The Cooperative Observer Program (COOP), established over 100 years ago, has become the backbone of temperature and precipitation data that characterize means, trends, and extremes in U.S. climate. However, significant and widespread biases in the way COOP observers measure daily precipitation have been discovered. These include 1) underreporting of light precipitation events (daily totals of less than 0.05 in., or 1.27 mm), and 2) overreporting of daily precipitation amounts evenly divisible by five- and/or ten-hundredths of an inch, that is, 0.10, 0.25, 0.30 in., etc. (2.54, 6.35, 7.62 mm, etc.). Observer biases were found to be highly variable in space and time, which has serious implications for the spatial and temporal trends and variations of commonly used precipitation statistics. In addition, it was found that few COOP stations had sufficiently complete data to allow the calculation of stable precipitation statistics for a stochastic weather simulation model. Out of more than 12,000 COOP stations nationally, only 784 (6%) passed data completeness and observer bias screening tests for the climatological period 1971–2000. Of the 1221 COOP stations selected for the U.S. Historical Climate Network (USHCN), which provides much of the country's official data on climate trends and variability over the past century, only 221 stations (18%) passed these tests. More effective training materials and regular communication with COOP observers could reduce observer bias in the future. However, it is unlikely that observer bias can be eliminated. One solution is to automate the COOP precipitation measurement system, but this is an expensive option, and may increase other biases associated with automated precipitation measurement. Further analyses are needed to better quantify and characterize observer bias, and to develop methods for dealing with its effects.

The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. Three field phases of the Fog Remote Sensing and Modeling (FRAM) project were conducted over the following two regions of Canada: 1) the Center for Atmospheric Research Experiments (CARE), in Toronto, Ontario (FRAM-C), during the winter of 2005/06, and 2) Lunenburg, Nova Scotia (FRAM-L), during June 2006 and June 2007. Fog conditions observed during FRAM-C were continental in nature, while those conditions observed during FRAM-L were of marine origin. The main objectives of the project were to attain 1) a better description of fog environments, 2) the development of microphysical parameterizations for model applications, 3) the development of remote sensing methods for fog nowcasting/forecasting, 4) an understanding of issues related to instrument capabilities and improvement of the analysis, and 5) an integration of model data with observations to predict and detect fog areas and particle phase. During the project phases, various measurements at the surface, including droplet and aerosol spectra, ice crystal number concentration, visibility, 3D turbulent wind components, radiative fluxes, precipitation, liquid water content profiles, and cloud ceiling, were collected together with satellite measurements. These observations will be studied to better forecast/nowcast fog events in association with results obtained from numerical forecast models. It is suggested that improved scientific understanding of fog will lead to better forecasting/nowcasting skills, benefiting the aviation, land transportation, and shipping communities.

The international experiment called the European Aqua Thermodynamic Experiment (EAQUATE) was held in September 2004 in Italy and the United Kingdom to validate Aqua satellite Atmospheric Infrared Sounder (AIRS) radiance measurements and derived products with certain groundbased and airborne systems useful for validating hyperspectral satellite sounding observations. A range of flights over land and marine surfaces were conducted to coincide with overpasses of the AIRS instrument on the Earth Observing System Aqua platform. Direct radiance evaluation of AIRS using National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I) and the Scanning High-Resolution Infrared Sounder has shown excellent agreement. Comparisons of level-2 retrievals of temperature and water vapor from AIRS and NAST-I validated against high-quality lidar and dropsonde data show that the 1-K/l-km and 10%/1-km requirements for temperature and water vapor (respectively) are generally being met. The EAQUATE campaign has proven the need for synergistic measurements from a range of observing systems for satellite calibration/validation and has paved the way for future calibration/validation activities in support of the Infrared Atmospheric Sounding Interferometer on the European Meteorological Operational platform and Cross-Track Infrared Sounder on the U.S. NPOESS Prepatory Project platform.

Abstract

The 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment obtained a diverse set of in situ and remotely sensed measurements before and during a pyrocumulonimbus (pyroCb) event over the Williams Flats fire in Washington State. This unique dataset confirms that pyroCb activity is an efficient vertical smoke transport pathway into the upper troposphere and lower stratosphere (UTLS). The magnitude of smoke plumes observed in the UTLS has increased significantly in recent years, following unprecedented wildfire and pyroCb activity observed worldwide. The FIREX-AQ pyroCb dataset is therefore extremely relevant to a broad community, providing the first measurements of fresh smoke exhaust in the upper troposphere, including from within active pyroCb cloud tops. High-resolution remote sensing reveals that three plume cores linked to localized fire fronts, burning primarily in dense forest fuels, contributed to four total pyroCb “pulses.” Rapid changes in fire geometry and spatial extent dramatically influenced the magnitude, behavior, and duration of pyroCb activity. Cloud probe measurements and weather radar identify the presence of large ice particles within the pyroCb and hydrometers below cloud base, indicating precipitation development. The resulting feedbacks suggest that vertical smoke transport efficiency was reduced slightly when compared with intense pyroCb events reaching the lower stratosphere. Physical and optical aerosol property measurements in pyroCb exhaust are compared with previous assumptions. A large suite of aerosol and gas-phase chemistry measurements sets a foundation for future studies aimed at understanding the composition of smoke plumes lifted by pyroconvection into the UTLS and their role in the climate system.

