Occurrence Of Precipitation Research Articles

Characteristics of summer tropopause folds over southeastern Central Asia and their influences on precipitation

Tropopause folding activities in the summer play a significant role in atmospheric circulations and weather anomalies. Using rain gauge data and the Climate Prediction Center (CPC) precipitation observations as well as the ERA5 reanalysis dataset during July–August (JA) of 1979–2020, three-dimensional circulation structure during 592 frequent tropopause fold days that occurred over southeastern Central Asia and their impacts on precipitation over Central Asia and western China are investigated. During the frequent tropopause fold days, a significant dipole precipitation anomaly pattern is observed with negative precipitation anomalies over Central Asia and positive precipitation anomalies over western China. The contribution of precipitation (extreme precipitation) in the frequent tropopause fold days to the JA climatology over the northwestern slope of the Tibetan Plateau (TP) and the southern Tarim Basin can reach above 40% (50%). Compared with that in no fold days, daily mean precipitation in the frequent tropopause fold days can increase to three times over the northwestern TP and the Tarim Basin. Strong upward motions associated with low level convergence (high level divergence) and high specific humidity are found downstream of the fold region, which is favorable for the occurrence of precipitation, especially extreme precipitation over western China. In contrast, strong downward motions associated with low level divergence (high level convergence) and low specific humidity suppress the occurrence of precipitation over Central Asia. Further analysis reveals that precipitation over western China is closely related to the strength of tropopause fold, with significant positive correlation over the northwestern TP and the Tarim Basin. As the tropopause fold strengthens, the intensity of upward motion and specific humidity in the middle to lower troposphere downstream of the fold region increase, resulting in changes in the frequency and location of precipitation over western China. These findings highlight important impacts of the atmosphere around the tropopause on precipitation over western China.

Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign

AbstractThe performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground‐based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar Prediction Special Observing Period at Dumont d'Urville (November 2018–February 2019), East Antarctic coast. The occurrence of precipitation is overall well predicted, but the number of days and intensity with snowfall are overestimated by the models. This is reflected by high values of bias, probability of detection, and false alarm ratios, in particular for reanalyses, due to too frequent simulated precipitating days. The Heidke skill score shows the overall great contribution of the models in the forecasting of precipitating days, and the best performances are achieved by numerical weather prediction models. The chronology is better represented when the models benefit from the data assimilation of in‐situ observations, such as in reanalysis or weather forecasting models. Precipitation amounts at the surface are overestimated by most of the models. In addition, data from a ground‐based radar make it possible to evaluate the representation of the vertical profiles of snowfall rate. We can show that an excessive sublimation in the atmospheric boundary layer can compensate for overly strong precipitation flux in the mid and low troposphere. Therefore, the need to expand the measurement of precipitation across the atmospheric column using radars is highlighted, in particular in Antarctica where the cold cloud microphysics is poorly known and observations are particularly rare.

Microstructure evolution and mechanical properties of wire-arc additive manufactured Al–Zn–Mg–Cu alloy assisted by interlayer friction stir processing

The interlayer friction stir processing (FSP) technology was used to assist wire-arc additive manufacturing (WAAM) Al–Zn–Mg–Cu alloy with the aim of improving microstructure and mechanical properties of the component. The metallurgical defects (pores) in the as-deposited zone (AZ) can be effectively eliminated by the interlayer FSP, and the coarse columnar grains were refined to fine equiaxed grains. Besides, the eutectic phase continuously distributed along the grain boundaries was significantly broken and dissolved into the α-Al matrix. The hardness from top to bottom of the component fabricated by hybrid WAAM and interlayer FSP was gradually decreased and finally reached stability, and thereby the corresponding component can be divided into variable and stable regions. The top-layer stir zone (SZ) in the variable region showed the highest tensile properties with yield strength (YS), ultimate tensile strength (UTS) and elongation (EL) of 388 MPa, 504 MPa and 16.1%, respectively. By contrast, the tensile properties of SZ in the stable region were decreased, and the average YS, UTS and EL were determined as 205 MPa, 348 MPa and 19%, respectively. Nevertheless, the SZ in the stable region still exceeded AZ in terms of tensile properties and exhibited isotropy between vertical and horizontal directions. The main reason for the mechanical properties of the component gradually decreased in the vertical direction can be attributed to the occurrence of precipitation and coarsening of η and η′ phase at previous layers induced by thermal cycling during the additive manufacturing process.

