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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Climate response to off-equatorial stratospheric sulfur injections in three Earth system models – Part 1: Experimental protocols and surface changes

There is now substantial literature on climate model studies of equatorial or tropical stratospheric SO 2 injections that aim to counteract the surface warming produced by rising concentrations of greenhouse gases. Here we present the results from the first systematic intercomparison of climate responses in three Earth system models wherein the injection of SO 2 occurs at different latitudes in the lower stratosphere: CESM2-WACCM6, UKESM1.0 and GISS-E2.1-G. The first two use a modal aerosol microphysics scheme, while two versions of GISS-E2.1-G use a bulk aerosol (One-Moment Aerosol, OMA) and a two-moment (Multiconfiguration Aerosol TRacker of mIXing state, MATRIX) microphysics approach, respectively. Our aim in this work is to determine commonalities and differences between the climate model responses in terms of the distribution of the optically reflective sulfate aerosols produced from the oxidation of SO 2 and in terms of the surface response to the resulting reduction in solar radiation. A focus on understanding the contribution of characteristics of models transport alongside their microphysical and chemical schemes, and on evaluating the resulting stratospheric responses in different models, is given in the companion paper (Bednarz et al., 2023). The goal of this exercise is not to evaluate these single-point injection simulations as stand-alone proposed strategies to counteract global warming; instead we determine sources and areas of agreement and uncertainty in the simulated responses and, ultimately, the possibility of designing a comprehensive intervention strategy capable of managing multiple simultaneous climate goals through the combination of different injection locations. We find large disagreements between GISS-E2.1-G and the CESM2-WACCM6 and UKESM1.0 models regarding the magnitude of cooling per unit of aerosol optical depth (AOD) produced, which varies from 4.7 K per unit of AOD in CESM2-WACCM6 to 16.7 K in the GISS-E2.1-G version with two-moment aerosol microphysics. By normalizing the results with the global mean response in each of the models and thus assuming that the amount of SO 2 injected is a free parameter that can be managed independently, we highlight some commonalities in the overall distributions of the aerosols, in the inter-hemispheric surface temperature response and in shifts to the Intertropical Convergence Zone, as well as some areas of disagreement, such as the extent of the aerosol confinement in the equatorial region and the efficiency of the transport to polar latitudes. In conclusion, we demonstrate that it is possible to use these simulations to produce more comprehensive injection strategies in multiple climate models. However, large differences in the injection magnitudes can be expected, potentially increasing inter-model spreads in some stratospheric quantities (such as aerosol distribution) while reducing the spread in the surface response in terms of temperature and precipitation; furthermore, the selection of the injection locations may be dependent on the models' specific stratospheric transport.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Intercomparison of Large-Eddy Simulations of Arctic Mixed-Phase Clouds: Importance of Ice Size Distribution Assumptions

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.

clouds↗
DOE OSTI2021

Measurements from mobile surface vehicles during the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE)

Abstract. Between 14 and 20 July 2018, small unmanned aircraft systems (UASs) were deployed to the San Luis Valley of Colorado (USA) alongside surface-based remote sensors, in situ sensors, and radiosonde systems as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). The measurements collected as part of LAPSE-RATE targeted quantities related to enhancing our understanding of boundary layer structure, cloud and aerosol properties and surface–atmosphere exchange and provide detailed information to support model evaluation and improvement work. Additionally, intensive intercomparison between the different unmanned aircraft platforms was completed. The current paper describes the observations obtained using three different types of surface-based mobile observing vehicles. These included the University of Colorado Mobile UAS Research Collaboratory (MURC), the National Oceanic and Atmospheric Administration National Severe Storms Laboratory Mobile Mesonet, and two University of Nebraska Combined Mesonet and Tracker (CoMeT) vehicles. Over the 1-week campaign, a total of 143 h of data were collected using this combination of vehicles. The data from these coordinated activities provide detailed perspectives on the spatial variability of atmospheric state parameters (air temperature, humidity, pressure, and wind) throughout the northern half of the San Luis Valley. These datasets have been checked for quality and published to the Zenodo data archive under a specific “community” setup for LAPSE-RATE (https://zenodo.org/communities/lapse-rate/, last access: 21 January 2021) and are accessible at no cost by all registered users. The primary dataset DOIs are https://doi.org/10.5281/zenodo.3814765 (CU MURC measurements; de Boer et al., 2020d), https://doi.org/10.5281/zenodo.3738175 (NSSL MM measurements; Waugh, 2020), and https://doi.org/10.5281/zenodo.3838724 (UNL CoMeT measurements; Houston and Erwin, 2020).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A protocol and analysis of year-long simulations of global storm-resolving models and beyond

