Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-365-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-365-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, United States of America
Steven J. Smith
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, United States of America
Ben Bond-Lamberty
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD 20740, United States of America
Related authors
Abigail Snyder, Noah Prime, Claudia Tebaldi, and Kalyn Dorheim
Earth Syst. Dynam., 15, 1301–1318, https://doi.org/10.5194/esd-15-1301-2024, https://doi.org/10.5194/esd-15-1301-2024, 2024
Short summary
Short summary
From running climate models to using their outputs to identify impacts, modeling the integrated human–Earth system is expensive. This work presents a method to identify a smaller subset of models from the full set that preserves the uncertainty characteristics of the full set. This results in a smaller number of runs that an impact modeler can use to assess how uncertainty propagates from the Earth to the human system, while still capturing the range of outcomes provided by climate models.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Claudia Tebaldi, Abigail Snyder, and Kalyn Dorheim
Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, https://doi.org/10.5194/esd-13-1557-2022, 2022
Short summary
Short summary
Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meets these demands in a comprehensive way and may thus support a fully integrated impact research effort and save resources for the climate modeling enterprise.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
Short summary
Short summary
We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
Short summary
Short summary
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-188, https://doi.org/10.5194/essd-2025-188, 2025
Preprint under review for ESSD
Short summary
Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
Short summary
Short summary
The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Abigail Snyder, Noah Prime, Claudia Tebaldi, and Kalyn Dorheim
Earth Syst. Dynam., 15, 1301–1318, https://doi.org/10.5194/esd-15-1301-2024, https://doi.org/10.5194/esd-15-1301-2024, 2024
Short summary
Short summary
From running climate models to using their outputs to identify impacts, modeling the integrated human–Earth system is expensive. This work presents a method to identify a smaller subset of models from the full set that preserves the uncertainty characteristics of the full set. This results in a smaller number of runs that an impact modeler can use to assess how uncertainty propagates from the Earth to the human system, while still capturing the range of outcomes provided by climate models.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
Short summary
Short summary
Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Fei Liu, Steffen Beirle, Joanna Joiner, Sungyeon Choi, Zhining Tao, K. Emma Knowland, Steven J. Smith, Daniel Q. Tong, Siqi Ma, Zachary T. Fasnacht, and Thomas Wagner
Atmos. Chem. Phys., 24, 3717–3728, https://doi.org/10.5194/acp-24-3717-2024, https://doi.org/10.5194/acp-24-3717-2024, 2024
Short summary
Short summary
Using satellite data, we developed a coupled method independent of the chemical transport model to map NOx emissions across US cities. After validating our technique with synthetic data, we charted NOx emissions from 2018–2021 in 39 cities. Our results closely matched EPA estimates but also highlighted some inconsistencies in both magnitude and spatial distribution. This research can help refine strategies for monitoring and managing air quality.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
Short summary
Short summary
We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
Short summary
Short summary
We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Claudia Tebaldi, Abigail Snyder, and Kalyn Dorheim
Earth Syst. Dynam., 13, 1557–1609, https://doi.org/10.5194/esd-13-1557-2022, https://doi.org/10.5194/esd-13-1557-2022, 2022
Short summary
Short summary
Impact modelers need many future scenarios to characterize the consequences of climate change. The climate modeling community cannot fully meet this need because of the computational cost of climate models. Emulators have fallen short of providing the entire range of inputs that modern impact models require. Our proposal, STITCHES, meets these demands in a comprehensive way and may thus support a fully integrated impact research effort and save resources for the climate modeling enterprise.