CVケーブル用プレハブ式終端接続箱における析出物発生過程の推定と数値計算手法の構築

A stress relief cone plays an essential role in a prefabricated termination for the XLPE cable system. It has been pointed out that precipitates occur on certain parts of the stress relief cone surface under long-term operation, which could lead to a dielectric breakdown. This paper describes the development of two-step numerical calculation programs to understand the appearance process of precipitate on the surface of the stress relief cone. The first step is to estimate the distribution of precipitation occurrence over time, considering several ten-year operations. The second step is to estimate the detailed formation process of precipitates based on the molecular dynamics method. As a result, it is confirmed that the occurrence condition of precipitate led by the developed numerical calculation methods is similar to that obtained at the dismantled stress relief cone.

Construction of a water-soluble fluorescent probe for copper (II) ion detection in live cells and food products

The quality of wine can be affected by excess Cu2+ due to the occurrence of oxidation reactions or precipitation. Therefore, it is essential to use simple and effective testing methods to ensure the Cu2+ content in wine. In this work, we designed and synthesized a rhodamine polymer fluorescent probe (PEG-R). The water solubility of PEG-R was improved by the introduction of polyethylene glycol, which improved the performance and broadened its application in the food field. The PEG-R was characterized by high sensitivity, selectivity and fast response to Cu2+ and was able to complete the response process within 30 s, with approximately 29-fold fluorescence enhancement of the probe after exposure to Cu2+, the limit of detection (LOD) was 1.295 × 10-6 M. The probe can be used for the determination of Cu2+ in living cells, zebrafish, white wine and food products, and it was made into practical gels and test strips.

A comprehensive evaluation of the satellite precipitation products across Iran

Study regionIran Study focusThis study evaluated three satellite precipitation products, including PERSIANN-CCS and TRMM-3B42RT V7 (near real-time satellites) and CMOROH (post real-time satellite), on hourly, daily, monthly, and annual time scales in 52 synoptic stations over Iran. This study aims to evaluate the accuracy of satellite- precipitation products over different return periods and durations as well as their performance in different climates and altitudes. The Pearson’s correlation coefficient (Rp), Relative Root Mean Square Error (RRMSE), and Relative Bias (RBias) as well as three probability indices including Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were applied to evaluate the accuracy of these products. In addition, the sub-daily IDF curves (6, 12, 18, and 24 h) were derived to evaluate the studied satellites precipitation for 5, 10-, 20-, 50-, and 100-year return periods. New hydrological insights for the regionThe results showed that the modification method could significantly improve all satellites' performance in precipitation estimation. The IDF curves derived from the CMORPH satellite as post real-time satellite precipitation product, showed the highest accuracy compared to synoptic stations. The TRMM and CMORPH underestimated precipitation by 56% and 8%, respectively, while PERSIANN-CCS overestimated precipitation by 143%. However, PERSIANN-CCS performed better in detecting the occurrence and non-occurrence of precipitation than other products. For Northeastern and Southwestern Iran, all products showed the same performance in accurately detecting occurrence and precipitation.

Using a Continental-Scale Data Quality Monitoring Framework to Evaluate a New Nonweather Filter for Radar Observations

Abstract Removing nonweather echoes is a critical component of the quality control (QC) chain used in the context of radar data assimilation for numerical weather prediction, quantitative precipitation estimation, and nowcasting applications. Recent studies show that using a simple QC method based on the depolarization ratio (DR) performs remarkably well in many situations. Nonetheless, this method may misclassify echoes in regions affected by nonuniform beamfilling or melting particles. This study presents an updated version of this QC used to remove nonweather echoes that uses the DR-based classification together with a set of physically based rules for correcting misclassifications of hail, nonuniform beamfilling, and melting particles. The potential of the new QC is evaluated using a continental-scale monitoring framework that compares the radar observations after QC with the precipitation occurrence derived from aviation routine weather reports (METARs). For this evaluation, the study uses the radar data and the METARs available over North America during the summer of 2019 and winter of 2020. In addition, the study demonstrates the usefulness of the monitoring framework to determine the optimal QC configuration. Some practical limitations of using the METAR-derived precipitation to assess radar data quality are also discussed.

