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A radiation parameterization for the NASA Goddard climate model was developed, tested, and implemented. Interactive and off-hire experiments with the climate model to determine the limitations of the present parameterization scheme are summarized. The parameterization of Cloud absorption in terms of solar zeith angle, column water vapors about the cloud top, and cloud liquid water content is discussed.
It was suggested that Mars may have possessed a relatively warm humid climate and a vigorous hydrological cycle involving meteoric precipitation, oceans, and continental ice sheets. Baker hypothesized that these geologically active conditions may have been repeated several times; each of these dynamic epochs was followed by a collapse of the climate and hydrologic cycle of Mars into essentially current conditions, completing what is termed a 'Baker cycle'. The purpose is to present an endmember possibility that Martian glacial landscapes, including some that were previously considered to have formed under warm climatic conditions, might be explained by processes compatible with an extremely cold surface. Two aspects of hypothesized Martian glacial terrains were cited as favoring a warm climate during Baker cycles: (1) the formation of some landscapes, including possible eskers, tunnel channels, drumlins, and outwash plains, appears to have required liquid water, and (2) a liquid-surfaced ocean was probably necessary to feed the glaciers. The requirement for liquid water, if these features were correctly interpreted, is difficult to avoid; it is entirely possible that a comparatively warm climate was involved, but it is not clear that formation of landforms by wet-based glaciers actually requires a warm climate. Even less certain is the supposed requirement for liquid oceans. Formation of glaciers only requires a source of water or ice to supply an amount of precipitation that exceeds losses due to melting and sublimation. At Martian temperatures precipitation is very low, but so are melting and sublimation, so a large body of ice that is unstable with respect to sublimation may take the role of Earth's oceans in feeding the glaciers. Recent models suggest that even current Martian polar caps, long thought to be static bodies of ice and dust, might actually be slow-moving, cryogenic continental glaciers. Is it possible that subglacial processes beneath cryogenic (but wetbased) ice sheets formed the hypothesized Martian glacial landscapes?
Ice cores and other paleotemperature proxies, together with general circulation models, have provided information on past surface temperatures and the atmosphere's composition in different climates. Little is known, however, about past temperatures at high altitudes, which play a crucial role in Earth's radiative energy budget. Paleoclimate records at high-altitude sites are sparse, and the few that are available show poor agreement with climate model predictions. These disagreements could be due to insufficient spatial coverage, spatiotemporal biases, or model physics; new records that can mitigate or avoid these uncertainties are needed. Here, we constrain the change in upper-tropospheric temperature at the global scale during the Last Glacial Maximum (LGM) using the clumped-isotope composition of molecular oxygen trapped in polar ice cores. Aided by global three-dimensional chemical transport modeling, we exploit the intrinsic temperature sensitivity of the clumped-isotope composition of atmospheric oxygen to infer that the upper troposphere (effective mean altitude 10–11 km) was 6–9°C cooler during the LGM than during the late preindustrial Holocene. A complementary energy balance approach supports a minor or negligible steepening of atmospheric lapse rates during the LGM, which is consistent with a range of climate model simulations. Proxy-model disagreements with other high-altitude records may stem from inaccuracies in regional hydroclimate simulation, possibly related to land-atmosphere feedbacks.
Heating associated with tropical cloud systems drive the global circulation. The overall research objectives of this project were to i) further quantify and understand the importance of heating in tropical convective cloud systems with innovative observational techniques, and ii) use global models to determine the large-scale circulation response to variability in tropical heating profiles, including anvil and cirrus cloud radiative forcing. The innovative observational techniques used a diversity of radar systems to create a climatology of vertical velocities associated with the full tropical convective cloud spectrum along with a dissection of the of the total heating profile of tropical cloud systems into separate components (i.e., the latent, radiative, and eddy sensible heating). These properties were used to validate storm-scale and global climate models (GCMs) and were further used to force two different types of GCMs (one with and one without interactive physics). While radiative heating was shown to account for about 20% of the total heating and did not have a strong direct response on the global circulation, the indirect response was important via its impact on convection, esp. in how radiative heating impacts the tilt of heating associated with the Madden-Julian Oscillation (MJO), a phenomenon that accounts for most tropical intraseasonal variability. This work shows strong promise in determining the sensitivity of climate models and climate processes to heating variations associated with cloud systems.
Mid-latitude storms have large climate impacts affecting the variability of precipitation, temperature, and winds in the extra-tropics. In the Southern Hemisphere, climate models project an intensification of winter storms and a poleward shift of summer storms by the end of the 21st century. However, previous studies, using idealized models, have shown a non-monotonic behavior of the storms with increasing temperatures. Thus, with the unabated emissions of greenhouse gases into the atmosphere, one might expect a similar non-monotonic behavior beyond the 21st century. To examine this, we here investigate the response of mid-latitude winter storms in the Southern Hemisphere to increasing CO 2 concentrations (up to eight times the preindustrial CO 2 levels) using two state-of-the-art climate models. We find that at high CO 2 levels, winter storms no longer exhibit an intensification across the entire extratropics, as projected by the end of the 21st century. Instead, winter storms shift poleward, similar to the projected response of summer storms by 2100, including a weakening of the storms at low-mid latitudes and an intensification at mid-high latitudes. Out results stresses the importance of investigating the mid latitude flow beyond 2100, to account for any non-monotonic response to increasing GHGs.
