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Abstract Smoldering multiple myeloma (SMM) precedes multiple myeloma (MM). The risk of progression of SMM patients is not uniform, thus different progression-risk models have been developed, although they are mainly based on clinical parameters. Recently, genomic predictors of progression have been defined for untreated SMM. However, the usefulness of such markers in the context of clinical trials evaluating upfront treatment in high-risk SMM (HR SMM) has not been explored yet, precluding the identification of baseline genomic alterations leading to drug resistance. For this reason, we carried out next-generation sequencing and fluorescent in-situ hybridization studies on 57 HR and ultra-high risk (UHR) SMM patients treated in the phase II GEM-CESAR clinical trial (NCT02415413). DIS3, FAM46C, and FGFR3 mutations, as well as t(4;14) and 1q alterations, were enriched in HR SMM. TRAF3 mutations were specifically associated with UHR SMM but identified cases with improved outcomes. Importantly, novel potential predictors of treatment resistance were identified: NRAS mutations and the co-occurrence of t(4;14) plus FGFR3 mutations were associated with an increased risk of biological progression. In conclusion, we have carried out for the first time a molecular characterization of HR SMM patients treated with an intensive regimen, identifying genomic predictors of poor outcomes in this setting.

Objectives: Radiation-induced dermatitis (RD) is one of the most common toxicities in radiation therapy (RT) patients. Corticosteroids, immunosuppressants, and natural products (NPs) have been used as treatment. The objective was to evaluate the efficacy of a NPs-based cream (Alantel®) to reduce the incidence of RD in women with breast cancer undergoing RT treatment. Design: We conducted a controlled, randomized, double-blind clinical trial. Setting: Radiation Oncology Unit of the Reina Sofía Hospital and 5 Primary Care centers of the Cordoba and Guadalquivir Health District (Spain). Interventions: Patients assigned to the experimental group (GTA) were treated with Alantel, while those in the control group (GTE) were treated with a moisturizer and emollient cream. Main outcome measures: The primary outcome variable was the incidence of RD. RD-free time, duration of RD, quality of life, and product safety were also assessed. Results: Seventy patients were included in the study, 35 in the GTA and 35 in the GTE. The incidence of RD was lower in the GTA (71.4%) than in the GTE (91.4%) after 4 weeks of follow-up (RR = 0.78; NNT = 5; p

The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90∘ N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from >50 Mm−1 close to the surface to Mm−1 at 4–6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm−1, were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1–2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50–500 cm−3 in winter to 10–100 cm−3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm−3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June–August). The strong winter vs. summer contrast in the INP number concentration by roughly 2–3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020.

A record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019–May 2020) and over Punta Arenas in southern Chile at 53.2∘ S (January 2020–November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10–12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10–12 km, smoke particle surface area (SA) concentrations of 5–7 µm2 cm−3 (Antarctica, spring 2021) and 6–10 µm2 cm−3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4–1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2–3.5 mPa (Arctic, 20 %–30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1–2 mPa (10 %–20 % contribution to the total ozone loss over Antarctica) was observed in the 14–23 km PSC height range in September–October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm−3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26–30 Dobson units (9 %–10 %, September 2020, 2021) and 52–57 Dobson units (17 %–20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70–80∘ S.

