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Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 kilometers to 0.6 kilometers. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

Hamann, U.↗

Observation of Trace Gases Seasonal Variability in the Marine Boundary Layer over the Atlantic Ocean during the ACTIVATE Field Campaign

High resolution in-situ measurements of carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and water vapor (H2O) were made onboard the NASA HU-25 aircraft during the ACTIVATE (Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment) campaign during 2020 and 2021 in different seasons (winter through summer) over the mid-latitude western Atlantic Ocean. As most of the flights focused on the marine boundary layer (MBL) during the campaign, these trace gas observations are an excellent data set to examine seasonal variability of trace gas background values in the MBL without the influence of localized point sources. We will describe the variability of these trace gases in the MBL background by filtering out concentrated point sources using back trajectory analysis along with trace gas ratios. Additionally, the ocean is a significant sink of anthropogenic CO2 capturing about one quarter of total anthropogenic carbon. By looking at the MBL CO2 variation as a function of season, we discuss observed changes in CO2 uptake over the ocean. These high accuracy observations of trace gas backgrounds in the MBL along with characterizing seasonal effects on oceanic sequestering of anthropogenic CO2 will improve the understanding of seasonal variations and change in climate and inverse modelling over the ocean.

Yonghoon Choi↗

Water Energy Simulation Toolset

The Water-Energy Simulation Toolset (WEST) is an interactive simulation model that helps visualize impacts of different stakeholders on water quantity and quality of a watershed. The case study is applied for the Snake River Basin with the fictional name Cutthroat River Basin. There are four groups of stakeholders of interest: hydropower, agriculture, flood control, and environmental protection. Currently, the quality component depicts nitrogen-nitrate contaminant. Users can easily interact with the model by changing certain inputs (climate change, fertilizer inputs, etc.) to observe the change over the entire system. Users can also change certain parameters to test their management policy.

Nguyen, Thuy↗

Helping Businesses and Communities Better Cope with Extreme Weather

The U.S. Department of Energy's Argonne National Laboratory is helping organizations – including AT&T – and communities better prepare for and adapt to the impacts of climate change and extreme weather events. Argonne's cutting-edge climate science and infrastructure analysis/resilience capabilities have helped a range of organizations (companies, federal agencies and cities) make more informed decisions and minimize negative impacts. To learn how your organization might collaborate with Argonne in this space, contact partners@anl.gov.

54 ENVIRONMENTAL SCIENCES↗

Accelerating Adoption of Energy-Efficient Technology with the Thermalize Model

The accelerating impacts of climate change destabilize food systems and ecosystems alongside the communities that rely on them. Thus, climate resilience is a health equity issue at both a physical (relating to biological impacts of pollution and environmental degradation) and a cultural level (loss of subsistence lifestyles, languages, etc). With roughly 20% of US energy-related greenhouse gas emissions stemming from heating, cooling, and powering households, accessible energy-efficient home retrofits are a critical element of climate change mitigation strategies. For communities already producing electricity from renewable sources, like Juneau, incentivizing ductless heat pump upgrades and energy efficiency retrofits provides an accessible pathway to transition households away from oil heating and drastically reduce emissions. Thermalize Juneau is a pilot program that will explore a repeatable framework for accelerating the adoption of energy-efficient technology in Alaska communities. This poster will describe Thermalize Juneau's goals and framework, progress through spring 2021, and future plans.

ductless heat pumps↗

Advance Local Mobility Through Energy Efficient Mobility Systems Technologies

Everyone deserves reliable, affordable, and safe transportation to connect people to jobs, healthcare, education, and recreation. Our transportation systems are interconnected, multimodal networks working together to move people and goods. These systems are dynamic and are being reshaped by factors such as population trends, new technologies, shifting labor models, economic forces, and changing climate. Energy efficient mobility systems (EEMS) technologies can help transportation planners ensure changes in our transportation systems are equitable and sustainable by improving energy efficiency, travel time, and affordability, as well as overall access to mobility. Transportation planners and decision makers can use the following EEMS tools and strategies to advance local mobility.

