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Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

The rainfall regime is changing in the Catalan territory, likely in most areas in the Mediterranean Basin. This variability, spatial and temporal, means that there may be periods of severe drought combined with periods of heavy rainfall and floods. In this way, the management of water resources is complicated and can produce a high impact on different social aspects. The high convective activity leads to investigating the relationship between the electric discharges and radar parameters (reflectivity, echo top, vertically integrated liquid, and accumulated rainfall). The correlation allows identifying some elements that may be significant in terms of changes in rainfall regimes. Besides, using several radar parameters apart from precipitation accumulation reveals interesting explicit patterns of the previously known. These patterns can help better understand the precipitation behavior and the changes associated with it.

The seasonal rainfall regime is a key factor control on local ecological and social processes and is commonly thought to be stable under long‐term climate changes. Here we present a unique high‐resolution rainfall record from the Thai‐Malay Peninsula, combined with a state‐of‐the‐art transient climate simulation, demonstrating a fundamental rainfall regime shift from summer to winter during the Holocene. Transient model simulation and new sensitivity experiments further reveal that westward migration of the boundary between summer and winter rainfall regimes results in a summer to winter rainfall regime shift forced by distinct changes in summer and winter monsoons. Our findings suggest that the seasonal rainfall regime could be unstable under climate change around the boundaries of rainfall regimes in the tropics and possibly worldwide, which might be more critical for shaping both past and future ecological environments. Plain Language Summary The observed seasonal rainfall regime, which varies over time, challenges the assumption of stable seasonal patterns in reconstructions of paleorainfall, suggesting that a reappraisal of the understanding of past ecological‐social changes with respect to rainfall may be needed. In this study, we have used a high‐resolution rainfall record from the Thai–Malay Peninsula and a state‐of‐the‐art transient paleoclimate simulation to describe a novel summer to winter rainfall regime shift during the Holocene era in the tropics, which may apply to regime‐boundary regions worldwide and thus provide a new perspective on dramatic ecological and social changes recorded around regime boundary regions for both past and future studies. Key Points A unique rainfall record in the Thai‐Malay and a transient simulation suggest a summer to winter rainfall regime shift during the Holocene Transient paleoclimate simulation simulation reveals that this shift was caused by westward migration of the boundary between summer and winter rainfall regimes This regime shift could occur in regions around the boundaries of rainfall regimes in the tropics and possibly worldwide

Although precipitation patterns have long been known to shape plant distributions 1 , the effect of changing climate on the interactions of species and therefore community composition is far less understood 2 , 3 . Here, we explored how changes in precipitation alter competitive dynamics via direct effects on individual species, as well as by the changing strength of competitive interactions between species, using an annual grassland community in California. We grew plants under ambient and reduced precipitation in the field to parameterize a competition model 4 with which we quantified the stabilizing niche and fitness differences that determine species coexistence in each rainfall regime. We show that reduced precipitation had little direct effect on species grown alone, but it qualitatively shifted predicted competitive outcomes for 10 of 15 species pairs. In addition, species pairs that were functionally more similar were less likely to experience altered outcomes, indicating that functionally diverse communities may be most threatened by changing interactions. Our results highlight how important it is to account for changes to species interactions when predicting species and community response to global change. Reduced precipitation changes competitive outcomes among plant species, and species pairs that were functionally more similar were less likely to experience these changes.

The northwestern Peruvian Amazon (NWPA) basin (78.4–75.8° W, 7.9–5.4° S) is an important region for coffee and rice production in Peru. Currently, no prediction models are available for estimating rainfall in advance during the wet season (January–February–March, JFM). Hence, we developed multiple linear regression (MLR) models using predictors derived from sea surface temperature (SST) indices of the Pacific, Atlantic, and Indian Oceans, including central El Niño (C), eastern El Niño (E), tropical South Atlantic (tSATL), tropical North Atlantic (tNATL), extratropical North Atlantic (eNATL), and Indian Ocean basin-wide with E and C removed (IOBW*) indices. Additionally, we utilized large-scale convection indices, namely, the eastern Pacific intertropical convergence zone (ITCZe) and South American Monsoon System (SAMSi) indices, for the 1981–2018 period. Rainfall in the lowland NWPA exhibits a bimodal annual cycle, whereas rainfall in the highland NWPA exhibits a unimodal annual cycle. The MLR model can be used to accurately capture the interannual variability during the wet season in the highland NWPA by utilizing predictors derived from the C and SAMSi indices. In contrast, regarding rainfall in the lowland NWPA, the Pacific SST variability, SAMS and tropical North Atlantic index were relevant. For long lead times, the MLR model provided reliable forecasts of JFM rainfall anomalies in the highlands (R3, approximately 2700 m asl) as these regions are governed by Pacific variability. However, the MLR model exhibited limitations in accurately estimating the wettest JFM season in the highlands due to the absence of a predictor for the amplified effect of the Madden–Julian Oscillation on rainfall.

An ever-increasing number of rainfall estimates is available. They are used in many important applications such as flood/drought monitoring, water management, or climate monitoring. Such data are especially valuable in sub-Saharan Africa, where rainfall has considerable socioeconomic impacts and the gauge and radar networks are sparse. The choice of a rainfall product can significantly influence the performance of such applications. This study reviews previous works, evaluating or comparing rainfall products over different parts of sub-Saharan Africa. Three types of rainfall products are considered: the gauge-only, the satellite-based, and the reanalysis ones. In addition to the global rainfall products, we included three regional ones specifically developed for Africa: the African Rainfall Climatology version 2 (ARC2), the Rainfall Estimate version 2 (RFE2), and the Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) African Rainfall Climatology and Time Series (TARCAT). The gauge density, the orography, and the rainfall regime, which vary with the climate and the season, influence the performance of the rainfall products. This review does not focus on comparing results, as many other publications doing so are already available. Instead, we propose this review as a guide through the different rainfall products available over Africa, and the factors influencing their performances. With this review, the reader can make informed decisions about which products serve their specific purpose best.