Record-breaking wildfires raged in southeastern Australia in late December 2019 and early January 2020. Rather strong pyrocumulonimbus (pyroCb) convection developed over the fire areas and lofted enormous amounts of biomass burning smoke into the tropopause region and caused the strongest wildfire-related stratospheric aerosol perturbation ever observed around the globe. We discuss the geometrical, optical, and microphysical properties of the stratospheric smoke layers and the decay of this major stratospheric perturbation. A multiwavelength polarization Raman lidar at Punta Arenas (53.2∘ S, 70.9∘ W), southern Chile, and an elastic backscatter Raman lidar at Río Grande (53.8∘ S, 67.7∘ W) in southern Argentina, were operated to monitor the major record-breaking event until the end of 2021. These lidar measurements can be regarded as representative for mid to high latitudes in the Southern Hemisphere. A unique dynamical feature, an anticyclonic, smoke-filled vortex with 1000 km horizontal width and 5 km vertical extent, which ascended by about 500 m d−1, was observed over the full last week of January 2020. The key results of the long-term study are as follows. The smoke layers extended, on average, from 9 to 24 km in height. The smoke partly ascended to more than 30 km height as a result of self-lofting processes. Clear signs of a smoke impact on the record-breaking ozone hole over Antarctica in September–November 2020 were found. A slow decay of the stratospheric perturbation detected by means of the 532 nm aerosol optical thickness (AOT) yielded an e-folding decay time of 19–20 months. The maximum smoke AOT was around 1.0 over Punta Arenas in January 2020 and thus 2 to 3 orders of magnitude above the stratospheric aerosol background of 0.005. After 2 months with strongly varying smoke conditions, the 532 nm AOT decreased to 0.03-0.06 from March–December 2020 and to 0.015–0.03 throughout 2021. The particle extinction coefficients at 532 nm were in the range of 10–75 Mm−1 in January 2020 and, later on, mostly between 1 and 5 Mm−1. Combined lidar–photometer retrievals revealed typical smoke extinction-to-backscatter ratios of 69 ± 19 sr (at 355 nm), 91 ± 17 sr (at 532 nm), and 120 ± 22 sr (at 1064 nm). An ozone reduction of 20 %–25 % in the 15–22 km height range was observed over Antarctica and New Zealand ozonesonde stations in the smoke-polluted air, with particle surface area concentrations of 1–5 µm2 cm−3.

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition to continuously monitor aerosol and cloud layers in the central Arctic up to 30 km height. The expedition lasted from September 2019 to October 2020 and measurements were mostly taken between 85 and 88.5∘ N. The lidar was integrated into a complex remote-sensing infrastructure aboard the Polarstern. In this article, novel lidar techniques, innovative concepts to study aerosol–cloud interaction in the Arctic, and unique MOSAiC findings will be presented. The highlight of the lidar measurements was the detection of a 10 km deep wildfire smoke layer over the North Pole region between 7–8 km and 17–18 km height with an aerosol optical thickness (AOT) at 532 nm of around 0.1 (in October–November 2019) and 0.05 from December to March. The dual-wavelength Raman lidar technique allowed us to unambiguously identify smoke as the dominating aerosol type in the aerosol layer in the upper troposphere and lower stratosphere (UTLS). An additional contribution to the 532 nm AOT by volcanic sulfate aerosol (Raikoke eruption) was estimated to always be lower than 15 %. The optical and microphysical properties of the UTLS smoke layer are presented in an accompanying paper (Ohneiser et al., 2021). This smoke event offered the unique opportunity to study the influence of organic aerosol particles (serving as ice-nucleating particles, INPs) on cirrus formation in the upper troposphere. An example of a closure study is presented to explain our concept of investigating aerosol–cloud interaction in this field. The smoke particles were obviously able to control the evolution of the cirrus system and caused low ice crystal number concentration. After the discussion of two typical Arctic haze events, we present a case study of the evolution of a long-lasting mixed-phase cloud layer embedded in Arctic haze in the free troposphere. The recently introduced dual-field-of-view polarization lidar technique was applied, for the first time, to mixed-phase cloud observations in order to determine the microphysical properties of the water droplets. The mixed-phase cloud closure experiment (based on combined lidar and radar observations) indicated that the observed aerosol levels controlled the number concentrations of nucleated droplets and ice crystals.

Abstract Long‐term satellite land surface temperature (LST) data are desirable to augment 2m air temperatures (T2m) measured in situ and as an independent measure of surface temperature change. However, previous studies show variable agreement between LST and T2m time series. The objective of this study is to assess the stability and trends in six new LST data sets from the European Space Agency's Climate Change Initiative for LST (LST_cci). LST anomalies are compared with homogenized station T2m anomalies over Europe, which verifies all six data sets are well coupled (LST vs T2m anomaly correlations and slopes: 0.6–0.9). The temporal stability of the LST_cci data is assessed through a comparison with the T2m anomaly time series. Only the LST_cci data sets for the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Advanced Along‐Track Scanning Radiometer (AATSR) appear stable; the MODIS/Terra, ATSR‐2, and multisensor InfraRed and MicroWave data sets show non‐climatic discontinuities associated with changes in sensor and/or drift over time. For MODIS/Aqua (2002–2018), significant trends in LST of 0.64–0.66 K/decade compare well with the equivalent T2m trends of 0.52–0.59 K/decade. The LST and T2m trends for AATSR (2002–2012) are found to be statistically insignificant, likely due to the comparatively short study period and specific years available for analysis. No evidence is found to suggest that trends calculated using cloud‐free InfraRed observations are affected by clear‐sky bias. This study suggests that satellite LST data can be used to assess warming trends over land and for other climate applications if the required homogeneity is assured.

