Precipitation Analysis Research Articles

Historical Trends Associated with Annual Temperature and Precipitation in Aegean Turkey, Where Are We Heading?

The trend analysis of annual temperature (daily average) and total precipitation has been conducted for 14 stations located in the Aegean Region, Turkey. The Sen, Spearman’s rho, and Mann-Kendall test methods are used in the detection of the historical trends in the region. The Pettitt test is also implemented to find the significance of the trend, while the Theil-Sen approach is applied to detect the change point(s) in the time series. Findings of the following study indicate that both precipitation and temperature time series in the selected stations depict statistically significant trends with increasing nature. The rate of increase in precipitation and temperature by the Theil-Sen test is found to be 4.2–7.9 mm/year and 0.20–0.35 °C/decade, respectively. It is also found that the turn points of the temperature trends determined by the Pettitt test occurred in 1998 for all the stations. According to the results, the magnitude of the extreme events would change in the future, which may help in conceptualizing the framework and the resilience of the infrastructures against climate change.

Benchmarking Simulated Precipitation Variability Amplitude across Time Scales

Abstract Objective performance metrics that measure precipitation variability across time scales from subdaily to interannual are presented and applied to Historical simulations of Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. Three satellite-based precipitation estimates (IMERG, TRMM, and CMORPH) are used as reference data. We apply two independent methods to estimate temporal variability of precipitation and compare the consistency in their results. The first method is derived from power spectra analysis of 3-hourly precipitation, measuring forced variability by solar insolation (diurnal and annual cycles) and internal variability at different time scales (subdaily, synoptic, subseasonal, seasonal, and interannual). The second method is based on time averaging and facilitates estimating the seasonality of subdaily variability. Supporting the robustness of our metric, we find a near equivalence between the results obtained from the two methods when examining simulated-to-observed ratios over large domains (global, tropics, extratropics, land, or ocean). Additionally, we demonstrate that our model evaluation is not very sensitive to the discrepancies between observations. Our results reveal that CMIP5 and CMIP6 models in general overestimate the forced variability while they underestimate the internal variability, especially in the tropical ocean and higher-frequency variability. The underestimation of subdaily variability is consistent across different seasons. The internal variability is overall improved in CMIP6, but remains underestimated, and there is little evidence of improvement in forced variability. Increased horizontal resolution results in some improvement of internal variability at subdaily and synoptic time scales, but not at longer time scales.

Performance evaluation of raw and bias-corrected ERA5 precipitation data with respect to extreme precipitation analysis: case study in Upper Jhelum Basin, South Asia

Performance evaluation of raw and bias-corrected ERA5 precipitation data with respect to extreme precipitation analysis: case study in Upper Jhelum Basin, South Asia

Statistical analysis of long-term precipitation in the Maghreb reveals significant changes in timing and intensity

Statistical analysis of long-term precipitation in the Maghreb reveals significant changes in timing and intensity

SM2RAIN-ASCAT satellite-based spatiotemporal drought monitoring using multiscale WT-VMD-ENERGY method

Drought is one of the severe natural disasters that has devastating effects on various parts of the environment. Therefore, spatiotemporal monitoring of drought using reliable methods is very important. In this study, using a new Discrete Wavelet Transform (DWT)-Variational Mode Decomposition (VMD)-Energy multi-scale approach, the efficiency of the new Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT) precipitation product was investigated in monitoring the spatiotemporal patterns of short- to long-term droughts for the Northwest part of Iran. In this regard, after validating the accuracy of the SM2RAIN-ASCAT datasets, a multi-scale method was developed based on the serial decomposition of the drought signals. The mean energy amounts of the obtained subseries were imposed into the K-means (K signifies the number of clusters) to identify the drought-prone regions. Results showed that the highest Correlation Coefficient (R) between SM2RAIN-ASCAT and in-situ observations are found at monthly time scales, in which 73% of the stations had R higher than 0.7. Investigating the reliability of this product for drought monitoring showed that for short- and mid-term timescales in 75% of the stations, the values of R were higher than 0.7. The applied methodology successfully showed the drought-prone regions and a direct relationship was found between energy and drought intensity. The capability of the applied methodology was verified via the CPC Merged Analysis of Precipitation (CMAP) and Moderate Resolution Imaging Spectroradiometer (MODIS) products and the obtained results proved the desirable performance of the SM2RAIN-ASCAT datasets. It was found that SOI, Nino3, and Nino3.4 had major effects on the drought index in the selected area, while AO had the least effect. The relationship between the LST and SPIs was negative, while there was a positive relationship between NDVI and SPIs.

