The Plumbing of Land Surface Models Best, M. J.; Abramowitz, G.; Johnson, H. R. ...
Journal of hydrometeorology,
06/2015, Letnik:
16, Številka:
3
Journal Article
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The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. ...Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically basedmodels and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.
Species distribution models (SDMs) are common tools for assessing the potential impact of climate change on species ranges. Uncertainty in SDM output occurs due to differences among alternate models, ...species characteristics and scenarios of future climate. While considerable effort is being devoted to identifying and quantifying the first two sources of variation, a greater understanding of climate scenarios and how they affect SDM output is also needed. Climate models are complex tools: variability occurs among alternate simulations, and no single 'best' model exists. The selection of climate scenarios for impacts assessments should not be undertaken arbitrarily - strengths and weakness of different climate models should be considered. In this paper, we provide bioclimatic modellers with an overview of emissions scenarios and climate models, discuss uncertainty surrounding projections of future climate and suggest steps that can be taken to reduce and communicate climate scenario-related uncertainty in assessments of future species responses to climate change.
Surface cooling in temperate regions is a common biogeophysical response to historical Land‐Use induced Land Cover Change (LULCC). The climate models involved in LUCID show, however, significant ...differences in the magnitude and the seasonal partitioning of the temperature change. The LULCC‐induced cooling is directed by decreases in absorbed solar radiation, but its amplitude is 30 to 50% smaller than the one that would be expected from the sole radiative changes. This results from direct impacts on the total turbulent energy flux (related to changes in land‐cover properties other than albedo, such as evapotranspiration efficiency or surface roughness) that decreases at all seasons, and thereby induces a relative warming in all models. The magnitude of those processes varies significantly from model to model, resulting on different climate responses to LULCC. To address this uncertainty, we analyzed the LULCC impacts on surface albedo, latent heat and total turbulent energy flux, using a multivariate statistical analysis to mimic the models' responses. The differences are explained by two major ‘features’ varying from one model to another: the land‐cover distribution and the simulated sensitivity to LULCC. The latter explains more than half of the inter‐model spread and resides in how the land‐surface functioning is parameterized, in particular regarding the evapotranspiration partitioning within the different land‐cover types, as well as the role of leaf area index in the flux calculations. This uncertainty has to be narrowed through a more rigorous evaluation of our land‐surface models.
Key Points
Non‐radiative effects of LULCC reduce by 30 to 50% the albedo‐induced cooling
Land use representation is a major cause of uncertainty in the LULCC impacts
LSMs' parameterizations lead to divergent evaporation responses to LULCC
Seven climate models were used to explore the biogeophysical impacts of human‐induced land cover change (LCC) at regional and global scales. The imposed LCC led to statistically significant decreases ...in the northern hemisphere summer latent heat flux in three models, and increases in three models. Five models simulated statistically significant cooling in summer in near‐surface temperature over regions of LCC and one simulated warming. There were few significant changes in precipitation. Our results show no common remote impacts of LCC. The lack of consistency among the seven models was due to: 1) the implementation of LCC despite agreed maps of agricultural land, 2) the representation of crop phenology, 3) the parameterisation of albedo, and 4) the representation of evapotranspiration for different land cover types. This study highlights a dilemma: LCC is regionally significant, but it is not feasible to impose a common LCC across multiple models for the next IPCC assessment.
The coupled climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are evaluated. The evaluation is focused on 12 regions of Australia for the daily ...simulation of precipitation, minimum temperature, and maximum temperature. The evaluation is based on probability density functions and a simple quantitative measure of how well each climate model can capture the observed probability density functions for each variable and each region is introduced. Across all three variables, the coupled climate models perform better than expected. Precipitation is simulated reasonably by most and very well by a small number of models, although the problem with excessive drizzle is apparent in most models. Averaged over Australia, 3 of the 14 climate models capture more than 80% of the observed probability density functions for precipitation. Minimum temperature is simulated well, with 10 of the 13 climate models capturing more than 80% of the observed probability density functions. Maximum temperature is also reasonably simulated with 6 of 10 climate models capturing more than 80% of the observed probability density functions. An overall ranking of the climate models, for each of precipitation, maximum, and minimum temperatures, and averaged over these three variables, is presented. Those climate models that are skillful over Australia are identified, providing guidance on those climate models that should be used in impacts assessments where those impacts are based on precipitation or temperature. These results have no bearing on how well these models work elsewhere, but the methodology is potentially useful in assessing which of the many climate models should be used by impacts groups.
