Basis Function Sampling: A New Paradigm for Material Property Computation
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Whitmer, Jonathan K.↗
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Improving Trigger Functions for Convective Parameterization Schemes Using GOAmazon Observations
Using observations from the Green Ocean Amazon (GOAmazon) field campaign, this study aims to improve trigger functions of convection schemes. Results show that the CAPE generation rate (dCAPE)-type triggers are the first tier and that the Bechtold and heated condensation framework (HCF) triggers are a distant second tier. The composite analysis reveals that the undilute dCAPE trigger underpredicts convection when there is bottom-heavy upward motion but overpredicts convection with low-level downward and upper-level upward motions. The empirical orthogonal function (EOF) analysis on vertical velocity shows that EOF1 (62.65%) exhibits upward motion throughout the troposphere and that EOF2 (28.05%) has lower-level upward motion and upper-level downward motion. Both of them have close relationships with precipitation, indicating the role of vertical velocity in triggering convection. The skill sensitivity analysis shows that the inclusion of 700-hPa upward motion significantly enhances the undilute dCAPE trigger. For the dilute dCAPE trigger, entrainment rate and dCAPE threshold are optimized to improve it. Opposite to dCAPE-type triggers, the Bechtold trigger overemphasizes the low-level vertical velocity and underpredicts the mature and decaying phases of long-lasting convection events. The HCF trigger overemphasizes the near-surface moist static energy and overlooks the vertical velocity. The performance of dCAPE-type triggers on various convective systems over the Amazon region is examined. The eastward-propagating systems are best represented, with only a few underpredictions in their decaying stages. The weak locally occurring systems and marginal phases of westward-propagating systems are easy to underpredict. The revised dCAPE-type triggers perform better on different convection systems and the diurnal cycle of convection.
54 ENVIRONMENTAL SCIENCES↗
Eigenvector analysis of some observed and model-generated Climatological fields
An empirical orthogonal function analysis of monthly mean synoptic fields computed with a general circulation model and the corresponding observed climatological patterns is presented. A computer program was used to compute the principal components of the data matrices representing global maps of various observed and model-generated climatological fields. The variables analyzed were: 500mb geopotential height, 850 mb temperature, and sea level pressure. It is concluded that eigenvector analysis of observed and model-generated synoptic climatological fields is a useful diagnostic aid in the evaluation of global model simulation. The maps of any climatological variables are readily decomposed into a few orthogonal components which account for a large fraction of the total spatial variance, and the observed and model-generated patterns may then be compared in terms of these principal components of the original data matrices.
Dennis, M.↗
An EOF Iteration Approach for Obtaining Homogeneous Radiative Fluxes from Satellites Observations
Conventional observations of climate parameters are sparse in space and/or in time and the representativeness of such information needs to be optimized. Observations from satellites provide improved spatial coverage than point observations however they pose new challenges for obtaining homogeneous coverage. Surface radiative fluxes, the forcing functions of the hydrologic cycle and biogeophysical processes, are now becoming available from global scale satellite observations. They are derived from independent satellite platforms and sensors that differ in temporal and spatial resolution and in the size of the footprint from which information is derived. Data gaps, degraded spatial resolution near boundaries of geostationary satellites, and different viewing geometries in areas of satellite overlap, could result in biased estimates of radiative fluxes. In this study, discussed will be issues related to the sources of inhomogeneity in surface radiative fluxes as derived from satellites; development of an approach to obtain homogeneous data sets; and application of the methodology to the widely used International Satellite Cloud Climatology Project (ISCCP) data that currently serve as a source of information for deriving estimates of surface and top of the atmosphere radiative fluxes. Introduced is an Empirical Orthogonal Function (EOF) iteration scheme for homogenizing the fluxes. The scheme is evaluated in several ways including comparison of the inferred radiative fluxes against ground observations, both before and after the EOF approach is applied. On the average, the latter reduces the rms error by about 2-3 W/m2.
Zhang, Banglin↗
RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers
RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.
Figueroa-Vinas, Adolfo↗
A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties
This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.
54 ENVIRONMENTAL SCIENCES↗
Evaluation of atmospheric precipitable water from reanalysis products using homogenized radiosonde observations over China
Many multidecadal atmospheric reanalysis products are available now, but their consistencies and reliability are far from perfect. In this work, atmospheric precipitable water (PW) from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), NCEP/Department of Energy (DOE), Modern Era Retrospective-Analysis for Research and Applications (MERRA), Japanese 55 year Reanalysis (JRA-55), JRA-25, ERA-Interim, ERA-40, Climate Forecast System Reanalysis (CFSR), and 20th Century Reanalysis version 2 is evaluated against homogenized radiosonde observations over China during 1979–2012 (1979–2001 for ERA-40). Results suggest that the PW biases in the reanalyses are within ~20% for most of northern and eastern China, but the reanalyses underestimate the observed PW by 20%–40% over western China and by ~60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR, and ERA-Interim) have smaller root-mean-sq uare error than the older-generation ones (NCEP/NCAR, NCEP/DOE, and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China. However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis relative humidity fields in the middle-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. An empirical orthogonal function (EOF) analysis revealed two leading modes that represent the long-term PW changes and El Niño–Southern Oscillation-related interannual variations with robust spatial patterns. The reanalysis products, especially the MERRA and JRA-25, roughly capture these EOF modes, which acco unt for over 50% of the total variance. The results show that even during the post-1979 satellite era, discontinuities in radiosonde data can still induce large spurious long-term changes in reanalysis PW and other related fields. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanalyses.
