ALBERT

Description: The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

Description: Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s−1).

Description: Methane (CH4) is the second most important greenhouse gas but its emissions from northern regions are still poorly constrained. In this study, we analyze a subset of in situ CH4 aircraft observations made over Alaska during the growing seasons of 2012–2014 as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Net surface CH4 fluxes are estimated using a Lagrangian particle dispersion model which quantitatively links surface emissions from Alaska and the western Yukon with observations of enhanced CH4 in the mixed layer. We estimate that between May and September, net CH4 emissions from the region of interest were 2.2 ± 0.5 Tg, 1.9 ± 0.4 Tg, and 2.3 ± 0.6 Tg of CH4 for 2012, 2013, and 2014, respectively. If emissions are only attributed to two biogenic eco-regions within our domain, then tundra regions were the predominant source, accounting for over half of the overall budget despite only representing 18 % of the total surface area. Boreal regions, which cover a large part of the study region, accounted for the remainder of the emissions. Simple multiple linear regression analysis revealed that, overall, CH4 fluxes were largely driven by soil temperature and elevation. In regions specifically dominated by wetlands, soil temperature and moisture at 10 cm depth were important explanatory variables while in regions that were not wetlands, soil temperature and moisture at 40 cm depth were more important, suggesting deeper methanogenesis in drier soils. Although similar environmental drivers have been found in the past to control CH4 emissions at local scales, this study shows that they can be used to generate a statistical model to estimate the regional-scale net CH4 budget.

Description: We provide atmospheric temperature variability indices for the tropical troposphere and stratosphere based on global navigation satellite system (GNSS) radio occultation (RO) temperature measurements. By exploiting the high vertical resolution and the uniform distribution of the GNSS RO temperature soundings we introduce two approaches, both based on an empirical orthogonal function (EOF) analysis. The first method utilizes the whole vertical and horizontal RO temperature field from 30∘ S to 30∘ N and from 2 to 35 km altitude. The resulting indices, the leading principal components, resemble the well-known patterns of the Quasi-Biennial Oscillation (QBO) and the El Niño–Southern Oscillation (ENSO) in the tropics. They provide some information on the vertical structure; however, they are not vertically resolved. The second method applies the EOF analysis on each altitude level separately and the resulting indices contain information on the horizontal variability at each densely available altitude level. They capture more variability than the indices from the first method and present a mixture of all variability modes contributing at the respective altitude level, including the QBO and ENSO. Compared to commonly used variability indices from QBO winds or ENSO sea surface temperature, these new indices cover the vertical details of the atmospheric variability. Using them as proxies for temperature variability is also of advantage because there is no further need to account for response time lags. Atmospheric variability indices as novel products from RO are expected to be of great benefit for studies on atmospheric dynamics and variability, for climate trend analysis, as well as for climate model evaluation.

Description: Atmospheric blocking represents a weather pattern where a stationary high-pressure system weakens or reverses the climatological westerly flow at mid-latitudes for up to several weeks. It is closely connected to strong anomalies in key atmospheric variables such as geopotential height, temperature, and humidity. Here we provide, for the first time, a comprehensive, global perspective on atmospheric blocking and related impacts by using an observation-based data set from Global Positioning System (GPS) radio occultation (RO) from 2006 to 2016. The main blocking regions in both hemispheres and seasonal variations are found to be represented well in RO data. The effect of blocking on vertically resolved temperature and humidity anomalies in the troposphere and lower stratosphere is investigated for blocking regions in the Northern and Southern hemispheres, respectively. We find a statistically significant correlation of blocking with positive temperature anomalies, exceeding 3 K in the troposphere, and a reversal above the tropopause with negative temperature anomalies below −3 K in the lower stratosphere. Specific humidity is positively correlated with temperature throughout the troposphere with larger anomalies revealed in the Southern Hemisphere. At the eastern and equatorward side of the investigated blocking regions, a band of tropospheric cold anomalies reveals advection of cold air by anticyclonic motion around blocking highs, which is less distinct in the Southern Hemisphere due to stronger zonal flow. We find GPS RO to be a promising new data set for blocking research that gives insight into the vertical atmospheric structure, especially in light of the expected increase in data coverage that future missions will provide.

Description: The demand for high-quality atmospheric data records, which are applicable in climate studies, is undisputed. Using such records requires knowledge of the quality and the specific characteristics of all contained data sources. The latest version of the Wegener Center (WEGC) multi-satellite Global Positioning System (GPS) radio occultation (RO) record, OPSv5.6, provides globally distributed upper-air satellite data of high quality, usable for climate and other high-accuracy applications. The GPS RO technique has been deployed in several satellite missions since 2001. Consistency among data from these missions is essential to create a homogeneous long-term multi-satellite climate record. In order to enable a qualified usage of the WEGC OPSv5.6 data set we performed a detailed analysis of satellite-dependent quality aspects from 2001 to 2017. We present the impact of the OPSv5.6 quality control on the processed data and reveal time-dependent and satellite-specific quality characteristics. The highest quality data are found for MetOp (Meteorological Operational satellite) and GRACE (Gravity Recovery and Climate Experiment). Data from FORMOSAT-3/COSMIC (Formosa Satellite mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate) are also of high quality. However, comparatively large day-to-day variations and satellite-dependent irregularities need to be taken into account when using these data. We validate the consistency among the various satellite missions by calculating monthly mean temperature deviations from the multi-satellite mean, including a correction for the different sampling characteristics. The results are highly consistent in the altitude range from 8 to 25 km, with mean temperature deviations less than 0.1 K. At higher altitudes the OPSv5.6 RO temperature record is increasingly influenced by the characteristics of the bending angle initialization, with the amount of impact depending on the receiver quality.

