Private

FS 3.235

Mountain Precipitation in a Changing Climate/Mountain Precipitation Change

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FS 3.233: Precipitation Changes in Mountainous Hydroclimates
FS 3.142: Mountain Precipitation in a Changing Climate: Processes, Feedbacks, and Implications

Details

Full Title
FS 3.235: Mountain Precipitation and Hydroclimate in a Changing Climate: Processes, Feedbacks, and Implications
Scheduled
TBA
Location
TBA
Convener
Lorenz Hänchen
Co-Conveners
Michael Brody, Lucia Scaff, Paolo Arias, Emily Potter, John Pomeroy, Ali Behrangi,
Assigned to Synthesis Workshop
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Thematic Focus
Adaptation, Atmosphere, Cryo- & Hydrosphere, Monitoring, Water Cycle, Water Resources
Keywords
Precipitation, Hydrology, Adaptation, Observations, Modeling

Description

Mountain precipitation has undergone significant changes in recent decades and is projected to continue evolving in the future due to climate change. As a critical component of the hydrological cycle, mountain precipitation serves as a primary source of freshwater for ecosystems, rivers, agriculture and downstream communities. The biggest uncertainties in climate modeling are still related to precipitation. In mountainous environments precipitation in particular, is suffering from a lack of observations, especially in high altitudes. That, combined with spatio-temporal variability due to topography that affects the total amount, intensity and type of precipitation makes for a challenging but essential problem to address. We invite submissions on mountain precipitation, including observation strategies, climate projections, feedback mechanisms, and socio-economic impacts. Topics of interest include AI/ML, remote sensing, citizen science, and case studies of extreme events. We also welcome discussions on model advancements, validation against observations, and interdisciplinary approaches to improving resilience in mountain regions and in the very vulnerable downstream ecosystems, communities and their economies.

Submitted Abstracts

ID: 3.8251

Using novel lake-based snowfall measurements in the Alps, Himalayas and Rockies to assess and optimise the representation of snowfall in the MetUM regional atmospheric model at kilometre grid-scales

Siddharth Gumber
Orr, Andrew; Field, Paul; Covi, Federico; Pritchard, Hamish; Deb, Pranab; Girona-Mata, Marc; Potter, Emily; Widmann, Martin

Abstract/Description

Complex mountain orography induces sharp gradients in precipitation accumulation locally, which makes snowfall observation and prediction by regional atmospheric models a major challenge and susceptible to bias. This study addresses these challenges by using a unique repository of snowfall measurements with little bias at a range of ‘super sites’ in the Rockies, European Alps and Himalayas, which are used to produce a snowfall-optimised version of the atmosphere-only UK Met Office Unified Model (MetUM) at a spatial resolution of 1.5 km. The snowfall measurements involve using the winter time-series of water pressure in frozen lakes to measure the mass of falling snow during extreme precipitation events directly over the lake area, which are comparable in size to the model’s grid cells. Development of the snowfall-optimised version of the MetUM involves undertaking a series of model sensitivity experiments focused on testing and understanding the influence of the double moment cloud microphysical scheme (CASIM) used by the MetUM, with the aim of better capturing the onset and end periods, and amounts received during observed snowfall events. The results presented here will show that the MetUM is able to accurately simulate both the timing and amounts of snowfall observed. Finally, using the snowfall-optimised MetUM, we also show detailed maps of snowfall over large-regions of the Alps and Himalayas from the year 2000 to the present day.

ID: 3.8360

Reasons for the Summer Precipitation Variability in the Central-Eastern Himalayas

Xuelong Chen

Abstract/Description

The central-eastern Himalayas (CEH), a key high-altitude barrier on the southern edge of the TP, experiences concentrated summer rainfall and is a crucial water source for Asian countries. What determines the variation in the summer precipitation of the CEH has not been investigated. Here, we investigated the relationship between the Central-Eastern Himalayas summer precipitation and all kinds of signals for the oceans. Analysis of long-term observations and reanalysis data revealed that the summer North Atlantic Oscillation (SNAO) has driven a positive summer precipitation in the CEH. The abnormal circulation in Indian subcontinent due to SNAO met with the south slope of Himalayas. The abnormal circulation caused a topographic mechanical forcing in the CEH. The topography forces the abnormal horizontal winds to generate a strong climb flow component, driving changes in the precipitation distribution. Experiments with removing the plateau topographic features show that the original positive precipitation distribution shifts into a dipole-like pattern. The CEH was dominated by negative precipitation distribution after removing topography. The negative distribution in the CEH were directly governed by the upstream atmospheric circulation from the Atlantic ocean. Thus, accurate predictions of summer precipitation in the CEH should consider both topographic dynamic forcing and the upstream Atlantic ocean signal changes.

