SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies

Abstract A reliable and accurate long-term rainfall dataset is an indispensable resource for climatological studies and crucial for application in water resource management, agriculture, and hydrology. SM2RAIN (Soil Moisture to Rain) derived datasets stand out as a unique and wholly independent global product that estimates rainfall from satellite soil moisture observations. Previous studies have demonstrated the SM2RAIN products’ high potential in estimating rainfall around the world. This manuscript describes the SM2RAIN-Climate rainfall product, which uses the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture v06.1 to provide monthly global rainfall for the 24-year period 1998–2021 at 1-degree spatial resolution. The assessment of the proposed rainfall dataset against different existing state-of-the-art rainfall products exhibits the robust performance of SM2RAIN-Climate in most regions of the world. This performance is indicated by correlation coefficients between SM2RAIN-Climate and state-of-the-art products, consistently exceeding 0.8. Moreover, evaluation results indicate the potential of SM2RAIN-Climate as an independent rainfall product from other satellite rainfall products in capturing the pattern of global rainfall trend

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset

Spatiotemporal precipitation trend analysis provides valuable information for water management decision-making. Satellite-based precipitation products with high spatial and temporal resolution and long records, as opposed to temporally and spatially sparse rain gauge networks, are a suitable alternative to analyze precipitation trends over Iran. This study analyzes the trends in annual, seasonal, and monthly precipitation along with the contribution of each season and month in the annual precipitation over Iran for the 1983–2018 period. For the analyses, the Mann–Kendall test is applied to the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) estimates. The results of annual, seasonal, and monthly precipitation trends indicate that the significant decreases in the monthly precipitation trends in February over the western (March over the western and central-eastern) regions of Iran cause significant effects on winter (spring) and total annual precipitation. Moreover, the increases in the amounts of precipitation during November in the south and south-east regions lead to a remarkable increase in the amount of precipitation during the fall season. The analysis of the contribution of each season and month to annual precipitation in wet and dry years shows that dry years have critical impacts on decreasing monthly precipitation over a particular region. For instance, a remarkable decrease in precipitation amounts is detectable during dry years over the eastern, northeastern, and southwestern regions of Iran during March, April, and December, respectively. The results of this study show that PERSIANN-CDR is a valuable source of information in low-density gauge network areas, capturing spatiotemporal variation of precipitation

Ten years of GLEAM : a review of scientific advances and applications

During the past decades, consistent efforts have been undertaken to model the Earth's hydrological cycle. Multiple mathematical models have been designed to understand, predict, and manage water resources, particularly under the context of climate change. A variable that has traditionally received limited attention by the hydrological community—but that is crucial to understand the links to climate—is terrestrial evaporation. The Global Land Evaporation Amsterdam Model (GLEAM) was developed ten years ago with the goal to derive terrestrial evaporation from satellite imagery. Since then, GLEAM has been used in a variety of applications, including trend analysis, drought and heatwave studies, hydrological model calibration and validation, water budget assessment, and studies of changes in vegetation. To streamline the development of the model and improve its ability and accuracy in capturing the spatiotemporal patterns of evaporation, while tailoring the development to the needs of stakeholders, it is important to review previous studies and highlight the potential strengths and weaknesses of the model. Therefore, in this study, we provide a literature review of the GLEAM model applications and its accuracy. The results of this metanalysis indicate that GLEAM is preferentially used in climate studies, potentially due to its coarse (25 km) spatial resolution being a limiting factor for its use in water management and, particularly, agricultural applications. Validations to date suggest that, while GLEAM provides a relatively accurate evaporation dataset, its performance over short canopies requires further improvement. Two major sources of uncertainty in the GLEAM algorithm have been identified: (1) the modelling of evaporative stress in response to water limitation, (2) the need to consider below canopy evaporation estimates for a more realistic attribution of evaporation to its different sources. These potential drawbacks of the model could be alleviated by combining the current algorithm with a machine learning-based approach for a next generation of the model. Likewise, ongoing activities of running the model at high (100 m–1 km) resolutions open possibilities to utilise the data for water and agricultural management applications

Occupational Exposure to Sharp Tools in Emergency Medical Service Staff; an Epidemiologic Study

