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Abstract
While snowfall makes a major contribution to the hydrological cycle in the Arctic, state-of-the-art climatologies still significantly disagree. We present a satellite-based characterization of snowfall in the Arctic using CloudSat observations, and compare it with various other climatologies. First, we examine the frequency and phase of precipitation as well as the snowfall rates from CloudSat over 2007–10. Frequency of solid precipitation is higher than 70% over the Arctic Ocean and 95% over Greenland, while mixed precipitation occurs mainly over North Atlantic (50%) and liquid precipitation over land south of 70°N (40%). Intense mean snowfall rates are located over Greenland, the Barents Sea, and the Alaska range (>500 mm yr−1), and maxima are located over the southeast coast of Greenland (up to 2000 mm yr−1). Then we compare snowfall rates with the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim, herein ERA-I) and Arctic System Reanalysis (ASR). Similar general geographical patterns are observed in all datasets, such as the high snowfall rates along the North Atlantic storm track. Yet, there are significant mean snowfall rate differences over the Arctic between 58° and 82°N between ERA-I (153 mm yr−1), ASR version 1 (206 mm yr−1), ASR version 2 (174 mm yr−1), and CloudSat (183 mm yr−1). Snowfall rates and differences are larger over Greenland. Phase attribution is likely to be a significant source of snowfall rate differences, especially regarding ERA-I underestimation. In spite of its nadir-viewing limitations, CloudSat is an essential source of information to characterize snowfall in the Arctic.
Abstract
While snowfall makes a major contribution to the hydrological cycle in the Arctic, state-of-the-art climatologies still significantly disagree. We present a satellite-based characterization of snowfall in the Arctic using CloudSat observations, and compare it with various other climatologies. First, we examine the frequency and phase of precipitation as well as the snowfall rates from CloudSat over 2007–10. Frequency of solid precipitation is higher than 70% over the Arctic Ocean and 95% over Greenland, while mixed precipitation occurs mainly over North Atlantic (50%) and liquid precipitation over land south of 70°N (40%). Intense mean snowfall rates are located over Greenland, the Barents Sea, and the Alaska range (>500 mm yr−1), and maxima are located over the southeast coast of Greenland (up to 2000 mm yr−1). Then we compare snowfall rates with the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim, herein ERA-I) and Arctic System Reanalysis (ASR). Similar general geographical patterns are observed in all datasets, such as the high snowfall rates along the North Atlantic storm track. Yet, there are significant mean snowfall rate differences over the Arctic between 58° and 82°N between ERA-I (153 mm yr−1), ASR version 1 (206 mm yr−1), ASR version 2 (174 mm yr−1), and CloudSat (183 mm yr−1). Snowfall rates and differences are larger over Greenland. Phase attribution is likely to be a significant source of snowfall rate differences, especially regarding ERA-I underestimation. In spite of its nadir-viewing limitations, CloudSat is an essential source of information to characterize snowfall in the Arctic.
Abstract
The sensitivity of sensible and latent heat fluxes and surface temperatures to the parameterization of the soil thermal conductivity is demonstrated using a soil vegetation atmosphere transfer scheme (SVATS) applied to intensive field campaigns (IFCs) 3 and 4 of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). In particular, the commonly used function for soil thermal conductivity presented by M. C. McCumber and R. A. Pielke results in overestimation during wet periods and underestimation during dry periods, as confirmed with thermal conductivity data collected at the FIFE site. The ground heat flux errors affect all components of the energy balance, but are partitioned primarily into the sensible heat flux and surface temperatures in the daytime. At nighttime, errors in the net radiation also become significant in relative terms, although all fluxes are small. In addition, this method erroneously enhances the spatial variability of fluxes associated with soil moisture variability. The authors propose the incorporation of an improved method for predicting thermal conductivity in both frozen and unfrozen soils. This method requires the specification of two additional parameters, and sensitivity studies and tables of recommended parameter values to facilitate the incorporation of this method into SVATS are presented.
Abstract
The sensitivity of sensible and latent heat fluxes and surface temperatures to the parameterization of the soil thermal conductivity is demonstrated using a soil vegetation atmosphere transfer scheme (SVATS) applied to intensive field campaigns (IFCs) 3 and 4 of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). In particular, the commonly used function for soil thermal conductivity presented by M. C. McCumber and R. A. Pielke results in overestimation during wet periods and underestimation during dry periods, as confirmed with thermal conductivity data collected at the FIFE site. The ground heat flux errors affect all components of the energy balance, but are partitioned primarily into the sensible heat flux and surface temperatures in the daytime. At nighttime, errors in the net radiation also become significant in relative terms, although all fluxes are small. In addition, this method erroneously enhances the spatial variability of fluxes associated with soil moisture variability. The authors propose the incorporation of an improved method for predicting thermal conductivity in both frozen and unfrozen soils. This method requires the specification of two additional parameters, and sensitivity studies and tables of recommended parameter values to facilitate the incorporation of this method into SVATS are presented.
