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DOE OSTI2015

Design of a Multisensory Probe for Measuring Carbon Cycle Processes in Aqueous Subterranean Environments

The global carbon cycle describes the exchange of carbon between the atmosphere, terrestrial vegetation, oceans, and soil. Mechanisms involving carbon in sub-terrestrial ecosystems and their impact on climate are not well understood. This lack of understanding limits current climate models and prevents accurate soil-carbon storage predications for future climate conditions. To address the lack of instrumentation for conducting high fidelity measurements of appropriate parameters in the field, a multi-sensory probe using a mix of optical, fiber optic, and electronic technologies to measure CO2, temperature, dissolved oxygen, redox potential, and water level in subsurface environments has been developed. Details of the design, fabrication and laboratory performance verification are presented. Use cases and the anticipated impacts of such measurements on climate models are discussed.

McIntyre, Timothy J↗

DOE OSTI2022

Tropical Cirrus in Global Storm-Resolving Models: 1. Role of Deep Convection

Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top-of-atmosphere radiation balance and stratospheric water vapor budget. These cirrus are often associated with deep convection, which global climate models must parameterize and struggle to accurately simulate. By comparing high-resolution global storm-resolving models from the Dynamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) intercomparison that explicitly simulate deep convection to satellite observations, we assess how well these models simulate deep convection, convectively generated cirrus, and deep convective injection of water into the TTL over representative tropical land and ocean regions. The DYAMOND models simulate deep convective precipitation, organization, and cloud structure fairly well over land and ocean regions, but with clear intermodel differences. All models produce frequent overshooting convection whose strongest updrafts humidify the TTL and are its main source of frozen water. Intermodel differences in cloud properties and convective injection exceed differences between land and ocean regions in each model. We argue that, with further improvements, global storm-resolving models can better represent tropical cirrus and deep convection in present and future climates than coarser-resolution climate models. To realize this potential, they must use available observations to perfect their ice microphysics and dynamical flow solvers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The Largest Ever Recorded Heatwave—Characteristics and Attribution of the Antarctic Heatwave of March 2022

An unprecedented heatwave impacted East Antarctica in March 2022, peaking at 39°C above climatology, the largest temperature anomaly ever recorded globally. We investigate the causes of the heatwave, the impact of climate change, and a climate model's ability in simulating such an event. The heatwave, which was skillfully forecast, resulted from a highly anomalous large-scale circulation pattern that advected an Australian airmass to East Antarctica in 4 days and produced record atmospheric heat fluxes. Southern Ocean sea surface temperatures anomalies had a minimal impact on the heatwave's amplitude. Simulations from a climate model fail to simulate such a large temperature anomaly mostly due to biases in its large-scale circulation variability, showcasing a pathway for future model improvement in simulating extreme heatwaves. The heatwave was made 2°C warmer by climate change, and end of 21st century heatwaves may be an additional 5–6°C warmer, raising the prospect of near-melting temperatures over the interior of East Antarctica.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Steric Sea Level Rise and Relationships with Model Drift and Water Mass Representation in GFDL CM4 and ESM4

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases.

Krasting, John P. [a NOAA/OAR/Geophysical Fluid Dy↗

DOE OSTI2014

Meeting the Radiative Forcing Targets of the Representative Concentration Pathways in a World with Agricultural Climate Impacts

This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the Representative Concentration Pathways (RCPs). We build on the recently completed ISI-MIP exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to the GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6 W/m2 in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts, simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.

agricultural climate impacts↗

DOE OSTI2015

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Evaluation of autoconversion and accretion enhancement factors in general circulation model warm-rain parameterizations using ground-based measurements over the Azores