54 ENVIRONMENTAL SCIENCES↗
Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration
The sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global-scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger-scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS-like events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP-CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS-like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five-summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one-moment and two-moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP-GCMs. Furthermore, these results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.
54 ENVIRONMENTAL SCIENCES↗
Relationships among climatological vertical moisture structure, column water vapor, and precipitation over the central Amazon in observations and CMIP5 models
Bias and spread in Coupled Model Intercomparison Project Phase 5 simulated vertical specific humidity (q) structure are examined and related to both precipitation and column water vapor (cwv) near Manaus, Brazil, site of the recent Green Ocean Amazon campaign. Simulated seasonal mean q profiles are typically too dry, especially at low levels and during the local dry season, consistent with previously identified surface hydroclimate biases in the Amazon. Multimodel empirical orthogonal function analysis of the models' monthly climatological q profiles indicates two significant modes of ensemble spread in moisture vertical structure, with the leading mode peaked at low levels and the second mode in the lower free troposphere (LFT). While both modes project onto simulated cwv spread, only the first projects on precipitation, suggesting inconsistent sensitivity of simulated rainfall to LFT moisture. Finally, relative to observations, models with high cwv and low-level moisture errors tend to exhibit high precipitation error.
54 ENVIRONMENTAL SCIENCES↗
Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA
This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation, the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.
EASM↗
Concurrent Inter-Model Spread of Boreal Winter Westerly Jet Meridional Positions Between the Northern and Southern Hemispheres in CMIP6 Models
Here, this study investigates the inter-model spread of climatological extratropical westerly jets in boreal winter, using the historical simulation of 52 Coupled Model Intercomparison Project phase 6 (CMIP6) models from 1851 to 2014. The results show that there is a substantial spread in the latitude of the upper-tropospheric westerly jet across models, characterised by large inter-model standard deviations to both the poleward and equatorward sides of the jet axis, although the multi-model ensemble mean (MME) performs well in simulating meridional position of westerly jets. Furthermore, we detect the consistency of inter-model jet position spread between the Northern and Southern Hemispheres, based on the inter-model empirical orthogonal function (EOF) decomposition and correlation of regional-averaged zonal winds. Specifically, the models that simulate the westerly jets poleward/equatorward relative to the MME position in one hemisphere also tend to simulate the jets poleward/equatorward in the other hemisphere. Accordingly, we define a global jet spread index to depict the concurrence of jet shift in the two hemispheres. The results of inter-model regression analyses based on this index indicate that the models positioning the jets poleward than the MME tend to simulate a wider Hadley Cell, a poleward-shifted Ferrel Cell in the Southern Hemisphere, enhanced precipitation in the subtropics and suppressed precipitation in the tropics, and warmer sea surface temperatures in the subtropics and mid-latitudes. The present results suggest that improving the simulation of jet positions in climate models requires a comprehensive consideration of thermal states in the tropics and subtropics/mid latitudes.
