Abstract. We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized (

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

A new approach to forecast solar irradiances using WRF and libRadtran models, validated with MERRA-2 reanalysis data and pyranometer measures

. Solar irradiance (SI) is the main driving factor contributing to climate change and energy balance between the land and atmosphere. High-quality records of global solar irradiance (GHI), direct normal irradiance (DNI) and diffuse solar irradiance (DIF) are of vital importance for solar applications, but the solar radiation observations are sparse around the world. As an alternative, numerous SI reanalysis data in grid format have been developed in regional and global scales. Among them, the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) products could provide high quality SI records with acceptable accuracy and long temporal ranges. This study attempted to improve the accuracy of GHI records derived from MERRA-2 products, and to generate grid DNI and DIF datasets for all-sky conditions over mainland China during 1981–2014, based on the REST2 model and cloud transmittance estimates combining sunshine observations. The results indicate that the estimated GHI values (GHInew) show higher agreements with GHI measurement at 17 CMA (China meteorological administrations) stations than that for the GHI records derived from MERRA-2 products (MERRA-2 GHI). Then, grid GHI, DNI and DIF datasets (0.50° (lat) *0.625° (lon)) throughout China were constructed. The results indicated that the MERRA-2 GHI records may overestimate the GHI values over mainland China. Generally, the GHI and DNI values gradually decreased during 1981-2014, however, DIF values gradually increased from 1981 to 2014, especially in 1992 (DIF = 90.914 W m−2, anomaly DIF value = 15.544 W m−2). The Qinghai Tibetan Plateau has always been an area with the highest GHI, the highest DNI and the lowest DIF values, whereas the Sichuan Basin has always been an area with the lowest GHI, the lowest DNI and the highest DIF values. The grid GHI, DNI and DIF dataset generated in this study can assist in numerous solar studies and applications. We provide these solar irradiance data in publicly available repository: https://doi.org/10.6084/m9.figshare.10026563 (Qin, W. et al., 2019).

/pdf/a-high-quality-hourly-daily-and-monthly-solar-1iylg2ljdw.pdf

A high-quality hourly, daily and monthly solar irradiancedataset in China during 1981–2014 based on MERRA-2Reanalysis products

Abstract Downward shortwave radiation (DSR) is one of the major driving forces of climate system. Knowledge of the Earth’s radiation budget is essential for improving our understanding of the Earth’s climate. Therefore, accurate estimation of DSR has great significance. Satellite remote sensing is a practical way to derive DSR with high spatial resolution and coverage. In this study, four machine learning methods, including gradient boosting regression tree (GBRT), random forest (RF), multivariate adaptive regression spline (MARS), and artificial neural network (ANN), were applied to estimate DSR at a spatial resolution of 5 km and a temporal resolution of 1 day using Advanced Very High Resolution Radiometer (AVHRR) data. The DSR estimates based on four machine learning methods were evaluated using ground measurements at 96 sites over China. The measurements were collected from the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA) from 2001 to 2003. The evaluation results showed that the GBRT method performed best at both daily and monthly time scales under both clear and cloudy sky conditions. The validation results at the daily time scale showed an overall root mean square error (RMSE) of 30.34 W m−2 and an R value of 0.90 under clear sky conditions, whereas these values were 42.03 W m−2 and 0.86, respectively, under cloudy sky conditions. The DSR estimates had an overall RMSE value of 16.93 W m−2 and an R value of 0.97 at the monthly time scale. The Clouds and Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) data sets were also used for comparison with the DSR estimates based on the GBRT method. The DSR estimates based on the GBRT method exhibited similar spatial distributions with those of the CERES-EBAF DSR product. Moreover, the DSR estimates based on the GBRT method did not show a clear overestimation tendency, as the CERES-EBAF DSR product did, at the CDC/CMA sites.

Estimation of Surface Downward Shortwave Radiation over China from AVHRR Data Based on Four Machine Learning Methods

Using trend surface method,this article discusses spatial process of the Neolithic Site i.e.Daxi culture(6.3-5.0 ka B.P.),Qujialing culture(5.0-4.6 ka B.P.) and Shijiahe culture(4.6-4.0 ka B.P.)in the middle and lower reaches of the Hanjaing Rvier.This research found that the spatial evolution of the Neolithic culture was divided into two stages:(1) Qujialing sites were diffused towards upstream along the Hanjiang River and the Yunshui River;(2) Shijiahe Cultural sites were instead of shrink in the zone of Danjiang-Zaoyang-Yunshui belt.In relation to the Holocene climate and landscape change process,we find that the elevation of the sites above the river was close to the changes of ancient floods and lake area.Therefore,this paper suggested the spatial-temporal distribution of sites is mainly controlled by paleo-floods and lake-expanding,meanwhile social factors e.g.agricultural style and cultural integration also play important roles.

Spatial Pattern of the Neolithic Cultural Sites in the Middle and Lower Reaches of Hanjiang River

This study analyzed the spatial and temporal distributions of 644 Neolithic sites in the Han River basin, China. The results showed that 31.06% of the Neolithic sites were distributed on low-altitu...

https://www.tandfonline.com/doi/pdf/10.1080/14614103.2018.1551505

Spatial-Temporal Evolution of the Distribution Pattern of Neolithic Sites in Han River Basin, China

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A high-quality hourly, daily and monthly solar irradiancedataset in China during 1981–2014 based on MERRA-2Reanalysis products

Spatial-Temporal Evolution of the Distribution Pattern of Neolithic Sites in Han River Basin, China