Articles | Volume 15, issue 13
https://doi.org/10.5194/gmd-15-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-15-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
12 Jul 2022
Development and technical paper |
| 12 Jul 2022
| 12 Jul 2022
Assimilation of GPM-retrieved ocean surface meteorology data for two snowstorm events during ICE-POP 2018
Xuanli Li
CORRESPONDING AUTHOR
Earth System Science Center, University of Alabama in Huntsville, Huntsville, Alabama, USA
Jason B. Roberts
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
Jayanthi Srikishen
Science and Technology Institute, Universities Space Research Association, Huntsville, Alabama, USA
Jonathan L. Case
ENSCO, Inc./NASA SPoRT Center, Huntsville, Alabama, USA
Walter A. Petersen
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
Gyuwon Lee
Department of Astronomy and Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu, Republic of Korea
Christopher R. Hain
NASA Marshall Space Flight Center, Huntsville, Alabama, USA
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Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-241, https://doi.org/10.5194/gmd-2023-241, 2024
Revised manuscript under review for GMD
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Researchers enhance the WDM6 scheme by incorporating prognostic graupel density. The modification affects graupel characteristics, including fall velocity-diameter and mass-diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating prognostic graupel density for a more realistic portrayal of microphysical properties in weather models.
Wei-Yu Chang, Yung-Chuan Yang, Chen-Yu Hung, Kwonil Kim, and Gyuwon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2023-3147, https://doi.org/10.5194/egusphere-2023-3147, 2024
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The snow density is derived by collocated MRR and Parsivel from the ICE-POP 2017/2018. The PSD from the Parsivel is applied to the T-matrix backscattering simulation and compared with the ZHH from MRR. The bulk density and bulk water fraction are derived from comparing simulated and calculated ZHH. The retrieved bulk density is validated by comparing the snowfall rate measurements from Pluvio. The consistency of snowfall rate confirms the proposed algorithm.
R. Bradley Pierce, Monica Harkey, Allen Lenzen, Lee M. Cronce, Jason A. Otkin, Jonathan L. Case, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 9613–9635, https://doi.org/10.5194/acp-23-9613-2023, https://doi.org/10.5194/acp-23-9613-2023, 2023
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We evaluate two high-resolution model simulations with different meteorological inputs but identical chemistry and anthropogenic emissions, with the goal of identifying a model configuration best suited for characterizing air quality in locations where lake breezes commonly affect local air quality along the Lake Michigan shoreline. This analysis complements other studies in evaluating the impact of meteorological inputs and parameterizations on air quality in a complex environment.
Jason A. Otkin, Lee M. Cronce, Jonathan L. Case, R. Bradley Pierce, Monica Harkey, Allen Lenzen, David S. Henderson, Zac Adelman, Tsengel Nergui, and Christopher R. Hain
Atmos. Chem. Phys., 23, 7935–7954, https://doi.org/10.5194/acp-23-7935-2023, https://doi.org/10.5194/acp-23-7935-2023, 2023
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We performed model simulations to assess the impact of different parameterization schemes, surface initialization datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were run with high-resolution, real-time datasets depicting lake surface temperatures, green vegetation fraction, and soil moisture. The most accurate results were obtained when using high-resolution sea surface temperature and soil datasets to constrain the model simulations.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev., 15, 4529–4553, https://doi.org/10.5194/gmd-15-4529-2022, https://doi.org/10.5194/gmd-15-4529-2022, 2022
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This study evaluates the performance of the four microphysics parameterizations, the WDM6, WDM7, Thompson, and Morrison schemes, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events are selected and classified into three categories (cold-low, warm-low, and air–sea interaction cases). The evaluation focuses on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
Ki-Hong Min, Kao-Shen Chung, Ji-Won Lee, Cheng-Rong You, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-18, https://doi.org/10.5194/gmd-2022-18, 2022
Revised manuscript not accepted
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LETKF underestimated the water vapor mixing ratio and temperature compared to 3DVAR due to a lack of a water vapor mixing ratio and temperature observation operator. Snowfall in GWD was less simulated in LETKF. The results signify that water vapor assimilation is important in radar DA and significantly impacts precipitation forecasts, regardless of the DA method used. Therefore, it is necessary to apply observation operators for water vapor mixing ratio and temperature in radar DA.
Paul Joe, Gyuwon Lee, and Kwonil Kim
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-620, https://doi.org/10.5194/acp-2021-620, 2021
Preprint withdrawn
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Strong gusty wind events were responsible for poor performance of competitors and schedule changes during the PyeongChang 2018 Olympic and Paralympic Winter Games. Three events were investigated and documented to articulate the challenges confronting forecasters which is beyond what they normally do. Quantitative evidence of the challenge and recommendations for future Olympics are provided.
