Frontal Rainfall Observation by a Commercial Microwave Communication Network

2009 ◽  
Vol 48 (7) ◽  
pp. 1317-1334 ◽  
Author(s):  
Artem Zinevich ◽  
Hagit Messer ◽  
Pinhas Alpert
Keyword(s):  
Communication Network ◽  
Rain Rate ◽  
Temporal Dynamics ◽  
Rain Gauge ◽  
Time Interval ◽  
Time Model ◽  
Near Surface ◽  
Novel Approach ◽  
Spatial Reconstruction ◽  
Microwave Communication

Abstract A novel approach for reconstruction of rainfall spatial–temporal dynamics from a wireless microwave network is presented. It employs a stochastic space–time model based on a rainfall advection model, assimilated using a Kalman filter. The technique aggregates the data in time and space along the direction of motion of the rainfall field, which is recovered from the simultaneous observation of a multitude of microwave links. The technique is applied on a standard microwave communication network used by a cellular communication system, comprising 23 microwave links, and it allows for observation of near-surface rainfall at the temporal resolutions of 1 min. The accuracy of the method is demonstrated by comparing instantaneous rainfall estimates with measurements from five rain gauges, reaching correlations of up to 0.85 at the 1-min time interval with a bias and RMSE of −0.2 and 4.2 mm h−1, respectively, and up to 0.96 with RMSE of 1.6 mm h−1 at the 10-min time interval for a 22-h intensive rainstorm with an average rain rate of 3.0 mm h−1 and a peak rain rate of 84 mm h−1. The results are compared with those of other spatial reconstruction techniques. The proposed dynamic rainfall reconstruction approach can be applied to larger-scale dynamic rainfall assimilation methods, enabling interpolation over data-void regions and straightforward incorporation of data from other sources, for example, rain gauge networks and radars.

Correlation between near-surface electromagnetic soil parameters and early-time GPR signals: An experimental study

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. A25-A28 ◽  
Author(s):  
Elena Pettinelli ◽  
Giuliano Vannaroni ◽  
Barbara Di Pasquo ◽  
Elisabetta Mattei ◽  
Andrea Di Matteo ◽  
...  
Keyword(s):  
Electrical Properties ◽  
Early Time ◽  
Test Site ◽  
Time Domain Reflectometry ◽  
Soil Parameters ◽  
Time Interval ◽  
Near Surface ◽  
Novel Approach ◽  
Natural Test ◽  
Ground Penetrating

We explore a new approach to evaluate the effect of soil electromagnetic parameters on early-time ground-penetrating radar (GPR) signals. The analysis is performed in a time interval which contains the direct airwaves and ground waves, propagating between transmitting and receiving antennas. To perform the measurements we have selected a natural test site characterized by very strong lateral gradient of the soil electrical properties. To evaluate the effect of the subsoil permittivity and conductivity on the radar response we compare the envelope amplitude of the GPR signals received in the first [Formula: see text] within [Formula: see text]-wide windows, with the electrical properties ([Formula: see text] and [Formula: see text]) determined using time-domain reflectometry (TDR). The results show that the constitutive soil parameters strongly influence early-time signals, suggesting a novel approach for estimating the spatial variability of water content with GPR.

scholarly journals Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xichuan Liu ◽  
Taichang Gao ◽  
Yuntao Hu ◽  
Xiaojian Shu
Keyword(s):  
Drop Size ◽  
Rain Rate ◽  
Monte Carlo Model ◽  
Rain Gauge ◽  
Sampling Schemes ◽  
Distribution Parameters ◽  
Optimum Sampling ◽  
Simulation Results ◽  
The Impact ◽  
Good Agreement

In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.