Central Asia daily extreme precipitation in observations and gridded datasets: A threshold criteria perspective

The extreme precipitation threshold is fundamental to extreme precipitation research, directly affecting the cognition of extreme characteristics. Based on the daily precipitation data of 62 meteorological stations from 1985 to 2005, this study uses parametric and non-parametric approaches to determine the extreme precipitation threshold in Central Asia, analyzes the statistics and spatial distribution of different threshold criteria, and discusses the trend of extreme precipitation. The capability of the grid dataset of APHRODITE and GPCC in the extreme precipitation analysis in Central Asia is evaluated from the threshold perspective. The results are as follows: 1) Contrary to the parametric approach, the threshold determined by the percentile indices in the warm season is slightly higher than in the cold season. The mean threshold of the warm (cold) season in Central Asia is defined by the 95th percentile index and the 10-year return period, which are 14.0 mm (13.5 mm) and 24.2 mm (25.7 mm), respectively. 2) The spatial distribution of extreme precipitation threshold in Central Asia is higher in the southeast and lower in the north during the cold season; In the warm season, it is high in the north and southwest and low in the center. 3) Although both APHRODITE and GPCC datasets can basically reproduce the spatial distribution of extreme precipitation threshold, they underestimate the magnitude of the threshold, especially APHRODITE. 4) There is no obvious extreme precipitation trend in Central Asia during the study period. Furthermore, the trend in characteristics of extreme precipitation based on different thresholds shows a consistent trend in time but not spatially. We suggest that the threshold selection should adjust the balance between sufficient samples and extreme values according to actual conditions. The results of this study can provide a reference for extreme precipitation threshold criteria under specific application conditions in Central Asia.

Innovative polygon trend analysis of monthly precipitation (1952–2015) in the Hindukush‐Karakoram‐Himalaya river basins of Pakistan

AbstractThe Hindukush‐Karakoram‐Himalayas (HKH) mountainous range supplies water to 10 river basins serving eight countries. The present study focuses on the river basins located within the HKH region in Pakistan. The modified Soil and Water Assessment Tool (SWAT+) was used to split the research region into 13 sub‐basins. The Mann–Kendall, Sen's slope, innovative polygon trend analysis (IPTA), and innovative trend analysis (ITA) methods were used for the monthly precipitation time series. The Shyok sub‐basin (central Karakoram) experienced rising trends for all seasons, while the southwestern Karakoram (Hunza) showed a rising trend only for the winter. The Hindukush Mountain Range feeds five sub‐basins (Gilgit, Chitral, Swat, Kabul, and Kurram). The Gilgit and Kurram sub‐basins observed an upward trend for all seasons. A falling trend in spring and transition from spring (falling) to summer (rising) was observed for the Swat and Kabul sub‐basins. The Chitral sub‐basin received rising precipitation in spring, summer, and autumn, whereas no trend was observed during winter. In the southern Himalayas (Kanshi and Jhelum), no trend was observed in winter and autumn and a falling trend in spring and summer. The Kunhar sub‐basin (southern Himalaya) showed rising trends in winter, spring, and autumn. In contrast, the Soan sub‐basin (eastern Himalaya) has no trend in spring, and other seasons show rising trends. The sub‐basin Upper Indus experienced a rising trend for autumn, winter, and summer, while a downward trend was observed in spring. The IPTA and ITA approaches are much more sensitive than the Mann–Kendall method in detecting trends. Although the innovative methods are mostly compatible with each other (90%), the IPTA presents additional information about trend transitions between successive parts of the time series. The results presented in this study are an advancement in the investigations made so far in this region and will help to understand the climate and hydrology of this region.

