@article{aguilos_warr_irving_gregg_grady_peele_noormets_sun_liu_mcnulty_et al._2022, title={The Unabated Atmospheric Carbon Losses in a Drowning Wetland Forest of North Carolina: A Point of No Return?}, volume={13}, ISSN={1999-4907}, url={http://dx.doi.org/10.3390/f13081264}, DOI={10.3390/f13081264}, abstractNote={Coastal wetlands provide the unique biogeochemical functions of storing a large fraction of the terrestrial carbon (C) pool and being among the most productive ecosystems in the world. However, coastal wetlands face numerous natural and anthropogenic disturbances that threaten their ecological integrity and C storage potential. To monitor the C balance of a coastal forested wetland, we established an eddy covariance flux tower in a natural undrained bottomland hardwood forest in eastern North Carolina, USA. We examined the long-term trends (2009–2019) in gross primary productivity (GPP), ecosystem respiration (RE), and the net ecosystem C exchange (NEE) seasonally and inter-annually. We analyzed the response of C fluxes and balance to climatic and hydrologic forcings and examined the possible effects of rising sea levels on the inland groundwater dynamics. Our results show that in 2009, a higher annual GPP (1922 g C m−2 yr−1) was observed than annual RE (1554 g C m−2 yr−1), resulting in a net C sink (NEE = −368 g C m−2 yr−1). However, the annual C balance switched to a net C source in 2010 and onwards, varying from 87 g C m−2 yr−1 to 759 g C m−2 yr−1. The multiple effects of air temperature (Tair), net radiation (Rn), groundwater table (GWT) depth, and precipitation (p) explained 66%, 71%, and 29% of the variation in GPP, RE, and NEE, respectively (p < 0.0001). The lowering of GWT (−0.01 cm to −14.26 cm) enhanced GPP and RE by 35% and 28%, respectively. We also observed a significant positive correlation between mean sea level and GWT (R2 = 0.11), but not between GWT and p (R2 = 0.02). Cumulative fluxes from 2009 to 2019 showed continuing C losses owing to a higher rate of increase of RE than GPP. This study contributes to carbon balance accounting to improve ecosystem models, relating C dynamics to temporal trends in under-represented coastal forested wetlands.}, number={8}, journal={Forests}, publisher={MDPI AG}, author={Aguilos, Maricar and Warr, Ian and Irving, Madison and Gregg, Olivia and Grady, Stanton and Peele, Toby and Noormets, Asko and Sun, Ge and Liu, Ning and McNulty, Steve and et al.}, year={2022}, month={Aug}, pages={1264} }
 @article{patel_yuter_miller_rhodes_bain_peele_2021, title={The Diurnal Cycle of Winter Season Temperature Errors in the Operational Global Forecast System (GFS)}, volume={48}, ISSN={["1944-8007"]}, url={https://doi.org/10.1029/2021GL095101}, DOI={10.1029/2021GL095101}, abstractNote={AbstractForecasts from NOAA's Global Forecast System (GFS) and the High‐Resolution Rapid Refresh (HRRR) weather models are matched to surface observations for the winter season of November 2019 to March 2020 at 210 airports across the United States. The 2‐m temperature errors, conditioned on observed weather conditions such as cloud cover amount and wind speed, are used to determine the nature of systematic model biases. We observe a strong diurnal cycle in 2‐m temperature errors in the GFS in conditions with 50% and 25% sky cover, with a 1°C warm bias at night and a 2°C cold bias during the day. The HRRR, which uses a different set of physical parameterizations, does not have a clear diurnal cycle in errors under the same conditions. These results highlight the utility of weather‐conditional comparisons across the diurnal cycle to diagnose sources of model weaknesses and to target model improvements.}, number={20}, journal={GEOPHYSICAL RESEARCH LETTERS}, publisher={American Geophysical Union (AGU)}, author={Patel, Ronak N. and Yuter, Sandra E. and Miller, Matthew A. and Rhodes, Spencer R. and Bain, Lily and Peele, Toby W.}, year={2021}, month={Oct} }