Kwonil Kim, Wonbae Bang, Eun-Chul Chang, Francisco J. Tapiador, Chia-Lun Tsai, Eunsil Jung, and Gyuwon Lee
Atmos. Chem. Phys., 21, 11955–11978, https://doi.org/10.5194/acp-21-11955-2021, https://doi.org/10.5194/acp-21-11955-2021, 2021
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This study analyzes the microphysical characteristics of snow in complex terrain and the nearby ocean according to topography and wind pattern during the ICE-POP 2018 campaign. The observations from collocated vertically pointing radars and disdrometers indicate that the riming in the mountainous region is likely caused by a strong shear and turbulence. The different behaviors of aggregation and riming were found by three different synoptic patterns (air–sea interaction, cold low, and warm low).
Anam M. Khan, Paul C. Stoy, James T. Douglas, Martha Anderson, George Diak, Jason A. Otkin, Christopher Hain, Elizabeth M. Rehbein, and Joel McCorkel
Biogeosciences, 18, 4117–4141, https://doi.org/10.5194/bg-18-4117-2021, https://doi.org/10.5194/bg-18-4117-2021, 2021
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Remote sensing has played an important role in the study of land surface processes. Geostationary satellites, such as the GOES-R series, can observe the Earth every 5–15 min, providing us with more observations than widely used polar-orbiting satellites. Here, we outline current efforts utilizing geostationary observations in environmental science and look towards the future of GOES observations in the carbon cycle, ecosystem disturbance, and other areas of application in environmental science.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, Jung-Hoon Kim, YongHee Lee, and GyuWon Lee
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-100, https://doi.org/10.5194/acp-2021-100, 2021
Preprint withdrawn
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This study examines a strong downslope wind event during ICE-POP 2018 using Doppler lidars, and observations. 3D winds can be well retrieved by
WISSDOM. This is first time to document the mechanisms of strong wind in observational aspect under fine weather. The PGF causing by adiabatic warming and channeling effect are key factors to dominate the strong wind. The values of this study are improving our understanding of the strong wind and increase the predictability of the weather forecast.
Josué Gehring, Alfonso Ferrone, Anne-Claire Billault-Roux, Nikola Besic, Kwang Deuk Ahn, GyuWon Lee, and Alexis Berne
Earth Syst. Sci. Data, 13, 417–433, https://doi.org/10.5194/essd-13-417-2021, https://doi.org/10.5194/essd-13-417-2021, 2021
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This article describes a dataset of precipitation and cloud measurements collected from November 2017 to March 2018 in Pyeongchang, South Korea. The dataset includes weather radar data and images of snowflakes. It allows for studying the snowfall intensity; wind conditions; and shape, size and fall speed of snowflakes. Classifications of the types of snowflakes show that aggregates of ice crystals were dominant. This dataset represents a unique opportunity to study snowfall in this region.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
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The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Hwayoung Jeoung, Guosheng Liu, Kwonil Kim, Gyuwon Lee, and Eun-Kyoung Seo
Atmos. Chem. Phys., 20, 14491–14507, https://doi.org/10.5194/acp-20-14491-2020, https://doi.org/10.5194/acp-20-14491-2020, 2020
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Radar and radiometer observations were used to study cloud liquid and snowfall in three types of snow clouds. While near-surface and shallow clouds have an area fraction of 90 %, deep clouds contribute half of the total snowfall volume. Deeper clouds have heavier snowfall, although cloud liquid is equally abundant in all three cloud types. The skills of a GMI Bayesian algorithm are examined. Snowfall in deep clouds may be reasonably retrieved, but it is challenging for near-surface clouds.
