Dataset of night-time emissions of the Earth in the near UV range (290-430 nm), with 6.3 km resolution in the latitude range -51.6

The data presented in this article are related to the research paper entitled "Observation of night-time emissions of the Earth in the near UV range from the International Space Station with the Mini-EUSO detector" (Remote Sensing of Environment, Volume 284, January 2023, 113336, https://doi.org/10.1016/j.rse.2022.113336). The data have been acquired with the Mini-EUSO detector, an UV telescope operating in the range 290-430 nm and located inside the International Space Station. The detector was launched in August 2019, and it has started operations from the nadir-facing UV-transparent window in the Russian Zvezda module in October 2019. The data presented here refer to 32 sessions acquired between 2019-11-19 and 2021-05-06. The instrument consists of a Fresnel-lens optical system and a focal surface composed of 36 multi-anode photomultiplier tubes, each with 64 channels, for a total of 2304 channels with single photon counting sensitivity. The telescope, with a square field-of-view of 44°, has a spatial resolution on the Earth surface of 6.3 km and saves triggered transient phenomena with a temporal resolution of 2.5 µs and 320 µs. The telescope also operates in continuous acquisition at a 40.96 ms scale. In this article, large-area night-time UV maps obtained processing the 40.96 ms data, taking averages over regions of some specific geographical areas (e.g., Europe, North America) and over the entire globe, are presented. Data are binned into 0.1° × 0.1° or 0.05° × 0.05° cells (depending on the scale of the map) over the Earth's surface. Raw data are made available in the form of tables (latitude, longitude, counts) and .kmz files (containing the .png images). These are - to the best of our knowledge - the highest sensitivity data in this wavelength range and can be of use to various disciplines.

One man, 73 years, and 25 species. Evaluating phenological responses using a lifelong study of first flowering dates.

Phenological shifts linked to global warming reflect the ability of organisms to track changing climatic conditions. However, different organisms track global warming differently and there is an increasing interest in the link between phenological traits and plant abundance and distribution. Long-term data sets are often used to estimate phenological traits to climate change, but so far little has been done to evaluate the quality of these estimates. Here, we use a 73-year long data series of first flowering dates for 25 species from north-temperate Sweden to evaluate (i) correlations between first flowering dates and year for different time periods and (ii) linear regression models between first flowering date and mean monthly temperatures in preceding months. Furthermore, we evaluate the potential of this kind of data to estimate the phenological temperature sensitivities (i.e. number of days phenological change per degree temperature change, ß60) in such models. The sign of the correlations between first flowering dates and year were highly inconsistent among different time periods, highlighting that estimates of phenological change are sensitive to the specific time period used. The first flowering dates of all species were correlated with temperature, but with large differences in both the strength of the response and the period(s) of the year that were most strongly associated with phenological variation. Finally, our analyses indicated that legacy data sets need to be relatively long-term to be useful for estimating phenological temperature sensitivities (ß60) for inter-specific comparisons. In 10-year long observation series only one out of 24 species reached ≥80 % probability of estimating temperature sensitivity (ß60) within a ±1 range, and 17 out of 24 species reached ≥80 % probability when observation series were 20 years or shorter. The standard error for ß60 ranged from 0.6 to 2.0 for 10-year long observation series, and 19 out of 24 species reached SE < 1 after 15 years. In general, late flowering species will require longer time series than early flowering species.

Warming experiments underpredict plant phenological responses to climate change.

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.