A great challenge in climate modeling is how to parameterize subgrid cloud processes, such as autoconversion and accretion in warm-rain formation. In this study, we use ground-based observations and retrievals over the Azores to investigate the so-called enhancement factors, E auto and E accr , which are often used in climate models to account for the influence of subgrid variance of cloud and precipitation water on the autoconversion and accretion processes. E auto and E accr are computed for different equivalent model grid sizes. The calculated E auto values increase from 1.96 (30 km) to 3.2 (180 km), and the calculated E accr values increase from 1.53 (30 km) to 1.76 (180 km). Comparing the prescribed enhancement factors in Morrison and Gettleman (2008, MG08) to the observed ones, we found that a higher E auto (3.2) at small grids and lower E accr (1.07) are used in MG08, which might explain why most of the general circulation models (GCMs) produce too-frequent precipitation events but with too-light precipitation intensity. The ratios of the rain to cloud water mixing ratio ( q r / q c ) at E accr =1.07 and E accr =2.0 are 0.063 and 0.142, respectively, from observations, further suggesting that the prescribed value of E accr =1.07 used in MG08 is too small to simulate precipitation intensity correctly. Both E auto and E accr increase when the boundary layer becomes less stable, and the values are larger in precipitating clouds ( CLWP>75 gm -2 ) than those in non-precipitating clouds ( CLWP<75 gm -2 ). Therefore, the selection of E auto and E accr values in GCMs should be regime- and resolution-dependent.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Reduced viscosity steadily weakens oceanic currents

The viscosity of both air and water is temperature dependent. A rising temperature leads to an increased viscosity for air but a decreased viscosity for water. As climate becomes warmer, this increased air viscosity can partly inhibit the reduction of wind stress over the ocean, and the reduced water viscosity causes less downward momentum and heat transport. As these opposing effects of warming on air and water viscosity are not included in the state-of-the-art climate models, the understanding of their potential impacts on the response of the climate system to the anthropogenic warming is lacking. Here, via analyzing the Simple Ocean Data Assimilation oceanic reanalysis dataset, we show that the ocean heat content increases at a rate of ~1.3 × 10 22 J/yr over 35 years, which leads to a continuous reduction of oceanic viscosity. As a result, the ocean vertical shear enhances with a shoaling of the mixed layer depth and a reduced vertical linkage in the ocean. Our calculations show a reduction of the oceanic kinetic energy at a rate of ~2.4 × 10 16 J/yr. Potentially, this could generate far-reaching impacts on the energy storage of the climate system and, hence, could pace the global warming. Thus, it is important to include the temperature-dependent viscosity in our climate models. Freshwater discharged from polar ice sheets and mountain glaciers also contributes to the reduction in oceanic viscosity but, at present, to a lesser extent than that in oceanic warming. Reduced oceanic viscosity, therefore, is an important, but hitherto overlooked, response to a warming climate and contributes to many recent weather extremes including heavier rainfall rates in hurricanes, slackening of the polar vortex, and oceanic heat waves.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

Projections of Declining Surface-Water Availability for the Southwestern United States

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

Seager, Richard↗

DOE OSTI2023

The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

climate models↗

DOE OSTI2024

An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles

Abstract. This work assesses a recently produced 21-member climate model large ensemble (LE) based on the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2 (E3SM2). The ensemble spans the historical era (1850 to 2014) and 21st century (2015 to 2100), using the SSP370 pathway, allowing for an evaluation of the model's forced response. A companion 500-year preindustrial control simulation is used to initialize the ensemble and estimate drift. Characteristics of the LE are documented and compared against other recently produced ensembles using the E3SM version 1 (E3SM1) and Community Earth System Model (CESM) versions 1 and 2. Simulation drift is found to be smaller, and model agreement with observations is higher in versions 2 of E3SM and CESM versus their version 1 counterparts. Shortcomings in E3SM2 include a lack of warming from the mid to late 20th century, likely due to excessive cooling influence of anthropogenic sulfate aerosols, an issue also evident in E3SM1. Associated impacts on the water cycle and energy budgets are also identified. Considerable model dependence in the response to both aerosols and greenhouse gases is documented and E3SM2's sensitivity to variable prescribed biomass burning emissions is demonstrated. Various E3SM2 and CESM2 model benchmarks are found to be on par with the highest-performing recent generation of climate models, establishing the E3SM2 LE as an important resource for estimating climate variability and responses, though with various caveats as discussed herein. As an illustration of the usefulness of LEs in estimating the potential influence of internal variability, the observed CERES-era trend in net top-of-atmosphere flux is compared to simulated trends and found to be much larger than the forced response in all LEs, with only a few members exhibiting trends as large as observed, thus motivating further study.