Gwo-Jong Huang, Viswanathan N. Bringi, Andrew J. Newman, Gyuwon Lee, Dmitri Moisseev, and Branislav M. Notaroš
Atmos. Meas. Tech., 12, 1409–1427, https://doi.org/10.5194/amt-12-1409-2019, https://doi.org/10.5194/amt-12-1409-2019, 2019
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This paper proposes a method for snow rate (SR) estimation using observations collected by NASA dual-frequency dual-polarized (D3R) radar during the GPM Cold-season Precipitation Experiment (GCPEx). The new method utilizes dual-wavelength radar reflectivity ratio (DWR) and 2-D-video disdrometer (2DVD) measurements to improve SR estimation accuracy. It is validated by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a Pluvio gauge for an entire GCPEx synoptic event.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386, https://doi.org/10.5194/hess-22-5373-2018, https://doi.org/10.5194/hess-22-5373-2018, 2018
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Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957, https://doi.org/10.5194/hess-22-4935-2018, https://doi.org/10.5194/hess-22-4935-2018, 2018
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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
Hydrol. Earth Syst. Sci., 22, 1351–1369, https://doi.org/10.5194/hess-22-1351-2018, https://doi.org/10.5194/hess-22-1351-2018, 2018
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In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Sungmin O, Ulrich Foelsche, Gottfried Kirchengast, Juergen Fuchsberger, Jackson Tan, and Walter A. Petersen
Hydrol. Earth Syst. Sci., 21, 6559–6572, https://doi.org/10.5194/hess-21-6559-2017, https://doi.org/10.5194/hess-21-6559-2017, 2017
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We evaluate gridded satellite rainfall estimates, from GPM IMERG, through a direct grid-to-grid comparison with gauge data from the WegenerNet Feldbach (WEGN) network in southeastern Austria. As the WEGN data are independent of the IMERG gauge adjustment process, we could analyze the IMERG estimates across its three different runs. Our results show the effects of additional retrieval processes on the final rainfall estimates, and consequently provide IMERG accuracy information for data users.
Min Huang, Gregory R. Carmichael, James H. Crawford, Armin Wisthaler, Xiwu Zhan, Christopher R. Hain, Pius Lee, and Alex B. Guenther
Geosci. Model Dev., 10, 3085–3104, https://doi.org/10.5194/gmd-10-3085-2017, https://doi.org/10.5194/gmd-10-3085-2017, 2017
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Various sensitivity simulations during two airborne campaigns were performed to assess the impact of different initialization methods and model resolutions on NUWRF-modeled weather states, heat fluxes, and the follow-on MEGAN isoprene emission calculations. Proper land initialization is shown to be important to the coupled weather modeling and the follow-on emission modeling, which is also critical to accurately representing other processes in air quality modeling and data assimilation.
John Kochendorfer, Rodica Nitu, Mareile Wolff, Eva Mekis, Roy Rasmussen, Bruce Baker, Michael E. Earle, Audrey Reverdin, Kai Wong, Craig D. Smith, Daqing Yang, Yves-Alain Roulet, Samuel Buisan, Timo Laine, Gyuwon Lee, Jose Luis C. Aceituno, Javier Alastrué, Ketil Isaksen, Tilden Meyers, Ragnar Brækkan, Scott Landolt, Al Jachcik, and Antti Poikonen
Hydrol. Earth Syst. Sci., 21, 3525–3542, https://doi.org/10.5194/hess-21-3525-2017, https://doi.org/10.5194/hess-21-3525-2017, 2017
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Precipitation measurements were combined from eight separate precipitation testbeds to create multi-site transfer functions for the correction of unshielded and single-Alter-shielded precipitation gauge measurements. Site-specific errors and more universally applicable corrections were created from these WMO-SPICE measurements. The importance and magnitude of such wind speed corrections were demonstrated.
Wade T. Crow, Eunjin Han, Dongryeol Ryu, Christopher R. Hain, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 21, 1849–1862, https://doi.org/10.5194/hess-21-1849-2017, https://doi.org/10.5194/hess-21-1849-2017, 2017
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Terrestrial water storage is defined as the total volume of water stored within the land surface and sub-surface and is a key variable for tracking long-term variability in the global water cycle. Currently, annual variations in terrestrial water storage can only be measured at extremely coarse spatial resolutions (> 200 000 km2) using gravity-based remote sensing. Here we provide evidence that microwave-based remote sensing of soil moisture can be applied to enhance this resolution.
Jussi Tiira, Dmitri N. Moisseev, Annakaisa von Lerber, Davide Ori, Ali Tokay, Larry F. Bliven, and Walter Petersen
Atmos. Meas. Tech., 9, 4825–4841, https://doi.org/10.5194/amt-9-4825-2016, https://doi.org/10.5194/amt-9-4825-2016, 2016
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In this study winter measurements collected in Southern Finland are used to document microphysical properties of falling snow. It is shown that a new video imager can be used for such studies. Snow properties do vary between winters.
Hae-Lim Kim, Mi-Kyung Suk, Hye-Sook Park, Gyu-Won Lee, and Jeong-Seok Ko
Atmos. Meas. Tech., 9, 3863–3878, https://doi.org/10.5194/amt-9-3863-2016, https://doi.org/10.5194/amt-9-3863-2016, 2016
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The main contribution of our paper is that we present a method to find optimal polarimetric rainfall algorithms on the Korean Peninsula using the 2-dimensional video disdrometer (2DVD) and Bislsan S-band dual-polarization radar. We believe that this contribution is theoretically and practically relevant because it will help improve rainfall estimation. Our research is of particular interest and use to those who use radar to provide climatic information and forecasting.
