cicsmd

A A A
Print

2022 CISESS Articles

Abushakra, Feras; Nathan Jeong; Deepak N. Elluru; Abhishek K. Awasthi; Shriniwas Kolpuke;  Tuan Luong; Omid Reyhanigalangashi; Drew Taylor; andS. Prasad Gogineni, 2022: A miniaturized ultra-wideband radar for UAV remote sensing applications. IEEE Microwave Wireless Compon. Lett., 32(3), 198-201, https://doi.org/10.1109/LMWC.2021.3129153.  

Campbell, Patrick C.; Youhua Tang, Pius Lee,Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam, 2022a: Development and evaluation of an advanced National Air Quality Forecast Capability using the NOAA Global Forecast System version 16, Geosci. Model Dev., 15(8), 3281–3313, https://doi.org/10.5194/gmd-2021-316.

Campbell, Patrick, Tong, Daniel, Rick Saylor, Yunyao Li, Siqi Ma, Xiaoyang Zhang, Shobha Kondragunta and Fangjun Li, 2022b:  Pronounced increases in nitrogen emissions and deposition due to the historic 2020 wildfires in the western U.S., Sci. Total Environ., 839, 156130, https://doi.org/10.1016/j.scitotenv.2022.156130.

Cao, Changyong, Bin Zhang, Frank Xia, and Yan Bai, 2022: Exploring VIIRS night light long-term time series with CNN/SI for urban change detection and aerosol monitoring. Remote Sens., 14(13), 3126, https://doi.org/10.3390/rs14133126.

Chang, Yue; Jingfeng Xiao, Xuxiang Li, Steve Frolking, Decheng Zhou, Annemarie Schneider, Qihao Weng, Peng Yu, Xufeng Wang, Xing Li, Shuguang Liu and Yiping Wu, 2022: Exploring diurnal cycles of surface urban heat island intensity in Boston with land surface temperature data derived from GOES-R geostationary satellites, Sci. Total Environ., 763, 144224, https://doi.org/10.1016/j.scitotenv.2020.144224.

Chen, Yong, I.-S. Flavio, D. Tremblay, D. Tobin, Larabee Strow, Likun Wang, D. L. Mooney, D. Johnson, J. Predina, L. Suwinski, H. E. Revercomb, N. Sun, Bin Zhang, C. Cao, S. Kalluri and L. Zhou, 2022: Reprocessing of Suomi NPP CrIS Sensor Data Records to improve the radiometric and spectral long-term accuracy and stability, in IEEE Transactions on Geoscience and Remote Sensing, 60, 5502714, https://dx.doi.org/10.1109/TGRS.2021.3060639.

Choi, Taeyoung, Changyong Cao, Xi Shao, andWenhui Wang, 2022: S-NPP VIIRS lunar calibrations over 10 years in reflective solar bands (RSB). Remote Sens.14, 3367, https://doi.org/10.3390/rs14143367.

Crawford, Alice; Chai, Tianfeng; Wang, Binyu; Ring, Allison; Stunder, Barbara; Loughner, Christopher P.; Pavolonis, Michael, and Sieglaff, Justin, 2022: Evaluation and bias correction of probabilistic volcanic ash forecasts, Atmos. Chem. Phys., 22(21), 13967–13996, https://doi.org/10.5194/acp-22-13967-2022.

Dennis, Eli J.; andE. Hugo Berbery, 2022: The effects of soil representation in WRF/CLM on the atmospheric moisture budget. J. Hydrometeor., 23(5), 681–696, , http://dx.doi.org/10.1175/JHM-D-21-0101.1

Fang,Li;  Xiwu Zhan, Satya Kalluri, Peng Yu, Chris Hain, Martha Anderson and Istvan Laszlo, 2022: Application of a machine learning algorithm in generating an evapotranspiration data product from coupled thermal infrared and microwave satellite observations. Front. Big Data, 5, 768676, https://doi.org/10.3389/fdata.2022.768676

Frame, Jonathan M.; Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shelev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta and Grey S. Nearing, 2022: Deep learning rainfall–runoff predictions of extreme events. Hydrol. Earth Syst. Sci., 26, 3377–3392, https://doi.org/10.5194/hess-26-3377-2022.