Impacts of different types of El Niño events on water quality over the Corn Belt, United States

Abstract. The United States Corn Belt region, which primarily includes two large basins, namely, the Ohio–Tennessee River basin (OTRB) and the Upper Mississippi River basin (UMRB), is responsible for the Gulf of Mexico hypoxic zone. Climate patterns such as El Niño can affect the runoff and thus the water quality over the Corn Belt. In this study, the impacts of eastern Pacific (EP) and central Pacific (CP) El Niño events on water quality over the Corn Belt region were analyzed using the Soil and Water Assessment Tool (SWAT) models. Our results indicated that, at the outlets, annual total nitrogen (TN) and total phosphorus (TP) loads decreased by 13.1 % and 14.0 % at OTRB and 18.5 % and 19.8 % at UMRB, respectively, during the EP El Niño years, whereas during the CP El Niño years, they increased by 3.3 % and 4.6 % at OTRB and 5.7 % and 4.4 % at UMRB, respectively. On the subbasin scales, more subbasins showed negative (positive) anomalies of TN and TP during EP (CP) El Niño. A seasonal study confirmed that water quality anomalies showed the opposite patterns during EP and CP El Niño years. At the outlet of OTRB, seasonal anomalies in nutrients matched the El Niño–Southern Oscillation (ENSO) phases, illustrating the importance of climate variables associated with the two types of El Niño events on water quality in the region. At the UMRB, TN and TP were also influenced by agricultural activities within the region, and their anomalies became greater in the growing seasons during both EP and CP El Niño years. A quantitative analysis of precipitation, temperature, and their effects on nutrients suggested that precipitation played a more important role than temperature did in altering the water quality in the Corn Belt region during both types of El Niño years. We also found specific watersheds (located in Iowa, Illinois, Minnesota, Wisconsin, and Indiana) that faced the greatest increases in TN and TP loads and were affected by both the precipitation and agricultural activities during the CP El Niño years. The information generated from this study may help proper decision-making for water environment protection over the Corn Belt.

Using a hybrid optimal interpolation–ensemble Kalman filter for the Canadian Precipitation Analysis

Abstract. Several data assimilation (DA) approaches exist to generate consistent and continuous precipitation fields valuable for hydrometeorological applications and land data assimilation. Usually, DA is based on either static or dynamic approaches. Static methods rely on deterministic forecasts to estimate background error covariance matrices, whereas dynamic approaches use ensemble forecasts. Associating the two methods is known as hybrid DA, and it has proven beneficial for different applications as it combines the advantages of both approaches. The present study intends to explore hybrid DA for the 6 h Canadian Precipitation Analysis (CaPA). Based on optimal interpolation (OI), CaPA blends forecasts and observations from surface stations and ground-based radar datasets to provide precipitation fields over the North American domain. The application of hybrid DA to CaPA consisted of finding the optimal linear combination between (i) an OI based on the Regional Deterministic Prediction System (RDPS) and (ii) an ensemble Kalman filter (EnKF) based on the 20-member Regional Ensemble Prediction System (REPS). The results confirmed the known effectiveness of the hybrid approach when low-density observation networks are assimilated. Indeed, the experiments conducted for the summer without radar datasets and for the winter (characterized by very few observations in CaPA) showed that attributing a relatively high weight to the EnKF (50 % and 70 % for summer and winter, respectively) resulted in better analysis skill and a reduction in false alarms compared with the OI method. A deterioration in the moderate- to high-intensity precipitation bias was, however, observed during summer. Reducing the weight attributed to the EnKF to 30 % alleviated the bias deterioration while improving skill compared with the OI-based CaPA.

Historical activity of debris flows in the medium-high mountains: Regional reconstruction using dendrogeomorphic approach

Detailed knowledge of the occurrence of debris flows in the past is key to understanding their linkage to changing climatic variables and their occurrence in the future. For a comprehensive understanding of the origin of these processes, regional reconstruction is optimal rather than detailed analysis of isolated catchments. This study presents the results of a dendrogeomorphic reconstruction of debris flows across an entire medium-high mountain range in Central Europe covering more than 500 km2. The tree-ring data allowed the reconstruction of 96 debris flow events at 21 sites. The average frequency of events was 6.8 per decade, which is comparable or higher compared to alpine valleys. A detailed analysis of potential precipitation triggers was also performed in the paper, whose magnitude significantly influenced not only the number of debris flows but also their magnitude. Debris flows occur in two forms in the study area, with channelized debris flows showing significantly higher magnitude but lower frequency than fan debris flows. The differences between the two types are probably due to the different source of material that is reactivated during precipitation events of different duration and magnitude.

Liquid-liquid phase reaction between crystal violet and sodium hydroxide: kinetic study and precipitate analysis.