Abstract
A frequently encountered difficulty in assessing model-predicted land–atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to evaluate the land surface schemes in coupled models, including comparisons of model-predicted evapotranspiration with values derived from atmospheric water balances, comparison of model-predicted energy and radiative fluxes with tower measurements during periods of intensive observations, comparison of model-predicted runoff with observed streamflow, and comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared—for example, observations are for points or areas much smaller than the model spatial resolution, comparisons are restricted to temporal averages, or the spatial scale is large compared to that resolved by the model. Furthermore, none of the datasets available at present allow an evaluation of the interaction of the water balance components over large regions for long periods. In this study, a model-derived dataset of land surface states and fluxes is presented for the conterminous United States and portions of Canada and Mexico. The dataset spans the period 1950–2000, and is at a 3-h time step with a spatial resolution of ⅛ degree. The data are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. The surface forcings include precipitation and air temperature (both gridded from observations), and derived downward solar and longwave radiation, vapor pressure deficit, and wind. Simulated runoff is shown to match observations quite well over large river basins. On this basis, and given the physically based model parameterizations, it is argued that other terms in the surface water balance (e.g., soil moisture and evapotranspiration) are well represented, at least for the purposes of diagnostic studies such as those in which atmospheric model reanalysis products have been widely used. These characteristics make this dataset useful for a variety of studies, especially where ground observations are lacking.
Abstract
A frequently encountered difficulty in assessing model-predicted land–atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to evaluate the land surface schemes in coupled models, including comparisons of model-predicted evapotranspiration with values derived from atmospheric water balances, comparison of model-predicted energy and radiative fluxes with tower measurements during periods of intensive observations, comparison of model-predicted runoff with observed streamflow, and comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared—for example, observations are for points or areas much smaller than the model spatial resolution, comparisons are restricted to temporal averages, or the spatial scale is large compared to that resolved by the model. Furthermore, none of the datasets available at present allow an evaluation of the interaction of the water balance components over large regions for long periods. In this study, a model-derived dataset of land surface states and fluxes is presented for the conterminous United States and portions of Canada and Mexico. The dataset spans the period 1950–2000, and is at a 3-h time step with a spatial resolution of ⅛ degree. The data are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. The surface forcings include precipitation and air temperature (both gridded from observations), and derived downward solar and longwave radiation, vapor pressure deficit, and wind. Simulated runoff is shown to match observations quite well over large river basins. On this basis, and given the physically based model parameterizations, it is argued that other terms in the surface water balance (e.g., soil moisture and evapotranspiration) are well represented, at least for the purposes of diagnostic studies such as those in which atmospheric model reanalysis products have been widely used. These characteristics make this dataset useful for a variety of studies, especially where ground observations are lacking.
Abstract
This paper summarizes and synthesizes the research carried out under the NOAA Drought Task Force (DTF) and submitted in this special collection. The DTF is organized and supported by NOAA’s Climate Program Office with the National Integrated Drought Information System (NIDIS) and involves scientists from across NOAA, academia, and other agencies. The synthesis includes an assessment of successes and remaining challenges in monitoring and prediction capabilities, as well as a perspective of the current understanding of North American drought and key research gaps. Results from the DTF papers indicate that key successes for drought monitoring include the application of modern land surface hydrological models that can be used for objective drought analysis, including extended retrospective forcing datasets to support hydrologic reanalyses, and the expansion of near-real-time satellite-based monitoring and analyses, particularly those describing vegetation and evapotranspiration. In the area of drought prediction, successes highlighted in the papers include the development of the North American Multimodel Ensemble (NMME) suite of seasonal model forecasts, an established basis for the importance of La Niña in drought events over the southern Great Plains, and an appreciation of the role of internal atmospheric variability related to drought events. Despite such progress, there are still important limitations in our ability to predict various aspects of drought, including onset, duration, severity, and recovery. Critical challenges include (i) the development of objective, science-based integration approaches for merging multiple information sources; (ii) long, consistent hydrometeorological records to better characterize drought; and (iii) extending skillful precipitation forecasts beyond a 1-month lead time.
