Impact of climate change on persistent cold-air pools in an alpine valley during the 21st century DOI Creative Commons
Sara Bacer, Julien Beaumet, Martin Ménégoz

et al.

Weather and Climate Dynamics, Journal Year: 2024, Volume and Issue: 5(1), P. 211 - 229

Published: Feb. 13, 2024

Abstract. When anticyclonic conditions persist over mountainous regions in winter, cold-air pools (i.e. thermal inversions) develop valleys and from a few days to weeks. During these persistent pool (PCAP) episodes the atmosphere inside valley is stable vertical mixing prevented, promoting accumulation of pollutants close bottom worsening air quality. The purpose this paper address impact climate change on PCAPs until end century for alpine Grenoble valleys. long-term projections produced with general circulation model MPI (from Max Planck Institute) downscaled Alps regional MAR (Modèle Atmosphérique Régional) are used perform statistical study period 1981–2100. trends main characteristics PCAPs, namely their intensity, duration, frequency, investigated two future scenarios, SSP2–4.5 SSP5–8.5. We find that intensity displays statistically significant decreasing trend SSP5–8.5 scenario only. This decay explained by fact temperature increases more at 2 m above than free mid-altitudes valley; might be due increase specific humidity near ground. structure one past around 2050, next detail. For purpose, WRF (Weather Research Forecasting) model, forced worst-case (SSP5–8.5), high resolution (111 m). PCAP carefully selected data so meaningful comparison can performed. episode warmer all altitudes (by least 4 ∘C) similar inversion height, which very likely generic features PCAPs. also have along-valley wind but different stability, being episode. Overall, shows during tends slightly less under scenario, unchanged still form.

Language: Английский

Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018 DOI Creative Commons
Kerttu Kouki, Kari Luojus, Aku Riihelä

et al.

˜The œcryosphere, Journal Year: 2023, Volume and Issue: 17(12), P. 5007 - 5026

Published: Nov. 29, 2023

Abstract. Seasonal snow cover of the Northern Hemisphere (NH) greatly influences surface energy balance; hydrological cycle; and many human activities, such as tourism agriculture. Monitoring at a continental scale is only possible from satellites or using reanalysis data. This study aims to analyze time series water equivalent (SWE), extent (SCE), albedo in spring ERA5 ERA5-Land data compare with several satellite-based datasets. As reference for SWE intercomparison, we use bias-corrected SnowCCI v1 non-mountainous regions mean Brown, MERRA-2, Crocus v7 datasets mountainous regions. For albedo, black-sky CLARA-A2 SAL, based on AVHRR data, MCD43D51, MODIS Additionally, Rutgers JAXA JASMES SCE products. Our covers land areas north 40∘ N period between 1982 2018 (spring season March May). The analysis shows that both overestimate total NH by 150 % 200 compared larger overestimation, which mostly due very high values over revealed discontinuity around year 2004 since adding Interactive Multisensor Snow Ice Mapping System (IMS) onwards considerably improves estimates but makes trends less reliable. negative range −249 −236 Gt per decade spring, 2 3 times than detected other (ranging −124 −77 decade). accurately described ERA5-Land, whereas notably Albedo are more consistent datasets, slight overestimation ERA5-Land. strongest May, when trend varies −0.011 −0.006 depending dataset. May (-1.22×106 km2 decade) about twice large all −0.66 -0.50×106 also there spatial variability trends, studies.

Language: Английский

Citations

26
Remote sensing of mountain snow from space: status and recommendations DOI Creative Commons
Simon Gascoin, Kari Luojus, Thomas Nägler

et al.

Frontiers in Earth Science, Journal Year: 2024, Volume and Issue: 12

Published: May 10, 2024

The spatial and temporal variation of the seasonal snowpack in mountain regions is recognized as a clear knowledge gap for climate, ecology water resources applications. Here, we identify three salient topics where recent developments snow remote sensing data assimilation can lead to significant progress: equivalent, high resolution snow-covered area long term cover observations including albedo. These be addressed near future with institutional support.

Language: Английский

Citations

11
Detecting the impact of climate change on alpine mass movements in observational records from the European Alps DOI Creative Commons
Mylène Jacquemart,

Samuel Weber,

Marta Chiarle

et al.

Earth-Science Reviews, Journal Year: 2024, Volume and Issue: 258, P. 104886 - 104886

Published: Aug. 14, 2024

Language: Английский

Citations

11
Landsat‐based greening trends in alpine ecosystems are inflated by multidecadal increases in summer observations DOI Creative Commons
Arthur Bayle, Simon Gascoin, Logan T. Berner

et al.

