scholarly journals LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome

2016 ◽  
Vol 9 (8) ◽  
pp. 2809-2832 ◽  
Author(s):  
Bart van den Hurk ◽  
Hyungjun Kim ◽  
Gerhard Krinner ◽  
Sonia I. Seneviratne ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Surface Radiation ◽  
The Arctic ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Systematic Biases ◽  
Intercomparison Project

Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

scholarly journals The Land Surface, Snow and Soil moisture Model Intercomparison Program (LS3MIP): aims, set-up and expected outcome

2016 ◽  
Author(s):  
Bart van den Hurk ◽  
Hyungjun Kim ◽  
Gerhard Krinner ◽  
Sonia I. Seneviratne ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Large Scale ◽  
Surface Radiation ◽  
The Arctic ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Systematic Biases

Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode ("LMIP", building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework ("LFMIP", building upon the GLACE-CMIP blueprint).

scholarly journals CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

2021 ◽  
Author(s):  
Binghao Jia ◽  
Longhuan Wang ◽  
Yan Wang ◽  
Ruichao Li ◽  
Xin Luo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Grid Point ◽  
Global Ocean ◽  
Surface Model ◽  
Past Century ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Intercomparison Project

AbstractThe datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

scholarly journals Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change

2020 ◽  
Vol 14 (9) ◽  
pp. 3155-3174 ◽  
Author(s):  
Eleanor J. Burke ◽  
Yu Zhang ◽  
Gerhard Krinner
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
High Latitude ◽  
Soil Profile ◽  
Coupled Model ◽  
The Arctic ◽  
Model Intercomparison ◽  
Model Ensemble ◽  
Northern High Latitude ◽  
Intercomparison Project

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.

Land-surface feedbacks on temperature and precipitation in CMIP6-LS3MIP projections

2021 ◽  
Author(s):  
Franco Catalano ◽  
Andrea Alessandri ◽  
Wilhelm May ◽  
Thomas Reerink
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Climate Change Signal ◽  
Moisture Change ◽  
Climate Conditions ◽  
Temperature And Precipitation ◽  
Systematic Biases ◽  
The Impact

<p align="justify"><span>The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) aims at diagnosing systematic biases in the land models of CMIP6 Earth System Models and assessing the role of land-atmosphere feedbacks on climate change. Two components of experiments have been designed: the first is devoted to the assessment of the systematic land biases in offline mode (LMIP) while the second component is dedicated to the analysis of the land feedbacks in coupled mode (LFMIP). Here we focus on the LFMIP experiments. In the LFMIP protocol (van den Hurk et al. 2016), which builds upon the GLACE-CMIP configuration, two sets of climate-sensitivity projections have been carried out in amip mode: in the first set (amip-lfmip-pdLC) the land feedbacks to climate change have been disabled by prescribing the soil-moisture states from a climatology derived from “present climate conditions” (1980-2014) while in the second set (amip-lfmip-rmLC) 30-year running mean of land-surface state from the corresponding ScenarioMIP experiment (O’Neill et al., 2016) is prescribed. The two sensitivity simulations span the period 1980-2100 with sea surface temperature and sea-ice conditions prescribed from the first member of historical and ScenarioMIP experiments. Two different scenarios are considered: SSP1-2.6 (f1) and SSP5-8.5 (f2).</span></p><p align="justify"><span>In this analysis, we focus on the differences between amip-lfmip-rmLC and amip-lfmip-pdLC at the end of the 21st Century (2071–2100) in order to isolate the impact of the soil moisture changes on surface climate change. The (2071-2100) minus (1985-2014) temperature change is positive everywhere over land and the climate change signal of precipitation displays a clear intensification of the hydrological cycle in the Northern Hemisphere. Warming and hydrological cycle intensification are larger in SSP5-8.5 scenario. Results show large differences in the feedbacks between wet, transition and semi-arid climates. In particular, over the regions with negative soil moisture change, the 2m-temperature increases significantly while the cooling signal is not significant over all the regions getting wetter. In agreement with Catalano et al. (2016), the larger effects on precipitation due to soil moisture forcing occur mostly over transition zones between dry and wet climates, where evaporation is highly sensitive to soil moisture. The sensitivity of both 2m-temperature and precipitation to soil moisture change is much stronger in the SSP5-8.5 scenario.</span></p>

Complementing ERA5 and E-OBS20 with high resolution river discharge

2020 ◽  
Author(s):  
Stefan Hagemann ◽  
Tobias Stacke
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Land Surface ◽  
River Discharge ◽  
River Mouth ◽  
Water Model ◽  
Model Intercomparison ◽  
Station Data ◽  
Intercomparison Project ◽  
Subsurface Runoff

<p>The 0.5° resolution of many global observational datasets is not sufficient for the requirements of current state-of-the-art regional climate model (RCM) simulations over Europe. Here, the ERA5 reanalysis of the ECMWF (C3S 2017) and E-OBS data (Cornes et al. 2018) are frequently used as reference datasets when RCM results are evaluated on resolutions higher than 0.5°. In addition, ERA5 data are also commonly used to force regional ocean models. As ERA data do not comprise river discharges, the lateral forcing of freshwater inflow from land is taken from other data sources, such as station data, runoff climatologies, etc. However, these data are not necessarily consistent with the ERA5 forcing over the ocean surface. If such data are derived from station data, they are only available for specific rivers and not spatially homogeneously distributed for all coastal areas. In addition, they might not be representative for the river mouth if the respective station location is too far away from the river mouth, which is often the case.</p><p>In order to allow a consistent forcing of river discharges and evaluation of simulated hydrological fluxes, we extended ERA5 and E-OBS v20.0e with high resolution river discharge. This also allows a consistent assessment of hydrological changes from these two datasets. The discharge was simulated with the recently developed 5 Min. version of the Hydrological discharge (HD) model (Hagemann et al., submitted). Note that for the development of this HD model version, no river specific parameter adjustments were conducted so that the HD model is generally applicable for climate change studies and over ungauged catchments.</p><p>The HD model requires gridded fields of surface and subsurface runoff as input with a daily temporal resolution or higher. As no large-scale observations of these variables exist, they need to be calculated by a land surface scheme or hydrology model using observed or re-analyzed meteorological data. Here, we used the HydroPy global hydrological model, which is the successor of the MPI-HM model (Stacke and Hagemann 2012). The latter has contributed to the WATCH Water Model Intercomparison Project (WaterMIP; Haddeland et al. 2011) and the inter-sectoral impact model intercomparison project (ISIMIP; Warszawski et al. 2014). Note that ERA5 also comprises archived fields of surface and subsurface runoff, but it turned out that its separation of total runoff is not suitable to generate adequate river discharges with the HD model. In our presentation, we evaluate the simulated discharge using various metrics and consider significant discharge trends over Europe.</p><p><strong>References</strong></p><p>C3S (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS)</p><p>Cornes, R., et al. (2018) J. Geophys. Res. Atmos. 123, doi:10.1029/2017JD028200</p><p>Haddeland, I., et al. (2011). J. Hydrometeorol. 12, doi: 10.1175/2011jhm1324.1</p><p>Hagemann, S., T. Stacke and H. Ho-Hagemann, High resolution discharge simulations over Europe and the Baltic Sea catchment. Frontiers in Earth Sci., submitted.</p><p>Stacke, T. and Hagemann, S. (2012). Hydrol. Earth Syst. Sci. 16, doi: 10.5194/hess-16-2915-2012</p><p>Warszawski, L., et al. (2014) Proc. Natl. Acad. Sci. USA 111, doi: 10.1073/pnas.1312330110</p>

scholarly journals CAS FGOALS-f3-L Large-ensemble Simulations for the CMIP6 Polar Amplification Model Intercomparison Project

2021 ◽  
Author(s):  
Bian He ◽  
Xiaoqi Zhang ◽  
Anmin Duan ◽  
Qing Bao ◽  
Yimin Liu ◽  
...  
Keyword(s):  
Time Lag ◽  
The Arctic ◽  
Global Ocean ◽  
Arctic Amplification ◽  
Model Intercomparison ◽  
Large Ensemble ◽  
Sea Ice Concentration ◽  
Ensemble Simulations ◽  
Polar Amplification ◽  
Intercomparison Project

AbstractLarge-ensemble simulations of the atmosphere-only time-slice experiments for the Polar Amplification Model Intercomparison Project (PAMIP) were carried out by the model group of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L). Eight groups of experiments forced by different combinations of the sea surface temperature (SST) and sea ice concentration (SIC) for pre-industrial, present-day, and future conditions were performed and published. The time-lag method was used to generate the 100 ensemble members, with each member integrating from 1 April 2000 to 30 June 2001 and the first two months as the spin-up period. The basic model responses of the surface air temperature (SAT) and precipitation were documented. The results indicate that Arctic amplification is mainly caused by Arctic SIC forcing changes. The SAT responses to the Arctic SIC decrease alone show an obvious increase over high latitudes, which is similar to the results from the combined forcing of SST and SIC. However, the change in global precipitation is dominated by the changes in the global SST rather than SIC, partly because tropical precipitation is mainly driven by local SST changes. The uncertainty of the model responses was also investigated through the analysis of the large-ensemble members. The relative roles of SST and SIC, together with their combined influence on Arctic amplification, are also discussed. All of these model datasets will contribute to PAMIP multi-model analysis and improve the understanding of polar amplification.

Deriving SAR Soil Moisture Retrieval Algorithms and Soil Drainage Classification for Boreal Peatlands

2021 ◽  
Author(s):  
Laura Bourgeau-Chavez ◽  
Jeremy Graham ◽  
Andrew Poley ◽  
Dorthea Leisman ◽  
Michael Battaglia
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Ground Surface ◽  
Terrestrial Ecosystem ◽  
Independent Study ◽  
Additive Models ◽  
Soil Drainage ◽  
Boreal Peatlands ◽  
Retrieval Algorithms

<p>Eighty percent of global peatlands are distributed across the boreal and subarctic regions, storing an estimated 30% of earth’s soil organic carbon (1,016 to 1,105 Gt C) despite representing only about 3% of the global land surface. The accumulation of C in peatlands generally depends on hydrologic conditions that maintain saturated soils and impede rates of decomposition. Boreal Peatlands have provided rich reservoirs of stored C for millennia. However, with climate change, warming and drying patterns across the boreal and arctic are resulting in dramatic changes in ecosystems and putting these systems at risk of changing from a C sink to a source.  Recent changes in climate including earlier springs, longer summers and changes in moisture patterns across the landscape, are affecting wildfire regimes of the boreal region including intensity, severity and frequency of wildfires. This in turn has potential to cause shifts in successional trajectories.  Understanding how these changes in climate are affecting peatlands and their vulnerability to wildfire has been a focus of study of the research team since 2009.  Soil moisture is one variable which can provide information to understand wildfire behavior including the depth of peat consumption in these wildfires but it also has a direct effect on post-fire successional trajectories. Further it is needed to understand methane emissions from peatlands.  To develop the soil moisture retrieval algorithms, we studied a range of boreal peatland sites (bogs and fens) stratified across geographic regions from 2012-2014.  We developed soil moisture retrieval algorithms from polarimetric C-band (5.7 cm wavelength) synthetic aperture radar (SAR) data.  Peatlands have low enough aboveground biomass (<3.0 kg/m<sup>2</sup>) to allow this shorter wavelength SAR to penetrate the canopy to reach the ground surface.  Data from over 60, 4 ha sites were collected over 3 seasons from Alaska and Michigan USA and Alberta Canada.  Both multi-linear regressions and general additive models (GAM) were developed.  Using both polarimetric SAR parameters that are sensitive to vegetation structure and parameters most sensitive to surface soil moisture in the models provided the best results.  GAM models were tested in an independent study area, Northwest Territories (NWT), Canada.  The sites of NWT were sampled in 2016-2019 coincident to Radarsat-2 polarimetric image collections.  The high accuracy results will be presented as well as methods developed to use multidate C-band data from Sentinel-1 to classify soil drainage (well drained to poorly drained) in recently burned peatlands.  These products are being used in a fire effects and emissions model, CanFIRE, as we parameterize it for peatlands; as well as the Functionally-Assembled Terrestrial Ecosystem Simulator <strong>(</strong>FATES) to understand the effects of wildfire and hydrology on peatland ecosystems.  Characterization and quantification of boreal peatlands in global C cycling is critical for proper accounting given that peatlands play a significant role in sequestering and releasing large amounts of C. The ability to retrieve soil moisture from C-band SAR, therefore, provides a means to monitor a key variable in scaling C flux estimates as well as understanding the vulnerability and resiliency of boreal peatlands to climate change.</p><p> </p>

scholarly journals Sensitivity of mid-Pliocene climate to changes in orbital forcing, and PlioMIP's boundary conditions

2020 ◽  
Author(s):  
Eric Samakinwa ◽  
Christian Stepanek ◽  
Gerrit Lohmann
Keyword(s):  
Boundary Conditions ◽  
The Arctic ◽  
Seasonal Temperature ◽  
Model Output ◽  
Orbital Forcing ◽  
Model Intercomparison ◽  
Model Sensitivity ◽  
Modelling Methodology ◽  
Intercomparison Project ◽  
Two Phases

Abstract. In this study, we compare results obtained from modelling the mid-Pliocene warm period using the Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) with the two different modelling methodologies and sets of boundary conditions prescribed for the two phases of the Pliocene Model Intercomparison Project (PlioMIP), tagged PlioMIP1 and PlioMIP2. Boundary conditions, model forcing, and modelling methodology for the two phases of PlioMIP differ considerably in palaeogeography, in particular with regards to the state of ocean gateways, ice-masks, treatment of vegetation and topography. Further differences between model setups as suggested for PlioMIP1 and PlioMIP2 consider updates to the concentration of trace gases: atmospheric carbon dioxide (CO2), is specified as 405 and 400 parts per million by volume (ppmv) for PlioMIP1 and PlioMIP2, respectively. There are also minor differences in the concentrations of methane (CH4) and nitrous oxide (N2O) due to changes in the protocol of the Paleoclimate Model Intercomparison Project (PMIP) from phase 3 to phase 4. Employing a single model across two phases of PlioMIP enables a better understanding of the impact that the various differences in modelling methodology between PlioMIP1 and PlioMIP2 have on model output. Yet, a dedicated comparison of COSMOS model output of PlioMIP1 and PlioMIP2 is not in the curriculum of model analyses proposed in PlioMIP2. Here, we bridge the gap between our contributions to PlioMIP1 (Stepanek and Lohmann, 2012) and PlioMIP2 (Stepanek et al., 2020). We highlight some of the effects that differences in the chosen mid-Pliocene model setup (PlioMIP2 vs. PlioMIP1) have on the climate state as derived with the COSMOS, as this information will be valuable in the framework of the model-model and model-data-comparison within PlioMIP2. We evaluate the model sensitivity to improved mid-Pliocene boundary conditions using PlioMIP's core mid-Pliocene experiments for PlioMIP1 and PlioMIP2, and present further simulations where we test model sensitivity to variations in palaeogeography, orbit and concentration of CO2. Firstly, we highlight major changes in boundary conditions from PlioMIP1 to PlioMIP2 and also the challenges recorded from the initial effort. The results derived from our simulations show that COSMOS simulates a mid-Pliocene climate state that is 0.29 K colder in PlioMIP2, if compared to PlioMIP1 (17.82 °C in PlioMIP1, 17.53 °C in PlioMIP2, values based on simulated surface skin temperature). On one hand, high-latitude warming, which is supported by proxy evidence of the mid-Pliocene, is underestimated in simulations of both PlioMIP1 and PlioMIP2. On the other hand, spatial variations in surface air temperature (SAT), sea surface temperature (SST) as well as the distribution of sea ice suggest improvement of simulated SAT and SST in PlioMIP2 if employing the updated palaeogeography. Our PlioMIP2 mid-Pliocene simulation produces warmer SSTs in the Arctic and North Atlantic Ocean than derived from the respective PlioMIP1 climate state. The difference in prescribed CO2 accounts for 1.1 K of warming in the Arctic, leading to an ice-free summer in the PlioMIP1 simulation, and a quasi ice-free summer in PlioMIP2. Beyond the official set of PlioMIP2 simulations, we present further simulations and analyses that sample the phase space of potential alternative orbital forcings that have acted during the Pliocene and may have impacted on geological records. Employing orbital forcing, which differ from that proposed for PlioMIP2 (i.e. corresponding to Pre-Industrial conditions) but falls into the Mid-Pliocene time period targeted in the PlioMIP, leads to pronounced annual and seasonal temperature variations, which are not directly retrievable from the marine and terrestrial reconstruction of the time-slice.

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