Regional Rain Research Articles

Multi-Index Rain Detection: A New Approach for Regional Rain Area Detection from Remotely Sensed Data

Abstract In this article, a new approach called Multi-Index Rain Detection (MIRD) is suggested for regional rain area detection and was tested for India using Kalpana-1 satellite data. The approach was developed based on the following hypothesis: better results should be obtained for combined indices than an individual index. Different combinations (scenarios) were developed by combining six commonly used rain detection indices using AND and OR logical connectives. For the study region, an optimal rain area detection scenario and optimal threshold values of the indices were found through a statistical multi-decision-making technique called the Technique for Order Preference by Similarity Ideal Solution (TOPSIS). The TOPSIS analysis was carried out based on independent categorical statistics like probability of detection, probability of no detection, and Heidke skill score. It is noteworthy that for the first time in literature, an attempt has been made (through sensitivity analysis) to understand the influence of the proportion of rain/no-rain pixels in the calibration/validation dataset on a few commonly used statistics. Thus, the obtained results have been used to identify the above-mentioned independent categorical statistics. Based on the results obtained and the validation carried out with different independent datasets, scenario 8 (TIRt < 260 K and TIRt − WVt < 19 K, where TIRt and WVt are the brightness temperatures from thermal IR and water vapor, respectively) is found to be an optimal rain detection index. The obtained results also indicate that the texture-based indices [standard deviation and mean of 5 × 5 pixels at time t (mean5)] did not perform well, perhaps because of the coarse resolution of Kalpana-1 data. It is also to be noted that scenario 8 performs much better than the Roca method used in the Indian National Satellite (INSAT) Multispectral Rainfall Algorithm (IMSRA) developed for India.

An Algorithm for Drop-Size Distribution Retrieval From GPM Dual-Frequency Precipitation Radar

The dual-frequency precipitation radar onboard the Global Precipitation Measurement (GPM) core satellite has reflectivity measurements at two independent frequencies, i.e., Ku-band and Ka-band. Dual-frequency retrieval algorithms have been developed traditionally through forward, backward, and recursive approaches. However, these algorithms suffer from a “dual value” problem when they retrieve median volume diameter D <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> from a dual-frequency ratio (DFR) in the rain region. It has been shown in the literature that a linear constraint of the drop-size distribution along the rain profile is a reasonable assumption to avoid the “dual value” problem. In this paper, a hybrid method is proposed to retrieve DSDs by combining the forward method and the linear constraint. The forward method is applied to ice and melting ice regions, whereas the linear constraint is applied to the rain region. The method is evaluated using data-based simulation. Different error sources, including sensitivity of snow density, system bias, and attenuation from nonprecipitating particles, are considered. The hybrid method is compared with the surface reference with weak constraint method and the Hitschfeld-Bordan DFR method and shows reasonable comparisons, particularly for medium-to-heavy precipitation. Retrieval examples for Hurricane Earl are shown using the hybrid method.

Investigation of rain effects on Aquarius Sea Surface Salinity measurements

The Aquarius/SAC-D mission has been providing Sea Surface Salinity (SSS), globally over the ocean, for almost 3 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity retrievals in the presence of rain and has noted the strong correlation between the spatial patterns of reduced SSS and the spatial distribution of rainfall. It was determined that this is the result of a cause and effect relationship, as opposed to SSS measurement errors. Hence, it is important to understand these SSS changes due to seawater dilution by rain and the associated near-surface salinity stratification. This paper addresses the effects of rainfall on the Aquarius (AQ) SSS retrieval using a macro-scale Rain Impact Model (RIM) in the region of high convective rain over the Inter-tropical Convergence Zone. This model, based on the superposition of a one-dimension eddy diffusion (turbulent diffusion) model, relates sea surface salinity to depth, rain accumulation and time since rainfall. For aiding in the identification of instantaneous and prior rainfall accumulations, an AQ Rain Accumulation product was developed. This product, based on the NOAA CMORPH rain data set, provides the rainfall history for 24 h prior to the observation time, which is integrated over each AQ SSS measurement cell. In this paper results of the RIM validation are presented by comparing AQ measured and RIM simulated SSS for several months of 2012. Results show the high cross correlation for these comparisons and also with the corresponding SSS anomalies relative to HYCOM.

