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Abstract
For this study, a sampled dataset from the original METEOSAT images was taken over a seven-month period for areas with a variety of different surface types and geographical locations. This was the initial BI dataset requested for the International Satellite Cloud Climatology Project (ISCCP). Cloud amounts were derived from these raw radiances from a scheme which utilized all three METEOSAT channels. For the daylight slots the visible channel was used to discriminate between low cloud and surface. In addition, a “spatial coherence technique” was employed to detect cloud, relying on the assumption that the cloud tops do not have a uniform temperature over small distances (∼20 km). The monthly mean cloudiness and mean diurnal variability for three months (April, July and October 1983) computed from the radiance data are described here. Significant seasonal variations in cloudiness were observed, such as the latitudinal movement of the ITCZ and the enhancement of the southern subtropical jet during July. The diurnal cycle of cloudiness was observed over equatorial Africa, particularly for the high cloud coverage.
Abstract
For this study, a sampled dataset from the original METEOSAT images was taken over a seven-month period for areas with a variety of different surface types and geographical locations. This was the initial BI dataset requested for the International Satellite Cloud Climatology Project (ISCCP). Cloud amounts were derived from these raw radiances from a scheme which utilized all three METEOSAT channels. For the daylight slots the visible channel was used to discriminate between low cloud and surface. In addition, a “spatial coherence technique” was employed to detect cloud, relying on the assumption that the cloud tops do not have a uniform temperature over small distances (∼20 km). The monthly mean cloudiness and mean diurnal variability for three months (April, July and October 1983) computed from the radiance data are described here. Significant seasonal variations in cloudiness were observed, such as the latitudinal movement of the ITCZ and the enhancement of the southern subtropical jet during July. The diurnal cycle of cloudiness was observed over equatorial Africa, particularly for the high cloud coverage.
Abstract
During August–September 1995 new near-surface wind datasets over the tropical Atlantic from both the ERS-1 scatterometer and Meteosat satellites were available at the European Centre for Medium-Range Weather Forecasts. At this time there was an unusually high number of hurricanes present in the tropical Atlantic and so the impact of these data on analyzing and forecasting the main cyclones was investigated. Assimilation experiments using a new variational scheme, with the ERS-1 winds, showed clear improvements both in the analyses and short-range forecasts, compared with the optimal interpolation scheme without these data. For example, the forecast positions for Hurricane Iris were reduced by almost 50% when the scatterometer data was included. For Hurricane Luis the improvement was for a higher percentage of cases when the model identified the cyclone in the 24- and 48-h forecasts. For the 72-h forecasts 80% of the reported cyclones were detected compared with only 33% for the analyses without ERS-1 data.
The impact of the Meteosat lower-tropospheric cloud motion winds was found to be small due to lack of coverage in the vicinity of the center of the hurricanes at this time. The impact of one profile from a ship in the vicinity of Hurricane Luis just before its approach to the Caribbean Islands was clearly demonstrated by large improvements to both analyses with and without the scatterometer winds.
Abstract
During August–September 1995 new near-surface wind datasets over the tropical Atlantic from both the ERS-1 scatterometer and Meteosat satellites were available at the European Centre for Medium-Range Weather Forecasts. At this time there was an unusually high number of hurricanes present in the tropical Atlantic and so the impact of these data on analyzing and forecasting the main cyclones was investigated. Assimilation experiments using a new variational scheme, with the ERS-1 winds, showed clear improvements both in the analyses and short-range forecasts, compared with the optimal interpolation scheme without these data. For example, the forecast positions for Hurricane Iris were reduced by almost 50% when the scatterometer data was included. For Hurricane Luis the improvement was for a higher percentage of cases when the model identified the cyclone in the 24- and 48-h forecasts. For the 72-h forecasts 80% of the reported cyclones were detected compared with only 33% for the analyses without ERS-1 data.
The impact of the Meteosat lower-tropospheric cloud motion winds was found to be small due to lack of coverage in the vicinity of the center of the hurricanes at this time. The impact of one profile from a ship in the vicinity of Hurricane Luis just before its approach to the Caribbean Islands was clearly demonstrated by large improvements to both analyses with and without the scatterometer winds.
