Precipitation Systems Research Articles

Global precipitation system scale increased from 2001 to 2020

How precipitation responds to global warming has drawn much interest from the scientific community. However, as one of the important properties of precipitation, changes in the precipitation system scale have rarely been studied. The latest retrospective merged satellite precipitation product has provided a great opportunity to investigate quasi-global precipitation system scale changes. This study uses the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) data during 2001–2020 to investigate quasi-global precipitation system scale changes. Our results indicate that, generally, quasi-global precipitation system scales exhibit a significant increasing trend, which is more significant in winter and spring than that in summer and autumn over both hemispheres. The scale of nearly all precipitation systems over land regions has increased over the last two decades. In oceanic regions, precipitation system scales increase over tropical oceans but decrease over subtropical oceans. Medium-scale precipitation systems (100–1000 km) significantly increase in scale and decrease in frequency, while large-scale precipitation systems significantly increase in frequency, which both lead to a quasi-global increase in the precipitation system scale. Diagnostic investigation based on atmospheric analysis reveals that an increase in atmospheric stability tends to suppress local convective precipitation, while an increase in the total column water vapor could help maintain and enhance precipitation system scale, which jointly contribute to quasi-global precipitation system scale increase.

Numerical Simulation of the Diurnal Cycle of a Precipitation System during KWAJEX by 2D and 3D Cloud-Resolving Models

Two-dimensional (2D) and three-dimensional (3D) cloud-resolving model (CRM) results from the Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX) were applied to analyze the diurnal cycle of cloud development in the tropics. Cloud development is intimately associated with the growth of secondary circulation, which can be analyzed in the budget of perturbation kinetic energy (PKE). The ice and liquid water path (IWP+LWP) is a fundamental parameter for estimating clouds, with the analyzed results suggesting that (1) the ice and liquid water path (IWP+LWP) and PKE values attained in convective regions were higher during the nighttime than during the daytime and that the maxima of IWP+LWP and PKE occurred at midnight in the lower troposphere in the 3D model run, and that (2) the IWP+LWP and PKE values in stratiform regions were much higher in the afternoon than in the morning, while the maxima of IWP+LWP and PKE occurred in the afternoon in the middle troposphere in the 2D model run. Further analysis demonstrated that both the high IWP+LWP and PKE values in the lower troposphere at midnight were mainly associated with the warm–humid lower troposphere in convective regions. However, those in the middle troposphere in the afternoon were primarily linked to the dry–cold upper troposphere and moist–warm lower troposphere in stratiform regions. The results further revealed that (1) both IWP+LWP and PKE exhibited shorter time scales in the 2D model runs than in the 3D model runs and that (2) the maximum IWP+LWP values occurred in the afternoon in the 2D model runs and at midnight in the 3D model runs.

Enhanced electrochemical precipitation of phosphorus in wastewater by the addition of drifting Corbicula shells.

Phosphorus (P) is a finite and essential resource, and its linear movement from mines to waste streams may result in shortages. This has encouraged efforts to recover P from sewage systems for reuse. This study developed a new electrochemical P precipitation system for the subnatant of the sludge flotation thickening process, in which drifting Corbicula shells are added to provide a supply of calcium ions (Ca2+) to promote P precipitation. However, adding Corbicula shells to coexisting suspended solids (SS) and coagulant resulted in adsorption of the shells in the neutralized and hydrophobized floc clusters, which limited their electrochemical dissolution. Adding Corbicula shells after SS removal by flotation with electrochemically generated gases resulted in their successful electrochemical dissolution, which enhanced phosphate-P removal. Increasing the amount of Corbicula shells enhanced the phosphate-P removal to a point, after which further addition simply increased Ca2+. The consumption of H+ generated near the anode for the dissolution of Corbicula shells increased the pH of the bulk solution, which enabled P precipitation not only onto the cathode but also in the bulk solution. Analysis of chemical composition in the generated particles suggests that they can be used as a slow P-release fertilizer and soil conditioner.