Steven J. Smith, Erin E. McDuffie, and Molly Charles
Atmos. Chem. Phys., 22, 13201–13218, https://doi.org/10.5194/acp-22-13201-2022, https://doi.org/10.5194/acp-22-13201-2022, 2022
Short summary
Short summary
Emissions into the atmosphere of greenhouse gases (GHGs) and air pollutants, quantified in emission inventories, impact human health, ecosystems, and the climate. We review how air pollutant and GHG inventory activities have historically been structured and their different uses and requirements. We discuss the benefits of increasing coordination between air pollutant and GHG inventory development efforts, but also caution that there are differences in appropriate methodologies and applications.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
Short summary
Short summary
Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Sumanta Sarkhel, Gunter Stober, Jorge L. Chau, Steven M. Smith, Christoph Jacobi, Subarna Mondal, Martin G. Mlynczak, and James M. Russell III
Ann. Geophys., 40, 179–190, https://doi.org/10.5194/angeo-40-179-2022, https://doi.org/10.5194/angeo-40-179-2022, 2022
Short summary
Short summary
A rare gravity wave event was observed on the night of 25 April 2017 over northern Germany. An all-sky airglow imager recorded an upward-propagating wave at different altitudes in mesosphere with a prominent wave front above 91 km and faintly observed below. Based on wind and satellite-borne temperature profiles close to the event location, we have found the presence of a leaky thermal duct layer in 85–91 km. The appearance of this duct layer caused the wave amplitudes to diminish below 91 km.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences, 19, 1435–1450, https://doi.org/10.5194/bg-19-1435-2022, https://doi.org/10.5194/bg-19-1435-2022, 2022
Short summary
Short summary
As carbon (C) and greenhouse gas (GHG) research has adopted appropriate technology and approach (AT&A), low-cost instruments, open-source software, and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility, and performance, the integration of low-cost and low-technology, participatory and networking-based research approaches can be AT&A for enhancing C and GHG research in developing countries.
Jinshi Jian, Xuan Du, Juying Jiao, Xiaohua Ren, Karl Auerswald, Ryan Stewart, Zeli Tan, Jianlin Zhao, Daniel L. Evans, Guangju Zhao, Nufang Fang, Wenyi Sun, Chao Yue, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-87, https://doi.org/10.5194/essd-2022-87, 2022
Manuscript not accepted for further review
Short summary
Short summary
Field soil loss and sediment yield due to surface runoff observations were compiled into a database named AWESOME: Archive for Water Erosion and Sediment Outflow MEasurements. Annual soil erosion data from 1985 geographic sites and 75 countries have been compiled into AWESOME. This database aims to be an open framework for the scientific community to share field-based annual soil erosion measurements, enabling better understanding of the spatial and temporal variability of annual soil erosion.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
Short summary
Short summary
In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
Short summary
Short summary
We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
Short summary
Short summary
We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Dawn L. Woodard, Alexey N. Shiklomanov, Ben Kravitz, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 4751–4767, https://doi.org/10.5194/gmd-14-4751-2021, https://doi.org/10.5194/gmd-14-4751-2021, 2021
Short summary
Short summary
We have added a representation of the permafrost carbon feedback to the simple, open-source global carbon–climate model Hector and calibrated the results to be consistent with historical data and Earth system model projections. Our results closely match previous work, estimating around 0.2 °C of warming from permafrost this century. This capability will be useful to explore uncertainties in this feedback and for coupling with integrated assessment models for policy and economic analysis.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
Short summary
Short summary
Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-85, https://doi.org/10.5194/bg-2021-85, 2021
Manuscript not accepted for further review
Short summary
Short summary
While greenhouse gas (GHG) research has adopted highly advanced technology some have adopted appropriate technology and approach (AT&A) such as low-cost instrument, open source software and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility and performance, integration of low-cost and low-technology, participatory and networking based research approaches can be AT&A for enhancing GHG research in developing countries.
