Heavy Rainfall Events Research Articles

Impact of assimilation of DWR reflectivity and radial velocity on simulation of active monsoon precipitation over Indian region

ABSTRACT This study explores the application of National Centre for Medium Range Weather Forecasting Unified Model-Regional (NCUM-R) modelling framework to simulate convective rainfall events during active summer monsoon conditions in the Indian region. The primary focus is on assessing the impact of assimilating reflectivity and radial wind data (RAD) from the Indian Doppler Weather Radar (DWR) networks with respect to control (CTL) experiment. By comparing model-simulated rainfall with merged satellite-rain gauge data, the analysis demonstrates that assimilation significantly enhances the accuracy of the analysis compared to relying solely on the background model analysis. The assimilation system with DWR data shows a substantial reduction in biases, indicating improved alignment with observations. Notably, assimilation of DWR observations positively influences wind patterns and rainfall predictions, particularly in regions with deep convection, leading to enhanced wind speeds and rainfall accuracy. The evaluation of RAD and CTL experiments is based on different rainfall categories, such as light-to-moderate and moderate-heavy rain events, highlighting the significant impact of assimilation of DWR observations on forecasts. The RAD experiment surpasses the CTL in simulating rainfall, reducing biases, and enhancing predictive capabilities, especially showing better performance in initial forecast hours and reduced gradually. Various statistical skill scores like Probability of Detection (POD), False Alarm Rate (FAR), Equitable Threat Score (ETS), and Frequency Bias (FBIAS) highlight the improved performance of the RAD experiment in predicting rainfall amount and location, particularly for moderate to heavy rainfall events. Therefore, the assimilation of reflectivity and radial velocity data improves dynamic and thermodynamic fields, enhancing wind convergence and cloud prediction accuracy of convective system. Further research is recommended to optimize background error settings and observational error specifications for convective systems over the Indian region.

Microphysical Evolution of Heavy Rainfall During a Bow Echo Event in South China: Characteristics and the Mesovortex‐Related Impacts

AbstractA heavy rainfall (HR) event caused by a bow echo struck South China on 11 April 2019. Two extremely HR periods were identified within this event, and the second rainfall period led to severe flooding in Shenzhen city, resulting in 11 fatalities. The first rainfall period was dominated by warm‐rain processes, while the development of the second period was closely related to the intensification of ice‐phase processes. The contribution of raindrops from the melting process played a crucial role in the formation of extreme rainfall, which achieved a high rain rate (RR) exceeding 120 mm hr−1. The enhancement of the ice‐phase processes during the second rainfall period was found to be closely associated with the development of a low‐level mesoscale vortex (MV). Due to the complementary non‐linear dynamical accelerations induced by the MV, the vertical velocity within the convective system rapidly intensified, leading to a more upright and deeper convective organization. As a result, more water vapor and supercooled water were lifted above the freezing level, which increased the presence of ice‐phase particles with the potential to melt, subsequently contributing to the extreme high RR. This study investigates the microphysical characteristics of two periods of HR that occurred during and after the development of a MV within a bow echo event, and examines the key microphysical processes affected by the MV, which partially contributed to the second HR period.

Solidified lake sediment with industrial waste and construction waste used as barrier cover material: mechanical strength, water resistance performance, and microscopic analysis

ABSTRACT This study introduces a novel landfill cover material, employing lake sediment as a substrate, stabilised with fly ash, slag, desulfurisation gypsum and construction waste. The mechanical properties, including shear strength parameters, unconfined compressive strength, hydraulic conductivity, volumetric shrinkage, and water content, of the solidified sludge were evaluated. The microscopic mechanism of the solidified sludge were investigated through XRD, FTIR, and SEM-EDS techniques. A novel three-layer composite capping cover system for landfills is proposed, comprising an upper capillary barrier layer, a middle drainage layer and a bottom impermeable layer . Indoor rainfall simulation tests were conducted to assess the water retention performance of this capping cover system under repeated moderate, heavy, and torrential rainfall events. The early strength of the solidified sludge exhibited rapid development, with cohesion and internal friction angle reaching 382.56 kPa and 57.67°, respectively, after 3 days. After 28d, the unconfined compressive strength ranged from 6.93 to 14.29 MPa, with hydraulic conductivity between 3.98–23.1 × 10−8cm/s. The hydration reactions of the industrial waste residues resulted in the formation of Ettringite, Gypsum, and hydrous calcium (aluminum) silicates. The Ettringite and Gypsum crystals formed an internal support framework, while the generation of gel-like substances such as C-S-H and C-A-S-H facilitated product aggregation. The RSM was employed to optimise the material ratio of the solidified sludge, while the Pearson coefficient facilitated correlation analysis. This study provides valuable data for designing landfill solidified sludge cover systems and offers a new approach for the co-disposal of sludge and industrial waste.