The goal of our project was to enhance our understanding of the role of coupling in the simulation of the Madden Julian Oscillation (MJO) in coupled climate models. We developed diagnostics of precipitation and Sea Surface Temperature variability in climate models and investigated how they are related to metrics of MJO simulation performance. We found a relationship between models with a high spatial coherence of precipitation and a good propagation of the MJO through the Maritime Continent region, but no relationship between metrics of precipitation organisation and intensity. Analysis of coupled and uncoupled model simulations from the Sixth Coupled Model Intercomparison Project (CMIP6) shows that coupling systematically improved the MJO simulation in both metrics that we investigated. We analysed the role of background moisture gradients in the MJO simulation performance following Lim et al. (2018) and found that although the model to model variation in moisture gradients to the west of Indonesia was related to model MJO performance, in general no single moisture gradient was as good at explaining a large fraction of MJO performance across the models as compared to a linear combination of those metrics, which was able to explain a significant fraction of the variance in the MJO performance. Those relationships were much stronger for coupled simulations than uncoupled simulations and stronger for those metrics that measured propagation of the MJO across the Maritime Continent than for overall MJO activity.
Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p < 0.01), the post La Niña sink is driven largely by tropical precipitation (r PG,T= -0.46, p = 0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. Furthermore, we find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.
Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.
Global climate models (GCMs) are the primary tools for predicting the evolution of the climate system. Through decades of development, GCMs have demonstrated useful skill in simulating climate at continental to global scales. However, large uncertainties remain in projecting climate change at regional scales, which limit our ability to inform decisions on climate change adaptation and mitigation. To bridge this gap, different modeling approaches including nested regional climate models (RCMs), global stretch-grid models, and global high-resolution atmospheric models have been used to provide regional climate simulations (Leung et al. 2003). In previous efforts to evaluate these approaches, isolating their relative merits was not possible because factors such as dynamical frameworks, physics parameterizations, and model resolutions were not systematically constrained. With advances in high performance computing, it is now feasible to run coupled atmosphere-ocean GCMs at horizontal resolution comparable to what RCMs use today. Global models with local refinement using unstructured grids have become available for modeling regional climate (e.g., Rauscher et al. 2012; Ringler et al. 2013). While they offer opportunities to improve climate simulations, significant efforts are needed to test their veracity for regional-scale climate simulations.
This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.
The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Furthermore, compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.
Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension D(sub f) approximately equals 1.8 mobility diameter D(sub m) (is) less than or equal to 1 micron, and aerodynamic diameter D(sub a) (is) less than or equal to 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic D(sub f) approximately equals 2.6,D(sub m) (is) greater than 1 micron, and D(sub a) is less than or equal to 300 nm that form via the cluster-dense aggregation mechanism.We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(sub f) approximately equals 1.8) aggregates, and approximately equals 90% more warming than the volume-equivalent spherical soot particles simulated in climate models.
Controlled environment chambers (e.g. growth chambers, SPAR chambers, or open-top chambers) are useful for measuring plant ecosystem responses to climatic variables and CO2 that affect plant water relations. However, data from chambers was found to overestimate responses of C fluxes to CO2 enrichment. Chamber data may be confounded by numerous artifacts (e.g. sidelighting, edge effects, increased temperature and VPD, etc) and this limits what can be measured accurately. Chambers can be used to measure canopy level energy balance under controlled conditions and plant transpiration responses to CO2 concentration can be elucidated. However, these measurements cannot be used directly in model development or validation. The response of stomatal conductance to CO2 will be the same as in the field, but the measured response must be recalculated in such a manner to account for differences in aerodynamic conductance, temperature and VPD between the chamber and the field.
The overall goal of this BOREAS Program was to develop, test, and apply a model of the carbon balance of boreal forest sites with a significant groundcover component (moss or lichen). The basic question addressed with this model was: What is the sensitivity of the boreal forest carbon balance to weather variability? More specifically: What are the differences in the sensitivities of carbon gains (photosynthesis) and carbon losses (respiration) of the various components of the ecosystem? Are there different seasonalities to their sensitivities (e.g., warmer springs will have one effect, warmer summers a different effect)? What are the effects of different patterns of successive weather years (wet/dry, warm/cool)? What, for example, would be the difference in effects of two "warmer than normal" months-one with each day warmer than normal, and the other with three normal weeks and one very hot week? Due to weather variability, how "noisy" will any carbon flux or carbon pool signal be that we might use to try to detect change? The project resulted in the development of a new boreal forest ecosystem model. This model was the first model in the BOREAS project to look closely at the role of mosses in the ecosystem carbon balance, and also was the first model in the BOREAS project to look closely at interannual variability in carbon fluxes. Along with the work of many other groups, TE-19 modeling analysis pointed to the need for a second, longer field season in 1996, with particular focus on the spring and fall transitions and on ground vegetation. BOREAS groups TE-19 (Frolking), TGB-1 (Crill) & TGB-3 (Moore & Roulet) analyzed BOREAS data and other published and unpublished data to develop a relationship between peatland ecosystem productivity and incoming radiation, which is quite distinct from the upland ecosystem relationships observed in other studies.