Multi-frame de-raining algorithm using a motion-compensated non-local mean filter for rainy video sequences

This paper proposes a rain detection and removal algorithm that is robust against camera motion. The proposed algorithm initially detects possible rain streaks by using spatial properties, such as the luminance and structure of rain streaks. Then, the rain streak candidates are selected based on a Gaussian distribution model. Finally, these detected regions are improved with an advanced temporal property in a block-matching process. After the rain detection step, a non-rain block-matching algorithm for each block is performed between adjacent frames to find blocks similar to the block that has rain pixels. If similar blocks are obtained, the rain region of the block is reconstructed by spatio-temporal non-local mean filtering using similar neighboring regions. Finally, a specific post-processing is performed for visibility enhancement and flickering artifact removal. Experiment results show that the proposed algorithm uses only five temporally adjacent frames for rain removal but outperforms previous methods in terms of subjective visual quality.

Direct evidence for the causal role of the left supplementary motor area in working memory: A preliminary study

Working memory is defined as active short-term memory nvolved in purpose-oriented tasks [1]. It plays an essential role n activities of daily living and social life, such as conversation, eading, and calculation. Previous functional magnetic resonance maging (MRI) studies have reported activation in some brain egionsduringa language-relatedN-back task that evaluatedworkng memory; these regions include the dorsolateral prefrontal ortex, anterior cingulate cortex, Broca’s area, supramarginal gyrus, uperior parietal lobule, and supplementary motor area (SMA) [2]. lthough several studies involving human brain mapping have ndicated that short-term memory could be subserved by several rain regions, including the perisylvian cortex, superior frontal yrus, and fornix, there is no direct evidence that the SMA plays a ole in working memory in the human brain [3–6]. Here, we report hat the left SMA plays a role in verbal working memory and the sefulness of the intraoperative 2-back task for evaluatingworking emory during awake surgery.

Assessing the Applicability of the Tropical Convective–Stratiform Paradigm in the Extratropics Using Radar Divergence Profiles

Abstract Long-term radar observations from a subtropical location in southeastern Texas are used to examine the impact of storm systems with tropical or extratropical characteristics on the large-scale circulation. Climatological vertical profiles of the horizontal wind divergence are analyzed for four distinct storm classifications: cold frontal (CF), warm frontal (WF), deep convective upper-level disturbance (DC-ULD), and nondeep convective upper-level disturbances (NC-ULD). DC-ULD systems are characterized by weakly baroclinic or equivalent barotropic environments that are more tropical in nature, while the remaining classifications are representative of common midlatitude systems with varying degrees of baroclinicity. DC-ULD systems are shown to have the highest levels of nondivergence (LND) and implied diabatic heating maxima near 6 km, whereas the remaining baroclinic storm classifications have LND altitudes that are about 0.5–1 km lower. Analyses of climatological mean divergence profiles are also separated by rain regions that are primarily convective, stratiform, or indeterminate. Convective–stratiform separations reveal similar divergence characteristics to those observed in the tropics in previous studies, with higher altitudes of implied heating in stratiform rain regions, suggesting that the convective–stratiform paradigm outlined in previous studies is applicable in the midlatitudes. Divergence profiles that cannot be classified as primarily convective or stratiform are typically characterized by large regions of stratiform rain with areas of embedded convection of shallow to moderate extent (i.e., echo tops &amp;lt;10 km). These indeterminate profiles illustrate that, despite not being very deep and accounting for a relatively small fraction of a given storm system, convection dominates the vertical divergence profile and implied heating in these cases.

Comparison of precipitation estimates between Version 7 3-hourly TRMM Multi-Satellite Precipitation Analysis (TMPA) near-real-time and research products

Over the years, blended methods that use multi-satellites and multi-sensors have been developed for estimating global precipitation and resulting products are widely used in applications. An example is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-Satellite Precipitation Analysis (TMPA) that consists of two products: near-real-time (3B42RT) and research-grade (3B42). The former provides quick, less accurate estimates suitable for monitoring activities; the latter provides more accurate estimates more suitable for research. Both products have been widely used in research and applications. Nonetheless, to improve near-real-time applications, it is important to understand their difference. In this study, seasonal mean difference (MD), mean absolute difference (MAD), root mean square difference (RMSD), and their inter-annual variations in boreal (June, July and August or JJA) and austral (December, January and February or DJF) summers and in different rain regimes over two surface types are investigated on a large scale (50°N–50°S) from 2000 and 2012. Over land, positive MD values (3B42RT>3B42) dominate, especially in western China, western United States, northwest Asia and over some oceanic regions of light rain in both JJA and DJF. Over ocean, negative MD values (3B42RT<3B42) prevail, except over regions of light rain. In general, relative (to 3B42) MD values increase with rain rate. Variation of the individual differences between the two products is small (large) over regions of heavy (light) rain. There is no significant inter-annual variation in the seasonal mean statistics. The difference between the two products is likely due to the algorithms and further investigations are needed.