ADVANCED PROPULSION SYSTEMS↗

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗

Projected Regime Shift in Arctic Cloud and Water Vapor Feedbacks

The Arctic climate is changing faster than any other large-scale region on Earth. A variety of positive feedback mechanisms are responsible for the amplification, most of which are linked with changes in snow and ice cover, surface temperature (T(sub s)), atmospheric water vapor (WV), and cloud properties. As greenhouse gases continue to accumulate in the atmosphere, air temperature and water vapor content also increase, leading to a warmer surface and ice loss, which further enhance evaporation and WV. Many details of these interrelated feedbacks are poorly understood, yet are essential for understanding the pace and regional variations in future Arctic change. We use a global climate model (Goddard Institute for Space Studies, Atmosphere-Ocean Model) to examine several components of these feedbacks, how they vary by season, and how they are projected to change through the 21st century. One positive feedback begins with an increase in T(sub s) that produces an increase in WV, which in turn increases the downward longwave flux (DLF) and T(sub s), leading to further evaporation. Another associates the expected increases in cloud cover and optical thickness with increasing DLF and T(sub s). We examine the sensitivities between DLF and other climate variables in these feedbacks and find that they are strongest in the non-summer seasons, leading to the largest amplification in Ts during these months. Later in the 21st century, however, DLF becomes less sensitive to changes in WV and cloud optical thickness, as they cause the atmosphere to emit longwave radiation more nearly as a black body. This regime shift in sensitivity implies that the amplified pace of Arctic change relative to the northern hemisphere could relax in the future.

Chen, Yonghua↗

The climate change mitigation potential of annual grasslands under future climates

Abstract Composted manure and green waste amendments have been shown to increase net carbon (C) sequestration in rangeland soils and have been proposed as a means to help lower atmospheric CO 2 concentrations. However, the effect of climate change on soil organic C (SOC) stocks and greenhouse gas emissions in rangelands is not well understood, and the viability of climate change mitigation strategies under future conditions is even less certain. We used a process‐based biogeochemical model (DayCent) at a daily time step to explore the long‐term effects of potential future climate changes on C and greenhouse gas dynamics in annual grassland ecosystems. We then used the model to explore how the same ecosystems might respond to climate change following compost amendments to soils and determined the long‐term viability of net SOC sequestration under changing climates. We simulated net primary productivity (NPP), SOC, and greenhouse gas fluxes across seven California annual grasslands with and without compost amendments. We drove the DayCent simulations with field data and with site‐specific daily climate data from two Earth system models (CanESM2 and HadGEM‐ES) and two representative concentration pathways (RCP4.5 and RCP8.5) through 2100. NPP and SOC stocks in unamended and amended ecosystems were surprisingly insensitive to projected climate changes. A one‐time amendment of compost to rangeland acted as a slow‐release organic fertilizer and increased NPP by up to 390–814 kg C ha −1 year −1 across sites. The amendment effect on NPP was not sensitive to Earth system model or emissions scenario and endured through the end of the century. Net SOC sequestration amounted to 1.96 ± 0.02 Mg C ha −1 relative to unamended soils at the maximum amendment effect. Averaged across sites and scenarios, SOC sequestration peaked 22 ± 1 years after amendment and declined but remained positive throughout the century. Though compost stimulated nitrous oxide (N 2 O) emissions, the cumulative net emissions (in CO 2 equivalents) due to compost were far less than the amount of SOC sequestered. Compost amendments resulted in a net climate benefit of 69.6 ± 0.5 Tg CO 2 e 20 ± 1 years after amendment if applied to similar ecosystems across the state, amounting to 39% of California's rangeland. These results suggest that the biogeochemical benefits of a single amendment of compost to rangelands in California are insensitive to climate change and could contribute to decadal‐scale climate change mitigation goals alongside emissions reductions.

