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Depending on the data record producer, different product requirements may be applied and they are used to evaluate validation results. An often-used way to handle this is to define several levels of requirements where each level is linked to specific needs or priorities. A three-level approach like the following is rather common:
Requirement | Description |
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Threshold requirement | A product should at least fulfill this level to be considered useful at all. Sometimes the term ‘Breakthrough” is used instead. |
Target requirement | This is the main quality goal for a product. It should reach this level based on the current knowledge on what is reasonable to achieve. |
Optimal requirement | This is a level where a product is considered to perform much better than expected given the current knowledge. |
Satellite product levels
Satellite-based products are often described as belonging to the following condensed description of processing levels, each one with different complexity and information content:
Level | Description |
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Level-0 | Raw data coming directly from satellite sensors, often described as sensor counts. |
Level-1 | Data being enhanced with information on calibration and geolocation. Three sub-levels are often referred to: Level-1a: Data with attached calibration and geolocation information Level-1b: Data with applied calibration and attached geolocation information Level-1c: Data with applied calibration and additional layers of geolocation, satellite viewing and solar angle information |
Level-2 | Derived geophysical variables at the same resolution and location as L1 source data. An often-used Level-2 variety is the following: Level-2b: Globally resampled images, two per day per satellite, describing both ascending (passing equator from south) and descending (passing equator from north) nodes. Resampling is based on the principle that the value for the pixel with the lowest satellite zenith angle is chosen in case two or several swaths are overlapping. |
Level-3 | Gridded data with results accumulated over time (e.g., monthly means). |
A more comprehensive definition of all processing levels is given here: https://www.earthdata.nasa.gov/engage/open-data-services-and-software/data-information-policy/data-levels.
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Key Performance Indices (KPIs) for ICDR products to be produced for the extension of the TCDR (so far covering the period January 2019 until June 2022) have been defined using MODIS Level 3 products as reference observations. The KPI test is based on a binomial test against low (2.5%) and high (97.5%) percentiles of the MODIS-CLARA difference distribution. The low and high percentiles are given in the following table:
Variable | KPI: lower percentile (2.5 %) | KPI: higher percentile (97.5 %) |
CFC | -0.718 % | 0.576 % |
CTP | -7.036 hPa | 4.353 hPa |
LWP | -0.0021 g/m² | 0.0022 g/m2 |
IWP | -0.0031 g/m² | 0.0021 g/m² |
An extensive description of past, current and future availability of data from the Advanced Very High Resolution Radiometer (AVHRR) is given. In addition, future prospects of utilizing AVHRR-heritage spectral channel data from new imaging sensors on new satellites are described. It is concluded that the AVHRR-based observations series, based on one morning and one afternoon orbit constellation, can be prolonged to reach at least 60 years if adding AVHRR-heritage information. However, for this to become effective, efforts are needed to harmonize and homogenize observations between true AVHRR data and AVHRR-heritage data. This concerns both calibration aspects and spatial resolution aspects. Regarding the development of retrieval methods, it is noted that the access to high quality cloud observations from active sensors (especially CALIPSO-CALIOP data) has played an important role in advancing both retrieval methods and methods for uncertainty estimations in recent years. The access to the high-quality reference data has been especially important for the development of Bayesian and artificial neural network (ANN) based retrievals. A future continuation of active observations from space is judged as crucial for further development of retrieval methods based on AVHRR-heritage data.
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Table 2‑2: Key Performance Indicators (KPIs) or target requirements (i.e., fulfilled requirements for CLARA-A2.1 in the CM SAF project) for the cloud products CFC, CTP, LWP and IWP (monthly means) of interest for C3S_312b_Lot1. More details are given in reference D5 (Table 1.1 to Table 1.3). Anchor table2_2 table2_2
Variable | KPI: accuracy (Bias) Fulfilled by CLARA-A2.1 CDR | KPI: decadal stability Fulfilled by CLARA-A2.1 CDR |
CFC | 5 % | 2 % /decade |
CTP | 50 hPa | 20 hPa/decade |
LWP | 10 g/m² | 3 g/m² decade |
IWP | 20 g/m² | 6 g/m² decade |
For the evaluation of the ICDR, corresponding products from the MODIS instrument (MODIS Collection 6.1) are used as a reference. The distribution of the de-seasonalised differences between MODIS products and the CLARA.A2.1 TCDR has been compiled and the corresponding 2.5 and 97.5 percentile differences are given in Table 2-3.
Table 2‑3: KPI percentiles (2.5 % and 97.5 %) requirements for the CLARA-A2.1 CFC, CTP, LWP and IWP product differences against MODIS C6.1. Anchor table2_3 table2_3
Variable | KPI: lower percentile (2.5 %) | KPI: higher percentile (97.5 %) |
CFC | -0.718 % | 0.576 % |
CTP | -7.036 hPa | 4.353 hPa |
LWP | -0.0021 g/m² | 0.0022 g/m2 |
IWP | -0.0031 g/m² | 0.0021 g/m² |
These percentiles are used to check, by means of a binomial test at 5 % significance level, whether the corresponding ICDR differences are consistent with the TCDR differences or not. Further details on these tests are found in the Report on Updated KPIs (D10).