Freshwater demand in Southeast Florida is predicted to increase over the next few decades. However, shifting patterns in the intensity and frequency of drought create considerable pressure on local freshwater availability. Well-established water resources management requires evaluating and understanding long-term rainfall patterns, drought intensity and cycle, and related rainfall deficit. In this study, the presence of rainfall monotonic trends was analyzed using linear regression and Mann-Kendal trend tests. Pettit's single point detection test examined the presence of an abrupt change of rainfall. Drought in Southeast Florida is assessed using the Standardized Precipitation Index (SPI) in 3-, 6-, 12-, and 24-months scale; and the Fast Fourier Transform is applied to evaluate the frequency of each drought intensity. There was an increase of rainfall in most of the wet season months, the total wet season, and the annual total. The wet season duration showed a decrease driven by a decrease in October rainfall. Since 1990, wet season and total annual rainfall exhibited an abrupt increase. The SPI analysis has indicated that extended wetness characterizes the contemporary rainfall regime since 1995, except for the incidence of intermittent dry spells. Short-term droughts have 3-year to 5-year recurrence intervals, and sustained droughts have a 10-year and 20-year recurrence intervals. In Southeast Florida, prolonged drought limits freshwater availability by decreasing recharge, resulting in a longer hydro-period to maintain the health of the Everglades Ecosystem, and to control saltwater intrusion. The increasing dry season duration suggests the growing importance of promoting surface water storage and demand-side management practices.

Increased temperature rates have the potential to change the rainfall regime in a given region, as well as to intensify its extreme events, which may lead to significant and negative socioeconomic and environmental impacts on urban populations. However, knowledge about the extent of changes in rainfall rates in Rio de Janeiro City (RJC) remains incipient; thus, it is necessary applying indices climate change to help better understanding this phenomenon. The aim of the current study is to investigate changes in rainfall distribution and increase in the number of extreme rainfall events in RJC. Daily rainfall data deriving from fifteen weather stations distributed in RJC were analyzed in the RclimDex software and Mann–Kendall test. The analysis has shown increased rainfall rates from the beginning of the series to approximately the first ten years of study. Total rainfall rate has decreased after this period. Rainfall intensity in almost all seasons has decreased after 2005; this outcome has indicated reduced annual rainfall rate and number of wet days. However, there was prevalence of positive trends in daily rainfall rates (Rx1day) and in total rainfall of five consecutive days (Rx5day). The increased number of extreme rainfall events in RJC can cause sudden inundations, floods, runoffs and river overflows with potential to cause landslides and human death due to irregular occupation of hills and slopes.

Previous lectures have shown that to effectively explore Taiwan’s climate change or other relevant topics, long-term and stable observation datasets are required. We introduce the high-resolution grided precipitation dataset (TCCIP_PR), which was constructed by the Taiwan Climate Change projection and adaptation Information Platform (TCCIP) program from thousands of station records. Although, a high spatial-time relationship exists between the TCCIP_PR and the stations, a large uncertainty occurs over the complex terrain on the southwest windward side during the summer, due to sparse stations. To better understand the change in the extreme rainfall trends, we analyze 9 suitable indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). Our result show that the extreme rainfall intensity and frequency have continuously increased for a long time, and the consecutive dry days have decreased in recent decades, particularly over southwest Taiwan. The regime change evaluations agree that the precipitation characteristics were amplified and become more unpredictable from the early (1960–2002) to the late (2003–2017) period. For future applications or research, the calculated results of the extreme indices can be found in the printed documentation and the online retrieval system. Key Points High resolution grid rainfall data established by thousands of station records Extreme indices long-term trend detection Extreme rainfall regime change evaluation

In this paper, the rainfall trend of the West Coast Plain and Hill Agro-Climatic Region is analyzed for 117 years (1901–2017). This region is a globally recognized biodiversity hotspot and known for one of the highest rainfall receiving regions in India. Rainfall grid dataset is used for the analysis of rainfall trends on monthly, seasonal, and decadal time scales. Modified Mann–Kendall’s test, Linear Regression, Innovative Trend Analysis, Sen’s Slope test, Weibull’s Recurrence Interval, Pearson’s Coefficient of Skewness, Consecutive Disparity Index, Kurtosis, and some other important statistical techniques are employed for trend analysis. Results indicate that the rainfall trend is significant in January, July, August, September as well as the Winter season. Among all the significant trends, January and July showed a decreasing rainfall trend. July has the highest contribution (30%) among all the obtained monotonic trend to annual rainfall and coincidentally has the highest trend magnitude. August and September months with a combined contribution of 30% to annual rainfall, show an increasing monotonic trend with high magnitude whereas Winter season shows a monotonic decreasing rainfall trend with comparatively low magnitudes. Decadal analysis along with the study of recurrence interval of excess and deficit years helps to understand the decadal rhythm of trend and the magnitude of extreme monthly and seasonal events. Skewness reveals that rainfall dataset of all the periodic results is right-skewed and the recurrence interval also supports the skewness results. Sharply decreasing rainfall in July and rising rainfall in August and September is predictive of the impact on agriculture, biodiversity and indicates the rainfall regime shift in the region.