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Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗

1DVAR Analysis of Temperature and Humidity Using GPS Radio Occultation Data

The Global Positioning System enables positioning in 3 dimensions about our planet. It has been operational since 1994. Twenty-four satellites are used to aclile\,e this performance. The signals sent by these satellites are electromagnetic waves travelling through our atmosphere down to the small receivers used by the civilian community and the military. Because of varying meteorological conditions (namely, temperature and humidity changes along the ray path), the rays do not travel in a straight line. They bend towards the surface. As a consequence, the ray path between two points is longer than a straight line, and the time it takes for a signal to travel this distance is longer. In 1995, a small GPS receiver was launched on a satellite (GPS/MET). It become possible to perform radio occultations around the Earth: the source - one of the 24 GPS satellites - is seen by the receiver as it rises or sets around the other side of the Earth. When the source disappears, the receiver progressively loses the signals. By measuring accurately the time delay between the emission and the reception of the signal, it is possible to infer which part of the delay is due to the atmosphere. We use GPS/MET data to retrieve temperature and humidity profiles simultaneously. A specific method is implemented: it combines information from numerical forecasts and GPS observations in an optimal way. Comparing the result with an independent source of observations (weather balloons), we demonstrate that GPS data have the potential to improve weather analyses. We also show that improved temperature and humidity profiles can be obtained using information from a forecast model. This confirms results obtained in this study using simulated data.

Poli, Paul↗

Evaluation of a Cloud Resolving Model Using TRMM Observations for Multiscale Modeling Applications

The climate change simulation community is moving toward use of global cloud resolving models (CRMs), however, current computational resources are not sufficient to run global CRMs over the hundreds of years necessary to produce climate change estimates. As an intermediate step between conventional general circulation models (GCMs) and global CRMs, many climate analysis centers are embedding a CRM in each grid cell of a conventional GCM. These Multiscale Modeling Frameworks (MMFs) represent a theoretical advance over the use of conventional GCM cloud and convection parameterizations, but have been shown to exhibit an overproduction of precipitation in the tropics during the northern hemisphere summer. In this study, simulations of clouds, precipitation, and radiation over the South China Sea using the CRM component of the NASA Goddard MMF are evaluated using retrievals derived from the instruments aboard the Tropical Rainfall Measuring Mission (TRMM) satellite platform for a 46-day time period that spans 5 May - 20 June 1998. The NASA Goddard Cumulus Ensemble (GCE) model is forced with observed largescale forcing derived from soundings taken during the intensive observing period of the South China Sea Monsoon Experiment. It is found that the GCE configuration used in the NASA Goddard MMF responds too vigorously to the imposed large-scale forcing, accumulating too much moisture and producing too much cloud cover during convective phases, and overdrying the atmosphere and suppressing clouds during monsoon break periods. Sensitivity experiments reveal that changes to ice cloud microphysical parameters have a relatively large effect on simulated clouds, precipitation, and radiation, while changes to grid spacing and domain length have little effect on simulation results. The results motivate a more detailed and quantitative exploration of the sources and magnitude of the uncertainty associated with specified cloud microphysical parameters in the CRM components of MMFs.

Posselt, Derek J.↗

Geophysical Retrievals and Cloud Analyses from Merged Airborne Radiometer Datasets Covering 10–684 GHz

Airborne microwave radiometers provide insight about numerous aspects of Earth’s atmosphere and yield critical validation datasets for spaceborne radiometers. Three radiometers that are important to NASA’s airborne remote-sensing arsenal include: the Advanced Microwave Precipitation Radiometer (AMPR), covering 10–85 GHz; the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR), covering 50–183 GHz; and the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR), covering 170–684 GHz. The NASA field campaigns of interest to this study include: the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014, the Olympic Mountains Experiment and Radar Definition Experiment (OLYMPEX/RADEX) in 2015–2016, the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) in 2020–2023, and the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) in 2023. To provide a more comprehensive perspective on clouds and precipitation observed during these airborne field campaigns, AMPR data were merged spatiotemporally with CoSMIR data for IPHEx, OLYMPEX/RADEX, and IMPACTS (2020 and 2022), while considering differences in instrument characteristics and operations, providing brightness temperature (Tb) values from 10–183 GHz in a common background grid throughout each flight. AMPR and CoSSIR data were similarly merged for IMPACTS (2023) and ALOFT, providing a common background grid with Tb values covering 10–684 GHz throughout each flight. These merged Tb data were employed in geophysical retrievals using the Community Radiative Transfer Model (CRTM), an Eddington radiative transfer model, and a one-dimensional variational (1DVAR) inversion method. Retrievals of cloud liquid water path were of primary interest. This presentation will include an overview of the methods for the radiometer data mergers, the radiative transfer methods, the geophysical retrievals, and detailed results from examining trends in Tb and cloud liquid water path in clouds, precipitation, and cloud-to-precipitation transition zones.