We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January–February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system.

The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority missions for the expansion of the Copernicus program within the European Space Agency (ESA). It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precision, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities. In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels. The famous figure from Wilheit (1979), describing the frequency sensitivity of passive microwave satellite observations to ocean parameters, has been extensively used for channel selection of microwave radiometer frequencies on board oceanic satellite missions. Here, we propose to update this sensitivity analysis, using state-of-the-art radiative transfer simulations for different geophysical conditions (Arctic, mid-latitude, tropics). We used the Radiative Transfer Model (RTM) from Meissner and Wentz (2012) for the ocean surface, the Round Robin Data Package of the ESA Climate Change Initiative (Pedersen et al., 2019) for the sea ice, and the RTM from Rosenkranz (2017) for the atmosphere. The sensitivities of the brightness temperatures (TBs) observed by CIMR as a function of sea surface temperature (SST), sea surface salinity (SSS), sea ice concentration (SIC), ocean wind speed (OWS), total column water vapor (TCWV), and total column liquid water (TCLW) are presented as a function of frequency between 1 and 40 GHz. The analysis underlines the difficulty to reach the user requirements with single-channel retrieval, especially under cold ocean conditions. With simultaneous measurements between 1.4 and 36 GHz onboard CIMR, applying multi-channel algorithms will be facilitated, to provide the user community with the required ocean and ice information under arctic environments.

In a companion article (Jimenez et al., 2020), we introduced a new lidar method to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration Nd) at a height of 50–100 m above the cloud base together with aerosol information (aerosol extinction coefficients, cloud condensation nuclei concentration NCCN) below the cloud layer so that detailed studies of the influence of given aerosol conditions on the evolution of liquid-water cloud layers with high temporal resolution solely based on lidar observations have become possible now. The novel cloud retrieval technique makes use of lidar observations of the volume linear depolarization ratio at two different receiver field of views (FOVs). In this article, Part 2, the new dual-FOV polarization lidar technique is applied to cloud measurements in pristine marine conditions at Punta Arenas in southern Chile. A multiwavelength polarization Raman lidar, upgraded by integrating a second polarization-sensitive channel to permit depolarization ratio observations at two FOVs, was used for these measurements at the southernmost tip of South America. Two case studies are presented to demonstrate the potential of the new lidar technique. Successful aerosol–cloud-interaction (ACI) studies based on measurements with the upgraded aerosol–cloud lidar in combination with a Doppler lidar of the vertical wind component could be carried out with 1 min temporal resolution at these pristine conditions. In a stratocumulus layer at the top of the convective boundary layer, we found values of Nd and NCCN (for 0.2 % water supersaturation) ranging from 15–100 and 75–200 cm−3, respectively, during updraft periods. The studies of the aerosol impact on cloud properties yielded ACI values close to 1. The impact of aerosol water uptake on the ACI studies was analyzed with the result that the highest ACI values were obtained when considering aerosol proxies (light-extinction coefficient αpar or NCCN) measured at heights about 500 m below the cloud base (and thus for dry aerosol conditions).

