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High-quality, freely accessible, long-term precipitation estimates with fine spatiotemporal resolution play essential roles in hydrologic, climatic, and numerical modeling applications. However, the existing daily gridded precipitation datasets over China are either constructed with insufficient gauge observations or neglect topographic effects and boundary effects on interpolation. Using daily observations from 2839 gauges located across China and nearby regions from 1961 to the present, this study compared eight different interpolation schemes that adjusted the climatology based on a monthly precipitation constraint and topographic characteristic correction, using an algorithm that combined the daily climatology field with a precipitation ratio field. Results from these eight interpolation schemes were validated using 45 992 high-density daily gauge observations from 2015 to 2019 across China. Of these eight schemes, the one with the best performance merges the Parameter-elevation Regression on Independent Slopes Model (PRISM) in the daily climatology field and interpolates station observations into the ratio field using an inverse-distance weighting method. This scheme had median values of 0.78 for the correlation coefficient, 8.8 mm d−1 for the root-mean-square deviation, and 0.69 for the Kling–Gupta efficiency for comparisons between the 45 992 high-density gauge observations and the best interpolation scheme for the 0.1∘ latitude × longitude grid cells from 2015 to 2019. This scheme had the best overall performance, as it fully considers topographic effects in the daily climatology field and it balances local data fidelity and global fitting smoothness in the interpolation of the precipitation ratio field. Therefore, this scheme was used to construct a new long-term, gauge-based gridded precipitation dataset for the Chinese mainland (called CHM_PRE, as a member of the China Hydro-Meteorology dataset) with spatial resolutions of 0.5, 0.25, and 0.1∘ from 1961 to the present. This precipitation dataset is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling. Free access to the dataset can be found at https://doi.org/10.6084/m9.figshare.21432123.v4 (Han and Miao, 2022).

The Three-River Source Region (TRSR), which is known as “China's Water Tower” and affects the water resources security of 700 million people living downstream, has experienced significant hydrological changes in the past few decades. In this work, we used an extended variable infiltration capacity (VIC) land surface hydrologic model (VIC-Glacier) coupled with the degree-day factor algorithm to simulate the runoff change in the TRSR during 1984–2018. VIC-Glacier performed well in the TRSR, with Nash–Sutcliffe efficiency (NSE) above 0.68, but it was sensitive to the quality of the limited ground-based precipitation. This was especially marked in the source region of the Yangtze River: when we used Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR), which has better spatial details, instead of ground-based precipitation, the NSE of Tuotuohe station increased from 0.31 to 0.86. Using the well-established VIC-Glacier model, we studied the contribution of each runoff component (rainfall, snowmelt, and glacier runoff) to the total runoff and the causes of changes in runoff. The results indicate that rainfall runoff contributed over 80 % of the total runoff, while snowmelt runoff and glacier runoff both contributed less than 10 % in 1984–2018. Climate change was the main reason for the increase in runoff in the TRSR after 2004, accounting for 75 %–89 %, except in the catchment monitored by Xialaxiu station. Among climate change factors, precipitation had the greatest impact on runoff. Finally, through a series of hypothetical climate change scenario experiments, we found that a future simultaneous increase in precipitation and temperature would increase the total runoff, rainfall runoff, and glacier runoff. The snowmelt runoff might remain unchanged because the increased precipitation, even with seasonal fluctuations, was basically completely compensated for by the decreased solid-to-liquid precipitation ratio. These findings improve our understanding of hydrological processes and provide insights for policy-makers on how to optimally allocate water resources and manage the TRSR in response to global climate change.

This study presents a comprehensive analysis of the spectral properties of 886 pulsars across a wide frequency range from 20 MHz–343.5 GHz, including a total of 86 millisecond pulsars (MSPs). The majority of the pulsars exhibit power-law behavior in their spectra, although some exceptions are observed. Five different spectral models, namely, simple power law, broken power law, low-frequency turnover, high-frequency cutoff, and double turnover, were employed to explore the spectral behaviors. The average spectral index for pulsars modeled with a simple power law is found to be −1.64 ± 0.80, consistent with previous studies. Additionally, significant correlations between the spectral index and characteristic parameters are observed, particularly in MSPs, while no strong correlation is observed in normal pulsars. Different models show variations in the most influential characteristic parameters associated with the spectral index, indicating diverse dominant radiation mechanisms in MSPs. Finally, this study identifies 22 pulsars of the gigahertz-peaked spectra type for the first time based on the Akaike information criterion.

