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NASA NTRS2020

Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25°×0.25°) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

land use land cover change↗

NASA NTRS2001

Orbital Noise in the Earth System and Climate Fluctuations

Frequency noise in the variations of the Earth's obliquity (tilt) can modulate the insolation signal for climate change. Including this frequency noise effect on the incoming solar radiation, we have applied an energy balance climate model to calculate the climate fluctuations for the past one million years. Model simulation results are in good agreement with the geologically observed paleoclimate data. We conclude that orbital noise in the Earth system may be the major cause of the climate fluctuation cycles.

Liu, Han-Shou↗

NASA NTRS2001

Regional Climate Studies with Variable-Resolution Stretched-Grid GCMs

A variable resolution GCM using a global stretched grid with fine resolution over the area(s) of interest, is a viable new approach to regional and subregional climate studies and applications. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The first version of the SG-GCM based on the GEOS (Goddard Earth Observing System) GCM using a finite-difference approximation, has been developed and thoroughly tested during the last few years. Successful simulations have been performed with the SG-GCM for the anomalous regional climate events of the U.S. 1988 summer drought and 1993 summer flood. They have shown the practical feasibility of the SG-approach for regional climate modeling. The GEOS SG-DAS (Data Assimilation System) incorporating the SG-GCM has also been developed and tested. The assimilated regional fields and diagnostics are used for validating the SG-GCM regional simulations. Two new SG-GCMs are being developed. The first is the SG-version of the new NASANCAR FV-GCM (with the finite-volume (FV) dynamics), and the second is the SG-version of the new GCM with spectral-element dynamics. Both GCMs use the WAR CCM4 physics. Using these advanced numerics will provide increased computational efficiency for the new the SG-GCMs, and will allow us to employ more flexible stretching strategies beneficial for the efficient regional down-scaling. The major current developments are focused on: simulating the 1997-1999 (and beyond) ENSO cycle and related monsoonal circulations, with enhanced regional resolution; studying intraseasonal and interannual regional climate variability for the extended multiyear (AMIP-type) SG-GCM simulations; and studying the impact of ensemble integrations.

Fox-Rabinovitz, Michael↗

NASA NTRS2021

Developing a Hydrological Monitoring and Sub-Seasonal to Seasonal Forecasting System for South and Southeast Asian River Basins

South and Southeast Asia is subject to significant hydrometeorological extremes, including drought. Under rising temperatures, growing populations, and an apparent weakening of the South Asian monsoon in recent decades, concerns regarding drought and its potential impacts on water and food security are on the rise. Reliable sub-seasonal to seasonal (S2S) hydrological forecasts could, in principle, help governments and international organizations to better assess risk and act in the face of an oncoming drought. Here, we leverage recent improvements in S2S meteorological forecasts and the growing power of Earth Observations to provide more accurate monitoring of hydrological states for forecast initialization. Information from both sources is merged in a South and Southeast Asia sub-seasonal to seasonal hydrological forecasting system (SAHFS-S2S), developed collaboratively with the NASA SERVIR program and end-users across the region. This system applies the Noah-MultiParameterization (NoahMP) Land Surface Model (LSM) in the NASA Land Information System (LIS), driven by downscaled meteorological fields from the Global Data Assimilation System (GDAS) and Climate Hazards InfraRed Precipitation products (CHIRP and CHIRPS) to optimize initial conditions. The NASA Goddard Earth Observing System Model - sub-seasonal to seasonal (GEOS-S2S) forecasts, downscaled using the National Center for Atmospheric Research (NCAR) General Analog Regression Downscaling (GARD) tool and quantile mapping, are then applied to drive 5-km resolution hydrological forecasts to a 9-month forecast time horizon. Results show that the skillful predictions of root zone soil moisture can be made one to two months in advance for forecasts initialized in rainy seasons and up to 8 months when initialized in dry seasons. The memory of accurate initial conditions can positively contribute to forecast skills throughout the entire 9-month prediction period in areas with limited precipitation. This SAHFS-S2S has been operationalized at the International Centre for Integrated Mountain Development (ICIMOD) to support drought monitoring and warning needs in the region.

Yifan Zhou↗

NASA NTRSDate not supplied

ROCKE-3D 2.0: An Updated General Circulation Model for Simulating the Climates of Rocky Planets

We present the second generation of ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics), the generalized 3-dimensional General Circulation Model (GCM) for use in Solar System and exoplanetary simulations of rocky planet climates. ROCKE-3D version 2.0 is a descendant of GISS ModelE2.1, the flagship GCM of the NASA Goddard Institute for Space Studies (GISS) used in the most recent Intergovernmental Panel for Climate Change (IPCC) assessment. ROCKE-3D is a continuous effort to expand the capabilities of GISS ModelE to handle a broader range of atmospheric conditions, including different atmospheric planet sizes, gravities, pressures, rotation rates, more diverse chemistries and atmospheric compositions, diverse ocean and land distributions and topographies, and potential basic biosphere functions. We present in this release many more supported configurations which can serve as starting points to simulate terrestrial planets of interest. Two different radiation schemes are supported, the GISS radiation, valid for Earth-like planets, and SOCRATES, which is more generalized but requires more CPU resources. In addition, three different atmospheric compositions are supported, three ocean configurations (prescribed, q-flux, and dynamic), and two resolutions: the medium resolution (4 x 5 degrees in latitude x longitude) used in ROCKE-3D 1.0, and the fine resolution, which has double the resolution in the atmosphere and 4 times the resolution in the ocean. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.

