Occurrence Of Precipitation Research Articles

Multiple E-Region Radar Propagation Modes Measured by the VHF SIMONe Norway System During Active Ionospheric Conditions

Multiple propagation modes between different bistatic radar links were measured during the operations of a very high frequency (VHF) 32.55 MHz radar system in northern Norway. The Spread Spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) Norway system detected meteor trails, direct transmitter to receiver signal propagation, over-the-horizon signal propagation from the SIMONe Germany system, ground and/or sea scatter, and ionospheric scatter on 27 August 2021 between 16:30–20:00 UT. These simultaneous detections were during an active ionospheric period with multiple occurrences of energetic charged particle precipitation. The SIMONe systems used continuous-wave (CW) pseudo-random phase modulated transmit signals and interferometry to make it possible to isolate each of these propagation modes and examine their characteristics. Different multistatic links at three receiver locations were analyzed, providing multistatic measurements of the regions with spatial and temporal resolutions on the order of 1.5 km and 2 s. The analysis techniques are described, with characteristics of the radar signal presented for each propagation mode and multistatic link. This study serves to highlight the capabilities of the SIMONe Norway system to research multiple aspects of ionospheric phenomena, specifically in the lower thermosphere-mesosphere boundary region.

Characteristics of summer hourly precipitation under different urbanization background in central China

The relationship between sub-daily precipitation and urbanization is widely concerned because short-term precipitation is sensitive to urbanization and difficult to predict. Using the data of summer hourly precipitation and urban development during 2007–2019 at four urban stations and an atmospheric background monitoring station in central China, this study investigates the characteristics of hourly precipitation and hourly extreme precipitation (HEP) under different urbanization background. It is found that high urbanization level may benefit precipitation intensity but not for accumulated precipitation amount and precipitation frequency, and it is also conducive to the occurrence of hourly precipitation within [20, 50) mm. Precipitation amount and frequency for hourly precipitation within [5, 50) mm have similar diurnal variation at fixed station, yet the diurnal variation of precipitation intensity is insignificant. The differences in temporal variation of precipitation are related to urbanization and terrain. Both high urbanization level and speed are conducive to summer HEP; especially summer HEP intensity may increase gradually under sustainable urbanization development. Although growth-type HEP occurs frequently with main contribution to total HEP precipitation amount in central China regardless of urbanization level, the frequency and contribution of continuous-type HEP tends to increase under high urbanization level and speed.

How China’s Fengyun Satellite Precipitation Product Compares with Other Mainstream Satellite Precipitation Products

AbstractSatellite-based and reanalysis precipitation estimates are an alternative and important supplement to rain gauge data. However, performance of China’s Fengyun (FY) satellite precipitation product and how it compares with other mainstream satellite and reanalysis precipitation products over China remain largely unknown. Here five satellite-based precipitation products (i.e., FY-2 precipitation product, IMERG, GSMaP, CMORPH, and PERSIANN-CDR) and one reanalysis product (i.e., ERA5) are intercompared and evaluated based on in situ daily precipitation measurements over mainland China during 2007–17. Results show that the performance of these precipitation products varies with regions and seasons, with better statistical metrics over wet regions and during warm seasons. The infrared–microwave combined precipitation [i.e., IMERG, GSMaP, and CMORPH, with median KGE (Kling–Gupta efficiency) values of 0.53, 0.52, 0.59, respectively] reveals better performance than the infrared-based only product (i.e., PERSIANN-CDR, with a median KGE of 0.31) and the reanalysis product (i.e., ERA5, with a median KGE of 0.43). IMERG performs well in retrieving precipitation intensity and occurrence over China, while GSMaP performs well in the middle to low reaches of the Yangtze River basin but poorly over sparsely gauged regions, e.g., Xinjiang in northwest China and the Tibetan Plateau. CMORPH performs well over most regions and has a greater ability to detect precipitation events than GSMaP. The FY-2 precipitation product can capture the overall spatial distribution of precipitation in terms of both precipitation intensity and occurrence (median KGE and CSI of 0.54 and 0.55), and shows better performance than other satellite precipitation products in winter and over sparsely gauged regions. Annual precipitation from different products is generally consistent, though underestimation exists in the FY-2 precipitation product during 2015–17.Significance StatementIntercomparison between the FY-2 precipitation product and mainstream precipitation products is valuable to guide applications of satellite precipitation products to China and its subregions. This study illustrates uncertainties in various satellite precipitation products, and could guide optimization of algorithms of precipitation retrieval and data fusion/merging to improve the accuracy and resolution of satellite precipitation products.

