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Aim: Trade-offs allow individuals to optimize their fitness by tailoring the investment into different traits to variable environmental conditions, such as along geographical gradients. Trade-offs thus can help in adjusting to changing thermal and insolation profiles, especially in small ectotherms, whose body temperature typically follows environmental temperatures closely. Two traits usually involved in latitudinal adaptation are body size and melanism. Since both traits are costly, individuals need to optimize investment into each trait. Here, we studied how environmental factors influence this trade-off in the short and long-term. Location: Europe. Methods: We raised flies from 15 latitudinal populations at three constant temperatures in a laboratory common garden to differentiate plastic and evolutionary responses to temperature. We further analysed how the different insolation components of the populations' habitats influenced the evolution of the trade-off. Results: Male Sepsis thoracica (Diptera: Sepsidae) feature a sigmoid relationship between melanism and body size, defining two strikingly different male morphs: obsidian (small and black) and amber (large and orange). This relationship was altered by the developmental temperature, documenting its plasticity. The relationship further evolved across populations in response to the environmental characteristics of their habitat, notably temperature, insolation and UV radiation, suggesting that plasticity also has an underlying genetic basis. Nevertheless, melanism, but not body size, merely slightly increased with latitude. Main conclusions: As the plastic and evolutionary responses of the relationship to temperature differed, plasticity does not necessarily follow the direction of evolution of this trade-off, but rather adds to it. Our study evinces the role of several environmental factors in shaping the evolution of a plastic melanism—body size relationship defining a rare male polymorphism in temperate sepsid flies.

The paper proposes a new variant of processing photographic plates for holography based on dichromed gelatin PFG-04 (produced by JSC “Slavich Company”, Pereslavl-Zalessky) for manufacturing high-frequency relief-phase holographic gratings with a spatial frequency of up to 1500 mm –1 . The technology is based on the selective destructive effect of shortwave UV radiation on gelatin and subsequent etching of the layer with various reagents. The relief-phase high-frequency holographic gratings with the maximum diffraction efficiency of 67% were obtained on PFG-04 photographic plates for the first time.

The Global Land Surface Satellite (GLASS) product suite currently contains 12 products, including leaf area index, fraction of absorbed photosynthetically active radiation, fraction of green vegetation coverage, gross primary production, broadband albedo, broadband longwave emissivity, downward shortwave radiation and photosynthetically active radiation, land surface temperature, downward and upwelling thermal radiation, all-wave net radiation, and evapotranspiration. These products are generated from the Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer satellite data. Their unique features include long-term temporal coverage (many from 1981 to the present), high spatial resolutions of the surface radiation products (1 km and 0.05°), spatial continuities without missing pixels, and high quality and accuracy based on extensive validation using in situ measurements and intercomparisons with other existing satellite products. Moreover, the GLASS products are based on robust algorithms that have been published in peer-reviewed literature. Herein, we provide an overview of the algorithm development, product characteristics, and some preliminary applications of these products. We also describe the next steps, such as improving the existing GLASS products, generating more climate data records (CDRs), broadening product dissemination, and fostering their wider utilization. The GLASS products are freely available to the public.

The close layout of buildings is an important cause of urban densification. It makes solar radiation and long-wave radiation being blocked, scattered, and reflected multiple times. Radiant heat is a key factor affecting building energy consumption. The formation mechanism of urban radiation field in the spaces surrounded by dense buildings was analysed. Calculation models were established for the intensity of short-wave and long-wave radiations in spaces surrounded by dense buildings. Characteristics of the radiation field in the enclosed space was analysed. Two typical cities were selected for the analysis of the impact of urban densification on building energy consumption in the hot summer and warm winter zones of China. Studies have shown that the cooling energy consumption of residential buildings in enclosed space can be reduced by 7-15% compared with open space in China's hot summer and warm winter areas. This research will lay the foundation for urban design and architectural design.

A multispectral single-pixel imaging system operating at three wavelengths – 800 nm, 1050 nm, and 1550 nm – was developed for the imaging of natural materials, such as nuts. Spectral multiplexing of structured illumination patterns was realized using optical elements, and radiation modulation was performed using a digital micromirror device. Data on the integral intensity of the radiation scattered from the object was collected using a collecting lens and one InGaAs photodetector. In accordance with the proposed scheme, images of 25 objects at wavelengths of 800 nm, 1050 nm and 1550 nm were reconstructed. The resolution of the obtained images was 64 by 64 pixels, the time of obtaining one image was about 40 seconds. Experimental results demonstrated the successful reconstruction of images of natural samples exhibiting distinct spectral features, confirming the potential of the system for material characterization and classification.

