The Impact of Anthropogenic Land Use and Land Cover Change on Regional Climate Extremes

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land useland cover change (LULCC) on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics

Measuring Winds From Space to Reduce the Uncertainty in the Southern Ocean Carbon Fluxes: Science Requirements and Proposed Mission

Strong winds in Southern Ocean storms drive air-sea carbon and heat fluxes. These fluxes are integral to the global climate system and the wind speeds that drive them are increasing. The current scatterometer constellation measuring vector winds remotely undersamples these storms and the higher winds within them, leading to potentially large biases in Southern Ocean wind reanalyses and the fluxes that derive from them. This observing system design study addresses these issues in two ways. First, we describe an addition to the scatterometer constellation, called Southern Ocean Storms -- Zephyr, to increase the frequency of independent observations, better constraining high winds. Second, we show that potential reanalysis wind biases over the Southern Ocean lead to uncertainty over the sign of the net winter carbon flux. More frequent independent observations per day will capture these higher winds and reduce the uncertainty in estimates of the global carbon and heat budgets

Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

Variations in Northern Hemisphere snowfall: an analysis of historical trends and the projected response to anthropogenic forcing in the twenty-first century

Snowfall is an important feature of the Earth's climate system that has the ability to influence both the natural world and human activity. This dissertation examines past and future changes in snowfall related to increasing concentrations of anthropogenic greenhouse gases. Snowfall observations for North America, derived snowfall products for the Northern Hemisphere, and simulations performed with 13 coupled atmosphere-ocean global climate models are analyzed. The analysis of the spatial pattern of simulated annual trends on a grid point basis from 1951 to 1999 indicates that a transition zone exists above 60° N latitude across the Northern Hemisphere that separates negative trends in annual snowfall in the mid-latitudes and positive trends at higher latitudes. Regional analysis of observed annual snowfall indicates that statistically significant trends are found in western North America, Japan, and southern Russia. A majority of the observed historical trends in annual snowfall elsewhere in the Northern Hemisphere, however, are not statistically significant and this result is consistent with model simulations. Projections of future snowfall indicate the presence of a similar transition zone between negative and positive snowfall trends that corresponds with the area between the -10 to -15° C isotherms of the multi-model mean temperature of the late twentieth century in each of the fall, winter, and spring seasons. Redistributions of snowfall throughout the entire snow season are likely -- even in locations where there is little change in annual snowfall. Changes in the fraction of precipitation falling as snow contribute to decreases in snowfall across most Northern Hemisphere regions, while changes in precipitation typically contribute to increases in snowfall. Snowfall events less than or equal to 5 cm are found to decrease in the future across most of the Northern Hemisphere, while snowfall events greater than or equal to 20 cm increase in some locations, such as northern Quebec. A signal-to-noise analysis reveals that the projected changes in snowfall are likely to become apparent during the twenty-first century for most locations in the Northern Hemisphere.Ph.D.Includes bibliographical references (p. 98-108)

Regional sensitivity patterns of Arctic Ocean acidification revealed with machine learning

Ocean acidification is a consequence of the absorption of anthropogenic carbon emissions and it profoundly impacts marine life. Arctic regions are particularly vulnerable to rapid pH changes due to low ocean buffering capacities and high stratification. Here, an unsupervised machine learning methodology is applied to simulations of surface Arctic acidification from two state-of-the-art coupled climate models. We identify four sub-regions whose boundaries are influenced by present-day and projected sea ice patterns. The regional boundaries are consistent between the models and across lower (SSP2-4.5) and higher (SSP5-8.5) carbon emissions scenarios. Stronger trends toward corrosive surface waters in the central Arctic Ocean are driven by early summer warming in regions of annual ice cover and late summer freshening in regions of perennial ice cover. Sea surface salinity and total alkalinity reductions dominate the Arctic pH changes, highlighting the importance of objective sub-regional identification and subsequent analysis of surface water mass properties

Ocean Biogeochemistry in GFDL’s Earth System Model 4.1 and its Response to Increasing Atmospheric CO2

This contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation ofGFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2 increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2 yr−1 simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments

Supporting GFDL data for Southern Ocean Freshwater release model experiments Initiative (SOFIA)