ROCKE-3D↗

NASA NTRS2024

An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).

Machine learning↗

NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗

NASA NTRS1982

Climatic influence of background and volcanic stratosphere aerosol models

A simple modelization of the earth atmosphere system including tropospheric and stratospheric aerosols has been derived and tested. Analytical expressions are obtained for the albedo variation due to a thin stratospheric aerosol layer. Also outlined are the physical procedures and the respective influence of the main parameters: aerosol optical thickness, single scattering albedo and asymmetry factor, and sublayer albedo. The method is applied to compute the variation of the zonal and planetary albedos due to a stratospheric layer of background H2SO4 particles and of volcanic ash.

Deschamps, P. Y.↗

NASA NTRS1994

Space observations for global and regional studies of the biosphere

The capability to make space-based measurements of Earth at high spatial and temporal resolutions, which would not otherwise be economically or practically feasible, became available just in time to contribute to scientific understanding of the interactive processes governing the total Earth system. Such understanding has now become essential in order to take practical steps which would counteract or mitigate the pervasive impact of the growing human population on the future habitability of the Earth. The paper reviews the rationale for using space observations for studies of climate and terrestrial ecosystems at global and regional scales, as well as the requirements for such observations for studies of climate and ecosystem dynamics. The present status of these developments is reported along with initiatives under way to advance the use of satellite observations for Earth system studies. The most important contribution of space observations is the provision of physical or biophysical parameters for models representing various components of the Earth system. Examples of such parameters are given for climatic and ecosystem studies.

Cihlar, J.↗

NASA NTRS2006

Development and Implementation of a Comprehensive Radiometric Validation Protocol for the CERES Earth Radiation Budget Climate Record Sensors

The CERES Flight Models 1 through 4 instruments were launched aboard NASA's Earth Observing System (EOS) Terra and Aqua Spacecraft into 705 Km sun-synchronous orbits with 10:30 a.m. and 1:30 p.m. equatorial crossing times. These instruments supplement measurements made by the CERES Proto Flight Model (PFM) instrument launched aboard NASA's Tropical Rainfall Measuring Mission (TRMM) into a 350 Km, 38-degree mid-inclined orbit. CERES Climate Data Records consist of geolocated and calibrated instantaneous filtered and unfiltered radiances through temporally and spatially averaged TOA, Surface and Atmospheric fluxes. CERES filtered radiance measurements cover three spectral bands including shortwave (0.3 to 5 microns), total (0.3 to 100 microns) and an atmospheric window channel (8 to 12 microns). The CERES Earth Radiation Budget measurements represent a new era in radiation climate data, realizing a factor of 2 to 4 improvement in calibration accuracy and stability over the previous ERBE climate records, while striving for the next goal of 0.3-percent per decade absolute stability. The current improvement is derived from two sources: the incorporation of lessons learned from the ERBE mission in the design of the CERES instruments and the development of a rigorous and comprehensive radiometric validation protocol consisting of individual studies covering different spatial, spectral and temporal time scales on data collected both pre and post launch. Once this ensemble of individual perspectives is collected and organized, a cohesive and highly rigorous picture of the overall end-to-end performance of the CERES instrument's and data processing algorithms may be clearly established. This approach has resulted in unprecedented levels of accuracy for radiation budget instruments and data products with calibration stability of better than 0.2-percent and calibration traceability from ground to flight of 0.25-percent. The current work summarizes the development, philosophy and implementation of the protocol designed to rigorously quantify the quality of the data products as well as the level of agreement between the CERES TRMM, Terra and Aqua climate data records.

Priestley, K. J.↗

NASA NTRS2002

Workshop on Spanning Regional-to-Global Pollution

Pollution is often considered a localized phenomenon, but it is now clear that it travels from region-to-region, country to country, and even continent to continent. In addition to urban pollution in developed countries, large emissions from developing nations and large-scale biomass fires add to the global pollution burden. Ozone and aerosols are two components of pollution that contribute to radiative forcing of the earth s climate. In turn, as climate changes, rates of chemical and microphysical reactions may be perturbed. Considering the earth as a coupled chemical-microphysical-climate system poses challenges for models and observations alike. These issues were the topic of a Workshop held in May 2002 at NASA GSFC s Laboratory for Atmospheres. Highlights of the Workshop are summarized in this article.

