Characteristics of evapotranspiration from a permafrost black spruce forest in interior Alaska

Nakai, T.; Kim, Yongwon; Busey, R.; Suzuki, Rikie; Nagai, Shin; Kobayashi, Hideki; Park, Hotaek; Sugiura, Komei; Ito, Akihiko

doi:10.1016/j.polar.2013.03.003

Cited by 65 publications

(49 citation statements)

References 34 publications

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“…2). At the boreal forest site, the model-simulated ALT (81 ± 15 cm) during the study period (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) was much larger than the ALT value reported at the tower site (∼ 43 cm, Nakai et al, 2013); however, the model-simulated ALT was close to the ALT (74±17 cm) calculated from the in situ soil temperature measurements during the observation period (2011)(2012)(2013). The seasonality of the model-simulated soil thaw depth also generally followed the pattern of soil thaw depth calculated from the in situ soil temperature observations (Fig.…”

Section: Comparison With In Situ Measurementsmentioning

confidence: 68%

“…The three tower sites were selected mainly for having relatively good-quality surface meteorology and temperature measurements, and supporting information on ground surface conditions. All three tower sites are underlain by permafrost, with relatively large soil organic layer thickness (OLT) and shallow seasonal thaw depth (∼ 40 cm) (Euskirchen et al, 2012;Nakai et al, 2013;Oechel et al, 2014). For the tower site comparisons, the soil process model was parameterized and driven by local tower site meteorological and OLT observations when available.…”

Section: In Situ Datamentioning

confidence: 99%

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Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

Kimball

Chen

et al. 2018

The Cryosphere

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Abstract. An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ∼ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L + P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higherpermafrost-probability (PP ≥ 70 %) areas (n = 33; R = 0.60; mean bias = 1.58 cm; RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr −1 ) and much larger increases (> 3 cm yr −1 ) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.

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Section: Comparison With In Situ Measurementsmentioning

confidence: 68%

Section: In Situ Datamentioning

confidence: 99%

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

Kimball

Chen

et al. 2018

The Cryosphere

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“…1): Fairbanks in Alaska (Nakai et al, 2013), Tiksi (Kodama et al, 2007;Yabuki et al, 2011;Watanabe et al, 2000) and Chokurdakh (Iwahana et al, 2014) in northeast Siberia, Yakutsk in central east Siberia (Ohta et al, 2001(Ohta et al, , 2008(Ohta et al, , 2014Kotani et al, 2013;Lopez et al, 2007;Yabuki et al, 2011), Tura in central Siberia , and Kevo in northern Europe (Sato et al, 2001; precipitation and air pressure in Kevo are provided by Finnish Meteorological Institute). The longitudes and latitudes of the sites are summarized in Table 1, as well as the observational periods for data collection.…”

Section: Study Sites and Observational Periodsmentioning

confidence: 99%

“…Fairbanks is located in the discontinuous permafrost zone with open black spruce forest; Tiksi and Chokurdakh are in the continuous permafrost zone, the former with tundra vegetation and the latter in the transition between tundra and taiga; Yakutsk and Tura are in the continuous permafrost zone with larch forest; and Kevo (Nakai et al, 2013). b Average canopy height is 18 m (Ohta et al, 2001).…”

Section: Study Sites and Observational Periodsmentioning

confidence: 99%

“…tic conditions at those sites. It is very difficult, however, to create a complete data set for driving a model solely from observations, which are prone to data gaps due to instrument problems, human mistakes, or other reasons (Nakai et al, 2013;Kodama et al, 2007;Watanabe et al, 2000;Iwahana et al, 2014;Ohta et al, 2001Ohta et al, , 2008Ohta et al, , 2014Kotani et al, 2013;Lopez et al, 2007;Nakai et al, 2008;Sato et al, 2001). Despite efforts to maintain and improve our observational network, data gaps are unavoidable, as the availability of instrumentation is often limited by logistical or funding issues.…”

Section: Introductionmentioning

confidence: 99%

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The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set

Sueyoshi

Saitô

Miyazaki

et al. 2016

Earth Syst. Sci. Data

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Abstract. Here, the authors describe the construction of a forcing data set for land surface models (including both physical and biogeochemical models; LSMs) with eight meteorological variables for the 35-year period from 1979 to 2013. The data set is intended for use in a model intercomparison study, called GTMIP, which is a part of the Japanese-funded Arctic Climate Change Research Project. In order to prepare a set of site-fitted forcing data for LSMs with realistic yet continuous entries (i.e. without missing data), four observational sites across the pan-Arctic region (Fairbanks, Tiksi, Yakutsk, and Kevo) were selected to construct a blended data set using both global reanalysis and observational data. Marked improvements were found in the diurnal cycles of surface air temperature and humidity, wind speed, and precipitation. The data sets and participation in GTMIP are open to the scientific community

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Change in surface energy balance in Alaska due to fire and spring warming, based on upscaling eddy covariance measurements

et al. 2014

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Warming in northern high latitudes has changed the energy balance between terrestrial ecosystems and the atmosphere. This study evaluated changes in regional surface energy exchange in Alaska from 2000 to 2011 when substantial declines in spring snow cover due to spring warming and large-scale fire events were observed. Energy fluxes from a network of 20 eddy covariance sites were upscaled using a support vector regression (SVR) model, by combining satellite remote sensing data and global climate data. Based on site-scale analysis, SVR reproduced observed net radiation, sensible heat flux, latent heat flux, and ground heat flux; 8 day root-mean-square errors for these variables were 15, 10, 9, and 3 W m À2 , respectively. Based on upscaled fluxes, decreases in spring snow cover induced an increase in surface net radiation, a net heating effect, of 0.56 W m À2 decade À1. This heating effect was comparable to the net cooling effect due to increased fire extent during the study period (up to 0.59 W m À2 decade À1). These land cover effects were larger than the change in the energy forcing associated with CO 2 balance for the Alaska region. Spring warming and postfire land cover change increased the regional latent heat flux. The regional sensible heat flux decreased with the postfire land cover change. Our results highlight the importance of positive spring snow albedo feedback to climate and a postfire negative feedback under the expected warming climate in the Arctic.

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Characteristics of evapotranspiration from a permafrost black spruce forest in interior Alaska

Cited by 65 publications

References 34 publications

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set

Change in surface energy balance in Alaska due to fire and spring warming, based on upscaling eddy covariance measurements

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