Abstract
This paper summarizes and synthesizes the research carried out under the NOAA Drought Task Force (DTF) and submitted in this special collection. The DTF is organized and supported by NOAA’s Climate Program Office with the National Integrated Drought Information System (NIDIS) and involves scientists from across NOAA, academia, and other agencies. The synthesis includes an assessment of successes and remaining challenges in monitoring and prediction capabilities, as well as a perspective of the current understanding of North American drought and key research gaps. Results from the DTF papers indicate that key successes for drought monitoring include the application of modern land surface hydrological models that can be used for objective drought analysis, including extended retrospective forcing datasets to support hydrologic reanalyses, and the expansion of near-real-time satellite-based monitoring and analyses, particularly those describing vegetation and evapotranspiration. In the area of drought prediction, successes highlighted in the papers include the development of the North American Multimodel Ensemble (NMME) suite of seasonal model forecasts, an established basis for the importance of La Niña in drought events over the southern Great Plains, and an appreciation of the role of internal atmospheric variability related to drought events. Despite such progress, there are still important limitations in our ability to predict various aspects of drought, including onset, duration, severity, and recovery. Critical challenges include (i) the development of objective, science-based integration approaches for merging multiple information sources; (ii) long, consistent hydrometeorological records to better characterize drought; and (iii) extending skillful precipitation forecasts beyond a 1-month lead time.
Abstract
Two commercial large-aperture scintillometers, Scintec BLS900, were tested on pathlengths of 1840 and 4200 m at about 45–65 m above ground in Helsinki, Finland. From July 2011 through June 2012, large variability in diurnal and annual cycles of both the temperature structure parameter 
Abstract
Two commercial large-aperture scintillometers, Scintec BLS900, were tested on pathlengths of 1840 and 4200 m at about 45–65 m above ground in Helsinki, Finland. From July 2011 through June 2012, large variability in diurnal and annual cycles of both the temperature structure parameter
Abstract
This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.
Abstract
This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.
The present paper describes the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study (VOCALS), an international research program focused on the improved understanding and modeling of the southeastern Pacific (SEP) climate system on diurnal to interannual time scales. In the framework of the SEP climate, VOCALS has two fundamental objectives: 1) improved simulations by coupled atmosphere–ocean general circulation models (CGCMs), with an emphasis on reducing systematic errors in the region; and 2) improved estimates of the indirect effects of aerosols on low clouds and climate, with an emphasis on the more precise quantification of those effects. VOCALS major scientific activities are outlined, and selected achievements are highlighted. Activities described include monitoring in the region, a large international field campaign (the VOCALS Regional Experiment), and two model assessments. The program has already produced significant advances in the understanding of major issues in the SEP: the coastal circulation and the diurnal cycle, the ocean heat budget, factors controlling precipitation and formation of pockets of open cells in stratocumulus decks, aerosol impacts on clouds, and estimation of the first aerosol indirect effect. The paper concludes with a brief presentation on VOCALS contributions to community capacity building before a summary of scientific findings and remaining questions.
The present paper describes the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study (VOCALS), an international research program focused on the improved understanding and modeling of the southeastern Pacific (SEP) climate system on diurnal to interannual time scales. In the framework of the SEP climate, VOCALS has two fundamental objectives: 1) improved simulations by coupled atmosphere–ocean general circulation models (CGCMs), with an emphasis on reducing systematic errors in the region; and 2) improved estimates of the indirect effects of aerosols on low clouds and climate, with an emphasis on the more precise quantification of those effects. VOCALS major scientific activities are outlined, and selected achievements are highlighted. Activities described include monitoring in the region, a large international field campaign (the VOCALS Regional Experiment), and two model assessments. The program has already produced significant advances in the understanding of major issues in the SEP: the coastal circulation and the diurnal cycle, the ocean heat budget, factors controlling precipitation and formation of pockets of open cells in stratocumulus decks, aerosol impacts on clouds, and estimation of the first aerosol indirect effect. The paper concludes with a brief presentation on VOCALS contributions to community capacity building before a summary of scientific findings and remaining questions.
Abstract
A focused cavity aerosol spectrometer aboard a NASA ER-2 high-altitude aircraft provided high-resolution measurements of the size of the stratospheric particles in the 0.06–2.0-µm-diameter range in flights following the eruption of Mount Pinatubo in 1991. Effects of anisokinetic sampling and evaporation in the sampling system were accounted for by means adapted and specifically developed for this instrument. Calibrations with monodisperse aerosol particles provided the instrument's response matrix, which upon inversion during data reduction yielded the particle size distributions. The resultant dataset is internally consistent and generally shows agreement to within a factor of 2 with comparable measurements simultaneously obtained by a condensation nuclei counter, a forward-scattering spectrometer probe, and aerosol particle impactors, as well as with nearby extinction profiles obtained by satellite measurements and with lidar measurements of backscatter.