This study investigated the effects of organic zinc (Zn) supplementation in early-lactation dairy cows on Zn content and distribution in raw milk and mozzarella cheese. Thirty-four multiparous dairy cows in early lactation were randomly assigned to 2 groups: basal diet (control; CON) and basal diet supplemented with a Zn AA complex (CZ). After feeding the diets for 8 wk, raw milk was collected for manufacturing mozzarella cheese. Total Zn content and Zn distribution in raw milk and cheese were determined by atomic absorption spectrophotometry. Results showed that milk fat content was significantly increased in the CZ group compared with the CON group. No significant differences in fat, protein, and moisture contents of cheese were observed between the 2 groups. Zinc contents in milk (4.25 vs. 3.85 mg/L) and cheese (38.65 vs. 27.20 mg/kg) were significantly higher in the CZ group than in the CON group. Little Zn was lost in stretch water (

Flood risk is projected to increase under future warming climates due to an enhanced hydrological cycle. Solar geoengineering is known to reduce precipitation and slow down the hydrological cycle and may therefore be expected to offset increased flood risk. We examine this hypothesis using streamflow and river discharge responses to Representative Concentration Pathway 4.5 (RCP4.5) and the Geoengineering Model Intercomparison Project (GeoMIP) G4 scenarios. Compared with RCP4.5, streamflow on the western sides of Eurasia and North America is increased under G4, while the eastern sides see a decrease. In the Southern Hemisphere, the northern parts of landmasses have lower streamflow under G4, and streamflow of southern parts increases relative to RCP4.5. We furthermore calculate changes in 30-, 50-, and 100-year flood return periods relative to the historical (1960–1999) period under the RCP4.5 and G4 scenarios. Similar spatial patterns are produced for each return period, although those under G4 are closer to historical values than under RCP4.5. Hence, in general, solar geoengineering does appear to reduce flood risk in most regions, but the overall effects are largely determined by this large-scale geographic pattern. Although G4 stratospheric aerosol geoengineering ameliorates the Amazon drying under RCP4.5, with a weak increase in soil moisture, the decreased runoff and streamflow leads to an increased flood return period under G4 compared with RCP4.5.

As a native tree species, Ulmus pumila var. sabulosa (sandy elm) is widely distributed in the Horqin Sandy Land, China. However, seedlings of this species have to withstand various depths of sand burial after emergence because of increasing soil degradation, which is mainly caused by overgrazing, climate change, and wind erosion. An experiment was conducted to evaluate the changes in its survivorship, morphological traits, and biomass allocation when seedlings were buried at different burial depths: unburied controls and seedlings buried vertically up to 33, 67, 100, or 133 % of their initial mean seedling height. The results showed that partial sand burial treatments (i.e., less than 67 % burial) did not reduce seedling survivorship, which still reached 100 %. However, seedling mortality increased when sand burial was equal to or greater than 100 %. In comparison with the control treatment, seedling height and stem diameter increased at least by 6 and 14 % with partial burial, respectively. In the meantime, seedling taproot length, total biomass, and relative mass growth rates were at least enhanced by 10, 15.6, and 27.6 %, respectively, with the partial sand burial treatment. Furthermore, sand burial decreased total leaf area and changed biomass allocation in seedlings, partitioning more biomass to aboveground organs (e.g., leaves) and less to belowground parts (roots). Complete sand burial after seedling emergence inhibited its re-emergence and growth, even leading to death. Our findings indicated that seedlings of sandy elm showed some resistance to partial sand burial and were adapted to sandy environments from an evolutionary perspective. The negative effect of excessive sand burial after seedling emergence might help in understanding failures in recruitments of sparse elm in the study region.

