| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- An, Dong, et al.
(författare)
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APPLICATION OF DIFFERENT HYDROLOGIC MODELS IN FLASH FLOODS SIMULATION
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, the flash flood occurs frequently and intensively. It has become a world-wide focus in the field of disaster prevention and mitigation. The flash flood critical rainfall determination method, flash floods forecasting model and experience forecasting method are the most commonly used methods. This study focused on the application of hydrological models for flash floods simulation.The research has adopted 7 flood forecasting models with different types and structures: topography-based API model, Xinanjiang Model, Xinanjiang Model with excess infiltration, Sacramento Model, IHACRES, BP-KNN Model and TOPKAPI. Every model will be applied in semi-humid and semi-arid watersheds Banqiao, Maduwang, Zhidan in China, which have high risk of flash floods. According to the characteristic of flash floods, a set of evaluation for the simulation results isput forward. The purpose is to find out one or several hydrological models fit for research area and to provide reference for future related research.Combining with topography and runoff characteristics of each watershed, the paper collected and compared various simulation results of different models. Results indicated that models performed varies in semi-humid and semi-arid basins because of the complicated runoff mechanism in these areas. Among the conceptual hydrological models, Xinanjiang Model with excess infiltration performed better than the models with single runoff mechanism. TOPKAPI has a better simulation results than the lumped models topography-based API model and IHACRES. However, it has higher data requirements. BP-KNN model contains no physical mechanism and performed best in calibration period, but the accuracy falls greatly in validation period.
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| 3. |
- An, Dong, et al.
(författare)
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Evidence of climate shift for temperature and precipitation extremes across Gansu Province in China
- 2020
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Ingår i: Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 1434-4483 .- 0177-798X. ; 139:3-4, s. 1137-1149
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Tidskriftsartikel (refereegranskat)abstract
- Temperature and precipitation extremes are the dominant causes of natural disasters. In this study, seven indices of extreme temperature and precipitation events in Gansu Province, China, were analysed for the period 1961–2017. An abrupt climate shift was recorded during 1980–1981. Thus, the study period was divided into a preshift (before the climate shift) period 1961–1980 and an aftshift (after the climate shift) period 1981–2017. Comparison of mean extreme indices for preshift and aftshift periods was performed for the purpose of exploring possible increasing/decreasing patterns. Generalized extreme value (GEV) distribution was applied spatially to fit the extreme indices with return periods up to 100 years for preshift/aftshift periods. Singular value decomposition (SVD) was adopted to investigate possible correlation between the extreme climate events and indices of large-scale atmospheric circulation. The results indicate that changes in mean and return levels between the preshift and aftshift periods vary significantly in time and space for different extreme indices. Increase in extreme temperature regarding magnitude and frequency for the aftshift period as compared with the preshift period suggests a change to a warmer and more extreme climate during recent years. Changes in precipitation extremes were different in southern and northern parts of Gansu. The precipitation extremes in the north have increased that can result in more serious floods and droughts in the future. SVD analyses revealed a complex pattern of correlation between climate extremes and indices of large-scale atmospheric circulation. Strengthening of westerlies and weakening of the south summer monsoon contribute to the complex changing patterns of precipitation extremes. Results in this study will contribute to disaster risk prevention and better water management in this area.
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| 4. |
- Du, Yiheng, et al.
(författare)
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Hydrologic response of climate change in the source region of the Yangtze River, based on water balance analysis
- 2017
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Ingår i: Water. - : MDPI AG. - 2073-4441. ; 9:2
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Tidskriftsartikel (refereegranskat)abstract
- Due to the large amount of water resources stored in glaciers, permafrost, and lakes, the source region of the Yangtze River (SRYR) is of great importance for the overall basin water flow. For this purpose, a state of art review and calculations were made for the period 1957-2013 using observed hydrological and meteorological data with a water balance approach. Actual evapotranspiration was calculated and validated by empirical formulas. Water storage change analysis was conducted with uncertainty boundaries using a 10-year moving window. Results show that temperature, precipitation, and actual evapotranspiration in the SRYR increased by 0.34°C, 11.4 mm, and 7.6 mm per decade, respectively (significant at 0.05 probability level). Runoffappears to have increased at a rate of 3.3 mm per decade. The SRYR water storage in total has not changed significantly during the period, although the moving average is mostly below zero. Based on the water balance equation, the increase in calculated evapotranspiration is mainly due to the significantly increasing temperature. This in combination with increasing precipitation leads to a relatively stable water storage during the study period. Correlation analyses show that precipitation dominates runoffduring the warm season (May to October), while temperature anomalies dominate the runoffduring the cold season (November to April). The influence of temperature on runoffseems to enhance during the winter period.
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| 5. |
- du, Yiheng, et al.