The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.
Early observational and modeling work suggested that low-latitude volcanic eruptions, comparable to the one of Pinatubo in 1991 or Krakatau in 1883, cause substantial surface warming over the northern continents at mid-latitudes in winter. The proposed mechanism consists of the formation of an anomalously strong Equator-to-pole temperature gradient in the stratosphere due to the presence of volcanic aerosols in the tropics, which are accompanied by an acceleration of the stratospheric polar vortex, which then shifts the Northern Annular Mode into a positive phase, resulting in warming surface temperatures over Eurasia. However, a large body of research in the past decade has shown that, for eruptions such as Pinatubo or Krakatau, no such warming is seen in simulations with more recent climate models which, in general, have much finer vertical and horizontal resolution than the early ones, and which have separated the forced response from the internal variability by using large ensembles of integrations. Since the proposed physical mechanism is sound, it is then possible that eruptions comparable to those of Pinatubo or Krakatau are simply too weak, but even larger ones might indeed be capable of causing Eurasian surface warming in winter. In this study, we explore this possibility using a state-of-the-art, stratosphere-resolving climate model, forced with prescribed aerosols from the Easy Volcanic Aerosol protocol. We consider eruptions with stratospheric sulfur injections of 5, 10, 20, 40, 80, and 160 Tg(S). With 20-member ensembles, we find that with injections of 20 Tg(S) or more – roughly twice the amplitude of the Pinatubo and Krakatau eruptions – our model simulates a winter surface warming over Eurasia, which is statistically significant with a t test given our 20-member ensembles. However, the forced volcanic signal on Eurasian winter surface temperatures is very small, barely exceeding the 1σ range of internal variability for the 160 Tg(S) injection case, and much smaller for smaller eruptions. Most importantly, the number of eruptions needed to establish statistical significance is considerably larger than the number of eruptions known to have occurred in the past 2000 years.
This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.
Abstract. This paper describes the addition of a stratospheric prognostic aerosol (SPA) capability – developed with the goal of accurately simulating sulfate aerosol formation and evolution in the stratosphere – in the Department of Energy (DOE) Energy Exascale Earth System Model, version 2 (E3SMv2). The implementation includes changes to the four-mode Modal Aerosol Module microphysics in the stratosphere to allow for larger particle growth and more accurate stratospheric aerosol lifetime following the Pinatubo eruption. E3SMv2-SPA reasonably reproduces stratospheric aerosol lifetime, burden, aerosol optical depth, and top-of-atmosphere flux when compared to remote sensing observations. E3SMv2-SPA also has close agreement with the interactive chemistry–climate model CESM2-WACCM (Community Earth System Model version 2–Whole Atmosphere Community Climate Model) – which has a more complete chemical treatment – and the observationally constrained, prescribed volcanic aerosol treatment in E3SMv2. Global stratospheric aerosol size distributions identify the nucleation and growth of sulfate aerosol from volcanically injected SO2 from both major and minor volcanic eruptions from 1991 to 1993. The modeled aerosol effective radius is consistently lower than satellite and in situ measurements (max differences of ∼ 30 %). Comparisons with in situ size distribution samples indicate that this simulated underestimation in both E3SMv2-SPA and CESM2-WACCM is due to overly small accumulation and coarse-mode aerosols 6–18 months post-eruption, with E3SMv2-SPA simulating ∼ 50 % of the coarse-mode geometric mean diameters of observations 11 months post-eruption. Effective radii from the models and observations are used to calculate offline scattering and absorption efficiencies to explore the implications of smaller simulated aerosol size for the Pinatubo climate impacts. Scattering efficiencies at wavelengths of peak solar irradiance (∼ 0.5 µm) are 10 %–80 % higher for daily samples in models relative to observations through 1993, suggesting higher diffuse radiation at the surface and a larger cooling effect in the models due to the smaller simulated aerosol; absorption efficiencies at the peak wavelengths of outgoing terrestrial radiation (∼ 10 µm) are 15 %–40 % lower for daily samples in models relative to observations, suggesting an underestimation in stratospheric heating in the models due to the smaller simulated aerosol. These potential biases are based on aerosol size alone and do not take into account differences in the aerosol number. The overall agreement of E3SMv2-SPA with observations and its similar performance to the well-validated CESM2-WACCM makes E3SMv2-SPA a viable alternative to simulating climate impacts from stratospheric sulfate aerosols.