J.-E. Lee, G. W. Lee, M. Earle, and R. Nitu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-4157-2015, https://doi.org/10.5194/hessd-12-4157-2015, 2015
Revised manuscript has not been submitted
C. Funk, A. Hoell, S. Shukla, I. Bladé, B. Liebmann, J. B. Roberts, F. R. Robertson, and G. Husak
Hydrol. Earth Syst. Sci., 18, 4965–4978, https://doi.org/10.5194/hess-18-4965-2014, https://doi.org/10.5194/hess-18-4965-2014, 2014
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Western Pacific SST gradients influence eastern East African precipitation in predictable ways. At seasonal and decadal timescales, warm equatorial western Pacific SSTs and cool eastern Pacific SSTs reduce precipitation in East Africa. The gradient between these regions can be used to make reasonably accurate forecasts in one of the world's most food-insecure regions. Recent warming in the western Pacific and stationary eastern Pacific conditions have produced large precipitation declines.
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Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
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Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
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Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
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Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
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This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
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This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
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Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
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Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
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Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
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Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
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This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
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Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
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Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
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Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Cited articles
Alcott, T. and Steenburgh, W.: Snow-to-Liquid Ratio Variability and Prediction at a High-Elevation Site in Utah's Wasatch Mountains, Weather Forecast., 25, 323–337,
https://doi.org/10.1175/2009WAF2222311.1, 2010.
Berg, W., Kroodsma, R., Kummerow, C., McKague, D., Berg, W., Kroodsma, R.,
Kummerow, C. D., and McKague, D. S.: Fundamental Climate Data Records of
Microwave Brightness Temperatures, Remote Sens., 10, 1306,
https://doi.org/10.3390/rs10081306, 2018.
Call, D. A.: Changes in ice storm impacts over time: 1886–2000, Wea.
Climate. Soc., 2, 23–35, https://doi.org/10.1175/2009WCAS1013.1, 2010.
Chang, C. P., Wang, Z., and Hendon, H.: The Asian winter monsoon, in: The
Asian Monsoon, Springer Praxis Books, Springer, Berlin, Heidelberg,
https://doi.org/10.1007/3-540-37722-0_3, 2006.
Changnon, S. A.: Characteristics of ice storms in the United States, J.
Appl. Meteor., 42, 630–639,
https://doi.org/10.1175/1520-0450(2003)042<0630:COISIT>2.0.CO;2, 2003.
Changnon, S. A.: Catastrophic winter storms: An escalating problem, Climatic
Change, 84, 131–139, https://doi.org/10.1007/s10584-007-9289-5, 2007.
Chen, F. and Dudhia, J.: Coupling an advanced land-surface/ hydrology model
with the Penn State/ NCAR MM5 modeling system. Part I: Model description and
implementation, Mon. Weather Rev., 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001.
Chou, M.-D. and Suarez, M. J.: A solar radiation parameterization for
atmospheric studies, NASA Tech. Memo. 104606, NASA, Greenbelt, MD., 40 pp.,
https://ntrs.nasa.gov/citations/19990060930 (last access: 7 July 2022), 1999.
Cucurull, L., Vandenberghe, F., Barker, D., Vilaclara, E., and Rius, A.:
Three-Dimensional Variational Data Assimilation of Ground-Based GPS ZTD and
Meteorological Observations during the 14 December 2001 Storm Event over the
Western Mediterranean Sea, Mon. Weather Rev., 132, 749–763,
https://doi.org/10.1175/1520-0493(2004)132<0749:TVDAOG>2.0.CO;2, 2004.
Curry, J. A., Bentamy, A., Bourassa, M., Bourras, D., Bradley, E., Brunke,
M., Castro, S., Chou, S., Clayson, C., Emery, W., Eymard, L., Cairall, C.,
Kubota, M., Lin, B., Perrie, W., Reeder, R., Renfrew, I., Rossow, W.,
Schulz, J., Smith, S., Webster, P., Wick, G., and Zeng, X.: Seaflux, B.
Am. Meteorol. Soc., 85, 409–424, https://doi.org/10.1175/BAMS-85-3-409, 2004.
De Pondeca, M., Manikin, G. S., Parrish, D. F., Purser, R. J., Wu, W. S.,
DiMego, G., Derber, J. C., Benjamin, S., Horel, J. D., Anderson, L., and
Colman, B.: The status of the real-time mesoscale analysis at NCEP,
Preprints of the 22nd Conference on Weather Analysis and Forecasting/18th
Conference on Numerical Weather Prediction, 24–29 June 2007, Park City, UT, USA, 4A.5, http://ams.confex.com/ams/pdfpapers/124364.pdf (last access: 7 July 2022), 2007.