Galarneau, Thomas J., Jr., Louis J. Wicker, Kent H. Knopfmeier, William J. S. Miller, Patrick S. Skinner, and Katie A. Wilson, 2022: Short-term prediction of a nocturnal significant tornado outbreak using a convection-allowing ensemble. Wea. Forecasting37(6), 1027–1047,  https://doi.org/10.1175/WAF-D-21-0160.1

Gardner, Wilford D., Mary Jo Richardson, Alexey Mishonov, Pheobe  Lam and Yang Xiang, 2022a: Distribution, sources, and dynamics of particulate matter along trans-Arctic sections. J. Geophys. Res. Oceans, 127(6), e2021JC017970,https://doi.org/10.1029/2021JC017970 [in Special Section on Uncovering the Hidden Links between Dynamics, Chemical, Biogeochemical and Biological Processes under the Changing Arctic].

Gardner, Wilford D.; Mary Jo Richardson, Alexey V. Mishonov, Daniel A. Bean and Juan Carlos Herguera, 2022b: Nepheloid layers in the deep Gulf of Mexico. Mar. Geol., 454, 106950, https://doi.org/10.1016/j.margeo.2022.106950.

Garrett, Kevin, Hui Liu, Kayo Ide, Ross Hoffman and Katherine Lukens, 2022: Optimization and impact assessment of Aeolus HLOS wind data assimilation in NOAA’s Global Forecast System. Quart. J. Roy. Meteor. Soc. B, 148, 2703, https://doi.org/10.1002/qj.4331.

Godin-Beekmann,Sophie; Niramson Azouz, Viktoria F. Sofieva, Daan Hubert, Irina Petropavlovskikh, Peter Effertz, Gérard Ancellet, Doug A. Degenstein, Daniel Zawada, Lucien Froidevaux, Stacey Frith, Jeannette Wild, Sean Davis, Wolfgang Steinbrecht, Thierry Leblanc, Richard Querel, Kleareti Tourpali, Robert Damadeo, Eliane Maillard Barras, René Stübi, Corinne Vigouroux, Carlo Arosio, Gerald Nedoluha, Ian Boyd, Roeland Van Malderen, Emmanuel Mahieu, Dan Smale, and Ralf Sussmann, 2022: Updated trends of the stratospheric ozone vertical distribution in the 60° S–60° N latitude range based on the LOTUS regression model. Atmos. Chem. Phys., 22(17), 11657–11673, https://doi.org/10.5194/acp-22-11657-2022.

He, Wenchong, Arpan Man Sainju,Zhe Jiang, Da Yan, and Yang Zhou, 2022b: Earth imagery segmentation on terrain surface with limited training labels: A Semi-supervised approach based on physics-guided graph co-training. ACM Trans. Intell. Syst. Technol., 13(2), 26, https://doi.org/10.1145/3481043.

Hoffman, Ross N.; Lukens, Katherine E.; Ide, Kayo; and Garrett, Kevin: 2022:, A collocation study of atmospheric motion vectors (AMVs) compared to aeolus wind profiles with a feature track correction (FTC) observation operator. Quart. J. Roy. Meteor. Soc. Pt. A, 148, 321-337, https://doi.org/10.1002/qj.4207.

Huang, Xinzhou, Kai Yang, Shobha Kondragunta, Zigang Wei, Lukas Valin, James Szykman and Mitch Goldberg, 2022: NO2 retrievals from NOAA-20 OMPS: Algorithm, evaluation, and observations of drastic changes during COVID-19. Atmos. Environ., 290, 119367, https://doi.org/10.1016/j.atmosenv.2022.119367.