Abstract Mandatory disclosure of physical climate risks to businesses is planned or being implemented in many countries. This raises the question, how viable is it to link increasing physical climate ...risk, expressed as extreme events, to an individual business. We demonstrate how the characteristics of increasing frequency, magnitude and duration of extreme events impact a hypothetical business supply chain using the analogy of a spider’s web, where an extreme event impacting a strand of the web (supply/market line) impacts the efficiency of the web (supply chain). We demonstrate that our hypothetical business, located in the centre of the web, can be unaffected by a very large number of extreme events, or be severely impacted by a small number of events, depending on exactly where the event occurs and the properties of the event. This implies that a business cannot assess physical climate risk based on a change in the frequency of events; the business needs to know the precise location of the events, as well as the magnitude and duration of each event. This information is not available and is unlikely to ever be available from climate model projections. Therefore, individual businesses required to disclose future physical climate risk are very unlikely to be able to provide useful quantitative assessments. We recommend that a business-specific storyline approach to future risk is used where multiple lines of evidence are woven into a risk assessment, including climate projections. Generic top–down prescriptions of future scenarios are very likely to lead to misrepresentation of risk and very poor outcomes for business, investors or financial regulators seeking to build resilience to future climate change.
A Fourier transform infrared (FTIR) spectroscopic study of changes in chemistry of Scots pine (
Pinus sylvestris L.) sapwood and beech (
Fagus sylvatica L.) decayed by
Coniophora puteana ...((Schumacher) Karsten),
Coriolus versicolor ((L.) Quelet) and
Phanerochaete chrysosporium (Burdsall) is presented. Wood was exposed to fungi for different durations up to 12 weeks, with decay assessed through weight loss and FTIR. The relative changes in intensities of spectral bands associated with lignin and carbohydrates as a result of decay were determined after different exposure periods. In wood decayed by
C. puteana there was a progressive increase in lignin content relative to carbohydrate evident from increases in the relative height of lignin associated bands (at 1596, 1505, 1330, 1230 and
1122
cm
−1
in beech and 1596, 1511, 1268 and
1220
cm
−1
in pine) and a corresponding decrease in the intensities of carbohydrate bands (at 1738, 1375, 1158 and
898
cm
−1
). At higher weight losses, spectra for wood decayed by
C. puteana have many similarities with that of Klason lignin isolated from wood. In contrast, wood decayed by
P.
chrysosporium showed selective type decay with a reduction in peak heights associated with lignin relative to carbohydrates. Although weight losses in samples exposed to
C. versicolor were high (45.5% and 39.8% for beech and Scots pine, respectively, after 12 weeks) simultaneous decay resulted in little change in the relative intensities of the lignin and carbohydrate bands, with only a slight preference for lignin.
Strong regional differences exist in how hot temperature extremes increase under global warming. Using an ensemble of coupled climate models, we examine the regional warming rates of hot extremes ...relative to annual average warming rates in the same regions. We identify hot spots of accelerated warming of model‐simulated hot extremes in Europe, North America, South America, and Southeast China. These hot spots indicate where the warm tail of a distribution of temperatures increases faster than the average and are robust across most Coupled Model Intercomparison Project Phase 5 models. Exploring the conditions on the specific day when the hot extreme occurs demonstrates that the hot spots are explained by changes in the surface energy fluxes consistent with drying soils. However, the model‐simulated accelerated warming of hot extremes appears inconsistent with observations, except over Europe. The simulated acceleration of hot extremes may therefore be unreliable, a result that necessitates a reevaluation of how climate models resolve the relevant terrestrial processes.
Key Points
Climate model simulations show distinct hot spots, robust across most CMIP5 models, where daily hot extremes warm faster than mean temperatures
Changes in surface energy fluxes, consistent with drying soils, accelerate warming on the day hot extremes occur
The spatial patterns of accelerated warming of hot extremes in the CMIP5 models are inconsistent with observations, except over Europe
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