Imaging spectroscopy of snow physical properties: Scientific and measurement requirements coupled with regional to global climate modeling for addressing uncertainties in melt controls in Earth's cryosphere

Atmospheric warming from greenhouse gases (GHG) is contributing to acceleration of snowmelt but its magnitude is uncertain due to our uncertainties in the controls on the dominant contributor to annual melt (90-95% of the net flux), absorbed sunlight, itself controlled by snow albedo. With increased solar absorption, warming and melt commence markedly earlier in the snow season. Despite this crucial role of albedo and solar radiation in snow and ice melt, sparse measurements have kept us from understanding the global distribution of controls on albedo, snow grain size (GS), and radiative forcing by light absorbing particles (e.g. dust, black carbon) on planet Earth.

Multispectral optical remote sensing has given us access to indications of the controls on snow albedo and in turn climatic feedbacks of the cryosphere in the Earth system, but the uncertainties in these retrievals inhibit the proper quantification relative to GHG forcings. The accuracies required to understand the relative roles of changes in albedo and GHG radiative forcing in changing snow warming and melt require the spectral resolving capacity of the visible-through-shortwave infrared imaging spectrometer, as annunciated in the need for the coming NASA Surface Biology and Geology mission concept [National Academies of Sciences, 2018].

In this talk, we first speak to the scientific requirements and their underpinnings for addressing the fundamental science question:

What are the driving energy components contributing to cryosphere loss on planet Earth?

Because the dominant control on melt remains more uncertain that our understanding of the GHG forcing itself, it is crucial that we bring to bear more accurate and precise measurements across the global cryosphere to reduce this uncertainty sufficiently. Thus, we present the remote sensing retrievals and snowmelt modeling constraints we are applying to existing airborne and coming spaceborne imaging spectrometers.