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Maina, F., A. Getirana, S.V. Kumar, M. Saharia, N. Biswas, S. McLarty, R. Appana, 2024, Irrigation-driven groundwater depletion in the Ganges-Brahmaputra basin decreases the streamflow in the Bay of Bengal, Communications of Earth and Environment, 5,169, doi:10.1038/s43247-024-01348-0

Pflug, J., M. Wrzesien, S.V. Kumar, E. Cho, K.R. Arsenault, P.R. Houser, C. Vuyovich, 2024, Extending the utility of space-borne snow water equivalent observations over vegetated areas with data assimilation, Hydrology and Earth System Sciences, 28(3), 631-648, doi:10.5194/hess-28-631-2024.

Dollan, I., F. Maina, S.V. Kumar, E. Nikolopoulos, V. Maggioni, 2024, An assessment of gridded precipitation products over High Mountain Asia, J. Hydrology: Regional Studies, 52,101675, doi:10.1016/j.ejrh.2024.101675

Oddo, P., J. Bolten, S.V. Kumar, B. Cleary, 2024, Deep Convolutional LSTM for Improved Flash Flood Prediction, Front. Water Sec. Water and Artificial Intelligence, 6, doi:10.3389/frwa.2024.1346104

Maina, F. and S.V. Kumar, 2024: Anthropogenic influences alter the response and seasonality of evapotranspiration: A case study over two high mountain asia basins, Geophys. Res. Lett., 51, e2023GL107182, doi:10.1029/2023GL107182

Ahmad, S., T. Holmes, S.V. Kumar, T. Lahmers, P.-W. Liu, W. Nie, A. Getirana, E. Orland, R. Bindlish, A. Guzman, C.R. Hain, F. Melton, K.A. Locke, Y. Yang, 2024: Droughts impede  water balance recovery from fires in the Western United States, Nature Ecology and Evolution, doi:10.1038/s41559-023-02266-8


Crow, W., H. Kim, S.V. Kumar, 2023, Systematic modelling errors underestimate the application of land data assimilation systems for hydrological and weather forecasting, J. Hydrometeorology, doi:10.1175/JHM-D-23-0069.1

Magotra, B., V. Prakash, M. Saharia, A. Getirana, S.V. Kumar, R. Pradhan, C.T. Dhanya, B. Rajagopalan, R.P. Singh, A. Pandey, M. Mohapatra, 2023, Towards and Indian Land Data Assimilation System (ILDAS): A coupled hydrologic-hydraulic system for water balance assessments, J. Hydrology, doi:10.1016/j.jhydrol.2023.130604

Cho, E., Y. Kwon, S.V. Kumar, C.Vuyovich, 2023, Assimilation of airborne gamma observations provides utility for snow estimation in forested environments, Hydrology and Earth System Sciences, 27, 4039-4056, doi:10.5194/hess-27-4039-2023

Cho, E., C. Vuyovich, S.V. Kumar, M.L. Wrzesien, R.S. Kim, 2023, Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments, The Cryosphere, 17, 3915-3931, doi:10.5194/tc-17-3915-2023

Yatheendradas, S., D. Mocko, C.D. Peters-Lidard, S.V. Kumar, 2023: Quantifying the importance of selected drought indicators for the United States Drought Monitor, J. Hydrometero., doi:10.1175/JHM-D-22-0180.1

Yin, J., X. Zhan, M. Barlage, S.V. Kumar, A. Fox, C. Albergel, C.R. Hain, R. Ferraro, J. Liu, 2023, Assimilation of blended soil moisture data products to further improve Noah-MP model skills, Journal of Hydrology, 621, 129596, doi:10.1016/j.jhydrol.2023.129596

Heyvaert, Z., S. Scherrer, M. Bechtold, A. Gruber, W. Dorigo, S.V. Kumar, G.D. Lannoy, 2023, Impact of design factors for ESA CCI satellite soil moisture data assimilation over Europe, J. Hydrometeorology, 24, 1193-1208, doi:10.1175/JHM-D-22-0141.1

Lahmers, T.M., S.V. Kumar, K.A. Locke, S. Wang, A. Getirana, M.L. Wrzesien, P.-W., Liu, S.K. Ahmad, 2023: Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation, Sci. Reports, 13, 3411, doi:10.1038/s41598-023-30484-4

Maina, F. and S.V. Kumar, 2023: Diverging trends in rain-on-snow over High Mountain Asia, Earth's Future, 11, e2022EF003009, doi: 10.1029/2022EF003009

Getirana, A., S.V. Kumar, G. Konapala, W. Nie, K. Locke, B. Loomis, C. Birkett, M. Ricko, M. Simard, 2023: Climate and human impacts on hydrological processes and flood risk in southern Louisiana, Water Resources Research, 59, e2022WR033238, doi:10.1029/2022WR033238

Hazra, A., A. McNally, K. Slinski, K.R. Arsenault, S. Shukla, A. Getirana, J. P. Jacob, D.P. Sarmiento, C. Peters-Lidard, S.V. Kumar, R.D. Koster, 2023: NASA’s NMME-based S2S hydrologic forecast system for food insecurity early warning in southern Africa, Journal of Hydrology, 617, Part B, 129005.

Ávila, A.V.A., Gonçalves, L.G.G., Souza, V.A., Alves, L.E.R., Galetti, G.D., Getirana, A., et al., 2023. Assessing the Performance of the South American Land Data Assimilation System version 2 (SALDAS-2) Energy Balance across Diverse Biomes. Atmosphere. doi:10.3390/atmos14060959.

Bechtold, M., Modanesi, S., Lievens, H., Brangers, I., Getirana, A., et al., 2023. Assimilation of Sentinel-1 backscatter into a land surface model with river routing and its impact on streamflow simulations in two Belgian catchments. Journal of Hydrometeorology. doi:10.1175/JHM-D-22-0198.1.

Getirana, A., Mandarino, F., Montezuma, P.N., Kirschbaum, D., 2023. An urban drainage scheme for large-scale flood models. Journal of Hydrology.
doi: 10.1016/j.jhydrol.2023.130410.


Ahmad, S. K.,  Kumar, S. V.,  Lahmers, T. M.,  Wang, S.,  Liu, P.-W.,  Wrzesien, M. L., et al. 2022.  Flash drought onset and development mechanisms captured with soil moisture and vegetation data assimilation. Water Resources Research,  58, e2022WR032894.

Getirana, A., N. Biswas, A. Qureshi, A. Rajib, S.V. Kumar, M. Rahman, R. Biswas, 2022: Avert Bangladesh's looming water crisis through open science and better data, Nature, 610, 626-629, doi:10.1038/d41586-022-0

Kumar, S.V., J. Kolassa, R. Reichle, W. Crow, G. de Lannoy, P. de Rosnay, N. MacBean, M. Girotto, A. Fox, T. Quaife, C. Draper, B. Forman, G. Balsamo, S. Steele-Dunne, C. Albergel, B. Bönan, J.-C. Calvet, J. Dong, H. Lindy, B. Ruston, 2022: An agenda for land data assimilation priorities: Realizing the promise of terrestrial water, energy, and vegetation observations from space, Journal of Advances in Modeling Earth Systems, doi:10.1029/2022MS003259

Cho, E., C. Vuyovich, S.V. Kumar, M.L. Wrzesien, R.S. Kim, J. Jacobs, 2022: Precipitation biases and snow physics limitations drive the uncertainties in macroscale modeled snow water equivalent, Hydrol. Earth Syst. Sci., 26, 5721-5735, doi:10.5194/hess-26-5721-2022

Wang, S., S.V. Kumar, D. Mocko, K. Arsenault, J.V. Geiger, C.D. Peters-Lidard, 2022: Automated model integration at source code level: An approach to implementing models into the NASA Land Information System, Environmental Modeling and Software, doi:10.1016/j.envsoft.2022.105539.