Abstract

The Diabatic Influences on Mesoscale Structures in Extratropical Storms (DIAMET) project aims to improve forecasts of high-impact weather in extratropical cyclones through field measurements, high-resolution numerical modeling, and improved design of ensemble forecasting and data assimilation systems. This article introduces DIAMET and presents some of the first results. Four field campaigns were conducted by the project, one of which, in late 2011, coincided with an exceptionally stormy period marked by an unusually strong, zonal North Atlantic jet stream and a succession of severe windstorms in northwest Europe. As a result, December 2011 had the highest monthly North Atlantic Oscillation index (2.52) of any December in the last 60 years. Detailed observations of several of these storms were gathered using the U.K.’s BAe 146 research aircraft and extensive ground-based measurements. As an example of the results obtained during the campaign, observations are presented of Extratropical Cyclone Friedhelm on 8 December 2011, when surface winds with gusts exceeding 30 m s^–1 crossed central Scotland, leading to widespread disruption to transportation and electricity supply. Friedhelm deepened 44 hPa in 24 h and developed a pronounced bent-back front wrapping around the storm center. The strongest winds at 850 hPa and the surface occurred in the southern quadrant of the storm, and detailed measurements showed these to be most intense in clear air between bands of showers. High-resolution ensemble forecasts from the Met Office showed similar features, with the strongest winds aligned in linear swaths between the bands, suggesting that there is potential for improved skill in forecasts of damaging winds.

Abstract

The European Union (EU)-funded project Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) investigates the relationship between weather, climate, and air pollution in southern West Africa—an area with rapid population growth, urbanization, and an increase in anthropogenic aerosol emissions. The air over this region contains a unique mixture of natural and anthropogenic gases, liquid droplets, and particles, emitted in an environment in which multilayer clouds frequently form. These exert a large influence on the local weather and climate, mainly owing to their impact on radiation, the surface energy balance, and thus the diurnal cycle of the atmospheric boundary layer.

In June and July 2016, DACCIWA organized a major international field campaign in Ivory Coast, Ghana, Togo, Benin, and Nigeria. Three supersites in Kumasi, Savè, and Ile-Ife conducted permanent measurements and 15 intensive observation periods. Three European aircraft together flew 50 research flights between 27 June and 16 July 2016, for a total of 155 h. DACCIWA scientists launched weather balloons several times a day across the region (772 in total), measured urban emissions, and evaluated health data. The main objective was to build robust statistics of atmospheric composition, dynamics, and low-level cloud properties in various chemical landscapes to investigate their mutual interactions.

This article presents an overview of the DACCIWA field campaign activities as well as some first research highlights. The rich data obtained during the campaign will be made available to the scientific community and help to advance scientific understanding, modeling, and monitoring of the atmosphere over southern West Africa.

Abstract

The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. During three field campaigns conducted in 2015 and 2016, the National Aeronautics and Space Administration (NASA) Global Hawk, instrumented with GPS dropwindsondes and remote sensors, flew 15 missions sampling 6 tropical cyclones and 3 winter storms. Missions were designed using novel techniques to target sampling regions where high model forecast uncertainty and a high sensitivity to additional observations existed. Data from the flights were examined in real time by operational forecasters, assimilated in operational weather forecast models, and applied postmission to a broad suite of data impact studies. Results from the analyses spanning different models and assimilation schemes, though limited in number, consistently demonstrate the potential for a positive forecast impact from the observations, both with and without a gap in satellite coverage. The analyses with the then-operational modeling system demonstrated large forecast improvements near 15% for tropical cyclone track at a 72-h lead time when the observations were added to the otherwise complete observing system. While future decisions regarding use of the Global Hawk platform will include budgetary considerations, and more observations are required to enhance statistical significance, the scientific results support the potential merit of the observations. This article provides an overview of the missions flown, observational approach, and highlights from the completed and ongoing data impact studies.

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

Abstract

The Pan and Parapan American Games (PA15) are the third largest sporting event in the world and were held in Toronto in the summer of 2015 (10–26 July and 7–15 August). This was used as an opportunity to coordinate and showcase existing innovative research and development activities related to weather, air quality (AQ), and health at Environment and Climate Change Canada. New observational technologies included weather stations based on compact sensors that were augmented with black globe thermometers, two Doppler lidars, two wave buoys, a 3D lightning mapping array, two new AQ stations, and low-cost AQ and ultraviolet sensors. These were supplemented by observations from other agencies, four mobile vehicles, two mobile AQ laboratories, and two supersites with enhanced vertical profiling. High-resolution modeling for weather (250 m and 1 km), AQ (2.5 km), lake circulation (2 km), and wave models (250-m, 1-km, and 2.5-km ensembles) were run. The focus of the science, which guided the design of the observation network, was to characterize and investigate the lake breeze, which affects thunderstorm initiation, air pollutant transport, and heat stress. Experimental forecasts and nowcasts were provided by research support desks. Web portals provided access to the experimental products for other government departments, public health authorities, and PA15 decision-makers. The data have been released through the government of Canada’s Open Data Portal and as a World Meteorological Organization’s Global Atmospheric Watch Urban Research Meteorology and Environment dataset.