Edson, J. B., Jampana, V., Weller, R. A., Bigorre, S. P., Plueddemann, A.
J., Fairall, C. W., Miller, S. D., Mahrt, L., Vickers, D., and Hersbach, H.:
On the Exchange of Momentum over the Open Ocean, J. Phys. Oceanogr., 43,
1589–1610, https://doi.org/10.1175/JPO-D-12-0173.1, 2013.
English, J. M., Kren, A. C., and Peevey, T. R.: Improving winter storm
forecasts with observing system simulation experiments (OSSEs). Part II:
Evaluating a satellite gap with idealized and targeted dropsondes, Earth
Space Sci., 5, 176–196, https://doi.org/10.1002/2017EA000350, 2018.
FEMA: FEMA disaster declarations summaries, FEMA [data set],
https://www.fema.gov/api/open/v2/DisasterDeclarationsSummaries (last access: 7 July 2022), 2021.
Fillion, L., Tanguay, M., Lapalme, E., Denis, B., Desgagne, M., Lee, V., Ek,
N., Liu, Z., Lajoie, M., Caron, J., and Pagé, C.: The Canadian Regional
Data Assimilation and Forecasting System, Weather Forecast., 25, 1645–1669,
https://doi.org/10.1175/2010WAF2222401.1, 2010.
Garvert, M., Woods, C., Colle, B., Mass, C., Hobbs, P., Stoelinga, M., and
Wolfe, B.: The 13–14 December 2001 IMPROVE-2 Event. Part II: Comparisons of
MM5 Model Simulations of Clouds and Precipitation with Observations, J.
Atmos. Sci., 62, 3520–3534, https://doi.org/10.1175/JAS3551.1, 2005.
Gehring, J., Oertel, A., Vignon, É., Jullien, N., Besic, N., and Berne, A.: Microphysics and dynamics of snowfall associated with a warm conveyor belt over Korea, Atmos. Chem. Phys., 20, 7373–7392, https://doi.org/10.5194/acp-20-7373-2020, 2020.
Grell, G. A. and Freitas, S. R.: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling, Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, 2014.
Hamill, T., Yang, F., Cardinali, C., and Majumdar, S.: Impact of Targeted
Winter Storm Reconnaissance Dropwindsonde Data on Midlatitude Numerical
Weather Predictions, Mon. Weather Rev., 141, 2058–2065,
https://doi.org/10.1175/MWR-D-12-00309.1, 2013.
Hartung, D. C., Otkin, J. A., Peterson, R. A., Turner, D. D., and Feltz, W.
F.: Assimilation of surface-based boundary-layer profiler observations
during a cool season observation system simulation experiment. Part II:
Forecast assessment, Mon. Weather Rev., 139, 2327–2346,
https://doi.org/10.1175/2011MWR3623.1, 2011.
Hou, A. Y., Kakar R., Neeck, S., Azarbarzin, A., Kummerow, C., Kojima, M.,
Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation Measurement
mission. B. Am. Meteorol. Soc., 95, 701–722,
https://doi.org/10.1175/BAMS-D-13-00164.1, 2014.
Hu, M., Ge, G., Shao, H., Stark, D., Newman, K., Zhou, C., Beck, J., and
Zhang, X.: Grid-point Statistical Interpolation (GSI) User's Guide Version
3.6, NOAA Developmental Testbed Center, 150 pp.,
https://dtcenter.ucar.edu/com-GSI/users/docs/users_guide/GSIUserGuide_v3.6.pdf (last access: 7 July 2022), 2016.
Hu, M., Ge, G., Zhou, C., Stark, D., Shao, H., Newman, K., Beck, J., and Zhang, X.: Grid-point Statistical Interpolation (GSI) User's Guide Version 3.7, NOAA Developmental Testbed Center, 149 pp., https://dtcenter.org/sites/default/files/GSIUserGuide_v3.7_0.pdf (last access: 11 July 2022), 2018.
Jackson, D. L., Wick, G., and Bates, J.: Near-surface retrieval of air
temperature and specific humidity using multisensor microwave satellite
observations, J. Geophys. Res., 111, D10306, https://doi.org/10.1029/2005JD006431,
2006.
Janjic, Z. I.: The step-mountain eta coordinate model: further developments
of the convection, viscous sublayer and turbulence closure schemes, Mon. Weather Rev., 122, 927–945,
https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994.