We propose a protocol to evaluate and analyze year-long simulations of global storm-resolving models (GSRMs). The proposed protocol complements an earlier 40-day simulation protocol under the DYAMOND (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains) project to allow the analysis of the seasonal cycle and associated climatic relevant phenomena. This intercomparison aims to reveal how GSRMs, which can simulate mesoscale convective systems (MCSs) in the global domain, reproduce atmospheric large-scale structures related to convection beyond month-long simulations. The intercomparison for one-year simulations is conducted by either atmosphere-only models or atmosphere–ocean coupled models with atmospheric horizontal mesh sizes less than 5 km. We recommend the continuous four seasons from March 2020 to February 2021 as a target period for the intercomparison but with options for many groups to join more flexibly. The output variables are collected at 0.25° resolution, and archives of a small set of native grid variables are encouraged to analyze tropical cyclones and MCSs. Through the proposed global storm-resolving simulation, we will evaluate the climatological distributions of the atmospheric large-scale circulations, such as the Intertropical Convergence Zone (ITCZ), monsoon, midlatitude jets, their time evolution, and the upscale impacts on them. We present sample analyses from a one-year simulation using the 3.5 km mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM), revealing the realistic zonal contrast of tropical precipitation, no double ITCZ structure, the reasonable midlatitude jet position and intensity but a weak bias of storm track activities, and a warm bias over the Eurasia during boreal winter. We also clarify the cross-scale interaction, such as the effects of cold pools on mean precipitation over the Maritime Continent through the precipitation diurnal cycle and the effects of resolved gravity waves on midlatitude mean flows. The proposed one-year simulation protocol is referred to as the “Sendai Protocol.” This protocol is not unique or definite for evaluating GSRMs; we prospect a hierarchical set of experiments from short-term to multi-year simulations as GSRM intercomparisons.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

"Hot Spots" of Land Atmosphere Coupling

Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a severe paucity of relevant observational data and by the model-dependence of the various computational estimates. To counter this limitation, a dozen climate modeling groups have recently performed the same highly-controlled numerical experiment as part of a coordinated intercomparison project. This allows, for the first time ever, a superior multi-model approach to the estimation of the regions on the globe where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Such estimation has many potential benefits; it can contribute, for example, to seasonal rainfall prediction efforts.

Koster, Randal D.↗
NASA NTRS2001

Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

Cox, C.↗
NASA NTRS1997

Comparative Modeling Studies of Boreal Water and Carbon Balance

The coordination of the modeling and field efforts for an Intensive Field Campaign (IFC) may resemble the chicken and egg dilemma. This session's theme advocates that early and proactive involvement by modeling teams can produce a scientific and operational benefit for the IFC and Experiment. This talk will provide some examples and suggestions originating from the NASA funded IFC's of the FIFE First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment, Oregon Transect Ecosystem Research (OTTER) and predominately Boreal Ecosystem-Atmosphere Study (BOREAS) Experiments. In February 1994 and prior to the final selection of the BOREAS study sites, a group of funded BOREAS investigators agreed to run their models with data for five community types representing the proposed tower flux sites. All participating models were given identical initial values and boundary conditions and driven with identical climate data. The objectives of the intercomparison exercise were: 1) compare simulation results of participating terrestrial, hydrological, and atmospheric models over selected time frames; 2) learn about model behavior and sensitivity to estimated boreal site and vegetation definitions; 3) prioritize BOREAS field data collection efforts supporting modeling studies; 4) identify individual model deficiencies as early as possible. Out of these objectives evolved some important coordination and science issues for the BOREAS Experiment that can be generalized to IFCs and long term archiving of the data. Some problems are acceptable because they are endemic to maintaining fair and open competition prior to the peer review process. Others are logistical and addressable through application of planning, management, and information sciences. This investigator has identified one source of measurement and model incompatibility that is manifest in the IFC scaling approach. Although intuitively obvious, scaling problems are already more formally defined in the Geography literature. An example of the scaling problem will be demonstrated with Vegetation/Ecosystem Mapping and Analysis Project (VEMAP) and OTTER data.

Coughlan, J.↗
NASA NTRS1990

Satellite-derived cloud fields during the FIRE cirrus IFO case study

The First ISCCP Regional Experiment (FIRE) Cirrus Intensive Field Observation (IFO) program measured cirrus cloud properties with a variety of instruments from the surface, aircraft, and satellites. Surface and aircraft observations provide a small scale point and line measurements of different micro- and macro-physical properties of advecting and evolving cloud systems. Satellite radiance data may be used to measure the areal variations of the bulk cloud characteristics over meso- and large scales. Ideally, the detailed cloud properties derived from the small scale measurements should be tied to the bulk cloud properties typically derived from the satellite data. Full linkage of these data sets for a comprehensive description of a given cloud field, one of the goals of FIRE, should lead to significant progress in understanding, measuring, and modeling cirrus cloud systems. The relationships derived from intercomparisons of lidar and satellite data by Minnis et al. are exploited in a mesoscale analysis of the satellite data taken over Wisconsin during the Cirrus IFO case study.

