Dr. Johanna Teresa Malle

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH₄ and CO₂ concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Land surface processes, crucial for exchanging carbon, nitrogen, water, and energy between the atmosphere and terrestrial Earth, significantly impact the climate system. Many of these processes vary considerably at small spatial and temporal scales, in particular in mountainous terrain and complex topography. To examine the impact of spatial resolution and representativeness of input data on modelled land surface processes, we conducted simulations using the Community Land Model 5 (CLM5) at different resolutions and based on a range of input datasets over the spatial extent of Switzerland. Using high-resolution meteorological forcing and land use data, we found that increased resolution substantially improved the representation of snow cover in CLM5 (up to 52 % enhancement), allowing CLM5 to closely match performance of a dedicated snow model. However, a simple lapse-rate-based temperature downscaling provided large positive effects on model performance, even if simulations were based on coarse-resolution forcing datasets only. Results demonstrate the need for resolutions higher than 0.25° for accurate snow simulations in topographically complex terrain. These findings have profound implications for climate impact studies. As improvements were observed across the cascade of dependencies in the land surface model, high spatial resolution and high-quality forcing data become necessary for accurately capturing the effects of a declining snow cover and consequent shifts in the vegetation period, particularly in mountainous regions. This study further highlights the utility of multi-resolution modelling experiments when aiming to improve representation of variables in land surface models. By embracing high-resolution modelling, we can enhance our understanding of the land surface and its response to climate change.

Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 m spatial resolution across Switzerland. Our results reveal strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 ^∘C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 ^∘C, respectively. We also found that, in open grasslands, maximum temperatures at 5 cm above ground are, on average, 3.4 ^∘C warmer than those of the macroclimate, suggesting that, in such habitats, heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed-effect models with input from detailed radiation estimates from radiative transfer models that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography, and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by root mean squared errors ranging from 1.18 to 3.43 ^∘C, with minimum temperatures being predicted more accurately overall than maximum temperatures. The microclimate-mapping methodology presented here enables a biologically relevant perspective when analysing climate–species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change.

Land Surface Albedo (LSA) of forested environments continues to be a source of uncertainty in land surface modeling, especially across seasonally snow covered domains. Assessment and improvement of global scale model performance has been hampered by the contrasting spatial scales of model resolution and in‐situ LSA measurements. In this study, point‐scale simulations of the Community Land Model 5.0 (CLM5) were evaluated across a large range of forest structures and solar angles at two climatically different locations. LSA measurements, using an uncrewed aerial vehicle with up and down‐looking shortwave radiation sensors, showed canopy structural shading of the snow surface exerted a primary control on LSA. Diurnal patterns of measured LSA revealed strong effects of both azimuth and zenith angles, neither of which were adequately represented in simulations. In sparse forest environments, LSA were overestimated by up to 66%. Further analysis revealed a lack of correlation between Plant Area Index (PAI), the primary canopy descriptor in CLM5, and measured LSA. Instead, measured LSA showed considerable correlation with the fraction of snow visible in the sensor's field of view, a correlation which increased further when only considering the sunlit fraction of visible snow. The use of effective PAI values as a simple first‐order correction for the discrepancy between measured and simulated LSA in sparse forest environments substantially improved model results (64%-76% RMSE reduction). However, the large biases suggest the need for a more generic solution, for example, by introducing a canopy metric that represents canopy gap fraction rather than assuming a spatially homogeneous canopy.

Forested environments feature a highly complex radiation regime. The three-dimensional canopy structure masks solar radiation as it penetrates through the forest. This entails sub-canopy radiation to vary in space, over time, season, and with weather conditions, which challenges both measurements and modelling. Here we combine the experimental acquisition of forest structure information with radiation transfer modelling to achieve efficient and accurate estimation of sub-canopy shortwave radiation at very high temporal resolution. For this purpose we have developed a Matlab-based software tool to analyse digital hemispherical imagery for directional canopy transmissivity which yields, in combination with measured or estimated above-canopy shortwave radiation, respective below-canopy radiation. We demonstrate the utility of the tool to accurately model shortwave radiation in comparison to pyranometer measurements at both the point scale and along a transect under heterogeneous canopy cover. Optimized for computational efficiency the software even enables fully-distributed simulations. Without necessitating high performance computing or complex ray-tracing, this tool enables easy access to detailed sub-canopy radiation information. These should be valuable for validating site-scale radiation transfer models, as input to eco-hydrological and snowmelt models, and for researching light-dependant bio-physiological processes.