(författare)
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Integrated large‐scale circulation impact on rainy season precipitation in the source region of the Yangtze River
- 2020
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Ingår i: International Journal of Climatology. - : Wiley. - 1097-0088 .- 0899-8418. ; 40:4, s. 2285-2295
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Tidskriftsartikel (refereegranskat)abstract
- Monthly precipitation data at regular grids of 0.5° × 0.5° derived from observations during June–August 1961–2016 were used to reveal characteristics of large‐scale circulations associated with rainy season precipitation over the source region of the Yangtze River (SRYR). The integrated impact of major influencing circulation patterns was examined by principal component analysis and composites. Results showed that the first rainy season precipitation mode associates with the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), explaining 64% of spatial and temporal rainy season precipitation variance in the region. Composites of precipitation pattern under different phases of SOI and PDO revealed that the effect of PDO on precipitation varies with the SOI phase. When out of phase with the SOI, PDO‐induced precipitation anomalies are magnified. When they are in phase, anomalies weaken or even disappear. Composites of moisture flux patterns show that large‐scale atmospheric circulation affects the strength of westerlies that transport moisture to the study area and formation of convergence. In coming decades, the PDO is likely to continue in a negative phase with La Niña (positive SOI) events, implying more precipitation during the rainy season. Consequently, this knowledge can be used to improve decision making regarding water supply and flood risk management in the SRYR.
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| 6. |
- du, Yiheng, et al.
(författare)
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Multi-Space Seasonal Precipitation Prediction Model Applied to the Source Region of the Yangtze River, China
- 2019
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Ingår i: Water. - 2073-4441. ; 11:12
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Tidskriftsartikel (refereegranskat)abstract
- This paper developed a multi-space prediction model for seasonal precipitation using a high-resolution grid dataset (0.5° × 0.5°) together with climate indices. The model is based on principal component analyses (PCA) and artificial neural networks (ANN). Trend analyses show that mean annual and seasonal precipitation in the area is increasing depending on spatial location. For this reason, a multi-space model is especially suited for prediction purposes. The PCA-ANN model was examined using a 64-grid mesh over the source region of the Yangtze River (SRYR) and was compared to a traditional multiple regression model with a three-fold cross-validation method. Seasonal precipitation anomalies (1961–2015) were converted using PCA into principal components. Hierarchical lag relationships between principal components and each potential predictor were identified by Spearman rank correlation analyses. The performance was compared to observed precipitation and evaluated using mean absolute error, root mean squared error, and correlation coefficient. The proposed PCA-ANN model provides accurate seasonal precipitation prediction that is better than traditional regression techniques. The prediction results displayed good agreement with observations for all seasons with correlation coefficients in excess of 0.6 for all spatial locations.
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| 7. |
- Du, Yiheng
(författare)
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Present and future precipitation variations in the source region of the Yangtze River, China
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The source region of the Yangtze River (SRYR), the origin of the longest river in China, is an area with high-mountains and river ecotones that face considerable challenges under climate change. Precipitation is fundamental for sustainable ecosystems in this area and for the downstream water supplies. Thus, this study investigated the present and future patterns of precipitation variation in the SRYR. To investigate historical climate characteristics of the SRYR, analysis of hydro-climatic components during 1957-2013 was performed. Temperature in the SRYR increased at a rate of 0.34°C/decade, precipitation and evaporation increased by 11.4 and 7.6 mm/decade, respectively. Runoff depth increased by 3.3 mm/decade. Considering the water balance, annual water storage was constant despite a continuous small negative trend. Increase in precipitation is mainly caused by increasing evapotranspiration, leading to the relatively stable water storage during the study period, which also suggests an accelerating water cycle in the SRYR. This knowledge is essential for the understanding of water resources conditions in the area. Rainy season precipitation (June-August) in the SRYR accounts for approximately 70% of the annual total, and its anomalies are essential for ecosystem resilience. Hence, analysis of rainy season precipitation variability in relation to sea surface temperature (SST) anomalies as well as large-scale circulations including El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) was conducted. Results indicate that the leading modes of rainy season precipitation variability can be explained by the variability of SST together with an integrated effect of ENSO and PDO. The influence of ENSO and PDO will enhance/decrease when they are in-/out-of-phase, respectively. Negative PDO induces more precipitation in La Niña years than in El Niño years for the SRYR, especially over central and eastern parts of the basin. Positive PDO induces precipitation decrease, and El Niño enhances the decrease. The mechanism behind this pattern is atmospheric circulation affecting the strength of westerlies that transport moisture to the inland areas and as well local convergence conditions. Results have implications for predicting the rainy season precipitation for coming decades over the study area. If the current negative PDO phase continues together with more frequent extreme La Niña events, as suggested in other research, more precipitation during rainy season is expected over the SRYR. To further quantify precipitation variability, a multi-space model for seasonal precipitation prediction was developed using principal component analysis (PCA) and artificial neural network (ANN). Correlation analysis shows that the most important climate indices for precipitation in the SRYR vary depending on the season and spatial location. The North Atlantic Oscillation (NAO), Polar/Eurasia Pattern (POL), Southern Oscillation Index (SOI), and Scandinavia Pattern (SCA) events have influence on precipitation in the SRYR during the cold