Water stable isotopes reveal the hydrological response of Costa Rican glacial lakes to climate variability

Lakes are generally considered a key information source for understanding paleoclimate. Here, we use stable water isotopes (δ2H and δ18O) in a high-elevation tropical glacial lake to inform about modern climate variability and local hydrological conditions. We report a data set of water isotopes in precipitation and lake water collected between June 2015 and November 2020 in the Chirripó National Park, Costa Rica. Using a linear resistance model, the isotopic information coupled with lake water temperature and hydrometeorological data allowed the calculation of seasonal evaporation to inflow ratios (E/I) for Lake Ditkevi. Isotopic variations (δ18O and d-excess) reflect seasonal changes in the evaporative conditions, with E/I ratios ranging from 2.7 ± 1.3% to 10.8 ± 5.4%. Significant correlations between lake d-excess, lake water temperature, and sea surface temperature anomalies in El Niño 3.4 region revealed the sensitive hydrological response of this high elevation tropical glacial lake to the cyclic deviations in the ocean-atmosphere domain of warm/cold El Niño Southern Oscillation episodes. Our findings contribute to i) a better understanding of the climatic controls on high-elevation precipitation and surface water systems in the tropics and ii) inform paleoclimate reconstructions in Central America.

Characterization of ensemble generation strategies: Application to three illustrative examples of Mediterranean high-impact weather

Predictability of high-impact weather constitutes a major challenge. In this study, we contribute to this relevant topic by analyzing the characteristics of multiple ensemble prediction systems aimed at sampling initial and/or model uncertainties for three exemplary heavy precipitation systems that occurred over the western Mediterranean. In particular, initial condition perturbations are generated by (i) directly downscaling the ensemble members from a global ensemble and (ii) creating perturbations by sampling a wide range of scales using an adaptation of the breeding methodology. Model error is sampled by applying stochastic perturbations to physical parameterizations and to microphysics parameters. A positive impact in terms of ensemble diversity is obtained when initial condition perturbations across a broad range of scales are applied, especially at low levels and for cases in which local factors are more relevant. Regarding stochastic model perturbations, they display very localized perturbations with low amplitude, which are insufficient to capture extreme scenarios, except when local factors play a dominant role. However, when combined with initial condition perturbations, they generally increase diversity and perturbation amplitude over areas characterized by deep moist convection. This outcome exhibits the positive impact of sampling both uncertainty sources, even in the extremely nonlinear regime that defines convective-scale phenomena.

A storm-centered multivariate modeling of extreme precipitation frequency based on atmospheric water balance

Abstract. Conventional rainfall frequency analysis faces several limitations. These include difficulty incorporating relevant atmospheric variables beyond precipitation and limited ability to depict the frequency of rainfall over large areas that is relevant for flooding. This study proposes a storm-based model of extreme precipitation frequency based on the atmospheric water balance equation. We developed a storm tracking and regional characterization (STARCH) method to identify precipitation systems in space and time from hourly ERA5 precipitation fields over the contiguous United States from 1951 to 2020. Extreme “storm catalogs” were created by selecting annual maximum storms with specific areas and durations over a chosen region. The annual maximum storm precipitation was then modeled via multivariate distributions of atmospheric water balance components using vine copula models. We applied this approach to estimate precipitation average recurrence intervals for storm areas from 5000 to 100 000 km2 and durations from 2 to 72 h in the Mississippi Basin and its five major subbasins. The estimated precipitation distributions show a good fit to the reference data from the original storm catalogs and are close to the estimates from conventional univariate GEV distributions. Our approach explicitly represents the contributions of water balance components in extreme precipitation. Of these, water vapor flux convergence is the main contributor, while precipitable water and a mass residual term can also be important, particularly for short durations and small storm footprints. We also found that ERA5 shows relatively good water balance closure for extreme storms, with a mass residual on average 10 % of precipitation. The approach can incorporate nonstationarities in water balance components and their dependence structures and can benefit from further advancements in reanalysis products and storm tracking techniques.

