Abstract Austrian observations of snow depth date back to 1895 and are thus among the longest available quantitative information from hydrometeorological networks worldwide. It is well known that such long‐term prone inhomogeneities, which may not only affect climatologies trends, but derived products used in research or practice. While reliability methods for detecting breaks time series has been shown before could also be confirmed by our work, we focused on improving adjustment method....

Abstract We investigate relationships between synoptic-scale atmospheric variability and the mass-balance of 13 Andean glaciers (located 16–55° S) using Pearson correlation coefficients (PCCs) multiple regressions. then train empirical glacier models (EGMs) in a cross-validated regression procedure for each glacier. find four distinct glaciological zones with regard to their climatic controls: (1) The Outer Tropics is linked temperature El Niño-Southern Oscillation (PCC ⩽ 0.6), (2) Desert...

Abstract. Snow cover plays a crucial role in regional climate systems worldwide. It is key variable the context of change because its direct feedback to system, while at same time being very sensitive change. Accurate long-term spatial data on snow are scarce, due lack satellite or forcing run land surface models back time. This study presents an R package, SnowQM, designed correct for bias water equivalent data, using more accurate calibrating correction. The correction based widely applied...

Abstract. Many methods exist to model snow densification in order calculate the depth of a single layer or total cover from its mass. Most these models need be tightly integrated with an accumulation and melt many forcing variables at high temporal resolution. However, when trying (HS) on climatological timescales, which is often needed for winter tourism-related applications, preconditions can cause barriers. Often, types empirical are used. These estimate snowmelt based daily precipitation...

Abstract. Knowledge concerning possible inhomogeneities in a data set is of key importance for any subsequent climatological analyses. Well-established relative homogenization methods developed temperature and precipitation exist but have rarely been applied to snow-cover-related time series. We undertook homogeneity assessment Swiss monthly snow depth series by running comparing the results from three well-established semi-automatic break point detection (ACMANT – Adapted Caussinus-Mestre...

Abstract. Historic measurements are often temporally incomplete and may contain longer periods of missing data, whereas climatological analyses require continuous measurement records. This is also valid for historic manual snow depth (HS) time series, which even whole winters can be in a station record, suitable methods have to found reconstruct the data. Daily situ HS data from 126 nivo-meteorological stations Switzerland an altitudinal range 230 2536 m above sea level used compare six...

Abstract. Snow plays a crucial role in regional climate systems worldwide. It is key variable the context of change because its direct feedback to system, while at same time being very sensitive change. Long-term spatial data on snow cover and water equivalent are scarce, due lack satellite or forcing run land surface models back time. This study presents an R package, SnowQM, designed correct for bias long-term compared shorter-term more accurate dataset, using calibrate correction. The...

Abstract. Many methods exist to model snow densification in order calculate the depth of a single layer or total cover from its mass. Most these models need be tightly integrated with an accumulation and melt many forcing variables at high temporal resolution. However, when trying on climatological timescales, which is often needed for winter tourism related applications, preconditions can cause barriers. Often, types applications empirical are used. These estimate based daily precipitation...

<p>Switzerland has a unique dataset of long-term manual daily snow depth time series ranging back more than 100 years for some stations. This makes the predestined to be analyzed in climatological sense. However, there are sometimes shorter (weeks, months) or longer (years) gaps these series, which hinder sound analysis and reasonable conclusions. Therefore, we examine different methods filling data series. We focus on use spatial interpolation, temperature index models machine...

Abstract. Knowledge concerning possible inhomogeneities in a data set is of key importance for any subsequent climatological analyses. Well-established relative homogenization methods developed temperature and precipitation exist, but with only little experience snow. We undertook homogeneity assessment Swiss snow depth series by running comparing the results from three well-established semi-automatic break point detection (ACMANT, Climatol, HOMER). Break points identified each method...

Abstract. Historic measurements are often temporally incomplete and may contain longer periods of missing data whereas climatological analyses require continuous measurement records. This is also valid for historic manual snow depth (HS) time series, where even whole winters can be in a station record suitable methods have to found reconstruct the data. Daily in-situ HS from 126 nivo-meteorological stations Switzerland an altitudinal range 230 2536 m above sea level used compare six...

<p>Models that consume meteorological data have often requirements are quite incompatible with the realities of continuously measured data: they require gapless when datasets gaps, sampling rate matching phenomena interest use a dictated by energy and storage capacities, ‘perfect’ sensors flaws.</p><p> </p><p><span>The MeteoIO library...

<p>Measurements of snow depth can vary dramatically over small distances, and as with any other meteorological variable, time series are affected by inhomogeneities or break points. Such arise due to e.g.; changes instrumentation, station location observer practices, in the local environment such urbanisation plant growth.</p><p>In order analyse monitor variation accurately, homogenised data required. In deriving series, it is essential...