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Classical tree-ring parameters like tree-ring width, maximum latewood density and cell wall thickness record summer air temperature at high latitudes well and allow for the reconstruction of summer temperature over centuries and millennia. However, information about other climatic factors (e.g. moisture and sunshine duration) is limited in these proxies, especially for temperature-limited environments in subarctic forests growing on permafrost soils. The application of stable hydrogen and oxygen isotopes can provide complementary information about moisture changes and solar irradiation.Solar irradiation and its seasonal distribution play an important role for trees in terms of photosynthesis and carbohydrate production, which can influence deuterium variations in organic matter in addition to hydrological processes. We found that hydrogen and oxygen isotopes in larch tree-ring cellulose from Siberia show a strong link with summer sunshine duration during the growth season. Negative correlations with sunshine duration during autumn of the previous year and winter of the current year can be related to the lack of light during polar nights at subarctic sites (> 60º N) and lack of needles in larch trees to produce photosynthates in a cold environment. Indirect effects might also arise as a high amount of winter sunshine means persistent high-pressure systems with low precipitation, therefore negatively affecting snow accumulation, which is an important water source after snow melt.Uptake of winter precipitation is possible in the warming spring and summer months after snowmelt and thawing of the active soil layer, resulting in significant correlations between tree-ring oxygen values and winter-spring air temperatures. Oxygen isotopes in organic matter are influenced by variations in the isotopic composition of source water, which is closely related to that of precipitation and soil water (though modified by evaporation at the soil surface).Furthermore, we observed that summer vapor pressure deficit is positively and significantly recorded in stable oxygen isotopes from northeastern Siberia, while continuously represented through spring-summer months in western Canada. Hydrogen tree-ring isotopes from the Canadian subarctic recorded a negative significant correlation with summer relative humidity, opposite to northeastern Siberia.The application of dual hydrogen and oxygen stable isotopes in tree rings can expand our knowledge beyond traditional summer air temperature reconstructions and will help to improve climate reconstructions over the past millennia.Acknowledgements: This work was supported by the project RSF 21-17-00006.

An increasing amount of Brazilian rainforest is being lost or degraded for various reasons, both anthropogenic and natural, leading to a loss of biodiversity and further global consequences. Especially in the Brazilian state of Mato Grosso, soy production and large-scale cattle farms led to extensive losses of rainforest in recent years. We used a spectral mixture approach followed by a decision tree classification based on more than 30 years of Landsat data to quantify these losses. Research has shown that current methods for assessing forest degradation are lacking accuracy. Therefore, we generated classifications to determine land cover changes for each year, focusing on both cleared and degraded forest land. The analyses showed a decrease in forest area in Mato Grosso by 28.8% between 1986 and 2020. In order to measure changed forest structures for the selected period, fragmentation analyses based on diverse landscape metrics were carried out for the municipality of Colniza in Mato Grosso. It was found that forest areas experienced also a high degree of fragmentation over the study period, with an increase of 83.3% of the number of patches and a decrease of the mean patch area of 86.1% for the selected time period, resulting in altered habitats for flora and fauna.

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmental change. Publisher PDF

