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En masse application of feature tracking algorithms to satellite image pairs has produced records of glacier surface velocities with global coverage, revolutionizing the understanding of global glacier change. However, glacier velocity records are sometimes incomplete due to gaps in the cloud-free satellite image record (for optical images) and failure of standard feature tracking parameters, e.g., search range, chip size, or estimated displacement, to capture rapid changes in glacier velocity. Here, we present a pipeline for pre-processing commercial high-resolution daily PlanetScope surface reflectance images and for generating georeferenced glacier velocity maps using NASA's autonomous Repeat Image Feature Tracking (autoRIFT) algorithm with customized parameters. We compare our velocity time series to the NASA Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) global glacier velocity dataset, which is produced using autoRIFT, with regional-scale feature tracking parameters. Using five surge-type glaciers as test sites, we demonstrate that the use of customized feature tracking parameters for each glacier improves upon the velocity record provided by ITS_LIVE during periods of rapid glacier acceleration (i.e., changes greater than several meters per day over 2–3 months). We show that ITS_LIVE can fail to capture velocities during glacier surges but that both the use of custom autoRIFT parameters and the inclusion of PlanetScope imagery can capture the progression of order-of-magnitude changes in flow speed with median uncertainties of m d−1. Additionally, the PlanetScope image record approximately doubles the amount of optical cloud-free imagery available for each glacier and the number of velocity maps produced outside of the months affected by darkness (i.e., polar night), augmenting the ITS_LIVE record. We demonstrate that these pipelines provide additional insights into speedup behavior for the test glaciers and recommend that they are used for studies that aim to capture glacier velocity change at sub-monthly timescales and with greater spatial detail.

The alluvial aquifer of the transnational Roya River watershed is an important water resource for drinking water supply. Through successive European projects, a monitoring network has been implemented over the alluvial plain to improve the understanding of the functioning of this aquifer. For instance, studies highlighted the predominant role of surface water in the recharge of the aquifer. Following the storm Alex and the resulting exceptional flood event in the Roya valley in October 2020, a general decrease of the piezometric levels was observed in the alluvial aquifer. Changes in the river morphology and in the granulometry of the hyporheic zone have impacted surface water – groundwater exchanges and reduced the aquifer recharge.

The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.org/10.5880/GFZ.5.4.2018.001 (Mikolaj et al., 2018).

Hydrological extremes are amongst the most devastating forms of natural disasters both in terms of lives lost and socio-economic impacts. There is consequently an imperative to robustly estimate the frequency and magnitude of hydrological extremes. Traditionally, engineers have employed purely statistical approaches to the estimation of flood risk. For example, for an observed hydrological timeseries, each annual maximum flood is extracted and a frequency distribution is fit to these data. The fitted distribution is then extrapolated to provide an estimate of the required design risk (i.e. the 1% Annual Exceedance Probability – AEP). Such traditional approaches are overly simplistic in that risk is implicitly assumed to be static, in other words, that climatological processes are assumed to be randomly distributed in time. In this study, flood risk estimates are evaluated with regards to traditional statistical approaches as well as Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) conditional estimates for a flood-prone catchment in eastern Australia. A paleo-reconstruction of pre-instrumental PDO/ENSO occurrence is then employed to estimate uncertainty associated with the estimation of the 1% AEP flood. The results indicate a significant underestimation of the uncertainty associated with extreme flood events when employing the traditional engineering estimates.

The study of pointer years of numerous tree-ring chronologies of the central Iberian Peninsula (Sierra de Guadarrama) could provide complementary information about climate variability over the last 405 yr. In total, 64 pointer years have been identified: 30 negative (representing minimum growths) and 34 positive (representing maximum growths), the most significant of these being 1601, 1963 and 1996 for the negative ones, and 1734 and 1737 for the positive ones. Given that summer precipitation was found to be the most limiting factor for the growth of Pinus in the Sierra de Guadarrama in the second half of the 20th century, it is also an explanatory factor in almost 50% of the extreme growths. Furthermore, these pointer years and intervals are not evenly distributed throughout time. Both in the first half of the 17th and in the second half of 20th, they were more frequent and more extreme and these periods are the most notable for the frequency of negative pointer years in Central Spain. The interval 1600–1602 is of special significance, being one of the most unfavourable for tree growth in the centre of Spain, with 1601 representing the minimum index in the regional chronology. We infer that this special minimum annual increase was the effect of the eruption of Huaynaputina, which occurred in Peru at the beginning of 1600 AD. This is the first time that the effects of this eruption in the tree-ring records of Southern Europe have been demonstrated.

La radiación solar es el factor más importante que limita el crecimiento de las plantas en los bosques tropicales y subtropicales húmedos. En función de esto, las especies de árboles se clasificaron históricamente en dos grupos funcionales sobre la base de sus requerimientos de germinación, establecimiento y crecimiento. Mientras que las especies más tolerantes a la sombra pueden germinar, crecer y establecerse en sitios con niveles bajos de radiación, las especies de sol necesitan niveles altos para su desarrollo. Sin embargo, dentro de los bosques existen variaciones espacio-temporales en la disponibilidad de luz y la mayoría de las especies tienen comportamientos ecofisiológicos intermedios entre las dos categorías extremas. En este trabajo analizamos adaptaciones relacionadas con la economía de agua y carbono (tales como la densidad de la madera, la eficiencia en el transporte de agua y la capacidad fotosintética) de especies arbóreas del Bosque Atlántico, bajo la hipótesis de que las presiones selectivas han moldeado características especie-específicas que les permiten optimizar la captura de la radiación solar y coordinarla con el transporte de agua hasta las hojas. Presentamos evidencia que indica que la densidad de la madera es una característica que permite predecir el comportamiento de las especies arbóreas, en relación a las tasas de crecimiento y características relacionadas con el transporte y regulación del uso del agua. Las especies menos tolerantes a la sombra tienen densidad de madera baja y una eficiencia alta en el transporte de agua. En ambientes con alta radiación y demanda evaporativa, las plantas que tienen una baja densidad de madera y una eficiencia alta en el transporte de agua desde el suelo hasta las hojas pueden mantener niveles altos de potencial hídrico foliares (menores déficits hídricos), una mayor conductancia estomática y, consecuentemente, una mayor tasa de asimilación de carbono y crecimiento. Los cambios drásticos en la radiación solar por la apertura de un claro pueden imponer también cambios muy grandes en las condiciones de crecimiento de la plantas. El desarrollo de los individuos en las nuevas condiciones depende de su plasticidad fenotípica, la cual puede variar ampliamente entre las distintas especies. Los individuos juveniles de especies menos tolerantes a la sombra pueden responder rápidamente a los cambios en los niveles de radiación aclimatando su fisiología y morfología para mantener tasas de crecimiento mayores que las de especies más tolerantes.