Nie, W., S.V. Kumar, C.D. Peters-Lidard, B.F. Zaitchik, K.R. Arsenault, R. Bindlish, P.-W. Liu, 2022: Assimilation of remotely sensed leaf area index enhances the estimation of anthropogenic irrigation water use, Journal of Advances in Modeling Earth Systems, doi:10.1029/2022MS003040

Portier, A., D. Kirschbaum, M. Gebremichael, E. Kemp, S.V. Kumar, I. Llabres, E. Snodgrass, J. Wegiel, 2022: NASA's Global Precipitation Measurement Mission: Leveraging stakeholder engagement & applications activities to inform decision-making, Remote Sensing Applications: Society and Environment, doi:10.1016/j.rsase.2022.100853

Eylander, J., S.V. Kumar, C.D. Peters-Lidard, T. Lewiston, C. Franks, J. Wegiel, 2022: History and development of the USAF Agriculture Meteorology Modeling System and resulting USAF-NASA strategic partnership, Weather and Forecasting, doi:10.1175/WAF-D-22-0064.1

Pinker, R., W. Chen, Y. Ma, S.V. Kumar, J. Wegiel, E. Kemp, 2022: Surface shortwave radiative fluxes derived from the US Air Force Cloud Depiction Forecast System World-Wide Merged Cloud Analysis, J. Hydrometeorology, doi:10.1175/JHM-D-22-0013.1

Maina, F., S.V. Kumar, C. Gangodagamage, 2022: Irrigation and warming drive the decreases in surface albedo over High Mountain Asia, Scientific Reports, 12, 16163, doi: 10.1038/s41598-022-20564-2.

Nie, W., S.V. Kumar, R. Bindlish, P.-W. Liu, S. Wang, 2022: Remote sensing-based vegetation and soil moisture constraints reduce irrigation estimation uncertainty, Environ. Res. Lett., doi: 10.1088/1748-9326/ac7ed8

Kwon, Y., S.V. Kumar, M. Navari, D. Mocko, E. Kemp, J. Wegiel, J. Geiger, R. Bindlish, 2022: Irrigation characterization improved by the direct use of SMAP soil moisture anomalies within a data assimilation system, Environ. Res. Lett., doi:10.1088/1748-9326/ac7f49

McNally, A., Jacob, J., Arsenault, K., Slinski, K., Sarmiento, D. P., Hoell, A., Pervez, S., Rowland, J., Budde, M., Kumar, S.V., Peters-Lidard, C.D., and Verdin, J. P., 2022: A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan, Earth Syst. Sci. Data, 14, 3115–3135,

Maina, F., S.V. Kumar, I.J. Dollan, V. Maggioni, 2022: Development and evaluation of ensemble consensus precipitation products over High Mountain Asia, Journal of Hydrometeorology, in early online release, doi:10.1175/JHM-D-21-0196.1

Kemp, E, J.W. Wegiel, S.V. Kumar, J. V. Geiger, D.M. Mocko, J. Jacob, C.D. Peters-Lidard, 2022: A NASA-Air Force Precipitation Analysis for Near-Real-Time Operations, Journal of Hydrometeorology, 23(6), 965-989, doi:10.1175/JHM-D-21-0228.1

Yoon, Y., E.M. Kemp, S.V. Kumar, J.W. Wegiel, C.M. Vuyovich, C.D. Peters-Lidard, 2022: Development of a global operational snow analysis: The US Air Force Snow and Ice Analysis, Remote Sensing of Environment, 278, 113080, doi:10.1016/j.rse.2022.113080

Nie, W., S.V. Kumar, K. Arsenault, C.D. Peters-Lidard, I.E. Mladenova, K. Bergaoui, A. Hazar, B.F. Zaitchik, S.P. Mahanama, R. McDowell, 2022: Towards Effective Drought Monitoring in the Middle East and North Africa (MENA) Region: Implications from Assimilating Leaf Area Index and Soil Moisture into the Noah-MP land surface model, Hydrol. Earth Syst. Sci., 26(9), 2365--2386, doi:10.5194/hess-2021-263

Ahmad, J., B.A. Forman, S.V. Kumar, 2022: SMAP retrieval assimilation improves soil moisture estimation across irrigated areas in South Asia, Hydrol. Earth Syst. Sci., 26, 2221-2243, doi:10.5194/hess-26-2221-2022

Xue, Y., P.R. Houser, V. Maggioni, Y. Mei, S.V. Kumar, Y. Yoon, 2022: Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. Impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model, J. Geophysical Res. Atmospheres, 127, e2021JD035992, doi:10.1029/2021JD035992.  

Lahmers, T., S.V. Kumar, D. Rosen, A. Dugger, D.J. Gochis, J.A. Santanello, C. Gangodagamage, R. Dunlap, 2022: Assimilation of NASA's Airborne Snow Observatory snow measurements for improved hydrological modeling: A case study enabled by the coupled LIS/WRF-Hydro system, Water Resources Research, 58, e2021WR029867, doi:10.1029/2021WR029867

Maina, F., S.V. Kumar, C. Albergel, S.P.P. Mahanama, 2022: Warming, increase in precipitation, and irrigation enhance greening in High Mountain Asia, Commun Earth Environ, 3, 43, doi:10.1038/s43247-022-00374-0

Rahman, A., V. Maggioni, X. Zhang, P. Houser, T. Sauer, and D.M. Mocko, 2022: The joint assimilation of remotely sensed leaf area index and surface soil moisture into a land surface model. Remote Sens., 14, 437, doi:10.3390/rs14030437

Wrzesien, M., S.V. Kumar, C. Vuyovich, E.D. Gutmann, R.S. Kim, B.A. Forman, M. Durand, M.S. Raleigh, R. Webb, and P.R. Houser, 2022: Development of a "nature run" for observing system simulation experiments (OSSEs) for snow mission development. J. Hydrometeor., early online release, doi:10.1175/JHM-D-21-0071.1

Kumar, S.V., A. Getirana, R. Libonati, C. Hain, S. Mahanama, and N. Andela, 2022: Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes. Sci. Rep., 12, 964, doi:0.1038/s41598-022-05130-0

Park, J., B.A. Forman, S.V. Kumar, 2022: Estimation of snow mass information via assimilation of C-band synthetic aperture radar backscatter observations into an advanced land surface model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 862-875, doi:10.1109/JSTARS.2021.3133513


Yatheendradas, S., and S.V. Kumar, 2021: A novel machine learning-based gap-filling of fine-resolution remotely sensed snow cover fraction data by combining downscaling and regression. J. Hydrometeor., early online release, doi:10.1175/JHM-D-20-01111.1

Cook, B.I., K. Slinski, C.D. Peters-Lidard, A. McNally, K. Arsenault, and A. Hazra, 2021: The efficacy of seasonal terrestrial water storage forecasts for predicting vegetation activity over Africa. J. Hydrometeor., 22(11), 3121-3137, doi:10.1175/JHM-D-21-0046.1

Sarmiento, D.P., K. Slinski, A. McNally, J.P. Jacob, C. Funk, P. Peterson, and C.D. Peters-Lidard, 2021: Daily precipitation frequency distributions impacts on land-surface simulations of CONUS. Frontiers in Water, 3, doi:10.3389/frwa.2021.640736

