Assessment of numerical weather prediction model re-forecasts of atmospheric rivers along the west coast of North America

2018 Fall.Includes bibliographical references.Atmospheric rivers (ARs) - narrow corridors of high atmospheric water vapor transport - occur globally and are associated with flooding and maintenance of the regional water supply. Therefore, it is important to improve forecasts of AR occurrence and characteristics. Although prior work has examined the skill of numerical weather prediction (NWP) models in forecasting ARs, these studies only cover several years of re-forecasts from a handful of models. Here, we expand this previous work and assess the performance of 10-30 years of wintertime (November-February) AR landfall re-forecasts from nine operational weather models, obtained from the International Subseasonal to Seasonal (S2S) Project Database. Model errors along the West Coast of North America at leads of 1-14 days are examined in terms of AR occurrence, intensity, and landfall location. We demonstrate that re-forecast performance varies across models, lead times, and geographical regions. Occurrence-based skill approaches that of climatology at 14 days, while models are, on average, more skillful at shorter leads in California, Oregon, and Washington compared to British Columbia and Alaska. We also find that the average magnitude of landfall Integrated Water Vapor Transport (IVT) error stays fairly constant across lead times, although over-prediction of IVT is more common at later lead times. We then show that northward landfall location errors are favored in California, Oregon, and Washington, although southward errors occur more often than expected from climatology. We next explore the link between the predictability of ARs at 1-14 days and synoptic-scale weather conditions by examining re-forecasts of 500-hPa geopotential height anomaly patterns conducive to landfalling ARs. Finally, the potential for skillful forecasts of IVT and precipitation at subseasonal to seasonal (S2S) leads is explored using an empirical forecast model based on the Madden-Julian oscillation (MJO) and the quasi-biennial oscillation (QBO). Overall, these results highlight the need for model improvements at 1-14 days, while helping to identify factors that cause model errors as well as sources of additional predictability

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High‐Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

209 - Kyle Matthew Nardi

Includes bibliographical references.Atmospheric rivers (ARs), narrow corridors of high atmospheric water vapor transport, influence large regions of the West Coast of North America, from southern California to British Columbia and Alaska. Regardless of location, areas influenced by landfalling ARs face various threats and disruptions from excessive rainfall and associated runoff. Therefore, improving forecasts of AR occurrence and characteristics is of great importance to those responsible for protecting life and property. When providing the public with outlooks and warnings related to ARs, forecasters must confront the challenge of assessing the output of different numerical weather prediction (NWP) models. Specifically, forecasters must understand how performance varies across different time scales, geographical regions, and individual models. Prior work, such as Wick et al. (2013), has examined the forecast skill of several NWP models at different lead times, yet as models are continuously updated, a fresh perspective on AR forecast performance is desired. This study aims to assess how different weather forecast models perform at varying lead times and for distinct regions of the West Coast of North America. Re-forecasts from several operational NWP models, obtained from the International S2S Project Database, are run out to approximately 60 days. An atmospheric river detection algorithm is applied to the model output in order to quantify how the models handle such features. The study examines atmospheric river re-forecasts for the West Coast of North America as well as three non-overlapping sub-regions along the coast. The first sub-region extends from southern California to the Oregon border. The second sub-region covers the Pacific Northwest from southern Oregon to the northern extent of Vancouver Island. The third and final sub-region consists of the coasts of British Columbia and southeastern Alaska. Together, these regions represent a large fraction of the AR landfall locations for western North America. Model performance is studied through the lens of AR occurrence, intensity, and location. Results indicate variations in re-forecast skill as a function of lead time, geographic region, and model used. A desired near-term outcome of this work is an increased awareness of both the utility and limitations of NWP models in the prediction of atmospheric river events at short, medium, and long-range leads. A desired long-term outcome is the use of these results as a bridge to understanding what gives rise to the differing characters of atmospheric rivers over the northeast Pacific and how models can improve their depictions of such features

Dataset associated with "Skillful all-season S2S prediction of U.S. precipitation using the MJO and QBO"

This repository contains files depicting the model’s skill in each region and season for different combinations of MJO phase, QBO phase, and forecast lead time. The files also show which phase and lead combinations are "skillful forecasts of opportunity", situations in which the model is significantly more skillful than a random forecast. Together, the contents of this repository allow users to better assess the utility of the empirical model in particular regions and seasons of interest. Please refer to the README file for additional details.Although useful at short and medium-ranges, current dynamical models provide little additional skill for precipitation forecasts beyond Week 2 (14 days). However, recent studies have demonstrated that downstream forcing by the Madden-Julian oscillation (MJO) and quasi-biennial oscillation (QBO) influences subseasonal variability, and predictability, of sensible weather across North America. Building on prior studies evaluating the influence of the MJO and QBO on the subseasonal prediction of North American weather, we apply an empirical model that uses the MJO and QBO as predictors to forecast anomalous (i.e., categorical above or below-normal) pentadal precipitation at Weeks 3 through 6 (15-42 days). A novel aspect of our study is the application and evaluation of the model for subseasonal prediction of precipitation across the entire contiguous U.S. and Alaska during all seasons. In almost all regions and seasons, the model provides "skillful forecasts of opportunity" for 20-50% of all forecasts valid Weeks 3 through 6. We also find that this model skill is correlated with historical responses of precipitation, and related synoptic quantities, to the MJO and QBO. Finally, we show that the inclusion of the QBO as a predictor increases the frequency of skillful forecasts of opportunity over most of the contiguous U.S. and Alaska during all seasons. These findings will provide guidance to forecasters regarding the utility of the MJO and QBO for subseasonal precipitation outlooks.Collection of the data in this repository is supported by NOAA Climate Test Bed grant NA18OAR4310296 and NSF Climate and Large-Scale Dynamics grant AGS-1841754