Iturbide Sanchez, Flavio, Larrabee Strow, David Tobin, Yong Chen , Denis Tremblay, Robert O. Knuteson, David G. Johnson, Clayton Buttles, Lawrence Suwinski, Bruce P. Thomas, Adhemar R. Rivera, Erin Lynch, Kun Zhang, Zhipeng Wang, Warren D. Porter, Xin Jin , Joseph P. Predina, Reima I. Eresmaa, Andrew Collard, Benjamin Ruston, James A. Jung, Christopher D. Barnet, Peter J. Beierle, Banghua Yan , Daniel Mooney, and Henry Revercomb, 2022: Recalibration and assessment of the SNPP CrIS instrument: A successful history of restoration after midwave infrared band anomaly. IEEE Trans. Geosci. Remote Sens., 60, 5514421, https://doi.org/10.1109/TGRS.2021.3112400.   

Jia, Aolin; Dongdong Wang, Shunlin Liang, Jingjing Peng, & Yunyue Yu, 2022a:. Global daily actual and snow-free blue-sky land surface albedo climatology from 20-year MODIS products. J. Geophys. Res. Atmos., 127(8), e2021JD035987, https://doi.org/10.1029/2021JD035987.

Jiang, Li-Qing, Pierrot Denis, Wanninkhof Rik, Feely Richard A., Tilbrook Bronte, Alin Simone, Barbero Leticia, Byrne Robert H., Carter Brendan R., Dickson Andrew G., Gattuso Jean-Pierre, Greeley Dana, Hoppema Mario, Humphreys Matthew P., Karstensen Johannes, Lange Nico, Lauvset Siv K., Lewis Ernie R., Olsen Are, Pérez Fiz F., Sabine Christopher, Sharp Jonathan D., Tanhua Toste, Trull Thomas W., Velo Anton, Allegra Andrew J., Barker Paul, Burger Eugene, Cai Wei-Jun, Chen Chen-Tung A., Cross Jessica, Garcia Hernan, Hernandez-Ayon Jose Martin, Hu Xinping, Kozyr Alex, Langdon Chris, Lee Kitack, Salisbury Joe, Wang Zhaohui Aleck, Xue Liang, 2022: Best practice data standards for discrete chemical oceanographic observations. Front. Mar. Sci., 8, https://www.frontiersin.org/articles/10.3389/fmars.2021.705638.

Jing, Xin, Sirish Uprety, Tung-Chang Liu, Bin Zhang, andXi Shao, 2022: Evaluation of SNPP and NOAA-20 VIIRS datasets using RadCalNet and Landsat 8/OLI data. Remote Sens., 14(16), 3913, https://doi.org/10.3390/rs14163913.

Kalluri, S., Barnet, C., Divakarla, M., Esmaili, R., Nalli, N., Pryor, K., Reale, T., Smith, N., Tan, C., Wang, T., Warner, Juying Xun, Wilson, M., Zhou, L., & Zhu, T., 2022:. Validation and utility of satellite retrievals of atmospheric profiles in detecting and monitoring significant weather events, Bull. Amer. Meteor. Soc., 103(2), E570-E590,https://doi.org/10.1175/BAMS-D-20-0126.1.

Kim, Edward; Saji Abraham, Joel Amato, William Blackwell, Peter Cho, James Fuentes, Mark Hernquist, James Kam, R. Vincent Leslie, Quanhua Liu, ChengHsuan Lyu, Taichien Mao, Idahosa Osaretin, Fabian Rodriguez-Gutierrez, MatthewSammons, Craig Smith, Ninghai Sun and Hu Yang, 2022: An evaluation of NOAA-20 ATMS instrument pre-launch and on-orbit performance characterization. IEEE Trans. Geosci. Remote Sens., 60, 5302813, https://doi.org/10.1109/TGRS.2022.3148663.

Kotsakis, Alexander, John T. Sullivan, Thomas F. Hanisco, Robert J. Swap, Vanessa Caicedo, Timothy A. Berkoff, Guillaume Gronoff, Christopher P. Loughner, Xinrong Ren, Winston T. Luke, Paul Kelley, Phillip R. Stratton, Ruben Delgado, Nader Abuhassan, Lena Shalaby, Fernando C. Santos, Joel Dreessen, 2022: Sensitivity of total column NO2 at a marine site within the Chesapeake Bay during OWLETS-2, Atmos. Environ., 277, 119063, https://doi.org/10.1016/j.atmosenv.2022.119063.