Impact of simulated acid rain on soil microbial community function in Masson pine seedlings

Accompanying its rapid economic development and population growth, China is the world's third largest acid rain region, following Europe and North America. The effects of acid rain on forest ecosystem were widely researched, including the growth, the nutrient of the leaf and soil, and so on. However, there are few reports about the effects of acid rain on the soil microbial diversity. This study investigated the effects of acid rain on soil microbial community function under potted Masson pine seedlings (Pinus massoniana Lamb). After 7 months of treatment with simulated acid rain, the low acid load treatment (pH 5.5) stimulated soil microbial activity, and increased soil microbial diversity and richness, while the higher levels of acid application (pH 4.5, pH 3.5) resulted in lower soil microbial activity and had no significant effects on soil microbial diversity and richness. Principal component analysis showed that there was clear discrimination in the metabolic capability of the soil microbial community among the simulated acid rain and control treatments. The results obtained indicated that the higher acid load decreased the soil microbial activity and no effects on soil microbial diversity assessed by Biolog of potted Masson pine seedlings. Simulated acid rain also changed the metabolic capability of the soil microbial community.

Simulation of Environmental Pollution Due to SO2 Dispersion

Other than volcanic activities, sulfur dioxide emission is common in various coal, oil, and gas industries. Sulfur dioxide has a great potential for long-range transport (beyond 500–1,000 km) and can create regional acid rains. Efficient modeling of SO2 dispersion process plays a crucial role in strategic environmental planning. A two-dimensional model is developed in this work to predict the SO2 emission under different meteorological conditions. Finite difference and orthogonal collocation techniques are used to solve the model partial differential equations. The simulation results show proper agreement with the results obtained from a commercial software (ISC-AERMOD) using the Industrial Source Complex Short Term model.

Rainfall estimation by S‐band polarimetric radar in Korea. Part I: preprocessing and preliminary results

ABSTRACTThe empirical relationships used to estimate rainfall amounts from polarimetric radar observations were developed and tested by using long‐period drop size distribution (DSD) data and monitoring of rainfall events prior to operational use in Korea. Rainfall associated with Typhoon Meari in 2011 was selected to assess the performance of these relationships for point and areal rainfall amounts. Data quality was checked in regions of light rain to enable the quantitative use of polarimetric variables. The distributions of the cross‐correlation co‐efficient and standard deviation of the differential phase shift agreed with those established in a previous study, but the absolute average deviation of differential reflectivity (ZDR) was a little distorted. Biases in reflectivity (Z) and differential reflectivity were calculated following established methods and found to be –0.18 and 0.47 dB, respectively. The accuracy of rainfall amounts calculated from R(KDP) and R(KDP, ZDR) was poor. The best estimates of rainfall were obtained using R(Z, ZDR) based on DSDs from Oklahoma (OKC) in the USA and Busan (BSC) for both the point and areal mean cases. Correlation co‐efficients of R(Z, ZDR) using the BSC DSDs were better than those using the OKC DSDs for areal mean rainfall amounts. Rainfall amounts in this particular case in Korea were estimated more accurately using the Brandes drop shape for R(Z, ZDR) than the equilibrium drop shape.

Conservational use of remote sensing techniques for a novel rainwater harvesting in arid environment

Remote sensing applications in water resources management are becoming an essential asset in all different levels of integrated water rational use. Due to remote sensing data availability and different acquisition sensors of satellite images, a wide variability of benchmarks could be conducted under the same theme. Rainwater harvesting is the branch of science where the rainwater is the main target to improve groundwater recharge, stratocumulus clouds are the main source of rain in arid regions. Cloud detection using remote sensing techniques proved to be efficient recently but the general uses of different cloud detection techniques are to precisely omit clouds from satellite images. The use of cloud detection scheme described herein is designed for the MERIS Level1B data; therefore, total set of 60 MERIS images was collected on monthly basis for 5 years started from January 2008. The use of the cloud detection algorithm is to find proper land cover suitable for rainwater harvesting mostly covered with cloud all over the year. Evaluation of land use for rainwater harvesting in terms of groundwater recharge is considered, several factors were taken into consideration and NDWI is one of the most important factors involved. Results pointed out that some regions in southern Saudi Arabia are qualified enough to be considered as potential sites for better rainwater harvesting.

