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Estimates of observed long-term changes in daily precipitation globally have been limited due to availability of high-quality observations. In this study, a new gridded dataset of daily precipitation, called Rainfall Estimates on a Gridded Network (REGEN) V1–2019, was used to perform an assessment of the climatic changes in precipitation at each global land location (except Antarctica). This study investigates changes in the number of wet days (≥1 mm) and the entire distribution of daily wet- and all-day records, in addition to trends in annual and seasonal totals from daily records, between 1950 and 2016. The main finding of this study is that precipitation has intensified across a majority of land areas globally throughout the wet-day distribution. This means that when it rains, light, moderate, or heavy wet-day precipitation has become more intense across most of the globe. Widespread increases in the frequency of wet days are observed across Asia and the United States, and widespread increases in the precipitation intensity are observed across Europe and Australia. Based on a comparison of spatial pattern of changes in frequency, intensity, and the distribution of daily totals, we propose that changes in light and moderate precipitation are characterized by changes in precipitation frequency, whereas changes in extreme precipitation are primarily characterized by intensity changes. Based on the uncertainty estimates from REGEN, this study highlights all results in the context of grids with high-quality observations., This study was funded by Australian Research Council (ARC) Grant DP160103439. MGD received funding from ARC Grant DE150100456, and the Spanish Ministry for the Economy, Industry and Competitiveness Grant RYC-2017-22964. LVA was also funded by ARC Grant CE110001028. We are also grateful to the National Centers for Environmental Information (NCEI) and the Global Precipitation Climatology Centre (GPCC) for support during the production of REGEN., Peer Reviewed, Postprint (published version)

A range of in situ, satellite and reanalysis products on a common daily 1° × 1° latitude/longitude grid were extracted from the Frequent Rainfall Observations on Grids database to help facilitate intercomparison and analysis of precipitation extremes on a global scale. 22 products met the criteria for this analysis, namely that daily data were available over global land areas from 50°S to 50°N since at least 2001. From these daily gridded data, 10 annual indices that represent aspects of extreme precipitation frequency, duration and intensity were calculated. Results were analysed for individual products and also for four cluster types: (i) in situ, (ii) corrected satellite, (iii) uncorrected satellite and (iv) reanalyses. Climatologies based on a common 13-year period (2001–2013) showed substantial differences between some products. Timeseries (which ranged from 13 years to 67 years) also highlighted some substantial differences between products. A coefficient of variation showed that the in situ products were most similar to each other while reanalysis products had the largest variations. Reanalyses however agreed better with in situ observations over extra-tropical land areas compared to the satellite clusters, although reanalysis products tended to fall into 'wet' and 'dry' camps overall. Some indices were more robust than others across products with daily precipitation intensity showing the least variation between products and days above 20 mm showing the largest variation. In general, the results of this study show that global space-based precipitation products show the potential for climate scale analyses of extremes. While we recommend caution for all products dependent on their intended application, this particularly applies to reanalyses which show the most divergence across results., LVA, MB and PLN are supported by the Australian Research Council (ARC) grants DP160103439 and CE170100023. MGD was supported by the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. Indices were calculated using the climpactv2 software (https://climpact-sci.org/get-started) and all analyses and graphics were produced using the NCAR Command Language (NCL 2013)., Peer Reviewed, Postprint (published version)

We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network – REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were quality-controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area-average estimates of daily precipitation for global land areas on a 1∘ × 1∘ latitude–longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets., This research has been supported by the Australian Research Council (grant nos. DP160103439, CE110001028 and DE150100456) and the Spanish Ministry for Science and Innovation (grant no. RYC-2017-22964), Peer Reviewed, Postprint (published version)

Understanding long-term changes in global precipitation is vital due to its impact on human and natural ecosystems. However, in many regions, confidence in precipitation changes is low due to a lack of high quality observations resulting in uncertainty in precipitation changes. This thesis investigates changes in the entire distribution of precipitation since 1950 over global land areas using a newly developed dataset of daily observations ideal for investigating climatic changes globally. The dataset developed in this thesis, Rainfall Estimates on a Gridded Network (REGEN), interpolates raw station-based daily precipitation records from multiple archives (including two of the largest) onto a 1 degree X 1 degree grid. The process of merging multiple station archives results in the highest station count (~135,000 stations) and the longest temporal record (1950-2013) of any existing global daily precipitation datasets, and is almost 30 years longer than the longest existing product. This thesis also demonstrates the importance of including observational uncertainties when developing such a dataset and intercomparing with existing products. The results presented in this thesis indicate that REGEN’s precipitation estimates are consistent with existing monthly and daily, global and regional datasets. Changes in the entire distribution of daily precipitation are investigated alongside changes in the frequency and intensity of precipitation events at each grid box over land. In doing so this thesis highlights key relationships between frequency of wet-days (>= 1 mm), precipitation intensity (amount of precipitation per rainy day) and the daily precipitation distribution. We find that precipitation intensity and extremes have increased since 1950 across the majority of global land areas. Furthermore, continental-scale increases in the frequency of wet-days are observed across Asia and the US, and similar widespread increases in the precipitation intensity are observed acros