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Abstract
Satellite estimates of surface shortwave radiation (SWR) at high latitudes agree less with ground observations than at other locations; moreover, ground observations at such latitudes are scarce. The comprehensive observations of radiative fluxes made since 1977 by the Department of Energy Atmospheric Radiation Measurement (ARM) Program at the Barrow North Slope of Alaska (NSA) site are unique. They provide an opportunity to revisit accuracy estimates of remote sensing products at these latitudes, which are problematic because the melting of snow/ice and lower solar elevation make the satellite retrievals more difficult.
A newly developed inference scheme for deriving SWR from the Moderate Resolution Imaging Spectroradiometer (MODIS; Terra and Aqua) that utilizes updated information on surface properties over snow and sea ice will be evaluated against these ground measurements and compared with other satellite and model products. Results show that the MODIS-based estimates are in good agreement with observations, with a bias of −5.3 W m−2 (−4% of mean observations) for the downward SWR, a bias of −5.3 W m−2 (−7%) for upward SWR, a bias of 1 (1%) for net SWR, and a bias of −0.001 (0%) for surface albedo. As such, the MODIS estimates of SWR can be useful for numerical model evaluations and for estimating the energy budgets at high latitudes.
Abstract
Satellite estimates of surface shortwave radiation (SWR) at high latitudes agree less with ground observations than at other locations; moreover, ground observations at such latitudes are scarce. The comprehensive observations of radiative fluxes made since 1977 by the Department of Energy Atmospheric Radiation Measurement (ARM) Program at the Barrow North Slope of Alaska (NSA) site are unique. They provide an opportunity to revisit accuracy estimates of remote sensing products at these latitudes, which are problematic because the melting of snow/ice and lower solar elevation make the satellite retrievals more difficult.
A newly developed inference scheme for deriving SWR from the Moderate Resolution Imaging Spectroradiometer (MODIS; Terra and Aqua) that utilizes updated information on surface properties over snow and sea ice will be evaluated against these ground measurements and compared with other satellite and model products. Results show that the MODIS-based estimates are in good agreement with observations, with a bias of −5.3 W m−2 (−4% of mean observations) for the downward SWR, a bias of −5.3 W m−2 (−7%) for upward SWR, a bias of 1 (1%) for net SWR, and a bias of −0.001 (0%) for surface albedo. As such, the MODIS estimates of SWR can be useful for numerical model evaluations and for estimating the energy budgets at high latitudes.
Abstract
The geographic and temporal variability of the surface–3600-m cloud frequency and cloud-base height over the contiguous United States for a 5-yr period (2008–12) and the interannual variations for a 16-yr period (2000–15) are described using information from the Automated Surface Observing System (ASOS) observations. Clouds were separated into four categories by the cloud amount reported by ASOS: few (FEW), scattered (SCT), broken (BKN), and overcast (OVC). The geographic distributions and seasonal and diurnal cycles of the four categories of surface–3600-m cloud frequency have different patterns. Cloud frequency of FEW, SCT, and BKN peaks just after noon, whereas the frequency of OVC peaks in the early morning. However, the geographic distributions and seasonal and diurnal cycles of the four categories of the surface–3600-m cloud-base height are similar. The diurnal cycles of the cloud-base height within the surface–3600-m level present a minimum in the morning and peak in the late afternoon or early evening. Cloud frequency and cloud-base height within this range are closely related to surface air temperature and humidity conditions. From 2000 to 2015, the cloud frequency in the contiguous United States showed a positive trend of 0.28% yr−1 while the cloud-base height showed a negative trend of −4 m yr−1 for the surface–3600-m level, accompanied with a positive trend of precipitation days (0.14 days yr−1). Moreover, the increase of cloud frequency and the decrease of cloud-base height were most obvious in winter in the eastern half of the contiguous United States.
Abstract
The geographic and temporal variability of the surface–3600-m cloud frequency and cloud-base height over the contiguous United States for a 5-yr period (2008–12) and the interannual variations for a 16-yr period (2000–15) are described using information from the Automated Surface Observing System (ASOS) observations. Clouds were separated into four categories by the cloud amount reported by ASOS: few (FEW), scattered (SCT), broken (BKN), and overcast (OVC). The geographic distributions and seasonal and diurnal cycles of the four categories of surface–3600-m cloud frequency have different patterns. Cloud frequency of FEW, SCT, and BKN peaks just after noon, whereas the frequency of OVC peaks in the early morning. However, the geographic distributions and seasonal and diurnal cycles of the four categories of the surface–3600-m cloud-base height are similar. The diurnal cycles of the cloud-base height within the surface–3600-m level present a minimum in the morning and peak in the late afternoon or early evening. Cloud frequency and cloud-base height within this range are closely related to surface air temperature and humidity conditions. From 2000 to 2015, the cloud frequency in the contiguous United States showed a positive trend of 0.28% yr−1 while the cloud-base height showed a negative trend of −4 m yr−1 for the surface–3600-m level, accompanied with a positive trend of precipitation days (0.14 days yr−1). Moreover, the increase of cloud frequency and the decrease of cloud-base height were most obvious in winter in the eastern half of the contiguous United States.