Snow Melting from Solar Radiation to Mitigate the Road Freezing

Road safety from various environmental disasters has gained much attention during construction project. Global warming has changed the weather patterns, such as regional torrential rains, heavy snow, and severe cold, and these irregular weather changes have brought huge amount of physical and human damages. In winter season, road freezing caused by snow or icing condition has increased the traffic accidents: traffic mortality is larger in winter than other seasons. In this paper, snow melting mechanism on road pavement by solar radiation and the effect of shadow and temperature is analyzed. Also, numerical analysis on snow melting is performed to provide the guideline of road design considering the solar radiation in an effort of mitigating the road freezing and reducing the traffic accidents in winter.

Prediction of Convective Morphology in Near-Cloud-Permitting WRF Model Simulations

Abstract The Weather Research and Forecasting (WRF) model’s ability to forecast convective morphological evolution is examined for 37 convective systems. The simulations used Thompson microphysics with 3-km horizontal grid spacing. Ten convective mode classifications were used. An objective score was developed to determine the accuracy of the simulated morphologies considering a normalized duration of each mode simulated and its agreement with observations. Rapid Update Cycle analyses were used to compare larger-scale preinitiation conditions to simulated morphology accuracy, as well as to examine how the WRF model’s skill at predicting these larger-scale conditions influenced its prediction of morphology. Two case studies selected as representative of the most common simulated morphology deficiencies were examined in detail. The model simulated cellular systems relatively well but struggled more with linear systems, particularly bow echoes and squall lines having trailing stratiform rain regions. Morphological evolution was generally better simulated in environments with enhanced deep-layer shear and cooler potential temperatures at the level of maximum θe. Weaker deep-layer shear, cooler potential temperatures at the surface, and quickly warming potential temperatures with height increased the likelihood of timing errors. The first case study showed that a warmer cold pool, much larger line-normal shear, and excessive midlevel drying were present in the model run that failed to develop a trailing stratiform region. The second case study showed that weak shear and the absence of a well-developed cold pool may have played a role in the lack of bowing.

Research on Physical-Mechanical Property of Reshaped Loess Contaminated by Acid

With the rapid development of process of industrialization in Inner Mongolia, the environmental pollution, such as phenomenon of regional acid rain is gradually increasing. The Quaternary loess spread widely in Inner Mongolia. The ecological environment must be affected the intrusion acid rain. Meanwhile the physical-mechanical properties of original loess also are significantly influenced by the acid rain. To investigate the influence of acid rain on the physical-mechanical properties of loess, a series of triaxial tests in laboratory are carried out. The results showed that changes of PH value has significant effect on the specific gravity of soil grain, the limit moisture content , maximum dry density, and strength characteristics of loess.

Analysis of Fade Dynamic at Ku-Band in Malaysia

This work investigates fade dynamics of satellite communication systems in equatorial heavy rain region based on a one year of Ku-band propagation measurement campaign carried out in Universiti Teknologi Malaysia (UTM), Johor, Malaysia. First order statistics of rain attenuation are deduced and the results are found to be in good agreement with those obtained from other beacon measurements gathered within the same area (Kuala Lumpur). Moreover, the fade duration and slope statistics of the satellite signal variations are also carefully derived and subsequently compared with the ITU-R recommendation model. Such information is useful for the system operator and radio communication engineer for the design of appropriate fade mitigation techniques as well as the quality of service that could be offered to the user (according to the time interval for a typical day). Further evaluation on the performances of several ITU-R models in the heavy rain region are needed based on the measurement database available of this climatic region.

Combining Satellite Infrared and Lightning Information to Estimate Warm‐Season Convective and Stratiform Rainfall

AbstractThis paper describes and evaluates a satellite rainfall estimation technique that combines infrared and lightning information to estimate precipitation in deep convective systems. The algorithm is developed and tested using seven years (2002–08) of TRMM measurements over the southern United States during the warm season. Lightning information is coupled with a modified IR-based convective–stratiform technique (CST) and produces a lightning-enhanced CST (CSTL). Both the CST and CSTL are then applied to the training (2002–04) and independent (2005–08) datasets. In general, this study shows significant improvement over the IR rainfall estimates (rain area, intensity, and volume) by adding lightning information. The CST and CSTL display critical skill in estimating warm‐season precipitation and the performance is very stable. The CST can generally identify the heavy (convective) and light rain regions, while CSTL further identifies convective areas that are missed by CST and removes convective cores that are incorrectly defined by CST. Specifically, the CSTL improves the convective cell detection by 5% and reduces the convective false alarm rate by more than 30%. Similarly, CSTL substantially improves the CST in the overall estimate of instantaneous rainfall rates. For example, when compared with passive microwave estimates, CSTL increases the correlation coefficient by 30%, reduces the bias by 50%, and reduces RMSE by 25%. Both CST and CSTL reproduce the rain area and volume fairly accurately over a region, although both techniques show some degree of overestimation relative to radar estimates.

