Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)
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54 ENVIRONMENTAL SCIENCES↗
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Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)
Explore the source record for details and available documents.
54 ENVIRONMENTAL SCIENCES↗
Field test to intercompare carbon monoxide, nitric oxide and hydroxyl instrumentation at Wallops Island, Virginia
Documentation of the first of three instrument intercomparisons conducted as part of NASA Global Tropospheric Experiment/Chemical Instrumentation Test and Evaluation (GTE/CITE-1) is given. This ground-based intercomparison was conducted during July 1983 at NASA Wallops Flight Facility. Instruments intercompared included one laser system and three grab-sample approaches for CO; two chemiluminescent systems and one laser-induced fluorescent (LIF) technique for NO; and two different LIF systems and a radiochemical tracer technique for OH. The major objectives of this intercomparison was to intercompare ambient measurements of CO, NO, and OH at a common site by using techniques of fundamentally different detection principles and to identify any major biases among the techniques prior to intercomparison on an aircraft platform. Included in the report are comprehensive discussions of workshop requirements, philosophies, and operations as well as intercomparison analyses and results. In addition, the large body of nonintercomparison data incorporated into the workshop measurements is summarized. The report is an important source document for those interested in conducting similar large and complex intercomparison tests as well as those interested in using the data base for purposes other than instrument intercomparison.
Gregory, Gerald L.↗
Ringberg15: Earth's Climate Sensitivities
To assess gaps in understanding of Earth's climate sensitivities a workshop was organised under the auspices of the WCRP (World Climate Research Programme) Grand Science Challenge on Clouds, Circulation and Climate Sensitivity (Ringberg15). The workshop took place in March 2015 and gathered together over thirty experts from around the world for one week. Attendees each gave short presentations and participated in moderated discussions of specific questions related to understanding Earth's climate sensitivities. Most of the time was focused on understanding of the equilibrium climate sensitivity, defined as the equilibrium near-surface warming associated with a doubling of atmospheric carbon dioxide. The workshop produced nine recommendations, many of them focusing on specific research avenues that could be exploited to advance understanding of climate sensitivity. Many of these dealt, in one fashion or another, with the need to more sharply focus research on identifying and testing story lines for a high (larger than 4 degrees Kelvin) or low (less than 2 degrees Kelvin) equilibrium climate sensitivity. Additionally, a subset of model intercomparison projects (CFMIP (Cloud Feedback Model Intercomparison Project), PMIP (Palaeoclimate Modelling Intercomparison Project), PDRMIP (Precipitation Driver and Response Model Intercomparison Project), RFMIP (Radiative Forcing Model Intercomparison Project) and VolMIP (Volcanic Forcings Model Intercomparison Project)) that have been proposed for inclusion within CMIP were identified as being central to resolving important issues raised at the workshop; for this reason modelling groups were strongly encouraged to participate in these projects. Finally the workshop participants encouraged the WCRP to initiate and support an assessment process lead by the Grand Science Challenge on Clouds, Circulation and Climate Sensitivity on the topic of Earth's Climate Sensitivities, culminating in a report that will be published in 2019, forty years after the seminal report by Charney and co-authors.
Sensitivity↗
The PMIP4 Contribution to CMIP6 - Part 1: Overview and Over-Arching Analysis Plan
This paper is the first of a series of four GMD (Geoscientific Model Development) papers on the PMIP4-CMIP6 (Paleoclimate Modelling Intercomparison Project - Phase 4 -- Coupled Model Intercomparison Project - Phase 6) experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016). The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21,000 years ago (lgm); the Last Interglacial, 127,000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.
climate↗
Machine Learning Emulators and Empirical Models Combining Climate and Global Crop Models for Seasonal Agricultural Production
We present results from several connected efforts to apply machine learning methods to estimates of seasonal agricultural production anomalies around the world. First, we apply the XGBoost Random Forest method to fit emulators that mimic global crop models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI). These are the same models used in the agricultural sector simulations of the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). These emulators use 8 climate variables split across 5 sub-seasonal representations of the growing season for each ½ degree grid cell around the world for maize, wheat, rice and soybeans. Emulators are useful for estimating conditions that have not already been simulated by GGCMI (e.g., in a seasonal prediction model) and also to diagnose model differences and capabilities. For example, emulators of the pDSSAT maize model tend to be more reliant on mean temperatures than the LPJmL model, and few models have strong responses to cold extremes. Second, we use a similar XGBoost approach to fit empirical models for national production data for the top 20 producing countries according to the United Nations Food and Agricultural Organization (FAO). Models utilize both climate observations and the GGCM models as predictors, resulting in skillful models for many (but not all) top producing-countries. The patterns of climate and crop model features selected indicate regions and systems that are better or worse simulated by the GGCMs. For example, information in cold extreme predictors is often combined with GGCM output predictors to provide sensitivity that models may underrepresent.
