Likelihood-Based Climate Model Evaluation
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Pacific Cross-section Intercomparison Project (GPC↗
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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↗
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↗
Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS
The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.
Pawson, Steven↗
Coupled Long-Term Experiment and Model Investigation of the Differential Response of Plants and Soil Microbes in a Changing Permafrost Tundra Ecosystem
The major research goal of this project was to understand and quantify the fate of carbon stored in permafrost ecosystems using a combination of field and laboratory experiments to measure and model isotope ratios and carbon fluxes in a tundra ecosystem exposed to experimental warming. Field measurements centered on a two-factor experimental warming to increase air and soil temperatures alone, and in combination, at a tundra field site in Alaska. A second manipulation of water table was embedded within the warming treatment such that both major environmental factors (temperature, moisture) controlling ecosystem carbon dynamics were experimentally altered. The experiment was interfaced with modeling activities using both data assimilation and forward modeling approaches. Models were used to make forecasts of ecosystem carbon dynamics beyond the time frame and environmental space of the experiment itself. This project was a follow-on to previous work that made use of the same field manipulation; here we continued the experimental manipulation in order to test new hypotheses regarding long-term effects of warming and permafrost thaw and subsequent changes in moisture availability on ecosystem carbon dynamics. These results were linked with ongoing synthesis and model intercomparison activities through the Permafrost Carbon Network, which led to additional synthesis publications as a result of collaboration and data sharing from this project. As key outcomes, this project has produced new papers published in the peer-reviewed literature, archived datasets used for model-data intercomparisons, trained graduate students and postdoctoral researchers, and has raised awareness about the vulnerability of permafrost carbon to a wider audience.
54 ENVIRONMENTAL SCIENCES↗
Quantifying Food Security and Mitigation Risks Consequential to Climate Change Impacts on Crop Yields
Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the Integrated Model to Assess the Global Environment integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as agriculture, forestry and other land use emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.
crop yields↗
Soil Surface Runoff Scheme for Improving Land-Hydrology and Surface Fluxes in Simple SiB (SSiB)
Evapotranspiration on land is hard to measure and difficult to simulate. On the scale of a GCM grid, there is large subgrid-scale variability of orography, soil moisture, and vegetation. Our hope is to be able to tune the biophysical constants of vegetation and soil parameters to get the most realistic space-averaged diurnal cycle of evaporation and its climatology. Field experiments such as First ISLSCP Field Experiment (FIFE), Boreal Ecosystem-Atmosphere Study (BOREAS), and LBA help a great deal in improving our evapotranspiration schemes. However, these improvements have to be matched with, and coupled to, consistent improvement in land-hydrology; otherwise, the runoff problems will intrinsically reflect on the soil moisture and evapotranspiration errors. Indeed, a realistic runoff simulation also ensures a reasonable evapotranspiration simulation provided the precipitation forcing is reliable. We have been working on all of the above problems to improve the simulated hydrologic cycle. Through our participation in the evaluation and intercomparison of land-models under the behest of Global Soil Wetness Project (GSWP), we identified a few problems with Simple SiB (SSIB; Xue et al., 1991) hydrology in regions of significant snowmelt. Sud and Mocko (1999) show that inclusion of a separate snowpack model, with its own energy budget and fluxes with the atmosphere aloft and soil beneath, helps to ameliorate some of the deficiencies of delayed snowmelt and excessive spring season runoff. Thus, much more realistic timing of melt water generation was simulated with the new snowpack model in the subsequent GSWP re-evaluations using 2 years of ISLSCP Initiative I forcing data for 1987 and 1988. However, we noted an overcorrection of the low meltwater infiltration of SSiB. While the improvement in snowmelt timing was found everywhere, the snowmelt infiltration has became excessive in some regions, e.g., Lena river basin. This leads to much reduced runoff in many basins as compared to observations. We believe this is a consequence of neglect of the influence of subgrid-scale variations in orography that affects the production of surface runoff.