To investigate reaction order and kinetic parameters of the reaction between crystal violet (CV) and sodium hydroxide (NaOH), various concentrations of the reactants were applied. The present work also verifies the unknown solid product produced under highly concentrated conditions. The reaction orders of CV and NaOH were determined to be 1 and 1.08 by pseudo rate method, respectively, with a rate constant, k, of 0.054 [(M−1.08) s−1]. In addition to pseudo rate method, the half-life approach was used to calculate the overall reaction order to verify the accuracy of pseudo rate method. The overall reaction order was determined to be 1.9 by the half-life method. The overall reaction order based on the two methods studied was approximately 2. The precipitate formation was observed when high concentrations of CV (0.01–0.1 M) and NaOH (1.0 M) were applied. Fourier transform infrared (FTIR) spectroscopy was used to compare the spectra of the precipitate generated and a commercial solvent violet 9 (SV9). Based on the FTIR spectra, it was confirmed that the molecular structure of the precipitate matched that of solvent violet 9.

Impact assessment of climate change and urbanization on the nonstationarity of extreme precipitation: A case study in an urban agglomeration in the middle reaches of the Yangtze river

• Impacts of climate change and urbanization on extreme precipitation changes are identified. • Nonstationary GAMLSS could better capture the variation of extreme precipitation. • Urbanization contributes more to the nonstationarity of extreme precipitation. Extreme precipitation events exert increasingly profound effects on public health and ecosystems under climate change and urbanization. In this study, the nonstationarity and spatiotemporal variation of extreme precipitation in an urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) from 1970 to 2017 were analyzed based on nine extreme precipitation indices. A nonstationary frequency analysis of extreme precipitation by the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) was constructed using 6 atmospheric metrics and 6 urbanization metrics as explanatory variables. Additionally, the separate contributions of climate change and urbanization to extreme precipitation were compared quantitatively. Results demonstrated that during 1970–2017, the extreme precipitation increased in magnitude, whereas mainly decreased in duration, with a spatial pattern gradually increasing from west to east in the UAMRYR. The nonstationary GAMLSS could better capture the evolution characteristics of extreme precipitation, indicating that the nonstationarity of extreme precipitation in the UAMRYR is significant. Among the constructed nonstationary models, the number of optimal models with the Largest Patch Index (LPI), Percentage of Landscape (PLAND), and Landscape Shape Index (LSI) as explanatory variables is the largest. In general, urbanization contributed greater to the nonstationarity of extreme precipitation than climate change in the majority of the UAMRYR. This study can provide scientific references for waterlogging control and urban planning.

Quantifying Heavy Precipitation throughout the Entire Tropical Cyclone Life Cycle

Abstract Tropical cyclones (TCs) and their associated precipitation can have devastating impacts on the areas affected, with outcomes ranging from mudslides to inland flash flooding. Previous studies have used a fixed radius around the TC to isolate storm-related precipitation. One previous study instead used a dynamic radius of 8 m s−1 winds, but the wind field of the TC can deteriorate or shift quickly after landfall or the onset of extratropical transition (ET). This study uses a dynamical radius derived from the 500-hPa geopotential height in and around the TC to define TC- and post-tropical cyclone (PTC)-related heavy precipitation, allowing for the analysis of precipitation with tropical origins after the official demise of the original TC. Climatologies are constructed, indicating a maximum in TC- and PTC-related heavy precipitation in the west North Pacific and a secondary maximum in the east North Pacific. PTC-related heavy precipitation accounts for as much as 40% of the annual heavy precipitation in the northwest portion of the west North Pacific basin and 3.13% of heavy precipitation globally. We observe that the major hurricane stage contributes on average 2.6% of the global TC- and PTC-related precipitation, while the less intense but more common tropical storm stages of the TC life cycle contribute 85.7% of this observed precipitation. This analysis framework can be further extended to assess model biases and climate projections of TC and PTC precipitation.