Note: This data collection is hosted at the Geophysical Fluid Dynamics Laboratory. Data DOI capability is provided by PUL. Please refer to the README for a detailed description of the dataset. For questions, please contact [email protected], with the subject line including the title of the dataset.See "how_to_access_data.txt" to access data files from GDFL servers.This output was produced in coordination with the Southern Ocean Freshwater release model experiments Initiative (SOFIA) and is the Tier 1 experiment where freshwater is delivered in a spatially and temporally uniform pattern at the surface of the ocean at sea surface temperature in a 1-degree latitude band extending from Antarctica’s coastline. The total additional freshwater flux imposed as a monthly freshwater flux entering the ocean is 0.1 Sv. Users are referred to the methods section of Beadling et al. (2022) for additional details on the meltwater implementation in CM4 and ESM4. The datasets in this collection contain model output from the coupled global climate model, CM4, and Earth System Model, ESM4, both developed at the Geophysical Fluid Dynamics Laboratory (GFDL) of the National Oceanic and Atmospheric Administration (NOAA). The ocean_monthly_z and ocean_annual_z output are provided as z depth levels in meters as opposed to the models native hybrid vertical ocean coordinate which consists of z* (quasi-geopotential) coordinates in the upper ocean through the mixed layer, transitioning to isopycnal (referenced to 2000 dbar) in the ocean interior. Please see README for further details.File list: doc/README data/ cm4_tier1_antwater.agessc.ocean_annual_z.tar.gz cm4_tier1_antwater.bsnk.ice_monthly.tar.gz cm4_tier1_antwater.cld_amt.atmos_level_monthly.tar.gz cm4_tier1_antwater.evap.atmos_level_monthly.tar.gz cm4_tier1_antwater.evs.ocean_monthly.tar.gz cm4_tier1_antwater.ficeberg.ocean_monthly.tar.gz cm4_tier1_antwater.frazil.ice_monthly.tar.gz cm4_tier1_antwater.friver.ocean_monthly.tar.gz cm4_tier1_antwater.heat_content_surfwater.ocean_monthly.tar.gz cm4_tier1_antwater.hfds.ocean_monthly.tar.gz cm4_tier1_antwater.hflso.ocean_monthly.tar.gz cm4_tier1_antwater.hfsifrazil.ocean_monthly.tar.gz cm4_tier1_antwater.hfsso.ocean_monthly.tar.gz cm4_tier1_antwater.lsrc.ice_monthly.tar.gz cm4_tier1_antwater.mlotst.ocean_monthly.tar.gz cm4_tier1_antwater.precip.atmos_level_monthly.tar.gz cm4_tier1_antwater.prlq.ocean_monthly.tar.gz cm4_tier1_antwater.prsn.ocean_monthly.tar.gz cm4_tier1_antwater.rlntds.ocean_monthly.tar.gz cm4_tier1_antwater.rsntds.ocean_monthly.tar.gz cm4_tier1_antwater.sfdsi.ocean_monthly.tar.gz cm4_tier1_antwater.siconc.ice_monthly.tar.gz cm4_tier1_antwater.sithick.ice_monthly.tar.gz cm4_tier1_antwater.siu.ice_monthly.tar.gz cm4_tier1_antwater.siv.ice_monthly.tar.gz cm4_tier1_antwater.slp.atmos_level_monthly.tar.gz cm4_tier1_antwater.snowfl.ice_monthly.tar.gz cm4_tier1_antwater.so.ocean_annual_z.tar.gz cm4_tier1_antwater.so.ocean_monthly_z_complete.tar.gz cm4_tier1_antwater.static_fields.tar.gz cm4_tier1_antwater.tauuo.ocean_monthly.tar.gz cm4_tier1_antwater.tauvo.ocean_monthly.tar.gz cm4_tier1_antwater.temp.atmos_level_monthly.tar.gz