machine learning↗
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↗
A Comparison of Aircraft and Ground-Based Measurements at Mauna Loa Observatory, Hawaii, During GTE PEM-West and MLOPEX 2
During October 19-20, 1991, one flight of the NASA Global Tropospheric Experiment (GTE) Pacific Exploratory Mission (PEM-West A) mission was conducted near Hawaii as an intercomparison with ground-based measurements of the Mauna Loa Observatory Photochemistry Experiment (MLOPEX 2) and the NOAA Climate Modeling and Diagnostics Laboratory (CMDL). Ozone, reactive nitrogen species, peroxides, hydrocarbons, and halogenated hydrocarbons were measured by investigators aboard the DC-8 aircraft and at the ground site. Lidar cross sections of ozone revealed a complex air mass structure near the island of Hawaii which was evidenced by large variation in some trace gas mixing ratios. This variation limited the time and spatial scales for direct measurement intercomparisons. Where differences occurred between measurements in the same air masses, the intercomparison suggested that biases for some trace gases was due to different calibration scales or, in some cases, instrumental or sampling biases. Relatively large uncertainties were associated with those trace gases present in the low parts per trillion by volume range. Trace gas correlations were used to expand the scope of the intercomparison to identify consistent trends between the different data sets.
Atlas, E.↗
Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling
With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.
Coastal ocean color↗
initMIP-Antarctica: an Ice Sheet Model Initialization Experiment of ISMIP6
Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.
ice sheet model↗
Implementation and Exploration of Parameterizations of Large-Scale Dynamics in NCAR's Single Column Atmosphere Model SCAM6
A single column model with parameterized large-scale (LS) dynamics is used to better understand the response of steady-state tropical precipitation to relative sea surface temperature under various representations of radiation, convection, and circulation. The large-scale dynamics are parametrized via the weak temperature gradient (WTG), damped gravity wave (DGW), and spectral weak temperature gradient (Spectral WTG) method in NCAR's Single Column Atmosphere Model (SCAM6). Radiative cooling is either specified or interactive, and the convective parameterization is run using two different values of a parameter that controls the degree of convective inhibition. Results are interpreted in the context of the Global Atmospheric System Studies -Weak Temperature Gradient (GASS-WTG) Intercomparison project. Using the same parameter settings and simulation configuration as in the GASS-WTG Intercomparison project, SCAM6 under the WTG and DGW methods produces erratic results, suggestive of numerical instability. However, when key parameters are changed to weaken the large-scale circulation's damping of tropospheric temperature variations, SCAM6 performs comparably to single column models in the GASS-WTG Intercomparison project. The Spectral WTG method is less sensitive to changes in convection and radiation than are the other two methods, performing qualitatively similarly across all configurations considered. Under all three methods, circulation strength, represented in 1D by grid-scale vertical velocity, is decreased when barriers to convection are reduced. This effect is most extreme under specified radiative cooling, and is shown to come from increased static stability in the column's reference radiative-convective equilibrium profile. This argument can be extended to interactive radiation cases as well, though perhaps less conclusively.
54 ENVIRONMENTAL SCIENCES↗
Climate impacts in scenarios: time to close the loop?
Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.
Tebaldi, Claudia↗
CONUS-wide Projected Flood Frequency and Uncertainty Estimates, Version 1.0
This dataset presents a large-ensemble of CONUS-wide projected flood frequency and uncertainty estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequences at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency and uncertainty estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates that allow for the comparison between local and regional approach-based estimates, assess projected changes, and characterize their uncertainties. For more reliable estimation of rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assests" project for the US Department of Energy (DOE) Hydropower and Hydrokinetic Office (H2O). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), Ghimire et al. (2025), and Hosking and Wallis (1997).
Ghimire, Ganesh [ORNL] (ORCID:0000000242843941)↗
An intercalibration of Meteosat-1 and GOES-2 visible and infrared measurements
An intercomparison between radiative parameters determined from visible and infrared channels of the Meteosat-1 and GOES-2 geosynchronous satellites has been carried out using data obtained over the central Atlantic Ocean for 5 November 1978. Hourly visible-infrared measurement pairs at a nominal resolution of 5 km (Meteosat) or 8 km (GOES) have been stored in 1 deg x 1 deg longitude-latitude regions. For the infrared intercomparisons, the GOES 11.5 micron radiance has been compared to Meteosat infrared counts. The scatter in partly cloudy regions is interpreted as being caused by meteorological differences arising from differences in measurement time between the two data sets. For the visible intercomparison, the GOES measurements for clear and cloudy scenes have first been converted with the aid of scene-dependent angular reflectance and albedo models to estimates of the filtered shortwave radiance that GOES would have measured had it been in the Meteosat position. This value has then been compared to Meteosat counts for the shortwave channel. The results indicate that earlier Meteosat calibrations made from airplane overflights of a limited variety of surfaces are applicable to much larger areas of cloud and ocean.