Kain, J., Goss, S., and Baldwin, M.: The Melting Effect as a Factor in
Precipitation-Type Forecasting, Weather Forecast., 15, 700–714,
https://doi.org/10.1175/1520-0434(2000)015<0700:TMEAAF>2.0.CO;2, 2000.
Kim, S., Kim, H. M., Kim, E.-J., and Shin, H.-C.: Forecast sensitivity to
observations for high-impact weather events in the Korean Peninsula,
Atmosphere, 23, 171–186, https://doi.org/10.14191/Atmos.2013.23.2.171, 2013 (in Korean with English abstract).
Kim, S.-M. and Kim, H. M.: Adjoint-based observation impact of Advanced
Microwave Sounding Unit-A (AMSU-A) on the short-range forecasts in East Asia, Atmosphere, 27, 93–104, https://doi.org/10.14191/Atmos.2017.27.1.093, 2017 (in Korean with English abstract).
Kleist, D. T., Parrish, D. F., Derber, J. C., Treadon, R., Wu, W.-S., and
Lord, S.: Introduction of the GSI into the NCEPs Global Data Assimilation
System, Weather Forecast., 24, 1691–1705,
https://doi.org/10.1175/2009WAF2222201.1, 2009.
Lee, H. S. and Yamashita, T.: On the wintertime abnormal storm waves along
the east coast of Korea, in: Asian and Pacific Coasts 2011, World
Scientific, Hong Kong, 1592–1599, https://doi.org/10.1142/9789814366489_0191, 2011.
Lee, J., Son, S.-W., Cho, H.-O., Kim, J., Cha, D.-H., Gyakum, J. R., and
Chen, D.: Extratropical cyclones over East Asia: climatology, seasonal
cycle, and long-term trend, Clim. Dynam., 54, 1131–1144, https://doi.org/10.1007/s00382-019-05048-w, 2020.
Lee, Y.-Y., Lim, G.-H., and Kug, J.-S.: Influence of the East Asian winter
monsoon on the storm track activity over the North Pacific, J. Geophys. Res.-Atmos., 115, D09102, https://doi.org/10.1029/2009JD012813, 2010.
Mitnik, L. M., Gurvich, I. A., and Pichugin, M. K.: Satellite sensing of
intense winter mesocyclones over the Japan Sea, 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), 24–29 July 2011, Vancouver, BC, Canada, Institute of Electrical and Electronics Engineers (IEEE), 2345–2348, https://doi.org/10.1109/IGARSS.2011.6049680, 2011.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated
squall line: Comparison of one- and two-moment schemes, Mon. Weather Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format),
Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO [data set], https://doi.org/10.5065/Z83F-N512, 2008.
Niziol, T. A., Snyder, W. R., and Waldstreicher, J. S.: Winter weather
forecasting throughout the eastern United States. Part IV: Lake effect snow,
Weather Forecast., 10, 61–77,
https://doi.org/10.1175/1520-0434(1995)010<0061:WWFTTE>2.0.CO;2, 1995.
Novak, D. and Colle, B.: Diagnosing Snowband Predictability Using a
Multimodel Ensemble System, Weather Forecast., 27, 565–585,
https://doi.org/10.1175/WAF-D-11-00047.1, 2012.
Novak, D. R., Brill, K. F., and Hogsett, W. A.: Using percentiles to
communicate snowfall uncertainty, Weather Forecast., 29, 1259–1265,
https://doi.org/10.1175/WAF-D-14-00019.1, 2014.
Oh, S.-H. and Jeong, W.-M.: Extensive monitoring and intensive analysis of
extreme winter-season wave events on the Korean east coast, J. Coastal
Research, 70, 296–301, https://doi.org/10.2112/SI70-050.1, 2014.
O'Hara, B., Kaplan, M., and Underwood, S.: Synoptic Climatological Analyses
of Extreme Snowfalls in the Sierra Nevada, Weather Forecast., 24, 1610–1624,
https://doi.org/10.1175/2009WAF2222249.1, 2009.
Parrish, D. F. and Derber, J.: The National Meteorological Center's spectral statistical interpolation analysis system, Mon. Weather Rev., 120, 1747–1763, https://doi.org/10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2, 1992.
Peevey, T. R., English, J. M., Cucurull, L., Wang, H., and Kren, A.
C.: Improving winter storm forecasts with observing system simulation
experiments (OSSEs). Part I: An idealized case study of three U.S.
storms, Mon. Weather Rev., 146, 1341–1366, https://doi.org/10.1175/MWR-D-17-0160.1, 2018.