In a series of two articles, a novel, robust, and practicable lidar approach is presented that allows us to derive microphysical properties of liquid-water clouds (cloud extinction coefficient, droplet effective radius, liquid-water content, cloud droplet number concentration) at a height of 50–100 m above the cloud base. The temporal resolution of the observations is on the order of 30–120 s. Together with the aerosol information (aerosol extinction coefficients, cloud condensation nucleus concentration) below the cloud layer, obtained with the same lidar, in-depth aerosol–cloud interaction studies can be performed. The theoretical background and the methodology of the new cloud lidar technique is outlined in this article (Part 1), and measurement applications are presented in a companion publication (Part 2) (Jimenez et al., 2020a). The novel cloud retrieval technique is based on lidar observations of the volume linear depolarization ratio at two different receiver fields of view (FOVs). Extensive simulations of lidar returns in the multiple scattering regime were conducted to investigate the capabilities of a dual-FOV polarization lidar to measure cloud properties and to quantify the information content in the measured depolarization features regarding the basic retrieval parameters (cloud extinction coefficient, droplet effective radius). Key simulation results and the overall data analysis scheme developed to obtain the aerosol and cloud products are presented.

Microwave remote sensing can be used to monitor the time evolution of some key parameters over land, such as land surface temperature or surface water extent. Observations are made with instruments, such as the Scanning Microwave Multichannel Radiometer (SMMR) before 1987, the Special Sensor Microwave/Imager (SSM/I) and the subsequent Special Sensor Microwave Imager/Sounder (SSMIS) from 1987 and still operating, and the more recent Global Precipitation Measurement Microwave Imager (GMI). As these instruments differ on some of their characteristics and use different calibration schemes, they need to be inter-calibrated before long-time-series products can be derived from the observations. Here an inter-calibration method is designed to remove major inconsistencies between the SMMR and other microwave radiometers for the 18 and 37 GHz channels over continental surfaces. Because of a small overlap in observations and a ∼6 h difference in overpassing times between SMMR and SSM/I, GMI was chosen as a reference despite the lack of a common observing period. The diurnal cycles from 3 years of GMI brightness temperatures are first calculated and then used to evaluate SMMR differences. Based on a statistical analysis of the differences, a simple linear correction is implemented to calibrate SMMR on GMI. This correction is shown to also reduce the biases between SMMR and SSM/I, and can then be applied to SMMR observations to make them more coherent with existing data records of microwave brightness temperatures over continental surfaces.

We present particle optical properties of stratospheric smoke layers observed with multiwavelength polarization Raman lidar over Punta Arenas (53.2∘ S, 70.9∘ W), Chile, at the southernmost tip of South America in January 2020. The smoke originated from the record-breaking bushfires in Australia. The stratospheric aerosol optical thickness reached values up to 0.85 at 532 nm in mid-January 2020. The main goal of this rapid communication letter is to provide first stratospheric measurements of smoke extinction-to-backscatter ratios (lidar ratios) and particle linear depolarization ratios at 355 and 532 nm wavelengths. These aerosol parameters are important input parameters in the analysis of spaceborne CALIPSO and Aeolus lidar observations of the Australian smoke spreading over large parts of the Southern Hemisphere in January and February 2020 up to heights of around 30 km. Lidar and depolarization ratios, simultaneously measured at 355 and 532 nm, are of key importance regarding the homogenization of the overall Aeolus (355 nm wavelength) and CALIPSO (532 nm wavelength) lidar data sets documenting the spread of the smoke and the decay of the stratospheric perturbation, which will be observable over the entire year of 2020. We found typical values and spectral dependencies of the lidar ratio and linear depolarization ratio for aged stratospheric smoke. At 355 nm, the lidar ratio and depolarization ratio ranged from 53 to 97 sr (mean 71 sr) and 0.2 to 0.26 (mean 0.23), respectively. At 532 nm, the lidar ratios were higher (75–112 sr, mean 97 sr) and the depolarization ratios were lower with values of 0.14–0.22 (mean 0.18). The determined depolarization ratios for aged Australian smoke are in very good agreement with respective ones for aged Canadian smoke, observed with lidar in stratospheric smoke layers over central Europe in the summer of 2017. The much higher 532 nm lidar ratios, however, indicate stronger absorption by the Australian smoke particles.

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m−2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m−2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m−2.

