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- Author or Editor: M. A. Rawlins x
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Abstract
Hydrological models require accurate precipitation and air temperature inputs in order to adequately depict water fluxes and storages across Arctic regions. Biases such as gauge undercatch, as well as uncertainties in numerical weather prediction reanalysis data that propagate through water budget models, limit the ability to accurately model the terrestrial arctic water cycle. A hydrological model forced with three climate datasets and three methods of estimating potential evapotranspiration (PET) was used to better understand the impact of these processes on simulated water fluxes across the Western Arctic Linkage Experiment (WALE) domain. Climate data were drawn from the NCEP–NCAR reanalysis (NNR) (NCEP1), a modified version of the NNR (NCEP2), and the Willmott–Matsuura (WM) dataset. PET methods applied in the model were Hamon, Penman–Monteith, and Penman–Monteith using adjusted vapor pressure data.
High vapor pressures in the NNR lead to low simulated evapotranspiration (ET) in model runs using the Penman–Monteith PET method, resulting in increased runoff. Annual ET derived from simulations using Penman–Monteith PET was half the magnitude of ET simulated when the Hamon method was used. Adjustments made to the reanalysis vapor pressure data increased the simulated ET flux, reducing simulated runoff. Using the NCEP2 or WM climate data, along with the Penman–Monteith PET function, results in agreement to within 7% between the simulated and observed runoff across the Yukon River basin. The results reveal the high degree of uncertainty present in climate data and the range of water fluxes generated from common model drivers. This suggests the need for thorough evaluations of model requirements and potential biases in forcing data, as well as corroborations with observed data, in all efforts to simulate arctic water balances.
Abstract
Hydrological models require accurate precipitation and air temperature inputs in order to adequately depict water fluxes and storages across Arctic regions. Biases such as gauge undercatch, as well as uncertainties in numerical weather prediction reanalysis data that propagate through water budget models, limit the ability to accurately model the terrestrial arctic water cycle. A hydrological model forced with three climate datasets and three methods of estimating potential evapotranspiration (PET) was used to better understand the impact of these processes on simulated water fluxes across the Western Arctic Linkage Experiment (WALE) domain. Climate data were drawn from the NCEP–NCAR reanalysis (NNR) (NCEP1), a modified version of the NNR (NCEP2), and the Willmott–Matsuura (WM) dataset. PET methods applied in the model were Hamon, Penman–Monteith, and Penman–Monteith using adjusted vapor pressure data.
High vapor pressures in the NNR lead to low simulated evapotranspiration (ET) in model runs using the Penman–Monteith PET method, resulting in increased runoff. Annual ET derived from simulations using Penman–Monteith PET was half the magnitude of ET simulated when the Hamon method was used. Adjustments made to the reanalysis vapor pressure data increased the simulated ET flux, reducing simulated runoff. Using the NCEP2 or WM climate data, along with the Penman–Monteith PET function, results in agreement to within 7% between the simulated and observed runoff across the Yukon River basin. The results reveal the high degree of uncertainty present in climate data and the range of water fluxes generated from common model drivers. This suggests the need for thorough evaluations of model requirements and potential biases in forcing data, as well as corroborations with observed data, in all efforts to simulate arctic water balances.
Abstract
Two autonomous ozone measurement systems for use on ocean buoys and towers have been built and are discussed herein. They are based on low-power atmospheric ozone sensors from Physical Sciences Inc. (PSI) and 2B Technologies. The PSI sensor operates at 1 Hz with a precision of 1 ppb but requires about 45 W with the present data system; the 2B makes a measurement every 10 s with a precision of 1–2 ppb and uses less than 4 W. The sensors have been packaged in watertight enclosures with a set of valves and filters to keep out seawater and aerosols. A controller uses data from the sensors and a meteorological system to determine whether sampling should proceed. If a sensor malfunction (such as an incorrect valve position or a temperature beyond its proper range) is detected, the controller attempts to correct it. Both sensors have been tested and used over the ocean, and one complete ozone measurement system (with the PSI sensor) has been successfully deployed on a buoy off Woods Hole, Massachusetts. In 2003, this system was operated at the Chesapeake Bay Lighthouse Tower for over a month with excellent results. The 2B system was also successfully tested in 2003 at a nearby offshore tower. The design of the systems and their testing and deployments are described, and data from some of the first experiments are presented.
Abstract
Two autonomous ozone measurement systems for use on ocean buoys and towers have been built and are discussed herein. They are based on low-power atmospheric ozone sensors from Physical Sciences Inc. (PSI) and 2B Technologies. The PSI sensor operates at 1 Hz with a precision of 1 ppb but requires about 45 W with the present data system; the 2B makes a measurement every 10 s with a precision of 1–2 ppb and uses less than 4 W. The sensors have been packaged in watertight enclosures with a set of valves and filters to keep out seawater and aerosols. A controller uses data from the sensors and a meteorological system to determine whether sampling should proceed. If a sensor malfunction (such as an incorrect valve position or a temperature beyond its proper range) is detected, the controller attempts to correct it. Both sensors have been tested and used over the ocean, and one complete ozone measurement system (with the PSI sensor) has been successfully deployed on a buoy off Woods Hole, Massachusetts. In 2003, this system was operated at the Chesapeake Bay Lighthouse Tower for over a month with excellent results. The 2B system was also successfully tested in 2003 at a nearby offshore tower. The design of the systems and their testing and deployments are described, and data from some of the first experiments are presented.