Long-term correlation analysis between monthly precipitable water vapor and precipitation using GPS data over China

Precipitable Water Vapor (PWV) is an important driving factor for the occurrence of precipitation. A deep understanding of the correlation between the PWV and the precipitation helps to understand the regional water cycle based on the theory of atmospheric water balance. This study aims to analyze the correlation between the precipitation and the PWV derived from Global Positioning System (GPS) observations collected from a total of 233 Global Navigation Satellite System (GNSS) stations in China mainland over 10 years. The PWV was calculated through Zenith Total Delay (ZTD) from the Precise Point Positioning (PPP) technique and metrological data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The relationship between PWV derived from GPS and the precipitation from the Tropical Rainfall Measuring Mission (TRMM) at monthly temporal resolution was analyzed through the cross-correlation analysis and the cross-wavelet analysis. Results showes that a 1-month lag was observed between monthly PWV and precipitation at some inland stations in the south-eastern region of China, which is due to the earlier peaks of precipitation caused by the quasi-stationary front in this region. After the time-lag shift, most of the stations showed a cross-correlation coefficient higher than 0.7, indicating that monthly PWV and precipitation are generally correlated over China mainland. Specifically, the cross-correlation coefficients from stations located in western China have a wide range of 0.16–0.95 and a large dispersion degree with the standard deviation (STD) of 0.2, which is due to the variable climatic conditions caused by the topographical distribution. The cross-correlation coefficients from stations located in the middle and north-eastern region of China are generally greater than 0.75 and have an STD of 0.08, while those located in the south-eastern region of China are generally less than 0.65 and have an STD of 0.09. This is because the south-eastern region of China has a relatively longer rainy season caused by the influences from Asian monsoon systems. These results could contribute to the further understanding of the regional water cycle based on the theory of atmospheric water balance within China.

Impacts of Western Disturbances on Wintertime Precipitation Over the Southeastern Tibetan Plateau

AbstractIn this work, we examine the impacts of wintertime western disturbances (WDs) on precipitation over the southeastern Tibetan Plateau (SETP) during 1979–2017. Most WDs initially formed within the central Himalayas and dissipated over southeastern China and its neighboring seas. All extreme precipitation days over the SETP region during this period were linked to WDs, often when a WD center entered the region about 10° west of the SETP. Significant warm temperature anomalies over the SETP region preceding WD arrival favored moisture accumulation there. During the passage of WDs, both strong updrafts along the eastern edge of the WD and rapid decreases in temperature over the SETP (linked to WD‐associated cold anomalies below 300 hPa) favored the occurrence of wintertime precipitation over the SETP region. WD strength and moist static energy variations over the SETP region were key factors affecting the intensity of WD‐induced precipitation, while the size and latitudinal position of the WD played minor roles. The relatively strong WDs that produced extreme precipitation days over the SETP mainly originated above the eastern Mediterranean Sea, northern Arabian Peninsula, and Iranian Plateau. A distinct transition of the circumglobal teleconnection pattern modulated the generation of strong‐intensity WDs within these major genesis regions, as well as their eastward propagation and the generation of extreme precipitation over the SETP region.

Coupling of satellite-derived precipitation products with Bartlett-Lewis model to estimate intensity-frequency-duration curves for remote areas