Mayer, Allegra↗

Changes in future air quality, deposition, and aerosol-cloud interactions under future climate and emission scenarios

The prospect of global climate change will have wide scale impacts, such as ecological stress and human health hazards. One aspect of concern is future changes in air quality that will result from changes in both meteorological forcing and air pollutant emissions. In this study, the GU-WRF/Chem model is employed to simulate the impact of changing climate and emissions following the IPCC AR4 SRES A1B scenario. An average of 4 future years (2020, 2030, 2040, and 2050) is compared against an average of 2 current years (2001 and 2010). Under this scenario, by the Mid-21st century global air quality is projected to degrade with a global average increase of 2.5 ppb in the maximum 8-hr O 3 level and of 0.3 mg m 3 in 24-hr average PM2.5. However, PM2.5 changes are more regional due to regional variations in primary aerosol emissions and emissions of gaseous precursor for secondary PM2.5. Increasing NOx emissions in this scenario combines with a wetter climate elevating levels of OH, HO 2 , H 2 O 2 , and the nitrate radical and increasing the atmosphere’s near surface oxidation state. This differs from findings under the RCP scenarios that experience declines in OH from reduced NOx emissions, stratospheric recovery of O 3 , and increases in CH 4 and VOCs. Increasing NO x and O 3 levels enhances the nitrogen and O 3 deposition, indicating potentially enhanced crop damage and ecosystem stress under this scenario. The enhanced global aerosol level results in enhancements in aerosol optical depth, cloud droplet number concentration, and cloud optical thickness. This leads to dimming at the Earth’s surface with a global average reduction in shortwave radiation of 1.2 W m 2 . This enhanced dimming leads to a more moderate warming trend and different trends in radiation than those found in NCAR’s CCSM simulation, which does not include the advanced chemistry and aerosol treatment of GU-WRF/Chem and cannot simulate the impacts of changing climate and emissions with the same level of detailed treatments. This study indicates that effective climate mitigation and emission control strategies are needed to prevent future health impact and ecosystem stress. Further, studies that are used to develop these strategies should use fully coupled models with sophisticated chemical and aerosol-interaction treatments that can provide a more realistic representation of the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

Impacts of climate change on estuarine stratification and implications for hypoxia within a shallow subtropical system

Vertical density stratification often plays an important role in the formation and expansion of coastal hypoxic zones through its effect on near-bed circulation and vertical oxygen flux. However, the impact of future climate change on estuarine circulation is widely unknown. Here, we developed and calibrated a three-dimensional hydrodynamic model for Pensacola Bay, a shallow subtropical estuary in the northeastern Gulf of Mexico. Model simulations based on years 2013–2017 were applied to examine changes in salinity, temperature, and density under future climate scenarios, including increased radiative forcing (IR) and temperature (T), increased freshwater discharge (D), sea level rise (SLR), and wind intensification (W). Simulations showed that the impacts of climate change on modeled state variables varied over time with external forcing conditions. The model demonstrated the potential for sea level rise and increased freshwater discharge to episodically increase vertical density gradients in the Bay. However, increased wind forcing destabilized vertical gradients, at times reducing the spatial extent and duration of stable stratification. For time periods with low freshwater discharge, moderate increases in wind speed (10%) can destabilize density gradients strengthened by increased discharge (10%) and sea level rise (0.48 m). In contrast, destruction of strong density gradients that form near the mid-Bay channel following flood events requires stronger wind forcing. Furthermore, these results highlight the importance of considering natural variability in freshwater and wind forcing, as well as local phenomena that are generally unresolved by global climate models.

54 ENVIRONMENTAL SCIENCES↗

Climate and land cover effects on the temperature of Puget Sound streams: Assessment of Climate and Land Use Impacts on Stream Temperature