Decadal precipitation in São Bento Una – Pernambuco, Brazil

The objective is to carry out an analysis of decadal precipitation and its historical comparisons for the municipality of São Bento do Una in the period 1920-2018, which will possibly contribute to the decisions of sectors such as socioeconomic, agriculture, poultry, irrigation, energy production, resources water resources and agricultural technicians and decision makers in the event of extreme winds that may occur. The rainfall data were acquired from the Superintendence of the Development of the Northeast and from the Pernambucana Water and Climate Agency, between the years 1920 to 2016. The statistical simplified calculations were used to define, mean, standard deviation, coefficient of variance, maximum and minimum absolute values ​​occurred, the rainy and dry seasons were defined. The rains registered between decades did not cause great inconvenience to the population, the local economy, except in months where the summer period was extended. The irregularities that occurred in the rainfall in the 1930-1939 decades; 1950-1959 and 2010-2018 were the most prominent in the contributions to livestock farmers for the production of survival agriculture, poultry and water storage in small, medium weirs and cisterns.

Flow assurance, simulation of wax deposition for Rawat field using PIPSIM software

One of the most relevant flow assurance issues in oil transportation is indeed the phenomena of wax deposition. Wax deposition occurs when the temperature along the pipeline falls below a point where it is described as Wax Appearance Temperature (WAT) The deposition may cause a lot of problems to the industry and definitely will involve expensive cause to overcome the problem. The flow system was built for Rawat field which is consists of (13) wells in the Rawat/Wateesh field. In this studies a series of cases were carried out at different flow rates, ambient temperature to study falling temperature through f pipline using PIPESIM Software and providing data from central petroleum laboratory and Rawat operating company. To check that temperature at all points along the flow line and trunk line is above the pour point and wax appearance temperature, check the requirement of heater, heat tracing and insulation for the pipelines more ever is used to studies the influence of changing flow rate, ambient temperature and water cut for pipeline temperature. The line size, line velocity and heat duty of the system have been calculated using excel program.The results show that the minimum temperature criteria for pipelines should be above 54C to avoid gelling of the fluid, Wax precipitation analysis results indicates that the minimum wax precipitation temperature for Wateesh W-was approximately 62°C and the same for Rawat RC-1 well were approximately 58°C.the flowlines size were determined 4” and 6” for trunk line.Also The results show that there is a direct relation between the wax deposition and temperature, It was observed that wax deposit increases with decreasing the temperature. On the other hand, an increase in flow rate results in a decrease in the wax deposition. Finally, hot insulation of the flow lines and trunk line was required, Electrical Heat Tracing to heat the fluid to 75 Deg, chemical injection such as wax inhibitors and pigging process to control the wax deposition.

Thermodynamic modelling and analysis of wax precipitation for CO2-rich Brazilian pre-salt live oils

Thermodynamic modelling and analysis of wax precipitation for CO2-rich Brazilian pre-salt live oils

Temporal Variability of Temperature, Precipitation and Drought Indices in Hyper-Arid Region of Northwest China for the Past 60 Years

The temporal variability and abrupt change analysis of temperature and precipitation in Turpan was investigated and examined based on a monthly data set of temperature, precipitation and drought indices (1960–2019) from three meteorological stations over the study area. The Yamamoto method, Mann–Kendall test, Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), and Reconnaissance Drought Index (RDI) were applied to reveal temperature, precipitation and drought indices trends in their annual volumes. The conclusions were as follows: (1) in the past 60 years, the annual average temperature in the Turpan region has increased at a rate of 0.33 °C·(10a)−1. Whereas the temperature has accelerated since the 1980s, the annual average minimum temperature has increased more than the annual average maximum temperature, and the temperature difference between winter and summer has increased since the 1990s. (2) The inter-annual, inter-decadal and normal value changes in precipitation in the Turpan region and its three meteorological stations indicated a decreasing trend during 1960–2019. Though the normal value of summer and autumn precipitation decreased and increased as a whole, the normal values of spring, summer, winter and annual precipitation in the Turpan region displayed downward trends. (3) Abrupt changes in temperature were observed in the mid-1990s, and abrupt changes in precipitation were not obvious. (4) The SPI and RDI responded quickly to precipitation and temperature, and the overall characteristics of dry and wet trend changes were consistent. When the SPEI considered the combined effect of temperature and precipitation, the SPI and SPEI are better correlated, and the SPI and RDI are better correlated than the SPEI and RDI. On the whole, the occurrence of drought has obvious regional and seasonal characteristics. These conclusions not only provide scientific data for sustainable development in Turpan but also offer scientific information to further understand the trends and periodicity of climate change and drought conditions in hyper-arid regions around the world.