58 GEOSCIENCES↗

DOE OSTI2023

Statistical Generation of Ocean Forcing With Spatiotemporal Variability for Ice Sheet Models

Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ice sheet model projections, this uncertainty has not previously been quantified because of the prohibitive computational expense of running large climate model ensembles. Here, we develop and demonstrate a technique that generates independent realizations of internal climate variability from a single climate model simulation. Building on previous developments in model emulation, this technique uses empirical orthogonal function decomposition and Fourier-phase randomization to generate statistically consistent realizations of spatiotemporal variability fields for the target climate variable. The method facilitates efficient sampling of a wide range of climate trajectories, which can also be incorporated within ice sheet or other physical models to represent feedback processes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

Interannual Variability of Tropospheric Trace Gases and Aerosols: The Role of Biomass Burning Emissions

Fires are responsible for a range of gaseous and aerosol emissions. However, their influence on the interannual variability of atmospheric trace gases and aerosols has not been systematically investigated from a global perspective. We examine biomass burning emissions as a driver of interannual variability of large-scale abundances of short-lived constituents such as carbon monoxide (CO), hydroxyl radicals (OH), ozone and aerosols using the GISS ModelE composition-climate model and a range of observations, with an emphasis on satellite information. Our model captures the observed variability of the constituents examined in most cases, but with substantial underestimates in boreal regions. The strongest interannual variability on a global scale is found for carbon monoxide (10 for its global annual burden), while the lowest is found for tropospheric ozone (10 for its global annual burden). Regionally, aerosol optical depth shows variability that exceeds 50. Areas of strong variability include the tropical land regions and northern high latitudes, while even regions in the northern midlatitudes experience substantial inteannual variability of aerosols. Ozone variability peaks over Equatorial Asia in boreal autumn, partly due to varying biomass burning emissions, and over the western and central Pacific in the rest of the year, mainly due to meteorological fluctuations. We find that biomass burning emissions are almost entirely responsible for global CO interannual variability, and similarly important for OH variability. The same is true for global and regional aerosol variability, especially when not taking into account dust and sea-salt particles. We show that important implications48 can arise from such interannual influences for regional climate and air quality.

aerosols↗

DOE OSTI2024

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

In the past decade, dynamical downscaling using “pseudo-global-warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)-simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic-scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large-scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic-scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Real-Time Ice Nuclei Measurements at Oliktok Point Field Campaign Report

The ability of atmospheric particles (aerosols) to serve as heterogeneous ice nuclei (IN) for formation of ice and mixed-phase clouds is one of the least understood microphysical processes resulting in large uncertainties in climate modeling. As stated in the Intergovernmental Panel on Climate Change 2007 report, “The effects of aerosol particles on heterogeneous ice formation are currently insufficiently understood and present another level of challenge for both observations and modeling.” IN can strongly affect cloud radiative properties and precipitation formation. Only a small fraction (often less than 1%) of all aerosol particles act as atmospheric IN. Therefore, it becomes important to identify the active fraction of aerosol particles under a variety of environmental conditions. Proposed IN measurement techniques provide IN concentrations as a function of temperature and humidity conditions, and this unique data set can be analyzed to develop or constrain IN parameterizations that models rely on to calculate primary ice formation. Currently, the processes of ice formation within models are poorly represented, such that climate models often inaccurately partition cloud water between liquid and solid ice. Model studies have shown that uncertainties in cloud phase partitioning induce large uncertainties in the impact of mixedphase clouds on climate change. Arctic clouds composed of ice particles and supercooled liquid droplets at temperatures warmer than -37°C are important for the Arctic’s climate because of their extensive horizontal coverage over long periods, and their impact on the surface radiative balance and thus ice sheet coverage. The complexity of microphysical processes within these clouds and the sensitivity of precipitation to the details of microphysics are not fully understood. In addition, representation of these processes in a variety of cloud models continues to be challenging. Arctic clouds provide unique conditions to understand heterogeneous ice nucleation mechanisms, particularly immersion freezing, and will be the initial focus of the ice nucleation group. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM)-North Slope of Alaska (NSA) site is well equipped with other aerosol measurement (number concentration, size) instruments, and a relationship among long-term IN measurements and aerosol physical and chemical properties under different environmental conditions can be identified and established. The long-term IN measurements will be critical for understanding the ice nucleation process in response to the seasonal variations of aerosol and developing robust ice nucleation parameterizations for cloud and climate models. In the future, IN measurements could also be made at other ARM-NSA sites, specifically, Oliktok Point.