Krishnamurthy, Venkataramanaia, and Cristiana Stan, 2022: Prediction of extreme events in precipitation and temperature over CONUS during boreal summer in the UFS coupled model. Climate Dyn., 59(1–2), 109–125, https://doi.org/10.1007/s00382-021-06120-0.

Lauvset, S. K., Lange, N., Tanhua, T., Bittig, H. C., Olsen, A., Kozyr, A., Alin, S. R., Álvarez, M., Azetsu-Scott, K., Barbero, L., Becker, S., Brown, P. J., Carter, B. R., da Cunha, L. C., Feely, R. A., Hoppema, M., Humphreys, M. P., Ishii, M., Jeansson, E.,Jiang, L.-Q., Jones, S. D., Lo Monaco, C., Murata, A., Müller, J. D., Pérez, F. F., Pfeil, B., Schirnick, C., Steinfeldt, R., Suzuki, T., Tilbrook, B., Ulfsbo, A., Velo, A., Woosley, R. J., and Key, R. M., 2022: GLODAPv2.2022: The latest version of the global interior ocean biogeochemical data product, Earth Syst. Sci. Data., 14(12), 5543–5572, https://doi.org/10.5194/essd-14-5543-2022.

Lauvset, Siv K.; Nico Lange, Toste Tanhua, Henry C. Bittig, Are Olsen, Alex Kozyr, Simone Alin, Marta Álvarez, Kumiko Azetsu-Scott, Leticia Barbero, Susan Becker, Peter J. Brown, Brendan R. Carter, Leticia Cotrim da Cunha, Richard A. Feely, Mario Hoppema, Matthew P. Humphreys, Masao Ishii, Emil Jeansson, Li-Qing Jiang, Steve D. Jones, Claire Lo Monaco, Akihiko Murata, Jens Daniel Müller, Fiz F. Pérez, Benjamin Pfeil, Carsten Schirnick, Reiner Steinfeldt, Toru Suzuki, Bronte Tilbrook, Adam Ulfsbo, Anton Velo, Ryan J. Woosley, and Robert M. Key, 2022: GLODAPv2.2022: the latest version of the global interior ocean biogeochemical data product, Earth Syst. Sci. Data, 14, 5543–5572, https://doi.org/10.5194/essd-14-5543-2022.

Lazar, Jay; Ronald L. Vogel, David G. Bruce, and Andrew McGowan, 2022: Using Satellite-Derived Total Suspended Matter Data to Evaluate the Impacts of Tributary-Scale Oyster Restoration on Water Clarity. NOAA Tech. Memo NMFS-OHC-10, 19 pp., https://doi.org/10.25923/7dqh-6825.

Lee, Yong-Keun, Christopher Grassotti, Quanhua (Mark) Liu, Shu-Yan Liu and Yan Zhou, 2022: In-depth evaluation of MiRS total precipitable water from NOAA-20 ATMS using multiple reference data sets. Earth Space Sci., 9, e2021EA002042, https://doi.org/10.1029/2021EA002042.

Liang, Xingming, Kevin Garrett, Quanhua Liu, Eric S. Maddy, Kayo Ide, and Sid Boukabara, 2022a: A deep learning-based microwave radiative transfer emulator for data assimilation and remote sensing. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15(Oct 2022), 8819–8833,  https://dx.doi.org/10.1109/JSTARS.2022.3210491.

Lin, Lin; and Xiaolei Zou, 2022: Associations of hurricane intensity changes to satellite total column ozone structural changes within hurricanes.  in IEEE Trans. Geosci. Remote Sens., 60, 4103407, https://doi.org/10.1109/TGRS.2021.3094107.