Diurnal Circulations and Rainfall in Taiwan during SoWMEX/TiMREX (2008)

Abstract The diurnal cycle of the local circulation, rainfall, and heat and moisture budgets is investigated in Taiwan's heavy rain (mei-yu) season using data from the 2008 Southwest Monsoon Experiment/Terrain-influenced Monsoon Rainfall Experiment (SoWMEX/TiMREX). Comparisons are made between an undisturbed (UNDIST; 22–29 May) and disturbed period (DIST; 31 May–4 June). Many aspects of the diurnal evolution in surface flows and rainfall were similar during both periods. At night and during early morning hours, the low-level southwesterly flow was deflected around Taiwan's main topographic barrier, the Central Mountain Range (CMR), with rainfall focused near areas of enhanced offshore confluence created by downslope and land-breeze flows. During the day, the flow switched to onshore and upslope, rainfall shifted inland, and deep convection developed along the coastal plains and windward slopes. Atmospheric budget analysis indicates a day-to-evening transition of convective structure from shallow to deep to stratiform. Evaporation associated with the evening/nighttime stratiform precipitation likely assisted the nocturnal katabatic flow. Though the flow impinging on Taiwan was blocked during both periods, a very moist troposphere and strengthened low-level oncoming flow during DIST resulted in more widespread and intense rainfall that was shifted to higher elevations, which resembled a more weakly blocked regime. Correspondingly, storm cores were tilted upslope during DIST, in contrast to the more erect storms characteristic of UNDIST. There were much more lofted precipitation-sized ice hydrometeors within storms during DIST, the upslope advection of which led to extensive stratiform rain regions overlying the CMR peaks, and the observed upslope shift in rainfall.

Impact of Misrepresentation of Freezing-Level Height by the TRMM Algorithm on Shallow Rain Statistics over India and Adjoining Oceans

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes &gt; 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.

Precipitation Classification and Quantification Using X-Band Dual-Polarization Weather Radar: Application in the Hydrometeorology Testbed

Abstract This paper presents new methods for rainfall estimation from X-band dual-polarization radar observations along with advanced techniques for quality control, hydrometeor classification, and estimation of specific differential phase. Data collected from the Hydrometeorology Testbed (HMT) in orographic terrain of California are used to demonstrate the methodology. The quality control and hydrometeor classification are specifically developed for X-band applications, which use a “fuzzy logic” technique constructed from the magnitude of the copolar correlation coefficient and the texture of differential propagation phase. In addition, an improved specific differential phase retrieval and rainfall estimation method are also applied. The specific differential phase estimation is done for both the melting region and rain region, where it uses a conventional filtering method for the melting region and a self-consistency-based method that distributes the total differential phase consistent with the reflectivity factor for the rain region. Based on the specific differential phase, rainfall estimations were computed using data obtained from the NOAA polarimetric X-band radar for hydrometeorology (HYDROX) and evaluated using HMT rain gauge observations. The results show that the methodology works well at capturing the high-frequency rainfall variations for the events analyzed herein and can be useful for mountainous terrain applications.

Evaluation of Cold-Season Precipitation Forecasts Generated by the Hourly Updating High-Resolution Rapid Refresh Model

Abstract The hourly updating High-Resolution Rapid Refresh (HRRR) model is evaluated with regard to its ability to predict the areal extent of cold-season precipitation and accurately depict the timing and location of regions of snow, rain, and mixed-phase precipitation on the ground. Validation of the HRRR forecasts is performed using observations collected by the Automated Surface Observing System (ASOS) stations across the eastern two-thirds of the United States during the 2010–11 cold season. The results show that the HRRR is able to reliably forecast precipitation extent during the cold season. In particular, the location and areal extent of both snow and rain are very well predicted. Depiction of rain-to-snow transitions and freezing rain is reasonably good; however, the associated evaluation scores are significantly lower than for either snow or rain. The analyses suggest the skill in accurately depicting precipitation extent and phase (i.e., rain, snow, and mixed phase) depends on the size and organization of a weather system. Typically, larger synoptically forced weather systems are better predicted than smaller weather systems, including the associated rain-to-snow transition or freezing-rain areas. Offsets in space or time (i.e., causing misses and false alarms) have a larger effect on the model performance for smaller weather systems.