Abstract. The Energy Exascale Earth System Model (E3SM) Project is an ongoing, state-of-the-science Earth system modeling, simulation, and prediction project developed by the U.S. Department of Energy (DOE). With an emphasis on supporting DOE's energy mission, understanding and quantifying how well the model simulates water cycle processes is of particular importance. Here, we evaluate E3SM version v1.0 for its ability to represent atmospheric rivers (ARs), which play significant roles in water vapor transport and precipitation. The characteristics and precipitation associated with global ARs in E3SM at standard resolution (1° × 1°) are compared to the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2). Global pattern of AR frequencies in E3SM show high degrees of correlation (>= 0.97) with MERRA2 and low mean absolute errors (< 1 %) annually, seasonally, and across different ensemble members. However, some large-scale condition biases exist leading to AR biases - most significant of which are: the double-ITCZ, a stronger and/or equatorward shifted subtropical jet during boreal and austral winter, and enhanced northern hemisphere westerlies during summer. By comparing atmosphere-only and fully coupled simulations, we attribute the sources of the biases to the atmospheric component or to a coupling response. Using relationships revealed in Dong et al. (2021), we provide evidence showing the stronger north Pacific jet in winter and enhanced northern hemisphere westerlies during summer associated with E3SM's double-ITCZ and related weaker AMOC, respectively, are the sources of much of the AR biases found in the coupled simulations.

Abstract. The role of the large scale atmospheric circulation and atmospheric rivers (ARs) in producing extreme flooding and heavy rainfall events in the lower part of Rhine River catchment area is examined in this study. Analysis of the largest 10 floods in the lower Rhine, between 1817–2015, indicate that all these extreme flood peaks have been preceded up to 7 days in advance by intense moisture transport from the tropical North Atlantic basin, in the form of narrow bands, also know as atmospheric rivers. The influence of ARs on the Rhine River flood events is done via the prevailing large-scale atmospheric circulation. Most of the ARs associated with these flood events are embedded in the trailing fronts of the extratropical cyclones. The typical large scale atmospheric circulation leading to heavy rainfall and flooding in the lower Rhine is characterized by a low pressure center south of Greenland which migrates towards Europe and a stable high pressure center over the northern part of Africa and southern part of Europe. The days preceding the flood peaks, lower (upper) level convergence (divergence) is observed over the analyzed region, which is an indication of strong vertical motions and heavy rainfall. The results presented in this study offer new insights regarding the importance of tropical moisture transport as driver of extreme flooding in the lower part of Rhine River catchment area and we show for the first time that ARs are an useful tool for the identification of potential damaging floods inland Europe.

Atmospheric rivers (ARs) are narrow regions of strong horizontal water vapor transport that play important roles in the global water cycle, weather, and hydrology. Motivated by challenges in simulating ARs with state-of-the-art global models, this paper diagnoses model errors with a focus on relative contributions of moisture convergence, evaporation, and precipitation to AR column–integrated water vapor (IWV) budget. Using 20-year simulations by 24 global weather/climate models, budget terms are calculated for four AR sectors: postfrontal, frontal, prefrontal, and pre-AR, with biases assessed against two reanalysis products. The results indicate that each sector is unique in terms of the dominant water vapor balance, and that the terms exhibiting the largest intermodel spread are the same terms dominating the water vapor balance in each sector. Overall, simulated bulk AR characteristics (e.g., geometry, frequency, and intensity) are more sensitive to biases in IVT convergence and IWV tendency than to biases in evaporation and precipitation, although evaporation/precipitation biases do affect key AR bulk characteristics in selected sectors. The large intermodel spread (particularly for precipitation) and, in certain cases, discrepancies between the reanalysis references themselves (particularly for precipitation types) highlight the need for observational efforts that target better constraining AR processes in weather/climate models and reanalyses.

The role of large-scale atmospheric circulation and atmospheric rivers (ARs) in producing extreme flooding and heavy rainfall events in the lower part of the Rhine catchment area is examined in this study. Analysis of the largest 10 floods in the lower Rhine, between 1817 and 2015, shows that all these extreme flood peaks have been preceded up to 7 d in advance by intense moisture transport from the tropical North Atlantic basin in the form of narrow bands also known as atmospheric rivers. Most of the ARs associated with these flood events are embedded in the trailing fronts of the extratropical cyclones. The typical large-scale atmospheric circulation leading to heavy rainfall and flooding in the lower Rhine is characterized by a low pressure center south of Greenland, which migrates toward Europe, and a stable high pressure center over the northern part of Africa and the southern part of Europe and projects on the positive phase of the North Atlantic Oscillation. On the days preceding the flood peaks, lower (upper) level convergence (divergence) is observed over the analyzed region, which indicates strong vertical motions and heavy rainfall. Vertically integrated water vapor transport (IVT) exceeds 600 kg m−1 s−1 for the largest floods, marking these as very strong ARs. The results presented in this study offer new insights regarding the importance of moisture transport as a driver of extreme flooding in the lower part of the Rhine catchment area, and we show, for the first time, that ARs are a useful tool for the identification of potentially damaging floods in inland Europe.