Tail asymptotics of an infinitely divisible space-time model with convolution equivalent Lévy measure

2021 ◽  
Vol 58 (1) ◽  
pp. 42-67 ◽  
Author(s):  
Mads Stehr ◽  
Anders Rønn-Nielsen
Keyword(s):  
Space Time ◽  
Time Interval ◽  
Lévy Measure ◽  
Infinitely Divisible ◽  
Time Model ◽  
Spatial Object ◽  
Tail Behaviour ◽  
Fixed Radius ◽  
The Right ◽  
Space Time Model

AbstractWe consider a space-time random field on ${{\mathbb{R}^d} \times {\mathbb{R}}}$ given as an integral of a kernel function with respect to a Lévy basis with a convolution equivalent Lévy measure. The field obeys causality in time and is thereby not continuous along the time axis. For a large class of such random fields we study the tail behaviour of certain functionals of the field. It turns out that the tail is asymptotically equivalent to the right tail of the underlying Lévy measure. Particular examples are the asymptotic probability that there is a time point and a rotation of a spatial object with fixed radius, in which the field exceeds the level x, and that there is a time interval and a rotation of a spatial object with fixed radius, in which the average of the field exceeds the level x.

Temporal dynamics of encrusting communities during the Late Devonian: a case study from the Central Devonian Field, Russia

Paleobiology ◽  
2017 ◽  
Vol 43 (4) ◽  
pp. 550-568 ◽  
Author(s):  
Michał Zatoń ◽  
Tomasz Borszcz ◽  
Michał Rakociński
Keyword(s):  
Temporal Dynamics ◽  
Small Sample ◽  
Time Interval ◽  
Faunal Turnover ◽  
Central Devonian Field ◽  
Before And After ◽  
Substrate Size ◽  
Mass Extinction Event ◽  
Diversity Dynamics

AbstractIn this study we focused on the dynamics of encrusting assemblages preserved on brachiopod hosts collected from upper Frasnian and lower Famennian deposits of the Central Devonian Field, Russia. Because the encrusted brachiopods come from deposits bracketing the Frasnian/Famennian (F/F) boundary, the results also shed some light on ecological differences in encrusting communities before and after the Frasnian–Famennian (F-F) event. To explore the diversity dynamics of encrusting assemblages, we analyzed more than 1300 brachiopod valves (substrates) from two localities. Taxon accumulation plots and shareholder quorum subsampling (SQS) routines indicated that a reasonably small sample of brachiopod host valves (n=50) is sufficient to capture the majority of the encrusting genera recorded at a given site. The richness of encrusters per substrate declined simultaneously with the number of encrusting taxa in the lower Famennian, accompanied by a decrease in epibiont abundance, with a comparable decrease in mean encrustation intensity (percentage of bioclasts encrusted by one or more epibionts). Epibiont abundance and occupancy roughly mirror each other. Strikingly, few ecological characteristics are correlated with substrate size, possibly reflecting random settlement of larvae. Evenness, which is negatively correlated with substrate size, shows greater within-stage variability among samples than between Frasnian and Famennian intervals and may indicate the instability of early Famennian biocenoses following the faunal turnover. The occurrence distribution of encrusters points to nonrandom associations and exclusions among several encrusting taxa. However, abundance and occupancy of microconchids remained relatively stable throughout the sampled time interval. The notable decline in abundance (~60%) and relatively minor decline in diversity (~30%) suggest jointly that encrusting communities experienced ecological collapse rather than a major mass extinction event. The differences between the upper Frasnian and lower Famennian encrusting assemblages may thus record a turnover associated with the F-F event.

scholarly journals Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Radar Reflectivity ◽  
Time Shift ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Reflectivity Data ◽  
Rain Rates ◽  
Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

Evaluation of Global Forecast System (GFS) Medium-Range Precipitation Forecasts in the Nile River Basin

2021 ◽  
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael ◽  
Vahid Nourani
Keyword(s):  
Temporal Dynamics ◽  
Disease Outbreaks ◽  
Rain Gauge ◽  
Global Forecast System ◽  
Forecast System ◽  
Forecast Performance ◽  
Weather Forecasts ◽  
Rain Gauges ◽  
Basin Scale ◽  
Medium Range