Evaluating the IMERG precipitation satellite product to derive intensity-duration-frequency curves in Colombia

This article explores the potentialities of the IMERG V06B FINAL product for estimating Intensity-Duration-Frequency curves in Colombia, using the in-situ data available for 110 rain gauges. From observed data for 76 of these stations, we validated the satellite IMERG precipitation data for the period 2001-2019, at daily, monthly, and annual resolutions. For 60 stations, better results were obtained for the monthly time aggregation, followed by the yearly and daily scales, suggesting that seasonality is the main rainfall characteristic captured by the product. Concerning the occurrence of daily precipitation, results indicate that both the probability of detection and the probability of false detection are high. In general terms, the comparison between intensities from existing IDF curves and those derived from IMERG showed underestimations of the rainfall intensities for the short durations studied (0.5 and 1 h), with mean relative errors in the range [-69%,+56%], and overestimations for the large durations of 2 and 6 h, with mean relative errors in the range [-61%,+171%]. Results also suggest that the IMERG product at this moment is not able to capture the daily rainfall distribution in most of the stations. Nevertheless, for almost 20% of the rain gauges, located mainly in the Amazon, Orinoco, and Pacific Regions, the analysis showed that the maximum intensities derived from IMERG are within +/-25% relative error, compared with the ones calculated using the traditional approach.

Human influence on historical heaviest precipitation events in the Yangtze River Valley

With the recurrence of high-impact extreme events and the growing public demands to understand the causes of the events, event attribution has emerged as a frontier of climate change research. Typically, an event attribution study focuses on one individual extreme event that has just occurred. Studies rarely examine human influence on multiple extreme events in different times of the past. Here we conduct a comprehensive attribution analysis on the four heaviest precipitation events in the Yangtze River Valley during the past 100 years. We start by defining extreme precipitation events as the heaviest precipitation over a fixed size area that is of direct relevance to flood preparedness and management. When examining the events over the historical time, we allow the precise location of the area to change in different years. By definition, four extremely strong events are identified, and they happened in the summer of 1931, 1954, 1998 and 2020. We find that the impacts of greenhouse gases (GHGs) and anthropogenic aerosols (AAs) on these events show clear difference in different time period. The impacts were negligible in the early period and became more and more discernible since the late 20th century. The GHGs have gradually increased the occurrence probability of extreme precipitaiton while the AAs have decreased the occurrence of extrem precipitation. These competing effects from the GHGs and AAs have led to a slight and then gradually increasing human influence on extreme precipitation over time. GHGs have exerted a larger influence on short-duration precipitation events while AAs have had a larger influence on monthly mean precipitation. The more extreme the precipitation event, the clearer the anthropogenic influence.

Fate of Rainfall Over the North Indian States in the 1.5 and 2°C Warming Scenarios

AbstractRise in mean temperature put a great deal of uncertainty about how weather and climate extremes may play out, particularly in India's varied climatic zones. Consequently, it is important to understand the possible changes in both magnitude and direction of weather and climate extremes like rainfall for different warming levels of 1.5 and 2°C scenarios concerning preindustrial and present levels. Hence in the present study, the precipitation behavior of seven North Indian states that is, Haryana, Himachal Pradesh, J&K, Punjab, Rajasthan, Uttar Pradesh, and Uttarakhand carefully studied using CMIP5 models. Future projections of precipitation has been done for the Paris Agreement global warming level of 1.5 and 2°C scenarios. Along with model validation and future projections of precipitation, the return period of extreme rainfall is also discussed to understand the behavior of the occurrence of extreme precipitation. Statistical analysis shows that the ensemble means have the least error as compared to the other six CMIP5 models. Therefore, future analysis has been done with the ensemble mean. Our findings show that the precipitation is likely to decrease in the 1.5°C scenarios, while it is likely to increase in the 2°C scenarios. The occurrence and intensity of extreme rainfall events are likely to be more frequent in all the models. The return period of the extreme rainfall events is likely to increase in all the states in both the warming scenarios. A three‐fold rise is likely to increase extreme rainfall events in the 2°C scenario.

Global Application of the Atmospheric River Scale

AbstractAtmospheric rivers (ARs) are narrow, elongated, transient corridors of enhanced water vapor transport that play important roles in the global water cycle. Increasing scientific and societal interests in ARs prompted the introduction of an AR scale (ranks 1–5, from weak to strong) initially focused on western North America. Aided by a global AR detection algorithm, the current study explores the insights the AR scale can help provide from a global perspective. It is found that AR event count is inversely related to AR rank and peaks in midlatitude oceans. Out of all precipitation occurrences, ARs account for an increasing fraction as the precipitation intensity considered increases. Over the oceans, this fraction is composed of comparable contributions from the five AR ranks, but the contribution of AR 5 is much smaller over land. Higher‐ranked ARs tend to initiate at lower latitudes, terminate at higher latitudes, but follow a less sloped track due to longer zonal displacement. Sensitivity analysis indicates that if ARs are defined using a sole IVT threshold of 250 kg m−1 s−1 globally but with the tropics excluded, the spatiotemporal patterns of key AR event characteristics are largely similar to those described above, except AR events are more frequent by a factor of ∼1.5–2 depending on the AR rank. The results demonstrate the potential of the AR scale in helping evaluate and communicate ARs' influences globally, where the uniform scaling facilitates intercomparisons across different regions and the perception of impacts can be adjusted according to local climatology.