Konapala, G., S.V. Kumar, and S.K. Ahmad, 2021: Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning. ISPRS Journal of Photogrammetry and Remote Sensing, 180, 163-173, doi:10.1016/j.isprsjprs.2021.08.016

Kwon, Y., Y. Yoon, B.A. Forman, S.V. Kumar, and L. Wang, 2021: Quantifying the observational requirements of a space-borne LiDAR snow mission. J. Hydrol., 601, 126709, doi:10.1016/j.jhydrol.2021.126709

Ahmad, J.A., B.A. Forman, E.H. Bair, and S.V. Kumar, 2021: Passive microwave brightness temperature assimilation to improve snow mass estimation across complex terrain in Pakistan, Afghanistan, and Tajikistan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 8849-8863, doi:10.1109/JSTARS.2021.3102965

Lawston-Parker, P., J.A. Santanello, Jr., and S.V. Kumar, 2021: Understanding the impacts of land surface and PBL observations on the terrestrial and atmospheric legs of land-atmosphere coupling. J. Hydrometeor., 22(9), 2241-2258, doi:10.1175/JHM-D-20-0263.1

Kim, H., V. Lakshmi, Y. Kwon, and S.V. Kumar, 2021: First attempt of global-scale assimilation of subdaily scale soil moisture estimates from CYGNSS and SMAP into a land surface model. Environ. Res. Lett., 16(7), doi:10.1088/1748-9326/ac0ddf

Maertens, M., G.J.M. De Lannoy, S. Apers, S.V. Kumar, and S.P.P. Mahanama, 2021: Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation, and landcover parameters. Hydrol. Earth Syst. Sci., 25, 4099-4125, doi:10.5194/hess-25-4099-2021

Zamora, R., B.F. Zaitchik, M. Rodell, A. Getirana, S.V. Kumar, K. Arsenault, and E. Gutmann, 2021: Contribution of meteorological downscaling to skill and prediction of seasonal drought forecasts. J. Hydrometeor., 22(8), 2009-2031, doi:10.1175/JHM-D-20-0259.1

Getirana, A., S.V. Kumar, G. Konapala, and C. Ndehedehe, 2021: Impacts of fully coupling land surface and flood models on the simulation of large wetland's water dynamics: the case of the Inner Niger Delta. Journal of Advances in Modeling Earth Systems, 13(5), e2021MS002463, doi:10.1029/2021MS002463

Xue, Y., P.R. Houser, V. Maggioni, Y. Mei, S.V. Kumar, and Y. Yoon, 2021: Evaluation of High Mountain Asia - Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A hyper-resolution terrestrial modeling system. J. Geophys. Res. Atmos., 126(8), e2020JD034131, doi:10.1029/2020JD034131

Peters-Lidard, C.D., D.M. Mocko, L. Su, D.P. Lettenmaier, P. Gentine, and M. Barlage, 2021: Advances in land surface models and indicators for drought monitoring and prediction. Bull. Amer. Meteor. Soc., 102(5), E1099-E1122, doi:10.1175/BAMS-D-20-0087.1

Su, L., Q. Cao, M. Xiao, D.M. Mocko, M. Barlage, D. Li, C.D. Peters-Lidard, and D.P. Lettenmaier, 2021: Drought variability over the conterminous United States for the past century. J. Hydrometeor., 22(5), 1153-1168, doi:10.1175/JHM-D-20-0158.1

Erlingis, J., M. Rodell, C.D. Peters-Lidard, B. Li, S.V. Kumar, and D.M. Mocko, 2021: A high-resolution land data assimilation system optimized for the western United States. J. Amer. Water Resour. Assoc., early online release, doi:10.1111/1752-1688.12910

Kim, R.S., S.V. Kumar, C. Vuyovich, P. Houser, J. Lundquist, L. Mudryk, M. Durand, A. Barros, E.J. Kim, B.A. Forman, E.D. Gutmann, M.L. Wrzesien, C. Garnaud, M. Sandells, H.-P. Marshall, N. Cristea, J.M. Pflug, J. Johnson, Y. Cao, D.M. Mocko, and S. Wang, 2021: Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling. The Cryosphere, 15, 771-791, doi:10.5194/tc-15-771-2021

Pervez, S., A. McNally, K. Arsenault, M. Budde, and J. Rowland, 2021: Vegetation monitoring optimization with NDVI and Evapotranspiration using remote sensing measurements and land surface models over East Africa. Front. Clim., 3(1), doi:10.3389/fclim.2021.589981

Mocko, D.M., S.V. Kumar, C.D. Peters-Lidard, and S. Wang, 2021: Assimilation of vegetation conditions improves the representation of drought over agricultural areas. J. Hydrometeor., 22(5), 1085-1098, doi:10.1175/JHM-D-20-0065.1

Kumar, S.V., T. Holmes, N. Andela, I. Dharssi, Vinodkumar, C. Hain, C.D. Peters-Lidard, S.P. Mahanama, K.R. Arsenault, W. Nie, and A. Getirana, 2021: The 2019-2020 Australian drought and bushfires altered the partitioning of hydrological fluxes. Geophys. Res. Lett., 48(1), e2020GL091411, doi:10.1029/2020GL091411

Zhou, Y., B.F. Zaitchik, S.V. Kumar, K.R. Arsenault, M.A. Matin, F.M. Qamer, R.A. Zamora, and K. Shakya, 2021: Developing a hydrological modeling and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins. Hydrol. Earth Syst. Sci., 25, 41-61, doi:10.5194/hess-2020-362

Recalde-Coronel, G.C., Zaitchik, B., Pan, W., Getirana, A., 2021. Influence of vegetation on simulation of the water balance and hydrological response to the El Niño Southern Oscillation in western tropical South America. Journal of Hydrometeorology. doi:10.1175/JHM-D-21-0081.1.


Li, B., M. Rodell, C.D. Peters-LIdard, J. Erlingis, S.V. Kumar, and D.M. Mocko, 2020: Groundwater recharge estimated by land surface models: An evaluation in the conterminous United States. J. Hydrometeor., 22(2), 499-522, doi:10.1175/JHM-D-20-0130.1

Nie, W., B.F. Zaitchik, M. Rodell, S.V. Kumar, K.R. Arsenault, and H.S. Badr, 2020: Irrigation water demand sensitivity to climate variability across the Contiguous United States. Water Resour. Res., 57(3), 2020WR027738, doi:10.1029/2020WR027738

Getirana, A., D. Kirschbaum, F. Mandarino, M. Ottoni, S. Khan, and K.R. Arsenault, 2020: Potential of GPM IMERG precipitation estimates to monitor natural disaster triggers in urban areas: The case of Rio de Janeiro, Brazil. Remote Sens., 12(24), 4095, doi:10.3390/rs12244095

Rahman, A., X. Zhang, Y. Xue, P. Houser, T. Sauer, S.V. Kumar, D.M. Mocko, and V. Maggioni, 2020: A synthetic experiment to investigate the potential of assimilating LAI through direct insertion in a land surface model. J. Hydrol. X, 9, 100063, doi:10.1016/j.hydroa.2020.100063

Shellito, P.J., S.V. Kumar, J.A. Santanello, P. Lawston-Parker, J.D. Bolten, M.H. Cosh, D.D. Bosch, C.D. Holifield Collins, S. Livington, J. Prueger, M. Seyfried, and P.J. Starks, 2020: Assessing the impact of soil layer depth specification on the observability of modeled soil moisture and brightness temperature. J. Hydrometeor., 21(9), 2041–2060, doi:10.1175/JHM-D-19-0280.1