ID: 3.8597

Observing Snowfall Using High Altitude Lakes: an Example from Rofental, Alps

Federico Covi
Pritchard, Hamish; Gumber, Siddharth; Orr, Andrew

Abstract/Description

Mountain snowfall is poorly observed, leading to large uncertainties and biases in weather models and therefore in our knowledge of water resources that are important to hundreds of millions of people. We present a novel set of observations from more than 30 sites in the Alps, Himalayas, Rockies, Finland, Greenland and Southern Ocean Islands that overcome key limitations of the conventional instruments that are routinely used to measure falling or accumulating snow water equivalent. We describe how our method uses frozen lakes as sensing surfaces, avoiding notable measurement biases of pluviometers and snow pillows and, most importantly, covering a very much larger surface area. The large scale of our lakes makes them comparable to the grid scale of operational weather models, which has allowed us to test their skill in representing mountain precipitation. We illustrate the instrument design as well as lessons learned from its deployment, and we present examples from these sites, with a particular focus on Austria’s Rofental INARCH catchment. Finally, this unique repository of snowfall measurements has also enabled us to produce a snowfall-optimised version of the atmosphere-only version of the UK Met Office Model (MetUM) at a spatial resolution of 1.5 km with the MetUM able to accurately simulate both the timing and amounts of snowfall observed.

ID: 3.9389

Precipitation and a Central Asian HydroClimate Research Project under the GEWEX Umbrella

Michael Brody
Orenbaev, Sagynbek; Kulikov, Maksim; van Oevelen, Peter

Abstract/Description

In the early 1990s a newly formed GEWEX Program (Then called the Global Energy and Water cycle Experiment now: Global Energy and Water EXchanges project) launched several regional studies to measure and model regional variations in the water and energy cycle. A continental scale experiment (CSE) was needed to develop the ability to measure and model the components of the water and energy cycles over a macroscale land surfaces from smaller scale observations. These projects are now called Regional Hydroclimate Projects and are much broader than just the geophysical science and cover the entire earth system. In the over the 30 years since the first of these projects much has changed. Currently, there are two mature Regional Hydroclimate Projects in Asia, ASIAPEX and Third Pole Environment – Water Sustainability and a new one is being developed in Central Asia. These projects are not operating in a vacuum and have numerous links to other activities, organizations and institutions. A very important aspect of mountain hydrology is the observation, modeling and prediction of precipitation. Mountainous regions have large variability in precipitation in both time and space. Earth observation techniques can help but these also suffer from observational drawbacks in mountainous regions. In this presentation we show the latest developments of these projects, how they relate to other hydroclimate research activities in the region and potential future directions with an emphasis on past precipitation observations and modeling in mountainous environments and what new avenues can be explored to address the various challenges.

ID: 3.9819

Climate Variability and their implication on Kenyas Mt Elgon Grassland

Nelly Masayi
Masayi, Dellila; Anyonje, Hudson

Abstract/Description

Climate change is global challenge that affects montane ecosystems and affecting community livelihoods globally. Mt Elgon ecosystem, Kenya is covered by expansive areas of grasslands that support community pastoralism livelihoods. The changing climatic conditions could adversely affect this ecosystem and the sustainability of their livelihoods. This study sought to establish the effects of climatic variability on natural and semi natural grasslands of Mt Elgon ecosystem between 2000 and 2022. Precipitation data was collected from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) while temperature data was collected from TERRACLIMATE websites. Data on potential evapotranspiration was collected on a 1-month timescale using the Standardized Precipitation Evapotranspiration Index (SPEI) while data on grasslands was derived from Land & Carbon Lab Global Pasture Watch and analysed using Google Earth Engine and ArcGIS software. There has been a 1.97 km2 annual increase in land under natural semi natural grasslands. Precipitation and SPEI recorded an annual increase of 16.66mm and 0.04 respectively while minimum temperature (Tmin) and maximum temperature (Tmax) recorded an annual decline of 0.009ºC, and 0.007ºC respectively. There were increases in precipitation in all the four seasons. Tmax recorded an increase of (0.001 ºC and 0.0006 ºC) while Tmin recorded an increase of (0.0121ºC and 0.0029ºC) for SON and JJA respectively. There was a strong positive correlation between precipitation and size of land under natural semi natural grasslands (r=0.625 p=0.0014) with SON (r= 0.443, p=0.034). There was a significant negative relationship between SPEI and size of land under natural semi natural grasslands (r= 0.683, p=0.0003). There was a significant negative relationship between SPEI values for December January February (DJF) (r=0.5312 p=0.009) and June July August (JJA) (r=0.4077, p=0.053). Regression revealed that precipitation explains about 36.1% of the size of land under grasslands, SPEI explains about 44%. JJA SPEI could explain about (13%) of the changes in grasslands while DJF SPEI explains (24.8%). There is a strong negative correlation between land under grasslands and the size of land under other land uses (r=-0.99971 p=0.0000). Land Use changes precipitation and SPEI are the major determinants of size of land under grasslands and community livelihoods.