Intensity-frequency-duration (IFD) curves (also known as intensity-duration-frequency (IDF) curves in some regions) are widely used to take into consideration the probability of occurrence of extreme precipitation for the design of water related infrastructure. Derivation of IFD curves is based on statistical analysis of observed extreme precipitation events and thus the reliability of the curves mostly depends on the record length of observations. At sub-hourly timescales however, ground-based precipitation observations are often absent or very limited in terms of spatial coverage and record length, particularly in remote areas around the world. Given the availability of satellite-derived precipitation products (SPPs) with finer spatiotemporal resolution and near-global coverage, there is great potential to use these products in the planning and design of infrastructure. This paper proposes a novel framework, SIFD (Satellite-derived IFD curves) to combine long-term daily gauge data and sub-hourly SPP to estimate IFD curves for time intervals from 0.5 to 24 h. A recent variant of the Random Parameter Bartlett-Lewis Rectangular Pulse model (RPBLRPX) was used to disaggregate daily gauge data to derive IFD curves. In the absence of sub-daily rain gauge data, the statistics required for the RPBLRPX model were obtained using the Integrated Multi-satellitE Retrievals for GPM (IMERG; 30-min, 0.1° resolution) product derived from the Global Precipitation Measurement (GPM) mission. Performance of the SIFD framework was tested against gauge data from seven Australian sites across a wide range of climatologies. The disaggregation scheme coupled with the RPBLRPX model was capable of reproducing the wet-period mean intensity, wet-period standard deviation, and wet-period fraction with reasonable accuracy across the sub-daily timescales. The coefficient of determination (r2) values were 0.39 (mean intensity), 0.38 (standard deviation), and 0.87 (wet-period fraction) at 0.5 h timescale. Furthermore, despite some differences in methodology and record length, the IFD estimates computed using the SIFD framework were fairly close to those of the Bureau of Meteorology (BoM). The skill metrics for Sydney were the best with a bias ratio (BR) of 1.01, root mean square error (RMSE) of 13% of the mean of the BoM estimates, and a Nash-Sutcliffe coefficient of efficiency (NSE) of 0.97. The worst case was found at Hobart (BR = 1.43, RMSE = 66%, and NSE = 0.26). Overall, the results indicate that the proposed SIFD framework could provide a viable alternative to estimate unbiased IFD curves at the sub-hourly timescale in the absence of adequate sub-hourly ground-based observations.

Southern Ocean Precipitation Characteristics Observed From CloudSat and Ground Instrumentation During the Macquarie Island Cloud & Radiation Experiment (MICRE): April 2016 to March 2017

AbstractA 1‐year blended surface precipitation data set using Parsivel disdrometer, surface W‐band radar, and tipping bucket measurements is produced for the Macquarie Island Cloud and Radiation Experiment (MICRE) and compared with retrievals from CloudSat (spaceborne 94 GHz radar). Surface precipitation was observed 44% ± 4% of the time between April 2016 and March 2017. Precipitation composed primarily of small particles (diameter <1 mm) occurred about 36% ± 2% of the time, constituting 10% of total accumulation. Remaining precipitation contained enough large particles such that the disdrometer could be used to identify the precipitation type as rain, ice, snow or wet snow. Seasonal and annual statistics on frequency of occurrence and accumulation for each precipitation type observed during MICRE are presented. Most ice and mixed phase precipitation was shallow, originating at a height of 3 km or lower, and occurred most often when Macquarie Island was to the northwest of the nearest cyclonic low‐pressure center. In contrast, rain was more often deep and occurred most frequently when the island was to the southeast of cyclonic lows. A weak diurnal cycle in frequency and mean rate was present with a minimum between 12:00 and 14:00 local time and maximum between 03:00 and 06:00 local time. The CloudSat 2C‐Precip‐Column product missed the lightest precipitation (because the near‐surface reflectivity is <−15 dBZ) and overestimated total liquid precipitation and occurrence of mixed phase precipitation, but captured reasonably well the distribution of rain rates for rates >0.5 mm/hr.

Environmental determinants predicting population vulnerability to high yellow fever incidence.

Yellow fever (YF) is an endemic mosquito-borne disease in Brazil, though many locations have not observed cases in recent decades. Some locations with low disease burden may resemble locations with higher disease burden through environmental and ecohydrological characteristics, which are known to impact YF burden, motivating increased or continued prevention measures such as vaccination, mosquito control or surveillance. This study aimed to use environmental characteristics to estimate vulnerability to observing high YF burden among all Brazilian municipalities. Vulnerability was defined in three categories based on yearly incidence between 2000 and 2017: minimal, low and high vulnerability. A cumulative logit model was fit to these categories using environmental and ecohydrological predictors, selecting those that provided the most accurate model fit. Per cent of days with precipitation, mean temperature, biome, population density, elevation, vegetation and nearby disease occurrence were included in best-fitting models. Model results were applied to estimate vulnerability nationwide. Municipalities with highest probability of observing high vulnerability was found in the North and Central-West (2000–2016) as well as the Southeast (2017) regions. Results of this study serve to identify specific locations to prioritize new or ongoing surveillance and prevention of YF based on underlying ecohydrological conditions.