Zhang, X., V. Maggioni, A. Rahman, P. Houser, Y. Xue, T. Sauer, S.V. Kumar, and D.M. Mocko, 2020: The influence of assimilating leaf area index in a land surface model on global water fluxes and storages. Hydrol. Earth Syst. Sci., 24, 3775-3788, doi:10.5194/hess-24-3775-2020

Kumar, S.V., T.R. Holmes, R. Bindlish, R. de Jeu, and C.D. Peters-Lidard, 2020: Assimilation of vegetation optical depth retrievals from passive microwave radiometry. Hydrol. Earth Syst. Sci., 24, 3431-3450, doi:10.5194/hess-24-3431-2020

Jung, H.C., D.-H. Kang, E. Kim, A. Getirana, Y. Yoon, S.V. Kumar, C.D. Peters-Lidard, and E. Hwang, 2020: Towards a soil moisture drought monitoring system for South Korea. J. Hydrol., 589, 125176, doi:10.1016/j.jhydrol.2020.125176

Yoo, J., J.A. Santanello, Jr., M. Shepherd, S.V. Kumar, P. Lawston-Parker, and A.M. Thomas, 2020: Quantification of the land surface and brown ocean influence on tropical cyclone intensification over land. J. Hydrometeor., 21, 1171-1192, doi:10.1175/JHM-D-19-0214.1

Shukla, S., K.R. Arsenault, A. Hazra, C.D. Peters-Lidard, R.D. Koster, F. Davenport, T. Magadzire, C. Funk, S.V. Kumar, A. McNally, A. Getirana, G. Husak, B. Zaitchik, J. Verdin, F.D. Nsadisa, and I. Becker-Reshef, 2020: Improving early warning of drought-driven food insecurity in southern Africa using operational hydrological monitoring and forecasting products. Nat. Hazards Earth Syst. Sci., 20, 1187-1201, doi:10.5194/nhess-20-1187-2020

Getirana, A., H.C. Jung, J. Van Den Hoek, and C.E. Ndehedehe, 2020: Hydropower dam operation strongly controls Lake Victoria's freshwater storage variability. Science of the Total Environment, 726, 138343, doi:10.1016/j.scitotenv.2020.138343

Arsenault, K.R., S. Shukla, A. Hazra, A. Getirana, A. McNally, S.V. Kumar, R.D. Koster, C.D. Peters-Lidard, B.F. Zaitchik, H. Badr, H.C. Jung, B. Narapusetty, M. Navari, S. Wang, D.M. Mocko, C. Funk, L. Harrison, G.J. Husak, A. Adoum, G. Galu, T. Magadzire, J. Roningen, M. Shaw, J. Eylander, K. Bergaoui, R.A. McDonnell, and J.P. Verdin, 2020: The NASA hydrological forecast system for food and water security applications. Bull. Amer. Meteor. Soc., 101, E1007–E1025, doi:10.1175/BAMS-D-18-0264.1

Stanley, T.A., D.B. Kirschbaum, S. Sobieszczyk, M. Jasinski, J. Borak, and S. Slaughter, 2020: Building a landslide hazard indicator with machine learning and land surface models. Environ. Model. and Soft., 129, 104692, doi:10.1016/j.envsoft.2020.104692

Lawston, P., J. Santanello, B. Hanson, and, K. Arsenault, 2020: Impacts of irrigation on summertime temperatures in the Pacific Northwest. Earth Interactions, 24, 1-26, doi:10.1175/EI-D-19-0015.1

Kumar, S.V., D.M. Mocko, C. Vuyovich, and C.D. Peters-Lidard, 2020: Impact of surface albedo assimilation on snow estimation. Remote Sens., 12(4), 645, doi:10.3390/rs12040645

Getirana, A., H.C. Jung, K.R. Arsenault, S. Shukla, S.V. Kumar, C.D. Peters-Lidard, I. Maigari, and B. Mamane, 2020: Satellite gravimetry improves seasonal streamflow forecast initialization in Africa. Water Resour. Res., 56(2), e2019WR026259, doi:10.1029/2019WR026259

Huang, M., J.H. Crawford, G.R. Carmichael, J.A. Santanello, S.V. Kumar, R.M. Stauffer, A.M. Thompson, A.J. Weinheimer, and J.D. Park, 2020: Impact of aerosols from urban and shipping emission sources on terrestrial carbon uptake and evapotranspiration: a case study in East Asia. J. Geophys. Res. Atmos., 125(2), e2019JD030818, doi:10.1029/2019JD030818

Nair, U., E. Rappin, E. Foshee, W. Smith, R. A. Pielke, Sr., R. Mahmood, J.L. Case, C.B. Blankenship, M. Shepherd, J. A. Santanello, and D. Niyogi, 2019: Influence of land cover and soil moisture based Brown Ocean Effect on an extreme rainfall event from a Louisiana Gulf Coast Tropical System. Scientific Reports, 9, 171356. 


Nie, W.S., B.F. Zaitchik, M. Rodell, S.V. Kumar, K.R. Arsenault, B. Li, and A. Getirana, 2019: Assimilating GRACE into a land surface model in the presence of an irrigation-induced groundwater trend. Water Resour. Res., 55, 11274-11294, doi:10.1029/2019WR025363

Getirana, A., M. Rodell, S.V. Kumar, H.K. Beaudoing, K. Arsenault, B. Zaitchik, H. Save, and S. Bettadpur, 2019: GRACE improves seasonal groundwater forecast initialization over the U.S. J. Hydrometeor., 21, 59-71, doi:10.1175/JHM-D-19-0096.1

Abolafia-Rosenzweig, R., B. Livneh, E.E. Small, and S.V. Kumar, 2019: Soil moisture data assimilation to estimate irrigation water use. Journal of Advances in Modeling Earth Systems, 11, doi:10.1029/2019MS001797

Kwon, Y., B.A. Forman, J. Ahmad, S.V. Kumar, and Y. Yoon, 2019: Exploring the utility of machine learning-based passive microwave brightness temperature data assimilation over terrestrial snow in High Mountain Asia. Remote Sens., 11(19), 2265, doi:10.3390/rs11192265

McNally, A., K. Verdin, L. Harrison, A. Getirana, J. Jacob, S. Shukla, K. Arsenault, C.D. Peters-Lidard, and J.P. Verdin, 2019: Acute water-scarcity monitoring for Africa. Water, 11(10), 1968, doi:10.3390/w11101968

Loomis, B., A.S. Richey, A. Arendt, R. Appana, Y.-J.C. Deweese, B. Forman, S.V. Kumar, T.J. Sabaka, and D. Shean, 2019: Water storage trends in High Mountain Asia. Frontiers Earth Sci., 7, 235, doi:10.3389/feart.2019.00235

Li, B., M. Rodell, S.V. Kumar, H.K. Beaudoing, A. Getirana, B.F. Zaitchik, L.G. de Goncalves, C. Cossetin, S. Bhanja, A. Mukherjee, S. Tian, N. Tangdamrongsub, D. Long, J. Nanteza, J. Lee, F. Policelli, I.B. Goni, D. Daira, M. Bila, G. de Lannoy, D.M. Mocko, S.C. Steele‐Dunne, H. Save, S. Bettadpur, 2019: Global GRACE data assimilation for groundwater and drought monitoring: Advances and challenges. Water Resour. Res., 55, 7564-7586, doi:10.1029/2018WR024618