The Sensitivityof GPS Precipitable Water Vapor Jumps to Intense Precipitation Associated with Tropical Organized Convective Systems

The Global Positioning System (GPS) consists of a constellation of satellites that transmit radio frequency signals to many users with varied applications. For meteorological purposes, the based-ground GPS receivers can provide high-quality column or precipitable water vapor (PWV), as obtained by radiosondes, but with high temporal resolution and low cost. A dense GPS network containing 16 ground-based receivers was installed in Belém city, Brazil, during the period 2–29 June 2011. This network provides a unique opportunity to evaluate the sensitivityof rapid increases in GPS PWV (GPS PWV jumps to the intense precipitation often associated with tropical organized convective systems. Results reveal a characteristic timescale of water vapor convergence before GPS-PWV maximum, which can be used for indicating the occurrence of precipitation associated with organized convective systems. A PWV increase of 4 mm h−1 in a period of an hour or 30 min before the maximum peak GPS-PWV (a peak of at least 57 mm) was observed during organized convection events. The contingency table obtained indicates a probability of detection of 84% and a false alarm ratio of 25% to forecast precipitation events. These results obtained suggest that GPS-PWV jumps can be employed to predict the events associated with organized convection.

The underestimation of spring precipitation over South China is caused by the weak simulations of the dynamic motion in CMIP6 models

AbstractThis study investigates the performance of the 23 CMIP6 models in simulating spring precipitation over China and preliminarily explores the reasons for the underestimation of spring precipitation over South China (SC). The results show that the CMIP6 models can generally capture spring precipitation over China but have distinct underestimations in SC. In addition to analysing the results of the multimodel ensemble mean (MME), based on the regional mean spring precipitation differences over SC, we also analyse five models with greater overestimated precipitation amounts composing the high‐value MME (H_MME) and five models with greater underestimated precipitation amounts composing the low‐value MME (L_MME) as comparisons. Moisture budget analysis reveals that the underestimated dynamic component of vertical moisture advection mainly causes the negative biases of spring precipitation over SC. Further analyses indicate that the underestimation of the intensity of the East Asian subtropical jet (EASJ) generally causes weakened secondary meridional circulation to the south of 30°N and moisture convergence over SC in CMIP6 models. Consequently, less moistened air would be lifted to high levels, providing an unfavourable background for the occurrence of spring precipitation and inducing underestimation compared with the observations. The modelling EASJ shows much stronger (weaker) H_MME (L_MME), which generally enhances (weakens) the dynamic component of the secondary circulation over SC, favourable for the increase (decrease) in spring precipitation.

Errors of five satellite precipitation products for different rainfall intensities

Revealing the errors of the satellite precipitation products (SPPs) for various rainfall intensity groups is crucial for their applications in the hydro-meteorological field. However, the spatial maps of errors of SPPs for different rainfall intensity groups and the impact of elevation on them are still unclear. In this study, the spatial maps of errors of the five satellite precipitation products (i.e., IMERG-Late, IMERG-Final, GSMaP-MVK, GSMaP-Gauge, and PERSIANN-CCS) for the four rainfall intensity groups (i.e., light precipitation, moderate precipitation, heavy precipitation, and storm) are depicted. A novel score, namely the relative rainfall occurrence bias (ROB), is proposed as a means to evaluate the reproducibility of the spatial patterns of SPPs for different surface rainfall intensity occurrences. All five SPPs cannot reproduce the spatial patterns of the four surface rainfall intensity occurrences. Despite that, all SPPs except for PERSIANN-CCS can capture almost all rainfall intensity groups (except light precipitation) because their probability of detection (POD) values exceeds 0.8. Moreover, we found that the detection capability of SPPs for light precipitation decreases with the increasing standard deviation of elevation (SDE) but is the opposite for bias, while the impacts of elevation on the errors of SPPs for other rainfall intensity groups are unapparent. The overestimations of the number of surface heavy precipitation and storm occurrences for IMERG-Late and GSMaP-MVK are mainly due to overestimating the rainfall amount of the lower rain-rate surface rainfall events, while their total biases for heavy precipitation and storms originate from hit bias. The potential limitations of the bias correction algorithms used in the IMERG and GSMaP retrieval systems in correcting different rainfall intensity groups are identified by comparing the performance between gauge-adjusted products and satellite-only products. Finally, the optimal SPP precipitation product for each rainfall intensity group is discussed. The findings reported in this study can provide valuable information for data users to select a product that best meets the requirements of the applications.