Repair of mortar cracks using Bacillus pumilus based bio-suspension assessed by machine learning algorithm for image processing

Shortcomings and contagious effect to the environment by existing concrete repairs have drawn interest to alternative solutions for concrete repair. In this study, Bio-suspension was prepared to repair pre-existing cracks on the mortar surface. Bio-suspension of a rarely explored alkaliphilic, spore-forming bacterial strain Bacillus pumilus is reported for the first time for repair. The biological metabolic activity of Bacillus pumilus is capable of calcite precipitation in a high alkaline environment of cementitious matrix. Samples repaired by both bio-suspension and conventional treatments were investigated against water permeability, ultra-sonic pulse velocity, crack sealing, and compressive strength. The machine-learning algorithm of image processing was used for acquiring crack features of pre-existing mortar surface cracks and the healing potency. OTSU method of thresholding was used in image processing. The results indicated that precipitated calcite by prepared bio-suspension successfully healed crack up to 1.55 mm. Alongside crack sealing, formulated bio-suspension showed 3 order lower value of water permeability in comparison to untreated cracked samples. Further, a significant increase in the value of ultra-sonic transmission and improved compressive strength of repaired samples is attained. The results obtained with bio-suspension were equivalent to conventional epoxy-based repair. Further, microstructural analysis of precipitates of bio-repair by SEM-EDX, XRD, RAMAN, and TGA confirmed the adequate presence of calcite crystal due to metabolic activity of introduced Bacillus pumilus inside the cracks.

Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation

Abstract. This paper presents an innovative approach, STREAM – SaTellite-based Runoff Evaluation And Mapping – to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and total water storage anomalies (TWSAs). Within a very simple model structure, precipitation and soil moisture data are used to estimate the quick-flow river discharge component while TWSAs are used for obtaining its complementary part, i.e., the slow-flow river discharge component. The two are then added together to obtain river discharge estimates. The method is tested over the Mississippi River basin for the period 2003–2016 by using precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), soil moisture data from the European Space Agency's Climate Change Initiative (ESA CCI), and total water storage data from the Gravity Recovery and Climate Experiment (GRACE). Despite the model simplicity, relatively high-performance scores are obtained in river discharge estimates, with a Kling–Gupta efficiency (KGE) index greater than 0.64 both at the basin outlet and over several inner stations used for model calibration, highlighting the high information content of satellite observations on surface processes. Potentially useful for multiple operational and scientific applications, from flood warning systems to the understanding of water cycle, the added value of the STREAM approach is twofold: (1) a simple modeling framework, potentially suitable for global runoff monitoring, at daily timescale when forced with satellite observations only, and (2) increased knowledge of natural processes and human activities as well as their interactions on the land.

Interdecadal variability of the austral summer precipitation over the Central Andes

The impacts of the interdecadal variability of the Pacific and the Atlantic Oceans on precipitation over the Central Andes during the austral summer (December-January-February, DJF) are investigated for the 1921–2010 period based on monthly gridded precipitation data and low-pass filtered time series of the Niño 4 index (IN4), the Niño 1 + 2 index with Niño 3.4 index removed (IN1+2*), Atlantic Multidecadal Oscillation (AMO), and Interdecadal Pacific Oscillation (IPO) indices, and the three first rotated principal components of the interdecadal component of the sea surface temperature (SST) anomalies over the Atlantic Ocean. A rotated empirical orthogonal function (REOF) analysis of precipitation in the Central Andes (10°S–30°S) yields two leading modes, RPC1 and RPC2, which represent 40.4% and 18.6% of the total variance, respectively. REOF1 features a precipitation dipole between the northern Bolivian and the Chilean Altiplano. REOF2 also features a precipitation dipole, with highest negative loading over the southern Peruvian Andes. The REOF1 positive phase is associated with moisture transport from the lowlands toward the Bolivian Altiplano, induced by upper-level easterly wind anomalies over the Central Andes. At the same time conditions tend to be dry over the southern Peruvian Andes. The positive phase of REOF2 is related to weakened moisture transport, induced by upper-level westerly wind anomalies over Peru. The IPO warm phase induces significant dry anomalies over the Bolivian Altiplano, albeit weaker than during the IN4 warm phase, via upper-level westerly wind anomalies over the Central Andes. No significant relationship was found between Central Andean precipitation and the AMO on interdecadal timescales.