Abstract
A focused cavity aerosol spectrometer aboard a NASA ER-2 high-altitude aircraft provided high-resolution measurements of the size of the stratospheric particles in the 0.06–2.0-µm-diameter range in flights following the eruption of Mount Pinatubo in 1991. Effects of anisokinetic sampling and evaporation in the sampling system were accounted for by means adapted and specifically developed for this instrument. Calibrations with monodisperse aerosol particles provided the instrument's response matrix, which upon inversion during data reduction yielded the particle size distributions. The resultant dataset is internally consistent and generally shows agreement to within a factor of 2 with comparable measurements simultaneously obtained by a condensation nuclei counter, a forward-scattering spectrometer probe, and aerosol particle impactors, as well as with nearby extinction profiles obtained by satellite measurements and with lidar measurements of backscatter.
The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The network's key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and the operational Doppler radar network. Examples are presented as a testimony to the potential of the network for urban studies, such as (i) evidence of a stable boundary layer possibly coupled to an urban surface, (ii) the comparison of scintillometer data with sonic anemometry above an urban surface, (iii) the application of scanning lidar over a city, and (iv) combination of sodar and lidar to give a fuller range of sampling heights for boundary layer profiling.
The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The network's key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and the operational Doppler radar network. Examples are presented as a testimony to the potential of the network for urban studies, such as (i) evidence of a stable boundary layer possibly coupled to an urban surface, (ii) the comparison of scintillometer data with sonic anemometry above an urban surface, (iii) the application of scanning lidar over a city, and (iv) combination of sodar and lidar to give a fuller range of sampling heights for boundary layer profiling.
Abstract
Rapid adjustments—the response of meteorology to external forcing while sea surface temperatures (SST) and sea ice are held fixed—can affect the midlatitude circulation and contribute to long-term forced circulation responses in climate simulations. This study examines rapid adjustments in the Southern Hemisphere (SH) circulation using nine models from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), which perform fixed SST and coupled ocean experiments for five perturbations: a doubling of carbon dioxide (2xCO2), a tripling of methane (3xCH4), a fivefold increase in sulfate aerosol (5xSO4), a tenfold increase in black carbon aerosol (10xBC), and a 2% increase in solar constant (2%Sol). In the coupled experiments, the SH eddy-driven jet shifts poleward and strengthens for forcings that produce global warming (and vice versa for 5xSO4), with the strongest response found in austral summer. In austral winter, the responses project more strongly onto a change in jet strength. For 10xBC, which induces strong shortwave absorption, the multimodel mean (MMM) rapid adjustment in DJF jet latitude is ~75% of the change in the coupled simulations. For the other forcings, which induce larger SST changes, the effect of SST-mediated feedbacks on the SH circulation is larger than the rapid adjustment. Nevertheless, for these perturbations the magnitude of the MMM jet shift due to the rapid adjustment is still around 20%–30% of that in the coupled experiments. The results demonstrate the need to understand the mechanisms for rapid adjustments in the midlatitude circulation, in addition to the effect of changing SSTs.
Abstract
Rapid adjustments—the response of meteorology to external forcing while sea surface temperatures (SST) and sea ice are held fixed—can affect the midlatitude circulation and contribute to long-term forced circulation responses in climate simulations. This study examines rapid adjustments in the Southern Hemisphere (SH) circulation using nine models from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), which perform fixed SST and coupled ocean experiments for five perturbations: a doubling of carbon dioxide (2xCO2), a tripling of methane (3xCH4), a fivefold increase in sulfate aerosol (5xSO4), a tenfold increase in black carbon aerosol (10xBC), and a 2% increase in solar constant (2%Sol). In the coupled experiments, the SH eddy-driven jet shifts poleward and strengthens for forcings that produce global warming (and vice versa for 5xSO4), with the strongest response found in austral summer. In austral winter, the responses project more strongly onto a change in jet strength. For 10xBC, which induces strong shortwave absorption, the multimodel mean (MMM) rapid adjustment in DJF jet latitude is ~75% of the change in the coupled simulations. For the other forcings, which induce larger SST changes, the effect of SST-mediated feedbacks on the SH circulation is larger than the rapid adjustment. Nevertheless, for these perturbations the magnitude of the MMM jet shift due to the rapid adjustment is still around 20%–30% of that in the coupled experiments. The results demonstrate the need to understand the mechanisms for rapid adjustments in the midlatitude circulation, in addition to the effect of changing SSTs.