Parameter specification usually has significant influence on the performance of land surface models (LSMs). However, estimating the parameters properly is a challenging task due to the following reasons: (1) LSMs usually have too many adjustable parameters (20 to 100 or even more), leading to the curse of dimensionality in the parameter input space; (2) LSMs usually have many output variables involving water/energy/carbon cycles, so that calibrating LSMs is actually a multi-objective optimization problem; (3) Regional LSMs are expensive to run, while conventional multi-objective optimization methods need a large number of model runs (typically ~105–106). It makes parameter optimization computationally prohibitive. An uncertainty quantification framework was developed to meet the aforementioned challenges, which include the following steps: (1) using parameter screening to reduce the number of adjustable parameters, (2) using surrogate models to emulate the responses of dynamic models to the variation of adjustable parameters, (3) using an adaptive strategy to improve the efficiency of surrogate modeling-based optimization; (4) using a weighting function to transfer multi-objective optimization to single-objective optimization. In this study, we demonstrate the uncertainty quantification framework on a single column application of a LSM – the Common Land Model (CoLM), and evaluate the effectiveness and efficiency of the proposed framework. The result indicate that this framework can efficiently achieve optimal parameters in a more effective way. Moreover, this result implies the possibility of calibrating other large complex dynamic models, such as regional-scale LSMs, atmospheric models and climate models.

Proper specification of model parameters is critical to the performance of land surface models (LSMs). Due to high dimensionality and parameter interaction, estimating parameters of an LSM is a challenging task. Sensitivity analysis (SA) is a tool that can screen out the most influential parameters on model outputs. In this study, we conducted parameter screening for six output fluxes for the Common Land Model: sensible heat, latent heat, upward longwave radiation, net radiation, soil temperature and soil moisture. A total of 40 adjustable parameters were considered. Five qualitative SA methods, including local, sum-of-trees, multivariate adaptive regression splines, delta test and Morris methods, were compared. The proper sampling design and sufficient sample size necessary to effectively screen out the sensitive parameters were examined. We found that there are 2–8 sensitive parameters, depending on the output type, and about 400 samples are adequate to reliably identify the most sensitive parameters. We also employed a revised Sobol' sensitivity method to quantify the importance of all parameters. The total effects of the parameters were used to assess the contribution of each parameter to the total variances of the model outputs. The results confirmed that global SA methods can generally identify the most sensitive parameters effectively, while local SA methods result in type I errors (i.e., sensitive parameters labeled as insensitive) or type II errors (i.e., insensitive parameters labeled as sensitive). Finally, we evaluated and confirmed the screening results for their consistency with the physical interpretation of the model parameters.

Shape and surface topography evaluation from measured orthogonal slope/gradient data is of considerable engineering significance since many full-field optical sensors and interferometers readily output such a data accurately. This has applications ranging from metrology of optical and electronic elements (lenses, silicon wafers, thin film coatings), surface profile estimation, wave front and shape reconstruction, to name a few. In this context, a new methodology for surface profile and stress field determination based on a recently introduced non-contact, full-field optical method called digital gradient sensing (DGS) capable of measuring small angular deflections of light rays coupled with a robust finite-difference-based least-squares integration (HFLI) scheme in the Southwell configuration is advanced here. The method is demonstrated by evaluating (a) surface profiles of mechanically warped silicon wafers and (b) stress gradients near growing cracks in planar phase objects. [ABSTRACT FROM AUTHOR]

We report the first detection of polarization angle orthogonal jumps, a phenomenon previously only observed from radio pulsars, from a fast radio burst (FRB) source FRB 20201124A. We find three cases of orthogonal jumps in over 2000 bursts, all resembling those observed in pulsar single pulses. We propose that the jumps are due to the superposition of two orthogonal emission modes that could only be produced in a highly magnetized plasma, and they are caused by the line of sight sweeping across a rotating magnetosphere. The shortest jump timescale is of the order of 1 millisecond, which hints that the emission modes come from regions smaller than the light cylinder of most pulsars or magnetars. This discovery provides convincing evidence that FRB emission originates from the complex magnetosphere of a magnetar, suggesting an FRB emission mechanism that is analogous to radio pulsars despite a huge luminosity difference between two types of objects.