Supernovae (SNe) that have been multiply imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply imaged Type Ia SN 2022qmx (aka, “SN Zwicky”) at z = 0.3544. SN Zwicky was discovered by the Zwicky Transient Facility in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multicycle “LensWatch ( http://www.lenswatch.org )” program. We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, and F814W) but unresolved with WFC3/IR F160W, and present an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between lens-model-predicted time delays (≲1 day), and delays estimated with the single epoch of Hubble Space Telescope colors (≲3.5 days), including the uncertainty from chromatic microlensing (∼1–1.5 days). Our lens models converge to an Einstein radius of ${\theta }_{{\rm{E}}}=({0.168}_{-0.005}^{+0.009})^{\prime\prime} $ , the smallest yet seen in a lensed SN system. The “standard candle” nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter than predicted by $\sim {1.7}_{-0.6}^{+0.8}$ mag and $\sim {0.9}_{-0.6}^{+0.8}$ mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

A shipborne Sun–sky–lunar photometer of type CE318-T was tested during two trans-Atlantic cruises aboard the German research vessel Polarstern from 54∘ N to 54∘ S in May/June and December 2018. The continuous observations of the motion-stabilized shipborne CE318-T enabled the first-time observation of a full diurnal cycle of aerosol optical depth (AOD) and column-mean Ångström coefficient of a mixed dust–smoke episode. The latitudinal distribution of the AOD from the shipborne CE318-T, Raman lidar and MICROTOPS II shows the same trend with highest values in the dust belt from 0 to 20∘ N and overall low values in the Southern Hemisphere. The linear-regression coefficients of determination between MICROTOPS II and the CE318-T were 0.988, 0.987, 0.994 and 0.994 for AODs at 380, 440, 500 and 870 nm and 0.896 for the Ångström exponent at 440–870 nm. The root-mean-squared differences of AOD at 380, 440, 500 and 870 nm were 0.015, 0.013, 0.010 and 0.009, respectively.

Remotely sensed brightness temperatures from passive observations in the microwave (MW) range are used to retrieve various geophysical parameters, e.g. near-surface temperature. Cloud contamination, although less of an issue at MW than at visible to infrared wavelengths, may adversely affect retrieval quality, particularly in the presence of strong cloud formation (convective towers) or precipitation. To limit errors associated with cloud contamination, we present an index derived from stand-alone MW brightness temperature observations, which measure the probability of residual cloud contamination. The method uses a statistical neural network model trained with the Global Precipitation Microwave Imager (GMI) observations and a cloud classification from Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). This index is available over land and ocean and is developed for multiple frequency ranges to be applicable to successive generations of MW imagers. The index confidence increases with the number of available frequencies and performs better over the ocean, as expected. In all cases, even for the more challenging radiometric signatures over land, the model reaches an accuracy of ≥70 % in detecting contaminated observations. Finally an application of this index is shown that eliminates grid cells unsuitable for land surface temperature estimation.

We present a new formalism to calibrate a three-signal polarization lidar and to measure highly accurate height profiles of the volume linear depolarization ratios under realistic experimental conditions. The methodology considers elliptically polarized laser light, angular misalignment of the receiver unit with respect to the main polarization plane of the laser pulses, and cross talk among the receiver channels. A case study of a liquid-water cloud observation demonstrates the potential of the new technique. Long-term observations of the calibration parameters corroborate the robustness of the method and the long-term stability of the three-signal polarization lidar. A comparison with a second polarization lidar shows excellent agreement regarding the derived volume linear polarization ratios in different scenarios: a biomass burning smoke event throughout the troposphere and the lower stratosphere up to 16 km in height, a dust case, and also a cirrus cloud case.

We present spectrally resolved optical and microphysical properties of western Canadian wildfire smoke observed in a tropospheric layer from 5–6.5 km height and in a stratospheric layer from 15–16 km height during a record-breaking smoke event on 22 August 2017. Three polarization/Raman lidars were run at the European Aerosol Research Lidar Network (EARLINET) station of Leipzig, Germany, after sunset on 22 August. For the first time, the linear depolarization ratio and extinction-to-backscatter ratio (lidar ratio) of aged smoke particles were measured at all three important lidar wavelengths of 355, 532, and 1064 nm. Very different particle depolarization ratios were found in the troposphere and in the stratosphere. The obviously compact and spherical tropospheric smoke particles caused almost no depolarization of backscattered laser radiation at all three wavelengths ( 500 nm). The stratospheric smoke particles formed a pronounced accumulation mode (in terms of particle volume or mass) centered at a particle radius of 350–400 nm. The effective particle radius was 0.32 µm. The tropospheric smoke particles were much smaller (effective radius of 0.17 µm). Mass concentrations were of the order of 5.5 µg m−3 (tropospheric layer) and 40 µg m−3 (stratospheric layer) in the night of 22 August 2017. The single scattering albedo of the stratospheric particles was estimated to be 0.74, 0.8, and 0.83 at 355, 532, and 1064 nm, respectively.