On the relay propagation of deep convection leading to a heavy rainfall event in a weak‐wind urban environment

On the relay propagation of deep convection leading to a heavy rainfall event in a weak‐wind urban environment

Stormy Subtropics and Stratiform South: Radar‐Based Classification and Analysis of Australian Rainfall Events

AbstractAustralia has a large operational weather radar network spanning multiple climatic regimes. However, data from this network is not commonly used to obtain heavy rainfall event characteristics. Drawing on the methodology presented in Bowden et al. (2024, https://doi.org/10.1029/2023jd039253), areal radar variables are used to identify and characterize rainfall events at 15 Australian radar sites over an 11‐year period. Rainfall events over all sites are grouped into three clusters based on their characteristics—stratiform (low rainfall intensities and small contributions from convective areas), convective (localized with high rainfall intensities and strong contributions from convective areas), and persistent (long‐lasting, moderately intense, extensive events). Further, the top 100 events by accumulation and intensity were identified for each site. Stratiform cluster events are most common in the cool season, convective cluster events are most common in the warm season, and persistent cluster events exhibit strong regional variation in seasonal occurrence over Australia. Convective cluster events are most common at tropical and subtropical sites, and stratiform cluster events are most common at mid‐latitude sites. Persistent cluster rainfall events occur least frequently, but make significant contributions to rainfall totals around Australia. Furthermore, almost all high accumulation rainfall events belong to the persistent cluster, and most high intensity events belong to the convective cluster. Examination of rainfall event environments with reanalysis data shows that persistent cluster events and high accumulation events both occur in environments with strong positive column moisture anomalies and mid‐level ascent, consistent with past findings on Australian heavy rainfall environments.

Synchronization frequency analysis and stochastic simulation of multi-site flood flows based on the complicated vine copula structure

Abstract. Accurately modeling and predicting flood flows across multiple sites within a watershed presents significant challenges due to potential issues of insufficient accuracy and excessive computational demands in existing methodologies. In response to these challenges, this study introduces a novel approach centered around the use of vine copula models, termed RDV-Copula (reduced-dimension vine copula construction approach). The core of this methodology lies in its ability to integrate and extract complex data before constructing the copula function, thus preserving the intricate spatial–temporal connections among multiple sites while substantially reducing the vine copula's complexity. This study performs a synchronization frequency analysis using the devised copula models, offering valuable insights into flood encounter probabilities. Additionally, the innovative approach undergoes validation by comparison with three benchmark models which vary in dimensions and nature of variable interactions. Furthermore, the study conducts stochastic simulations, exploring both unconditional and conditional scenarios across different vine copula models. Applied in the Shifeng Creek watershed, China, the findings reveal that vine copula models are superior in capturing complex variable relationships, demonstrating significant spatial interconnectivity crucial for flood risk prediction in heavy-rainfall events. Interestingly, the study observes that expanding the model's dimensions does not inherently enhance simulation precision. The RDV-Copula method not only captures comprehensive information effectively but also simplifies the vine copula model by reducing its dimensionality and complexity. This study contributes to the field of hydrology by offering a refined method for analyzing and simulating multi-site flood flows.

Runoff Simulation and Waterlogging Analysis of Rainstorm Scenarios with Different Return Periods on Campus: A Case Study at China University of Geosciences

Urban flooding disasters are increasingly prevalent because of global climate change and urbanization. University campuses, as independent functional zones, exhibit complex rainfall–runoff dynamics. This study focuses on the China University of Geosciences, using data from two extremely heavy rainfall events and on-site waterlogging investigations in Wuhan in 2020 and 2021. A stormwater management model was employed to simulate campus catchment runoff and pipe network performance under rainstorm scenarios of various return periods, illustrating the spatial and temporal evolution of waterlogging on the campus. The simulation results indicate that the discharge at the main outlets aligned with rainfall patterns but exhibited a delayed response. During an overload period exceeding one hour, the ratios of overflow nodes and overloaded conduits reached 72.22% and 57.94%, respectively. Ponding was concentrated mainly in the southwest region of the campus, with the maximum ponding depth reaching 0.5 m. Future flood mitigation measures, such as enhancing permeable surfaces, upgrading pipeline infrastructure, and promoting rainwater reuse, could support the development of a “sponge campus” layout to alleviate flood pressure and enhance campus sustainability and resilience.