Brooks, D. R.↗
Millimeter-wave ozone measurements for the network for the detection of stratospheric change
The primary research objective is to initiate long-term monitoring of stratospheric ozone with a ground-based millimeter-wave spectrometer, the first of several such instruments projected to be part of the Network for the Detection of Stratospheric Change. The ultimate goal of this monitoring is twofold. First, to detect any secular trend in stratospheric ozone abundance, whether of natural or anthropogenic origin and, second, to provide ground-truth validation for existing and future satellite measurements of ozone. With this goal in mind, a more immediate objective is to validate the millimeter-wave measurements by tests of the instrument, internal consistency tests on the data, and most importantly, by intercomparison with all other available ozone measurements. The validation process is expected to lead to refinements in the instrument and its operating procedures and in the data analysis. The final objective is to perform short-term scientific studies with the data, including studies of the ozone diurnal and seasonal variations, and comparison of ozone variations with changes in other geophysical parameters, notably temperature and water vapor. Routine observations are now ongoing; these will allow continuing intercomparisons with the Stratospheric Aerosol and Gas Experiment (SAGE II) and one of the lidars, which is permanently on site. The experience gained during the Stratospheric Ozone Intercomparison (STOIC) caused us to refine our calibration procedures and identify the need for internal shielding of the millimeter receiver from radio frequency interference. Installation of this shielding is planned for the near future and should allow improvements in the instrument calibration and a higher signal-to-noise ratio, both of which will result in improved measurement precision.
Connor, Brian J.↗
The Fifth Calibration/Data Product Validation Panel Meeting
The minutes and associated documents prepared from presentations and meetings at the Fifth Calibration/Data Product Validation Panel meeting in Boulder, Colorado, April 8 - 10, 1992, are presented. Key issues include (1) statistical characterization of data sets: finding statistics that characterize key attributes of the data sets, and defining ways to characterize the comparisons among data sets; (2) selection of specific intercomparison exercises: selecting characteristic spatial and temporal regions for intercomparisons, and impact of validation exercises on the logistics of current and planned field campaigns and model runs; and (3) preparation of data sets for intercomparisons: characterization of assumptions, transportable data formats, labeling data files, content of data sets, and data storage and distribution (EOSDIS interface).
Source record↗
Metafitting: Weight optimization for least-squares fitting of PTTI data
For precise time intercomparisons between a master frequency standard and a slave time scale, we have found it useful to quantitatively compare different fitting strategies by examining the standard uncertainty in time or average frequency. It is particularly useful when designing procedures which use intermittent intercomparisons, with some parameterized fit used to interpolate or extrapolate from the calibrating intercomparisons. We use the term 'metafitting' for the choices that are made before a fitting procedure is operationally adopted. We present methods for calculating the standard uncertainty for general, weighted least-squares fits and a method for optimizing these weights for a general noise model suitable for many PTTI applications. We present the results of the metafitting of procedures for the use of a regular schedule of (hypothetical) high-accuracy frequency calibration of a maser time scale. We have identified a cumulative series of improvements that give a significant reduction of the expected standard uncertainty, compared to the simplest procedure of resetting the maser synthesizer after each calibration. The metafitting improvements presented include the optimum choice of weights for the calibration runs, optimized over a period of a week or 10 days.
Douglas, Rob J.↗
An Overview of Measurement Comparisons from the INTEX-B/MILAGRO Airborne Field Campaign
As part of the NASA's INTEX-B mission, the NASA DC-8 and NSF C-130 conducted three wing-tip to wing-tip comparison flights. The intercomparison flights sampled a variety of atmospheric conditions (polluted urban, non-polluted, marine boundary layer, clean and polluted free troposphere). These comparisons form a basis to establish data consistency, but also should also be viewed as a continuation of efforts aiming to better understand and reduce measurement differences as identified in earlier field intercomparison exercises. This paper provides a comprehensive overview of 140 intercomparisons of data collected as well as a record of the measurement consistency demonstrated during INTEX-B. It is the primary goal to provide necessary information for the future research to determine if the observations from different INTEX-B platforms/instrument are consistent within the PI reported uncertainties and used in integrated analysis. This paper may also contribute to the formulation strategy for future instrument developments. For interpretation and most effective use of these results, the reader is strongly urged to consult with the instrument principle investigator.
Kleb, Mary M.↗