ID: 3.10583

A High-Impact Precipitation Event database for the Alps (1961-2023)

Marc Lemus-Canovas
Lemus-Canovas, Marc; Crespi, Alice; Pittore, Massimiliano; Zebisch, Marc; Brunner, Manuela

Abstract/Description

Understanding High-Impact Precipitation Events (HIPEs) in the Alps is essential for evaluating their societal and environmental consequences. To support such understanding, this work aimed to develop a comprehensive HIPEs database for the Alps covering the period 1961–2023, based on long-term and high-quality regional and national gridded precipitation records. We first assessed the consistency of available daily gridded precipitation data within the Alpine region and merged them by maximizing their compatibility, resulting in a spatially comprehensive dataset of ~7km spatial and daily temporal resolution. Next, we identified the HIPEs from both local and regional perspectives. The local threshold for a HIPE was defined as the product of the mean daily precipitation and ten times its standard deviation at each grid point. The regional event magnitude was then quantified as the average of all local exceedances above the threshold occurring on the same day. Finally, we obtained the overall magnitude indicator by multiplying the average local magnitude by the fraction of the affected area. This metric defined the ranked list of events, resulting in more than 1,000 across the Alpine region. We further enriched the database by linking extreme precipitation events with associated recorded impacts, such as river floods, flash floods, and associated fatalities under varying magnitudes of extreme precipitation events through cross-referencing them with events recorded in the Historical Analysis of Natural Hazards in Europe (HANZE) database. Furthermore, we performed a principal component analysis to classify the dominant large-scale atmospheric patterns driving these events. This analysis included an evaluation of key thermo-dynamical and dynamical characteristics, providing deeper insights into the mechanisms triggering HIPEs across the Alps that could be efficiently leveraged by risk practitioners to improve risk management and climate change adaptation strategies.

ID: 3.10678

Evaluation and application of methods for estimating the water equivalent of new snow from daily snow depth recordings

Jan Magnusson
Cluzet, Bertrand; Queno, Louis; Mott, Rebecca; Oberrauch, Moritz; Mazzotti, Giulia; Marty, Christoph; Jonas, Tobias

Abstract/Description

The water equivalent of new snow (HNW) plays a crucial role in various fields, including hydrological modeling, avalanche forecasting, and assessing snow loads on structures. However, in contrast to snow depth (HS), obtaining HNW measurements is challenging as well as time-consuming and is hence rarely measured. In this study, we assessed two semi-empirical methods, HS2SWE and ΔSNOW, for estimating HNW. These methods are designed to simulate continuous water equivalent of the snowpack (SWE) from daily HS only, with changes in SWE yielding daily HNW estimates. We compare both parametric methods against HNW predictions from a physics-based snow model (FSM2oshd) that integrates daily HS recordings using data assimilation. For replicating SWE observations, all methods show similar performance, with small relative biases (≤ 3%). At the same time, ΔSNOW tends to underestimate daily HNW by 17%, whereas FSM2oshd combined with a particle filter data assimilation scheme and HS2SWE provide estimates with lower biases (≤ 5%). Thus, our study demonstrates that daily SWE observations or supplementary measurements like HNW are important for validating the day-to-day accuracy of models simulating the daily evaluation of the snowpack. Furthermore, unlike the empirical methods, the physics-based approach can yield information about unobserved variables, such as total solid precipitation amounts, that may differ from HNW due to concurrent melt. Finally, we showcase how the estimated HNW values for HS recordings can be used for improving spatial snowfall obtained from numerical weather prediction models through an optimal interpolation data assimilation scheme.

ID: 3.11343

Cloudburst Studies, it’s Impacts on Human and Environment- A Case Study of South West Monsoon in 2022-2024 in Sirmaur District of Himachal Pradesh.

