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#vEGU21 Game Jam!

  • EGU news
  • 1 February 2021

Submit your favorite geoscience game for a chance to win the coveted ‘EGU Game of the Year’ title!

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Highlight articles

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The Cryosphere

Macroscopic water vapor diffusion is not enhanced in snow

Water vapor transport in dry snowpacks plays a significant role for snow metamorphism and the mass and energy balance of snowpacks. The molecular diffusion of water vapor in the interstitial pores is usually considered to be the main or only transport mechanism, and current detailed snow physics models therefore rely on the knowledge of the effective diffusion coefficient of water vapor in snow. Numerous previous studies have concluded that water vapor diffusion in snow is enhanced relative to that in air. Various field observations also indicate that for vapor transport in snow to be explained by diffusion alone, the effective diffusion coefficient should be larger than that in air. Here we show using theory and numerical simulations of idealized and measured snow microstructures that, although sublimation and deposition of water vapor onto snow crystal surfaces do enhance microscopic diffusion in the pore space, this effect is more than countered by the restriction of diffusion space due to ice. The interaction of water vapor with the ice results in water vapor diffusing more than inert molecules in snow but still less than in free air, regardless of the value of the sticking coefficient of water molecules on ice. Our results imply that processes other than diffusion play a predominant role in water vapor transport in dry snowpacks.

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Geoscientific Instrumentation, Methods and Data Systems

Experiments on magnetic interference for a portable airborne magnetometry system using a hybrid unmanned aerial vehicle (UAV)

Using unmanned aerial vehicles (UAVs) for airborne magnetometry offers not only improved access and rapid sampling but also reduced logistics costs. More importantly, the UAV-borne aeromagnetometry can be performed at low altitudes, which makes it possible to resolve fine features otherwise only evident in ground surveys. Developing such a UAV-borne aeromagnetometry system is challenging owing to strong magnetic interference introduced by onboard electric and electronic components. An experiment concerning the static magnetic interference of the UAV was conducted to assess the severity of the interference of a hybrid vertical take-off and landing (VTOL) UAV. The results of the static experiment show that the wing area is highly magnetic due to the proximity to servomotors and motors, whereas the area along the longitudinal axis of the UAV has a relatively smaller magnetic signature. Assisted by the static experiment and aerodynamic simulations, we first proposed a front-mounting solution with two compact magnetometers. Subsequently, two dynamic experiments were conducted with the setup to assess the dynamic interference of the system. The results of the dynamic experiments reveal that the strongest source of in-flight magnetic interference is the current-carrying cables connecting the battery to the flight controller and that this effect is most influential during pitch maneuvers of the aircraft.

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Climate of the Past

Last Glacial Maximum (LGM) climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity

Equilibrium climate sensitivity (ECS) has been directly estimated using reconstructions of past climates that are different than today’s. A challenge to this approach is that temperature proxies integrate over the timescales of the fast feedback processes (e.g., changes in water vapor, snow, and clouds) that are captured in ECS as well as the slower feedback processes (e.g., changes in ice sheets and ocean circulation) that are not. A way around this issue is to treat the slow feedbacks as climate forcings and independently account for their impact on global temperature. Here we conduct a suite of Last Glacial Maximum (LGM) simulations using the Community Earth System Model version 1.2 (CESM1.2) to quantify the forcingand efficacy of land ice sheets (LISs) and greenhouse gases (GHGs) in order to estimate ECS. Our forcing and efficacy quantification adopts the effective radiative forcing (ERF) and adjustment framework and provides a complete accounting for the radiative, topographic, and dynamical impacts of LIS on surface temperatures. ERF and efficacy of LGM LIS are -3.2 W m-2 and 1.1, respectively. The larger-than-unity efficacy is caused by the temperature changes over land and the Northern Hemisphere subtropical oceans which are relatively larger than those in response to a doubling of atmospheric CO2. The subtropical sea-surface temperature (SST) response is linked to LIS-induced wind changes and feedbacks in ocean–atmosphere coupling and clouds. ERF and efficacy of LGM GHG are -2.8 W m-2 and 0.9, respectively. The lower efficacy is primarily attributed to a smaller cloud feedback at colder temperatures. Our simulations further demonstrate that the direct ECS calculation using the forcing, efficacy, and temperature response in CESM1.2 overestimates the true value in the model by approximately 25 % due to the neglect of slow ocean dynamical feedback. This is supported by the greater cooling (6.8 ∘C) in a fully coupled LGM simulation than that (5.3 ∘C) in a slab ocean model simulation with ocean dynamics disabled. The majority (67 %) of the ocean dynamical feedback is attributed to dynamical changes in the Southern Ocean, where interactions between upper-ocean stratification, heat transport, and sea-ice cover are found to amplify the LGM cooling. Our study demonstrates the value of climate models in the quantification of climate forcings and the ocean dynamical feedback, which is necessary for an accurate direct ECS estimation.

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The Cryosphere

Review article: Earth’s ice imbalance

We combine satellite observations and numerical models toshow that Earth lost 28 trillion tonnes of ice between 1994 and 2017. Arcticsea ice (7.6 trillion tonnes), Antarctic ice shelves (6.5 trillion tonnes),mountain glaciers (6.1 trillion tonnes), the Greenland ice sheet (3.8trillion tonnes), the Antarctic ice sheet (2.5 trillion tonnes), andSouthern Ocean sea ice (0.9 trillion tonnes) have all decreased in mass.Just over half (58 %) of the ice loss was from the Northern Hemisphere,and the remainder (42 %) was from the Southern Hemisphere. The rate ofice loss has risen by 57 % since the 1990s – from 0.8 to 1.2 trilliontonnes per year – owing to increased losses from mountain glaciers,Antarctica, Greenland and from Antarctic ice shelves. During the sameperiod, the loss of grounded ice from the Antarctic and Greenland ice sheetsand mountain glaciers raised the global sea level by 34.6 ± 3.1 mm.The majority of all ice losses were driven by atmospheric melting (68 %from Arctic sea ice, mountain glaciers ice shelf calving and ice sheetsurface mass balance), with the remaining losses (32 % from ice sheetdischarge and ice shelf thinning) being driven by oceanic melting.Altogether, these elements of the cryosphere have taken up 3.2 % of theglobal energy imbalance.

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Latest posts from EGU blogs

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Rain or snow? Answering the question with citizen scientists

Rain or snow? Answering the question with citizen scientists

As a New Englander interested in weather, I was used to a fairly intuitive air temperature split between rain and snow. Once air temperature got slightly above freezing, I’d commonly see rainfall with snowfall more frequent below freezing. Then something happened when I moved to the Intermountain West of the United States. Instead of seeing rain when it was slightly above freezing, I’d see snow at seemingly paradoxically warm air temperature values, sometimes exceeding 4°C or 5°C (as shown on …

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The Sassy Scientist – You Don’t Have To Be Mad To Work Here…

The Sassy Scientist – You Don’t Have To Be Mad To Work Here…

…but it helps. Everyone has one colleague with that pinned above their desk. Sometimes with pictures of kittens. Lucile doesn’t want to be that interview candidate, so she asks: How can I prepare for an academic interview? Dear Lucile, Tips on how to appear to be a sane, motivated, enthusiastic, friendly, people-loving, positive, high-achieving, committed scientist? You’ve come to the wrong person. However, since The Sassy Scientist would definitely not hire The Sassy Scientist, I can give you a comprehensive …

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