Thompson, Anne M.↗

NASA NTRS2022

Remote sensing-based vegetation and soil moisture constraints reduce irrigation estimation uncertainty

Understanding the human water footprint and its impact on the hydrological cycle is essential to inform water management under climate change. Despite efforts in estimating irrigation water withdrawals in earth system models, uncertainties and discrepancies exist within and across modeling systems conditioned by model structure, irrigation parameterization, and the choice of input datasets. Achieving model reliability could be much more challenging for data-sparse regions, given limited access to ground truth for parameterization and validation. Here, we demonstrate the potential of utilizing remotely sensed vegetation and soil moisture observations in constraining irrigation estimation in the Noah-MP land surface model. Results indicate that the two constraints together can effectively reduce model sensitivity to the choice of irrigation parameterization by 7%–43%. It also improves the characterization of the spatial patterns of irrigation and its impact on evapotranspiration and surface soil moisture by correcting for vegetation conditions and irrigation timing. This study highlights the importance of utilizing remotely sensed soil moisture and vegetation measurements in detecting irrigation signals and correcting for vegetation growth. Integrating the two remote sensing datasets into the model provides an effective and less feature engineered approach to constraining the uncertainty of irrigation modeling. Such strategies can be potentially transferred to other modeling systems and applied to regions across the globe.

Wanshu Nie↗

NASA NTRS2010

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗

NASA NTRS2005

Towards an A-train Aerosol Assimilation System: Assimilation of MODIS Aerosol Optical Thickness Retrievals into a Global Aerosol Transport and Radiation Model

To understand the role of atmospheric aerosols in Earth's climate system we ideally require a global, three-dimensional, and temporally continuous system of measurements. The view of aerosols provided by a single polar-orbiting satellite instrument (e.g., MODIS), while providing the greatest spatial coverage of any measurement system available, can offer only a single relevant observation per day of a particular location. Furthermore, the quantitative interpretation of those observations is subject to considerable uncertainty because of we do not know the aerosol optical properties or vertical profiles well enough. Ground-based and in situ measurements can provide missing detail about aerosol vertical and optical properties, but lack the spatial (and sometimes temporal) coverage desired. Chemical transport models treating the aerosol lifecycle complement this picture by providing three-dimensional, global, and continuous aerosol fields, but suffer from poor constraints on their initial conditions (e.g., the aerosol source, sink, and transformation mechanisms). Here we present a global, three- dimensional aerosol transport model and assimilation system. The model assimilates the MODIS aerosol optical thickness product to constrain its aerosol distributions and burdens. We provide an analysis of the model aerosol distributions as constrained by ground-based sun photometer measurements and aerosol products from other satellite measurements.

Colarco, P.↗

NASA NTRS2019

Volcanic Eruption Signatures in the Isotope Enabled Last Millennium Ensemble

Explosive volcanic eruptions are one of the largest natural climate perturbations, but few observational constraints exist on either the climate responses to eruptions or the properties (size, hemispheric aerosol distribution, etc.) of the eruptions themselves. Paleoclimate records are thus important sources of information on past eruptions, often through the measurement of oxygen isotopic ratios (𝛿18O) in natural archives. However, since many processes affect 𝛿18O, the dynamical interpretation of these records can be quite complex. Here we present results from new, isotope-enabled members of the Community Earth System Model Last Millennium Ensemble, documenting eruption-induced 𝛿18O variations throughout the climate system. Eruptions create significant perturbations in the 𝛿18O of precipitation and soil moisture in central/eastern North America, via excitation of the Atlantic Multidecadal Oscillation. Monsoon Asia and Australia also exhibit strong precipitation and soil 𝛿18O anomalies; in these cases, 𝛿18O may reflect changes to El Niño-Southern Oscillation phase following eruptions. Salinity and seawater 𝛿18O patterns demonstrate the importance of both local hydrologic shifts and the phasing of the El Niño-Southern Oscillation response, both along the equator and in the subtropics. In all cases, the responses are highly sensitive to eruption latitude, which points to the utility of isotopic records in constraining aerosol distribution patterns associated with past eruptions. This is most effective using precipitation 𝛿18O; all Southern eruptions and the majority (66%) of Northern eruptions can be correctly identified. This work thus serves as a starting point for new, quantitative uses of isotopic records for understanding volcanic impacts on climate.

Stevenson, S.↗

NASA NTRS2022

Model Evaluation of Short-Lived Climate Forcers for the Arctic Monitoring and Assessment Programme: A Multi-Species, Multi-Model Study

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008-2009 and 2014-2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, 03, BC, and SO(sup 2-)(sub 4)), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for C"4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

Arctic Monitoring and Assessment Programme↗

NASA NTRS2023

Observations Suggest That North African Dust Absorbs Less Solar Radiation Than Models Estimate

Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.

Atmospheric science↗

NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