Zusammenfassung Ziel der Studie Der Gemeinsame Bundesausschuss hat beschlossen, im Jahr 2020 ein organisiertes Zervixkarzinom-Screening einzuführen. Die vorliegende Arbeit beschreibt die Entwicklung von Entscheidungshilfen, die Frauen im Rahmen dieses Programms zugesendet werden sollen. Methodik Es wurde eine systematische Recherche nach qualitativen Studien und Surveys zur Erfassung von Erfahrungen, Einstellungen und Informationsbedürfnissen durchgeführt. Ebenso wurde nach systematischen Übersichten zu den Vor- und Nachteilen des Screenings recherchiert. Darüber hinaus wurde eine bereits existierende Entscheidungsanalyse für das Zervixkarzinom-Screening in Deutschland herangezogen. Die Entwürfe wurden einer qualitativen Testung (Fokusgruppen mit 26 Frauen und 8 Experteninterviews), einer quantitativen Nutzertestung (Online-Survey n=2 014 Frauen) sowie einer öffentlichen Anhörung unterzogen. Ergebnisse Die meisten Frauen fanden in den Nutzertestungen die Entscheidungshilfen informativ und hilfreich. Die Mehrzahl würde die Materialien weiterempfehlen. Für viele Frauen war ein Teil der Informationen neu, obwohl sie schon länger an der Zervixkarzinom-Früherkennung teilnahmen. Die Darstellung der Vor- und Nachteile wurde als ausgewogen beurteilt. An der durchschnittlichen Teilnahmebereitschaft änderte sich nach Lesen der Materialien wenig. Allerdings änderten etwa 10 % ihre Einstellung dazu. Etwa 70 % der Frauen würde am Screening teilnehmen. Schlussfolgerungen Die Entscheidungshilfen fanden eine hohe Akzeptanz unter den Nutzerinnen. Sie können helfen, Wissensdefizite zum Zervixkarzinom-Screening abzubauen, und eine informierte Entscheidung unterstützen.

As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data is questioning the causality of this relationship. Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow/NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west to east snow cover gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over Eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.

"1.Remote sensing data is a valuable tool in movement ecology. However, the way it's combined with animal movement data is far from optimal as most studies overlook differences in the spatial, temporal and thematic resolutions between both data types. 2.rsMove uses a pixel‐based approach to link animal tracking and remote sensing data that bridge the gap between these two disciplines while respecting the limitations of the latest. Additionally, if offers standardize methods to pre‐analyze the connection between animal movement and environmental change. 3.The package guides the choice of study sites, satellite data and environmental predictors though data mining and visualization tools. rsMove offers a simple methodology to analyze animal‐environment interactions that helps avoid unnecessary, time‐consuming satellite data processing through an informed decision process. 4.The package offers a basis for a better communication between ecologists and remote sensing experts contributing to the definition of clear remote sensing data requirements. Additionally, it provides future studies on animal movement tools for a more critical approach on the selection of environmental data supporting their reproducibility."

Forest systems provide crucial ecosystem functions to our environment, such as balancing carbon stocks and influencing the local, regional and global climate. A trend towards an increasing frequency of climate change induced extreme weather events, including drought, is hereby a major challenge for forest management. Within this context, the application of remote sensing data provides a powerful means for fast, operational and inexpensive investigations over large spatial scales and time. This study was dedicated to explore the potential of satellite data in combination with harmonic analyses for quantifying the vegetation response to drought events in German forests. The harmonic modelling method was compared with a z-score standardization approach and correlated against both, meteorological and topographical data. Optical satellite imagery from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used in combination with three commonly applied vegetation indices. Highest correlation scores based on the harmonic modelling technique were computed for the 6th harmonic degree. MODIS imagery in combination with the Normalized Difference Vegetation Index (NDVI) generated hereby best results for measuring spectral response to drought conditions. Strongest correlation between remote sensing data and meteorological measures were observed for soil moisture and the self-calibrated Palmer Drought Severity Index (scPDSI). Furthermore, forests regions over sandy soils with pine as the dominant tree type were identified to be particularly vulnerable to drought. In addition, topographical analyses suggested mitigated drought affects along hill slopes. While the proposed approaches provide valuable information about vegetation dynamics as a response to meteorological weather conditions, standardized in-situ measurements over larger spatial scales and related to drought quantification are required for further in-depth quality assessment of the used methods and data.

We investigate the climate signature of δ18O tree-ring records from sites distributed all over Europe covering the last 400 years. An empirical orthogonal function (EOF) analysis reveals two distinct modes of variability on the basis of the existing δ18O tree-ring records. The first mode is associated with anomaly patterns projecting onto the El Niño–Southern Oscillation (ENSO) and reflects a multi-seasonal climatic signal. The ENSO link is pronounced for the last 130 years, but it is found to be weak over the period from 1600 to 1850, suggesting that the relationship between ENSO and the European climate may not be stable over time. The second mode of δ18O variability, which captures a north–south dipole in the European δ18O tree-ring records, is related to a regional summer atmospheric circulation pattern, revealing a pronounced centre over the North Sea. Locally, the δ18O anomalies associated with this mode show the same (opposite) sign with temperature (precipitation). Based on the oxygen isotopic signature derived from tree rings, we argue that the prevailing large-scale atmospheric circulation patterns and the related teleconnections can be analysed beyond instrumental records.