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
Short summary
Short summary
The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
Short summary
Short summary
Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Erin E. McDuffie, Steven J. Smith, Patrick O'Rourke, Kushal Tibrewal, Chandra Venkataraman, Eloise A. Marais, Bo Zheng, Monica Crippa, Michael Brauer, and Randall V. Martin
Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, https://doi.org/10.5194/essd-12-3413-2020, 2020
Short summary
Short summary
Global emission inventories are vital to understanding the impacts of air pollution on the environment, human health, and society. We update the open-source Community Emissions Data System (CEDS) to provide global gridded emissions of seven key air pollutants from 1970–2017 for 11 source sectors and multiple fuel types, including coal, solid biofuel, and liquid oil and natural gas. This dataset includes both monthly global gridded emissions and annual national totals.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Jinshi Jian, Xuan Du, Ryan D. Stewart, Zeli Tan, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-283, https://doi.org/10.5194/essd-2020-283, 2020
Preprint withdrawn
Short summary
Short summary
Field soil loss due to surface runoff observations were compiled into a global database (SoilErosionDB). The database focuses on three erosion-related metrics – surface runoff, soil erosion, and nutrient leaching – and also records background information. Data from 99 geographic sites and 22 countries around the world have been compiled into SoilErosionDB. SoilErosionDB aims to be a data framework for the scientific community to share field-based soil erosion measurements.
Cited articles
Acosta Navarro, J. C., Varma, V., Riipinen, I., Seland, Ø., Kirkevåg, A., Struthers, H., Iversen, T., Hansson, H.-C., and Ekman, A. M. L.: Amplification of Arctic warming by past air pollution reductions in Europe, Nat. Geosci., 9, 277–281, https://doi.org/10.1038/ngeo2673, 2016.
Boas, M. L.: Mathematical Methods in the Physical Sciences, Wiley,
available at: https://books.google.com/books?id=1xV0CgAAQBAJ (last access: 11 January 2021), 2006.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T.,
DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne,
S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M.,
Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K.,
Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U.,
Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C.
S.: Bounding the role of black carbon in the climate system: A scientific
assessment, J. Geophys. Res.-Atmos., 118,
5380–5552, https://doi.org/10.1002/jgrd.50171, 2013.
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre,
M.-F., Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R.,
Ganopolski, A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov,
V., Stone, P., and Wang, Z.: Earth system models of intermediate complexity:
closing the gap in the spectrum of climate system models, Clim. Dynam.,
18, 579–586, https://doi.org/10.1007/s00382-001-0200-1, 2002.
Dorheim, K. and Bond-Lamberty, B.: JGCRI/HIRM: Dorheim et al. 2020 submitted to GMD (Version v1.0.0), Zenodo, https://doi.org/10.5281/zenodo.3756122, 2020.
Dorheim, K., Link, R., Hartin, C., Kravitz, B., and Snyder, A.: Calibrating
simple climate models to individual Earth system models: Lessons learned
from calibrating Hector, Earth Space Sci., 7,
https://doi.org/10.1029/2019EA000980, 2020a.
Dorheim, K. R., Smith, S. J., and Bond-Lamberty, B.: Code and Data for A hybrid impulse response model for climate modeling and uncertainty analyses, OSF, https://doi.org/10.17605/OSF.IO/KMRJ8, 2020b.
Etminan, M., Myhre, G., Highwood, E. J., and Shine, K. P.: Radiative forcing
of carbon dioxide, methane, and nitrous oxide: A significant revision of the
methane radiative forcing, Geophys. Res. Lett., 43,
12614–12623, https://doi.org/10.1002/2016GL071930, 2016.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Fan, J., Wang, Y., Rosenfeld, D., and Liu, X.: Review of Aerosol–Cloud
Interactions: Mechanisms, Significance, and Challenges, J. Atmos. Sci.,
73, 4221–4252, https://doi.org/10.1175/JAS-D-16-0037.1, 2016.
Forest, C. E.: Inferred Net Aerosol Forcing Based on Historical Climate
Changes: a Review, Current Climate Change Reports, 4, 11–22,
https://doi.org/10.1007/s40641-018-0085-2, 2018.