Arctic processes (meteorology), Oliktok Point, aer↗

NASA NTRS1993

Obliquity variation in a Mars climate evolution model

The existence of layered terrain in both polar regions of Mars is strong evidence supporting a cyclic variation in climate. It has been suggested that periods of net deposition have alternated with periods of net erosion in creating the layered structure that is seen today. The cause for this cyclic climatic behavior is variation in the annually averaged latitudinal distribution of solar insolation in response to obliquity cycles. For Mars, obliquity variation leads to major climatological excursion due to the condensation and sublimation of the major atmospheric constituent, CO2. The atmosphere will collapse into the polar caps, or existing caps will rapidly sublimate into the atmosphere, dependent upon the polar surface heat balance and the direction of the change in obliquity. It has been argued that variations in the obliquity of Mars cause substantial departures from the current climatological values of the surface pressure and the amount of CO2 stored in both the planetary regolith and polar caps. In this new work we have modified the Haberle et al. model to incorporate variable obliquity by allowing the polar and equatorial insolation to become functions of obliquity, which we assume to vary sinusoidally in time. As obliquity varies in the model, there can be discontinuities in the time evolution of the model equilibrium values for surface pressure, regolith, and polar cap storage. The time constant, tau r, for the regolith to find equilibrium with the climate is estimated--depending on the depth, thermal conductivity, and porosity of the regolith--between 10(exp 4) and 10(exp 6) yr. Thus, using 2000-yr timesteps to move smoothly through the 0.1250 m.y. obliquity cycles, we have an atmosphere/regolith system that cannot be assumed in equilibrium. We have dealt with this problem by limiting the rate at which CO2, can move between the atmosphere and regolith, mimicking the diffusive nature and effects of the temperature and pressure waves, by setting the time rate of change of regolith storage proportional to the difference between equilibrium storage and current storage.

Tyler, D.↗

DOE OSTI2017

The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework

Millimeter Wavelength Cloud Radar (MMCR) data from December 1996 to December 2010, collected at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site, are used to examine the diurnal cycle of hydrometeor occurrence. These data are categorized into clouds (-40 dBZ e ≤ reflectivity < -10 dBZ e ), drizzle and light precipitation (-10 dBZ e ≤ reflectivity < 10 dBZ e ), and heavy precipitation (reflectivity ≥ 10 dBZ e ). The same criteria are implemented for the observation-equivalent reflectivity calculated by feeding outputs from a Multiscale Modeling Framework (MMF) climate model into a radar simulator. The MMF model consists of the National Center for Atmospheric Research Community Atmosphere Model with conventional cloud parameterizations replaced by a cloud-resolving model. We find that a radar simulator combined with the simple reflectivity categories can be an effective approach for evaluating diurnal variations in model hydrometeor occurrence. It is shown that the MMF only marginally captures observed increases in the occurrence of boundary layer clouds after sunrise in spring and autumn and does not capture diurnal changes in boundary layer clouds during the summer. Above the boundary layer, the MMF captures reasonably well diurnal variations in the vertical structure of clouds and light and heavy precipitation in the summer but not in the spring.

54 ENVIRONMENTAL SCIENCES↗