The Role of the Subtropical Jet Stream in Dry Season Severe Caribbean Rainstorms: Climatology and Composite Analyses

Abstract Although high-impact heavy rainfall events in the Caribbean are typically associated with tropical cyclones (TCs) during the wet season, significant heavy rainfall events can also occur during the Caribbean dry season, absent of TCs. Dry season severe Caribbean rainstorms (CRs) can produce rainfall totals that surpass climatological dry season monthly mean rainfall, ranging from 25 to 200 mm, by >3 sigma over a relatively short duration (2–16 days), resulting in infrastructure- and life-threatening flooding and mudslides. This paper introduces a 35-yr (1983–2017) dry season severe CR climatology derived from the PERSIANN-CDR precipitation dataset, revealing that dry season severe CRs occur, on average, eight times per year with some interannual variability and exhibit a seasonality that includes relative maxima in November/December and April/May as well as a relative minimum in February. Self-organizing map (SOM) analyses are applied to detect subtropical jet stream (STJS) flow patterns governing events in this climatology which include an upper-level trough reaching the Caribbean (Trough cases, 23% of all events), a frontal boundary extending into the Caribbean attendant to an extratropical cyclone (EC) at midlatitudes (EC Front cases, 54% of all events), or a potential vorticity stream (PVS) forming near the Caribbean (PVS cases, 7% of all events). In these events, extratropical forcing, occasionally combined with orographic forcing, can promote intense, organized, and widespread deep, moist convection that produces heavy rainfall. The remaining events do not have a discernable extratropical connection and are not considered to be influenced by the STJS (16% of events). Significance Statement High-impact heavy rainfall events in the Caribbean are typically associated with tropical cyclones during the wet season, but significant heavy rainfall events can also occur during the Caribbean dry season without tropical cyclones. Dry season Caribbean rainstorms (CRs) can result in infrastructure- and life-threatening flooding and mudslides from rainfall totals that substantially surpass normal dry season monthly rainfall in a short duration (2–16 days). A 35-yr dry season severe CR climatology is constructed, indicating that these events occur on average eight times per year. The subtropical jet stream is recognized as an important driver and influencer of thunderstorms with heavy rainfall in most (84% of all cases) dry season severe CRs. The results of this study could help Caribbean weather forecasters recognize the nature of dry season severe CRs and associated weather patterns to provide more information and advanced warning to local emergency management and the public.

Topographical assessment of electrical distribution system vulnerability to heavy rainfall events

Topographical assessment of electrical distribution system vulnerability to heavy rainfall events

The Teleconnection between Rainfall over the Northeastern Slope of the Tibetan Plateau and Downstream Regions: Insights from 20 Years of Heavy Rainfall Events

The Teleconnection between Rainfall over the Northeastern Slope of the Tibetan Plateau and Downstream Regions: Insights from 20 Years of Heavy Rainfall Events

Characteristics of Mesoscale Convective Systems and Their Impact on Heavy Rainfall in Indonesia’s New Capital City, Nusantara, in March 2022

Nusantara, the new capital city of Indonesia, and its surrounding areas experienced intense heavy rainfall on 15–16 March 2022, leading to devastating and widespread flooding. However, the factors triggering such intense heavy rainfall and the underlying physical mechanisms are still not fully understood. Using high-resolution GSMaP (Global Satellite Mapping of Precipitation) data, we show that a mesoscale convective system (MCS) was the primary cause of the heavy rainfall event. The rainfall peak occurred during the MCS’s mature stage at 1800 UTC 15 March 2022, and diminished as it entered the dissipation stage. To understand the large-scale environmental factors affecting the MCS event, we analyzed contributions from the MJO, equatorial waves, and low-frequency variability to column water vapor and moisture flux convergence. Results indicate a substantial influence of the MJO and equatorial waves on lower-level (boundary layer) meridional moisture flux convergence during the pre-MCS stage and initiation, with their contributions accounting for up to 80% during the growth phase. Moreover, while La Niña and the Asian monsoon had negligible impacts on MCS moisture supply, we find a large contribution from the residual term of the water vapour budget during the maturation and decay phases of the MCS. This suggests that local forcing (such as small-scale convection, local evaporation, land-surface feedback, and topography) also contributed to modulation of the intensity and duration of the MCS. The results of this study can help in our understanding of the potential causes of extreme rainfall in Nusantara and could be leveraged to improve rainstorm forecasting and risk management across the region in the future.