Corey G Amiot↗

Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling

This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.

54 ENVIRONMENTAL SCIENCES↗

Biodiversity and Stoichiometric Plasticity Increase Pico‐Phytoplankton Contributions to Marine Net Primary Productivity and the Biological Pump

Earth System Models generally predict increasing upper ocean stratification from 21st century warming, which will cause a decrease in the vertical nutrient flux forcing declines in marine net primary productivity (NPP) and carbon export. Recent advances in quantifying marine ecosystem carbon to nutrient stoichiometry have identified large latitudinal and biome variability, with low-latitude oligotrophic systems harboring pico-sized phytoplankton exhibiting large phosphorus to carbon cellular plasticity. The climate forced changes in nutrient flux stoichiometry and phytoplankton community composition are thus likely to alter the ocean's biogeochemical response and feedback with the carbon-climate system. We have added three pico-phytoplankton functional types within the Biogeochemical Elemental Cycling component of the Community Earth System Model while incorporating variable cellular phosphorus to carbon stoichiometry for all represented phytoplankton types. The model simulates Prochlorococcus and Synechococcus populations that dominate the productivity and sinking carbon export of the tropical and subtropical ocean, and pico-eukaryote populations that contribute significantly to productivity and export within the subtropical to mid-latitude transition zone, with the western subtropical regions of each basin supporting the most P-poor stoichiometries. Subtropical gyre recirculation regions along the poleward flanks of surface western boundary currents are identified as regional hotspots of enhanced carbon export exhibiting C-rich/P-poor stoichiometry, preferentially inhabited by pico-eukaryotes and diatoms. Collectively, pico-phytoplankton contribute ∼58% of global NPP and ∼46% of global particulate organic carbon export below 100 m through direct and ecosystem processing pathways. Biodiversity and cellular nutrient plasticity in marine pico-phytoplankton combine to increase their contributions to ocean productivity and the biological carbon pump.

Environmental Sciences & Ecology↗

The CCSM4 Land Simulation, 1850–2005: Assessment of Surface Climate and New Capabilities

This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels. Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia. New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m -2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.

54 ENVIRONMENTAL SCIENCES↗

Toward a Global Map of Raindrop Size Distributions: Rain-Type Classification and Its Implications for Validating Global Rainfall Products - Part 1

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

L'Ecuyer, Tristan S.↗

Uncertainty Quantification in Climate Modeling and Projection

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop reported herein aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.

54 ENVIRONMENTAL SCIENCES↗

Particle kinetic simulation of high altitude hypervelocity flight

In this grant period, the focus has been on enhancement and application of the direct simulation Monte Carlo (DSMC) particle method for computing hypersonic flows of re-entry vehicles. Enhancement efforts dealt with modeling gas-gas interactions for thermal non-equilibrium relaxation processes and gas-surface interactions for prediction of vehicle surface temperatures. Both are important for application to problems of engineering interest. The code was employed in a parametric study to improve future applications, and in simulations of aeropass maneuvers in support of the Magellan mission. Detailed comparisons between continuum models for internal energy relaxation and DSMC models reveals that several discrepancies exist. These include definitions of relaxation parameters and the methodologies for implementing them in DSMC codes. These issues were clarified and all differences were rectified in a paper (Appendix A) submitted to Physics of Fluids A, featuring several key figures in the DSMC community as co-authors and B. Haas as first author. This material will be presented at the Fluid Dynamics meeting of the American Physical Society on November 21, 1993. The aerodynamics of space vehicles in highly rarefied flows are very sensitive to the vehicle surface temperatures. Rather than require prescribed temperature estimates for spacecraft as is typically done in DSMC methods, a new technique was developed which couples the dynamic surface heat transfer characteristics into the DSMC flow simulation code to compute surface temperatures directly. This model, when applied to thin planar bodies such as solar panels, was described in AIAA Paper No. 93-2765 (Appendix B) and was presented at the Thermophysics Conference in July 1993. The paper has been submitted to the Journal of Thermophysics and Heat Transfer. Application of the DSMC method to problems of practical interest requires a trade off between solution accuracy and computational expense and limitations. A parametric study was performed and reported in AIAA Paper No. 93-2806 (Appendix C) which assessed the accuracy penalties associated with simulations of varying grid resolution and flow domain size. The paper was also presented at the Thermophysics Conference and will be submitted to the journal shortly. Finally, the DSMC code was employed to assess the pitch, yaw, and roll aerodynamics of the Magellan spacecraft during entry into the Venus atmosphere at off-design attitudes. This work was in support of the Magellan aerobraking maneuver of May 25-Aug. 3, 1993. Furthermore, analysis of the roll characteristics of the configuration with canted solar panels was performed in support of the proposed 'Windmill' experiment. Results were reported in AIAA Paper No. 93-3676 (Appendix D) presented at the Atmospheric Flight Mechanics Conference in August 1993, and were submitted to Journal of Spacecraft and Rockets.