Abstract Reliable weather forecasts are valuable in a number of applications, such as, agriculture, hydropower, and weather-related disease outbreaks. Global weather forecasts are widely used, but detailed evaluation over specific regions is paramount for users and operational centers to enhance the usability of forecasts and improve their accuracy. This study presents evaluation of the Global Forecast System (GFS) medium-range (1 day – 15 day) precipitation forecasts in the nine sub-basins of the Nile basin using NASA’s Integrated Multi-satellitE Retrievals (IMERG) “Final Run” satellite-gauge merged rainfall observations. The GFS products are available at a temporal resolution of 3-6 hours, spatial resolution of 0.25°, and its version-15 products are available since 12 June 2019. GFS forecasts are evaluated at a temporal scale of 1-15 days, spatial scale of 0.25° to all the way to the sub-basin scale, and for a period of one year (15 June 2019 – 15 June 2020). The results show that performance of the 1-day lead daily basin-averaged GFS forecast performance, as measured through the modified Kling-Gupta Efficiency (KGE), is poor (0 < KGE < 0.5) for most of the sub-basins. The factors contributing to the low performance are: (1) large overestimation bias in watersheds located in wet climate regimes in the northern hemispheres (Millennium watershed, Upper Atbara & Setit watershed, and Khashm El Gibra watershed), and (2) lower ability in capturing the temporal dynamics of watershed-averaged rainfall that have smaller watershed areas (Roseires at 14,110 sq. km and Sennar at 13,895 sq. km). GFS has better bias for watersheds located in the dry parts of the northern hemisphere or wet parts of the southern hemisphere, and better ability in capturing the temporal dynamics of watershed-average rainfall for large watershed areas. IMERG Early has better bias than GFS forecast for the Millennium watershed but still comparable and worse bias for the Upper Atbara & Setit, and Khashm El Gibra watersheds. The variation in the performance of the IMERG Early could be partly explained by the number of rain gauges used in the reference IMERG Final product, as 16 rain gauges were used for the Millennium watershed but only one rain gauge over each Upper Atbara & Setit, and Khashm El Gibra watershed. A simple climatological bias-correction of IMERG Early reduces in the bias in IMERG Early over most watersheds, but not all watersheds. We recommend exploring methods to increase the performance of GFS forecasts, including post-processing techniques through the use of both near-real-time and research-version satellite rainfall products.

scholarly journals Metabolic and immune markers for precise monitoring of COVID-19 severity and treatment

2021 ◽  
Author(s):  
André F. Rendeiro ◽  
Charles Kyriakos Vorkas ◽  
Jan Krumsiek ◽  
Harjot Singh ◽  
Shashi Kapatia ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Severe Disease ◽  
Deep Understanding ◽  
Response To Therapy ◽  
High Dimensional ◽  
Time Resolved ◽  
Novel Approach ◽  
Metabolomic Data ◽  
Clinical Action ◽  
Rich Information

AbstractDeep understanding of the SARS-CoV-2 effects on host molecular pathways is paramount for the discovery of early biomarkers of outcome of coronavirus disease 2019 (COVID-19) and the identification of novel therapeutic targets. In that light, we generated metabolomic data from COVID-19 patient blood using high-throughput targeted nuclear magnetic resonance (NMR) spectroscopy and high-dimensional flow cytometry. We find considerable changes in serum metabolome composition of COVID-19 patients associated with disease severity, and response to tocilizumab treatment. We built a clinically annotated, biologically-interpretable space for precise time-resolved disease monitoring and characterize the temporal dynamics of metabolomic change along the clinical course of COVID-19 patients and in response to therapy. Finally, we leverage joint immuno-metabolic measurements to provide a novel approach for patient stratification and early prediction of severe disease. Our results show that high-dimensional metabolomic and joint immune-metabolic readouts provide rich information content for elucidation of the host’s response to infection and empower discovery of novel metabolic-driven therapies, as well as precise and efficient clinical action.

scholarly journals Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

2015 ◽  
Vol 8 (9) ◽  
pp. 3685-3699 ◽  
Author(s):  
A. Chandra ◽  
C. Zhang ◽  
P. Kollias ◽  
S. Matrosov ◽  
W. Szyrmer
Keyword(s):  
Rain Rate ◽  
Tropical Indian Ocean ◽  
Rain Gauge ◽  
Signal Attenuation ◽  
Ka Band ◽  
Automated Algorithm ◽  
Atmospheric Radiation Measurement ◽  
Microphysical Processes ◽  
The Tropics ◽  
Rain Rates

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

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