Sub-daily scale rainfall extremes in India and incongruity between hourly rain gauges data and CMIP6 models

Self-recording rain gauges hourly rainfall data from 1969 to 2010 have been utilized to identify rain events at a sub-daily scale. At the sub-daily scale, a significant decrease in the frequency of heavy rainfall events (HREs) is observed over central India and northeast India, while an increase is observed over the northern west coast of India. Frequency of short-duration HREs over central India and long duration HREs over northern west coast of India is increased in the recent decades than in earlier decades. Incongruity with the observations, CMIP6 historical and AMIP high temporal resolution models are not able to simulate the short-duration HREs and, in turn, the observed trends at a sub-daily scale over the India landmass. The inability of CMIP6 models to predict short-duration HREs suggests caution in predicting future projections of extreme precipitation at a sub-daily scale and highlights the need for further improvements in climate models.

The Impact of Rainfall on Water, Energy, Industry and Economic Growth—Based on Empirical Data from 29 Provinces in China

Sustainable urban development requires good interaction between water, energy, infrastructure and socio-economic areas. In the context of more frequent heavy rainfall and flooding events, managing the subsystems within the city in an integrated manner and realizing sustainable development have become popular research topics. Based on the above analysis, this paper constructs a water, energy, industry and economic growth system. It also introduces rainfall as an exogenous variable into the model in order to simulate the process of interactions between subsystems within a city and achieve sustainable development. By measuring the dynamic changes and spatial distribution characteristics of the efficiency values of the total water–energy–industry and economic growth system and each subsystem in 29 provinces in China, the following conclusions are drawn: (1) Most of the provinces are in the situation of “high-efficiency–negative growth” or “low-efficiency–positive growth”, and the constraints for them to reach the state of “high efficiency–positive growth” are due to the water subsystem. (2) The low-efficiency provinces are mainly concentrated in the central region, and the spillover effect of the low-efficiency provinces on the neighboring regions is more notable than that of the high-efficiency provinces. (3) The addition of rainfall improves the total efficiency in most provinces, with the most obvious improvement in the efficiency of the water subsystem. (4) The efficiency value of the industry and economic growth subsystem is relatively less affected by the amount of rainfall, but excessive rainfall will also have a negative impact. Finally, relevant policy recommendations are made to inform the relevant government departments in formulating policies related to addressing climate change and achieving sustainable urban development.

Rainfall Erosivity Projection in South‐East Australia Using the Improved Regional Climate Simulations

ABSTRACTRainfall erosivity is one of the most dynamic factors in the soil erosion process. The increase in soil erosion caused by high rainfall erosivity, and the subsequent loss of soil nutrients, can lead to reduced food production and ecosystem services. This research program under the New South Wales (NSW) Climate Change Adaptation Strategy, assesses rainfall pattern change, rainfall erosivity and erosion risk across NSW under future climate conditions. Daily rainfall erosivity and erosion risk were modelled by Revised Soil Loss Universal Equation (RUSLE) approach and compared with that driven by observed rainfall data. Future rainfall erosivity and soil erosion risk change were investigated from daily precipitation projection of the updated NSW and Australian Regional Climate Modelling (NARCliM1.5) for two future scenarios, RCP4.5 and RCP8.5, from the historical (1986–2005) to far future (2060–2079) periods. The annual average rainfall erosivity is projected to increase about 8% under RCP 4.5 and further decrease 5% under RCP 8.5 in NSW due to the predicted temperature rises. More frequent heavy rainfall events are projected to occur during summer (December–January–February), and the rainfall from these extreme rainfall events is expected to account for 51% of the total annual rainfall in the far future. NARCliM‐derived results underestimate annual rainfall erosivity compared with observation‐derived erosivity. There are greater instability (root mean squared error [RMSE]: 803.2) and erosivity uncertainty (Bias: 16%~48%) in high rainfall zones. At a monthly scale, dry months (June–July–August) are becoming drier, while wet months (December–January–February) are becoming wetter and more erosive. 67% of NSW is predicted to experience increased rainfall erosivity under RCP4.5, whereas most of NSW will shift to drought and its consequent effects under the high‐end emission scenario (RCP 8.5). To address the dual challenges of excessive wetness in coastal and north‐east NSW and increasing aridity in Western NSW, it is necessary to develop climate change adaptation management strategies based on high‐risk areas and monthly or seasonal conditions. With the emerging launch of NARCliM2.0, we anticipate further improvements of these predictions will be achieved by more accurate models and data at higher spatial and temporal resolutions.