Little, Christine M., Gang Liu, Jacqueline L. De La Cour, C. Mark Eakin, Derek Manzello and Scott F. Heron, 2022: Global coral bleaching event detection from satellite monitoring of extreme heat stress. Front. Mar. Sci., 9, 883271, https://doi.org/10.3389/fmars.2022.883271  [in special issue onMarine and Coastal Environments under Extreme Stress].

Liu, Chunying, Eric Freeman, Elizabeth C. Kent, David I. Berry, Steven J. Worley, Shawn R. Smith, Boyin Huang, Huai-min Zhang, Thomas Cram, Zaihua Ji, Mathieu Ouellet, Isabelle Gaboury, Frank Oliva, Axel Andersson, William E. Angel, Angela R. Sallis, and Adedoja Adeyeye, 2022: Blending TAC and BUFR marine in situ data for ICOADS Near-Real-Time Release 3.0.2. J. Atmos. Oceanic Technol., in press, https://doi.org/10.1175/JTECH-D-21-0182.1.

Liu, Hui, Kevin Garrett,Kayo Ide, Ross Hoffman, andKatherine Lukens: 2022: A statistically optimal analysis of systematic differences between Aeolus HLOS Winds and NOAA’s Global Forecast System, Atmos. Meas. Tech., 15, 3925–3940, https://doi.org/10.5194/amt-15-3925-2022.

Liu, Quanhua; Banghua Yan; Kevin Garrett; Yingtao Ma; Xingming Liang; Jingfeng Huang; Wenhui Wang; and Changyong Cao, 2022: Deriving surface reflectance from visible/near infrared and ultraviolet satellite observations through the Community Radiative Transfer Model. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15, 2004-2011, https://doi.org/10.1109/JSTARS.2022.3149767

Liu, Quanhua;Yong-Keun Lee, Christopher Grassotti, XingMing Liang, Stanley Q. Kidder and Sheldon Kusselson, 2022: The challenge of surface type changes over the Aral Sea for satellite remote sensing of precipitation.IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15 (Oct 2022), 8650–8655, https://doi.org/10.1109/JSTARS.2022.3212647. (Published 10 October 2022)

Liu, Shuyan, Christopher Grassotti, Quanhua Liu, Yan Zhou, and Yong-Keun Lee, 2022: Improvement of MiRS Sea Surface Temperature Retrievals Using a Machine Learning Approach. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15, 1857-1868, https://dx.doi.org/10.1109/JSTARS.2022.3151002.

Liu, Shuyan, Christopher Grassotti, Quanhua Liu, Yan Zhou, and Yong-Keun Lee, 2022: Improvement of AMSR2 Snow Water Equivalent Retrievals Retrievals Using a Machine Learning Approach. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15, 1857-1868, https://dx.doi.org/10.1109/JSTARS.2022.3151002.

Liu, Yuling, Peng Yu, Heshun Wang, Jingjing Peng, and Yunyue Yu, 2022: Ten years of VIIRS land surface temperature product validation. Remote Sens., 14(12), 2863, https://doi.org/10.3390/rs14122863.

McWhorter, Jennifer K.; Paul R. Halloran; George Roff; William J. Skirving and Peter J. Mumby, 2022: Climate refugia on the Great Barrier Reef fail when global warming exceeds 3°C. Global Change Biol., 28, 5768–5780,  https://dx.doi.org/10.1111/gcb.16323.

Moradi, Isaac,Patrick Stegmann, Benjamin Johnson, Vasileios Barlakas, Patrick Eriksson, Alan Geer, Ronald Gelaro, Satya Kalluri, Daryl Kleist, Quanhua Liu, Will McCarty, 2022: Implementation of a discrete dipole approximation scattering database into community radiative transfer model. J. Geophys. Res. Atmos., 127(24), e2022JD036957, https://doi.org/10.1029/2022JD036957.

Moreno, Allison R.; Alyse A. Larkin, Jenna A. Lee, Skylar D. Gerace, Glen A. Tarran and Adam C. Martiny, 2022:. Regulation of the respiration quotient across ocean basins. AGU Adv., 3(5), e2022AV000679. https://doi.org/10.1029/2022AV000679.