For the better and stronger information retrieval function, the sequence of search result queue and the correlation of query expression are the key problems that could be computed by similarity algorithm. A new method which is ontology-based weighted semantic tree similarity algorithm (OWSTS) is presented here. In this paper, the construction method of OWSTS and the implementation of similarity algorithm are introduced firstly. And an ontology-based information retrieval prototype system of mechanical products domain is developed secondly. Finally the relative accuracy of retrieval results by OWSTS and generally used cosine vector space based similarity algorithm (TF*IDF) are compared. The successful running of this system shows that OWSTS algorithm is feasible for information retrieval and the similarity algorithm makes the sequence of search result queue fit for userspsila semantic requirement.

With the internet technology developing and web information exploding, users urgently need a stronger web information retrieval function. For the better and stronger function, the sequence of search result queue and the correlation of query expression are the key problems that could be computed by similarity algorithm. Now we recommend a new method which is ontology-based weighted semantic tree similarity algorithm (OWSTS). In this paper, we introduce the construction method of OWSTS and the implementation of similarity algorithm. Then we use a deep groove ball bearing as an example to show how to implement intelligent retrieval system for machinery production. Finally the relative accuracy of retrieval results by OWSTS and generally used cosine vector space based similarity algorithm (TF*IDF) are compared. Experiment result shows that OWSTS algorithm is feasible for information retrieval and the similarity algorithm makes the sequence of search result queue fit for users semantic requirement.

The SARS (severe acute respiratory syndrome) epidemic of 2003 caused almost 800 deaths, many of them due to acute respiratory distress syndrome (ARDS) as a complication. There are no effective drugs available for treating ARDS, but new work in mice suggests that ACE2 (angiotensin-converting enzyme 2) might be an option. ACE2 can protect mice from lung injury in an ARDS-like syndrome, whereas other components of the renin–angiotensin system for controlling blood pressure and salt balance actually make the condition worse. ACE2 is expressed in the healthy lung but downregulated by lung injury and it was shown recently (Nature 426, 450–454; 2003) to be a receptor for the SARS coronavirus. Acute respiratory distress syndrome (ARDS), the most severe form of acute lung injury, is a devastating clinical syndrome with a high mortality rate (30–60%) (refs 1–3). Predisposing factors for ARDS are diverse1,3 and include sepsis, aspiration, pneumonias and infections with the severe acute respiratory syndrome (SARS) coronavirus4,5. At present, there are no effective drugs for improving the clinical outcome of ARDS1,2,3. Angiotensin-converting enzyme (ACE) and ACE2 are homologues with different key functions in the renin–angiotensin system6,7,8. ACE cleaves angiotensin I to generate angiotensin II, whereas ACE2 inactivates angiotensin II and is a negative regulator of the system. ACE2 has also recently been identified as a potential SARS virus receptor and is expressed in lungs9,10. Here we report that ACE2 and the angiotensin II type 2 receptor (AT2) protect mice from severe acute lung injury induced by acid aspiration or sepsis. However, other components of the renin–angiotensin system, including ACE, angiotensin II and the angiotensin II type 1a receptor (AT1a), promote disease pathogenesis, induce lung oedemas and impair lung function. We show that mice deficient for Ace show markedly improved disease, and also that recombinant ACE2 can protect mice from severe acute lung injury. Our data identify a critical function for ACE2 in acute lung injury, pointing to a possible therapy for a syndrome affecting millions of people worldwide every year.

During several months of 2003, a newly identified illness termed severe acute respiratory syndrome (SARS) spread rapidly through the world1,2,3. A new coronavirus (SARS-CoV) was identified as the SARS pathogen4,5,6,7, which triggered severe pneumonia and acute, often lethal, lung failure8. Moreover, among infected individuals influenza such as the Spanish flu9,10 and the emergence of new respiratory disease viruses11,12 have caused high lethality resulting from acute lung failure13. In cell lines, angiotensin-converting enzyme 2 (ACE2) has been identified as a potential SARS-CoV receptor14. The high lethality of SARS-CoV infections, its enormous economic and social impact, fears of renewed outbreaks as well as the potential misuse of such viruses as biologic weapons make it paramount to understand the pathogenesis of SARS-CoV. Here we provide the first genetic proof that ACE2 is a crucial SARS-CoV receptor in vivo. SARS-CoV infections and the Spike protein of the SARS-CoV reduce ACE2 expression. Notably, injection of SARS-CoV Spike into mice worsens acute lung failure in vivo that can be attenuated by blocking the renin-angiotensin pathway. These results provide a molecular explanation why SARS-CoV infections cause severe and often lethal lung failure and suggest a rational therapy for SARS and possibly other respiratory disease viruses.