We apply an integrated hydrology-stream temperature modeling system, DHSVM-RBM, to examine the response of the temperature of the major streams draining to Puget Sound to land cover and climate change. We first show that the model construct is able to reconstruct observed historic streamflow and stream temperature variations at a range of time scales. We then explore the relative effect of projected future climate and land cover change, including riparian vegetation, on streamflow and stream temperature. Streamflow in summer is likely to decrease as the climate warms especially in snowmelt-dominated and transient river basins despite increased streamflow in their lower reaches associated with urbanization. Changes in streamflow also result from changes in land cover, and changes in stream shading result from changes in riparian vegetation, both of which influence stream temperature. However, we find that the effect of riparian vegetation changes on stream temperature is much greater than land cover change over the entire basin especially during summer low flow periods. Furthermore, while future projected precipitation change will have relatively modest effects on stream temperature, projected future air temperature increases will result in substantial increases in stream temperature especially in summer. These summer stream temperature increases will be associated both with increasing air temperature, and projected decreases in low flows. We find that restoration of riparian vegetation could mitigate much of the projected summer stream temperature increases. We also explore the contribution of riverine thermal loadings to the heat balance of Puget Sound, and find that the riverine contribution is greatest in winter, when streams account for up to 1/8 of total thermal inputs (averaged from December through February), with larger effects in some sub-basins. We project that the riverine impact on thermal inputs to Puget Sound will become greater with both urbanization and climate change in winter but become smaller in summer due to climate change.

Cao, Qian↗

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well as a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.

climate change↗

MSD CoP Webinar: Representing Climate Impacts in Scenaros

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Scenarios of future emissions and land use have been most commonly produced without accounting for the effects that climate impacts linked to those emissions and land use changes may have. The questions of how important such impacts could be, at the regional or global scale, has become an increasingly cogent one. Using the Global Change Analysis Model (GCAM), we implement climate impacts on water supply, agricultural productivity, and energy demand driven by climatic impact drivers whose evolution over the 21st century is representative of a climate consistent with GCAM's reference scenario and compare the output to the reference at both regional and global scales. We show that the impacts from the version of GCAM that uses GDP as an exogenous input are not sufficient to bend emission pathways at the global scale. However, we see effects emerge at the regional scale in terms of emissions, among other metrics linked to water, land and energy. We expect the impacts to become more significant at an aggregate, global scale in a forthcoming version of the model with endogenous GDP. Meanwhile, we document the mechanisms that drive the difference at regional scales which could still be significant in their impacts for individual economies and populations. Presenters: Dr. Claudia Tebaldi (Joint Global Change Research Institute, Pacific Northwest National Laboratory) Moderator(s): Jennifer Morris (MSD CoP SSG member), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 5, 2024 from 1 PM - 2:15 PM ET

Climate Scenarios↗

CO2 induced climatic change and spectral variations in the outgoing terrestrial infrared radiation

The published temperature changes produced in general circulation model simulations of CO2 induced climate modification are used to compute the top of the atmosphere, clear sky outgoing infrared radiance changes expected for doubled CO2. A significant wavenumber shift is produced, with less radiance emerging in the 500-800 per cm (20.0-12.5 micron) CO2 band and with more emerging in the 800-1200 per cm (12.5-8.3 micron) window. The effect varies greatly with latitude. The radiance shift in the 2300 per cm (4.3 micron) region is of the order of 10-30 percent for doubled CO2. It is suggested that the 2300 per cm region be carefully monitored as an aid in detecting the climatic effects of increasing CO2. The change in the wavenumber-integrated radiant exitance is at most a few percent.

Charlock, T. P.↗

Environment-sensitivity functions for gross primary productivity in light use efficiency models

The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO 2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full factorial light use efficiency (LUE) model structure, leading to a collection of 5600 distinct LUE models. Each model was optimized against daily GPP and evapotranspiration fluxes from 196 FLUXNET sites and ranked across sites based on a bootstrap approach. The GPP sensitivity to each environmental factor, including CO 2 fertilization, was shown to be significant, and that none of the previously published model structures performed as well as the best model selected. From daily and weekly to monthly scales, the best model's median Nash-Sutcliffe model efficiency across sites was 0.73, 0.79 and 0.82, respectively, but poorer at annual scales (0.23), emphasizing the common limitation of current models in describing the interannual variability of GPP. Although the best global model did not match the local best model at each site, the selection was robust across ecosystem types. The contribution of light saturation and cloudiness to GPP was observed across all biomes (from 23% to 43%). Temperature and W dominates GPP and LUE but responses of GPP to temperature and W are lagged in cold and arid ecosystems, respectively. The findings of this study provide a foundation towards more robust LUE-based estimates of global GPP and may provide a benchmark for other empirical GPP products.

54 ENVIRONMENTAL SCIENCES↗