Monitoring global biodiversity from space through remotely sensing geospatial patterns has high potential to add to our knowl- edge acquired by field observation. Although a framework of essential biodiversity variables (EBVs) is emerging for monitoring biodiversity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing biodiversity products that can further improve the monitoring of geospatial biodiversity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of biodiversity from satellites. Biodiversity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for example, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of biodiversity from local to global scales.

As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.

In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use ofremote sensingapproaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similarspectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called “spectral species”. Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method toMODISimagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a singleplant speciesin the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to deriveα- (local relative abundance and richness of spectral species) andβ-diversity (turnover of spectral species) maps over wide geographical areas.

In the version of this Perspective initially published, there was an error in units reported in the main text. Specifically, in the first sentence of the sixth paragraph under the heading “A critical review of EBVs retrieved by remote sensing,” in the text now reading “Finally, when harmonizing the terminology used by ecological and remote sensing communities, it is important to emphasize that utilizing broadband optical wavelengths (for example, for PlanetScope, approximately 400–700 nm) at very high spatial resolution,” 400–700 nm originally appeared as “60–90 nm.” The error has been corrected in the online version of the article.

In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called “spectral species”. Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method to MODIS imagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a single plant species in the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to derive α- (local relative abundance and richness of spectral species) and β-diversity (turnover of spectral species) maps over wide geographical areas.

This is a book about how ecologists can integrate remote sensing and GIS in their research. It will allow readers to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS). In addition, readers will be guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis, empowering the reader to turn data acquired in the field into actual spatial data. Readers will learn to process and analyse spatial data of different types and interpret the data and results. After finishing this book, readers will be able to address questions such as “What is the distance to the border of the protected area?”, “Which points are located close to a road?”, “Which fraction of land cover types exist in my study area?” using different software and techniques. This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data. The software used is the widely applied open source scientific programs QGIS and R. All scripts and data sets used in the book will be provided online at book.ecosens.org. This book covers specific methods including: what to consider before collecting in situ data how to work with spatial data collected in situ the difference between raster and vector data how to acquire further vector and raster data how to create relevant environmental information how to combine and analyse in situ and remote sensing data how to create useful maps for field work and presentations how to use QGIS and R for spatial analysis how to develop analysis scripts

We investigate the annual variability of δ18O tree ring records from sites distributed all over Europe covering the last 400 years. An Empirical Orthogonal Function (EOF) analysis reveals two distinct modes of variability on the basis of the existing δ18O tree ring records. The first mode of δ18O variability is associated with anomaly patterns of the El Niño-Southern Oscillation (ENSO) and reflects a multi-seasonal climatic signal. The ENSO signal is visible for the last 130 years, but is found weak during the period 1600 to 1850 suggesting that the relationship between ENSO and the European climate may not stable over time. The second mode of δ18O variability, which captures an out-of-phase variability between northwestern and southeastern European δ18O tree ring records, is related to a regional summer atmospheric circulation pattern revealing a pronounced centre over the North Sea. Locally, the δ18O anomalies associated with this mode show the same (opposite) sign with temperature (precipitation). We infer that the investigation of large-scale atmospheric circulation patterns and related teleconnections far beyond instrumental records can be done with oxygen isotopic signature derived from tree rings. However, the European δ18Ocel tree network needs to be consolidated and updated, as well as additional research on the stationarity of reconstructed climate signals and the stationarity of teleconnections is advisable.

