Development of a near-real-time global in situ daily precipitation dataset for 0000–0000 UTC

In this study, we have developed a global in situ daily precipitation dataset based on quasi-real-time sub-daily observations of precipitation totals for the 0000–0000 UTC (Co-ordinated Universal Time) day everywhere in the world. The sub-daily precipitation data from meteorological stations are obtained via the World Meteorological Organization's (WMO) Global Telecommunication System (GTS) and China Meteorological Administration Net (CMANet) archived by the National Meteorological Information Centre (NMIC) in China and the Integrated Surface Database (ISD) released by the National Centers for Environmental Information (NCEI) in the USA. We have combined these three sources into a global dataset, referred to as NMIC. Accumulated precipitation totals (depending on the country and the WMO region) are transmitted at a variety of times on the GTS. Of these, about 4,500 stations report daily for the 0000–0000 UTC day. Here, we significantly add to this, by developing two-way accumulation algorithms to decompose other reported sub-daily totals to shorter intervals, and then re-cumulate them where possible to the 0000–0000 UTC day. Using these algorithms, we increase by 51.1% of the number of stations during 2009–2016 to around 6,800 day−1. Additionally, date boundary adjustment (sliding between 1 and 6 hours either side of 0000 UTC) raises the data volume to between 7,800 and 8,700 day−1. We compare our NMIC product with the First Guess Daily (FGD) product from the Global Precipitation Climatology Centre (GPCC) and GHCN-Daily from NCEI (National Centers for Environmental Information). Root mean square differences between our NMIC and GPCC FGD products over the 2009–2016 period are around 3.4–3.7 mm·day−1 and the average consistency percentage is about 75.1–76.8%. Greater differences between NMIC and GHCN-daily are found which are probably due to the non-uniform date boundary in GHCN-Daily

Laser ablation loading of a radiofrequency ion trap

The production of ions via laser ablation for the loading of radiofrequency (RF) ion traps is investigated using a nitrogen laser with a maximum pulse energy of 0.17 mJ and a peak intensity of about 250 MW/cm^2. A time-of-flight mass spectrometer is used to measure the ion yield and the distribution of the charge states. Singly charged ions of elements that are presently considered for the use in optical clocks or quantum logic applications could be produced from metallic samples at a rate of the order of magnitude 10^5 ions per pulse. A linear Paul trap was loaded with Th+ ions produced by laser ablation. An overall ion production and trapping efficiency of 10^-7 to 10^-6 was attained. For ions injected individually, a dependence of the capture probability on the phase of the RF field has been predicted. In the experiment this was not observed, presumably because of collective effects within the ablation plume.Comment: submitted to Appl. Phys. B., special issue on ion trappin

Scale issues in soil moisture modelling: problems and prospects

Soil moisture storage is an important component of the hydrological cycle and plays a key role in land-surface-atmosphere interaction. The soil-moisture storage equation in this study considers precipitation as an input and soil moisture as a residual term for runoff and evapotranspiration. A number of models have been developed to estimate soil moisture storage and the components of the soil-moisture storage equation. A detailed discussion of the impli cation of the scale of application of these models reports that it is not possible to extrapolate processes and their estimates from the small to the large scale. It is also noted that physically based models for small-scale applications are sufficiently detailed to reproduce land-surface- atmosphere interactions. On the other hand, models for large-scale applications oversimplify the processes. Recently developed physically based models for large-scale applications can only be applied to limited uses because of data restrictions and the problems associated with land surface characterization. It is reported that remote sensing can play an important role in over coming the problems related to the unavailability of data and the land surface characterization of large-scale applications of these physically based models when estimating soil moisture storage.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline