Diagnosis and Improvement of Cryosphere Shortwave Radiation Biases in Global Climate Models.

Faithful representation of cryospheric change is critical for accurate climate modeling, but there are complicating issues in representing snow extent and reflectance in physically realistic ways. This thesis is a collection of diagnostics and improvements of cryospheric shortwave radiation in climate models. Firstly, we incorporate a diagnostic called the cryosphere radiative effect (CrRE), the instantaneous influence of surface snow and sea ice on the top-of-model solar energy budget, into two released versions of the Community Earth System Model. CrRE offers a more climatically relevant metric of the cryospheric state than snow and sea ice extent and is influenced by factors such as the seasonal cycle of insolation, cloud masking, and vegetation cover. We evaluate CrRE during the late 20th century and over the 21st century, specifically diagnosing the CrRE contributions from terrestrial and marine sources. Present-day boreal CrRE compares well with observationally derived estimates. Similar present-day CrRE in the two model versions results from compensating differences in cloud masking and sea ice extent. Radiative forcing in future warming scenarios reduces boreal and austral sea ice cover, and boreal snow cover, which each contribute roughly 1 W/m-2 to enhancing global absorbed shortwave radiation. Similar global cryospheric albedo feedbacks between 0.41-0.45 W/m2/K indicate the models exhibit similar temperature-normalized CrRE change. Secondly, we incorporated a modified canopy scheme into the Community Land Model with snow interception as a prognostic variable and snow unloading tuned to in-situ measurements. The canopy radiation scheme has been updated from a direct temperature dependence of optical parameters to a dependence on the prognostic snow storage. With these improvements, boreal forest zones show large, significant albedo error reductions relative to MODIS observations. 13% gridcell RMSE reduction during spring results from a more gradual seasonal transition in albedo, while 27% reduction in winter is from a lower albedo. Over all North Hemisphere land area, error was also reduced. Thirdly, we assess the impacts of the snow canopy vegetation treatment in coupled model warming scenarios. Little change in global albedo feedback or climate sensitivity were shown, but significant alterations resulted that varied both regionally and temporally.PhDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113453/1/perketj_1.pd

Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models

Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal‐scale SAF is strongly correlated with century‐scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m−2 K−1. These results suggest that models’ mean decadal‐scale SAFs are good estimates of their century‐scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.Key PointsPeriods with global warming of at least 0.5 K provide reasonable estimates of surface albedo feedbackModels’ 21st century surface albedo feedbacks are strongly correlated with their mean decadal‐scale feedbacksSixteen CMIP5 models show significant strengthening in decadal‐scale surface albedo feedback throughout the 21st centuryPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142955/1/grl56989.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142955/2/grl56989_am.pd

Diagnosing shortwave cryosphere radiative effect and its 21st century evolution in CESM

We incorporate a new diagnostic called the cryosphere radiative effect (CrRE), the instantaneous influence of surface snow and sea ice on the top‐of‐model solar energy budget, into two released versions of the Community Earth System Model (CESM1 and CCSM4). CrRE offers a more climatically relevant metric of the cryospheric state than snow and sea ice extent and is influenced by factors such as the seasonal cycle of insolation, cloud masking, and vegetation cover. We evaluate CrRE during the late 20th century and over the 21st century, specifically diagnosing the nature of CrRE contributions from terrestrial and marine sources. The radiative influence of ice sheets and glaciers is not considered, but snow on top of them is accounted for. Present‐day global CrRE in both models is −3.8 W m −2 , with a boreal component (−4.2 to −4.6 W m −2 ) that compares well with observationally derived estimates (−3.9 to −4.6 W m −2 ). Similar present‐day CrRE in the two model versions results from compensating differences in cloud masking and sea ice extent. Over the 21st century, radiative forcing in the Representative Concentration Pathway (RCP) 8.5 scenario causes reduced boreal sea ice cover, austral sea ice cover, and boreal snow cover, which all contribute roughly equally to enhancing global absorbed shortwave radiation by 1.4–1.8 Wm −2 . Twenty‐first century RCP8.5 global cryospheric albedo feedback are +0.41 and +0.45 W/m 2 /K, indicating that the two models exhibit similar temperature‐normalized CrRE change. Key Points We implement the first GCM diagnostic calculation of cryosphere radiative effect Global average CrRE from snow and sea ice is −4 W m −2 in present‐day simulations Earth absorbs 1.6 W m −2 more insolation from cryosphere loss by 2099 in RCP8.5Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106707/1/jgrd51156.pd

Land-Focused Changes in the Updated GEOS FP System (Version 5.25)

Many of the changes imposed in the January 2020 upgrade from Version 5.22 to 5.25 of the Goddard Earth Observing System (GEOS) Forward Processing (FP) analysis system were designed to increase the realism of simulated land variables. The changes, which consist of both land model parameter updates and improvements to the physical treatments employed for various land processes, have generally positive or neutral impacts on the character of the FP product, as documented here

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.National Science Foundation (NSF); National Center for Atmospheric Research - NSF [1852977]; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science; Columbia University Presidential Fellowship; U.S. Department of Agriculture NIFA Award [2015-67003-23485]; NASA Interdisciplinary Science Program Award [NNX17AK19G]; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program [DE-SC0008317, DESC0016188]; National Science Foundation (NSF) [DEB-1153401]; NASA's CARBON program; NASA's TE program; National Aeronautics & Space Administration (NASA)Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]