54 ENVIRONMENTAL SCIENCES↗
West African monsoon decadal variability and surface-related forcings: second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II)
The Sahel climate system had experienced one of the strongest interdecadal climate variabilities and the longest drought on the planet in the twentieth century. Most modeling studies on the decadal variability of the Sahel climate so far have focused on the role of anomalies in either sea surface temperature (SST), land surface processes, or aerosols concentration. The Second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedback of SST, land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The WAMME II strategy is to apply observationally based anomaly forcing, i.e., “idealized but realistic” forcing, in simulations by general circulation models’ (GCMs) and regional climate models’ (RCMs) to test the relative impacts of such forcings in producing/amplifying the Sahelian seasonal and decadal climate variability, including the 20th century drought. To test individual ocean’s SST effect, a special approach in the experimental design is taken to avoid undermine its effect. This is the first multi-model experiment specifically designed to simultaneously evaluate relative contributions of multiple-external forcings to the Sahel drought. This paper presents the major results and preliminary findings of the WAMME II SST experiment, including each ocean’s contribution to the global SST effect, as well as comparison of the SST effect with the LULCC effect. The common empirical orthogonal functions and other analyses are applied to assess and comprehend the discrepancies among the models. In general, the WAMME II models have reached a consensus on SST’s major contribution to the great Sahel drought and show that with the maximum possible SST forcing, it can produce up to 60% of the absolute amount of precipitation difference between the 1980s and the 1950s. This paper has 3 also delineated the role of SSTs in triggering and maintaining the Sahel drought, suggesting a potential predictability of WAM development linked to SST. Among different ocean basins, the Pacific and Indian Ocean SSTs have the greatest impact on the 1980s drought. The WAMME II, however, fails to reach a consensus on the role of the Mediterranean Sea SST. The changes in circulation, moisture flux convergence, and associated surface energy balances are the main mechanisms for the SST effect. The paper also compares the SST effect with the LULCC effects. It is shown that the prescribed land forcing produces about 40% of the precipitation difference between the 1980s and the 1950s, which is less than SST contribution but still of first order in the Sahel climate system. The role of land surface processes in responding to and amplifying the drought has also been identified. The results demonstrate that catastrophic consequences likely occur in the regional climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. Due to limited ensemble members, aerosol effects are not compared. Since the SST and land forcing in the real world are likely smaller than specified in this study, further investigations on the effects of aerosols as well as of other external forcings, such as greenhouse gases, and of atmospheric internal variability, are necessary. Moreover, although the WAMEE II models support a general consensus on SST and LULCC effects, there are still large discrepancies in how these models produce the Sahel drought in the 1980s. Better atmospheric observational and analysis data including more processes and components are necessary to validate and constrain models, and to guide further model development and improvement.
Xue, Yongkang (ORCID:0000000261699631)↗
Global teleconnections influencing large-scale drought in the United States using SVDI
Understanding recent large-scale drought patterns and the mechanisms producing extreme drought events is vital for future drought forecasts and understanding future drought risks. Increasingly, vapor pressure deficit (VPD) has been used as an important measure of evaporative demand and proxy for drought detection. In this study, VPD is used to calculate the new Standardized VPD Drought Index (SVDI) with NASA North American Land Data Assimilation System (NLDAS) data. Previous studies have shown that SVDI accurately identifies the timing and magnitude short-term droughts in the United States (U.S). In the present study, SVDI is now used to identify large-scale drought patterns between 1980 and 2021 and drought variability driven by selected global teleconnections originating in the Pacific and Atlantic Oceans. Spatial drought characteristics were extracted from SVDI using empirical orthogonal function (EOF) analysis. Then a k-means clustering algorithm was applied to both EOF principal components and primary teleconnections, including the El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) to identify drought events driven by the Pacific Ocean. Results show that the SVDI is useful in evaluating large-scale drought variability in the U.S. related to global teleconnections, and that mechanisms influencing summer drought patterns in the Western and Southwestern U.S. are driven by a tropical-extratropical interactions originating in the equatorial Pacific Ocean related to ENSO dynamics with interdecadal variability modulated by PDO. The large-scale droughts in the Central and Southern U.S., like those in 2011 and 2012, on the other hand, are driven by the North Pacific Ocean warm pool during a strong negative PDO, which subsequently influenced variability in the Bermuda-Azores High in the Atlantic Ocean. In summer 2011, the Bermuda-Azores High weakened, reducing the onshore winds and moisture transport along the eastern Gulf of Mexico and contributing to ongoing drought in the region. The Northern Pacific and Atlantic Ocean sea surface temperatures (SSTs) have increased between 1980 and 2021. In conclusion, as SSTs continue to rise in the Northern Pacific Ocean, one consequence of the coupled North Pacific warm pool and atmospheric dynamics, is to increase summer drought variability over a large region in the southern and midwestern U.S. under global warming.
54 ENVIRONMENTAL SCIENCES↗
Numerical Analysis of Offshore Wind-Farm-Induced Drag Effects on Coastal Upwelling Dynamics
Wind farms extract momentum from the atmospheric flow, generating wind-speed deficits both within the plant, and extending downstream. When located offshore, these deficits modulate air-sea coupling, potentially impacting coastal upwelling in sensitive regions. We investigate impacts of wind farms on coastal upwelling using kilometre-scale, three-way-coupled simulations with the coupled ocean-atmosphere-wave-sediment transport system for the US West Coast. Wind-farm effects are represented by a generalised turbine drag formulation, an idealised, height-dependent body force whose magnitude is systematically varied. This approach isolates the leading-order fluid-dynamical response in a realistic coastal configuration. The atmospheric adjustment exhibits an approximately linear relation between drag force and wind-speed deficit, with wakes that expand downstream and increase in magnitude as drag increases. An empirical orthogonal function analysis of sea-surface-temperature anomalies reveals the emergence of a canonical dipole pattern under strong drag forcing. Subsurface diagnostics show consistent shoaling of the mixed layer and suppressed upward velocities in areas near wind-farm region, accompanied by compensating enhancements of shoaling closer to the coast. These results identify turbine drag as a control parameter in assessing interactions between wind-farm wake and coastal upwelling and provide scaling relationships for understanding offshore wind-farm effects on the coastal circulation dynamics.