Funk, C., S. Shukla, W.M. Thiaw, J. Rowland, A. Hoell, A. McNally, G. Husak, N. Novella, M. Budde, C.D. Peters-Lidard, A. Adoum, G. Galu, D. Korecha, T. Magadzire, M. Rodriguez, M. Robjhon, E. Bekele, K. Arsenault, P. Peterson, L. Harrison, S. Fuhrman, F. Davenport, M. Landsfeld, D. Pedreros, J.P. Jacob, C. Reynolds, I. Becker-Reshef, and J. Verdin, 2019: Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security. Bull. Amer. Meteor. Soc., 100, 1011-1027, doi:10.1175/BAMS-D-17-0233.1

Jasinski, M.F., J.S. Borak, S.V. Kumar, D.M. Mocko, C.D. Peters-Lidard, M. Rodell, H. Rui, H.K. Beaudoing, B.E. Vollmer, K.R. Arsenault, B. Li, J.D. Bolten, and N. Tangdamrongsub, 2019: NCA-LDAS: Overview and analysis of hydrologic trends for the National Climate Assessment. J. Hydrometeor., 20, 1595-1617, doi:10.1175/JHM-D-17-0234.1

Kumar, S.V., M. Jasinski, D.M. Mocko, M. Rodell, J. Borak, B. Li, H. Kato Beaudoing, and C.D. Peters-Lidard, 2019: NCA-LDAS land analysis: Development and performance of a multisensor, multivariate land data assimilation system for the National Climate Assessment. J. Hydrometeor., 20, 1571-1593, doi:10.1175/JHM-D-17-0125.1

McNally, A., S. McCartney, A.C. Ruane, I.E. Mladenova, A.K. Whitcraft, I. Becker-Reshef, J.D. Bolten, C.D. Peters-Lidard, C. Rosenzweig, and S.S. Uz, 2019: Hydrologic and Agricultural Earth Observations and Modeling for the Water-Food Nexus. Frontiers Earth Sci., 7, 23, doi:10.3389/fenvs.2019.00023

Tavakol, A., V. Rahmani, S.M. Quiring, and S.V. Kumar, 2019: Evaluation analysis of NASA SMAP L3 and L4 and SPoRT-LIS soil moisture data in the United States. Remote Sens. Environ., 229, 234-246, doi:10.1016/j.rse.2019.05.006

Jung, H.C., A. Getirana, K.R. Arsenault, S.V. Kumar, and I. Maigary, 2019: Improving surface soil moisture estimates in West Africa through GRACE data assimilation. J. Hydrology, 575, 192-201, doi:10.1016/j.jhydrol.2019.05.042

Yoon, Y., S.V. Kumar, B.A. Forman, B. Zaitchik, Y. Kwon, Y. Qian, S. Rupper, V. Maggioni, P. Houser, D. Kirschbaum, A. Richey, A. Arendt, D.M. Mocko, J. Jacob, S. Bhanja, and A. Mukherjee, 2019: Evaluating the uncertainty of terrestrial water budget components over High Mountain Asia. Frontiers Earth Sci., 7, 120, doi:10.3389/feart.2019.00120

Xue, Y., P.R. Houser, V. Maggioni, Y. Mei, S.V. Kumar, and Y. Yoon, 2019: Assimilation of satellite-based snow cover and freeze/thaw observations over High Mountain Asia. Frontiers Earth Sci., 7, 115, doi:10.3389/feart.2019.00115

Kumar, S.V., D.M. Mocko, S. Wang, C.D. Peters-Lidard, and J. Borak, 2019: Assimilation of remotely sensed Leaf Area Index into the Noah-MP land surface model: Impacts on water and carbon fluxes and states over the Continental U.S. J. Hydrometeor., 20, 1359-1377, doi:10.1175/JHM-D-18-0237.1

Santanello, J.A., P. Lawston, S.V. Kumar, and E. Dennis, 2019: Understanding the impacts of soil moisture initial conditions on NWP in the context of land-atmosphere coupling. J. Hydrometeor., 20, 793-819, doi:10.1175/JHM-D-18-0186.1

Jung, H.C., A. Getirana, K.R. Arsenault, T.R. Holmes, and A. McNally, 2019: Uncertainties in evapotranspiration estimates over West Africa. Remote Sens., 11(8), 892, doi:10.3390/rs11080892

Blankenship, C.B., J.L. Case, W.L. Crosson, and B.T. Zavodsky, 2018: Correction of forcing-related spatial artifacts in a land surface model by satellite soil moisture data assimilation. IEEE Geosci. Remote Sens. Lett., 15 (4), 498-502, doi: 10.1109/LGRS.2018.2805259.


Ghatak, D., B.F. Zaitchik, S.V. Kumar, M.A. Matin, B. Bajracharya, C. Hain, and M.A. Anderson, 2018: Influence of precipitation forcing uncertainty on hydrological simulations with the NASA South Asia Land Data Assimilation System. Hydrology, 5(4), 57, doi:10.3390/hydrology5040057

Huang, M., J.H. Crawford, G.S. Diskin, J.A. Santanello, S.V. Kumar, S.E. Pusede, M. Parrington, and G.R. Carmichael, 2018: Modeling regional pollution transport events during KORUS-AQ: Progress and challenges in improving representation of land-atmosphere feedbacks. J. Geophys. Res. Atmos., 123, 10,732-10,756, doi:10.1029/2018JD028554

Arsenault, K.R., S.V. Kumar, J.V. Geiger, S. Wang, E. Kemp, D.M. Mocko, H. Kato Beaudoing, A. Getirana, M. Navari, B. Li, J. Jacob, J. Wegiel, and C.D. Peters-Lidard, 2018: The Land surface Data Toolkit (LDT v7.2) - a data fusion environment for land data assimilation systems. Geosci. Model Dev., 11, 3605-3621, doi:10.5194/gmd-2018-63

Nie, W., B.F. Zaitchik, M. Rodell, S.V. Kumar, M.C. Anderson, and C. Hain, 2018: Groundwater withdrawals under drought: Reconciling GRACE and land surface models in the United States High Plains Aquifer. Water Resour. Res., 54, 5282-5299, doi:10.1029/2017WR022178

Xia, Y., D.M. Mocko, S. Wang, M. Pan, S.V. Kumar, C.D. Peters-Lidard, H. Wei, D. Wang, and M.B. Ek, 2018: Comprehensive evaluation of the variable infiltration capacity (VIC) model in the North American Land Data Assimilation System. J. Hydrometeor., 19, 1853-1879, doi:10.1175/JHM-D-18-0139.1

Kumar, S.V., T. Holmes, D.M. Mocko, S. Wang, and C.D. Peters-Lidard, 2018: Attribution of flux partitioning variations between land surface models over the continental U.S. Remote Sens., 10(5), 751, doi:10.3390/rs10050751

Arsenault, K.R., G.S. Nearing, S. Wang, S. Yatheendradas, and C.D. Peters-Lidard, 2018: Parameter sensitivity of the Noah-MP land surface model with dynamic vegetation. J. Hydrometeor., 19, 815-830, doi:10.1175/JHM-D-17-0205.1

Kumar, S.V., P. Dirmeyer, C.D. Peters-Lidard, R. Bindlish, and J. Bolten, 2018: Information theoretic evaluation of satellite soil moisture retrievals. Remote Sens. Environ., 204, 392-400, doi:10.1016/j.rse.2017.10.016


Kumar, S.V., S. Wang, D.M. Mocko, C.D Peters-Lidard, and Y. Xia, 2017: Similarity assessment of land surface model outputs in the North American Land Data Assimilation System (NLDAS). Water Resour. Res., 53, 8941-8965, doi:10.1002/2017WR020635