Suitable yeast extract concentration for the production of self-healing mortar with expanded clay as bacterial carrier

In microbial induced calcium carbonate precipitation (MICP) system, yeast extract (YE) is needed for spores germination. The aim of this research is to evaluate the minimum amount of YE in mortar that allows spores of Bacillus sphaericus to germinate with limited negative effect on mortar properties. Two YE concentrations of 2 and 5 g/l were tested and compared to a reference without YE. To protect the bacteria in the mortar matrix, spores or cells were encapsulated into porous expanded clay. The ureolytic activity of bacteria with YE variation, the mechanical properties and the healing ability of mortar were assessed. The results show that a YE concentration of 2 g/l provided acceptable mortar properties, while it was sufficient for spores to germinate and provide a satisfactory healing ability to resulting mortar. When vegetative cells are used as a healing agent, it is best to omit yeast extract from the mortar mixture.

A method for predicting hydrogen and oxygen isotope distributions across a region's river network using reach-scale environmental attributes

Abstract. Stable isotope ratios (isotope values) of surface water reflect hydrological pathways, mixing processes, and atmospheric exchange within catchments. Development of maps of surface water isotope values (isoscapes) is limited by methods to interpolate point measures across river networks. Catchment attributes that alter surface water isotope values affect downstream river reaches via flow, but some attributes such as artificial dams are no more likely to affect nearby unconnected catchments than distant ones. Hence, simple distance-based geospatial and statistical interpolation methods used to develop isoscapes for precipitation and terrestrial systems are less appropriate for river networks. We used a water-balance-based method to map long-term average δ2H and δ18O for New Zealand rivers, incorporating corrections using catchment environmental predictors. Inputs to the model are national rainfall precipitation isoscapes, a digital elevation layer, a national river water isotope monitoring dataset (3 years of monthly sampling at 58 sites), and river environmental databases covering around 600 000 reaches and over 400 000 km of rivers. Much of the spatial variability in δ2H and δ18O of New Zealand river water was explained using the initial combination of precipitation isoscapes and a simple water balance model. δ2H and δ18O isoscapes produced by subsequently applying residuals from the water balance model as a correction factor across the river network using regression kriging showed improved fits to the validation data compared to the correction using ordinary kriging. Predictors of high importance in the regression included upstream lake and wetland area, which was not strongly spatially autocorrelated nationally. Hence, additional hydrological process information such as evaporation effects can be incorporated into river isoscapes using regression kriging of residuals. The resulting isoscapes have potential applications in ecological, hydrological, and provenance studies that consider differences between surface water isotope values and those of other components of the hydrological cycle (e.g. subsurface runoff or local precipitation).

Variation and Influencing Factors of Cloud Characteristics over Qinghai Lake from 2006 to 2019

Clouds are an indispensable part of climate change, and the occurrence and development of clouds in the Qinghai Lake area (QHL) have great significance for the regional energy budget and precipitation system. To a certain extent, clouds will affect the water resources, agriculture, animal husbandry, and photovoltaic power industry in this region. In this study, we used CloudSat satellite data, combined with meteorological elements and atmospheric circulation, to analyze the cloud occurrence frequency and cloud water content in QHL. The results demonstrate that the frequency of cloud occurrences in QHL is 33% with a decreasing trend from 2006 to 2019. Altostratus and Nimbostratus are the main types of cloud systems in QHL. The cloud ice water content is 62.21 mg/m3 and the cloud liquid water content is 261.66 mg/m3. The highest value of the vertical cloud fraction occurs from March to June, at a height of 7–11 km in QHL. The height of the mixed-phase clouds is approximately 4–8 km and the ice clouds are above 8 km. The vertical distribution of ice particles is relatively dispersed, while the vertical distribution of liquid particles is relatively concentrated. The time and height of high particle effective radius and high particle concentration are consistent with the high value of cloud water content. The decrease in total cloud occurrence frequency in QHL is caused by the increase in temperature. This study helps to clarify the detailed structure of clouds and the distribution of cloud water resources, which has an important reference value for the study of climate change impact and the sustainable development of lake resources in QHL.