Introduction: Sharp tools are among the major risk factors for transmission of blood borne infections. Therefore, the present study was carried out with the aim of determining epidemiologic aspects of occupational exposure and injury with sharp tools in emergency medical service (EMS) of Dezfoul, Iran, in 2014-2015. Methods: This cross-sectional study was carried out on 140 EMS staff who met the inclusion criteria, using census method. The tool used for data gathering was a questionnaire prepared by the researcher including demographic and personal health data, prevalence and cause of injury with sharp tools, knowledge, mental state, reporting exposure, measures taken, and follow-ups. Data were analyzed using statistical tests such as chi square. Results: Overall, 75% of the participants had been exposed to sharp tools at least once in the past year. Most injuries had occurred during venipuncture of the patient (41.09%). 54.2% of all exposures had happened during transfer. In addition, sadly, 63.9% of the exposures of the staff to patients’ infected secretions were not reported. 63% of injuries with sharp objects had occurred in the night shift. There was a correlation between working experience and frequency of exposure (p=0.02, r=0.19). Conclusion: The results of the present study are indicative of the high occupational exposure to sharp tools among staff of the studied EMS, a significant number of which had not been reported

مواجهه شغلی با وسایل تیز و برنده در پرسنل اورژانس پیش بیمارستانی؛ یک مطالعه اپیدمیولوژیک

Introduction: Sharp tools are among the major risk factors for transmission of blood borne infections. Therefore, the present study was carried out with the aim of determining epidemiologic aspects of occupational exposure and injury with sharp tools in emergency medical service (EMS) of Dezfoul, Iran, in 2014-2015. Methods: This cross-sectional study was carried out on 140 EMS staff who met the inclusion criteria, using census method. The tool used for data gathering was a questionnaire prepared by the researcher including demographic and personal health data, prevalence and cause of injury with sharp tools, knowledge, mental state, reporting exposure, measures taken, and follow-ups. Data were analyzed using statistical tests such as chi square. Results: Overall, 75% of the participants had been exposed to sharp tools at least once in the past year. Most injuries had occurred during venipuncture of the patient (41.09%). 54.2% of all exposures had happened during transfer. In addition, sadly, 63.9% of the exposures of the staff to patients’ infected secretions were not reported. 63% of injuries with sharp objects had occurred in the night shift. There was a correlation between working experience and frequency of exposure (p=0.02, r=0.19). Conclusion: The results of the present study are indicative of the high occupational exposure to sharp tools among staff of the studied EMS, a significant number of which had not been reported. مقدمه: وسایل تیز و برنده از عوامل خطر عمده برای انتقال عفونت های منتقله از راه خون می باشد. از این رو این مطالعه با هدف تعیین جنبه های اپیدمیولوژیک مواجهه شغلی با وسایل تیز و برنده در اورژانس پیش بیمارستانی شهر دزفول، ایران در سال 94-1393 انجام شد. روش کار: این پژوهش مقطعی بر روی 140 نفر از پرسنل فوریتهای پزشکی که معیارهای ورود به مطالعه را داشتند، به روش سرشماری انجام شد. ابزار جمع آوري اطلاعات پرسشنامه ای محقق ساخته شامل مشخصات دموگرافیک و سلامت فردي، شیوع و علل مواجهه با وسایل تیز و برنده، میزان آگاهی، شرایط روحی – روانی، گزارش مواجهات، اقدامات و پیگیری ها بود. داده ها با استفاده از آزمونهای آماری از جمله کای اسکوئر تجزیه و تحلیل شد. يافته ها: بطور کلی 75 درصد از شرکت کنندگان در یک سال گذشته حداقل یکبار با وسایل تیز و برنده مواجهه داشتند. بیشترین مواجهه (09/41 درصد) حین رگ گیری از بیمار بود. 2/54 درصد از کل مواجهات در حین انتقال اتفاق افتاده بود. همچنین 3/69 درصد از مواجهه پرسنل با ترشحات آلوده بیمار متاسفانه گزارش نشده بودند. 63 درصد مواجهات با وسایل تیز و برنده در شیفت شب اتفاق افتاده بود. بین سابقه کاری و فراوانی مواجهات همبستگی وجود داشت (19/0=r، 02/0=p). نتيجه گيری: نتايج مطالعه حاضر حاكي از بالا بودن ميزان مواجهات شغلی با وسایل تیز و برنده بین پرسنل فوریتهای پزشکی مورد مطالعه بود که تعداد قابل توجهی از این موارد گزارش نشده بودند