scholarly journals Global precipitation system size

2021 ◽  
Vol 16 (5) ◽  
pp. 054005
Author(s):  
Yan Zhang ◽  
Kaicun Wang
2019 ◽  
Vol 20 (9) ◽  
pp. 1907-1923 ◽  
Author(s):  
Abishek Adhikari ◽  
Chuntao Liu ◽  
Lindsey Hayden

Abstract The uncertainties in the version 5 Global Precipitation Measurement (GPM) Microwave Imager (GMI) precipitation retrievals are evaluated via comparison with the radar–radiometer (so-called “Combined”) retrievals between 40°S and 40°N. Results show the precipitation estimates are close (~7% GMI overestimation) globally. However, some specific regions, such as central Africa, the Amazon, the Himalayan region, and the tropical eastern Pacific, show a large overestimation (up to 50%) in GMI retrievals when compared to Combined retrievals. The uncertainties are further evaluated based on precipitation system properties, such as size and intensity of the system. GMI tends to underestimate precipitation volume when the system is relatively warm (>250 K) and small (<200 km2) due to the lack of ice scattering signatures. However, for large systems (>2000 km2), GMI-derived precipitation is typically higher than Combined over all surfaces. Based on the system properties, a simple bias correction methodology is proposed to implement in the Goddard Profiling Algorithm (GPROF) to reduce GMI biases. GMI precipitation volume is adjusted in each precipitation system based on the size and minimum 89 GHz polarization-corrected temperature (PCT) over land and ocean separately. The overall GMI bias is reduced to 3%, with significant improvement over land. The GMI biases (up to 50%) over the previously mentioned regions are significantly or partially removed, becoming less than 20%. This method also shows effectiveness in removing zonal and seasonal biases from GMI estimates. These results suggest the importance of utilizing the information of whole precipitation systems instead of individual pixels in the precipitation retrieval.


2020 ◽  
Author(s):  
Yan Zhang ◽  
Kaicun Wang

<p>The scale of precipitation systems can provide important information to acquire a better understanding of formation mechanism and environmental effects of precipitation as well as model promotion. However, the global geographical distribution of precipitation system scale remains poorly known from previous studies. This study uses the latest Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) data to get global patterns of precipitation system scale by grouping the contiguous rainy gridboxes during 2015-2018. Our results show that the large precipitation systems (>10<sup>3</sup> km) occur more frequently over ocean and the midlatitude land areas with low precipitation amount such as Siberia as well as the western and central parts of North America. The most apparent seasonal variation of precipitation system scale occurs over midlatitude ocean along with the northern and southern coast of South America. Most regions of the world have the highest peak in the late afternoon at around 17:00 local time (LT). In a statistical average, the relationships between scale and other precipitation properties including amount, frequency, intensity and duration all seem to be positive. The strongest associations of scale with amount, frequency, intensity and duration all occur over tropics and ocean with the highest correlation coefficient greater than 0.8.</p>


2019 ◽  
Vol 3 ◽  
pp. 1063
Author(s):  
Fatkhuroyan Fatkhuroyan

Satelit GPM (Global Precipitation Measurement) merupakan proyek kerjasama antara NASA (National Aeronautics and Space Administration) dan JAXA (Japan Aerospace Exploration Agency) serta lembaga internasional lainnya untuk membuat satelit generasi terbaru dalam rangka pengamatan curah hujan di bumi sejak 2014. Model Cuaca WRF (Weather Research and Forecasting) merupakan model cuaca numerik yang telah dipakai oleh BMKG (Badan Meteorologi Klimatologi dan Geofisika) untuk pelayan prediksi cuaca harian kepada masyarakat. Pada tanggal 27 November – 3 Desember 2017 telah terjadi bencana alam siklon tropis Cempaka dan Dahlia di samudra Hindia sebelah selatan pulau Jawa. Tujuan Penelitian ialah untuk mengetahui sebaran akumulasi curah hujan antara observasi satelit GPM dan model cuaca WRF, serta keakuratan model WRF terhadap observasi satelit GPM saat terjadinya bencana alam tersebut. Metode yang dipakai ialah dengan melakukan analisa meteorologi pertumbuhan terjadinya siklon tropis tersebut hingga terjadinya hujan sangat lebat secara temporal maupun spasial. Dari hasil analisa disimpulkan bahwa satelit GPM memiliki luasan sebaran curah hujan yang lebih kecil daripada sebaran hujan model cuaca WRF pada saat siklon tropis Cempaka dan Dahlia. Bias akumulasi sebaran hujan model cuaca WRF juga cukup bagus terhadap satelit GPM sehingga dapat dilakukan antisipasi dampak hujan lebat yang terjadi.


2019 ◽  
Author(s):  
Brian Nguyen ◽  
Guo P Chen ◽  
Matthew M. Agee ◽  
Asbjörn M. Burow ◽  
Matthew Tang ◽  
...  