The complex dynamics of snow accumulation and melt processes under forest canopies entail major observational and modeling challenges, as they vary strongly in space and time. In this study, we present novel data sets acquired with mobile multisensor platforms in subalpine and boreal forest stands. These data sets include spatially and temporally resolved measurements of shortwave and longwave irradiance, air and snow surface temperatures, wind speed, and snow depth, all coregistered to canopy structure information. We then apply the energy balance snow model FSM2 to obtain concurrent, distributed simulations of the forest snowpack at very high ("hyper") resolution (2 m). Our data sets allow us to assess the performance of alternative canopy representation strategies within FSM2 at the level of individual snow energy balance components and in a spatially explicit manner. We demonstrate the benefit of accounting for detailed spatial patterns of shortwave and longwave radiation transfer through the canopy and show the importance of describing wind attenuation by the canopy using stand‐scale metrics. With the proposed canopy representation, snowmelt dynamics in discontinuous forest stands were successfully reproduced. Hyper‐resolution simulations resolving these effects provide an optimal basis for assessing the snow‐hydrological impacts of forest disturbances and for validating and improving the representation of forest snow processes in land surface models intended for coarser‐scale applications.

Radiative processes are substantially altered by the presence of forest canopies, further affecting snow energetics during wintertime. In situ measurements of subcanopy radiation can help improve process‐scale understanding of these complex interactions, which are needed to further constrain and improve land surface models. In this study, a custom‐made cable car was used to measure incoming and outgoing, shortwave and longwave radiation below an evergreen forest stand. Hemispherical photographs taken concurrently from the cable car measured view fractions of shaded snow, sunlit snow, and bare ground. With this setup it was possible to quantify diurnal and seasonal radiation patterns together with their potential drivers at high spatiotemporal resolution. Measurements were performed between January and May 2018, along a 48‐m transect in a discontinuous needleleaf forest in the Swiss Alps. Analysis of diurnal radiation patterns revealed a strong linear relationship (R = 0.94) between outgoing shortwave radiation and sunlit snow‐view fraction, highlighting shading as the main control on the subcanopy shortwave radiation budget. Measurements of outgoing longwave radiation were strongly controlled by the snow cover extent, with locations of diminished snow cover showing an increase in outgoing longwave radiation of up to 60 W/m². The subcanopy radiation budget was shown to be dominated by shortwave radiation when surrounding canopy structure and the position of the sun allowed for direct insolation of the forest floor, but longwave radiation was the dominating component in the absence of direct insolation.

Small-scale variations in radiative transfer through forest canopies are strongly linked to canopy-structural heterogeneity. To date, upscaling of radiative transfer parametrizations developed at the point scale is hampered by (i) poor representation of canopy structure variability and (ii) limited spatially-explicit sub-canopy irradiance data to assess the performance of radiative transfer schemes at typical resolutions of land surface models. This study presents a novel approach for efficient in-situ characterization of canopy structure and sub-canopy irradiance over large spatial extents. The method involves a handheld radiometer assembly mounted on a motorized gimbal developed for non-stationary continuous measurements of shortwave and longwave radiation along forest transects. In combination with radiation and temperature data from a stationary reference station, spatially-resolved estimates of sky-view fraction, canopy transmissivity and longwave enhancement could be obtained. Under favourable meteorological conditions, validation against sky-view fraction data from hemispherical photographs yielded a RMSE of 0.03 (i.e. 3%). Irradiance measurements under heterogeneous canopy cover revealed strong spatial coherence between longwave radiation enhancement, shortwave radiation attenuation, and sky-view fraction on overcast days. Under clear-sky conditions however, sun flecks caused highly variable shortwave radiation transmissivity patterns. This study demonstrates the potential of handheld radiometer surveys to deliver valuable spatially-distributed datasets of co-located canopy structure and sub-canopy irradiance which can be used (i) as reference data for alternative approaches to derive canopy structure parameters, (ii) to improve modelling of sub-canopy radiation across a wide range of canopy distributions, and (iii) to support respective model upscaling efforts.