Understanding Land–Atmosphere Interactions across a Range of Spatial and Temporal Scales

Abstract

What: Scientists from 15 different countries met to update the state of the science on landatmosphere interactions considering a wide range of spatial and temporal scales and to discuss how to improve both our understanding of biophysical processes that occur at the land surface and their representation in atmospheric models. here is an increasing awareness of landatmosphere interactions (L-AI) in modulating local phenomena as well as weather and climate variability at regional scales. As a result, the increasing attention that L-AI processes are receiving nowadays is not surprising. Our understanding of the biophysical processes governing these interactions is still limited, thereby hampering improvement in model parameterizations and their influence at different spatial and temporal scales.A collaborative effort between the Research Centre for Energy, Environment and Technology (CIEMAT; Spain), the Wageningen University (WU; the Netherlands) and the Complutense University of Madrid (UCM; Spain) was directed to organize an international workshop to update our scientific understanding of the biophysical processes controlling L-AI, the different modeling approaches used to represent them, and the impacts that these processes and their interactions produce in the regional climate. The special format of the workshop 1 with keynote lectures, posters, and large time slots dedicated to discussion facilitated the necessary interaction among the participants considering the many subdisciplines within the field. The following sections highlight the main topics covered in the 1 The event was partially funded by the European Geosciences Union (EGU) and the Ministerio de Economa y Competitividad (MINECO) from the Spanish government.

Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET

“…The increase in coupling between LE and H to T a and R g for small P/ET p further highlights the importance of convective processes that impact ABL growth and present multiple avenues for feedbacks mediated by the surface-ABL system. [15][16][17][18][19] PNs applied across aridity gradients can be used to better understand potential changes to land-atmosphere interactions and ecosystem functioning across temporal and spatial scales. Given that semi-arid ecosystems are critical to the carbon cycle and climate, [64][65][66] and are likely to expand 67 and deteriorate 68 under climate change, the ability of PNs to quantify their coupling to the atmosphere is of particular importance.…”

“…These energy fluxes modify the composition of the atmospheric boundary-layer (ABL) and drive convective processes that deepen the ABL and result in entrainment of air from the free troposphere. [15][16][17][18][19] These changes then impact nearsurface temperature and humidity as well as precipitation processes, resulting in potential feedbacks through ecosystem physiological response to favor subsequent latent or sensible heat fluxes that in turn impact ABL processes. 20 Such feedback processes may intensify with future climate changes, 21 with the potential to impact critical functions such as water availability 22 and ecosystem resilience, 23 and to intensify phenomena such as heat waves, [24][25][26] drought, [27][28][29] and local convective precipitation.…”

Effects of modified soil water‐heat physics on RegCM4 simulations of climate over the Tibetan Plateau

“…Land surface properties affect the climate and atmosphere mainly because they have a large influence on local circulation and the monsoon [Koster et al, 2004;Suh and Lee, 2004;Kim and Wang, 2007;Jimenez et al, 2014;Hirsch et al, 2014]. Land surface condition changes such as soil moisture or land use/land cover changes can influence surface temperature and humidity by means of the partitioning of the surface energy fluxes [Koster et al, 2004;Leung et al, 2011;Cho et al, 2014;Hirsch et al, 2014].…”

Regional modeling of surface‐atmosphere interactions and their impact on Great Lakes hydroclimate

“…When coupled with the NCAR Community Land Model (CLM), RegCM identifies relatively weak coupling over the Great Lakes and elsewhere in the U.S. [ Mei et al , ]. However, while RCMs generally reproduce atmospheric conditions, their ability to accurately simulate land‐lake‐atmosphere feedbacks remains uncertain [ Jimenez et al , ].…”