korea) where no precipitation is observed. The difference in upwind precipitation by 77% on average between the two simulations leads to the difference in PM2.5 by ∼39% both in the upwind and downwind regions. The transboundary transport of aerosol precursors, especially nitric acid, has a considerable impact on ammonium-nitrate aerosol formation in the ammonia-rich downwind region. This study highlights that skillful prediction of atmospheric moisture can have ultimate potential to skillful prediction of aerosols across regions.

Evaluating daytime planetary boundary-layer height estimations resolved by both active and passive remote sensing instruments during the CHEESEHEAD19 field campaign

During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, held in the summer of 2019 in northern Wisconsin, U.S.A., active and passive ground-based remote sensing instruments were deployed to understand the response of the planetary boundary layer to heterogeneous land surface forcing. These instruments include Radar Wind Profilers, Microwave Radiometers, Atmospheric Emitted Radiance Interferometers, Ceilometers, High Spectral Resolution Lidars, Doppler Lidars, and Collaborative Lower Atmospheric Modelling Profiling Systems that combine several of these instruments. In this study, these ground-based remote sensing instruments are used to estimate the height of the daytime planetary boundary layer, and their performance is compared against independent boundary-layer depth estimates obtained from radiosondes launched as part of the field campaign. The impact of clouds (in particular boundary layer clouds) on boundary-layer depth is also investigated. We found that while overall all instruments are able to provide reasonable boundary-layer depth estimates, each of them shows strengths and weaknesses under certain conditions. For example, Radar Wind Profilers perform well during cloud free conditions, and Microwave Radiometers and Atmospheric Emitted Radiance Interferometers have a very good agreement during all conditions, but are limited by the smoothness of the retrieved thermodynamic profiles. The estimates from Ceilometers and High Spectral Resolution Lidars can be hindered by the presence of elevated aerosol layers or clouds, and the multi-instrument retrieval from the Collaborative Lower Atmospheric Modelling Profiling Systems can be constricted to a limited height range in low aerosol conditions.

Executable books make campaign data tangible

<p>Large field campaigns dedicated to study the earth system are run by large groups of people from many research institutions that are scattered around the globe. That way, it is possible to create a great wealth of original datasets, thoroughly quantifying the state of a specific region in space and time on our planet. All collected data is potentially very useful for model validation, process studies, teaching and more. But while researchers way beyond those participating at the field campaign might be interested in the data, even those participating are often faced by difficulties to discover, access and use the data.</p> <p>To tackle these challenges in the context of the EUREC4A field campaign, we started the „How to EUREC4A“ executable book project. It is an openly accessible online book, written collaboratively by participants from the field campaign and the broader community around. The book contains explanations about the available instruments, data and typical usage patterns. The book is also an executable book, which means that each of the chapters contain explanatory text, code and figures that can be modified by readers, either on their own computer or without any prior setup using an online service called „binder“. Thus, the book also forms a collection of data quicklooks and is an interactive plotting software at the same time.</p> <p>On first sight, the book might seem to be just yet another shiny user interface, similar to other data catalogs. But due to the way it is made, it really becomes the hub of a larger ecosystem. In order to make the book executable by everyone, data must be openly accessible and understandable to everyone, thus the book fosters the creation and maintenance of a comprehensive data catalog and the publication of datasets in an analysis friendly way. Every time the book is executed, we can test if the data is still accessible and still compatible. Furthermore, making beautiful and understandable usage examples for your dataset makes your data visible to a broader community, feels rewarding and motivates others to do the same. As the book lives due to motivated contributors, this creates a positive feedback loop to enlarge the collection of accessible and understandable data.</p>

C³ONTEXT: A Common Consensus on Convective OrgaNizaTion during the EUREC⁴A eXperimenT

The C3ONTEXT (A Common Consensus on Convective OrgaNizaTion during the EUREC4A eXperimenT) dataset is presented as an overview about the meso-scale cloud patterns identified during the EUREC4A field campaign in early 2020. Based on infrared and visible satellite images, 50 researchers of the EUREC4A science team manually identified the four prevailing meso-scale patterns of shallow convection observed by Stevens et al. (2020). The common consensus on the observed meso-scale cloud patterns emerging from these manual classifications is presented. It builds the basis for future studies and reduces the subjective nature of these visually defined cloud patterns. This consensus makes it possible to contextualize the measurements of the EUREC4A field campaign and interpret them in the meso-scale setting. Commonly used approaches to capture the meso-scale patterns are computed for comparison and show good agreement with the manual classifications. All four patterns as classified by Stevens et al. (2020) were present in January–February 2020 although not all were dominant during the observing period of EUREC4A. The full dataset including postprocessed datasets for easier usage are openly available at the Zenodo archive at https://doi. org/10.5281/zenodo.5724585 (Schulz, 2021b).