A novel combined model for prediction of daily precipitation data using instantaneous frequency feature and bidirectional long short time memory networks.

Meteorological events constantly affect human life, especially the occurrence of excessive precipitation in a short time causes important events such as floods. However, in case of insufficient precipitation for a long time, drought occurs. In recent years, significant changes in precipitation regimes have been observed and these changes cause socio-economic and ecological problems. Therefore, it is of great importance to correctly predict and analyze the precipitation data. In this study, a reliable and accurate precipitation forecasting model is proposed. For this aim, three deep neural network models, long short-time memory networks (LSTM), gated recurrent unit (GRU), and bidirectional long short time memory networks (biLSTM), were applied for one ahead forecasting of daily precipitation data and compared the performances of these models. Moreover, to increase the far ahead forecasting performance of the biLSTM model, the instantaneous frequency (IF) feature was applied as the input parameter for the first time in the literature. Therefore, a novel model ensemble of IF and biLSTM was employed for the aim of one-six ahead forecasting of daily precipitation data. The performance of the proposed IF-biLSTM model was evaluated using mean absolute error (MAE), mean square error (MSE), correlation coefficient (R), and determination coefficient (R2) performance parameter and spider charts were used to assess the model performances. According to the numerical results, the biLSTM model outperformed compared with the LSTM and GRU models. After the good score achieved with biLSTM model, IF feature applied to biLSTM and IF-biLSTM model has the best forecasting performance for daily precipitation data with R2 value 0.9983, 0.9827, 0.9092, 0.8508, 0.7827, and 0.7646, respectively, for one-six ahead forecasting of daily precipitation data. It has been observed that the IF-biLSTM model has higher forecasting performance than the biLSTM model, especially in far ahead forecasting studies, and the IF feature improves the estimation performance.

Evaluation of classification and decision trees in predicting daily precipitation occurrences

Abstract Due to the heterogeneous distribution of precipitation, predicting its occurrence is one of the primary and basic strategies to prevent possible disasters and their damages. Hence, this study aims at evaluating the capabilities of Logistic Model Tree (LMT), J48, Random Forest (RF), and PART classification algorithms in precipitation forecasts at Pars Abad station using previous 1–4 days data of meteorological variables. So, five scenarios were considered based on the cross-correlation function and partial autocorrelation function for validation of the studied methods in the period of 2004–2019. In general, by examining the Kappa, root mean squared error (RMSE), mean absolute error (MAE) indicators, scenario number 1 using the input parameters of 1-day lag was determined as the most appropriate scenario to predict daily precipitation. Also, the obtained results showed that the PART had better performance with more than 80% accuracy in precipitation forecasting. Moreover, the most accurate performance of PART was scenario 1 with Kappa = 0.2007, RMSE = 0.3879 and MAE = 0.2856. The conclusive results indicated that by implementing classification algorithms and decision trees and using meteorological data of the previous days, daily precipitation could be predicted accurately.

Impacts of global warming on Meiyu–Baiu extreme rainfall and associated mid-latitude synoptic-scale systems as inferred from 20km AGCM simulations