Stromatolite formation by Anaerolineae-dominated microbial communities in hot spring travertine in North Sumatra, Indonesia

The travertine deposits could provide a prospective geomicrobiological snapshot of the early Earth considering its similarity with ancient stromatolites. Herein, we investigated the travertine carbonate deposits in a calcareous and sulfidic hot spring at Sipoholon, Northern Sumatra, Indonesia, with an emphasis on the formation of a laminated texture similar to one observed in the stromatolites. The travertine deposits were associated with microbial mats of different colors that change from yellow, pink, and green, lowering water temperature and H2S concentration along the water passages. A phylotype analysis of the Prokaryotic 16S rRNA gene revealed that chemolithoautotrophic sulfur and hydrogen oxidizing bacteria were abundant in the yellow sediment around vent sites. At the same time, photoheterotrophs, a linage of Anaerolineae, dominated the pink to green sediment at mid- to downstream. Laminated textures are developed in pink and green-colored sediments among these categories. Monitoring water chemical parameters and sediment texture for an Anaerolineae-dominated sample collected from a midstream site revealed that daily lamination was formed due to the daytime biofilm formation under the stable chemical composition of water conditions except for dissolved oxygen concentration. Daily laminations were also formed in other samples by microbial communities with lower Anaerolineae abundance. Further, the results showed that if mineral precipitation and microbial growth rates are appropriately balanced, cyanobacteria were not essential for the lamina development. This indicating that such a geochemical system could occur in early-time stromatolites even before the evolution of cyanobacteria. The microbial-mineral precipitation systems identified in this study provide significant insights into the formation of stromatolites, which can in turn shed light on the history of early Earth.

A new pixel-to-object method for evaluating the capability of the GPM IMERG product to quantify precipitation systems

One of the major advantages of satellite precipitation estimates is that they can provide a complete picture of precipitation systems; a difficult task to achieve using sparsely distributed rain gauges. This advantage greatly enhances our understanding of natural precipitation. Also, for this reason, it is difficult to know satellite-derived precipitation system performance using a direct “object-to-object” method involving ground-truth reference data. To solve this issue, we develop a broadly applicable method, namely, a “pixel-to-object” method, which regards discrete gauges as sampling gridboxes to evaluate a satellite precipitation product from the precipitation system perspective. Approximately 46,000 AWSs recorded hourly data in China are used to evaluate the IMERG precipitation product. The results show that the smaller the precipitation systems are, the higher the false alarm proportion, the lower the miss proportion, and the more underestimated the precipitation rates are. The miss and false alarm proportions near the precipitation system boundaries are much larger than those far away from the boundaries, while the precipitation rate bias presents a negative-positive–negative bias pattern from the boundaries to the centers of precipitation systems. These results indicate the strong influences of the precipitation system scale and position in the systems on satellite product biases. A universal overestimation of precipitation system sizes is revealed, which is more severe for small systems than for large systems and in the afternoon than in the morning. The different data sources in the IMERG product throughout a day evidently influence the delineation accuracy of precipitation system size in a day.

Complex dynamics in the improved Koren–Feingold cloud–rain system

In this paper, we study the improved aerosol–cloud–precipitation system. Since in our previous article, we guessed that the delayed term y(t−τ) in the denominator tends to cause singularity. So we remove the denominator by time transformation, the original cloud–rain model is transformed into a simpler polynomial system under certain conditions, namely, the improved Koren–Feingold cloud–rain system. Fortunately, the new model meets our expectations. The main work of the present paper is to study the mechanism of cloud and rain interaction by double Hopf bifurcation analysis via the methods of multiple scales. We find some complicated dynamical behaviors of the system via analytical method, such as stable quasi-periodic solutions and chaos. The numerical simulations agree well with those of theoretical analysis, which shows that we are improving the model in the right direction, meanwhile perhaps it suggests that the MMS employed in this paper provides us an effective and accurate method of analyzing double Hopf bifurcation. The above complex dynamical phenomena are of great significance for the researchers to understand the mechanism of aerosol–cloud–precipitation system. And it is also significant to ecosystem and climate control.

