Joseph Hamman
University of Washington
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Joseph Hamman.
Journal of Climate | 2016
Alice K. DuVivier; John J. Cassano; Anthony P. Craig; Joseph Hamman; Wieslaw Maslowski; Bart Nijssen; Robert Osinski; Andrew Roberts
AbstractStrong, mesoscale tip jets and barrier winds that occur along the southeastern Greenland coast have the potential to impact deep convection in the Irminger Sea. The self-organizing map (SOM) training algorithm was used to identify 12 wind patterns that represent the range of winter [November–March (NDJFM)] wind regimes identified in the fully coupled Regional Arctic System Model (RASM) during 1990–2010. For all wind patterns, the ocean loses buoyancy, primarily through the turbulent sensible and latent heat fluxes; haline contributions to buoyancy change were found to be insignificant compared to the thermal contributions. Patterns with westerly winds at the Cape Farewell area had the largest buoyancy loss over the Irminger and Labrador Seas due to large turbulent fluxes from strong winds and the advection of anomalously cold, dry air over the warmer ocean. Similar to observations, RASM simulated typical ocean mixed layer depths (MLD) of approximately 400 m throughout the Irminger basin, with indi...
Journal of Geophysical Research | 2017
Joseph Hamman; Bart Nijssen; Andrew Roberts; Anthony P. Craig; Wieslaw Maslowski; Robert Osinski
The coastal streamflow flux from the Arctic drainage basin is an important driver of dynamics in the coupled ice-ocean system. Comprising more than one-third of the total freshwater flux into the Arctic Ocean, streamflow is a key component of the regional and global freshwater cycle. To better represent the coupling of the streamflow flux to the ocean, we have developed and applied the RVIC streamflow routing model within the Regional Arctic System Model (RASM). The RASM is a high-resolution regional Earth System Model whose domain includes all of the Arctic drainage basin. In this paper, we introduce the RVIC streamflow routing model, detailing its application within RASM and its advancements in terms of representing high-resolution streamflow processes. We evaluate model simulated streamflow relative to in-situ observations and demonstrate a method for improving model performance using a simple optimization procedure. We also present a new, spatially and temporally consistent, high-resolution dataset of coastal freshwater fluxes for the Arctic drainage basin and surrounding areas that is based on a fully-coupled RASM simulation and intended for use in Arctic Ocean modeling applications. This dataset is evaluated relative to other coastal streamflow datasets commonly used by the ocean modeling community. We demonstrate that the RASM-simulated streamflow flux better represents the annual cycle than existing datasets, especially in ungauged areas. Finally, we assess the impact that streamflow has on the coupled ice-ocean system, finding that the presence of streamflow leads to reduced sea surface salinity, increased sea surface temperatures, and decreased sea ice thickness. This article is protected by copyright. All rights reserved.
Journal of Climate | 2016
Joseph Hamman; Bart Nijssen; Michael A. Brunke; John J. Cassano; Anthony P. Craig; Alice K. DuVivier; Mimi Hughes; Dennis P. Lettenmaier; Wieslaw Maslowski; Robert Osinski; Andrew Roberts; Xubin Zeng
AbstractThe Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979–2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are ...
Journal of Climate | 2017
John J. Cassano; Alice K. DuVivier; Andrew Roberts; Mimi Hughes; Mark W. Seefeldt; Michael A. Brunke; Anthony P. Craig; Brandon Fisel; William J. Gutowski; Joseph Hamman; Matthew E. Higgins; Wieslaw Maslowski; Bart Nijssen; Robert Osinski; Xubin Zeng
AbstractThe near-surface climate, including the atmosphere, ocean, sea ice, and land state and fluxes, in the initial version of the Regional Arctic System Model (RASM) are presented. The sensitivity of the RASM near-surface climate to changes in atmosphere, ocean, and sea ice parameters and physics is evaluated in four simulations. The near-surface atmospheric circulation is well simulated in all four RASM simulations but biases in surface temperature are caused by biases in downward surface radiative fluxes. Errors in radiative fluxes are due to biases in simulated clouds with different versions of RASM simulating either too much or too little cloud radiative impact over open ocean regions and all versions simulating too little cloud radiative impact over land areas. Cold surface temperature biases in the central Arctic in winter are likely due to too few or too radiatively thin clouds. The precipitation simulated by RASM is sensitive to changes in evaporation that were linked to sea surface temperature...
Northwest Science | 2016
Joseph Hamman; Alan F. Hamlet; Se-Yeun Lee; Roger Fuller; Eric E. Grossman
Abstract Current understanding of the combined effects of sea level rise (SLR), storm surge, and changes in river flooding on near-coastal environments is very limited. This project uses a suite of numerical models to examine the combined effects of projected future climate change on flooding in the Skagit floodplain and estuary. Statistically and dynamically downscaled global climate model scenarios from the ECHAM-5 GCM were used as the climate forcings. Unregulated daily river flows were simulated using the VIC hydrology model, and regulated river flows were simulated using the SkagitSim reservoir operations model. Daily tidal anomalies (TA) were calculated using a regression approach based on ENSO and atmospheric pressure forcing simulated by the WRF regional climate model. A 2-D hydrodynamic model was used to estimate water surface elevations in the Skagit floodplain using resampled hourly hydrographs keyed to regulated daily flood flows produced by the reservoir simulation model, and tide predictions adjusted for SLR and TA. Combining peak annual TA with projected sea level rise, the historical (1970–1999) 100-yr peak high water level is exceeded essentially every year by the 2050s. The combination of projected sea level rise and larger floods by the 2080s yields both increased flood inundation area (+ 74%), and increased average water depth (+ 25 cm) in the Skagit floodplain during a 100-year flood. Adding sea level rise to the historical FEMA 100-year flood resulted in a 35% increase in inundation area by the 2040s, compared to a 57% increase when both SLR and projected changes in river flow were combined.
Journal of open research software | 2017
Stephan Hoyer; Joseph Hamman
Geoscientific Model Development | 2018
Joseph Hamman; Bart Nijssen; Theodore J. Bohn; Diana Gergel; Yixin Mao
Geoscientific Model Development Discussions | 2018
Michael A. Brunke; John J. Cassano; Nicholas Dawson; Alice K. DuVivier; William J. Gutowski; Joseph Hamman; Wieslaw Maslowski; Bart Nijssen; J.E. Jack Reeves Eyre; Jose C. Renteria; Andrew Roberts; Xubin Zeng
Climate Services | 2018
Julie A. Vano; Jeffrey R. Arnold; Bart Nijssen; Martyn P. Clark; Andrew W. Wood; Ethan D. Gutmann; Nans Addor; Joseph Hamman; Flavio Lehner
Journal of Geophysical Research | 2017
Joseph Hamman; Bart Nijssen; Andrew Roberts; Anthony P. Craig; Wieslaw Maslowski; Robert Osinski
Collaboration
Dive into the Joseph Hamman's collaboration.
Cooperative Institute for Research in Environmental Sciences
View shared research outputs