Nezlin, Nikolay P.; Jeremy M. Testa, Guangming Zheng, and Paul M. DiGiacomo, 2022: Satellite observations estimating the effects of river dischargeand wind‐driven upwelling on phytoplankton dynamicsin the Chesapeake Bay.Integr. Environ. Assess. Manage., 18(4), 921–938, https://doi.org/10.1002/ieam.4597.

Nyadjro, Ebenezer. S.; Zhankun Wang, James Reagan, Just Cebrian and Jay F. Shriver, 2022: Bio-physical changes in the Gulf of Mexico during the 2018 Hurricane Michael,IEEE Geosci. Remote Sens. Lett., 19, 1002205, https://dx.doi.org/10.1109/LGRS.2021.3068600.

Orescanin, Marko; Veljko Petković, Scott W. Powell, Benjamin R. Marsh and Sean C. Heslin, 2022: Bayesian Deep Learning for passive microwave precipitation type detection, IEEE Geosci. Remote Sens. Lett., 19, 4500705,  https://dx.doi.org/10.1109/LGRS.2021.3090743

Orescanin, Marko; Veljko Petković, Scott W. Powell, Benjamin R. Marsh and Sean C. Heslin, 2022: Bayesian Deep Learning for passive microwave precipitation type detection, IEEE Geosci. Remote Sens. Lett., 19, 4500705,  https://dx.doi.org/10.1109/LGRS.2021.3090743

Ortiz, Pedro; Orescanin, Marko; Petković, Veljko; Powell, Scott W.; Marsh, Benjamin, 2022: Decomposing satellite-based classification uncertainties in large Earth science datasets. IEEE Trans. Geosci. Remote Sens., 60, 4106211, https://doi.org/10.1109/TGRS.2022.3152516.

Pinker, Rachel T.; Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels, 2022: Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R. Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022.

Poterjoy, Jonathan, 2022: Implications of Multivariate non-gaussian data assimilation for multi-scale weather prediction. Mon. Wea. Rev.,150, 1475-1493,https://doi.org/10.1175/MWR-D-21-0228.1.

Reyhanigalangashi, Omid; Taylor, Drew; Kolpuke, Shriniwas; Elluru, Deepak N.; Abushakra, Feras; Awasthi, Abhishek K.;  and Gogineni, Siva-Prasad, 2022: An RF-SoC-Based Ultra-Wideband Chirp Synthesizer, IEEE Access, 10, pp. 47715-47725, 2022, https://dx.doi.org/10.1109/ACCESS.2022.3171830.

Rishmawi, Khaldoun; Chengquan Huang; Karen Schleeweis and Xiwu Zhan, 2022: Integration of VIIRS observations with GEDI-lidar measurements to monitor forest structure dynamics from 2013 to 2020 across the Conterminous United States. Remote Sens. 2022, 14(10), 2320. https://doi.org/10.3390/rs14102320.

Seo, Eunkyo, and Paul Alan Dirmeyer, 2022: Understanding the diurnal cycle of land-atmosphere interactions from flux site observations. Hydrol. Earth Syst. Sci., 26(20), 5411–5429, https://doi.org/10.5194/hess-26-5411-2022.

Seo, Eunkyo, and Paul Dirmeyer, 2022: Improving the ESA CCI daily soil moisture time series with physically-based land surface model datasets using a Fourier time-filtering method. J. Hydrometeor., 23(3), 473–489, https://doi.org/10.1175/JHM-D-21-0120.1.

Shao, Xi,Francis P. Padula, Changyong Cao, Xiangqian Wu, Fangfang Yu, Aaron Pearlman, Haifeng Qian, Sirish Uprety and Taeyoung Choi, 2022: Validation of geostationary operational environmental satellite-16 advanced baseline imager radiometric calibration with airborne field campaign data and reanalysis of north-south scan data.J. Appl. Remote Sens., 16(3), 037501, https://doi.org/10.1117/1.JRS.16.037501.