Getirana, A., C.D. Peters-Lidard, M. Rodell, and P.D. Bates, 2017: Trade-off between cost and accuracy in large-scale surface water dynamic modeling. Water Resour. Res., 53, 4942–4955, doi:10.1002/2017WR020519

Getirana, A., S.V. Kumar, M. Girotto, and M. Rodell, 2017: Rivers and floodplains as key components of global terrestrial water storage variability. Geophys. Res. Lett., 44, 10,359-10,368, doi:10.1002/2017GL074684

Jung, H.C., A. Getirana, F. Policelli, A. McNally, K. Arsenault, S.V. Kumar, T. Tadesse, and C.D. Peters-Lidard, 2017: Upper Blue Nile Basin water budget from a multi-model perspective. J. Hydrology, 555, 535-546, doi:10.1016/j.jhydrol.2017.10.040

Lawston, P.M., J.A. Santanello, S.V. Kumar, 2017: Irrigation signals detected from SMAP soil moisture retrievals. Geophys. Res. Lett.., 44, 11860-11867, doi:10.1002/2017GL075733

Lawston, P.M., J.A. Santanello, T.E. Franz, and M. Rodell, 2017: Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets. Hydrol. Earth Syst. Sci., 21, 2953-2966, doi:10.5194/hess-21-2953-2017

Kumar, S.V., J. Dong, C.D. Peters-Lidard, D.M. Mocko, and B. Gomez, 2017: Role of forcing uncertainty and background model error characterization in snow data assimilation. Hydrol. Earth Syst. Sci., 21, 2637-2647, doi:10.5194/hess-21-2637-2017

McNally, A., K. Arsenault, S.V. Kumar, S. Shukla, P. Peterson, S. Wang, C. Funk, C.D. Peters-Lidard, and J.P. Verdin, 2017: A land data assimilation system for sub-Saharan Africa food and water security applications. Scientific Data, 4, doi:10.1038/sdata.2017.12

Xia, Y., D.M. Mocko, M. Huang, B. Li, M. Rodell, K.E. Mitchell, X. Cai, and M.B. Ek, 2017: Comparison and assessment of three advanced land surface models in simulating terrestrial water storage components over the United States. J. Hydrometeor., 18(3), 625-649, doi:10.1175/jhm-d-16-0112.1


Santanello, J.A., S.V. Kumar, C.D. Peters-Lidard, and P.M. Lawston, 2016: Impact of soil moisture assimilation on land surface model spinup and coupled land-atmosphere prediction. J. Hydrometeor., 17, 517-540, doi:10.1175/jhm-d-15-0072.1

Kumar, S.V., B.F. Zaitchik, C.D. Peters-Lidard, M. Rodell, R.H. Reichle, B. Li, D.M. Mocko, A. Getirana, G. Lannoy, M. Cosh, C. Hain, M. Anderson, K. Arsenault, Y. Xia, and M. Ek, 2016: Assimilation of gridded GRACE terrestrial water storage estimates in the North American Land Data Assimilation System. J. Hydrometeor., 17(7), 1951-1972, doi:10.1175/JHM-D-15-0157.1

Nearing, G.S., D.M. Mocko, C.D. Peters-Lidard, S.V. Kumar, and Y. Xia, 2016: Benchmarking NLDAS-2 soil moisture and evapotranspiration to separate uncertainty contributions. J. Hydrometeor., 17(3), 745-759, doi:10.1175/JHM-D-15-0063.1

McNally, A., S. Shukla, K. Arsenault, S. Wang, C.D. Peters-Lidard, and J.P. Verdin, 2016: Evaluating ESA CCI soil moisture in East Africa. International Journal of Applied Earth Observation and Geoinformation, 48, 96-109, doi:10.1016/j.jag.2016.01.001

Harrison, K.W., Y. Tian, C.D. Peters-Lidard, S. Ringerud, and S.V. Kumar, 2015: Calibration to improve forward model simulations of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains. IEEE Trans. on Geosci. and Remote Sensing, 54(2), doi:10.1109/TGRS.2015.2474120

Blankenship, C. B., J. L. Case, B. T. Zavodsky, and W. L. Crosson, 2016: Assimilation of SMOS Retrievals in the Land Information System. IEEE Trans. Geosci. Remote Sens, 54 (11), 6320-6332.


Kumar, S.V., C.D. Peters-Lidard, J.A. Santanello, R.H. Reichle, C.S. Draper, R.D. Koster, G. Nearing, and M.F. Jasinski, 2015: Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes. Hydrol. Earth Syst. Sci., 19, 4463-4478, doi:10.5194/hess-19-4483-2015

Lawston, P.M., J.A. Santanello, B.F. Zaitchik, and M. Rodell, 2015: Impact of irrigation methods on land surface model spinup and initialization of WRF forecasts. J. Hydrometeor., 16, 1135-1154, doi:10.1175/JHM-D-14-0203.1

Tian, Y., C.D. Peters-Lidard, K.W. Harrison, Y. You, S. Ringerud, S.V. Kumar, and J. Turk, 2015: An examination of methods estimating land surface microwave emissivity. J. Geophys. Res. Atmos., 120(21), 11,114-11,128, doi:10.1002/2015JD023582

Mazrooei, A., T. Sinha, A. Sankarasubramanian, S.V. Kumar, and C.D. Peters-Lidard, 2015: Decomposition of sources of errors in seasonal streamflow forecasting over the US Sunbelt. J. Geophys. Res. Atmos., 120(23), 11,809-11,825, doi:10.1002/2015JD023687

Kumar, S.V., C.D. Peters-Lidard, K.R. Arsenault, A. Getirana, D.M. Mocko, and Y. Liu, 2015: Quantifying the added value of snow cover area observations in passive microwave snow depth data assimilation. J. Hydrometeor., 16, 1736-1741, doi:10.1175/JHM-D-15-0021.1

Peters-Lidard, C.D., E.M. Kemp, T. Matsui, J.A. Santanello, Jr., S.V. Kumar, J.P. Jacob, T. Clune, W.-K. Tao, M. Chin, A. Hou, J.L. Case, D. Kim, K.-M. Kim, W. Lau, Y. Liu, J.-J. Shi, D. Starr, Q. Tan, Z. Tao, B.F. Zaitchik, B. Zavodsky, S.Q. Zhang, and M. Zupanski, 2015: Integrated modeling of aerosol, cloud, precipitation and land processes at satellite-resolved scales. Environ. Modeling & Software, 67, 149-159, doi:10.1016/j.envsoft.2015.01.007

Liu, Y., C.D. Peters-Lidard, S.V. Kumar, K. Arsenault, and D.M. Mocko, 2015: Blending satellite-based snow depth products with in situ observations for streamflow predictions in the Upper Colorado River Basin. Water Resour. Res., 51, 1182-1202, doi:10.1002/2014WR016606

McNally, A., G.J. Husak, M. Brown, M. Carroll, C. Funk, S. Yatheendradas, K. Arsenault, C.D. Peters-Lidard, and J.P. Verdin, 2015: Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture. J. Hydrometeor., 16, 295-305, doi:10.1175/JHM-D-14-0049.1


Kumar, S.V., K.W. Harrison, C.D. Peters-Lidard, J.A. Santanello, and D. Kirschbaum, 2014: Assessing the impact of L-band observations on drought and flood risk estimation: A decision theoretic approach in an OSSE environment. J. Hydrometeor., 15, 2140-2156, doi:10.1175/JHM-D-13-0204.1