Petersen, W., Wolff, D., Chandrasekar, V., Roberts, J., and Case, J.: NASA
Observations and Modeling during ICE-POP, KMA ICE-POP Meeting,
27–30 November 2018, Seoul, Republic of Korea,
https://ntrs.nasa.gov/api/citations/20190001414/downloads/20190001414.pdf?attachment=true (last access: 7 July 2022), 2018.
Powers, J. G., Klemp, J., Skamarock, W., Davis, C., Dudhia, J., Gill, D.,
Coen, J., Gochis, D., Ahmadov, R., Peckham, S., Grell, G., Michalakes, J.,
Trahan, S., Benjamin, S., Alexander, C., Dimego, G., Wang, W., Schwartz, C.,
Romine, G., Liu, Z., Snyder, C., Chen, F., Barlage, M., Yu, W., and Duda,
M.: The weather research and forecasting model: Overview, system efforts,
and future directions, B. Am. Meteorol. Soc., 98, 1717–1737,
https://doi.org/10.1175/BAMS-D-15-00308.1, 2017 (code available at: https://www2.mmm.ucar.edu/wrf/users/download/get_sources.html, last access: 7 July 2022).
Ralph, F., Rauber, R., Jewett, B., Kingsmill, D., Pisano, P., Pugner, P.,
Rasmussen, R., Reynolds, D., Schlatter, T., Stewart, R., Tracton, S., and
Waldstreicher, J.: Improving Short-Term (0–48 h) Cool-Season Quantitative
Precipitation Forecasting: Recommendations from a USWRP Workshop, B.
Am. Meteorol. Soc., 86, 1619–1632, https://doi.org/10.1175/BAMS-86-11-1619, 2005.
Ralph, F. M., Sukovich, E., Reynolds, D., Dettinger, M., Weagle, S., Clark, W., and Neiman, P. J.: Assessment of extreme quantitative Precipitation Forecasts and Development of Regional Extreme Event Thresholds Using Data from HMT-2006 and COOP Observers, J. Hydrometeorol., 11, 1286–1304, https://doi.org/10.1175/2010JHM1232.1, 2010.
Roberts, J. B.: GPM Ground Validation SEA FLUX ICE POP, NASA Global Hydrology Resource Center DAAC, Huntsville, AL, USA [data set], https://doi.org/10.5067/GPMGV/ICEPOP/SEAFLUX/DATA101, 2020.
Roberts, J. B., Clayson, C. A., Robertson, F. R., and Jackson, D.
L.: Predicting near-surface atmospheric variables from Special Sensor
Microwave/Imager using neural networks with a first-guess approach, J.
Geophys. Res., 115, D19113, https://doi.org/10.1029/2009JD013099, 2010.
Roller, C., Qian, J.-H., Agel, L., Barlow, M., and Moron, V.: Winter Weather
Regimes in the Northeast United States, J. Climate, 29, 2963–2980,
https://doi.org/10.1175/JCLI-D-15-0274.1, 2016.
Ryu, S., Song, J. J., Kim, Y., Jung, S.-H., Do, Y., and Lee, G.: Spatial
Interpolation of Gauge Measured Rainfall Using Compressed Sensing,
Asia-Pac. J. Atmos. Sci., 57, 331–345,
https://doi.org/10.1007/s13143-020-00200-7, 2020.
Saslo, S. and Greybush, S. J.: Prediction of lake-effect snow using
convection-allowing ensemble forecasts and regional data assimilation, Weather Forecast., 32, 1727–1744, https://doi.org/10.1175/WAF-D-16-0206.1, 2017.
Schultz, D. M., Steenburgh, W. J., Trapp, R. J., Horel, J., Kingsmill, D.
E., Dunn, L. B., Rust, W. D., Cheng, L., Bansemer, A., Cox, J., Daugherty,
J., Jorgensen, D. P., Meitín, J., Showell, L., Smull, B. F., Tarp, K.,
and Trainor, M.: Understanding Utah winter storms: The Intermountain
Precipitation Experiment, B. Am. Meteorol. Soc., 83, 189–210,
https://doi.org/10.1175/1520-0477(2002)083<0189:UUWSTI>2.3.CO;2, 2002.
Schuur, T., Park, H.-S., Ryzhkov, A., and Reeves, H.: Classification of
Precipitation Types during Transitional Winter Weather Using the RUC Model
and Polarimetric Radar Retrievals, J. Appl. Meteorol. Clim., 51, 763–779,
https://doi.org/10.1175/JAMC-D-11-091.1, 2012.