Abstract
The First ATSR Tropical Experiment was carded out in November 1991 over the tropical Atlantic to validate daytime measurements of sea surface temperature (SST) made by the Along Track Scanning Radiometer (ATSR) on the European remote sensing satellite, ERS-1. An airborne infrared radiometer with channels at 11 and 12 µm spectrally matched to those on the ATSR was used to make nadir, 60° to nadir, and zenith view radiance measurements at a number of different altitudes from 70 m to 8 km above the sea surface. The effect of stratospheric aerosols on the ATSR radiances, due to the June 1991 eruption of Mount Pinatubo, was quantified as nadir view brightness temperature deficits of up to 0.6 K at 11 µm. ATSR retrievals of SST (using both nadir and forward views) were compared with SSTs inferred from low-level radiance measurements of the sea surface that were unaffected by atmospheric absorption. ATSR SSTs retrieved using the nadir only views had negative (i.e., cold) biases of about 2 K. If the forward view was also included in the retrieval, the negative biases reduced to approximately 0.7 K. Radiance profiles through the atmosphere were also obtained for comparison with those computed by the Rutherford Appleton Laboratory radiative transfer model, which had been used to Venerate the ATSR SST retrieval coefficients. These showed that a positive (warm) bias of 1.5 K exists between the model and nadir view aircraft radiometer measurements at the 6-km altitude for these tropical atmospheres.
Abstract
The First ATSR Tropical Experiment was carded out in November 1991 over the tropical Atlantic to validate daytime measurements of sea surface temperature (SST) made by the Along Track Scanning Radiometer (ATSR) on the European remote sensing satellite, ERS-1. An airborne infrared radiometer with channels at 11 and 12 µm spectrally matched to those on the ATSR was used to make nadir, 60° to nadir, and zenith view radiance measurements at a number of different altitudes from 70 m to 8 km above the sea surface. The effect of stratospheric aerosols on the ATSR radiances, due to the June 1991 eruption of Mount Pinatubo, was quantified as nadir view brightness temperature deficits of up to 0.6 K at 11 µm. ATSR retrievals of SST (using both nadir and forward views) were compared with SSTs inferred from low-level radiance measurements of the sea surface that were unaffected by atmospheric absorption. ATSR SSTs retrieved using the nadir only views had negative (i.e., cold) biases of about 2 K. If the forward view was also included in the retrieval, the negative biases reduced to approximately 0.7 K. Radiance profiles through the atmosphere were also obtained for comparison with those computed by the Rutherford Appleton Laboratory radiative transfer model, which had been used to Venerate the ATSR SST retrieval coefficients. These showed that a positive (warm) bias of 1.5 K exists between the model and nadir view aircraft radiometer measurements at the 6-km altitude for these tropical atmospheres.
Abstract
Using collocations of three different observation types of sea surface temperatures (SSTs) gives enough information to enable the standard deviation of error on each observation type to be derived. SSTs derived from the Advanced Along-Track Scanning Radiometer (AATSR) and Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E) instruments are used, along with SST observations from buoys. Various assumptions are made within the error theory, including that the errors are not correlated, which should be the case for three independent data sources. An attempt is made to show that this assumption is valid and that the covariances between the different observations because of representativity error are negligible. Overall, the spatially averaged nighttime AATSR dual-view three-channel bulk SST observations for 2003 are shown to have a very small standard deviation of error of 0.16 K, whereas the buoy SSTs have an error of 0.23 K and the AMSR-E SST observations have an error of 0.42 K.
Abstract
Using collocations of three different observation types of sea surface temperatures (SSTs) gives enough information to enable the standard deviation of error on each observation type to be derived. SSTs derived from the Advanced Along-Track Scanning Radiometer (AATSR) and Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E) instruments are used, along with SST observations from buoys. Various assumptions are made within the error theory, including that the errors are not correlated, which should be the case for three independent data sources. An attempt is made to show that this assumption is valid and that the covariances between the different observations because of representativity error are negligible. Overall, the spatially averaged nighttime AATSR dual-view three-channel bulk SST observations for 2003 are shown to have a very small standard deviation of error of 0.16 K, whereas the buoy SSTs have an error of 0.23 K and the AMSR-E SST observations have an error of 0.42 K.