season, while NAO, PDO, and SOI are more important for the warm season. A spatiotemporal model for predicting grid precipitation using significant correlated indices was established for each season, the PCA-ANN model. Results show that the PCA-ANN model can predict precipitation in the study area. By reconstructing principal components, the model provides a simulated dataset with the same size as the original dataset. The PCA-ANN model performs well in terms of both temporal variability and spatial distribution following the rank summer> winter> spring> autumn. A small basin with many variables/grids is recommended for the PCA-ANN model. To access future precipitation pattern, historical performance, and future projections of monthly precipitation in the SRYR were investigated, using the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset. Performance of the 21 models were compared against in situ observations for the historical period 1961–2005, therefore rankings were listed according to their performance. Projected future changes in precipitation were assessed under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios, for near-future (2041-2060) and far-future (2081–2100) time slices with respect to 1986–2005. The results show that models derived from NEX-GDDP data effectively produce observed precipitation magnitude in the study area and optimum models were selected based on comprehensive ranking index. The future climate projections indicate a consistent rise in mean precipitation, especially in summer. The average annual precipitation during the near-future and the far-future showed an increase of 18.6% and 24.4% under RCP 4.5, and a larger increase under RCP 8.5 of 22.5% and 49.7%. The summer precipitation shows similar increase as the annual precipitation but with a slightly larger amplitude. The findings in this thesis provide insights to improve the understanding of water resources variations under the background of climate change, and to establish sustainable management of water resources. The precipitation variability in relation to large-scale circulation can help to improve weather forecasting at a low-cost level. Besides, identification of physical mechanisms of integrated impacts from two major circulation patterns can improve the understanding of drivers behind precipitation variability. Future projections provide guidance for future adaptive solutions, including both spatial and temporal changes. With such information, adaptive plans for the study area can be set up with higher accuracy, lower budget, and localized suitability.
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| 8. |
- Du, Yiheng, et al.
(författare)
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SPATIAL VARIATION OF PRECIPITATION IN THE HUANG-HUAI-HAI RIVER BASIN UNDER CLIMATE CHANGE
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The Huang-Huai-Hai River Basin covers the major political and socioeconomic centers of China. Thus, flood protection and economic development by sustainable water supply are important. Due to this, it is imperative to study distribution and variation of precipitation characteristics under climate change. As hydrological observations are limited, scholars have done more research on daily, monthly, and annual data but less research on hourly data. Meanwhile, short-term extreme precipitation is the main cause of urban flooding and related rural disasters and analysis of these patterns can reflect trend changes of extreme hydrological events. This paper uses daily and hourly data from six rainfall stations in the Huang-Huai-Hai Basin representing the precipitation characteristics over the basin. A variety of statistical methods is used to analyze the observations. Intensity-duration curves are used for extreme value characteristics. The results show that the annual precipitation amount is increasing in the northern area of the Huang-Huai-Hai Basin. Similarly, the southern areas display a decreasing trend. The annual effective rainfall intensity shows an overall increasing trend. Analyzing the extreme values of precipitation in the basin shows that short-term rainfall intensity displays both increasing and decreasing trends depending on the latitude. Thus, there is no general trend but instead changes in rainfall climate that is spatially dependent. This may be connected to spatial changes in the occurring East-Asian monsoon that is influencing the general rainfall climate in the area.
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| 9. |
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| 10. |
- Olsson, Jonas, et al.
(författare)
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An Analysis of (Sub-)Hourly Rainfall in Convection-Permitting Climate Simulations Over Southern Sweden From a User’s Perspective
- 2021
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Ingår i: Frontiers in Earth Science. - : Frontiers Media SA. - 2296-6463. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- To date, the assessment of hydrological climate change impacts, not least on pluvial flooding, has been severely limited by i) the insufficient spatial resolution of regional climate models (RCMs) as well as ii) the simplified description of key processes, e.g., convective rainfall generation. Therefore, expectations have been high on the recent generation of high-resolution convection-permitting regional climate models (CPRCMs), to reproduce the small-scale features of observed (extreme) rainfall that are driving small-scale hydrological hazards. Are they living up to these expectations? In this study, we zoom in on southern Sweden and investigate to which extent two climate models, a 3-km resolution CPRCM (HCLIM3) and a 12-km non-convection permitting RCM (HCLIM12), are able to reproduce the rainfall climate with focus on short-duration extremes. We use three types of evaluation–intensity-based, time-based and event-based–which have been designed to provide an added value to users of high-intensity rainfall information, as compared with the ways climate models are generally evaluated. In particular, in the event-based evaluation we explore the prospect of bringing climate model evaluation closer to the user by investigating whether the models are able to reproduce a well-known historical high-intensity rainfall event in the city of Malmö 2014. The results very clearly point at a substantially reduced bias in HCLIM3 as compared with HCLIM12, especially for short-duration extremes, as well as an overall better reproduction of the diurnal cycles. Furthermore, the HCLIM3 model proved able to generate events similar to the one in Malmö 2014. The results imply that CPRCMs offer a clear potential for increased confidence in future projections of small-scale hydrological climate change impacts, which is crucial for climate-proofing, e.g., our cities, as well as climate modeling in general.
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