Skofronick-Jackson, G., Petersen, W., Berg, W., Kidd, C., Stocker, E.,
Kirschbaum, D., Kakar, R., Braun, S., Huffman, G., Iguchi, T., Kirstetter,
P., Kummerow, C., Meneghini, R., Oki, R., Olson, W., Takayabu, Y., Furukawa,
K., and Wilheit, T.: The Global Precipitation Measurement (GPM) mission for
science and society, B. Am. Meteorol. Soc., 98, 1679–1695,
https://doi.org/10.1175/BAMS-D-15-00306.1, 2017.
Smith, A. B.: U.S. Billion-dollar Weather and Climate Disasters, 1980–present (NCEI Accession 0209268), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/stkw-7w73, 2020.
Tomita, H., Hihara, T., and Kubota, M.: Improved Satellite Estimation of
Near-Surface Humidity Using Vertical Water Vapor Profile Information,
Geophys. Res. Lett., 45, 899–906, https://doi.org/10.1002/2017GL076384, 2018.
Tsuboki, K. and Asai, T.: The multi-scale structure and development
mechanism of mesoscale cyclones over the Sea of Japan in winter, J. Meteorol.
Soc. Jpn., 82, 597–621, https://doi.org/10.2151/jmsj.2004.597, 2004.
Wu, W.-S.: Background error for NCEP's GSI analysis in regional mode, Proceeding of the 4th International Symposium on Analysis of Observations in Meteorology and Oceanography, 18–22 April 2005, Prague, Czech Republic, WMO, WWRP 9, WMO-TD 1316, CD-ROM, 2005.
Wu, W.-S., Parrish, D. F., and Purser, R. J.: Three-dimensional variational
analysis with spatially inhomogeneous covariances, Mon. Weather Rev., 130,
2905–2916, https://doi.org/10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2, 2002.
Xiao, Q., Kuo, Y. H., Sun, J., Lee, W. C., Lim, E., Guo, Y. R., and Barker,
D. M.: Assimilation of Doppler Radar Observations with a Regional 3DVAR
System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case,
J. Appl. Meteor., 44, 768–788, https://doi.org/10.1175/JAM2248.1, 2005.
Yang, E.-G. and Kim, H. M.: A comparison of variational, ensemble-based,
and hybrid data assimilation methods over East Asia for two one-month
periods, Atmos. Res., 249, 105257, https://doi.org/10.1016/j.atmosres.2020.105257, 2021.
Yoshiike, S. and Kawamura, R.: Influence of wintertime large-scale
circulation on the explosively developing cyclones over the western North
Pacific and their downstream effects, J. Geophys. Res.-Atmos., 114, D13110,
https://doi.org/10.1029/2009JD011820, 2009.
Zhang, F., Meng, Z., and Aksoy, A.: Tests of an Ensemble Kalman Filter for
Mesoscale and Regional-Scale Data Assimilation. Part I: Perfect Model
Experiments, Mon. Weather Rev., 134, 722–736,
https://doi.org/10.1175/MWR3101.1, 2006.
Zhang, F., Sun, Y. Q., Magnusson, L., Buizza, R., Lin, S.-J., Chen, J.-H.,
and Emanuel, K.: What is the predictability limit of midlatitude weather?, J.
Atmos. Sci., 76, 1077–1091, https://doi.org/10.1175/JAS-D-18-0269.1, 2019.
Zhang, Y., Sperber, K. R., and Boyle, J. S.: Climatology and interannual
variation of the East Asian Winter Monsoon: Results from the 1979–95
NCEP/NCAR reanalysis, Mon. Weather Rev., 125, 2605–2619, https://doi.org/10.1175/1520-0493(1997)125<2605:CAIVOT>2.0.CO;2, 1997.
Zhang, Y., Ding, Y., and Li, Q.: A climatology of extratropical cyclones
over East Asia during 1958–2001, Acta. Meteorol. Sin., 26, 261–277,
https://doi.org/10.1007/s13351-012-0301-2, 2012.
Zupanski, M., Zupanski, D., Parrish, D., Rogers, E., and DiMego, G.:
Four-Dimensional Variational Data Assimilation for the Blizzard of 2000,
Mon. Weather Rev., 130, 1967–1988,
https://doi.org/10.1175/1520-0493(2002)130<1967:FDVDAF>2.0.CO;2, 2002.
Short summary
This research assimilated the Global Precipitation Measurement (GPM) satellite-retrieved ocean surface meteorology data into the Weather Research and Forecasting (WRF) model with the Gridpoint Statistical Interpolation (GSI) system. This was for two snowstorms during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games' (ICE-POP 2018) field experiments. The results indicated a positive impact of the data for short-term forecasts for heavy snowfall.
This research assimilated the Global Precipitation Measurement (GPM) satellite-retrieved ocean...