Changing seasonality of daily and monthly precipitation extremes for the contiguous USA and possible connections with large‐scale climate patterns

AbstractTemporal changes in the seasonality of extreme precipitation, and possible teleconnections between the seasonality of extreme precipitation and large‐scale climate patterns are not well understood. In this study, we investigated temporal changes in seasonality of annual daily maximum (ADM) and monthly maximum (MM) precipitation indices over the period 1951–2014 for 1,108 stations across the contiguous USA. We also examined seasonality of extreme precipitation during negative and positive phases of three major oscillations: the El Niño–Southern Oscillation, the Northern Atlantic Oscillation, and the Pacific Decadal Oscillation. Our results show that many climate regions within the contiguous USA display distinct seasonality for both ADM and MM. Comparison of seasonality between two historical records of equal length, that is, before and after 1981, shows great spatial variability across the contiguous USA. While a spatial coherence of change in the mean date of occurrence of extreme precipitation across a large area is not visible, a cluster of stations showing decrease in strength of seasonality for the recent period is concentrated in the eastern Gulf Coast and coastal sites of Northeast and Northwest regions. Extreme precipitation seasonality during negative and positive phases of three climate indices revealed that large‐scale climate variabilities have a strong influence on the mean date of occurrence of extreme precipitation but generally weak influence on the strength of seasonality in the contiguous USA. Results from our study might be helpful for sustainable water resource management, flood risk mitigation, and prediction of future precipitation seasonality.

Water dynamics of cover crops: No evidence for relevant water input through occult precipitation

AbstractRising temperatures and disruption of rainfall patterns due to climate change make water a limiting growth factor even in regions of temperate climates. Thus, producing ‘more crop per drop’ is of utmost importance. While cover crops provide many benefits to cropping systems, their influence on soil water is discussed controversially. While an increase in transpiration can lead to soil water depletion, the reduction of evaporation in combination with possible additional water inputs could provide a water benefit for a succeeding crop. Occult precipitation could be such an additional water input. The objective of this study was to quantify whether cover crops provide a net water benefit over a bare fallow due to the occurrence of occult precipitation. In a 2‐year experiment, seven different cover crops were cultivated in pure stands and as a mixture under semi‐controlled conditions in a container experiment. Water fluxes and meteorological conditions were closely monitored. Although favourable conditions occurred during both vegetation periods, we found no evidence of occult precipitation. In autumn, soil water was depleted by fast‐growing cover crops. In winter, soil water was recharged due to the early preparation of a mulch layer combined with high winter precipitation while in early spring rising temperatures increased transpiration losses of a winter‐hardy cover crop, leading to a reduction of soil water. For middle European conditions, this shows that (1) living cover crops do not provide any water benefits and that (2) soil water recharge in winter is highly dependent on meteorological conditions and cover crop management. From a water budget viewpoint, negative effects on a succeeding cash crop can only be prevented if cover crops are terminated early enough for replenishment of soil water.