Sahil Thakur

Abstract/Description

Cloudbursts are extreme weather events that cause significant disruptions, especially in the mountainous regions. This study tries to examine the cloudburst events that took place in Sirmaur district of Himachal Pradesh between 2022 and 2024(upto 20 July), focusing on their socio-economic and environmental impacts. The study tries to highlights the damage and the intensity of destruction caused by cloudbursts, e.g. loss of human lives, livestock, infrastructure, and livelihoods. Besides the above mentioned primary impacts, cloudbursts trigger secondary disasters such as landslides and flash floods, which further exacerbaes the damage in valleys. A combination of ground surveys and data collection from the District Emergency Operations Center (DEOC) was employed to assess the extent of destruction and response measures taken by the governmental departments(Department of Revenue) and the locals. The ground surveys involved direct field assessments, interviews with affected communities, and observations of the impacted regions. Data from DEOC also provided critical information like meteorological records, damage assessments, and response reports(rehabilitation costs and fundings). These methods ensured a comprehensive understanding of the disasters and their cascading effects. Findings revealed that cloudbursts in Sirmaur have had severe socio-economic repercussions, with damage to agricultural lands, disruption of essential services, loss of domesticated animals in farming communities and increased financial strain on affected families. Environmental consequences, including deforestation, altered river courses during the time of excessive rains, and increased sedimentation and far off deposition due to the above mentioned reasons. Further the work highlight the need for improved disaster preparedness and mitigation strategies in such areas. The study suggests the necessity of enhanced early warning systems, community awareness programs, and robust infrastructure resilience to mitigate future risks.

ID: 3.11430

Evaluation of multi-sources precipitation datasets in ungauged mountainous regions using glacier-hydrological modeling

Lu Li
Li, HuiJie; Chen, Jie

Abstract/Description

Precipitation in mountainous regions remains one of the largest uncertainties in climate and hydrological modeling, particularly due to sparse or absent in-situ observations at high altitudes. This observational gap restricts our ability to accurately quantify precipitation variability, impacting hydrological assessments. To address this, gridded precipitation datasets—including satellite-based products, global and regional reanalyses, and merged datasets—are widely used. However, their reliability in complex alpine environments remains uncertain. This study evaluates the accuracy of five precipitation datasets—ERA5-Land (global reanalysis), TPReanalysis (regional reanalysis), TPMFD and CMFD (merged datasets), and GPM (satellite-based)—in an ungauged alpine watershed of the Tibetan Plateau. Using a physically-based glacier-hydrological modeling approach (WRF-Hydro/Glacier), we assess their ability to reproduce spatial, inter-annual, and extreme precipitation characteristics and their hydrological impacts. Results show that all five precipitation datasets perform similarly in terms of spatial distribution, inter-annual variability and intra-annual distribution, while large discrepancies exist in precipitation amounts, where the watershed-averaged mean annual precipitation varying between 718 and 1593 mm. Generally, the ERA5-Land and TPReanalysis have the largest precipitation amounts, followed by the TPMFD, while the GPM and CMFD have the least precipitation amounts. In terms of the hydrological modeling, ERA5-Land and TPReanalysis simulated runoff show the best agreement with the observed streamflow with the Nash efficiency coefficient (NSE) value above 0.86 for the 2004-2018 period. In particular, the high flow is reasonably captured by those two datasets, as well as the TPMFD. In contrast, the GPM and CMFD considerably underestimate the observed runoff, especially for the high flow. Findings highlight the need for caution when using satellite-derived precipitation datasets as benchmarks in alpine regions with sparse in-situ observations. Furthermore, our results suggest that high-resolution global and regional reanalysis offer significant potential for improving hydrological assessments in data-scarce mountain environments. This study underscores the critical role of physically-based modeling in evaluating precipitation uncertainties and bridging the gap between observation and simulation in complex hydroclimates.

ID: 3.11486

Exploring spatio-temporal characteristics of extreme rainfall events in the tropical Andes