Surface downward solar radiation compositions (SSRC), including photosynthetically active radiation (PAR), ultraviolet-A (UVA), ultraviolet-B (UVB), and shortwave radiation (SWR), with high spatial–temporal resolutions and precision are essential for applications including solar power, vegetation photosynthesis, and environmental health. In this study, an optimal algorithm was developed to calculate SSRC, including their direct and diffuse components. Key features of the algorithm include combining the radiative transfer model with machine learning techniques, including full consideration of the effects of aerosol types, cloud phases, and gas components. A near-real-time monitoring system was developed based on this algorithm, with SSRC products generated from Himawari-8/9 and Fengyun-4 series data. Validation with ground-based data shows that the accuracy of the SWR and PAR compositions (daily mean RMSEs of 19.7 and 9.2 W m−2, respectively) are significantly better than those of state-of-the-art products from CERES, ERA5, and GLASS. The accuracy of UVA and UVB measurements is comparable with CERES. Characteristics of aerosols, clouds, gases, and their impacts on SSRC are investigated before, during, and post COVID-19; in particular, significant SSRC variations due to the reduction of aerosols and increase of ozone are identified in the Chinese central and eastern areas during that period. The spatial–temporal resolution of data products [up to 0.05° (10 min)−1 for the full-disk region] is one of the most important advantages. Data for the East Asia–Pacific region during 2016–20 is available from the CARE home page (www.slrss.cn/care/sp/pc/).

This paper evaluates sea surface temperature (SST) biases of coupled models participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. Overall, CMIP6 models perform better than CMIP5 ones in reproducing SST climatology, with lower multi‐model ensemble mean (MME) globally averaged absolute bias (1.17 vs. 1.31 K). MME bias in global mean annual SST shifts from cooling (−0.09 ± 0.52 K) to warming (0.23 ± 0.60 K). Regionally, in CMIP6 cooling biases over the Northwest Pacific and North Atlantic are reduced by 20% and 18%, while warming biases over the Northeast Pacific, Southeast Atlantic and Southern Ocean are increased by 25%, 16% and 107% respectively. These changes are mainly attributed to the combined effects from aggravated positive (or alleviated negative) bias in clear‐sky surface downward longwave radiation, and alleviated negative bias in cloud radiative effect, partially reduced by enhanced cooling bias in clear‐sky surface downward shortwave radiation. Plain Language Summary As the primary approach to projecting future climate change, state‐of‐the‐art climate models still suffer pronounced biases in climatological annual mean sea surface temperature (SST), such as cold biases over the Northwest Pacific and North Atlantic, and warm biases over the Northeast Pacific, Southeast Pacific, Southeast Atlantic and Southern Ocean. We have evaluated the changes in mean‐state SST biases between the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. CMIP6 models perform better in reproducing SST climatology with lower absolute bias, which is attributed to the process‐level improvement. Overall, annual global mean SST bias shifts from cold (−0.09 ± 0.52 K) to warm (0.23 ± 0.60 K), which is mainly due to the regionally alleviated cooling biases or aggravated warming biases. This warmer shift is contributed by the increased positive (or decreased negative) bias in clear‐sky surface downward longwave radiation and decreased negative bias in cloud radiative effect. Key Points Coupled Model Intercomparison Project Phase 6 (CMIP6) models perform better than CMIP5 ones, with significantly lower global‐mean absolute bias in annual sea surface temperature (SST) Global‐mean SST bias is with a warmer shift (+0.32 K) in CMIP6, with salient regional cold biases alleviated and warm biases aggravated Reduced cold bias in cloud radiative effect and positive change in bias in clear‐sky surface downward longwave together account for the shift