Prompted by recent reports of large errors in noncovalent interaction (NI) energies obtained from many-body perturbation theory (MBPT), we compare the performance of second-order Møller–Plesset MBPT (MP2), spin-scaled MP2, dispersion-corrected semilocal density functional approximations (DFA), and the post-Kohn–Sham random phase approximation (RPA) for predicting binding energies of supramolecular complexes contained in the S66, L7, and S30L benchmarks. All binding energies are extrapolated to the basis set limit, corrected for basis set superposition errors, and compared to reference results of the domain-based local pair-natural orbital coupled-cluster (DLPNO-CCSD(T)) or better quality. Our results confirm that MP2 severely overestimates binding energies of large complexes, producing relative errors of over 100% for several benchmark compounds. RPA relative errors consistently range between 5-10%, significantly less than reported previously using smaller basis sets, whereas spin-scaled MP2 methods show limitations similar to MP2, albeit less pronounced, and empirically dispersion-corrected DFAs perform almost as well as RPA. Regression analysis reveals a systematic increase of relative MP2 binding energy errors with the system size at a rate of approximately 1‰ per valence electron, whereas the RPA and dispersion-corrected DFA relative errors are virtually independent of the system size. These observations are corroborated by a comparison of computed rotational constants of organic molecules to gas-phase spectroscopy data contained in the ROT34 benchmark. To analyze these results, an asymptotic adiabatic connection symmetry-adapted perturbation theory (AC-SAPT) is developed which uses monomers at full coupling whose ground-state density is constrained to the ground-state density of the complex. Using the fluctuation–dissipation theorem, we obtain a nonperturbative “screened second-order” expression for the dispersion energy in terms of monomer quantities which is exact for non-overlapping subsystems and free of induction terms; a first-order RPA-like approximation to the Hartree, exchange, and correlation kernel recovers the macroscopic Lifshitz limit. The AC-SAPT expansion of the interaction energy is obtained from Taylor expansion of the coupling strength integrand. Explicit expressions for the convergence radius of the AC-SAPT series are derived within RPA and MBPT and numerically evaluated. Whereas the AC-SAPT expansion is always convergent for nondegenerate monomers when RPA is used, it is found to spuriously diverge for second-order MBPT, except for the smallest and least polarizable monomers. The divergence of the AC-SAPT series within MBPT is numerically confirmed within RPA; prior numerical results on the convergence of the SAPT expansion for MBPT methods are revisited and support this conclusion once sufficiently high orders are included. The cause of the failure of MBPT methods for NIs of large systems is missing or incomplete “electrodynamic” screening of the Coulomb interaction due to induced particle–hole pairs between electrons in different monomers, leaving the effective interaction too strong for AC-SAPT to converge. Hence, MBPT cannot be considered reliable for quantitative predictions of NIs, even in moderately polarizable molecules with a few tens of atoms. The failure to accurately account for electrodynamic polarization makes MBPT qualitatively unsuitable for applications such as NIs of nanostructures, macromolecules, and soft materials; more robust non-perturbative approaches such as RPA or coupled cluster methods should be used instead whenever possible.<br>


2019 ◽  
Author(s):  
Rebecca Lindsey ◽  
Nir Goldman ◽  
Laurence E. Fried ◽  
Sorin Bastea

<p>The interatomic Chebyshev Interaction Model for Efficient Simulation (ChIMES) is based on linear combinations of Chebyshev polynomials describing explicit two- and three-body interactions. Recently, the ChIMES model has been developed and applied to a molten metallic system of a single atom type (carbon), as well as a non-reactive molecular system of two atom types at ambient conditions (water). Here, we continue application of ChIMES to increasingly complex problems through extension to a reactive system. Specifically, we develop a ChIMES model for carbon monoxide under extreme conditions, with built-in transferability to nearby state points. We demonstrate that the resulting model recovers much of the accuracy of DFT while exhibiting a 10<sup>4</sup>increase in efficiency, linear system size scalability and the ability to overcome the significant system size effects exhibited by DFT.</p>


1992 ◽  
Vol 26 (9-11) ◽  
pp. 2141-2143 ◽  
Author(s):  
Y. Wang ◽  
P. R. Anderson

Two types of seed with different surface area are used in a precipitation system to evaluate the effectiveness of seed surface characteristics on sludge dewatering properties. We expect that the surface area of the seed will stongly affect the sludge properties. The preliminary study shows that the seeded system has a lower precipitation pH and lower supersaturation level.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Chih-Chuen Lin ◽  
Phani Motamarri ◽  
Vikram Gavini

AbstractWe present a tensor-structured algorithm for efficient large-scale density functional theory (DFT) calculations by constructing a Tucker tensor basis that is adapted to the Kohn–Sham Hamiltonian and localized in real-space. The proposed approach uses an additive separable approximation to the Kohn–Sham Hamiltonian and an L1 localization technique to generate the 1-D localized functions that constitute the Tucker tensor basis. Numerical results show that the resulting Tucker tensor basis exhibits exponential convergence in the ground-state energy with increasing Tucker rank. Further, the proposed tensor-structured algorithm demonstrated sub-quadratic scaling with system-size for both systems with and without a gap, and involving many thousands of atoms. This reduced-order scaling has also resulted in the proposed approach outperforming plane-wave DFT implementation for systems beyond 2000 electrons.


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