Gabriela Urgiles
Célleri, Rolando; Bendix, Jörg; Orellana-Alvear, Johanna

Abstract/Description

Floods and rainstorms are closely related since extreme rainfall often leads to flooding. Therefore, a deeper understanding of rainfall variability during these events is critical for improving flood forecasting. Rainfall variability is exacerbated in mountainous areas, such as the tropical Andes, where complex orography and atmospheric processes influence rainfall patterns. The analysis of extreme rainfall events in the Ecuadorian Andes has remained a challenge due to the lack of high spatio-temporal resolution data. However, the recent availability of rainfall radar data in this region presents the possibility of improving our knowledge about these extremes. Recently, high-resolution extreme rainfall events in the Tropical Andes have been classified into three groups based on the similarities of their rainfall characteristics (i.e., rainfall accumulation, maximum intensity, and month of occurrence). This study aims to analyze the spatio-temporal patterns within these three groups of extreme rainfall events (i.e., class 1, class 2 and class 3) using high-resolution (5-minute) X-band radar data. This study was carried out with three years of data, from April 2015 to June 2017 and December 2020 to March 2022. The study was conducted in the headwaters of the Paute River basin (2200-4400 m a.s.l) in the south of Ecuador. Extreme rainfall event characteristics (e.g., rainfall intensity, tracking individual storm cores, and the area of the storm) were identified for each event. Class 1 showed the highest values of rainfall intensity (40 mm/5 min), while Class 3 showed the lowest values (20 mm/5 min). Additionally, extreme events in Class 1 occurred between 11:00 and 20:00, with rainfall peaks around 14:00 to 16:00, while extreme events in Classes 2 and 3 occurred throughout the day. However, the intensities during the morning (00:00 to 10:00) remained below 2 mm/5 min. Also, Class 1 showed predominant months of occurrence (October-December). This is the first study that explores the intra-event rainfall characteristics with high spatio-temporal resolution. It enhances our understanding of extreme rainfall behavior and can improve flood forecasting in the tropical Andes.

ID: 3.11820

Perceived Climate Change and Observed Impact on Agriculture in Ladakh Region, India: A Case Study of Suru Valley

Kacho Amir Khan

Abstract/Description

The present study investigates the people’s perception of climate change and its observed impact on agriculture in the Suru valley of the Ladakh region. Due to less number of weather monitoring stations in the region, it is difficult to get daily weather data for the region. In such a scarce climate data region, the ERA5 data was used as an alternative to understanding the annual temperature and precipitation trends. Further, the study explored the perceived climate change and its impacts by collecting data from 270 households and a few in-depth interviews. An increasing trend of temperature and decreasing trend of precipitation was observed. We found that most people perceived climatic changes like less snowfall, less rainfall, high temperature, erratic rainfall, and erratic snowfall in the region, which significantly impacted staple crop production such as barley buckwheat and wheat. However, a gender difference was observed in the perception of climate change. To cope with climate change, people changed their cropping patterns, used pesticides and chemical fertilizers to increase production, and shifted their profession from agriculture to income-based jobs.

ID: 3.12155

Hourly Precipitation Biases and Clausius-Clapeyron Scaling in Convection-Resolving and Convection-Parameterizing Regional Climate Models

Alzbeta Medvedova
Kohlhauser, Isabella; Maraun, Douglas; Rotach, Mathias W.; Ban, Nikolina

Abstract/Description

Regional climate models (RCMs) are crucial tools for understanding and predicting climate change and its impacts, such as precipitation extremes. We investigate the characteristics of hourly precipitation and the associated extremes in RCM ensembles with two resolutions: km-scale (the CORDEX-FPS Convection ensemble with ~3 km grid spacing, where deep convection is represented explicitly), and coarser-scale (~12 km grid spacing, with parameterized convection). The km-scale ensemble is downscaled from the coarser one, and both cover three time periods: evaluation, historical, and end-of-the-century period under the RCP8.5 warming scenario (2000-2009, 1996-2005, and 2090-2099, respectively). Evaluating the model ensembles against data from 179 weather stations in Austria, we study how the intensity, duration, and the time of onset of precipitation depend on mean daily temperature. We then examine how these characteristics change under warming conditions.

It is well established that over the Alps the coarser RCMs produce too much light and persistent precipitation which is triggered too early in the day. We find that these shortcomings in models with parameterized convection become more pronounced with rising temperatures. We show that the km-scale ensemble closely matches observations and greatly outperforms the coarser ensemble in capturing the investigated hourly precipitation characteristics, especially at higher temperatures and on days with heavy rainfall. As high temperatures are expected to become more common in future climates, our results imply that coarser RCMs suffer from more severe biases in hourly precipitation in the future than under present climate conditions, especially for short-duration extremes.

In this light, we also assess the ability of both km-scale and coarser RCM ensembles to capture the Clausius-Clapeyron scaling of extreme precipitation with temperature, and discuss how model deficiencies in the coarser ensemble affect this relationship.

In summary, our findings highlight the importance of km-scale RCMs for accurate simulations of hourly precipitation and its extremes, particularly in the warming climate.