Ghan, S. J., Smith, S. J., Wang, M., Zhang, K., Pringle, K., Carslaw, K., Pierce, J., Bauer, S., and Adams, P.: A simple model of global aerosol indirect effects, J. Geophys. Res.-Atmos., 118, 6688–6707, https://doi.org/10.1002/jgrd.50567, 2013.
Good, P., Gregory, J. M., Lowe, J. A. and Andrews, T.: Abrupt CO2
experiments as tools for predicting and understanding CMIP5 representative
concentration pathway projections, Clim. Dynam., 40, 1041–1053,
https://doi.org/10.1007/s00382-012-1410-4, 2013.
Hartin, C. A., Patel, P., Schwarber, A., Link, R. P., and Bond-Lamberty, B. P.: A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0, Geosci. Model Dev., 8, 939–955, https://doi.org/10.5194/gmd-8-939-2015, 2015.
Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V., Brönnimann, S., Charabi, Y. A. R., Dentener, F. J., Dlugokencky, E. J., Easterling, D. R., Kaplan, A., Soden, B. J., Thorne, P. W., Wild, M., and Zhai, P.: Observations: Atmosphere and surface, in: Climate Change 2013 the Physical Science Basis, Cambridge University Press, 159–254, https://doi.org/10.1017/CBO9781107415324.008, 2013.
Hooss, G., Voss, R., Hasselmann, K., Maier-Reimer, E., and Joos, F.: A
nonlinear impulse response model of the coupled carbon cycle-climate system
(NICCS), Clim. Dynam., 18, 189–202, https://doi.org/10.1007/s003820100170, 2001.
Harvey, L. D. D., Gregory, J. M., Hoffert, M., Jain, A., Lal, M., Leemans, R., Raper, S. C. B., Wigley, T. M. L., and de Wolde, J.: An Introduction to Simple Climate Models used in the IPCC Second Assessment Report: IPCC Technical Paper 2, Tech. rep., Intergovernmental Panel on Climate Change, 1997.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner,
P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb,
W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P.,
Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl,
J., and Marshall, S.: The Community Earth System Model: A Framework for
Collaborative Research, B. Am. Meteorol. Soc.,
94, 1339–1360, https://doi.org/10.1175/BAMS-D-12-00121.1, 2013.
Joos, F. and Bruno, M.: Pulse response functions are cost-efficient tools to
model the link between carbon emissions, atmospheric CO2 and global warming,
Phys. Chem. Earth, 21, 471–476, https://doi.org/10.1016/S0079-1946(97)81144-5, 1996.
Joos, F., Müller-Fürstenberger, G., and Stephan, G.: Correcting the carbon cycle representation: How important is it for the economics of climate change?, Environ. Model. Assess., 4, 133–140, https://doi.org/10.1023/A:1019004015342, 1999.
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F. T., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, 2013.
Kriegler, E.: Imprecise probability analysis for integrated assessment of
climate change, dissertation, 2005.
Link, R., Bond-Lamberty, B., Hartin, C., Shiklomanov, A., bvegawe, Patel,
P., Willner, S., Dorheim, K. R., Gieseke, R., Smith, S., and Lynch, C.:
JGCRI/hector: Hector version 2.3.0, Zenodo, https://doi.org/10.5281/zenodo.3144007, 2019.
Meehl, G. A., Stocker, T. A., Collins, W. D., Friedlingstein, P., Gregory,
J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B.,
Watterson, I. G., Weaver, A. J., and Zhao, Z. C.: Global Climate Projections,
in Climate Change 2007: The Physical Science Basis, Contribution of Working
Group I to the Fourth Assessment Report of the Intergovernmental Panel on
Climate Change, Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA, 2007.
Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C. B., Frieler, K.,
Knutti, R., Frame, D. J., and Allen, M. R.: Greenhouse-gas emission targets
for limiting global warming to 2 ∘C, Nature, 458,
1158–1162, https://doi.org/10.1038/nature08017, 2009.
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011.