cm4_tier1_antwater.thetao.ocean_annual_z.tar.gz cm4_tier1_antwater.thetao.ocean_monthly_z.tar.gz cm4_tier1_antwater.t_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.ucomp.atmos_level_monthly.tar.gz cm4_tier1_antwater.umo.ocean_annual_z.tar.gz cm4_tier1_antwater.umo.ocean_monthly_z.tar.gz cm4_tier1_antwater.uo.ocean_annual_z.tar.gz cm4_tier1_antwater.uo.ocean_monthly_z.tar.gz cm4_tier1_antwater.u_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.vcomp.atmos_level_monthly.tar.gz cm4_tier1_antwater.vmo.ocean_annual_z.tar.gz cm4_tier1_antwater.vmo.ocean_monthly_z.tar.gz cm4_tier1_antwater.volcello.ocean_annual_z.tar.gz cm4_tier1_antwater.volcello.ocean_monthly_z.tar.gz cm4_tier1_antwater.vo.ocean_annual_z.tar.gz cm4_tier1_antwater.vo.ocean_monthly_z.tar.gz cm4_tier1_antwater.v_ref.atmos_level_monthly.tar.gz cm4_tier1_antwater.wfo.ocean_monthly.tar.gz cm4_tier1_antwater.zos.ocean_monthly.tar.gz esm4_tier1_antwater.agessc.ocean_annual_z.tar.gz esm4_tier1_antwater.bsnk.ice_monthly.tar.gz esm4_tier1_antwater.cld_amt.atmos_level_monthly.tar.gz esm4_tier1_antwater.evap.atmos_level_monthly.tar.gz esm4_tier1_antwater.evs.ocean_monthly.tar.gz esm4_tier1_antwater.ficeberg.ocean_monthly.tar.gz esm4_tier1_antwater.frazil.ice_monthly.tar.gz esm4_tier1_antwater.friver.ocean_monthly.tar.gz esm4_tier1_antwater.heat_content_surfwater.ocean_monthly.tar.gz esm4_tier1_antwater.hfds.ocean_monthly.tar.gz esm4_tier1_antwater.hflso.ocean_monthly.tar.gz esm4_tier1_antwater.hfsifrazil.ocean_monthly.tar.gz esm4_tier1_antwater.hfsso.ocean_monthly.tar.gz esm4_tier1_antwater.lsrc.ice_monthly.tar.gz esm4_tier1_antwater.mlotst.ocean_monthly.tar.gz esm4_tier1_antwater.precip.atmos_level_monthly.tar.gz esm4_tier1_antwater.prlq.ocean_monthly.tar.gz esm4_tier1_antwater.prsn.ocean_monthly.tar.gz esm4_tier1_antwater.rlntds.ocean_monthly.tar.gz esm4_tier1_antwater.rsntds.ocean_monthly.tar.gz esm4_tier1_antwater.sfdsi.ocean_monthly.tar.gz esm4_tier1_antwater.siconc.ice_monthly.tar.gz esm4_tier1_antwater.sithick.ice_monthly.tar.gz esm4_tier1_antwater.siu.ice_monthly.tar.gz esm4_tier1_antwater.siv.ice_monthly.tar.gz esm4_tier1_antwater.sivol.ice_monthly.tar.gz esm4_tier1_antwater.slp.atmos_level_monthly.tar.gz esm4_tier1_antwater.snowfl.ice_monthly.tar.gz esm4_tier1_antwater.so.ocean_monthly_z.tar.gz esm4_tier1_antwater.static_fields.tar.gz esm4_tier1_antwater.tauuo.ocean_monthly.tar.gz esm4_tier1_antwater.tauvo.ocean_monthly.tar.gz esm4_tier1_antwater.temp.atmos_level_monthly.tar.gz esm4_tier1_antwater.thetao.ocean_monthly_z.tar.gz esm4_tier1_antwater.t_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.ucomp.atmos_level_monthly.tar.gz esm4_tier1_antwater.umo.ocean_monthly_z.tar.gz esm4_tier1_antwater.uo.ocean_monthly_z.tar.gz esm4_tier1_antwater.u_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.vcomp.atmos_level_monthly.tar.gz esm4_tier1_antwater.vmo.ocean_monthly_z.tar.gz esm4_tier1_antwater.volcello.ocean_monthly_z.tar.gz esm4_tier1_antwater.vo.ocean_monthly_z.tar.gz esm4_tier1_antwater.v_ref.atmos_level_monthly.tar.gz esm4_tier1_antwater.wfo.ocean_monthly_complete.tar.gz esm4_tier1_antwater.zos.ocean_monthly.tar.g