A plausible simulation of the global energy balance is a first-order requirement for a credible climate model. Here I investigate the representation of the global energy balance in 40 state-of-the-art global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). In the CMIP6 multi-model mean, the magnitudes of the energy balance components are often in better agreement with recent reference estimates compared to earlier model generations on a global mean basis. However, the inter-model spread in the representation of many of the components remains substantial, often on the order of 10–20 Wm −2 globally, except for aspects of the shortwave clear-sky budgets, which are now more consistently simulated by the CMIP6 models. The substantial inter-model spread in the simulated global mean latent heat fluxes in the CMIP6 models, exceeding 20% (18 Wm −2 ), further implies also large discrepancies in their representation of the global water balance. From a historic perspective of model development over the past decades, the largest adjustments in the magnitudes of the simulated present-day global mean energy balance components occurred in the shortwave atmospheric clear-sky absorption and the surface downward longwave radiation. Both components were gradually adjusted upwards over several model generations, on the order of 10 Wm −2 , to reach 73 and 344 Wm −2 , respectively in the CMIP6 multi-model means. Thereby, CMIP6 has become the first model generation that largely remediates long-standing model deficiencies related to an overestimation in surface downward shortwave and compensational underestimation in downward longwave radiation in its multi-model mean.

We review the capability of current and scheduled satellite observations of atmospheric methane in the shortwave infrared (SWIR) to quantify methane emissions from the global scale down to point sources. We cover retrieval methods, precision and accuracy requirements, inverse and mass balance methods for inferring emissions, source detection thresholds, and observing system completeness. We classify satellite instruments as area flux mappers and point source imagers, with complementary attributes. Area flux mappers are high-precision (<1 %) instruments with 0.1–10 km pixel size designed to quantify total methane emissions on regional to global scales. Point source imagers are fine-pixel (<60 m) instruments designed to quantify individual point sources by imaging of the plumes. Current area flux mappers include GOSAT (2009–present), which provides a high-quality record for interpretation of long-term methane trends, and TROPOMI (2018–present), which provides global continuous daily mapping to quantify emissions on regional scales. These instruments already provide a powerful resource to quantify national methane emissions in support of the Paris Agreement. Current point source imagers include the GHGSat constellation and several hyperspectral and multispectral land imaging sensors (PRISMA, Sentinel-2, Landsat-8/9, WorldView-3), with detection thresholds in the 100–10 000 kg h−1 range that enable monitoring of large point sources. Future area flux mappers, including MethaneSAT, GOSAT-GW, Sentinel-5, GeoCarb, and CO2M, will increase the capability to quantify emissions at high resolution, and the MERLIN lidar will improve observation of the Arctic. The averaging times required by area flux mappers to quantify regional emissions depend on pixel size, retrieval precision, observation density, fraction of successful retrievals, and return times in a way that varies with the spatial resolution desired. A similar interplay applies to point source imagers between detection threshold, spatial coverage, and return time, defining an observing system completeness. Expanding constellations of point source imagers including GHGSat and Carbon Mapper over the coming years will greatly improve observing system completeness for point sources through dense spatial coverage and frequent return times.

High-resolution, multiplexed experiments are a staple in cellular imaging. Analogous experiments in animals are challenging, however, due to substantial scattering and autofluorescence in tissue at visible (350–700 nm) and near-infrared (700–1,000 nm) wavelengths. Here, we enable real-time, non-invasive multicolour imaging experiments in animals through the design of optical contrast agents for the shortwave infrared (SWIR, 1,000–2,000 nm) region and complementary advances in imaging technologies. We developed tunable, SWIR-emissive flavylium polymethine dyes and established relationships between structure and photophysical properties for this class of bright SWIR contrast agents. In parallel, we designed an imaging system with variable near-infrared/SWIR excitation and single-channel detection, facilitating video-rate multicolour SWIR imaging for optically guided surgery and imaging of awake and moving mice with multiplexed detection. Optimized dyes matched to 980 nm and 1,064 nm lasers, combined with the clinically approved indocyanine green, enabled real-time, three-colour imaging with high temporal and spatial resolutions.Conducting high-resolution, multiplexed imaging in living mammals is challenging because of considerable scattering and autofluorescence in tissue at visible and near-infrared wavelengths. Now, real-time, non-invasive multicolour imaging experiments in live animals have been achieved through the design of optical contrast agents for the shortwave infrared (SWIR, 1,000–2,000 nm) region and the introduction of excitation multiplexing with single-channel SWIR detection.