Sud, Y. C.↗
Intercomparison of Global Precipitation Products: The Third Precipitation Intercomparison Project (PIP-3)
A set of global, monthly rainfall products has been intercompared to understand the quality and utility of the estimates. The products include 25 observational (satellite-based), four model and two climatological products. The results of the intercomparison indicate a very large range (factor of two or three) of values when all products are considered. The range of values is reduced considerably when the set of observational products is limited to those considered quasi-standard. The model products do significantly poorer in the tropics, but are competitive with satellite-based fields in mid-latitudes over land. Over ocean, products are compared to frequency of precipitation from ship observations. The evaluation of the observational products point to merged data products (including rain gauge information) as providing the overall best results.
Adler, Robert F.↗
Intercomparison of Global Precipitation Products: The Third Precipitation Intercomparison Project (PIP-3)
A set of global, monthly rainfall products has been intercompared to understand the quality and utility of the estimates. The products include 25 observational (satellite-based), four model and two climatological products. The results of the intercomparison indicate a very large range (factor of two or three) of values when all products are considered. The range of values is reduced considerably when the set of observational products is limited to those considered quasi-standard. The model products do significantly poorer in the tropics, but are competitive with satellite-based fields in mid-latitudes over land. Over ocean, products are compared to frequency of precipitation from ship observations. The evaluation of the observational products point to merged data products (including rain gauge information) as providing the overall best results.
Adler, Robert F.↗
Likelihood-Based Climate Model Evaluation
Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.
climate models↗
CGILS: Results from the First Phase of an International Project to Understand the Physical Mechanisms of Low Cloud Feedbacks in Single Column Models
1] CGILS-the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)-investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the "NESTS" negative cloud feedback and the "SCOPE" positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence-Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations
Single Column Models↗
Bio-Optical Measurement and Modeling of the California Current and Polar Oceans
This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project contract supports in situ ocean optical observations in the California Current, Southern Ocean, Indian Ocean as well as merger of other in situ data sets we have collected on various global cruises supported by separate grants or contracts. The principal goals of our research are to validate standard or experimental products through detailed bio-optical and biogeochemical measurements, and to combine ocean optical observations with advanced radiative transfer modeling to contribute to satellite vicarious radiometric calibration and advanced algorithm development. In collaboration with major oceanographic ship-based observation programs funded by various agencies (CalCOFI, US JGOFS, NOAA AMLR, INDOEX and Japan/East Sea) our SIMBIOS effort has resulted in data from diverse bio-optical provinces. For these global deployments we generate a high-quality, methodologically consistent, data set encompassing a wide-range of oceanic conditions. Global data collected in recent years have been integrated with our on-going CalCOFI database and have been used to evaluate Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithms and to carry out validation studies. The combined database we have assembled now comprises more than 700 stations and includes observations for the clearest oligotrophic waters, highly eutrophic blooms, red-tides and coastal case two conditions. The data has been used to validate water-leaving radiance estimated with SeaWiFS as well as bio optical algorithms for chlorophyll pigments. The comprehensive data is utilized for development of experimental algorithms (e.g., high-low latitude pigment transition, phytoplankton absorption, and cDOM).
