Rainfall Estimates on a Gridded Network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016

Abstract

Abstract. 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.

Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure

“…This is not surprising given that the MENA region is the most observationally scarce region. Despite this, REGEN is able to estimate precipitation in many parts of this region, which has been shown in Contractor et al (2020). In general, the best performance obtained over the tropics is by GPCP.…”

“…The advancement of satellite technology and remote sensing retrieval algorithms together with computational capabilities have led to the development of a suite of satellite-driven estimates of precipitation at the global gridded scale. These include upscaled ground P observations (hereafter ground-based) that use sophisticated interpolation techniques that, in some cases, incorporate other remote-sensed variables (e.g., elevation) (Legates and Willmott 1990;Chen et al 2008;Becker et al 2013;Harris et al 2014;Contractor et al 2020), entirely satellite-driven datasets (Joyce et al 2004;Hong et al 2004;Huffman et al 2007;Ushio et al 2009;Ashouri et al 2015;Brocca et al 2014;Huffman et al 2015), reanalysis products (Saha et al 2010;Dee et al 2011;Kobayashi et al 2015;Derber et al 1991;Suarez et al 2005), and any combination of these (Huffman et al 1997;Joyce et al 2004;Ashouri et al 2015;Weedon et al 2014;Funk et al 2015;Bosilovich et al 2015;Beck et al 2017a;Reichle et al 2017;Beck et al 2019). These global P estimates have been able to fill the spatial gaps in in situ measurements.…”

“…Details about the type and source of errors in precipitation datasets are provided in Bytheway and Kummerow (2013), Dunn et al (2014), Bytheway and Kummerow (2013), Avila et al (2015), Awange et al (2016), Sun et al (2018), and others. Unfortunately, few datasets provide estimates for uncertainties in precipitation (e.g., Hou et al 2014;Reichle et al 2017;Schneider et al 2017;Adler et al 2018;Contractor et al 2020). Examining the adequacy of the uncertainty representation in precipitation is necessary for better characterization of the sources of errors (Steiner et al 2003) and for use of precipitation products in many applications such as water resources management and other hydrological applications (Maggioni et al 2016).…”

“…Reanalysis https://disc.gsfc.nasa.gov/datasets/M2TMNXFLX_V5.12.4/summary (MERRA-2 tavgM_2d_flx_Nx; GMAO 2015) REGEN All Stations v1-2019 (REGEN) Daily, 18 Ground-based http://dapds00.nci.org.au/thredds/catalogs/ks32/CLEX/REGEN/ REGEN_AllStns.html(Contractor 2018) …”

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

“…The VRB case study is particularly interesting from both scientific and societal perspectives. On the one hand, precipitation modelling in tropical monsoon climates is a challenging task due to strong seasonality and diurnal variations of rainfall (Turner et al, 2011;Pfeifroth et al, 2016;Cook and Vizy, 2019), and due to isolated convection systems in semiarid regions (Taylor et al, 2017;Mathon et al, 2002;Parker and Diop-Kane, 2017). On the other hand, open-access and good-quality datasets are needed for water resources management in West Africa (Roudier et al, 2014;Serdeczny et al, 2017;Di Baldassarre et al, 2010;Dinku, 2019).…”