Observational evidence of impact of heavy rainfall events on surface energetics and soil variables over a tropical station Tirupati

Two back-to-back heavy rainfall events (HREs) produced enormous rainfall over a pilgrim city, Tirupati, located in the southern peninsular India, during 10–12 November 2021 (149.2 mm) and 17–19 November 2021 (234.2 mm). Surface measurements at Yerpedu, Tirupati (13.74°, 79.60°E) showed a drop of 2–3 °C in temperature and 8 hPa in pressure during HREs, indicating that these HREs were associated with two landfalling tropical depressions from the Bay of Bengal. The sporadic HREs in the past three decades caused floods over Tirupati and devastated landslides in the sacred Tirumala hills especially during the second HRE. Fundamental understanding of diurnal cycle of surface radiation is critical to model the climate. The effect of HREs on the surface essential climate variables at diurnal scale indicate a reduction in peak solar and net radiations by 500 W m−2 (> 62.5 %). Similar to observations, ERA5 reanalysis also indicates a significant reduction in net surface solar and thermal radiations, which are nearly equal in terms of % but vary in magnitude. Net solar and thermal radiations show dominant diurnal cycles with a reduced (66.7 % and 74.4 % respectively) diurnal amplitudes from no-rain to HREs. Soil moisture drydown curves at 5- and 10-cm depths shows 3 h long e-folding decay time for HREs, indicating an enhanced soil moisture memory after HREs. The soil drying process takes longer time at 10 cm than at 5 cm depth. Soil temperatures are significantly low at 5 cm to 30 cm depths and less than the 50 cm depth with weak diurnal variation during the events. The reflectivity (Z)-rain rate (R) and shape (μ)-slope (Λ) relations show variations from HREs to normal rain events. Knowing the importance of land-atmospheric processes feedbacks in model predictions at diurnal scale, this study quantified the HREs impact on surface essential climate variables, especially the energy balance and soil variables.

Optimization of hybrid data assimilation for cases of very heavy rainfall events over the Indian region

Optimization of hybrid data assimilation for cases of very heavy rainfall events over the Indian region

Impact of extreme rainfall and flood events on harmful cyanobacterial communities and ecological safety in the Baiyangdian Lake Basin, China

Globally, climate change has intensified extreme rainfall events, leading to substantial hydrological changes in aquatic ecosystems. These changes, in turn, have increased the frequency of harmful algal blooms, particularly those of cyanobacteria. This study examines cyanobacterial community dynamics in the Baiyangdian Lake Basin, China, after heavy rainfall and flooding events. The aim was to clarify how such extreme hydrological events affect cyanobacterial populations in floodplain ecosystems and assess related ecological risks. The results demonstrated a significant increase in cyanobacterial diversity, exemplified by an increase of the Shannon diversity index from an average of 1.7 to 2.1 (p < 0.05). Following heavy rainfall and subsequent flooding, the average relative abundance of cyanobacteria in the microbial community increased from 7.59 % to 9.62 %, along a notable rise in the abundance of harmful cyanobacteria. The community structure exhibited notable differences after flooding, showing an increase in species richness, but a decrease in community tightness and clustering, as well as a reduction in niche overlap among harmful cyanobacteria. Environmental factors such as dissolved oxygen, water temperature, and pH were identified as crucial predictors of harmful cyanobacterial community differences and abundance variations resulting from flooding. These findings provide a critical framework for predicting ecological risks associated with the expansion of bloom-forming cyanobacteria in large shallow lake basins, particularly under intensified rainfall and flooding events. This insight is essential to anticipate potential ecological disruptions in sensitive aquatic ecosystems.

