A New Approach for Improving Measurements of Cloud Water Contents from Aircraft

This work addresses the need for improved measurements of condensed water in clouds from research aircraft. First, new spectral line fitting codes are shown to improve retrievals of H216O in evaporated clouds by traditional near-infrared tunable diode laser spectroscopy. These codes are then applied to measurements of cloud water contents (CWC) with the University of Colorado Closed-Path Laser Hygrometer (CLH-2) during a series of flights in 2018 into clouds of varying types over the Southern Ocean. By comparing with observations of CWCs from cloud probes ranging from hot wires to droplet imagers, it is found that measurements of CWC using bulk water are generally accurate, but they can also be adversely affected by inlet artifacts such as icing, especially in the presence of mixed phases of water. Because the same can be true of other methods, there is currently no one instrument that accurately measures CWC under all conditions.Second, using knowledge gained from improvements in optics and electronics for CWC measurements, alongside improved retrievals of H216O abundances using sophisticated line-fitting methods developed for those CWC measurements, it is demonstrated through a series of laboratory studies that traditional hygrometer measurements of multiple isotopologues of water may be possible on research aircraft with distributed feedback lasers operating in the near-infrared (1.4 and 2.6 ). It is proposed to conduct these measurements as the ratio of absorbances of pairs of adjacent absorption lines of two isotopologues (e.g., H216O and H216O&nbsp;to characterize fractionation that can be used to elucidate important issues related to properties of clouds, such as liquid and ice-water contents and precipitation, and the microphysics of cloud particle formation. Through such measurements it should be possible to reduce outstanding uncertainties in cloud processes and the hydrological cycle, such as precipitation efficiency related to the aerosol indirect effect, mixed-phase cloud microphysics, and atmospheric transport and mixing in the vicinity of clouds. In addition, augmenting existing TDLAS instruments with the capability to detect isotopologue pairs will allow for characterization of inlet artifacts, such as condensation on sample lines and icing on inlet surfaces.</p

Robotic Solar Tracking Spectrophotometer for Remote Sensing of Column Radiative Properties

Aerosols in the atmosphere are poorly understood in terms of how they affect weather and drive climate and climate change. To advance this knowledge of aerosols, I constructed a robotic solar tracking spectrophotometer to measure direct solar radiation in a wide spectral range. From this data, I will obtain the cirrus cloud optical depth, column ozone concentration, aerosol optical depth, and aerosol size distribution. Long term collection of this data is used to analyze the effects of aerosols and to quantify local radiative forcing. By using University of Nevada, Reno as a measurement site, I can quantify the role of aerosols in local radiative forcing from the variety of aerosols observed at the surface and aloft. Reno is susceptible to dynamic aerosol transport across the Sierras and is greatly affected by forest fires and dust storms making it a favorable place for aerosol and climate research. Presented is the design of this instrument and measurement comparisons with auxiliary instrumentation for the air above Reno, Nevada, USA

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model

Cloud‐Nucleating Particles Over the Southern Ocean in a Changing Climate

International audienc

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making

The O2/N2 Ratio and CO2 Airborne Southern Ocean Study

The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings

The O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) Study

The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings

Observations of clouds, aerosols, precipitation, and surface radiation over the Southern Ocean: An overview of CAPRICORN, MARCUS, MICRE and SOCRATES

International audienc