We present the design of a porous-core PCF with elliptical holes in the core that achieved low loss, high birefringence, and flattened dispersion for guiding terahertz waves. The finite element method is used to study the properties of the designed waveguide in detail: effective material loss, birefringence, confinement losses, and dispersion. Simulation results show that the proposed structure exhibits simultaneously high modal birefringence of 1.32 × 10-2 and a flattened dispersion over a broadband of 1.28 THz. Then, polarization splitters, based on both symmetric and asymmetric porous-core PCF structures, are designed and evaluated at 1 THz. We show that this kind of device exhibits a strong polarization-dependent coupling behavior. Numerical results show that the configuration based on dual-core waveguide with asymmetric cores can achieve a 10.9 cm long splitter with a broadband of 0.306 THz for x -polarization and 0.23 THz for y-polarization. Finally, this paper offers an effective method to design an ultrawideband polarization beam splitter to operate in the THz region, which might be relevant for future applications in technical areas, such as spectroscopy, sensing, and high-speed data transmission.

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m−2; 0.65), followed closely by GLEAM (0.68; 64 W m−2; 0.62), with values in parentheses representing the R2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m−2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m−2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Challenges related to the robust assessment of the LandFlux product are also discussed.

The search for food resources is a constant in human history. Nowadays, the search for natural and safe food supplies is of foremost importance. Accordingly, there is a renewed interest in eco-friendly and natural products for substitution of synthetic additives. In addition, microbial contamination of food products during their obtaining and distribution processes is still a sanitary issue, and an important target for the food industry is to avoid food contamination and its related foodborne illnesses. These diseases are fundamentally caused by certain microorganisms listed in this review and classified according to their Gram negative or positive character. Algae have proven to possess high nutritional value and a wide variety of biological properties due to their content in active compounds. Among these capabilities, macroalgae are recognized for having antimicrobial properties. Thus, the present paper revises the actual knowledge of microbial contaminants in the food industry and proposes antimicrobial algal compounds against those pathogenic bacteria responsible for food contamination as valuable molecules for its growth inhibition. The capacity of algae extracts to inhibit some major food pathogen growth was assessed. Moreover, the main applications of these compounds in the food industry were discussed while considering their favorable effects in terms of food safety and quality control.

Microwave passive and active radiative transfer simulations are performed with the Atmospheric Radiative Transfer Simulator (ARTS) for a mid-latitude snowfall event, using outputs from the Meso-NH mesoscale cloud model. The results are compared to the corresponding microwave observations available from MHS and CloudSat. The spatial structures of the simulated and observed brightness temperatures show an overall agreement since the large-scale dynamical structure of the cloud system is reasonably well captured by Meso-NH. However, with the initial assumptions on the single-scattering properties of snow, there is an obvious underestimation of the strong scattering observed in regions with large frozen hydrometeor quantities. A sensitivity analysis of both active and passive simulations to the microphysical parametrizations is conducted. Simultaneous analysis of passive and active calculations provides strong constraints on the assumptions made to simulate the observations. Good agreements are obtained with both MHS and CloudSat observations when the single-scattering properties are calculated using the "soft sphere" parametrization from Liu (2004), along with the Meso-NH outputs. This is an important step toward building a robust data set of simulated measurements to train a statistically based retrieval scheme.

Gasoline, which currently presents a well-developed distribution network, represents an ideal fuel source for H2 production onboard or in stationary facilities. In this work, a novel alumina supported Ni (NiAl2O4/Al2O3) catalyst derived from the reduction of nickel aluminate at high temperature was investigated for the partial oxidation of isooctane, which was selected as a gasoline surrogate. While being relatively active in the process due to its small crystallite size, the catalyst did not show a stable behavior with time on stream since a considerably coke formation was noticed. Interestingly a better performance in terms of conversion, yield of hydrogen and stability was observed when water was added to the feedstream.