Three-Dimensional Structure Analysis and Droplet Spectrum Characteristics of Southwest Vortex Precipitation System Based on GPM-DPR

This study is the first in the region to use Global Precipitation Mission Dual-Frequency Precipitation Radar (GPM-DPR) and Fengyun-2G (FY-2G) observations to qualitatively and quantitatively study the Southwest Vortex evolution characteristics during the flood season from 2019 to 2021. Furthermore, vertical characteristics of the two main precipitation types in the Southwest Vortex, stratiform and convective, were statistically analyzed at different life stages, including horizontal and vertical distribution of precipitation particles, droplet spectrum characteristics, and vertically layered precipitation contribution. The results showed that: (1) The typical convective precipitation (CP) in the developing and mature stages has strong reflectivity distribution centers in the upper and lower layers, showing characteristics related to terrain. Additionally, the high-level hydrometeor particles are mainly solid precipitation particles, and particles in the lower layers collide and coalesce in the violent vertical motion of the airflow. (2) For the three stages of CP, the reflectivity below melting layer (ML) first showed a rapid weakening trend toward the surface and then remained unchanged, significantly changing its vertical structure. The main rainfall type of the Southwest Vortex system was stratiform precipitation (SP) in the three stages. (3) In the two types of cloud precipitation, the developing stage is generally composed of large and sparse precipitation particles, the mature stage of large and dense precipitation particles, and the dissipating stage of small and sparse precipitation particles. The findings of this study reveal the three-dimensional refined structure and vertical variation characteristics of different life stages of the Southwest Vortex precipitation cloud system and provide important tools and references for improving the accuracy of numerical models and the forecast level of short-term heavy precipitation under complex terrain.

Effect of the Surface Treatment Process of Filter Bags on the Performance of Hybrid Electrostatic Precipitators and Bag Filters

Hybrid electrostatic precipitators consisting of electrostatic precipitation (ESP) and a bag filter are potential devices for ultralow emissions. The ESP captures and charges the particles; subsequently, the charged particles that escape enter the bag filter. The charged particles can cause the electric field of the filter bag to develop, thereby enhancing the filtration efficiency due to the force of the electric field. Experiments based on the coupling-reinforced electrostatic–fabric integrated precipitator system were conducted to investigate the outlet total dust concentration, dust removal efficiency, pressure drop, energy consumption of bag filter, and hybrid electrostatic precipitators with various filter bags. The measured results demonstrate that the removal performance of filter bags with smaller fiber diameters was superior. However, the pressure drop and energy consumption were high due to the increased filtration resistance. Compared to bag filters, hybrid electrostatic precipitators had lower total and grade dust mass concentrations at the outlet, higher total and grade dust removal efficiencies, a minor average pressure drop variation per minute, and lower total energy consumption. Consequently, the quality factor was utilized to comprehensively evaluate the overall performance of dust collectors. The hybrid electrostatic precipitators had a significant greater quality factor; their overall performance was superior to that of bag filters. Overall, a smaller filter bag’s fiber diameter resulted in more effective dust removal capabilities. Hybrid electrostatic precipitators with various filter bags were significantly better than bag filters in terms of dust removal performance, cycle life, and energy consumption.

Radar Reflectivity–Based Model Initialization Using Specified Latent Heating (Radar-LHI) within a Diabatic Digital Filter or Pre-Forecast Integration