16 TIDAL AND WAVE POWER↗
Compartmentalization of Incompatible Catalytic Transformations for Tandem Catalysis
In Nature, incompatible catalytic transformations are being carried out simultaneously through compartmentalization that allows for the combination of incompatible catalysts in tandem reactions. Herein, we take the compartmentalization concept to the synthetic realm and present an approach that allows two incompatible transition metal catalyzed transformations to proceed in one pot in tandem. The key is the site isolation of both catalysts through compartmentalization using a core-shell micellar support in an aqueous environment. The support is based on amphiphilic triblock copolymers of poly(2-oxazoline)s with orthogonal functional groups on the side-chain that can be used to crosslink covalently the micelle and to conjugate two metal catalysts in different domains of the micelle. Here, the micelle core and shell provide different microenvironments for the transformations: Co-catalyzed hydration of an alkyne proceeds in the hydrophobic core while the Rh-catalyzed asymmetric transfer hydrogenation of the intermediate ketone into a chiral alcohol occurs in the hydrophilic shell.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Spatial Patterns and Trends of Summertime Low Cloudiness for the Pacific Northwest, 1996–2017
Summertime low clouds are common in the Pacific Northwest (PNW), but spatiotemporal patterns have not been characterized. We show the first maps of low cloudiness for the western PNW and North Pacific Ocean using a 22-year satellite-derived record of monthly mean low cloudiness frequency for May through September and supplemented by airport cloud base height observations. Domain-wide cloudiness peaks in midsummer and is strongest over the Pacific. Empirical orthogonal function (EOF) analysis identified four distinct PNW spatiotemporal modes: oceanic, terrestrial highlands, coastal, and northern coastal. There is a statistically significant trend over the 22-year record toward reduced low cloudiness in the terrestrial highlands mode, with strongest declines in May and June; however, this decline is not matched in the corresponding airport records. The coastal mode is partly constrained from moving inland by topographic relief and migrates southward in late summer, retaining higher late-season low cloud frequency than the other areas.
54 ENVIRONMENTAL SCIENCES↗
The Impact of Inherited Morphology on Sandbar Migration During Mild Wave Seasons
Sandbars are ubiquitous morphologic features found in the nearshore environment throughout the world, yet predictive capabilities of their evolution remain limited. In order to provide new insights on the relevant processes controlling sandbar morphodynamics, this study uses a 41-year record of 637 monthly cross-shore profiles from Duck, North Carolina, USA, to derive complex empirical orthogonal functions representative of the two dominant modes of sandbar migrations: offshore and onshore propagation. Interference of these two modes produces commonly observed sandbar states. While mild wave energies are traditionally assumed to drive onshore sandbar migration, the offshore mode is repeatedly seen to dominate sandbar migration in mild wave seasons following anomalously high late-winter wave energy and when the inherited morphology is composed of a single bar or terrace, as opposed to a more common two-bar state. A data-derived conceptual model is presented synthesizing the effect of antecedent morphology and wave climate chronology on interannual trends in net offshore sandbar migration.
58 GEOSCIENCES↗
Evaluation of CMIP6 GCMs Over the CONUS for Downscaling Studies
Despite the necessity of Global Climate Models (GCMs) sub-selection in downscaling studies, an objective approach for their selection is currently lacking. Building on the previously established concepts in GCMs evaluation frameworks, we develop a weighted averaging technique to remove the redundancy in the evaluation criteria and rank 37 GCMs from the sixth phase of the Coupled Models Intercomparison Project over the contiguous United States. GCMs are rated based on their average performance across 66 evaluation measures in the historical period (1981–2014) after each metric is weighted between zero and one, depending on its uniqueness. The robustness of the outcome is tested by repeating the process with the empirical orthogonal function analysis in which each GCM is ranked based on its sum of distances from the reference in the principal component space. The two methodologies work in contrasting ways to remove the metrics redundancy but eventually develop similar GCMs rankings. A disparity in GCMs' behavior related to their sensitivity to the size of the evaluation suite is observed, highlighting the need for comprehensive multi-variable GCMs evaluation at varying timescales for determining their skillfulness over a region. The sub-selection goal is to use a representative set of skillful models over the region of interest without substantial overlap in their future climate responses and modeling errors in representing historical climate. Additional analyses of GCMs' independence and spread in their future projections provide the necessary information to objectively select GCMs while keeping all aspects of necessity in view.
54 ENVIRONMENTAL SCIENCES↗