Haas, Brian L.↗

Hydrogen Biogeochemistry in Anaerobic and Photosynthetic Ecosystems

The simple biochemistry of molecular hydrogen is central to a large number of microbial processes, affecting the interaction of organisms with each other and with the environment. In anoxic sediments, a great majority of microbial redox processes involve hydrogen as a reactant, product or potential by-product. Accordingly, the energetics (thermodynamics) of each of these processes is affected by variations in local H2 concentrations. It has long been established that this effect is important in governing microbe-microbe interactions and there are multiple demonstrations that "interspecies hydrogen transfer" can alter the products of, inhibit/stimulate, or even reverse microbial metabolic reactions. In anoxic sediments, H2 concentrations themselves are thought to be controlled by the thermodynamics of the predominant H2-consuming microbial process. In sediments from Cape Lookout Bight, this relationship quantitatively describes the co-variation of H2 concentrations with temperature (for methanogens and sulfate reducers) and with sulfate concentration (for sulfate reducers). The quantitative aspect is import= for two reasons: 1) it permits the modeling of H2-sensitive biogeochemistry, such as anaerobic methane oxidation or pathways of organic matter remineralization, as a function of environmental controls; 2) for such a relationship to be observed requires that intracellular biochemistry and bioenergetics are being directly expressed in a component of the extracellular medium. H2 could therefore be utilized a non-invasive probe of cellular energetic function in intact microbial ecosystems. Based on the latter principle we have measured down-core profiles of H2 and other relevant physico-chemical parameters in order to calculate the metabolic energy yields (DG) that support microbial metabolism in Cape Lookout Bight sediments. Methanogens in this system apparently function with energy yields significantly smaller than the minimum requirements suggested by pure culture studies. Our recent work has extended the study of hydrogen to cyanobacterial mat communities. The large amounts of reducing power generated during photosynthetic activity carry the potential to contribute a swamping term to the H2 economy of the anaerobic microbial populations within the mat - and thereby to alter the population structure and biogeochemical function of the mat as a whole. In hypersaline microbial mats, we observe a distinct diel cycle in H2 production and a substantial corresponding flux. On an early Earth dominated by microbial mats, this transmission of photosynthetic reducing power may have carried important implications for both biospheric and atmospheric evolution.

Hoehler, Tori M.↗

Ecosystem Modeling of Biological Processes to Global Budgets

From an ecological perspective, the search for life on distant planets begins from several key assumptions. The first of these is that, viewed from a remote location in space, the signature of life on a distant planet will be the result of net gas exchange of organisms with their environment. On the basis of extensive biogeochemical measurements and biogenic trace gas fluxes in modem Earth environments, it is probable that certain groups of organisms both produce and consume the same trace gas(es) within a single bioprofile of Solid (porous) substrate or surface water. The net gas exchange rate with the atmosphere measured at the living surface is frequently the result of competing metabolic reactions, which may carried out by different functional groups of organisms located at dissimilar 'climatic' or chemical microsites within the same bioprofile. Biogenic gases produced at one (deep) level of a bioprofile may be consumed by another functional group of organisms located closer to the level of surface exchange with the atmosphere. A second key assumption is that the net biogenic fluxes of atmospheric gases on Earth can be used to infer relative abundance and functional composition of the major organisms on a distant planet. Examples of this principle include the presence of methanogenic microorganisms abundant today in freshwater ecosystems worldwide, which are major source of atmospheric methane and its seasonal variability in Earth's atmosphere. A third assumption is that scaling up biogenic gas fluxes from a single biological community to the planetary level requires flux measurements at the whole ecosystem level. This implies that measurements of biogenic gas exchange with the global atmosphere cannot be easily inferred from measurements of gas production rates of single organisms, which may have been isolated in some manner from the setting of their native ecosystem. Hence, the unit of biological organization used in modern Earth Science for scaling up to biosphere effects on atmospheric composition is the ecosystem level. These assumptions are the foundation for developing modern emission budgets for biogenic gases such as carbon dioxide, methane, carbon monoxide, isoprene, nitrous and nitric oxide, and ammonia. Such emission budgets commonly include information on seasonal flux patterns, typical diurnal profiles, and spatial resolution of at least one degree latitude/longitude for the globe. On the basis of these budgets, it is possible to compute 'base emission rates' for the major biogenic trace gases from both terrestrial and ocean sources, which may be useful benchmarks for defining the gas production rates of organisms, especially those from early Earth history, which are required to generate a detectable signal on a global atmosphere. This type of analysis is also the starting point for evaluation of the 'biological processes to global gas budget' extrapolation procedure described above for early Earth ecosystems.