Heck, Patrick W.↗
NASA NTRS2000

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Mocko, David M.↗
NASA NTRS2012

Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have been analyzed

Xue, Yan↗
NASA NTRS2007

Intercomparisons of Aura MLS, ACE, and HALOE Observations of Long-Lived Trace Species Using the Langley Lagrangian Chemistry and Transport Model

We use the LaRC Lagrangian Chemistry and Transport Model (LCTM) [Considine et al., 2007; Pierce et al., 2003] to intercompare ACE, Aura, and HALOE observations of long-lived trace species. The LCTM calculates the transport, mixing, and photochemical evolution of an ensemble of parcels that have been initialized from ACE-FTS measurements. Here we focus on late November, 2004 comparisons, due to the previous 3-week period of continuous HALOE observations and MLS v2.2 data on November 29, 2004.

Considine, David B.↗
DOE OSTI2025

Atmospheric River Detection Under Changing Seasonality and Mean-State Climate: ARTMIP Tier 2 Paleoclimate Experiments

Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single-forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO2 levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean-state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.

Atmospheric river, paleoclimate↗
NASA NTRS2001

Inorganic Chlorine Partitioning in the Summer Lower Stratosphere: Modeled and Measured [ClONO2/HCl] During POLARIS

We examine inorganic chlorine (Cly) partitioning in the summer lower stratosphere using in situ ER-2 aircraft observations made during the Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) campaign. New steady state and numerical models estimate [ClONO2]/[HCl] using currently accepted photochemistry. These models are tightly constrained by observations with OH (parameterized as a function of solar zenith angle) substituting for modeled HO2 chemistry. We find that inorganic chlorine photochemistry alone overestimates observed [ClONO2]/[HCl] by approximately 55-60% at mid and high latitudes. On the basis of POLARIS studies of the inorganic chlorine budget, [ClO]/[ClONO2], and an intercomparison with balloon observations, the most direct explanation for the model-measurement discrepancy in Cly partitioning is an error in the reactions, rate constants, and measured species concentrations linking HCl and ClO (simulated [ClO]/[HCl] too high) in combination with a possible systematic error in the ER-2 ClONO2 measurement (too low). The high precision of our simulation (+/-15% 1-sigma for [ClONO2]/[HCl], which is compared with observations) increases confidence in the observations, photolysis calculations, and laboratory rate constants. These results, along with other findings, should lead to improvements in both the accuracy and precision of stratospheric photochemical models.

Voss, P. B.↗
NASA NTRSDate not supplied

Overview of the SPARC Reanalysis Intercomparison Project (S-RIP) during 2013-2020

The Stratosphere-troposphere Processes And their Role in Climate (SPARC) project is one of the four core projects of the World Climate Research Programme (WCRP). Researchers interested in SPARC use global atmospheric reanalysis products to understand a wide range of processes and variability in the atmosphere, to validate chemistry climate models, and to investigate and identify climate change. The SPARC Reanalysis Intercomparison Project (S-RIP) was initiated in 2011 and officially started in 2013 to conduct a coordinated intercomparison of all major global atmospheric reanalysis data sets. The S-RIP has been aiming at writing up an assessment report in the SPARC report series (to be published by the end of 2020) (1) on overall quality of temperature, winds, ozone, and water vapor data, (2) on more process- and region-oriented evaluation of the Brewer–Dobson circulation, extratropical stratosphere-troposphere coupling, extratropical upper troposphere and lower stratosphere, the tropical tropopause layer, the quasi-biennial oscillation, polar processes, and the upper stratosphere and lower mesosphere, and (3) with a coordinated description of the reanalysis systems. We also have an inter-journal special issue on "The SPARC Reanalysis Intercomparison Project (S-RIP)" in Atmospheric Chemistry and Physics (ACP) and Earth System Science Data (ESSD). In the presentation, we will discuss key findings and recommendations as well as the evaluation of this rst phase of the S-RIP activity.

Masatomo Fujiwara↗
DOE OSTI2021

OpenET: Filling a Critical Data Gap in Water Management for the Western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Assimilation of TES Water Vapor Observations

The Thermal Emission Spectrometer (TES) on the Mars Global Surveyor has made extensive observations of the Martian atmospheric water vapor column since the beginning of its mapping mission in early 1999. The results show broad agreement with the earlier Viking Mars Atmospheric Water Detector (MAWD) results (though column amounts in southern summer are higher, perhaps due to dust obscuration during the Viking mission). General circulation model (GCM) simulations of the annual Martian water cycle also show broad agreement with the TES observations. Details of the simulations depend on cloud and boundary layer parameterizations and on the adsorbing properties of the regolith. In order to make quantitative assessments of this agreement and to obtain observational values for the required physical parameters, a tracer transport data assimilation model has been developed. Model winds are derived from both tracer measurements and retrieved atmospheric temperature structures, providing a useful check of the underlying dynamical core of the GCM. By allowing detailed intercomparison between spacecraft and ground-based observations of Martian water vapor, the model should also contribute significantly to our understanding of the diurnal water cycle.

Houben, Howard↗