ID: 3.12216

A 1-km gridded dataset of daily precipitation observations for the Adige River catchment (1990-2023): data evaluation and assessment of systematic errors through snow height records

Azadeh Yousefi
Crespi, Alice; Bertoldi, Giacomo; Bozzoli, Michele; Galletti, Andrea; Zebisch, Marc; Pittore, Massimiliano

Abstract/Description

Climate change is increasingly influencing environmental and socio-economic systems, necessitating accurate meteorological datasets to assess regional climate variability and related risks. Due to their key role for water storage and supply, accurate precipitation records for Alpine regions are crucial for understanding ongoing trends in precipitation regime as well as for modelling hydrological processes. However, transboundary river basins often suffer from data fragmentation due to inconsistencies in data collection, processing, and harmonization across regional and national providers. The mountainous nature of the territory poses an additional challenge for the retrieval of accurate precipitation fields, due to the general reduction of station data availability in high-elevation areas and systematic errors due to rain-gauge under-catch, especially for snowfall. In this framework, we developed a high-resolution (1-km) gridded dataset of daily precipitation spanning 1990–2023 for an extended area centered on the Adige River catchment starting from approximately 700 rain gauges from multiple data providers in Italy and surrounding countries. The Adige River catchment, located in the south-eastern Alps, represents an important Italian region providing water to multiple sectors and over a wide downstream area. The interpolation method based on a two-step procedure incorporating orographic influences was selected by comparing the performance of different approaches and tuned to minimize the interpolation errors. To estimate and address the underestimation of precipitation in the high-mountain portions of the basin, a first test for exploiting available snow height measurements and quantifying the magnitude of potential corrections was carried out. Specifically, we investigated and discussed the benefits and challenges of using of snow measurement sites as virtual rain gauges, through deriving the water equivalent of new snow, in mountain locations to get a more reliable representation of precipitation fields at high elevation. The final dataset was evaluated against existing large-scale precipitation products covering the area, showing the improved spatial representation offered by the enhanced data density and grid resolution. This research is conducted within the framework of the RETURN Extended Partnership (European Union Next-GenerationEU, National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022,

ID: 3.12225

Orographic rain shadows in the Andes: are they weakening with climate change?

Sihan Li
Potter, Emily; Jones, Julie; Bhattacharjee, Sutapa; Davies, Bethan; Ely, Jeremy

Abstract/Description

Orographic rain shadows play an important role in shaping regional climates, ecosystems, and water resources in the Andes. As moist air from the Amazon/the Pacific rises over the Andes, it generates significant rainfall and snowfall on the windward side, replenishing glaciers, lakes, and river systems that support agriculture, hydropower, and drinking water supplies for local communities, while leaving the leeward side significantly drier. Given that orographic precipitation serves as a vital freshwater source in this region, improving our understanding and prediction of its response to climate change is crucial.
However, characterizing how orographic precipitation responds to climate change in the Andes remains challenging, due to the complexity of warming’s effects on orographic processes. In addition to thermodynamic changes (increased atmospheric moisture), warming could raise freezing levels, causing a shift from snow to rain, resulting in less snowpack, faster runoff, and higher flood risk. Shifts in wind patterns and static stability could alter atmospheric moisture transport and mountain wave dynamics, affecting where and how much precipitation falls. Current global and regional climate models applied in studying the Andes often struggle to accurately represent the fine-scale topography and atmospheric dynamics involved in orographic precipitation. Previous research (mostly Western U.S. focused) on orographic rain shadows’ response to warming—primarily relying on idealized simulations or lower resolution climate models that cannot fully capture convection—found higher fractional increases in precipitation extremes on the climatological leeward slope compared to the windward slope, indicating a future weakening of orographic rain shadows in midlatitude mountain ranges.
In this study, we assess how orographic rain shadows respond to climate change across the different climate zones of the Andes. We present results comparing a contemporary time period (2000-2024) with a future time period (2140-2050) from convection-permitting (4km) simulations conducted with the Weather Research and Forecasting model (version 4.6) over the entire Andes. We further investigate the role played by various physical factors in determining changes in orographic precipitation extremes. Given the Andes’ role as water towers for South America, understanding and adapting to shifts in orographic rain shadows is crucial for ensuring long-term water security.

ID: 3.12305

Impacts of triple-dip La Niña on the Andean climate

Sutapa Bhattacharjee
Potter, Emily; Hall, Richard; Li, Sihan; Jones, Julie; Davis, Bethan; Ely, Jeremy

