Abstract

A simple radiative model designed to estimate insolation from geostationary satellite data has been applied to GOES-East calibrated visible data. Insolation results for 90 days are presented and compared with pyranometer measurements for three stations in southern Canada. The root-mean-square of the difference between satellite-estimated insolation and pyranometer measurements is within 8% of the mean measurements. The advantage of the satellite approach to obtaining insolation for regions where no measurements are available is also demonstrated and quantified.

Mean monthly and seasonal insolation maps have been obtained for southeastern Canada and northeastern United States using the method described, and maps for May, October and spring (April–June) 1978 are presented. They distinctively show the influence of Lake Ontario on the mean insolation and the effects of orography in northern New York State.

The “natural variability” of insolation, defined as the ratio of the standard deviation to the mean, has also been estimated. The results show that in general this variability of daily insolation is large for all the months studied. Its spatial variation decreases with averaging time (from month to season).

Abstract

We present the first results concerning solar radiation at the ocean surface during the Tropic Heat experiment. Using calibrated GOES visible brightness measurements, a simple radiative transfer model calculates hourly and daily surface solar irradiance values. To validate the satellite-estimated solar irradiance, surface solar irradiance measurements are taken from three sources; the Tropic Heat buoy 3, the R/V Weeama, and the small tropical Pacific island of Hiva Oa. The comparison with the limited set of ocean measurements demonstrates that the method's accuracy is about 12 W m⁻² on a daily (for the range of observed values: 240 to 310 W m⁻²), which meets the requirements of the TOGA program. These results, however, am not yet statistically significant. In comparing model estimates to island data, both satellite observations and measurements indicate that the island's topography influences the oceanic environment by causing local, daily arographic cloud formation over the island's highest mountain. In partly clear conditions these clouds have a twofold effect: 1) to reduce solar irradiance under the mountain by shadowing, and 2) to increase surface solar irradiance near the mountain (instrument location) by cloud side reflection. Because of these effects new-noon surface measurements are often larger than the model estimates (up to 80 W m⁻²). Comparisons between the model results and oceanic measurements (buoy and the R/V Wecoma) suggest that the satellite-based estimates represent the oceanic conditions better than the island measurements.

Abstract

In this paper we briefly describe the method applied to derive the net shortwave radiation (NSW) at the surface from combinations of calibrated visible geostationary satellite data. We then discuss the anticipated accuracy of the satellite estimations of NSW as a function of averaging time and space scales, as well as some intermediary results (surface albedo field).

The main purpose of the paper is, however, to describe and analyze the evolution of the NSW fields during the monsoon of 1979. We show that during the pre-onset phase (1 May–11 June), the characteristics of the NSW field are dominated by a strong maximum in the entire Arabian Sea (about 300 W m⁻²) and by a strong minimum in the central and eastern equatorial Indian Ocean (East of 80°E, in a band from 10°N to 10°S). This minimum is associated with the intense convective activity occurring in that region; very little activity exists in the western part of the Indian ocean.

As the season evolves, the minima of NSW associated with the large-scale convective activity occur more and more westward in the equatorial ocean, as is illustrated by a time sequence of NSW fields. Just a few days prior to the monsoon onset, several consecutive large-scale convective systems are present in the equatorial regions. These systems are then found more and more northwards. During the few days surrounding the onset (11 June–20 June), the entire field of NSW is drastically modified. The Arabian Sea maximum has retreated towards the Somalia coast, and most of the sea then experiences a strong minimum of NSW associated with the intense precipitation occurring along the southwestern coast of the Indian subcontinent.

Abstract

A pool of cool surface water was observed on 15 July 1974 during the GATE experiment, where down-drafts were present inside the cloud cluster. Downdrafts are assumed to destroy the buoyant moist plume convection that normally exists in the tropical mixed layer. The vertical fluxes of heat and moisture from the ocean are thus increased by the lowered equivalent potential temperatures and the increased winds which am produced by the downdrafts. These enhanced fluxes may induce a sea surface temperature cooling if they last for a few hours. The cooling due to the downdrafts is of a magnitude at least comparable to that produced by precipitation.

Abstract

Ocean surface shortwave irradiance estimates, From GOES satellite data computed using the model of Gautier and Frouin (1985), are compared to in situ measurements from research vessels and buoys during the frontal air-sea interaction experiment (FASINEX). They reveal that the satellite method overestimates percentage cloudiness during fractional cloud cover and large satellite viewing angles. An empirical relationship, based on physical constraints, is developed to correct for the overestimation of percentage cloud cover under these conditions. Subsequent comparisons of the corrected satellite estimates with in situ measurements show a root-mean-square difference of 10% of the daily mean values, with a mean difference between satellite and in situ data of 1–10 W m⁻².

