Search for: All records

Abstract The THINICE field campaign, based from Svalbard in August 2022, provided unique observations of summertime Arctic cyclones, their coupling with cloud cover, and interactions with tropopause polar vortices and sea ice conditions. THINICE was motivated by the need to advance our understanding of these processes and to improve coupled models used to forecast weather and sea ice, as well as long-term projections of climate change in the Arctic. Two research aircraft were deployed with complementary instrumentation. The Safire ATR42 aircraft, equipped with the RALI (RAdar-LIdar) remote sensing instrumentation and in-situ cloud microphysics probes, flew in the mid-troposphere to observe the wind and multi-phase cloud structure of Arctic cyclones. The British Antarctic Survey MASIN aircraft flew at low levels measuring sea-ice properties, including surface brightness temperature, albedo and roughness, and the turbulent fluxes that mediate exchange of heat and momentum between the atmosphere and the surface. Long duration instrumented balloons, operated by WindBorne Systems, sampled meteorological conditions within both cyclones and tropospheric polar vortices across the Arctic. Several novel findings are highlighted. Intense, shallow low-level jets along warm fronts were observed within three Arctic cyclones using the Doppler radar and turbulence probes. A detailed depiction of the interweaving layers of ice crystals and supercooled liquid water in mixed-phase clouds is revealed through the synergistic combination of the Doppler radar, the lidar and in-situ microphysical probes. Measurements of near-surface turbulent fluxes combined with remote sensing measurements of sea ice properties are being used to characterize atmosphere-sea ice interactions in the marginal ice zone. 

Abstract Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and High-Resolution Rapid Refresh (HRRR) 2-m temperature, 10-m wind speed, and precipitation accumulation forecasts initialized at 1200 UTC are verified against New York State Mesonet (NYSM) observations from 1 January 2018 through 31 December 2021. NYSM observations at 126 site locations are used to calculate standard error statistics (e.g., forecast error, root-mean-square error) for temperature and wind speed and contingency table statistics for precipitation across forecast hours, meteorological seasons, and regions. The majority of the focus is placed on the first 18 forecast hours to allow for comparison among all three models. A daily NYSM station-mean temperature error analysis identified a slight cold bias at temperatures below 25°C in the GFS, a cool-to-warm bias as forecast temperatures warm in the HRRR, and a warm bias at temperatures above 30°C in each model. Differences arise when considering temperature biases with respect to lead times and seasons. Wind speeds are overforecast at all ranges in each season, and forecast wind speeds ≥ 18 m s⁻¹are rarely observed. Performance diagrams indicate overall good forecast performance at precipitation thresholds of 0.1–1.5 mm, but with a high frequency bias in the GFS and NAM. This paper provides an overview of deterministic forecast performance across New York State, with the aim of sharing common biases associated with temperature, wind speed, and precipitation with operational forecasters and is the first step in developing a real-time model forecast uncertainty prediction tool. 

Abstract This study examines climatological potential vorticity streamer (PVS) activity associated with Rossby wave breaking (RWB), which can impact TC activity in the subtropical North Atlantic (NATL) basin via moisture and wind anomalies. PVSs are identified along the 2-PVU (1 PVU = 10 −6 K kg −1 m 2 s −1 ) contour on the 350-K isentropic surface, using a unique identification technique that combines previous methods. In total, 21 149 individual PVS instances are identified from the ERA-Interim (ERAI) climatology during June–November over 1979–2015 with a peak in July–August. The total number of PVSs identified in this study is more than previous PVS climatologies for this region, since the new technique identifies a wider range of cases. Variations in PVS size and intensity prompt the development of a new PVS activity index (PVSI), which provides an integrated measure of PVS activity that can improve comparisons with TC activity. For instance, PVSI has a stronger negative correlation with seasonal TC activity ( r = −0.55) relative to PVS frequency, size, or intensity alone. PVSI in June–July is also positively correlated with PVSI in August–November ( r = 0.67), suggesting predictive capability. Compared to the ERAI and Japan Meteorological Agency 55-Year Reanalysis (JRA-55) climatology, there are more PVSs in the Climate Forecast System Reanalysis (CFSR) but these have weaker average intensity overall. While no long-term trend in PVSI is observed in the ERAI or JRA-55 climatologies, a negative trend is observed in CFSR, which could be related to differences in near tropopause static stability early in the climatological period (1979–86) between the CFSR and ERAI datasets.