Abstract
The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate available for driving hydrologic and ecosystem models within the western Arctic during the late twentieth century indicate that there are substantial differences among the mean states of datasets for temperature, precipitation, vapor pressure, and radiation variables. Among the studies that examined temporal trends among the alternative climate datasets, there is not much consensus on trends among the datasets. In contrast, monthly and interannual variations of some variables showed some correlation across the datasets. The application of hydrology models driven by alternative climate drivers revealed that the simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellite-based analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by different models from 1980 to 2000 was generally consistent with estimates based on the satellite record for applications driven with alternative climate datasets. However, the magnitude of the fluxes differed by as much as a factor of 2.5 among applications driven with different climate data, and spatial patterns of temporal trends in carbon dynamics were quite different among simulations. Finally, the study identified that the simulation of fire by ecosystem models is particularly sensitive to alternative climate datasets, with little or no fire simulated for some datasets. The results of WALE identify the importance of conducting retrospective analyses prior to coupling hydrology and ecosystem models with climate system models. For applications of hydrology and ecosystem models driven by projections of future climate, the authors recommend a coupling strategy in which future changes from climate model simulations are superimposed on the present mean climate of the most reliable datasets of historical climate.
Abstract
The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate available for driving hydrologic and ecosystem models within the western Arctic during the late twentieth century indicate that there are substantial differences among the mean states of datasets for temperature, precipitation, vapor pressure, and radiation variables. Among the studies that examined temporal trends among the alternative climate datasets, there is not much consensus on trends among the datasets. In contrast, monthly and interannual variations of some variables showed some correlation across the datasets. The application of hydrology models driven by alternative climate drivers revealed that the simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellite-based analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by different models from 1980 to 2000 was generally consistent with estimates based on the satellite record for applications driven with alternative climate datasets. However, the magnitude of the fluxes differed by as much as a factor of 2.5 among applications driven with different climate data, and spatial patterns of temporal trends in carbon dynamics were quite different among simulations. Finally, the study identified that the simulation of fire by ecosystem models is particularly sensitive to alternative climate datasets, with little or no fire simulated for some datasets. The results of WALE identify the importance of conducting retrospective analyses prior to coupling hydrology and ecosystem models with climate system models. For applications of hydrology and ecosystem models driven by projections of future climate, the authors recommend a coupling strategy in which future changes from climate model simulations are superimposed on the present mean climate of the most reliable datasets of historical climate.
Abstract
Hydrologic cycle intensification is an expected manifestation of a warming climate. Although positive trends in several global average quantities have been reported, no previous studies have documented broad intensification across elements of the Arctic freshwater cycle (FWC). In this study, the authors examine the character and quantitative significance of changes in annual precipitation, evapotranspiration, and river discharge across the terrestrial pan-Arctic over the past several decades from observations and a suite of coupled general circulation models (GCMs). Trends in freshwater flux and storage derived from observations across the Arctic Ocean and surrounding seas are also described.
With few exceptions, precipitation, evapotranspiration, and river discharge fluxes from observations and the GCMs exhibit positive trends. Significant positive trends above the 90% confidence level, however, are not present for all of the observations. Greater confidence in the GCM trends arises through lower interannual variability relative to trend magnitude. Put another way, intrinsic variability in the observations tends to limit confidence in trend robustness. Ocean fluxes are less certain, primarily because of the lack of long-term observations. Where available, salinity and volume flux data suggest some decrease in saltwater inflow to the Barents Sea (i.e., a decrease in freshwater outflow) in recent decades. A decline in freshwater storage across the central Arctic Ocean and suggestions that large-scale circulation plays a dominant role in freshwater trends raise questions as to whether Arctic Ocean freshwater flows are intensifying. Although oceanic fluxes of freshwater are highly variable and consistent trends are difficult to verify, the other components of the Arctic FWC do show consistent positive trends over recent decades. The broad-scale increases provide evidence that the Arctic FWC is experiencing intensification. Efforts that aim to develop an adequate observation system are needed to reduce uncertainties and to detect and document ongoing changes in all system components for further evidence of Arctic FWC intensification.
Abstract
Hydrologic cycle intensification is an expected manifestation of a warming climate. Although positive trends in several global average quantities have been reported, no previous studies have documented broad intensification across elements of the Arctic freshwater cycle (FWC). In this study, the authors examine the character and quantitative significance of changes in annual precipitation, evapotranspiration, and river discharge across the terrestrial pan-Arctic over the past several decades from observations and a suite of coupled general circulation models (GCMs). Trends in freshwater flux and storage derived from observations across the Arctic Ocean and surrounding seas are also described.
With few exceptions, precipitation, evapotranspiration, and river discharge fluxes from observations and the GCMs exhibit positive trends. Significant positive trends above the 90% confidence level, however, are not present for all of the observations. Greater confidence in the GCM trends arises through lower interannual variability relative to trend magnitude. Put another way, intrinsic variability in the observations tends to limit confidence in trend robustness. Ocean fluxes are less certain, primarily because of the lack of long-term observations. Where available, salinity and volume flux data suggest some decrease in saltwater inflow to the Barents Sea (i.e., a decrease in freshwater outflow) in recent decades. A decline in freshwater storage across the central Arctic Ocean and suggestions that large-scale circulation plays a dominant role in freshwater trends raise questions as to whether Arctic Ocean freshwater flows are intensifying. Although oceanic fluxes of freshwater are highly variable and consistent trends are difficult to verify, the other components of the Arctic FWC do show consistent positive trends over recent decades. The broad-scale increases provide evidence that the Arctic FWC is experiencing intensification. Efforts that aim to develop an adequate observation system are needed to reduce uncertainties and to detect and document ongoing changes in all system components for further evidence of Arctic FWC intensification.