From fields of corrected satellite estimates a cloudiness parameter, called the equivalent cloud amount, is used to examine the influences and feedbacks between the clouds and the sea surface temperatures (SST's). Correlations between cloud and SST fields show a high day-to-day variability attributed to the passage of several large-scale frontal cloud bands. The monthly mean correlation, however, shows large, positive values. This indicates that in the mean there are more clouds and/or clouds with higher liquid water content over the colder northern waters versus the warmer southern waters. Thus, the longer-term mean cloudiness field may act in a positive feedback sense, keeping the cold water from gaining as much heat as the already warmer water.

Abstract

The accurate estimate of the latent heat flux (LHF) is important to understand better the coupling between the atmosphere and the ocean and their respective circulation. In the near future, the availability of satellite-derived datasets over long periods will allow us to perform studies that, so far, have only been possible with historic in situ datasets. Therefore, a natural issue to explore is how the computation derived from both data types agree on LHF estimates, Comprehensive Ocean-Atmosphere Data Set (COADS) on one hand and satellite-derived parameters on the other hand are input to a similarity theory-based model and treated in completely equivalent ways to compute global latent heat flux. In order to compute latent heat flux exclusively from satellite measurements, an empirical relationship (Q−W relationship) is used to compute the air mixing ratio from Special Sensor Microwave/Imager precipitable water W and a new one is derived to compute the air temperature also from retrieved W (T−W relationship). First analyses indicate that in situ and satellite LHF computations compare within 40%, but systematic errors increase the differences up to 100% in some regions. By investigating more closely the origin of the discrepancies, the spatial sampling of ship reports has been found to be an important source of error in the observed differences. When the number of in situ data records increases (more than 20 per month), the agreement is about 50 W m⁻² rms (40 W m⁻² rms for multiyear averages). Limitations of both empirical relationships and W retrieval errors strongly affect the LHF computation. Systematic LHF overestimation occurs in strong subsidence regions and LHF underestimation occurs within surface convergence zones and over oceanic upwelling areas. The analysis of time series of the different parameters in these regions confirms that systematic LHF discrepancies are negatively correlated with the differences between COADS and satellite-derived values of the air mixing ratio and air temperature. To reduce the systematic differences in satellite-derived LHF, a preliminary ship-satellite blending procedure has been developed for the air mixing ratio and air temperature. The T−W relationship is not used any more and the air temperature is computed by adding the 3-yr-averaged COADS air-sea temperature difference to the satellite SST maps. The method to get the air mixing ratio is based on a weighted combination of COADS and satellite values according to the number of COADS observations available. After the blending proem is applied, large improvements are observed in the Northern Hemisphere where both datasets are complementary. At midlatitudes, the blending procedure does not modify LHF values since satellite and COADS air mixing ratio do not differ by more than the expected satellite uncertainty (1 g kg⁻¹). In the eastern and northern part of the basin, where the air mixing ratio difference is large and ship observations are numerous, blended LHF values are efficiently corrected toward in situ estimates compensating for the limitations of Q−W relationship. In the Southern Hemisphere, the number of in situ observations rarely exceeds four values per month, and without “ground truth,” more confidence is given to the satellite-derived values. Statistically, the rms difference drops to 28 W M⁻² when 20 ship observations are available, which is likely a good approximation of the lowest bound of the blended LHF uncertainty compared with optimal in situ estimates. However, along the eastern boundaries in the southern oceans, local differences are expected to be much larger.

Abstract

This study presents surface solar radiation flux and cloud radiative forcing results obtained by using a combination of satellite and surface observations interpreted by means of a simple plane-parallel radiative transfer model called 2001. This model, a revised version of a model initially introduced by Gautier et al., relates calibrated radiance observations from space to incoming surface solar flux. After a description of the model, an evaluation is presented by comparison with a more complex model that the authors have developed, the Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART) based on the discrete ordinate model of Stamnes et al. This evaluation demonstrates this model’s accuracy for instantaneous surface flux when used to retrieve daily (and monthly) surface solar flux. Limitations related to its lack of treatment of the bidirectional reflectance properties of clouds are also discussed and quantified by comparison with SBDART for instantaneous surface solar flux retrievals. The influence of satellite sensor calibration uncertainty is also examined in terms of surface solar flux.