Sharp, J. D., A. J. Fassbender, B. R. Carter, Piage D. Lavin and A. J. Sutton, 2022: A monthly surface pCO2  product for the California Current Large Marine Ecosystem, Earth Syst. Sci. Data., 14, 2081–2108, https://doi.org/10.5194/essd-14-2081-2022.

Spady, Blake L.; William J. Skirving, Gang Liu, Jacqueline L. De La Cour,Cathy J. McDonald and Derek P. Manzello, 2022: Unprecedented early-summer heat stress and forecast of coral bleaching on the Great Barrier Reef, 2021-2022. F1000Research 2022, 11, 127 https://doi.org/10.12688/f1000research.108724.1.

Sun, Luyu, Stephen G. Penny, and Matthew Harrison, 2022: Impacts of the Lagrangian data assimilation of surface drifters on estimating ocean circulation during the Gulf of Mexico Grand Lagrangian Deployment. Mon. Wea. Rev., 150, 949-965,  https://doi.org/10.1175/MWR-D-21-0123.1.

Tang, Youhua; Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang: 2022: Evaluation of the NAQFC driven by the NOAA Global ForecastSystem (version 16): comparison with the WRF-CMAQ duringthe summer 2019 FIREX-AQ campaign.  Geosci. Model Dev., 15(21), 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022.

Tanioka, Tatsuro; Catherine A. Garcia, Alyse A. Larkin, Nathan S. Garcia, Adam J. Fagan &Adam C. Martiny, 2022: Global patterns and predictors of C:N:P in marine ecosystems. Commun. Earth Environ., 3, 271, https://doi.org/10.1038/s43247-022-00603-6.

Tian, Jingjing; Yunyan Zhang, Stephen A. Klein, Rusen Öktem and Likun Wang, 2022: How does land cover and its heterogeneity length scales affect the formation of summertime shallow cumulus clouds in observations from the US Southern Great Plains? Geophys. Res. Lett., 49(7), e2021GL097070. https://doi.org/10.1029/2021GL097070.

Tian, Miao; Taidong Zhang; Guanghui Liu and Lin Lin, 2022: Estimation of tropical cyclone intensity using synthetic satellite microwave temperature anomaly structure and a multi-feature distribution learning network. IEEE Trans. Geosci. Remote Sens., 60, 4105512, https://doi.org/10.1109/TGRS.2021.3132620.

Wang, Wenhui,Changyong Cao and Slawomir Blonski, 2022a: Estimating the VIIRS thermal emissive band response versus scan (RVS) and calibration offsets using on-orbit pitch maneuver data. IEEE Trans. Geosci. Remote Sens., 60, 5002610, https://dx.doi.org/10.1109/TGRS.2022.3181233.

Wang, Wenhui; Changyong Cao, Slawomir Blonski, Yalong Gu, Bin Zhang and Sirish Uprety, 2022b: An improved method for VIIRS radiance limit verification and saturation rollover flagging. IEEE Trans. Geosci. Remote Sens., 60, 5403011, https://doi.org/10.1109/TGRS.2021.3097896.

Wang, Wenhui; Changyong Cao, Xi Shao, Slawomir Blonski, Taeyoung Choi, Sirish Uprety, Bin Zhang, and Yan Bai, 2022c: Evaluation of 10-Year NOAA/NASA Suomi NPP and NOAA-20 VIIRS reflective solar band (RSB) sensor data records (SDR) over deep convective clouds. Remote Sens., 14(15), 3566. https://doi.org/10.3390/rs14153566. In the special issue on VIIRS 2011–2021: Ten Years of Success in Earth Observations.

Wang, Zhipeng, Flavio Iturbide-Sanchez, Peter Beierle, Kun Zhang, and Denis Tremblay, 2022: Validation of CrIS radiometric performance through its comparison to ABI. Remote Sens., 14(4), 876. https://doi.org/10.3390/rs14040876.