The impacts of global warming on Meiyu–Baiu extreme rainfall and the associated mid-latitude synoptic-scale weather systems over the Eastern China (EC) and the Baiu rainband (Bu) regions in East Asia have been examined, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model (MRI-AGCM3.2S). This model was demonstrated to give realistic Asian extreme rainfall, when compared with data from the Tropical Rainfall Measuring Mission (TRMM). Here we used a novel wave-selection algorithm based on the 300 hPa wind, in order to identify upper-level propagating wave signals in conjunction with the occurrence of extreme precipitation in either EC or Bu. The same algorithm was applied for both the present (1979–2003) and future (2075–2099) climate simulations from the AGCM, so as to infer the impacts of global warming on the behavior of these systems. Results show robust decrease of intensity of systems influencing both Bu and EC in the future warmer climate. Their corresponding low-to-mid level circulation, as revealed by vertical velocity, temperature advection and sea-level pressure composites, was also found to be weakened. This is likely related to changes in the background circulation in future over the East Asian mid-latitude zone, such as the widespread increment of the seasonal mean static stability at 500 hPa. However, the wave-associated precipitation over these regions was enhanced in the future climate simulations. This can be attributed to more strong intensity rainfall, which increases as the background temperature in these regions warms, largely following the Clausius–Clapeyron relation. Therefore, changes of wave-related extreme precipitation in EC and Bu are mainly controlled by the thermodynamic effect; the latter appears to be much stronger than the potential impacts due to the slight weakening of these weather systems.

Pore Scale Numerical Modelling of Geological Carbon Storage Through Mineral Trapping Using True Pore Geometries

Mineral trapping (MT)is the most secure method of sequestering carbon for geologically significant periods of time. The processes behind MT fundamentally occur at the pore scale, therefore understanding which factors control MT at this scale is crucial. We present a finite elements advection–diffusion–reaction numerical model which uses true pore geometry model domains generated from upmuCT imaging. Using this model, we investigate the impact of pore geometry features such as branching, tortuosity and throat radii on the distribution and occurrence of carbonate precipitation in different pore networks over 2000 year simulated periods. We find evidence that a greater tortuosity, greater degree of branching of a pore network and narrower pore throats are detrimental to MT and contribute to the risk of clogging and reduction of connected porosity. We suggest that a tortuosity of less than 2 is critical in promoting greater precipitation per unit volume and should be considered alongside porosity and permeability when assessing reservoirs for geological carbon storage (GCS). We also show that the dominant influence on precipitated mass is the Damköhler number, or reaction rate, rather than the availability of reactive minerals, suggesting that this should be the focus when engineering effective subsurface carbon storage reservoirs for long term security.Article HighlightsThe rate of reaction has a stronger influence on mineral precipitation than the amount of available reactant.In a fully connected pore network preferential flow pathways still form which results in uneven precipitate distribution.A pore network tortuosity of <2 is recommended to facilitate greater carbon mineralisation.

Perceived Effective Adaptation Strategies against Climate Change Impacts: Perspectives of Maize Growers in the Southern Highlands of Tanzania.

The world has been experiencing a tremendous increase in the average of warmth and shifts in rainfall quantity, seasonality, and occurrence of prolonged droughts, increased temperatures and intense precipitation. This study assessed effective adaptation strategies used by maize growers in cushioning climate change impacts in Iringa district. Both qualitative and quantitative data were collected. Qualitative data were collected through focus group discussions, key informant interviews and participant observations, while quantitative data were collected using household questionnaire. Both qualitative and quantitative data were collected covering a wide range of climate change impacts and response strategies. We found that maize production has decreased during the past two decades, since the year 2000 (i.e., from the average of 10-15 to 2-5 maize sacks per acre). It was affirmed that increased yield outputs and incomes are among the key determinants for the effectiveness of a response strategy. Findings indicate that some response strategies indicated a significant increase in maize crop yield. Such responses include using improved maize variety (P = 0.000 (P < 0.05), drought-tolerant crop (P = 0.014 (P < 0.05), changing planting dates (P = 0.001 (P < 0.05) and crop rotation (P = 0.000 (P < 0.05). Barriers such as access to capital, poor farming technologies, absence of improved maize agencies or shops, poor access to weather information and high prices for farm inputs to adopting effective adaptation strategies were uncovered. Moreover, most adaptation strategies were found to significantly increase crop production to most of the household farmers, thus leading to high mazie production. Thus, maize growers need support to enhance their locally-led adaptation options to climatic impacts.

