An investigation of the sensitivity of a land surface model to climate change using a reduced form model

Abstract. Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25±5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44±4.37 and 14.98±4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

Download Full-text

QA4SM – An online tool for satellite soil moisture data validation

10.5194/egusphere-egu21-7398 ◽

2021 ◽

Author(s):

Samuel Scherrer ◽

Wolfgang Preimesberger ◽

Monika Tercjak ◽

Zoltan Bakcsa ◽

Alexander Boresch ◽

...

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Land Surface ◽

Global Climate ◽

European Space Agency ◽

Land Surface Model ◽

Surface Model ◽

Space Applications ◽

Online Tool ◽

Soil Moisture Data

To validate satellite soil moisture products and compare their quality with other products, standardized, fully traceable validation methods are required. The QA4SM (Quality Assurance for Soil Moisture; ) free online validation tool provides an easy-to-use implementation of community best practices and requirements set by the Global Climate Observing System and the Committee on Earth Observation Satellites. It sets the basis for a community wide standard for validation studies.QA4SM can be used to preprocess, intercompare, store, and visualise validation results. It uses state-of-the-art open-access soil moisture data records such as the European Space Agency&#8217;s Climate Change Initiative (ESA CCI) and the Copernicus Climate Change Services (C3S) soil moisture datasets, as well as single-sensor products, e.g. H-SAF Metop-A/B ASCAT surface soil moisture, SMOS-IC, and SMAP L3 soil moisture. Non-satellite data include in-situ data from the International Soil Moisture Network (ISMN: ), as well as land surface model or reanalysis products, e.g. ERA5 soil moisture.Users can interactively choose temporal or spatial subsets of the data and apply filters on quality flags. Additionally, validation of anomalies and application of different scaling methods are possible. The tool provides traditional validation metrics for dataset pairs (e.g. correlation, RMSD) as well as triple collocation metrics for dataset triples. All results can be visualised on the webpage, downloaded as figures, or downloaded in NetCDF format for further use. Archiving and publishing features allow users to easily store and share validation results. Published validation results can be cited in reports and publications via DOIs.The new version of the service provides support for high-resolution soil moisture products (from Sentinel-1), additional datasets, and improved usability.We present an overview and examples of the online tool, new features, and give an outlook on future developments.Acknowledgements: This work was supported by the QA4SM & QA4SM-HR projects, funded by the Austrian Space Applications Programme (FFG).

Download Full-text

Relative contributions of climate change, stomatal closure, and leaf area index changes to 20th and 21st century runoff change: A modelling approach using the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model

Journal of Geophysical Research Atmospheres ◽

10.1029/2009jd013408 ◽

2010 ◽

Vol 115 (D17) ◽

Cited By ~ 33

Author(s):

Ramdane Alkama ◽

Masa Kageyama ◽

Gilles Ramstein

Keyword(s):

Climate Change ◽

21St Century ◽

Land Surface ◽

Stomatal Closure ◽

Land Surface Model ◽

Surface Model ◽

Area Index ◽

Runoff Change ◽

Index Changes ◽

Modelling Approach

Download Full-text

Ecosystem Feedbacks to Climate Change in California: Development, Testing, and Analysis Using a Coupled Regional Atmosphere and Land Surface Model (WRF3–CLM3.5)

Earth Interactions ◽

10.1175/2010ei331.1 ◽

2011 ◽

Vol 15 (15) ◽

pp. 1-38 ◽

Cited By ~ 33

Author(s):

Z. M. Subin ◽

W. J. Riley ◽

J. Jin ◽

D. S. Christianson ◽

M. S. Torn ◽

...

Keyword(s):

Climate Change ◽

Land Cover ◽

Air Temperature ◽

Land Surface ◽

Vegetation Change ◽

Land Surface Model ◽

Natural Vegetation ◽

Surface Model ◽

Temperature Changes ◽

Model Version

Abstract A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California’s climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California’s climate was assessed by comparing simulations by WRF3–CLM3.5 and WRF3–Noah to observations from 1982 to 1991. Using WRF3–CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of −0.7° to +1°C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2°–1.2°C reductions in summer daily-mean 2-m air temperature and 2.0°–3.7°C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate–vegetation interactions.

Download Full-text

MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

Geoscientific Model Development ◽

10.5194/gmd-13-4713-2020 ◽

2020 ◽

Vol 13 (10) ◽

pp. 4713-4747

Author(s):

Tokuta Yokohata ◽

Tsuguki Kinoshita ◽

Gen Sakurai ◽

Yadu Pokhrel ◽

Akihiko Ito ◽

...

Keyword(s):

Climate Change ◽

Water Management ◽

Land Use ◽

Land Use Change ◽

Land Surface ◽

Crop Yields ◽

Land Surface Model ◽

Climate System ◽

Surface Model ◽

Earth System

Abstract. Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural–human earth system components.

Download Full-text

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-6773-2014 ◽

2014 ◽

Vol 7 (5) ◽

pp. 6773-6809

Author(s):

T. Osborne ◽

J. Gornall ◽

J. Hooker ◽

K. Williams ◽

A. Wiltshire ◽

...

Keyword(s):

Climate Change ◽

Land Surface ◽

Land Surface Model ◽

Water Security ◽

Climate Change Impacts ◽

Heat Fluxes ◽

Surface Model ◽

Yield Model ◽

Area Index ◽

The Impact

Abstract. Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

Download Full-text

Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

Hydrology and Earth System Sciences ◽

10.5194/hess-22-1411-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 1411-1435 ◽

Cited By ~ 5

Author(s):

Gina Tsarouchi ◽

Wouter Buytaert

Keyword(s):

Climate Change ◽

Land Use ◽

Water Resources ◽

Land Use Change ◽

Land Surface ◽

Land Surface Model ◽

Coupled Model ◽

Surface Model ◽

Climate Change Scenarios ◽

Ganges River

Abstract. Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000–2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000–2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030–2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

Download Full-text