Yan, Banghua, Chunhui Pan, Trevor Beck, Xin Jin, Likun Wang, Ding Liang, Lawrence Flynn, Junye Chen, Jingfeng Huang, Steven Buckner, Cheng-Zhi Zou, Ninghai Sun, Lin Lin, Alisa Young, Lihang Zhou and Wei Hao, 2022. New reprocessing towards life-time quality-consistent Suomi NPP OMPS Nadir Sensor Data Records (SDR): Calibration improvements and impact assessments on long-term quality stability of OMPS SDR data sets. Remote Sens., 14, 3125, https://doi.org/10.3390/rs14133125.

Yang, John Xun, Yalei You, William Blackwell, Sidharth Misra and Rachael A. Kroodsma, 2022a: Quantifying and characterizing striping of microwave humidity sounder with observation and simulation, IEEE Trans. Geosci. Remote Sens., 60, 5302413, https://dx.doi.org/10.1109/TGRS.2021.3132560.

Yang, John Xun; and Hu Yang, 2022c: A new algorithm for determining the noise equivalent delta temperature of in-orbit microwave radiometers, IEEE Trans. Geosci. Remote Sens., 60, 1-11, 5301611, https://dx.doi.org/10.1109/TGRS.2021.3097594.

Yang, John Xun; Yalei You, William Blackwell, Quanhua Liu, Ralph Ferraro, David Draper, Nigel Atkinson, Tim Hewison, Sidharth Misra and Jinzheng Peng: 2022b: An adaptive calibration window for noise reduction of satellite microwave radiometers. IEEE Trans. Geosci. Remote Sens., 60, 5304616, https://doi.org/10.1109/TGRS.2022.3184670.

Yi, Donghui; Alejandro Egido; Waler H.F. Smith; Laurence Connor; Christopher Buchhaupt and Dexin Zhang, 2022: Sea-ice surface elevation distribution from NASA’s Operation IceBridge ATM data.Remote Sens., 14, 3011. https://doi.org/10.3390/rs14133011.

Yin, Jifu, Xiwu Zhan, Jicheng Liu, and Ralph R. Ferraro, 2022: A new method for generating the SMOPS blended satellite soil moisture data product without relying on a model climatology. Remote Sens., 14(7), 1700, https://doi.org/10.3390/rs14071700.

You, Yalei, Huan Meng, Jun Dong, John Xun Yang, Sarah Ringerud and Yongzhen Fan, 2022b: Precipitation phase determination by brightness temperatures from ATMS. IEEE Geosci. Remote Sens. Lett., 19, 1006005, https://dx.doi.org/10.1109/LGRS.2022.3196386.

You, Yalei; Huan Meng; Jun Dong; Yongzhen Fan; Ralph Ferraro; Guojun Gu; andLikun Wang, 2022a: A snowfall detection algorithm for ATMS over ocean, sea ice, and coast. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15, 1411–1420, https://doi.org/10.1109/JSTARS.2022.3140768.

Zhang, Bin;Shu-peng Ho, Changyong Cao, Xi Shao, Jun Dong, Yong Chen, 2022: Verification and validation of the COSMIC-2 excess phase and bending angle algorithms for data quality assurance at STAR. Remote Sens., 14(14), 3288, https://doi.org/10.3390/rs14143288.

Zhang, Yi; Shunlin Liang, Tao He, Dongdong Wang, Yunyue Yu, and Han Ma, 2022: Estimation of land surface incident shortwave radiation from geostationary Advanced Himawari Imagerand Advanced Baseline Imager observations using an optimization method. IEEE Trans. Geosci. Remote Sens.,60, 5600611,https://doi.org/10.1109/TGRS.2020.3038829.

Zhou, Jun; Hu Yangand Robbie Iacovazzi, 2022: Improving ATMS Remapping Accuracy Using Adaptive Window and Noise-tuning Method in Backus-Gilbert Inversion, in IEEE Trans. Geosci. Remote Sens., 60, 5304412, https://dx.doi.org/10.1109/TGRS.2022.3182630.

 

close (X)