Regional Impacts Poorly Constrained by Climate Sensitivity

AbstractClimate risk assessments must account for a wide range of possible futures, so scientists often use simulations made by numerous global climate models to explore potential changes in regional climates and their impacts. Some of the latest‐generation models have high effective climate sensitivities (EffCS). It has been argued these “hot” models are unrealistic and should therefore be excluded from analyses of climate change impacts. Whether this would improve regional impact assessments, or make them worse, is unclear. Here we show there is no universal relationship between EffCS and projected changes in a number of important climatic drivers of regional impacts. Analyzing heavy rainfall events, meteorological drought, and fire weather in different regions, we find little or no significant correlation with EffCS for most regions and climatic drivers. Even when a correlation is found, internal variability and processes unrelated to EffCS have similar effects on projected changes in the climatic drivers as EffCS. Model selection based solely on EffCS appears to be unjustified and may neglect realistic impacts, leading to an underestimation of climate risks.

Influences of vegetation types and near-surface characteristics on hydrodynamics and soil erosion of steep spoil heaps under rainfall and overland flow conditions

Spoil heaps, are characterized by loose structure, high infiltration, steep slopes, etc, and have become a source of soil erosion and geological disasters. Vegetation was regarded as an effective way to curb soil erosion of spoil heaps. However, few studies have been conducted to explore the effects of vegetation types and their near-surface characteristics on hydrodynamics and soil erosion of steep spoil heaps. This study aimed to address this research gap by conducting field simulated rainfall and rainfall with run-on experiments using simulated spoil heap plots with 3.4m × 2m × 0.6m (length × width × depth) and a slope of 30 degree. The material used in the spoil heaps comprised a uniform mixture of silt soil particles, constituting 90% by mass, and gravel, constituting 10% by mass. For this study, bare slope (BS), Artemisia gmelinii (A. gmelinii), and Cynodon dactylon (C. dactylon) treatments were designed. Additionally, the grass-covered underwent two treatments: intact grass (IG) and only root (OR). The simulation experiments consisted of two types: rainfall conditions with intensities of 0.8, 1.2, and 1.8mmmin-1, and rainfall with run-on conditions with three intensities and a discharge flow rate of 15Lmin-1. The results showed that: under rainfall conditions, A. gmelinii had a higher soil loss reduction benefit (93.3%) than C. dactylon (88.5%), while the percentages reversed with A. gmelinii at 82.1% and C. dactylon at 91.9% under rainfall with run-on. Moreover, A. gmelinii exhibited higher runoff volume reduction benefits than C. dactylon under both experimental conditions, except for rainfall intensity of 0.8mmmin-1 in IG treatments. The canopy of A. gmelinii accounted for 53% to 69% of the reduction in average soil loss rate, whereas the root and canopy of C. dactylon contributed 58% and 162% under rainfall and rainfall with run-on conditions, respectively. During heavy rainfall events, vegetation could experience more severe soil and runoff loss compared to BS once its aboveground canopy was lost. Furthermore, A. gmelinii had a greater effect in reducing average velocity and increasing resistance coefficient compared to C. dactylon. Additionally, C. dactylon had twice the effect in improving shear stress and stream power than A. gmelinii. Vegetation influences slope sediment and runoff yield by modulating erosion dynamic parameters. This study can serve as a valuable reference and practical guidance for the ecological restoration of similar engineering spoil heaps in the future.

Using radiotracers 137Cs and 210Pbex to document climate change in mountain areas through the estimate of soil erosion rates

Abstract. During the last few decades, a general increase in heavy rainfall events has been documented in many areas of the world. These events have caused changes in soil erosion rates and strongly affected the human activities in mountain areas by reducing the national income obtained from cultivated land. In this context, the use of fallout radiotracers can be an important tool for better understanding the consequences of climate change in these areas and proposing effective countermeasures in order to reduce soil loss. In this contribution, plot experiments carried out in southern Italy that involve the use of 137Cs and 210Pbex measurements were performed to estimate soil erosion rates during the last few decades. The overall results indicate an increase in soil erosion rates during the last 15–20 years and suggest the use of this technique to detect climate change in mountain areas.