A data set of observed daily precipitation, maximum and minimum temperature, gridded to a 1/16° (~6 km) resolution, is described that spans the entire country of Mexico, the conterminous U.S. (CONUS), and regions of Canada south of 53° N for the period 1950–2013. The dataset improves previous products in spatial extent, orographic precipitation adjustment over Mexico and parts of Canada, and reduction of transboundary discontinuities. The impacts of adjusting gridded precipitation for orographic effects are quantified by scaling precipitation to an elevation-aware 1981–2010 precipitation climatology in Mexico and Canada. Differences are evaluated in terms of total precipitation as well as by hydrologic quantities simulated with a land surface model. Overall, orographic correction impacts total precipitation by up to 50% in mountainous regions outside CONUS. Hydrologic fluxes show sensitivities of similar magnitude, with discharge more sensitive than evapotranspiration and soil moisture. Because of the consistent gridding methodology, the current product reduces transboundary discontinuities as compared with a commonly used reanalysis product, making it suitable for estimating large-scale hydrometeorologic phenomena.
We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
Abstract:The sensitivity of Earth's wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992-2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface WAter Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS' FW compares favorably (R 2 = 91%-94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS' inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.
A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO 2 and CH 4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 10 3 km 2 yr À1 ). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr À1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO 2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the MCGUIRE ET AL.MODELING PERMAFROST CARBON DYNAMICS 1015 PUBLICATIONS
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