Abstract
Weekly average satellite-based estimates of latent heat flux (LHTFL) are used to characterize spatial patterns and temporal variability in the intraseasonal band (periods shorter than 3 months). As expected, the major portion of intraseasonal variability of LHTFL is due to winds, but spatial variability of humidity and SST are also important. The strongest intraseasonal variability of LHTFL is observed at the midlatitudes. It weakens toward the equator, reflecting weak variance of intraseasonal winds at low latitudes. It also decreases at high latitudes, reflecting the effect of decreased SST and the related decrease of time-mean humidity difference between heights z = 10 m and z = 0 m. Within the midlatitude belts the intraseasonal variability of LHTFL is locally stronger (up to 50 W m−2) in regions of major SST fronts (like the Gulf Stream and Agulhas). Here it is forced by passing storms and is locally amplified by unstable air over warm SSTs. Although weaker in amplitude (but still significant), intraseasonal variability of LHTFL is observed in the tropical Indian and Pacific Oceans due to wind and humidity perturbations produced by the Madden–Julian oscillations. In this tropical region intraseasonal LHTFL and incoming solar radiation vary out of phase so that evaporation increases just below the convective clusters.
Over much of the interior ocean where the surface heat flux dominates the ocean mixed layer heat budget, intraseasonal SST cools in response to anomalously strong upward intraseasonal LHTFL. This response varies geographically, in part because of geographic variations of mixed layer depth and the resulting variations in thermal inertia. In contrast, in the eastern tropical Pacific and Atlantic cold tongue regions intraseasonal SST and LHTFL are positively correlated. This surprising result occurs because in these equatorial upwelling areas SST is controlled by advection rather than by surface fluxes. Here LHTFL responds to rather than drives SST.
Abstract
Weekly average satellite-based estimates of latent heat flux (LHTFL) are used to characterize spatial patterns and temporal variability in the intraseasonal band (periods shorter than 3 months). As expected, the major portion of intraseasonal variability of LHTFL is due to winds, but spatial variability of humidity and SST are also important. The strongest intraseasonal variability of LHTFL is observed at the midlatitudes. It weakens toward the equator, reflecting weak variance of intraseasonal winds at low latitudes. It also decreases at high latitudes, reflecting the effect of decreased SST and the related decrease of time-mean humidity difference between heights z = 10 m and z = 0 m. Within the midlatitude belts the intraseasonal variability of LHTFL is locally stronger (up to 50 W m−2) in regions of major SST fronts (like the Gulf Stream and Agulhas). Here it is forced by passing storms and is locally amplified by unstable air over warm SSTs. Although weaker in amplitude (but still significant), intraseasonal variability of LHTFL is observed in the tropical Indian and Pacific Oceans due to wind and humidity perturbations produced by the Madden–Julian oscillations. In this tropical region intraseasonal LHTFL and incoming solar radiation vary out of phase so that evaporation increases just below the convective clusters.
Over much of the interior ocean where the surface heat flux dominates the ocean mixed layer heat budget, intraseasonal SST cools in response to anomalously strong upward intraseasonal LHTFL. This response varies geographically, in part because of geographic variations of mixed layer depth and the resulting variations in thermal inertia. In contrast, in the eastern tropical Pacific and Atlantic cold tongue regions intraseasonal SST and LHTFL are positively correlated. This surprising result occurs because in these equatorial upwelling areas SST is controlled by advection rather than by surface fluxes. Here LHTFL responds to rather than drives SST.
Abstract
A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST–NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April–September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST–NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST–NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water—not energy—is the primary factor limiting vegetation growth.
Abstract
A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST–NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April–September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST–NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST–NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water—not energy—is the primary factor limiting vegetation growth.
Abstract
The impacts of high-frequency surface forcing in the upper ocean over the equatorial Pacific are investigated using a nonlinear reduced-gravity isopycnal ocean circulation model forced by daily and monthly mean forcing. The simulated sea surface temperature (SST) in the daily forcing experiment is colder than that in the monthly forcing experiment near the equator. A mixed layer heat budget calculation shows that the net surface heat flux is primarily responsible for the SST difference in the western Pacific, while zonal advection accounts for the SST difference in the eastern Pacific where other budget terms are large but canceling each other. The daily forcing primarily enhances vertical mixing that reduces the vertical shear of the upper ocean. It also changes the net heat into the ocean through two contrasting processes: one is the increased surface latent heat loss induced by transient winds and the other is colder SST due to stronger mixing, which further reduces heat loss at the surface. As a result, the annual mean net surface heat flux into the ocean is reduced and the meridional thermal advection is weaker. The daily forcing also impacts the variation of the thermocline through a changing mixed layer depth so that the temperature in the simulation with the daily forcing is warmer around the thermocline.
Abstract
The impacts of high-frequency surface forcing in the upper ocean over the equatorial Pacific are investigated using a nonlinear reduced-gravity isopycnal ocean circulation model forced by daily and monthly mean forcing. The simulated sea surface temperature (SST) in the daily forcing experiment is colder than that in the monthly forcing experiment near the equator. A mixed layer heat budget calculation shows that the net surface heat flux is primarily responsible for the SST difference in the western Pacific, while zonal advection accounts for the SST difference in the eastern Pacific where other budget terms are large but canceling each other. The daily forcing primarily enhances vertical mixing that reduces the vertical shear of the upper ocean. It also changes the net heat into the ocean through two contrasting processes: one is the increased surface latent heat loss induced by transient winds and the other is colder SST due to stronger mixing, which further reduces heat loss at the surface. As a result, the annual mean net surface heat flux into the ocean is reduced and the meridional thermal advection is weaker. The daily forcing also impacts the variation of the thermocline through a changing mixed layer depth so that the temperature in the simulation with the daily forcing is warmer around the thermocline.