Daily Atmospheric Circulation Patterns and Their Influence on Dry/Wet Events in Iran

Analyzing atmospheric circulation patterns characterize prevailing weather in a region. The method of principal component analysis and clustering was used to classify daily atmospheric circulation patterns. The average daily geopotential height of 500 hPa with 0.5° resolution of the ECMWF (1990–2019) were extracted from the Middle East. The S array was used to identify air types, and k-means clustering was used to classify daily air types. All days were divided into eighteen groups. Then, the surface maps and moisture flux divergence at the 850-hPa level of each pattern were studied. The, the connection between circulation patterns and precipitation occurrence is investigated by the PI index. The existence of a variety of precipitation and temperature regimes and consequent dry/wet periods is related to the type and frequency of the circulation patterns. In patterns with south to southwesterly currents, the low-pressure surface center extends from the south of the Red Sea to southern Turkey and is associated with the mid-level trough, where the moisture fluxes converge in the south of the Red Sea, southwest/south of Iran, and east of the Mediterranean Sea. Therefore, according to the intensity of the patterns, the most precipitation falls in the country’s western half, and the Zagros Mountain’s wind side. With the eastward movement of the Cyclonic patterns, the rainfall area extends to the eastern half of the country. With the pattern that the thermal low surface pressure extends to 35 °N latitude and is associated with the mid-level subtropical high, almost no rain occurs in the country.

Mitigating avian collisions with power lines through illumination with ultraviolet light

Collisions with anthropogenic structures by long-distance migrants and threatened and endangered species are a growing global conservation concern. Increasing the visibility of these structures may reduce collisions but may only be accepted by local residents if it does not create a visual disturbance. Recent research has shown the potential for ultraviolet (UV) light, which is nearly imperceptible to humans, to mitigate avian collisions with anthropogenic structures. We tested the effectiveness of two UV (390–400 nm) Avian Collision Avoidance Systems (ACASs) at reducing collisions at two 260-m spans of marked power lines at the Iain Nicolson Audubon Center at Rowe Sanctuary, an important migratory bird stopover location in Nebraska. We used a randomized design and a tiered model selection approach employing generalized linear models and the Akaike Information Criterion to assess the effectiveness of ACASs considering environmental (e.g., precipitation) and detection probability (e.g., migration chronology) variables. We found focal (assessed power line) and distal (neighboring power line) ACAS status and environmental variables were important predictors of avian collisions. Our top model suggests that the focal ACAS illumination reduced collisions by 88%, collisions were more likely at moderate (10–16 km/h) compared to lower or higher wind speeds, and collision frequency decreased with precipitation occurrence. Our top model also indicates that the distal ACAS illumination reduced collisions by 39.4% at the focal power line when that ACAS was off, suggesting a positive “neighbor effect” of power line illumination. Although future applications of ACASs would benefit from additional study to check for potential negative effects (for example, collisions involving nocturnal foragers such as bats or caprimulgiform birds drawn to insects), we suggest that illuminating power lines, guy wires, towers, wind turbines, and other anthropogenic structures with UV illumination will likely lower collision risks for birds while increasing human acceptance of mitigation measures in urban areas.

Effect of binary basicity on chromium occurrence in stainless steel slag

Comprehensive utilization of stainless-steel slag (SSS) is restrained due to the risk of Cr6+ leaching. Based on the studying the microstructure of synthetic slag (SS) containing Cr2O3 with XRD, SEM-EDS, and Image pro, the effect of binary basicity on the chromium occurrence in SSS was investigated. The results indicated that the binary basicity had a significant impact on the properties of spinel crystals. There was a positive correlation between the calcium content in spinel crystals and the SS basicity. The size of spinel crystals varied from large to small and the precipitation occurrence changed with the basicity increase. Furthermore, the chromium occurrences changed with the basicity. The chromium was produced in spinel crystals at lower basicity, but as the basicity increased to 3.0, the chromium precipitated as calcium chromate. In view of the relationship between the chromium leaching behavior and its occurrence, increasing basicity raised the Cr6+ leaching.