Abstract A technique for model initialization using three-dimensional radar reflectivity data has been developed and applied within the NOAA 13-km Rapid Refresh (RAP) and 3-km High-Resolution Rapid Refresh (HRRR) regional forecast systems. This technique enabled the first assimilation of radar reflectivity data for operational NOAA forecast models, critical especially for more accurate short-range prediction of convective storms. For the RAP, the technique uses a diabatic digital filter initialization (DFI) procedure originally deployed to control initial inertial gravity wave noise. Within the forward-model integration portion of diabatic DFI, temperature tendencies obtained from the model cloud/precipitation processes are replaced by specified latent heating–based temperature tendencies derived from the three-dimensional radar reflectivity data, where available. To further refine initial conditions for the convection-allowing HRRR model, a similar procedure is used in the HRRR, but without DFI. Both of these procedures, together called the “Radar-LHI” (latent heating initialization) technique, have been essential for initialization of ongoing precipitation systems, especially convective systems, within all NOAA operational versions of the 13-km RAP and 3-km HRRR models extending through the latest implementation upgrade at NCEP in 2020. Application of the latent heat–derived temperature tendency induces a vertical circulation with low-level convergence and upper-level divergence in precipitation systems. Retrospective tests of the Radar-LHI technique show significant improvement in short-range (0–6 h) precipitation system forecasts, as revealed by reflectivity verification scores. Results presented document the impact on HRRR reflectivity forecasts of the radar reflectivity initialization technique applied to the RAP alone, HRRR alone, and both the RAP and HRRR. Significance Statement The large forecast uncertainty of convective situations, even at short lead times, coupled with the hazardous weather they produce, makes convective storm prediction one of the most significant short-range forecast challenges confronting the operational numerical weather prediction community. Prediction of heavy precipitation events also requires accurate initialization of precipitation systems. An innovative assimilation technique using radar reflectivity data to initialize NOAA operational weather prediction models is described. This technique, which uses latent heating specified from radar reflectivity (and can accommodate lightning data and other convection/precipitation indicators), was first implemented in 2009 at NOAA/NCEP and continues to be used in 2022 in the NCEP-operational RAP and HRRR models, making it a backbone of the NOAA rapidly updated numerical weather prediction capability.

Polygonal boundary gaps in multiple diffusion source precipitation systems in gel media.

We investigate multiple reaction-diffusion processes that engender the formation of distinct precipitation zones. In this paper, we carry out various original precipitation reactions in a gel medium, wherein the interdiffusion of the co-precipitates occurs from various sources arranged in a symmetric framework in 2D Petri dishes. The distinct precipitation zones are separated by clear polygonal boundaries, in congruence with the spatial distribution of the diffusion holes hosting the outer electrolyte. We use scanning electron microscopy, energy dispersive x-ray diffraction spectrometry, and notably powder x-ray diffraction for the characterization of the differentiated precipitate patterning zones for each system studied. The obtained patterns find their application niche in the chemical analogs of Voronoi diagrams and the rift scenery in geological landscapes.

Ensemble Representation of Satellite Precipitation Uncertainty Using a Nonstationary, Anisotropic Autocorrelation Model

AbstractThe usefulness of satellite multi‐sensor precipitation (SMP) and other satellite‐informed precipitation products in water resources modeling can be hindered by substantial errors which vary considerably with spatiotemporal scale. One approach to cope with these errors is to combine SMPs with ensemble generation methods, such that each ensemble member reflects one plausible realization of the true—but unknown—precipitation. This requires replicating the spatiotemporal autocorrelation structure of SMP errors. The climatology of this structure is unknown for most locations due to a lack of ground‐reference observations, while the unique anisotropy and nonstationarity within any particular precipitation system limit the relevance of this climatology to the depiction of individual storm systems. Characterizing and simulating autocorrelation across spatiotemporal scales has thus been called a grand challenge within the precipitation community. We introduce the Space‐Time Rainfall Error and Autocorrelation Model (STREAM), which combines uncalibrated, anisotropic and nonstationary SMP spatiotemporal correlation modeling with a pixel‐scale precipitation error model to stochastically generate ensemble precipitation fields that resemble “ground truth” precipitation. We generate STREAM precipitation ensembles at high resolution (1‐hr, 0.1°) and evaluate these ensembles at multiple scales. STREAM ensembles consistently bracket ground‐truth observations and replicate the autocorrelation structure of ground‐truth precipitation fields. STREAM is compatible with pixel‐scale error/uncertainty formulations beyond those presented here, and could be applied to other precipitation sources such as numerical weather predictions or blended products. Although ground truth is used here to parameterize pixel‐scale uncertainty, if combined with other recent work in SMP uncertainty characterization, STREAM could be used without any ground data.

