Improving satellite-retrieved surface radiative fluxes in polar regions using a smart sampling approach

Abstract

Abstract. The surface energy budget (SEB) of polar regions is key to understanding the polar amplification of global climate change and its worldwide consequences. However, despite a growing network of ground-based automatic weather stations that measure the radiative components of the SEB, extensive areas remain where no ground-based observations are available. Satellite remote sensing has emerged as a potential solution to retrieve components of the SEB over remote areas, with radar and lidar aboard the CloudSat and CALIPSO satellites among the first to enable estimates of surface radiative long-wave (LW) and short-wave (SW) fluxes based on active cloud observations. However, due to the small swath footprints, combined with a return cycle of 16 days, questions arise as to how CloudSat and CALIPSO observations should be optimally sampled in order to retrieve representative fluxes for a given location. Here we present a smart sampling approach to retrieve downwelling surface radiative fluxes from CloudSat and CALIPSO observations for any given land-based point-of-interest (POI) in polar regions. The method comprises a spatial correction that allows the distance between the satellite footprint and the POI to be increased in order to raise the satellite sampling frequency. Sampling frequency is enhanced on average from only two unique satellite overpasses each month for limited-distance sampling < 10 km from the POI, to 35 satellite overpasses for the smart sampling approach. This reduces the root-meansquare errors on monthly mean flux estimates compared to ground-based measurements from 23 to 10 W m −2 (LW) and from 43 to 14 W m −2 (SW). The added value of the smart sampling approach is shown to be largest on finer temporal resolutions, where limited-distance sampling suffers from severely limited sampling frequencies. Finally, the methodology is illustrated for Pine Island Glacier (Antarctica) and the Greenland northern interior. Although few ground-based observations are available for these remote areas, important climatic changes have been recently reported. Using the smart sampling approach, 5-day moving average time series of downwelling LW and SW fluxes are demonstrated. We conclude that the smart sampling approach may help to reduce the observational gaps that remain in polar regions to further refine the quantification of the polar SEB.

Polar clouds and radiation in satellite observations, reanalyses, and climate models

“…For downwelling fluxes, a comparison to ground stations suggests that both satellite remote sensing data sets exhibit significant uncertainties. The spatial gridding of satellite tracks enhances errors in coastal regions, where most stations are located [Van Tricht et al, 2016b]. Moreover, the crude representation of surface albedo in the satellite product algorithms, in combination with fixed overpass times, leads to significant uncertainties in downwelling shortwave radiation retrievals, especially over the ice sheets and over sea ice.…”

“…The highest biases are found in ERA-Interim over the Arctic Ocean, with a SW d deficit exceeding −40 W m −2 . However, we should be cautious in interpreting this signal, since C-C tends to overestimate SW d in coastal areas ( Figure S4), a bias that is probably enhanced over the Arctic Ocean where surface albedos are poorly constrained [Van Tricht et al, 2016b].…”

Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars

“…Four analyses will be described in this paper. As a first step, a statistical analysis is executed in order to obtain an overview of the uncertainty caused by the low temporal revisit time of CloudSat (Palerme et al, 2014;Van Tricht et al, 2016). The revisit time of CloudSat equals several days for most of the locations on the AIS.…”

“…The Cloud Profiling Radar on board the Cloud-Sat satellite (Stephens et al, 2002) is the first to provide information about snowfall on a continental scale over the AIS using the 2C-SNOW-PROFILE product (Wood et al, 2013. Launched in 2006, it overpasses each location on the AIS within 100 km with a temporal revisit time of 7 days or less and has a strong latitudinal dependency (Van Tricht et al, 2016). Palerme et al (2014) constructed a continental snowfall climatology at a grid of 1 • latitude by 2 • longitude, including information about the phase and frequency of snowfall.…”

Present‐Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2

“…Near‐surface specific humidity is also downscaled, assuming that relative humidity is constant with elevation. New in CESM2 is an EC correction for LW with a linear lapse rate of 32 W m km , a value inferred from Van Tricht, Lhermitte, Lenaerts, Gorodetskaya, van Lipzig, et al () (their Figure 6). As no radiation should be added to (or removed from) the CLM grid cell mean, LW is normalized after this downscaling.…”