Kumar, S.V., C.D. Peters-Lidard, D.M. Mocko, R. Reichle, Y. Liu, K. Arsenault, Y. Xia, M. Ek, G. Riggs, B. Livneh, and M. Cosh, 2014: Assimilation of remotely sensed soil moisture and snow depth retrievals for drought estimation. J. Hydrometeor., 15, 2446-2469, doi:10.1175/JHM-D-13-0132.1

Getirana, A.C.V., E. Dutra, M. Guimberteau, J. Kam, H.-Y. Li, B. Decharme, Z. Zhang, A. Ducharne, A. Boone, G. Balsamo, M. Rodell, A. M. Toure, Y. Xue, C.D. Peters-Lidard, S.V. Kumar, K. Arsenault, G. Drapeau, L. R. Leung, J. Ronchail, and J. Sheffield, 2014: Water balance in the Amazon Basin from a land surface model ensemble. J. Hydrometeor., 15(6), 2586-2614, doi:10.1175/JHM-D-14-0068.1

Ringerud, S., C. Kummerow, C.D. Peters-Lidard, Y. Tian, and K. Harrison, 2014: A comparison of microwave window channel retrieved and forward-modeled emissivities over the U.S. Southern Great Plains. IEEE Trans. on Geosci. and Remote Sensing, 52(5), 2395-2412, doi:10.1109/TGRS.2013.2260759

Arsenault, K.R., P.R. Houser, and G.J.M. De Lannoy, 2014: Evaluation of the MODIS snow cover fraction product. Hydrological Processes, 28(3), 980-998, doi:10.1002/hyp.9636

Yilmaz, M.T., M.C. Anderson, B.F. Zaitchik, C.R. Hain, W.T. Crow, M. Ozdogan, J.A. Chun, and J.P. Evans, 2014: Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin. Water Resour. Res., 50(1), 386-408, doi:10.1002/2013WR014194


Santanello, J.A., C.D. Peters-Lidard, A. Kennedy, and S.V. Kumar, 2013: Diagnosing the nature of land-atmosphere coupling: A case study of dry/wet extremes in the U.S. Southern Great Plains. J. Hydrometeor., 14, 3-24, doi:10.1175/JHM-D-12-023.1

Santanello, J.A., S.V. Kumar, C.D. Peters-Lidard, K.W. Harrison, and S. Zhou, 2013: Impact of land model calibration on coupled land-atmosphere prediction. J. Hydrometeor., 14, 1373-1400, doi:10.1175/JHM-D-12-0127.1

Kumar, S.V., C.D. Peters-Lidard, D.M. Mocko, and Y. Tian, 2013: Multiscale evaluation of the improvements in surface snow simulation through terrain adjustments to radiation. J. Hydrometeor., 14, 220-232, doi:10.1175/JHM-D-12-046.1

Zaitchik, B.F., J.A. Santanello, S.V. Kumar, and C.D. Peters-Lidard, 2013: Representation of soil moisture feedbacks during drought in NASA Unified WRF (NU-WRF). J. Hydrometeor., 14, 360-367, doi:10.1175/JHM-D-12-069.1

Case, J.L., LaFontaine, F.J., G.J. Jedlovec, S.V. Kumar, and C.D. Peters-Lidard, 2013: A real-time MODIS vegetation product for land surface and numerical weather prediction models. IEEE Trans. on Geosci. and Remote Sensing, 52(3), 1772-1786, doi:10.1109/TGRS.2013.2255059

Mohr, K.I., W.-K. Tao, J.-D. Chern, S.V. Kumar, and C.D. Peters-Lidard, 2013: The NASA-Goddard Multi-scale Modeling Framework-Land Information System: Global land/atmosphere interaction with resolved convection. Environ. Modeling & Software, 39, 103-115, doi:10.1016/j.envsoft.2012.02.023

Liu, Y., C.D. Peters-Lidard, S.V. Kumar, J.L. Foster, M. Shaw, Y. Tian, and G.M. Fall, 2013: Assimilating satellite-based snow depth and snow cover products for improving snow predictions in Alaska. Advances in Water Resources, 54, 208-227, doi:10.1016/j.advwatres.2013.02.005

Arsenault, K.R., P.R. Houser, G.J.M. De Lannoy, and P.A. Dirmeyer, 2013: Impacts of snow cover fraction data assimilation on modeled energy and moisture budgets. J. Geophys. Res. Atmos., 118, 7489-7504, doi:10.1002/jgrd.50542


Harrison, K.E., S.V. Kumar, J.A. Santanello, and C.D. Peters-Lidard, 2012: Quantifying the change in soil moisture modeling uncertainty from remote sensing observations using Bayesian inference techniques. Water Resour. Res., 48(11), W11514, doi:10.1029/2012WR012337

Yatheendradas, S., C.D. Peters-Lidard, V.I. Koren, B. Cosgrove, L.G.G. de Goncalves, M.B. Smith, J. Geiger, Z. Cui, J. Borak, S.V. Kumar, D. Toll, G.A. Riggs, and N. Mizukami, 2012: Distributed assimilation of satellite-based snow extent for improving simulated streamflow in mountainous, dense forests: An example over the DMIP2 western basins. Water Resour. Res., 48, W09557, doi:10.1029/2011WR011347

Crow, W.T., S.V. Kumar, and J.D. Bolten, 2012: On the utility of land surface models for agricultural drought monitoring. Hydrol. Earth Syst. Sci., 16, 3451-3460, doi:10.5194/hess-16-3451-2012

Kumar, S.V., R.H. Reichle, K.W. Harrison, C.D. Peters-Lidard, S.Yatheendradas, and J. Santanello, 2012: A comparison of methods for a priori bias correction in soil moisture data assimilation. Water Resour. Res., 48(3), W03515, doi:10.1029/2010WR010261

Kumar, S.V., C.D. Peters-Lidard, J. Santanello, K. Harrison, Y. Liu, and M. Shaw, 2012: Land surface Verification Toolkit (LVT) - A generalized framework for land surface model evaluation. Geosci. Model Dev., 5, 869-886, doi:10.5194/gmd-5-869-a

De Lannoy, G., R.H. Reichle, K.R. Arsenault, P.R. Houser, S.V. Kumar, N.E.C. Verhoest, and V.R.N. Pauwels, 2012: Multiscale assimilation of Advanced Microwave Scanning Radiometer–EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado. Water Resour. Res., 48, W01522, doi:10.1029/2011WR010588

Case, J.L., S.V. Kumar, J. Srikishen, and G.J. Jedlovec, 2012: Improving numerical weather predictions of summertime precipitation over the southeastern United States through a high-resolution initialization of the surface state. Weather and Forecasting, 26(6), 785-807, doi:10.1175/2011WAF2222455.1

Anderson, W.B., B.F. Zaitchik, C.R. Hain, M.C. Anderson, M.T. Yilmaz, J. Mecikalski, and L. Schultz, 2012: Towards an integrated soil moisture drought monitor for East Africa. Hydrol. Earth Syst. Sci., 16, 2893-2913, doi:10.5194/hess-16-2893-2012


Peters-Lidard, C.D., S.V. Kumar, D.M. Mocko, and Y. Tian, 2011: Estimating evapotranspiration with land data assimilation systems. Hydrological Processes, 25(26), 3979-3992, doi:10.1002/hyp.8387

Santanello, J.A., C.D. Peters-Lidard, and S.V. Kumar, 2011: Diagnosing the sensitivity of local land-atmosphere coupling via the soil moisture boundary layer interaction. J. Hydrometeor., 12, 766-786, doi:10.1175/JHM-D-10-05014.1