Millar, R. J., Otto, A., Forster, P. M., Lowe, J. A., Ingram, W. J., and Allen, M. R.: Model structure in observational constraints on transient climate response, Climatic Change, 131, 199–211, https://doi.org/10.1007/s10584-015-1384-4, 2015.
Millar, R. J., Nicholls, Z. R., Friedlingstein, P., and Allen, M. R.: A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions, Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, 2017.
Myhre, G., Shindell, D., Breon, F. M., Collins, W., Fuglestvedt, J., and
Huang, J.: Anthropogenic and Natural Radiative Forcing, in Climate Change
2013: The Physical Science Basis, Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
Cambridge University Press, 2013.
Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Gieseke, R., Dommenget, D., Dorheim, K., Fan, C.-S., Fuglestvedt, J. S., Gasser, T., Golüke, U., Goodwin, P., Hartin, C., Hope, A. P., Kriegler, E., Leach, N. J., Marchegiani, D., McBride, L. A., Quilcaille, Y., Rogelj, J., Salawitch, R. J., Samset, B. H., Sandstad, M., Shiklomanov, A. N., Skeie, R. B., Smith, C. J., Smith, S., Tanaka, K., Tsutsui, J., and Xie, Z.: Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response, Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, 2020.
Richardson, T. B., Forster, P. M., Smith, C. J., Maycock, A. C., Wood, T.,
Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Hodnebrog, Ø.,
Kasoar, M., Kirkevåg, A., Lamarque, J.-F., Mülmenstädt, J.,
Myhre, G., Olivié, D., Portmann, R. W., Samset, B. H., Shawki, D.,
Shindell, D., Stier, P., Takemura, T., Voulgarakis, A., and Watson-Parris,
D.: Efficacy of Climate Forcings in PDRMIP Models, J. Geophys.
Res.-Atmos., 124, 12824–12844, https://doi.org/10.1029/2019JD030581, 2019.
Sand, M., Iversen, T., Bohlinger, P., Kirkevåg, A., Seierstad, I.,
Seland, Ø., and Sorteberg, A.: A Standardized Global Climate Model Study
Showing Unique Properties for the Climate Response to Black Carbon Aerosols,
J. Climate, 28, 2512–2526, https://doi.org/10.1175/JCLI-D-14-00050.1,
2015.
Schwarber, A. K., Smith, S. J., Hartin, C. A., Vega-Westhoff, B. A., and Sriver, R.: Evaluating climate emulation: fundamental impulse testing of simple climate models, Earth Syst. Dynam., 10, 729–739, https://doi.org/10.5194/esd-10-729-2019, 2019.
Shindell, D. T.: Inhomogeneous forcing and transient climate sensitivity,
Nat. Clim. Change, 4, 274–277, https://doi.org/10.1038/nclimate2136, 2014.
Shine, K. P., Derwent, R. G., Wuebbles, D. J. and Morcrette, J. J.: Radiative forcing of climate, in: Climate Change: The IPCC Scientific Assessment, edited by: Houghton, J. T., Jenkins, G. J., and Ephraums, J. J., Cambridge University Press, Cambridge, UK, 41–68, 1990.
Smith, C. J., Forster, P. M., Allen, M., Leach, N., Millar, R. J., Passerello, G. A., and Regayre, L. A.: FAIR v1.3: a simple emissions-based impulse response and carbon cycle model, Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, 2018a.
Smith, C. J., Kramer, R. J., Myhre, G., Forster, P. M., Soden, B. J.,
Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Hodnebrog, Ø.,
Kasoar, M., Kharin, V., Kirkevåg, A., Lamarque, J.-F.,
Mülmenstädt, J., Olivié, D., Richardson, T., Samset, B. H.,
Shindell, D., Stier, P., Takemura, T., Voulgarakis, A., and Watson-Parris,
D.: Understanding Rapid Adjustments to Diverse Forcing Agents, Geophys.
Res. Lett., 45, 12023–12031, https://doi.org/10.1029/2018GL079826, 2018b.