TIROS–N Advanced Very High Resolution Radiometer (AVHRR) imagery has been used to study the temperature structure of the sea surface around the British Isles. We have combined the satellite imagery from both TIROS–N, METEOSAT, and conventional synoptic data to obtain a calibration for both 11 μm infrared channels, which gave sea surface temperatures accurate to ± 1 K. The changes in the sea surface temperature around the British Isles for 12 July 1979 are shown well by the satellite data. In particular, we have made a study of an anomalously warm patch in the North Sea that appeared at local noon over an area where the surface winds were weak, inhibiting surface mixing.
TIROS–N Advanced Very High Resolution Radiometer (AVHRR) imagery has been used to study the temperature structure of the sea surface around the British Isles. We have combined the satellite imagery from both TIROS–N, METEOSAT, and conventional synoptic data to obtain a calibration for both 11 μm infrared channels, which gave sea surface temperatures accurate to ± 1 K. The changes in the sea surface temperature around the British Isles for 12 July 1979 are shown well by the satellite data. In particular, we have made a study of an anomalously warm patch in the North Sea that appeared at local noon over an area where the surface winds were weak, inhibiting surface mixing.
Abstract
During the 1989 intensive field campaign of the International Cirrus Experiment (ICE) over the North Sea, broadband radiative fluxes were measured in, above, and below cirrus cloud by a number of European meteorological research aircraft. One mission during the campaign was an intercomparison flight in clear air with no cloud above in order to compare, among other things, radiative flux measurements made by the U.K. C-130, the French Merlin, and the German Falcon aircraft. All three aircraft measured shortwave flux (0.3–3 µm) with standard Eppley pyranometers above and below the fuselage. The intercomparison showed agreement between the three aircraft of within 2% for both the upwelling and downwelling shortwave flux components. Using a coincident temperature and humidity radiosonde profile, the downward clear-sky fluxes at the level of the aircraft were also calculated using a variety of different radiation models. Modeled shortwave fluxes were all higher (between 2% and 4%) than the measured values. In addition to shortwave fluxes the C-130 and Merlin also measured near-infrared fluxes (0.7–3 µm) by having additional Eppley pyranometers mounted with red domes over the thermopiles. The near-infrared fluxes measured by the Merlin and C-130 were different because slightly different red-dome filters were used; model calculations show the difference between the measured fluxes was consistent with the different pass band of the filters. Infrared fluxes (4–40 µm) were measured using standard Eppley pyrgeometers on the Falcon and pyrgeometers developed at the Meteorological Research Flight on the C-130; comparisons show no significant differences for the downwelling fluxes but the Falcon upwelling fluxes were 7% higher than the corresponding C-130 values. This latter difference is higher than would be expected for these instruments. The modeled infrared fluxes were up to 9% lower than the C-130 and Falcon measurements.
Abstract
During the 1989 intensive field campaign of the International Cirrus Experiment (ICE) over the North Sea, broadband radiative fluxes were measured in, above, and below cirrus cloud by a number of European meteorological research aircraft. One mission during the campaign was an intercomparison flight in clear air with no cloud above in order to compare, among other things, radiative flux measurements made by the U.K. C-130, the French Merlin, and the German Falcon aircraft. All three aircraft measured shortwave flux (0.3–3 µm) with standard Eppley pyranometers above and below the fuselage. The intercomparison showed agreement between the three aircraft of within 2% for both the upwelling and downwelling shortwave flux components. Using a coincident temperature and humidity radiosonde profile, the downward clear-sky fluxes at the level of the aircraft were also calculated using a variety of different radiation models. Modeled shortwave fluxes were all higher (between 2% and 4%) than the measured values. In addition to shortwave fluxes the C-130 and Merlin also measured near-infrared fluxes (0.7–3 µm) by having additional Eppley pyranometers mounted with red domes over the thermopiles. The near-infrared fluxes measured by the Merlin and C-130 were different because slightly different red-dome filters were used; model calculations show the difference between the measured fluxes was consistent with the different pass band of the filters. Infrared fluxes (4–40 µm) were measured using standard Eppley pyrgeometers on the Falcon and pyrgeometers developed at the Meteorological Research Flight on the C-130; comparisons show no significant differences for the downwelling fluxes but the Falcon upwelling fluxes were 7% higher than the corresponding C-130 values. This latter difference is higher than would be expected for these instruments. The modeled infrared fluxes were up to 9% lower than the C-130 and Falcon measurements.