Description: It was recently shown by the CERN CLOUD experiment that biogenic highly oxygenated molecules (HOMs) form particles under atmospheric conditions in the absence of sulfuric acid, where ions enhance the nucleation rate by 1–2 orders of magnitude. The biogenic HOMs were produced from ozonolysis of α-pinene at 5 ∘C. Here we extend this study to compare the molecular composition of positive and negative HOM clusters measured with atmospheric pressure interface time-of-flight mass spectrometers (APi-TOFs), at three different temperatures (25, 5 and −25 ∘C). Most negative HOM clusters include a nitrate (NO3-) ion, and the spectra are similar to those seen in the nighttime boreal forest. On the other hand, most positive HOM clusters include an ammonium (NH4+) ion, and the spectra are characterized by mass bands that differ in their molecular weight by ∼ 20 C atoms, corresponding to HOM dimers. At lower temperatures the average oxygen to carbon (O : C) ratio of the HOM clusters decreases for both polarities, reflecting an overall reduction of HOM formation with decreasing temperature. This indicates a decrease in the rate of autoxidation with temperature due to a rather high activation energy as has previously been determined by quantum chemical calculations. Furthermore, at the lowest temperature (−25 ∘C), the presence of C30 clusters shows that HOM monomers start to contribute to the nucleation of positive clusters. These experimental findings are supported by quantum chemical calculations of the binding energies of representative neutral and charged clusters.

Description: High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

Description: We investigate the sensitivity of aerosol representation in the regional climate model RegCM4 for two dust parameterizations for the period 2007–2014 over the Sahara and the Mediterranean. We apply two discretization methods of the dust size distribution keeping the total mass constant: (1) the default RegCM4 4-bin approach, where the size range of each bin is calculated using an equal, logarithmic separation of the total size range of dust, using the diameter of dust particles, and (2) a newly implemented 12-bin approach with each bin defined according to an isogradient method where the size ranges are dependent on the dry deposition velocity of dust particles. Increasing the number of transported dust size bins theoretically improves the representation of the physical properties of dust particles within the same size bin. Thus, more size bins improve the simulation of atmospheric processes. The radiative effects of dust over the area are discussed and evaluated with the CALIPSO dust optical depth (DOD). This study is among the first studies evaluating the vertical profile of simulated dust with a pure dust product. Reanalysis winds from ERA-Interim and the total precipitation flux from the Climate Research Unit (CRU) observational gridded database are used to evaluate and explain the discrepancies between model and observations. The new dust binning approach increases the dust column burden by 4 and 3 % for fine and coarse particles, respectively, which increases DOD by 10 % over the desert and the Mediterranean. Consequently, negative shortwave radiative forcing (RF) is enhanced by more than 10 % at the top of the atmosphere and by 1 to 5 % on the surface. Positive longwave RF locally increases by more than 0.1 W m−2 in a large portion of the Sahara, the northern part of the Arabian Peninsula and the Middle East. The four-bin isolog method is to some extent numerically efficient, nevertheless our work highlights that the simplified representation of the four-bin approach produces less dust optical depth and RF, a fact that should be taken into account by future studies of the same region.

Description: Measurements of aerosol dynamics in the sub-10 nm size range are crucially important for quantifying the impact of new particle formation onto the global budget of cloud condensation nuclei. Here we present the development and characterization of a differential mobility analyzer train (DMA-train), operating six DMAs in parallel for high-time-resolution particle-size-distribution measurements below 10 nm. The DMAs are operated at six different but fixed voltages and hence sizes, together with six state-of-the-art condensation particle counters (CPCs). Two Airmodus A10 particle size magnifiers (PSM) are used for channels below 2.5 nm while sizes above 2.5 nm are detected by TSI 3776 butanol-based or TSI 3788 water-based CPCs. We report the transfer functions and characteristics of six identical Grimm S-DMAs as well as the calibration of a butanol-based TSI model 3776 CPC, a water-based TSI model 3788 CPC and an Airmodus A10 PSM. We find cutoff diameters similar to those reported in the literature. The performance of the DMA-train is tested with a rapidly changing aerosol of a tungsten oxide particle generator during warmup. Additionally we report a measurement of new particle formation taken during a nucleation event in the CLOUD chamber experiment at CERN. We find that the DMA-train is able to bridge the gap between currently well-established measurement techniques in the cluster–particle transition regime, providing high time resolution and accurate size information of neutral and charged particles even at atmospheric particle concentrations.