Smith, S. J. and Bond, T. C.: Two hundred fifty years of aerosols and climate: the end of the age of aerosols, Atmos. Chem. Phys., 14, 537–549, https://doi.org/10.5194/acp-14-537-2014, 2014.
Stainforth, D. A., Aina, T., Christensen, C., Collins, M., Faull, N., Frame,
D. J., Kettleborough, J. A., Knight, S., Martin, A., Murphy, J. M., Piani,
C., Sexton, D., Smith, L. A., Spicer, R. A., Thorpe, A. J., and Allen, M. R.:
Uncertainty in predictions of the climate response to rising levels of
greenhouse gases, Nature, 433, 403–406, https://doi.org/10.1038/nature03301, 2005.
Stocker, T.: Model Hierarchy and Simplified Climate Models, in: Introduction
to Climate Modelling, Advances in Geophysical and Environmental Mechanics
and Mathematics, Springer, Berlin, 25–51, 2011.
Strassmann, K. M. and Joos, F.: The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle–climate simulations, Geosci. Model Dev., 11, 1887–1908, https://doi.org/10.5194/gmd-11-1887-2018, 2018.
Tang, J. and Riley, W. J.: Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions, Nat. Clim. Change, 5, 56–60, https://doi.org/10.1038/nclimate2438, 2015.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/bams-d-11-00094.1, 2012.
Tomassini, L., Reichert, P., Knutti, R., Stocker, T. F., and Borsuk, M. E.:
Robust Bayesian Uncertainty Analysis of Climate System Properties Using
Markov Chain Monte Carlo Methods, J. Climate, 20, 1239–1254,
https://doi.org/10.1175/JCLI4064.1, 2007.
Urban, N. M., Holden, P. B., Edwards, N. R., Sriver, R. L., and Keller, K.:
Historical and future learning about climate sensitivity, Geophys.
Res. Lett., 41, 2543–2552, https://doi.org/10.1002/2014GL059484,
2014.
van Vuuren, D., Lowe, J., Stehfest, E., Gohar, L., Hof, A., Hope, C., Warren,
R., Meinshausen, M., and Plattner, G.-K.: How well do integrated assessment
models imulate cliamte change?, Climatic Change, 104, 255–285,
https://doi.org/10.1007/s10584-009-9764-2, 2011.
Webster, M., Sokolov, A. P., Reilly, J. M., Forest, C. E., Paltsev, S.,
Schlosser, A., Wang, C., Kicklighter, D., Sarofim, M., Melillo, J., Prinn,
R. G., and Jacoby, H. D.: Analysis of climate policy targets under
uncertainty, Climatic Change, 112, 569–583, https://doi.org/10.1007/s10584-011-0260-0, 2012.
Wenzel, S., Cox, P. M., Eyring, V., and Friedlingstein, P.: Emergent constraints on climate-carbon cycle feedbacks in the CMIP5 Earth system models, J. Geophys. Res.-Biogeo., 119, 794–807, https://doi.org/10.1002/2013JG002591, 2014.
Wickham, H. and Hesselberth, J.: pkgdown: Make Static HTML Documentation for
a Package, 2020.
Wigley, T. M. L. and Raper, S. C. B.: Implications for climate and sea level
of revised IPCC emissions scenarios, Nature, 357, 293–300,
https://doi.org/10.1038/357293a0, 1992.
Wigley, T. M. L., Smith, S. J., and Prather, M. J.: Radiative Forcing due to Reactive Gas Emissions, J. Climate, 15, 2690–2696, 2002.
Yang, Y., Smith, S. J., Wang, H., Mills, C. M., and Rasch, P. J.: Variability, timescales, and nonlinearity in climate responses to black carbon emissions, Atmos. Chem. Phys., 19, 2405–2420, https://doi.org/10.5194/acp-19-2405-2019, 2019.
Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
Simple climate models are frequently used in research and decision-making communities because of...