Stochastic modelling of the daily precipitation occurrence in the Tocantins-Araguaia hydrographic region, Amazon, Brazil

Stochastic modelling of the daily precipitation occurrence in the Tocantins-Araguaia hydrographic region, Amazon, Brazil

A Global Evaluation of IMERG Precipitation Occurrence Using SMAP Detected Soil Moisture Change

Abstract A globally consistent ground validation method for remotely sensed precipitation products is crucial for building confidence in these products. This study develops a new methodology to validate the IMERG precipitation products through the use of SMAP soil moisture changes as a proxy for precipitation occurrence. Using a standard 2 × 2 contingency table method, preliminary results provide confidence in SMAP’s ability to be utilized as a validation tool for IMERG as results are comparable to previous validation studies. However, the method allows for an overestimate of false alarm frequency due to light precipitation events that can evaporate before the subsequent SMAP overpass and changes in overpass-to-overpass SMAP soil moisture that are within the range of SMAP uncertainty. To counter these issues, a 3 × 3 contingency table is used to reduce noise and extract more signal from the detection method. Through the use of this novel approach, the validation method produces a global mean POD of 0.64 and global mean FAR of 0.40, the first global-scale ground validation skill scores for the IMERG products. Advancing the method to validate precipitation quantity and the development of a real-time validation for the IMERG Early product are the crucial next developments. Significance Statement We wanted to see if there was a method in which remotely sensed precipitation observations could be validated at a near-global scale for land areas. Scientific literature is filled with studies that validate various precipitation datasets over local-to-regional scales, with very few extending beyond that domain. This study provides a robust first attempt at validating a global precipitation product at a global scale using changes in remotely sensed soil moisture as an independent proxy for precipitation presence/absence. While the method demonstrates that there is skill in using soil moisture as a tool to validate precipitation at the global scale, we find that there are still instances of a systemic bias for arid climate regimes. This method lays the groundwork for future studies to provide a comprehensive global validation in a globally consistent manner.

Chains of Spatial and Temporal Precipitation Occurrence Predictability Across the Continental U.S.

Both spatial and temporal information sources contribute to the predictability of precipitation occurrence at a given location. These sources, and the level of predictability they provide, are relevant to forecasting and understanding precipitation processes at different time scales. We use information theory-based measures to construct connected “chains of influence” of spatial extents and timescales of precipitation occurrence predictability across the continental U.S, based on gridded daily precipitation data. These regions can also be thought of as “footprints” or regions where precipitation states tend to be most synchronized. We compute these chains of precipitation influence for grid cells in the continental US, and study metrics regarding their lengths, extents, and curvature for different seasons. We find distinct geographic and seasonal patterns, particularly longer chain lengths during the summer that are indicative of larger spatial extents for storms. While synchronous, or instantaneous, relationships are strongest for grid cells in the same region, lagged relationships arise as chains reach areas farther from the original cell. While this study focuses on precipitation occurrence predictability given only information about precipitation, it could be extended to study spatial and temporal properties of other driving factors.

Effects of heat treatment before extrusion on dynamic recrystallization behavior, texture and mechanical properties of as-extruded Mg-Gd-Y-Zn-Zr alloy

The effects of heat treatment before extrusion on the dynamic recrystallization (DRX) behavior, texture, and mechanical properties of the extruded Mg-9.8Gd-3.5Y-2.0Zn-0.4Zr (wt. %) alloy were comparatively investigated in this work. A large number of dendritic microstructures in as-homogenized alloy and intergranular block-shaped LPSO phases in as-aged alloy were found to promote the operation of particle-stimulated nucleation (PSN) and discontinuous dynamic recrystallization (DDRX) mechanisms, which further accelerate growth of dynamic recrystallized grains due to the lack of solute drag and dynamic precipitation. Also, we determined the nucleation of dynamic recrystallization affects little to the formation of abnormal texture, whereas the shear stress results from the flow velocity gradient and the pyramidal-2 slip during the growth of the dynamic recrystallized grains leading the formation of abnormal texture. However, the solution treatment before extrusion could effectively eliminate the dendritic microstructures and increase the solid solubility of the matrix, which would facilitate the occurrence of continuous dynamic recrystallization (CDRX) and dynamic precipitation during the hot extrusion process. Meanwhile, CDRX and dynamic precipitation co-contribute to the formation of a bimodal microstructure that composed of coarse deformed grains with basal orientation and fine dynamic recrystallized grains with random orientation. The observed bimodal microstructure, fine dynamic precipitations, strong fiber texture, and substructure thus well explained the improved strength and elongation of samples extruded with the solution treated materials.