Abstract/Description

Triple-dip La Niña was most recently observed during 2020-2023, during which a series of unusual and extreme meteorological phenomena occurred worldwide. This rare climatic phenomenon is characterized by prolonged La Niña conditions and is defined by Oceanic Niño Index (ONI) values below -0.5°C for three consecutive years. Triple-dips have only been observed four times during the period of reliable reanalysis data since 1950. The first observed triple-dip La Niña in this period occurred between 1954 and 1956 and was relatively weak, followed by the strongest episode from 1974 to 1976, and another between 1998 and 2001, apart from the recent episode Although the exact mechanisms behind these exceptional events are not fully understood, they appear to recur in every 20–25 years approximately.
As part of the Deplete and Retreat: The Future of Andean Water Towers project, this study investigates the impact of these four triple-dip La Niña episodes on temperature and precipitation dynamics across the Andes, which could directly influence the region’s water reserves. The latitudinal, topographical, and geographical diversity of the Andean mountains makes land–atmosphere interactions highly complex, which is further intensified during such extraordinary extreme climatic conditions. We use high-resolution Weather Research and Forecasting (WRF) model simulations (4 km resolution) to understand the effect of the triple-dip La Niña events on the regional Andean meteorological extremes. Here, we present the modelled results for the period of peak event intensity, identified by very high ONI value for at least three consecutive months, which also roughly overlaps with the snow accumulation season of the region. We further evaluate CMIP6 historical simulations to assess their ability to capture triple-dip La Nina episodes and investigate similar signatures in future projections to determine the potential recurrence of such episodes in the future. This study contributes to enhance our understanding of the patterns and regional climate dynamics associated with this extraordinary climate phenomenon and its implications on Andean water resources.

ID: 3.12463

The influence of westerly moisture transport events on mountain regions in Eastern Africa

Robert Peal
Collier, Emily

Abstract/Description

Rapidly retreating glaciers in Eastern Africa, such as at the summit of Kilimanjaro, are highly sensitive to moisture and precipitation variability. Previous research has shown that on sub-seasonal timescales, precipitation variability in this region is closely related to the wind direction, with precipitation more probable on days where the wind blows anomalously from the west, advecting moisture from the Congo basin. However, the role of westerly moisture transport events on precipitation in high elevation areas, and the impact of these precipitation events on glaciers in the region, has received relatively little attention. Here, we use the ERA5 reanalysis and 20 years of surface height change observations from the glacier on Kilimanjaro to investigate how regional moisture transport patterns are manifested at high elevations in Eastern Africa and the role they play in driving sub-seasonal precipitation variability on Kilimanjaro.

ID: 3.12487

The Role of the European Center for Cloud Ambient Intercomparison (ECCINT) within ACTRIS and the Topical Center for Cloud In Situ Measurements (CIS)

Christian Maier
Ludewig, Elke; Bachleitner, Thomas; Lacher, Larissa; Höhler, Kristina; Möhler, Ottmar; Büttner, Nicole; Fösig, Romy; Schwarzenböck, Alfons; van Pinxteren, Dominik; Käfer, Uwe

Abstract/Description

The impact of climate change on cloud properties and cloud occurrence remains an area of active research. To enhance our understanding and improve cloud representation in climate models, the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) has established the Topical Center for Cloud In Situ Measurements (CIS). The mission of ACTRIS-CIS is to develop a monitoring network for key cloud properties, in conjunction with the Centre for Cloud Remote Sensing, ensuring comprehensive observation of cloud amount, altitude, and opacity. The European Centre for Cloud Ambient Intercomparisons (ECCINT), hosted at the Sonnblick Observatory (SBO) in Austria, is part of the ACTRIS Topical Centre for Cloud In Situ measurements (CIS) being responsible for implementing the cloud physical parameters such as Cloud Liquid Water Content (LWC) and Cloud Effective Radius (Reff). The focus is particularly on LWC, a central variable for the water cycle, weather forecasts and climate models. LWC not only influences the probability of precipitation and the redistribution of water between the atmosphere and the surface, it also plays a major role in determining cloud properties and thus their influence on temperature, radiation and precipitation. LWC data improves simulations of global warming and precipitation patterns in long-term climate projections, but also in weather forecasts. As part of the Austrian geological, geophysical, climatological and meteorological service, GeoSphere Austria, the Sonnblick Observatory conducts regular cloud in situ intercomparisons with all relevant and new developed cloud probes to ensure the comparability of various measurements at European sites and improve the understanding of cloud-aerosol interactions. During two international field studies in 2022 and 2024, the focus was on capturing the cloud physical base parameters of liquid water content and effective radius. The aim of these measurement campaigns was to compare different observation techniques to develop and improve Standard Operating Procedures (SOPs) for ACTRIS. Here we present an overview of all ECCINT related activities within ACTRIS and the European Cloud In Situ community as well as out coming results and conclusions of our intercomparison campaigns for cloud droplet probes at Sonnblick Observatory.

