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Nina Raoult, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, and Pascal Maugis

(European Space Agency Climate Change Initiative Soil Moisture) combined product ( Dorigo et al. 2017 ). Soil moisture observations and retrievals can be used not only to evaluate the different processes in the model but also to calibrate the associated parameters, using for example data assimilation (DA) techniques. DA refers to the act of combining models and observations, while using the available knowledge about their respective uncertainties ( Tarantola 2005 ). This can be used to improve the

Open access
Ryan Gonzalez and Christian D. Kummerow

constrained by the amount of initial snowfall at the gauge site. Parameter-Elevation Regressions on Independent Slopes Model (PRISM) is considered to be a high-quality precipitation dataset in the mountains for the contiguous United States ( Daly et al. 1994 ). PRISM uses a climate-elevation regression technique to distribute climatological precipitation data observed mostly by National Weather Service Cooperative Observer Program (COOP) precipitation gauges. Lundquist et al. (2015) showed the PRISM

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Zeyu Xue and Paul Ullrich

dynamical downscaling relative to the original CMIP5/6 data. d. LOCA statistical downscaling data LOCA is a statistical downscaling technique that uses historical analogs to add fine-scale details to global climate model simulations. The LOCA dataset includes 28 downscaled CMIP5 models from 1950 to 2005 at a resolution of 0.0625° ( Pierce et al. 2014 ). Bias correction is applied in LOCA based on the Livneh observationally based gridded product ( Livneh et al. 2015 ). e. Watershed Boundary Dataset

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Rebecca Gugerli, Marco Gabella, Matthias Huss, and Nadine Salzmann

radars improves the coarse distribution of rain gauge estimates while the higher absolute accuracy of rain gauges improves the overall precipitation estimates. Rain gauge adjustment of radar-derived estimates was already attempted in the 1970s and 1980s (e.g., Cain and Smith 1976 ; Koistinen and Puhakka 1981 ; Collier et al. 1983 ; Collier 1986 ). Several refined gauge-adjustment techniques have since confirmed the improvement of the combination of radar and rain gauge networks ( Koistinen et al

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Hanqing Chen, Bin Yong, Weiqing Qi, Hao Wu, Liliang Ren, and Yang Hong

1. Introduction Accurate estimation of precipitation is essential for climate analysis, hydrological simulation, drought monitoring, flood forecasting, landslide warning, and related emergency management ( Kidd and Levizzani 2011 ; Maggioni et al. 2016 ). At present, high-quality precipitation estimation mainly depends on rain gauge networks and ground-based radars although satellite technology and satellite-based retrievals have made great progress in recent years. The widely used satellite

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Liang Chen, Trent W. Ford, and Priyanka Yadav

fully coupled atmosphere and land components in accordance with the Atmospheric Model Intercomparison Project (AMIP) protocol. Considering the model uncertainties, the second experiment is a Control simulation with atmospheric nudging to effectively drive the model states toward observations ( Wehrli et al. 2019 ). Following the approach in reference ( Wehrli et al. 2019 , 2018 ), we relax the horizontal winds toward the 6-hourly European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis

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Hanh Nguyen, Jason A. Otkin, Matthew C. Wheeler, Pandora Hope, Blair Trewin, and Christa Pudmenzky

the ET fraction, and r E T ¯ and σ ( r ET ) are its climatological mean and standard deviation, respectively, for that time of the year computed over the period 1975–2018. Note that 2019 was not included in the climatological mean because at the time of computation the year was not complete. Therefore, we fixed the climatology to 1975–2018. Further details on the AWRA-L land surface model and the ESI computational technique can be found in Nguyen et al. (2019) . Areas that lack enough in situ

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Omar V. Müller, Pier Luigi Vidale, Benoît Vannière, Reinhard Schiemann, and Patrick C. McGuire

mapping. The results showed that this procedure remarkably reduces the differences between the discharge estimates from low- and high-resolution models in most of the 5992 outlets, and thereby globally. Moreover, the method remains robust and independent of resolution when discarding observation sites that represent up to 1 × 10 3 km 3 yr −1 , or even excluding more, if the discarded sites are not those that require strong bias correction. Comparing the bias correction techniques, CDF mapping is

Open access
Sharon E. Nicholson, Douglas Klotter, and Adam T. Hartman

African gauge data, using “smart” interpolation techniques that take the spatial correlation structure into account. The CHIRPS2 data have low bias and better gauge coverage over Africa compared to other similar products ( Dezfuli et al. 2017 ). PERSIANN-CDR ( Ashouri et al. 2015 ) is also based on geostationary thermal IR brightness temperature, with a neural network approach applied to produce the precipitation estimates. The product is calibrated using NCEP/NCAR precipitation forecasts. It is bias

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Zhongkun Hong, Zhongying Han, Xueying Li, Di Long, Guoqiang Tang, and Jianhua Wang

America ( He et al. 2016 ). In addition, the random forest–based merging procedure (RF-MEP) that combines gridded precipitation products performs well over Chile for 2000–16 ( Baez-Villanueva et al. 2020 ). A recurrent neural network (RNN) model for simulating the hydrological response from various sources of rainfall was used to merge multiple precipitation sources for flash flood forecasting in Taiwan in China, indicating the potential of neural networks in merging multisource information ( Chiang

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