Ecography, Journal Year: 2024, Volume and Issue: 2024(12)

Published: Aug. 27, 2024

Remote sensing is an invaluable tool for tracking decadal‐scale changes in vegetation greenness response to climate and land use changes. While the Landsat archive has been widely used explore these trends their spatial temporal complexity, its inconsistent sampling frequency over time space raises concerns about ability provide reliable estimates of annual indices such as maximum normalised difference index (NDVI), commonly a proxy plant productivity. Here we demonstrate seasonally snow‐covered ecosystems, that greening derived from NDVI can be significantly overestimated because number available observations increases time, mostly magnitude overestimation varies along environmental gradients. Typically, areas with short growing season few experience largest bias trend estimation. We show conditions are met late snowmelting habitats European Alps, which known particularly sensitive temperature present conservation challenges. In this critical context, almost 50% estimated explained by bias. Our study calls greater caution when comparing magnitudes between different snow observations. At minimum recommend reporting information on observations, including per year, long‐term studies undertaken.

Language: Английский

Citations

11
A semi-parametric distribution stitch based on the Berk-Jones test for French daily precipitation bias correction DOI
Philippe Ear,

Éléna Di Bernardino,

Thomas Laloë

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Language: Английский

Citations

1
Elevation-dependent biases of raw and bias-adjusted EURO-CORDEX regional climate models in the European Alps DOI Creative Commons
Michael Matiu, Anna Napoli, Sven Kotlarski

et al.

Climate Dynamics, Journal Year: 2024, Volume and Issue: 62(9), P. 9013 - 9030

Published: Aug. 6, 2024

Abstract Data from the EURO-CORDEX ensemble of regional climate model simulations and CORDEX-Adjust dataset were evaluated over European Alps using multiple gridded observational datasets. Biases, which are here defined as difference between models observations, assessed a function elevation for different indices that span average extreme conditions. Moreover, we impact datasets on evaluation, including E-OBS, APGD, high-resolution national Furthermore, bi-variate dependency temperature precipitation biases, their temporal evolution, bias adjustment methods reference Biases in seasonal temperature, precipitation, wet-day frequency found to increase with elevation. Differences trends RCMs observations caused could be removed by detrending both RCMs. The choice observation used turned out more relevant than method itself. Consequently, change assessments mountain regions need pay particular attention and, furthermore, dependence biases increasing uncertainty order provide robust information future climate.

Language: Английский

Citations

4
A comprehensive comparison of bias correction methods in climate model simulations: application on ERA5-Land across different temporal resolutions DOI Creative Commons
Pranav Dhawan, Daniele Dalla Torre, Majid Niazkar

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(23), P. e40352 - e40352

Published: Nov. 14, 2024

Climate data plays a crucial role in water resources management, which is becoming an increasingly relevant asset all types of hydrological analysis not only for climate change studies but various horizon forecasting. Though the ever-improving accuracy models' spatial and temporal resolution has surged validity their outputs, products global regional models need to be corrected reliably used local purposes. Here, we propose comprehensive statistical univariate multivariate, as well machine learning methods bias correction, are compared on different scales, ranging from hourly time steps monthly aggregations, environment complex Alpine orthography, using ERA5-Land reanalysis data. The results reveal trends performance correction precipitation temperature across resolutions.

Language: Английский

Citations

3
Snow depth sensitivity to mean temperature, precipitation, and elevation in the Austrian and Swiss Alps DOI Creative Commons
Matthew B. Switanek, Gernot Resch, Andreas Gobiet

et al.

˜The œcryosphere, Journal Year: 2024, Volume and Issue: 18(12), P. 6005 - 6026

Published: Dec. 19, 2024

Abstract. Snow depth plays an important role in the seasonal climatic and hydrological cycles of alpine regions. Previous studies have shown predominantly decreasing trends average snow across European Alps. Additionally, prior work has bivariate statistical relationships between mean air temperature or precipitation. Building upon existing research, our study uses observational records situ station data Austria Switzerland to better quantify sensitivity historical changes through a multivariate framework that depends on elevation, temperature, These sensitivities, which are obtained over 1901–1902 1970–1971 period, then used estimate depths more recent period 1971–1972 2020–2021. We find year-to-year estimates depths, derived from empirical–statistical model (SnowSens), rely solely sensitivities nearly as skillful operational SNOWGRID-CL by weather service at GeoSphere Austria. Furthermore, observed long-term last 50 years agreement with SnowSens than SNOWGRID-CL. results indicate depth, precipitation quite robust decadal-length scales time, they can be effectively translate expected into depth.

Language: Английский

Citations

3
Estimating changes in extreme snow load in Europe as a function of global warming levels DOI Creative Commons
Guillaume Évin, Erwan Le Roux,

Elisa Kamir

et al.

Cold Regions Science and Technology, Journal Year: 2025, Volume and Issue: 231, P. 104424 - 104424

Published: Jan. 16, 2025

Language: Английский

Citations

0
Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran DOI Creative Commons

Faezehsadat Majidi,

Samaneh Sabetghadam, Maryam Gharaylou

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102246 - 102246

Published: Feb. 18, 2025

Language: Английский

Citations

0