Abstract
Daily averaged and instantaneous values or the Earth's radiation budget have been computed from the satellite measurements of reflected solar and emitted terrestrial radiation with MEUGSAT 1, Nimbus 7 ERB and TIROS-N scanning radiometers. The estimates have been compared for 12 selected 2.5° × 2.5° latitude-longitude moons for 14 October 1979. The METEOSAT daily mean values were used to study the effects of diurnal variations because observations were available nearly every hour of the day. The comparisons between the three independent data sets is discussed and an assessment is made of the relative importance of diurnal variations and anisotropic scattering models. A cheek was made on the inferred broad-band MEUOSAT fluxes by a direct comparison with coincident Nimbus 7 ERB measurements.
Abstract
Daily averaged and instantaneous values or the Earth's radiation budget have been computed from the satellite measurements of reflected solar and emitted terrestrial radiation with MEUGSAT 1, Nimbus 7 ERB and TIROS-N scanning radiometers. The estimates have been compared for 12 selected 2.5° × 2.5° latitude-longitude moons for 14 October 1979. The METEOSAT daily mean values were used to study the effects of diurnal variations because observations were available nearly every hour of the day. The comparisons between the three independent data sets is discussed and an assessment is made of the relative importance of diurnal variations and anisotropic scattering models. A cheek was made on the inferred broad-band MEUOSAT fluxes by a direct comparison with coincident Nimbus 7 ERB measurements.
Abstract
The Advanced Along Track Scanning Radiometer (AATSR) Sea Surface Temperature (SST) Meteo product, a fast-delivery level-2 product at 10 arc min spatial resolution, has been available from the European Space Agency (ESA) since 19 August 2002. Validation has been performed on these data at the Met Office on a daily basis, with a 2-day lag from data receipt. Meteo product skin SSTs have been compared with point measurements of buoy SST, a 1° climate SST analysis field compiled from in situ measurements and Advanced Very High Resolution Radiometer (AVHRR) SSTs, and a 5° latitude–longitude 5-day averaged in situ dataset. Comparisons of the AATSR Meteo product against Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SSTs are also presented. These validation results have confirmed the AATSR Meteo product skin SST to be within ±0.3 K of in situ data.
Comparisons of the AATSR skin SSTs against buoy SSTs, from 19 August 2002 to 20 August 2003, give a mean difference (AATSR – buoy) of 0.04 K (standard deviation = 0.28 K) during nighttime, and a mean difference of 0.02 K (standard deviation = 0.39 K) during the day. Analyses of the buoy matchups have shown that there is no cool skin effect observed in the nighttime observations, implying that the three-channel AATSR product skin SST may be 0.1–0.2 K too warm. Comparisons with TMI SSTs confirm that the lower-latitude SSTs are not significantly affected by residual cloud contamination.
Abstract
The Advanced Along Track Scanning Radiometer (AATSR) Sea Surface Temperature (SST) Meteo product, a fast-delivery level-2 product at 10 arc min spatial resolution, has been available from the European Space Agency (ESA) since 19 August 2002. Validation has been performed on these data at the Met Office on a daily basis, with a 2-day lag from data receipt. Meteo product skin SSTs have been compared with point measurements of buoy SST, a 1° climate SST analysis field compiled from in situ measurements and Advanced Very High Resolution Radiometer (AVHRR) SSTs, and a 5° latitude–longitude 5-day averaged in situ dataset. Comparisons of the AATSR Meteo product against Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SSTs are also presented. These validation results have confirmed the AATSR Meteo product skin SST to be within ±0.3 K of in situ data.
Comparisons of the AATSR skin SSTs against buoy SSTs, from 19 August 2002 to 20 August 2003, give a mean difference (AATSR – buoy) of 0.04 K (standard deviation = 0.28 K) during nighttime, and a mean difference of 0.02 K (standard deviation = 0.39 K) during the day. Analyses of the buoy matchups have shown that there is no cool skin effect observed in the nighttime observations, implying that the three-channel AATSR product skin SST may be 0.1–0.2 K too warm. Comparisons with TMI SSTs confirm that the lower-latitude SSTs are not significantly affected by residual cloud contamination.
Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties.
There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together.
This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.
Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties.
There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together.
This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.