Dong, J., and C.D. Peters-Lidard, 2010: On the relationship between temperature and MODIS snow cover retrieval errors in the western U.S. IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 3(1), 132-140, doi:10.1109/JSTARS.2009.2039698

Hall, D.K., G.A. Riggs, J.L. Foster, and S.V. Kumar, 2010: Development and evaluation of a cloud-gap-filled MODIS daily snow-cover product. Remote Sens. Environ., 114, 496-503, doi:10.1016/j.rse.2009.10.007

Reichle, R.H., S.V. Kumar, S.P.P. Mahanama, R.D. Koster, and Q. Liu, 2010: Assimilation of satellite-derived skin temperature observations into land surface models. J. Hydrometeor., 11, 1103-1122, doi:10.1175/2010JHM1262.1

Tian, Y., C.D. Peters-Lidard, R.F. Adler, T. Kubota, and T. Ushio, 2010: Evaluation of GSMaP precipitation estimates over contiguous U.S. J. Hydrometeor., 11(2), 566-574, doi:10.1175/2009JHM1190.1


Bounoua, L., A. Safia, J. Masek, C.D. Peters-Lidard, and M.L. Imhoff, 2009: Impact of urban growth on surface climate: A case study in Oran, Algeria. J. Appl. Meteor. Climatol., 48, 217-231, doi:10.1175/2008JAMC2044.1

Kumar, S.V., R.H. Reichle, R.D. Koster, W.T. Crow, and C.D. Peters-Lidard, 2009: Role of subsurface physics in the assimilation of surface soil moisture observations. J. Hydrometeor., 10, 1534-1547, doi:10.1175/2009JHM1134.1

Santanello, Jr., J.A., C.D. Peters-Lidard, S.V. Kumar, C.A. Alonge, and W.-K. Tao, 2009: A modeling and observational framework for diagnosing local land-atmosphere coupling on diurnal time scales. J. Hydrometeor., 10, 577-599, doi:10.1175/2009JHM1066.1

Tao, W.K., J.D. Chern, R. Atlas, D. Randall, M. Khairoutdinov, J.L. Li, D.E. Waliser, A. Hou, X. Lin, C.D. Peters-Lidard, W. Lau, J. Jiang, and J. Simpson, 2009: A multiscale modeling system: Developments, applications, and critical issues. Bull. Amer. Meteor. Soc., 90(4), 515-534, doi:10.1175/2008BAMS2542.1

Tian, Y., C.D. Peters-Lidard, J.B. Eylander, R.J. Joyce, G.J. Huffman, R.F. Adler, K. Hsu, F.J. Turk, M. Garcia, and J. Zeng, 2009: Component analysis of errors in satellite-based precipitation estimates. J. Geophys. Res. Atmos., 114, D24101, doi:10.1029/2009JD011949

Zaitchik, B.F., and M. Rodell, 2009: Forward-looking assimilation of MODIS-derived snow covered area into a land surface model. J. Hydrometeor., 10(1), 130-148, doi:10.1175/2008JHM1042.1


Case, J.L., W.L. Crosson, S.V. Kumar, W.M. Lapenta, and C.D. Peters-Lidard, 2008: Impacts of high-resolution land surface initialization on regional sensible weather forecasts from the WRF model. J. Hydrometeor., 9(6), 1249-1266, doi:10.1175/2008JHM990.1

Garcia, M., C.D. Peters-Lidard, and D.C. Goodrich, 2008: Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United States. Water Resour. Res., 44, W05S13, doi:10.1029/2006WR005788

Kumar, S.V., C.D. Peters-Lidard, J.L. Eastman, and W.-K. Tao, 2008: An integrated high resolution hydrometeorological modeling testbed using LIS and WRF. Environ. Modelling & Software, 23(2), 169-181, doi:10.1016/j.envsoft.2007.05.012

Kumar, S.V., C.D. Peters-Lidard, Y. Tian, R.H. Reichle, J. Geiger, C. Alonge, J. Eylander, and P. Houser, 2008: An integrated hydrologic modeling and data assimilation framework enabled by the Land Information System (LIS). IEEE Computer, 41(12), 52-59, doi:10.1109/MC.2008.475

Kumar, S.V., R.H. Reichle, C.D. Peters-Lidard, R.D. Koster, X. Zhan, W.T. Crow, J.B. Eylander, and P.R. Houser, 2008: A land surface data assimilation framework using the Land Information System: Description and applications. Advances in Water Resources, 31, 1419-1432, doi:10.1016/j.advwatres.2008.01.013

Peters-Lidard, C.D., D.M. Mocko, M. Garcia, J.A. Santanello, Jr., M.A. Tischler, M.S. Moran, and Y. Wu, 2008: Role of precipitation uncertainty in the estimation of hydrologic soil properties using remotely sensed soil moisture in a semiarid environment. Water Resour. Res., 44, W05S18, doi:10.1029/2007WR005884

Tian, Y., C.D. Peters-Lidard, S.V. Kumar, J. Geiger, P.R. Houser, J.L. Eastman, P. Dirmeyer, B. Doty, and J. Adams, 2008: High-performance land surface modeling with a Linux cluster. Comput. Geosci., 34(11), 1492-1504, doi:10.1016/j.cageo.2007.12.014


Peters-Lidard, C.D., P.R. Houser, Y. Tian, S.V. Kumar, J. Geiger, S. Olden, L. Lighty, B. Doty, P. Dirmeyer, J. Adams, K. Mitchell, E.F. Wood and J. Sheffield, 2007: High-performance Earth system modeling with NASA/GSFC's Land Information System. Innovations in Systems and Software Engineering, 3(3), 157-165, doi:10.1007/s11334-007-0028-x

Santanello, Jr., J.A., C.D. Peters-Lidard, M. Garcia, D.M. Mocko, M. Tischler, M.S. Moran, and D.P. Thoma, 2007: Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed. Remote Sens. Environ., 110(1), 79-97, doi:10.1016/j.rse.2007.02.007

Tian, Y., C.D. Peters-Lidard, B.J. Choudhury, and M. Garcia, 2007: Multitemporal analysis of TRMM-based satellite precipitation products for land data assimilation applications. J. Hydrometeor., 8, 1165-1183, doi:10.1175/2007JHM859.1

Tischler, M., M. Garcia, C.D. Peters-Lidard, M.S. Moran, S. Miller, D. Thoma, S.V. Kumar, and J.V. Geiger, 2007: A GIS framework for surface-layer soil moisture estimation combining satellite radar measurements and land surface modeling with soil physical property estimation. Environ. Modeling & Software, 22(6), 891-898, doi:10.1016/j.envsoft.2006.05.022

Zeng, X., W.-K. Tao, M. Zhang, S. Lang, C.D. Peters-Lidard, J. Simpson, S. Xie, S.V. Kumar, J.V. Geiger, C.-L. Shie, and J.L. Eastman, 2007: Evaluating clouds in long-term cloud resolving model simulations with observational data. Journal of Atmospheres, 64(12), 4153-4177, doi:10.1175/2007JAS2170.1


Kumar, S.V., C.D. Peters-Lidard, Y. Tian, P.R. Houser, J. Geiger, S. Olden, L. Lighty, J.L. Eastman, B. Doty, P. Dirmeyer, J. Adams, K. Mitchell, E.F. Wood, and J. Sheffield, 2006: Land Information System - An interoperable framework for high resolution land surface modeling. Environ. Modeling & Software, 21, 1402-1415, doi:10.1016/j.envsoft.2005.07.004