Unfolding unique features of precipitation-temperature scaling across India

Warming of the climate is now unequivocal. However, probable dynamics of changes in the precipitation regimes remains disputable under potential future warming. Theoretically, increasing atmospheric heat translates to increase the atmospheric moisture holding capacity at the Clausius-Clapeyron (C-C) scaling rate in the absence of moisture limitation, which in turn raises the possibilities of more intense precipitation events. Here we investigated the scaling relationship between observed and reanalysis precipitation with surface air temperature and dew point temperature at daily and sub-daily time scales on annual and season-wise basis. To reach a robust conclusion, entire Indian mainland is considered as the study area that spans across a vast climatic characteristics. More influential temperature dependence is found for heavier precipitation events than the lighter ones on annual basis as well as for different seasons. Negative and peak type scaling patterns between the daily surface air temperature (SAT) and precipitation is noticed across the different climatic regimes of the study region. In contrast, positive dependence between dew point temperature (DPT) and precipitation is obtained to be dominant across the study region. Negative sensitivity noticed for the daily surface temperature is mainly the consequence of the local cooling effect due to the occurrence of precipitation and the moisture limitation at higher end of the local temperature. In general, the scaling relation varies from season to season, which tend towards a negative scaling in hotter seasons, but a positive scaling in colder seasons. Extreme precipitation can be better portrayed by sub-daily temperature conditions prior to the start of the storm events. Scaling relationship obtained between the sub-daily precipitation and surface air and dew point temperature exhibits greater consistency in the relationship across the regions. The Western Ghats region is consistently noticed to exhibit a positive scaling relation, whereas rest of the country exhibits mostly a peak type relation. The SAT considered up to 6-h prior to the precipitation might not reflect the actual response of precipitation towards the temperature increase, possibly due to the prevailing cloudy conditions preceding the precipitation event. Findings of this study provides a better understanding related to the anticipated changes in precipitation regimes under future climate with a warming condition across different climatic regimes.

Anthropogenic influence on extremes and risk hotspots

Study of the frequency and magnitude of climate extremes as the world warms is of utmost importance, especially separating the influence of natural and anthropogenic forcing factors. Record-breaking temperature and precipitation events have been studied using event-attribution techniques. Here, we provide spatial and temporal observation-based analyses of the role of natural and anthropogenic factors, using state-of-the-art time series methods. We show that the risk from extreme temperature and rainfall events has severely increased for most regions worldwide. In some areas the probabilities of occurrence of extreme temperatures and precipitation have increased at least fivefold and twofold, respectively. Anthropogenic forcing has been the main driver of such increases and its effects amplify those of natural forcing. We also identify risk hotspots defined as regions for which increased risk of extreme events and high exposure in terms of either high Gross Domestic Product (GDP) or large population are both present. For the year 2018, increased anthropogenic forcings are mostly responsible for increased risk to extreme temperature/precipitation affecting 94%/72% of global population and 97%/76% of global GDP relative to the baseline period 1961–1990.

Extreme precipitations and their influence on the River flood Hazards: A case study of the Sana River Basin in Bosnia and Herzegovina

The subject of the research paper is the use of remote sensing in monitoring and analyzing the impact of climate change on the occurrence of extreme precipitation, and the cause-and-effect occurrence of floods in the area of the Sana River Basin in Bosnia and Herzegovina. The goal is to process the "product" of remote sensing to identify the time intervals of occurrence of extreme precipitation, to assess their impact on water levels, and to map potential floods in space. Spatial identification of zones that are at risk of flooding is an integral part of the aforementioned goal. Precipitation monitoring was performed by processing Climate Hazards Group InfraRed Precipitation with Station Data through the Google Earth Engine platform. The observed 30-year period (1992-2022) was compared with the average precipitation for 2017, 2018 and 2019. The impact of extreme precipitation on the water level of the Sana River was analyzed. Flooding periods have been identified: February and December 2017, March 2018 and May 2019. Mapping of flooded areas was carried out by pre-processing and post-processing of Sentinel-1 radar satellite images. The total flooded area is: 710.38 ha (February 2017), 496.79 ha (December 2017), 417.86 ha (March 2018) and 422.42 ha (May 2019). Based on the identified flooded areas, a flood risk map was created on the main course of the Sana River. The research contributes to a better understanding of the changes that occur in the area under the influence of climate change, and the data presented are important for numerous practical issues in the field of water resource management and flood protection.

Stochastic modelling of the daily precipitation occurrence in the Tocantins-Araguaia hydrographic region, Amazon, Brazil

Evaluating the temporal and spatial variation of the occurrence of dry and rainy days is essential for planning the use of water resources. This article evaluated the behaviour of daily precipitation in the Tocantins-Araguaia hydrographic region (TAHR). The 1st-order stationary Markov chain (MC) of two states was used without considering the spatial correlation between the rainfall gauge stations. The developed model was efficient in estimating the occurrences of daily precipitation for the entire TAHR, as the maximum errors found were equal to RMSE: 14.1568, RSR: 0.0149, NSE: 0.9973 and PBIAS: -1.7650. However, the areas located in the Amazon-Cerrado Biome (Ecotone) require more attention due to the greater occurrence of consecutive drought days. Therefore, it is suitable to use MCs of higher orders for greater accuracy. In addition, the transition probabilities that led to rain conditions were greater when they were closer to the Atlantic Ocean, while the transition probabilities that led to drought conditions were greater in the areas located in the Cerrado biome.