ID: 3.12514

Enhancing mountain precipitation insights via crowdsourcing and regional models

Marie Pontoppidan
Opach, Tomasz; Rød, Jan Ketil

Abstract/Description

Validating precipitation in high-resolution climate models is challenged by insufficient spatial and temporal observations, particularly for precipitation in complex and mountanious terrain. Traditional datasets, relying on sparse official weather stations and gridded observations, often lack the spatio-temporal resolution needed for accurate localized studies. This study is two-fold and investigates the potential of integrating Personal Weather Stations (PWSs) to enhance spatial precipitation distribution insights in complex terrain, and the potential to increased spatial datasets to validate regional climate models. 1) A case study of a convective burst also demonstrated the value of PWSs. The intense 45 minute event recorded precipitation of 55.8 mm at a PWS, compared to 28.1 mm at the nearest MET station, kilometers away. This highlighted PWSs ability to capture high localized variability and provided critical data during extreme events. 2) After a quality control, the precipitation from 87% of about 600 PWSs in Western Norway was meshed with 90 official meteorological stations. PWSs provided significantly improved spatial coverage, especially in populated areas, revealing spatial variability often missed by traditional gridded precipitation datasets. Simulations with the Weather Research and Forecasting (WRF) regional climate model match observed spatial variability and thereby supports the reliability of PWS data. In conclusion, PWS networks significantly enhance observational coverage, aiding high-resolution model validation and local precipitation understanding. As PWS numbers grow, refined quality control measures will further solidify their role in meteorological research and emergency preparedness, particularly for localized extreme weather events in complex terrain.

ID: 3.13128

Rainfall and fog in the paramo ecosystem, the water tower of the tropical Andes

Rolando Célleri

Abstract/Description

The headwaters of the tropical Andes are covered by the paramo ecosystem, which is recognized as a reliable water source for Andean communities. Despite its importance, little was known about precipitation inputs into this ecosystem. Fifteen years ago, we established the Zhurucay Ecohydrological Observatory at 3,700 meters above sea level in southern Ecuador to enhance our understanding of the processes that support hydrological services, including water regulation and the factors influencing water quality. In addition to standard meteorological stations, Zhurucay is equipped with a laser disdrometer, fog collectors, an eddy covariance tower, and other specialized sensors to monitor the water balance. This poster presents the findings gathered over this period. Notably, drizzle emerged as the primary water input to the system, accounting for over 80% of total precipitation. Fog, while present year-round, was not a significant direct water source but contributed indirectly by reducing evaporation and transpiration, supporting other ecosystem functions. We conclude that long-term observatories are essential for developing sustainable solutions for water and ecosystem management.

ID: 3.13804

Spatial and Temporal variability of Extreme Precipitation Events (EPEs) and their future projection over the Himalayan Ganga Basin (HGB)

Hemant Singh Bisht
Chen, Ruishan; Kumar, Pankaj; Bandooni, Suresh Kumar; Rongpi, Rumi

Abstract/Description

The Himalayas, a tectonically active, topographically complex, and strong modulator of weather and climate patterns over high mountain Asia, are highly vulnerable to a number of natural hazards, including extreme precipitation events (EPEs), which are exacerbated by climate change. Such events introduce significant losses to life, infrastructure, agriculture, and, in turn, the region’s economy. This paper provides an assessment of long-term (1951–2023) precipitation extremes and projections (2024-2090) over the Himalayan Ganga Basin (HGB) using state-of-the-art, high-resolution Indian Meteorological Department (IMD) and statistically downscaled NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) during southwest monsoon season (JJAS) under different scenarios (SSPs). The data includes historical data (1951–2023) and future projections (2024–2090) from various global climate models (GCMs). The selected extreme precipitation indices are classified into intensity, frequency, and duration measures. The findings reveal geographically heterogeneous and mixed trends among different scenarios with clustering in Dehradun and Ukhimath; however, extremes are intensifying and becoming more frequent over the years in the region during both seasons, although large numbers of 1-day EPEs have been recorded during the decade 1961–1970. The change in rainfall in the northern parts of the basin is relatively higher than that in the southern parts of the basin. Stations at higher altitudes recorded extreme rainfall during the October and January months, whereas plain area stations recorded extreme rainfall during the June to September monsoon months. The results also suggest that monsoon rainfall in the region could increase in the near future and more significantly in the far future, with the amount of rainfall during the monsoon season expected to rise under both scenarios. Extreme rainfall events, such as the highest 1-day and 5-day rainfall, are projected to become more frequent, while the number of dry days in between is expected to decrease. These findings highlight the importance of planning for more intense and frequent rainfall in future climate resilience efforts in the region.

FS 3.101: High Mountain Asia’s cryo-hydrosphere: process understanding, downstream impacts, and prospects for operational solutions

FS 3.236: Agricultural and non-agricultural jobs in rural communities and attractiveness of mountain areas

FS 3.235

Mountain Precipitation in a Changing Climate/Mountain Precipitation Change

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