Dominance of the Southern Ocean in Anthropogenic Carbon and Heat Uptake in CMIP5 Models

The authors assess the uptake, transport, and storage of oceanic anthropogenic carbon and heat over the period 1861-2005 in a new set of coupled carbon-climate Earth system models conducted for the fifth phase of the Coupled Model Intercomparison Project (CMIP5), with a particular focus on the Southern Ocean. Simulations show that the Southern Ocean south of 30 degrees S, occupying 30% of global surface ocean area, accounts for 43% 63% (42 + 5 PgC) of anthropogenic CO2 and 75% 622% (23 + 9 x 10(22) J) of heat uptake by the ocean over the historical period. Northward transport out of the Southern Ocean is vigorous, reducing the storage to 33 +/- 6 Pg anthropogenic carbon and 12 +/- 7 x 10(22) J heat in the region. The CMIP5 models, as a class, tend to underestimate the observation-based global anthropogenic carbon storage but simulate trends in global ocean heat storage over the last 50 years within uncertainties of observation-based estimates. CMIP5 models suggest global and Southern Ocean CO2 uptake have been largely unaffected by recent climate variability and change. Anthropogenic carbon and heat storage show a common broad-scale pattern of change, but ocean heat storage is more structured than ocean carbon storage. The results highlight the significance of the Southern Ocean for the global climate and as the region where models differ the most in representation of anthropogenic CO2 and, in particular, heat uptake

Simple Global Ocean Biogeochemistry With Light, Iron, Nutrients and Gas Version 2 (BLINGv2): Model Description and Simulation Characteristics in GFDL's CM4.0

Simulation of coupled carbon-climate requires representation of ocean carbon cycling, but the computational burden of simulating the dozens of prognostic tracers in state-of-the-art biogeochemistry ecosystem models can be prohibitive. We describe a six-tracer biogeochemistry module of steady-state phytoplankton and zooplankton dynamics in Biogeochemistry with Light, Iron, Nutrients and Gas (BLING version 2) with particular emphasis on enhancements relative to the previous version and evaluate its implementation in Geophysical Fluid Dynamics Laboratory's (GFDL) fourth-generation climate model (CM4.0) with 1/4 degrees ocean. Major geographical and vertical patterns in chlorophyll, phosphorus, alkalinity, inorganic and organic carbon, and oxygen are well represented. Major biases in BLINGv2 include overly intensified production in high-productivity regions at the expense of productivity in the oligotrophic oceans, overly zonal structure in tropical phosphorus, and intensified hypoxia in the eastern ocean basins as is typical in climate models. Overall, while BLINGv2 structural limitations prevent sophisticated application to plankton physiology, ecology, or biodiversity, its ability to represent major organic, inorganic, and solubility pumps makes it suitable for many coupled carbon-climate and biogeochemistry studies including eddy interactions in the ocean interior. We further overview the biogeochemistry and circulation mechanisms that shape carbon uptake over the historical period. As an initial analysis of model historical and idealized response, we show that CM4.0 takes up slightly more anthropogenic carbon than previous models in part due to enhanced ventilation in the absence of an eddy parameterization. The CM4.0 biogeochemistry response to CO2 doubling highlights a mix of large declines and moderate increases consistent with previous models.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]

Impact of Mountains on Tropical Circulation in Two Earth System Models

Two state-of-the-art Earth systemmodels (ESMs) were used in an idealized experiment to explore the role of mountains in shaping Earth's climate system. Similar to previous studies, removing mountains from both ESMs results in the winds becoming more zonal and weaker Indian and Asian monsoon circulations. However, there are also broad changes to the Walker circulation and El Nino-Southern Oscillation (ENSO). Without orography, convection moves across the entire equatorial Indo-Pacific basin on interannual time scales. ENSO has a stronger amplitude, lower frequency, and increased regularity. A wider equatorial wind zone and changes to equatorial wind stress curl result in a colder cold tongue and a steeper equatorial thermocline across the Pacific basin during La Nina years. Anomalies associated with ENSO warm events are larger without mountains and have greater impact on the mean tropical climate than when mountains are present. Without mountains, the centennial-mean PacificWalker circulation weakens in both models by approximately 45%, but the strength of the mean Hadley circulation changes by less than 2%. Changes in the Walker circulation in these experiments can be explained by the large spatial excursions of atmospheric deep convection on interannual time scales. These results suggest that mountains are an important control on the large-scale tropical circulation, impacting ENSO dynamics and the Walker circulation, but have little impact on the strength of the Hadley circulation.National Science Foundation (NSF) Frontiers in Earth System Dynamics and NSF [EAR-1338553]6 month embargo; Published Online: 8 May 2017This 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]