1. Visualizing movement data is challenging: While traditional spatial data can be sufficiently displayed as two‐dimensional plots or maps, movement trajectories require the representation of time in a third dimension. To address this, we present moveVis, an r package, which provides tools to animate movement trajectories, overlaying simultaneous uni‐ or multi‐temporal raster imagery or vector data.2. moveVis automates the processing of movement and environmental data to turn such into an animation. This includes (a) the regularization of movement trajectories enforcing uniform time instances and intervals across all trajectories, (b) the frame‐wise mapping of movement trajectories onto temporally static or dynamic environmental layers, (c) the addition of customizations, for example, map elements or colour scales and (d) the rendering of frames into an animation encoded as GIF or video file.3. moveVis is designed to display interactions and concurrencies of animal movement and environmental data. We present examples and use cases, ranging from data exploration to visualizing scientific findings.4. Static spatial plots of movement data disregard the temporal dimension that distinguishes movement from other spatial data. In contrast, animations allow to display relocation in both time and space. We deem animations a powerful way to visually explore movement data, frame analytical findings and display potential interactions with spatially continuous and temporally dynamic environmental covariates. published

The Federal Joint Committee has decided to introduce organized cervical carcinoma screening in 2020. The present work describes the development of decision aids that will be sent to women in this program.A systematic search for qualitative studies and surveys was conducted to gather information on experiences, attitudes and information needs. Furthermore, we searched for systematic reviews on advantages and disadvantages of screening. An existing decision analysis for cervical carcinoma screening in Germany was used. The designs were subjected to a qualitative test (focus groups with 26 women and 8 expert interviews), to a quantitative user test (online survey n=2,014 women) and to a public hearing.Most women found the decision aids informative and helpful. The majority would recommend the use of these materials to others. For many women, part of the information was new, although they had been involved in cervical cancer screening for some time. The presentation of the advantages and disadvantages was judged to be balanced. However, 10% changed their attitude towards participation and 70% of women would attend screening.The decision aids found a high acceptance among the users. They can help to reduce knowledge deficits on cervical carcinoma screening and support a informed decision making.Der Gemeinsame Bundesausschuss hat beschlossen, im Jahr 2020 ein organisiertes Zervixkarzinom-Screening einzuführen. Die vorliegende Arbeit beschreibt die Entwicklung von Entscheidungshilfen, die Frauen im Rahmen dieses Programms zugesendet werden sollen.Es wurde eine systematische Recherche nach qualitativen Studien und Surveys zur Erfassung von Erfahrungen, Einstellungen und Informationsbedürfnissen durchgeführt. Ebenso wurde nach systematischen Übersichten zu den Vor- und Nachteilen des Screenings recherchiert. Darüber hinaus wurde eine bereits existierende Entscheidungsanalyse für das Zervixkarzinom-Screening in Deutschland herangezogen. Die Entwürfe wurden einer qualitativen Testung (Fokusgruppen mit 26 Frauen und 8 Experteninterviews), einer quantitativen Nutzertestung (Online-Survey n=2 014 Frauen) sowie einer öffentlichen Anhörung unterzogen.Die meisten Frauen fanden in den Nutzertestungen die Entscheidungshilfen informativ und hilfreich. Die Mehrzahl würde die Materialien weiterempfehlen. Für viele Frauen war ein Teil der Informationen neu, obwohl sie schon länger an der Zervixkarzinom-Früherkennung teilnahmen. Die Darstellung der Vor- und Nachteile wurde als ausgewogen beurteilt. An der durchschnittlichen Teilnahmebereitschaft änderte sich nach Lesen der Materialien wenig. Allerdings änderten etwa 10 % ihre Einstellung dazu. Etwa 70 % der Frauen würde am Screening teilnehmen.Die Entscheidungshilfen fanden eine hohe Akzeptanz unter den Nutzerinnen. Sie können helfen, Wissensdefizite zum Zervixkarzinom-Screening abzubauen, und eine informierte Entscheidung unterstützen.