This work was focused on the study of the catalytic behaviour of nickel aluminate supported either on ceria or ceria-zirconia (NiAl2O4/CexZr1-xO2, x= 0.13 and 1, 14 wt.% Ni) for the steam reforming and partial oxidation of methane. Activity results revealed that these catalytic formulations showed a notable performance for POM under stoichiometric conditions (molar ratio O/C = 1), irrespective of the composition of the support. However, under more severe reforming conditions (O/C = 0.8) NiAl2O4/CeO2 was the optimal catalyst as its marked reducibility helped in minimising the negative effect of coking. Conversely, the NiAl2O4/Ce0.13Zr0.87O2 sample was the most efficient system for SRM due to its high hydrothermal stability.

Land evapotranspiration (ET) estimates are available from several global data sets. Here, monthly global land ET synthesis products, merged from these individual data sets over the time periods 1989–1995 (7 yr) and 1989–2005 (17 yr), are presented. The merged synthesis products over the shorter period are based on a total of 40 distinct data sets while those over the longer period are based on a total of 14 data sets. In the individual data sets, ET is derived from satellite and/or in situ observations (diagnostic data sets) or calculated via land-surface models (LSMs) driven with observations-based forcing or output from atmospheric reanalyses. Statistics for four merged synthesis products are provided, one including all data sets and three including only data sets from one category each (diagnostic, LSMs, and reanalyses). The multi-annual variations of ET in the merged synthesis products display realistic responses. They are also consistent with previous findings of a global increase in ET between 1989 and 1997 (0.13 mm yr−2 in our merged product) followed by a significant decrease in this trend (−0.18 mm yr−2), although these trends are relatively small compared to the uncertainty of absolute ET values. The global mean ET from the merged synthesis products (based on all data sets) is 493 mm yr−1 (1.35 mm d−1) for both the 1989–1995 and 1989–2005 products, which is relatively low compared to previously published estimates. We estimate global runoff (precipitation minus ET) to 263 mm yr−1 (34 406 km3 yr−1) for a total land area of 130 922 000 km2. Precipitation, being an important driving factor and input to most simulated ET data sets, presents uncertainties between single data sets as large as those in the ET estimates. In order to reduce uncertainties in current ET products, improving the accuracy of the input variables, especially precipitation, as well as the parameterizations of ET, are crucial.

On 27 February 2010, a megathrust earthquake of Mw = 8.8 generated a destructive tsunami in Chile. It struck not only Chilean coast but propagated all the way to Japan. After the event occurred, the post-tsunami survey team was assembled, funded by the Japan Science and Technology Agency (JST), to survey the area severely affected by the tsunami. The tsunami damaged and destroyed numerous houses, especially in the town of Dichato. In order to estimate the structural fragility against tsunami hazard in this area, tsunami fragility curves were developed. Surveyed data of inundation depth and visual inspection of satellite images of Dichato were used to classify the damage to housing. A practical method suitable when there are limitations on available data for numerical simulation or damage evaluation from surveys is presented here. This study is the first application of tsunami fragility curves on the South American Pacific coast and it might be of practical use for communities with similar characteristics along the west Pacific coast. The proposed curve suggests that structures in Dichato will be severely damaged – with a 68% probability – already at 2 m tsunami inundation depth.

El terremoto de Bolivia de 1994, con hipocentro a 641 km de profundidad, es el de mayor magnitud registrado instrumentalmente en los últimos 50 años. No produjo daños en la superficie pero fue percibido en la mayor parte del hemisferio sur. Este evento sísmico tuvo un proceso de ruptura múltiple y complejo durante 55 s y la ruptura se propagó en la dirección N-E con una velocidad promedio de 1.6 km/s. La longitud de la ruptura fue de 90 km y la aspereza principal estuvo contenida en un área de 40×40 km2. La ruptura corresponde a un mecanismo focal de tipo normal con planos orientados en dirección E-O, siendo el plano de ruptura cercano a la vertical. El momento sísmico escalar calculado mediante inversión de ondas de volumen es 2.30 × 1021 Nm y corresponde a una magnitud de 8.2 Mw.