The model has been applied to hourly GOES data collected over the Atmospheric Radiation Measurement (ARM) program’s central cloud and radiation testbed site in Oklahoma during a 14-month period to estimate hourly, daily, and monthly surface solar radiation flux. Comparisons of the model’s results with surface measurements made from pyranometers located at the ARM site indicate good overall agreement. The best results are obtained for daily integrated clear skies with an rms error less than 10 W m⁻² (or about 3% of the mean value) and a 2.8 W m⁻² bias. These results indicate that the clear sky model is quite accurate and also that the threshold-based technique to detect cloudy conditions works well for the resolution of the satellite data used in this study. For partly cloudy conditions the comparisons show an rms error of about 20 W m⁻² (or less than 7% of the mean) and a −2.5 W m⁻² bias. The performance of the model degrades with cloud cover conditions with an rms error of 22 W m⁻² (or 13% of the mean) and a bias of 13.9 W m⁻² for overcast conditions. The results improve considerably for monthly average values with an rms error of about 11 W m⁻² (or 4% of the mean) and a bias of 2.6 W m⁻² for all conditions.

The model has also been used to evaluate the cloud radiative forcing at the surface and results indicate large values of forcing for the spring and summer reaching daily values over 200 W m⁻² in May.

One of the issues facing educators of earth system science is how to teach the policy relevance of this discipline to students with mostly science backgrounds and interests. A “mini-Rio Summit” has been added to the earth system science curriculum at the University of California, Santa Barbara, to address this issue. Just as the Earth Summit held in Rio de Janeiro, Brazil, provided a forum for the nations of the world to voice and share their opinions on environmental protection and the move toward sustainable development, the mini-Rio Summit offered an avenue for students to express their concerns regarding global environmental change and to confront some of the intricacies of global decision making. By encouraging dialogue among students (nations) on topics of global change, the minisummit broadened students' awareness of particular political and socioeconomic considerations that individual countries must face when developing policy to deal with global change. Student reviews of the summit were enthusiastic and indicated that the summit was a successful method of bringing them more in touch with the complexities involved in dealing with the physical and human aspects of global change.

Abstract

This paper examines the evolution of the net surface solar irradiance from March 1982 to October 1985 in an important region of the equatorial Pacific where the TROPIC HEAT Experiment took place (4.6°N to 7.4°S, 142.6° to 117.17°W). The investigation, which focuses on the dramatic modification of radiative processes as a consequence of the 1982-83 El Niño episode, analyzes annual and monthly net surface solar irradiance fields computed from geostationary satellite observations. An annual mean for the year October 1984-September 1985, the year most distant from the El Niño event during the study, is computed and compared with existing climatologies. It is found that, while our values compare well with those of Weare et al., they are significantly higher than those of Esbensen and Kushnir and those of Chou. In the case of Esbensen and Kushnir, a climatology often used to force numerical ocean circulation models, the discrepancy reaches 40 W m⁻². Among the three annual fields computed, the two non-El Niño years are relatively similar, exhibiting features analogous to those found in all the climatologies. As expected, the El Niño year's annual mean field is remarkably different and is characterized by a complete disappearance of the zonal orientation and much smaller values along the equator, particularly in the western part of the studied region. The monthly mean fields confirm the El Niño's marked effect on net surface solar irradiance, especially during January, February, and March 1983, when the solar irradiance at the equator is reduced by more than 150 Wm⁻². An empirical orthogonal function analysis of the monthly fields containing the annual cycle quantifies the annual and interannual variations of the net surface solar irradiance and demonstrates that the two main forcing periods for the study area are both 12 months. The one explaining most of the variance (62%), however, exhibits two pronounced maxima at six-month intervals. This mode is much more perturbed during the El Niño than the other and confirms that the effects of the El Niño on solar irradiance are much stronger in the equatorial region than in higher latitudes; it further indicates that the solar irradiance deviations from the annual mean are more positive (less cloudiness) than during normal years al the end of the event. Although the study's results are limited to the area and the period examined, they are strongly indicative of the radiative processes occurring near the equator during a strong El Niño.

Abstract

A method is developed to estimate oceanic heat content (0–300 m) variations from sea level measurements in the tropical Pacific. To this end, statistical relationships between heat content and steric level, used as a surrogate variable for the sea level, are derived from climatological data. These relationships are then applied on independent datasets and the predictive ability of the method is determined regionally by comparing heat content estimated from XBT and sea level measurements recorded in three tropical Pacific islands (Christmas Fanning and Truk) during the 1979–85 period.

Good qualitative agreements are found between the two heat content estimates with correlations R = 0.78 to 0.94 and rms differences of average temperature of 0.25° to 0.50°C over an observed range of 6°C. Quantitative disagreements are observed in the central Pacific during the fall 1982 (El Niñc) period. These deficiencies in the method are found to be primarily due to intense and unusual salinity fluctuations at the surface which notably contribute to sea level variations. The difference between heat content variations deduced from sea level and calculated ones (from XBT) is significantly correlated (R = 0.54) with these sea surface salinity fluctuations.

For the investigated areas, the adopted method thus indicates that: 1) 2- and 3-month averaged sea level measurements can account for 61% to 88% of the 0–300 m heat content variations and, 2) special attention is required in its application when intense and unusual sea surface salinity anomalies occur.