International audience; This is an introduction to the issue: Special feature: improving biodiversity monitoring using satellite remote sensing. The preservation of biodiversity has become a major challenge for sustainable development at national, European (Natura 2000 and Habitats Directive) and international levels (Convention on Biological Diversity, 2011-2020). To address the current conservation needs, there is a need to operationalise methods to assess the distribution of natural resources while integrating information on habitat condition; inform conservation planning and support the assessment of ecosystem services. Increased access to satellite imagery and new developments in data analyses can support progress towards biodiversity conservation targets by stepping up monitoring processes at various spatial and temporal scales. Satellite remote sensing is however no panacea, and little can be achieved without a robust understanding of the socio‐ecological system considered. We aim to demonstrate how the coupling of satellite remote sensing data with ground observations and adequate modelling can provide tangible operational solutions towards a better understanding and management of natural systems.

In recent years, many components of the connection between Eurasian autumn snow cover and wintertime North Atlantic Oscillation (NAO) were investigated, suggesting that November snow cover distribution has strong prediction power for the upcoming Northern Hemisphere winter climate. However, non-stationarity of this relationship could impact its use for prediction routines. Here we use snow products from long-term reanalyses to investigate interannual and interdecadal links between autumnal snow cover and atmospheric conditions in winter. We find evidence for a negative NAO tendency after November with a strong west-to-east snow cover gradient, which is valid throughout the last 150 years. This correlation is linked with a consistent impact of November snow on a slowed stratospheric polar vortex. Nevertheless, interdecadal variability for this relationship shows episodes of decreased correlation power, which co-occur with episodes of low variability in the November snow index. We find that the same is also true for sea ice as an NAO predictor. The snow dipole itself is associated with reduced Barents-Kara sea ice concentration, increased Ural blocking frequency and negative temperature anomalies in eastern Eurasia. Increased sea ice variability in recent years is linked to increased snow variability, thus increasing its power in predicting the winter NAO.

Habitat degradation and hunting have caused the widespread loss of larger vertebrate species (defaunation) from tropical biodiversity hotspots. However, these defaunation drivers impact vertebrate biodiversity in different ways and, therefore, require different conservation interventions. We conducted landscape-scale camera-trap surveys across six study sites in Southeast Asia to assess how moderate degradation and intensive, indiscriminate hunting differentially impact tropical terrestrial mammals and birds. We found that functional extinction rates were higher in hunted compared to degraded sites. Species found in both sites had lower occupancies in the hunted sites. Canopy closure was the main predictor of occurrence in the degraded sites, while village density primarily influenced occurrence in the hunted sites. Our findings suggest that intensive, indiscriminate hunting may be a more immediate threat than moderate habitat degradation for tropical faunal communities, and that conservation stakeholders should focus as much on overhunting as on habitat conservation to address the defaunation crisis., Andrew Tilker, Jesse F. Abrams et al. assessed habitat degradation and hunting on tropical terrestrial mammals and birds in Southeast Asia. They find higher levels of functional extinction and consistently lower animal occupancy in hunted sites, suggesting that indiscriminate hunting is a more immediate threat for tropical animal communities.

The Tibetan Plateau (TP) region, often referred to as the Third Pole, is the world's highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impact on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric reanalyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global reanalyses with satellite and in situ data. Yet, snow in reanalyses provides critical surface information for forecast systems from the medium to sub-seasonal timescales. Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, the Japanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), are inter-compared over the TP region. The reanalyses are evaluated against a set of 33 in situ station observations, as well as against the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in situ observations provides confidence in the station data despite the relative paucity of in situ measurement sites and the harsh operating conditions. While several reanalyses show a systematic overestimation of the snow depth or snow cover, the reanalyses that assimilate local in situ observations or IMS snow cover are better capable of representing the shallow, transient snowpack over the TP region. The latter point is clearly demonstrated by examining the family of reanalyses from the ECMWF, of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. We further tested the sensitivity of the ERA5-Land model in offline experiments, assessing the impact of blown snow sublimation, snow cover to snow depth conversion and, more importantly, excessive snowfall. These results suggest that excessive snowfall might be the primary factor for the large overestimation of snow depth and cover in ERA5 reanalysis. Pending a solution for this common model precipitation bias over the Himalayas and the TP, future snow reanalyses that optimally combine the use of satellite snow cover and in situ snow depth observations in the assimilation and analysis cycles have the potential to improve medium-range to sub-seasonal forecasts for water resources applications.