Mitchell, B. Greg↗
SAO and Kelvin Waves in the EuroGRIPS GCMS and the UK Meteorological Offices Analyses
This work is an intercomparison of four tropospheric-stratospheric climate models, the Unified Model (UM) of the U.K. Meteorological Office (UKMO), the model of the Free University in Berlin (FUB). the ARPEGE-climat model of the National Center for Meteorological Research (CNRM), and the Extended UGAMP GCM (EUGCM) of the Center for Global Atmospheric Modelling (CGAM), against the UKMO analyses. This comparison has been made in the framework of the "GSM-Reality Intercomparison Project for SPARC" (GRIPS). SPARC (Stratospheric Processes and their Role in Climate) aims are to investigate the effects of the middle atmosphere on climate and the GRIPS purpose is to organized a comprehensive assessment of current Middle Atmosphere-Climate Models (MACMs). The models integrations were made without identical contraints e.g. boundary conditions, incoming solar radiation). All models are able to represent the dominant features of the extratropical circulation. In this paper, the structure of the tropical winds and the strengths of the Kelvin waves are examined. Explanations for the differences exhibited. between the models. as well as between models and analyses, are also proposed. In the analyses a rich spectrum of waves (eastward and westward) is present and contributes to drive the SAO (SemiAnnual Oscillation) and the QBO (Quasi-Biennal Oscillation). The amplitude of the Kelvin waves is close to the one observed in UARS (Upper Atmosphere Research Satellite) data. In agreement with observations, the Kelvin waves generated in the models propagate into the middle atmosphere as wave packets which underlines convective forcing origin. In most models, slow Kelvin waves propagate too high and are hence overestimated in the upper stratosphere and in the mesosphere, except for the UM which is more diffusive. These waves are not sufficient to force realistic westerlies of the QBO or SAO westerly phases. If the SAO is represented by all models only two of them are able to generate westerlies between 10 hPa and 50 hPa. The importance of the role played by subgrided gravity waves is more and more recognized. Actually, the EUGCM which includes a parametrization of gravity waves with a non-zero phase speed is able to simulate. with however some unrealistic features, clear easterly to westerly transitions as well as westerlies downward propagations. Thermal damping is also important in the westerlies forcing in the stratosphere. The model ARPEGE-climat shows more westerlies in the stratosphere than tile other three models probably due to the use of a simplified scheme to predict the ozone distribution in the middle atmosphere.
Amodei, M.↗
Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP)
Anthropogenic climate change is unfolding rapidly, yet its regional manifestation can be obscured by internal variability. A primary goal of climate science is to identify the externally forced climate response from among the noise of internal variability. Separating the forced response from internal variability can be addressed in climate models by using a large ensemble to average over different possible realizations of internal variability. However, with only one realization of the real world, it is a major challenge to isolate the forced response directly in observations. In the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP), contributors used existing and newly developed statistical and machine learning methods to estimate the forced response over 1950–2022 within individual realizations of the climate system. Participants used neural networks, linear inverse models, fingerprinting methods, and low-frequency component analysis, among other approaches. These methods were trained using large ensembles from multiple climate models and then applied to observations. Here, we evaluate method performance within large ensembles and investigate the estimates of the forced response in observations. Our results show that many different types of methods are skillful for estimating the forced response in climate models, though the relative skill of individual methods varies depending on the variable and evaluation metric. Methods with comparable skill in models can give a wide range of estimates of the forced response pattern in observations, illustrating the epistemic uncertainty in forced response estimates. ForceSMIP gives new insights into the forced response in observations, its uncertainty, and methods for its estimation.
Climate attribution↗
Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble
Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.
crop models↗
Low-cost solar array project: Four absolute cavity radiometer (pyrheliometer) intercomparisons at New River, Arizona: Radiometer standards
Four detailed intercomparisons were made for a number of models of cavity-type self-calibrating radiometers (pyrheliometers). Each intercomparison consisted of simultaneous readings of pyrheliometers at 30-second intervals in runs of 10 minutes, with at least 15 runs per intercomparison. Twenty-seven instruments were in at least one intercomparison, and five were in all four. Summarized results and all raw data are provided from the intercomparisons.
Estey, R. S.↗
Are 100 Ensemble Members Enough to Capture the Remote Atmospheric Response to +2°C Arctic Sea Ice Loss?
This study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of +2°C. Using two general circulation models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100 ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the midlatitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean–atmosphere PAMIP experiments are analyzed. Substantial differences in the midlatitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean–atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s t and false discovery rate tests. This is problematic for the multimodel assessment of the response, as some of the spread may be attributed to different model sensitivities whereas it is due to internal variability. Here, we propose a method to overcome this consistency issue that allows for more robust conclusions when only 100 ensemble members are used.
58 GEOSCIENCES↗
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↗