We report the timing analysis of PSR J1846−0513, a pulsar discovered by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in Commensal Radio Astronomy FAST Survey. The pulsar possesses a spin period of 23.36 ms and a spin-down rate ( $\dot{P}$ ) of 1.0106(3) × 10 ^−18 s s ^−1 , and it is located in an eccentric orbit ( e ∼0.208) with an orbital period of 0.61 days. The characteristic age and surface magnetic field of the pulsar are found to be 366.62 Myr and 4.9178 × 10 ^9 G, respectively, indicating that it is a recycled pulsar. Using over two years of timing data, we measure the periastron advance $\dot{\omega }$ = 0.8956(8) deg yr ^−1 . By assuming that this effect is purely relativistic, we have estimated the total mass M = 2.6287(35) M _⊙ and obtained an upper limit for the pulsar mass and a lower limit for the companion’s mass. Our results indicate that this is a double neutron star system.

We present phase-connected timing ephemerides, polarization pulse profiles, and Faraday rotation measurements of 12 pulsars discovered by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in the Commensal Radio Astronomy FAST Survey. The observational data for each pulsar span at least 1 yr. Among them, PSR J1840+2843 shows subpulse drifting, and five pulsars are detected to exhibit pulse nulling phenomena. PSR J0640−0139 and PSR J2031−1254 are isolated millisecond pulsars (MSPs) with stable spin-down rates ( $\dot{P}$ ) of 4.8981(6) × 10 ^−20 s s ^−1 and 6.01(2) × 10 ^−21 s s ^−1 , respectively. Additionally, one pulsar (PSR J1602−0611) is in a neutron star−white dwarf (WD) binary system with an 18.23-day orbit and a companion of ≤0.65 M _⊙ . PSR J1602−0611 has a spin period, companion mass, and orbital eccentricity that are consistent with the theoretical expectations for MSP−helium WD (He WD) systems. Therefore, we believe that it might be an MSP−He WD binary system. The locations of PSR J1751−0542 and PSR J1840+2843 on the $P-\dot{P}$ diagram are beyond the traditional death line. This indicates that FAST has discovered some low- $\dot{E}$ pulsars, contributing new samples for testing pulsar radiation theories. We estimated the distances of these 12 pulsars based on NE2001 and YMW16 electron density models, and our work enhances the data set for investigating the electron density model of the Galaxy.

PSR J2150+3427 is a 0.654 s pulsar discovered by the Commensal Radio Astronomy FAST Survey. From the follow-up observations, we find that the pulsar is in a highly eccentric orbit ( e = 0.601) with an orbital period of 10.592 days and a projected semimajor axis of 25.488 lt-s. Using 2.7 yr of timing data, we also measured the rate of periastron advance $\dot{\omega }$ = 0.0115(4) deg yr ^−1 . An estimate for the total mass of the system using the $\dot{\omega }$ gives M _tot = 2.59(13) M _⊙ , which is consistent with most of the known double neutron star (DNS) systems and one neutron star (NS)–white dwarf (WD) system named B2303+46. Combining $\dot{\omega }$ with the mass function of the system gives the masses of M _p < 1.67 and M _c > 0.98 M _⊙ for the pulsar and the companion star, respectively. This constraint, along with the spin period and orbital parameters, suggests that it is possibly a DNS system, and we cannot entirely rule out the possibility of an NS–WD system. Future timing observations will vastly improve the uncertainty in $\dot{\omega }$ , and are likely to allow the detection of additional relativistic effects, which can be used to modify the values of M _p and M _c . With a spin-down luminosity of $\dot{E}$ = 5.07(6) × 10 ^29 erg s ^−1 , PSR J2150+3427 is a very low-luminosity pulsar, with only the binary pulsar J2208+4610 having a smaller $\dot{E}$ .

Optically addressable paramagnetic defects in wide-band-gap semiconductors are promising platforms for quantum communications and sensing. The presence of avoided crossings between the electronic levels of these defects can substantially alter their quantum dynamics and be both detrimental and beneficial for quantum information applications. Here we present a joint theoretical and experimental study of the quantum dynamics of paramagnetic defects interacting with a nuclear spin bath at avoided crossings. We find that we can condition the clock transition of the divacancies in SiC on multiple adjacent nuclear spins states. We suppress the effects of fluctuating charge impurities and demonstrate an increased coherence time at clock transition, which is limited purely by magnetic noise. Our results pave the way to designing single defect quantum devices operating at avoided crossings.

The length of time a qubit can store information is linked to its coherence time. Here, the authors demonstrate that industrially important crystals comprising more than one species can host qubits with unexpectedly long coherence times.