The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary‐layer and convective‐cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft for the first project of this scale in India, to accrue almost 100 h of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary‐layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre‐monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4 km convection‐permitting limited‐area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy‐covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid‐level dry intrusion during the monsoon onset.

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.

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The Tropospheric Airborne Fourier Transform Spectrometer measured near surface upwelling and downwelling radiances within the far infrared (FIR) over Greenland during two flights in March 2015. Here we exploit observations from one of these flights to provide in situ estimates of FIR surface emissivity, encompassing the range 80–535 cm−1. The flight campaign and instrumental setup are described as well as the retrieval method, including the quality control performed on the observations. The combination of measurement and atmospheric profile uncertainties means that the retrieved surface emissivity has the smallest estimated error over the range 360–535 cm−1 (18.7–27.8 μm), lying between 0.89 and 1 with an associated error that is of the order ±0.06. Between 80 and 360 cm−1, the increasing opacity of the atmosphere, coupled with the uncertainty in the atmospheric state, means that the associated errors are larger and the emissivity values cannot be said to be distinct from 1. These FIR surface emissivity values are, to the best of our knowledge, the first ever from aircraft‐based measurements. We have compared them to a recently developed theoretical database designed to predict the infrared surface emissivity of frozen surfaces. When considering the FIR alone, we are able to match the retrievals within uncertainties. However, when we include contemporaneous retrievals from the mid‐infrared (MIR), no single theoretical representation is able to capture the FIR and MIR behaviors simultaneously. Our results point toward the need for model improvement and further testing, ideally including in situ characterization of the underlying surface conditions.

We present retrievals of infrared spectral surface emissivities spanning the far infrared and mid-infrared from aircraft observations over Greenland, taken at an altitude of 9.2 km above sea level. We describe the flight campaign, available measurements, and the retrieval method. The principal barriers to reducing uncertainty in the emissivity retrievals are found to be instrumental noise and our ability to simultaneously retrieve the underlying surface temperature. However, our results indicate that using the instrumentation available to us it is possible to retrieve emissivities from altitude with an uncertainty of~0.02 or better across much of the infrared. They confirm that the far-infrared emissivity of snow and ice surfaces can depart substantially from unity, reaching values as low as 0.9 between 400 and 450 cm −1. They also show good consistency with retrievals from the same flight made from near-surface observations giving confidence in the methodology used and the results obtained for this more challenging viewing configuration. To the best of our knowledge, this is the first time that far-infrared surface emissivity has been retrieved from altitude and demonstrates that the methodology has the potential to be extended to planned satellite far-infrared missions.

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