Christopher, Potter S.↗

Improved Spectral and Angular Characterization of Libya-4 and Dome-C for consistent MODIS and VIIRS Radiometric Scaling

The NASA CERES observed SW and LW fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. To facilitate seamless flux and cloud properties across MODIS, VIIRS, and geostationary (GEO) imagers the CERES project intercalibrates the imagers directly comparing the coincident ray-matched analogous channel radiances. For CERES edition 4 products, the MODIS, VIIRS and GEO imagers were radiometrically scaled to the Aqua-MODIS C5 calibration reference. There are no direct comparison opportunities between NPP and NOAA20 VIIRS, since they are positioned a half an orbit apart. The previous usage of Aqua-MODIS as a transfer radiometer is coming to an end, since the Aqua orbit is slowly drifting towards the terminator and will be deorbited in 2026. The CERES project will utilize the Libya-4 and Dome-C invariant targets to radiometrically scale between MODIS and VIIRS reflective solar bands. The Libya-4 and Dome-C Earth invariant targets will be characterized by the repeat cycle angular configuration. The target spectral band adjustment factors (SBAF) will be derived using EMIT and DESIS hyper-spectral observations onboard the ISS and will be compared with the existing SCIAMACHY, GOME-2, and Hyperion SBAFs. The DESIS and EMIT SBAF approach can incorporate the future CLARREO CPF SI traceable hyper-spectral measurements allowing the targets to be referenced to an absolute calibration reference. Utilizing the BRDF and atmospheric corrected characterization of one sensor with another will provide the scaling factors. Consistent scaling factors between the two invariant target validates the method.

David R. Doelling↗

Rainbows and Climate Change: A tutorial on climate model diagnostics and parameterization

Earth System Models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an ESM: the Community Earth System Model version 2 (CESM2). Using the 'state' of the model, basic physical laws, and some assumptions, we generate a representation of this unique optical phenomena as a diagnostic output. Rainbow occurrence and it's possible changes are related to cloud occurrence and rain formation which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostics parameterizations such as assumptions, uncertain parameters and the difficulty of evaluation against uncertain observations. Results agree qualitatively with limited available global 'observations' of Rainbows. Rainbows are seen in expected locations in the sub-tropics over the ocean where broken clouds and frequent precipitation occurs. The diurnal peak is in the morning over ocean and in the evening over land. The representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic projects that rainbows will increase in the future, with the largest changes at mid-latitudes. The diagnostic may be useful for assessing cloud parameterizations, and is an exercise in how to build and test parameterizations of atmospheric phenomena.

54 ENVIRONMENTAL SCIENCES↗

SPoRT's Participation in the GOES-R Proving Ground Activity

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

Jedlovec, Gary↗

Impacts of the East Asian Monsoon on springtime dust concentrations over China

We use 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of the East Asian Monsoon strength on interannual variations of springtime dust concentrations over China. The simulated interannual variations in March-April-May (MAM) dust column concentrations range between 20–40% and 10–60% over eastern and western China, respectively. The dust concentrations over eastern China correlate negatively with the East Asian Monsoon (EAM) index, which represents the strength of monsoon, with a regionally averaged correlation coefficient of 0.64. Relative to the strongest EAM years, MAMdust concentrations in the weakest EAM years are higher over China, with regional relative differences of 55.6%, 29.6%, and 13.9% in the run with emissions calculated interactively and of 33.8%, 10.3%, and 8.2% over eastern, central, and western China, respectively, in the run with prescribed emissions. Both interactive run and prescribed emission run show the similar pattern of climate change between the weakest and strongest EAM years. Strong anomalous northwesterly and westerly winds over the Gobi and Taklamakan deserts during the weakest EAM years result in larger transport fluxes, and thereby increase the dust concentrations over China. Here, these differences in dust concentrations between the weakest and strongest EAM years (weakest-strongest) lead to the change in the net radiative forcing by up to -8 and -3Wm -2 at the surface, compared to -2.4 and +1.2Wm -2 at the top of the atmosphere over eastern and western China, respectively.

58 GEOSCIENCES↗