The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance

Abstract The High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecast (WRF-ARW) Model that covers the conterminous United States and Alaska and runs hourly (for CONUS; every 3 h for Alaska) in real time at the National Centers for Environmental Prediction. The high-resolution forecasts support a variety of user applications including aviation, renewable energy, and prediction of many forms of severe weather. In this second of two articles, forecast performance is documented for a wide variety of forecast variables and across HRRR versions. HRRR performance varies across geographical domain, season, and time of day depending on both prevalence of particular meteorological phenomena and the availability of both conventional and nonconventional observations. Station-based verification of surface weather forecasts (2-m temperature and dewpoint temperature, 10-m winds, visibility, and cloud ceiling) highlights the ability of the HRRR to represent daily planetary boundary layer evolution and the development of convective and stratiform cloud systems, while gridded verification of simulated composite radar reflectivity and quantitative precipitation forecasts reveals HRRR predictive skill for summer and winter precipitation systems. Significant improvements in performance for specific forecast problems are documented for the upgrade versions of the HRRR (HRRRv2, v3, and v4) implemented in 2016, 2018, and 2020, respectively. Development of the HRRR model data assimilation and physics paves the way for future progress with operational convective-scale modeling. Significance Statement NOAA’s operational hourly updating convection-allowing model, the High-Resolution Rapid Refresh (HRRR), is a key tool for short-range weather forecasting and situational awareness. Improvements in assimilation of weather observations, as well as in physics parameterizations, has led to improvements in simulated radar reflectivity and quantitative precipitation forecasts since the initial implementation of HRRR in September 2014. Other targeted development has focused on improved representation of the diurnal cycle of the planetary boundary layer, resulting in improved near-surface temperature and humidity forecasts. Additional physics and data assimilation changes have led to improved treatment of the development and erosion of low-level clouds, including subgrid-scale clouds. The final version of HRRR features storm-scale ensemble data assimilation and explicit prediction of wildfire smoke plumes.

Strain-Induced Self-Rolling of Electrochemically Deposited Co(OH)2 Films into Organic–Inorganic Microscrolls

Strain-induced self-folding is a ubiquitous phenomenon in biology, but is rarely seen in brittle geological or synthetic inorganic materials. We here apply this concept for the preparation of three-dimensional free-standing microscrolls of cobalt hydroxide. Electrodeposition in the presence of structure-directing water-soluble polyelectrolytes interfering with solid precipitation is used to generate thin polymer/inorganic hybrid films, which undergo self-rolling upon drying. Mechanistically, we propose that heterogeneities with respect to the nanostructural motifs along the surface normal direction lead to substantial internal strain. A non-uniform response to the release of water then results in a bending motion of the two-dimensional Co(OH)2 layer accompanied by dewetting from the substrate. Pseudomorphic conversion into Co3O4 affords the possibility to generate hierarchically structured solids with inherent catalytic activity. Hence, we present an electrochemically controllable precipitation system, in which the biological concepts of organic matrix-directed mineralization and strain-induced self-rolling are combined and translated into a functional material.

Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data

In weather radar applications, the Z-R relationship is considered one of the most crucial factors for providing quality quantitative precipitation estimates. However, the relationship’s parameters vary in time and space, making the derivation of an optimal relationship for a specific weather radar system challenging. This research focused on the analysis of the spatiotemporal variability of the parameters for a newly installed X-Band weather radar in Athens, Greece, by performing correlation and optimization analyses between high temporal resolution weather radar and rain gauge datasets. The correlation analysis was performed to assess the available datasets and provide the base of quality control. Multiple Z-R relationships were then derived for the following three optimization procedures; event-based relationships, station-based relationships, and a single area-based relationship. The results highlighted the region’s spatial variability regarding the Z-R relationship and the correlation between the station location and its parameter values. Moreover, it was found that stations near the coast and the front end of precipitation systems featured parameter values typical of convective type events. Finally, a single Z-R relationship was determined under a calibration and validation scheme, Z = 321R1.53,, which was validated with good agreement.