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Table 2‑4: GCOS-154 requirements for CFC, CTP, LWP and IWP compared to CLARA-A2.1 requirements. Anchor table2_4 table2_4
Requirements | GCOS (Target) | CLARA-A2.1 TCDR + ICDR v2.x |
Spatial resolution | 50 km | 25 km |
Temporal resolution | 3-hourly | Monthly |
Accuracy: CFC CTP LWP IWP | 1-5 % 15-50 hPa 25 % 25 % | 5 % 50 hPa 10 gm-2 20 g m-2 |
Stability: CFC CTP LWP IWP | 0.3-3 %/decade 3-15 hPa/decade 5 %/decade 5 %/decade | 2 %/decade 20 hPa/decade 3 g/m2/decade 6 g/m2/decade |
2.1.6 Data format and content issues
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Table 2‑5: Key Performance Indicators (KPIs) for the CFC, CTP, CTT, COT, CER, LWP and IWP products (monthly means) of Cloud_cci v3.0 of interest for C3S_312b_Lot1. Anchor table2_5 table2_5
Variable | KPI: accuracy (Bias) Fulfilled by Cloud_cci TCDR | KPI: decadal stability Fulfilled by Cloud_cci TCDR | ||||
CFC | 8.09 % | -0.35 % /decade | ||||
CTP | -25.52 hPa | 3.99 hPa/decade | ||||
CTT | No individual requirement. Compliance of CTP, LWP and IWP considered. | |||||
COT | 2.4 (liquid), 0.58 (ice) | 0.01 (liquid), -0.02 (ice) /decade | ||||
CER | -1.8(liquid), -12.5 (ice)
| -0.09 (liquid),-0.12 (ice)
/decade | ||||
LWP | -17.29 g/m² | 0.99 g/m² decade | ||||
IWP | -28.77 g/m² | -2.27 g/m² decade |
In order to monitor the performance of the SLSTR extension ICDR, new KPI values were also generated from comparisons of the Cloud Properties TCDR ESA AATSR to the NASA MODIS Cloud Properties product. These comparisons are represented as the 2.5 and 97.5 percentiles of the distribution of differences between (A)ATSR monthly-mean values and the corresponding MODIS values (corrected for the mean seasonal cycle), and are summarised in Table 2-6.
Table 2-6 :KPIs to be applied to corresponding SLSTR ICDR products in Table 2-4, based on comparison of the Cloud_cci v3.0 TCDR against MODIS Collection 6.1. Anchor table2_6 table2_6
Variable | KPI: 2.5thpercentile | KPI: 97.5th percentile |
CFC | -1.3 % | 3.1 % |
CTP | -7.9 hPa | 6.9 hPa/decade |
CTT | No individual requirement. Compliance of CTP, LWP and IWP considered. | |
COT | ||
CER | ||
LWP | -4.65 g/m² | 4.48 g/m² decade |
IWP | -16.4 g/m² | 11.3 g/m² decade |
2.2.2 Data format and content issues
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Table 3‑1:Spectral channels of the Advanced Very High Resolution Radiometer (AVHRR). The three different versions of the instrument are described as well as their corresponding satellites. Notice that channel 3A was only used continuously on NOAA-17 and on the Metop satellites. For the other satellites with AVHRR/3 it was used only for shorter periods. (Table taken from reference document D4 but extended with information on satellites Tiros-N and Metop-C). Anchor table3_1 table3_1
Channel | Wavelength | Wavelength | Wavelength |
1 | 0.58-0.68 | 0.58-0.68 | 0.58-0.68 |
2 | 0.725-1.10 | 0.725-1.10 | 0.725-1.10 |
3A | - | - | 1.58-1.64 |
3B | 3.55-3.93 | 3.55-3.93 | 3.55-3.93 |
4 | 10.50-11.50 | 10.50-11.50 | 10.50-11.50 |
5 | Channel 4 repeated | 11.50-12.50 | 11.50-12.50 |
Table 3‑2: Channel 3A and 3B activity for the AVHRR/3 instruments during daytime. Notice that the given time periods show the availability in the CLARA TCDR v2.0 and not the true lifetime of the individual sensor/satellite. The table is taken from reference document D4 (slightly modified with respect to end of data record). Anchor table3_2 table3_2
Satellite | Channel 3A active | Channel 3B active |
NOAA-15 | 06/1998 – 12/2015 | |
NOAA-16 | 10/2000 – 04/2003 | 05/2003 – 12/2011 |
NOAA-17 | 07/2002 – 02/2010 | |
NOAA-18 | 09/2005 – 12/2018 | |
NOAA-19 | 03/2009 – 05/2009 | 06/2009 – 12/2018 |
Metop-A | 09/2007 – 12/2018 | |
Metop-B | 01/2013 – 12&2015 |
In the following text we will refer to some figures prepared for the description of the complete CLARA-A2.1 data record from the CM SAF project (described in D4). It is identical to the TCDR AVHRR CLARA v2.0 except that it also includes data for the first six months of 2019.
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Table 3‑5: Next generation polar orbiting meteorological satellites in low earth orbit (LEO) for the US/European Joint Polar Satellite System. Satellites are listed in chronological order based on true and planned launch dates. All information is taken from the WMO OSCAR site (https://www.wmo-sat.info/oscar/satellites/) in April 2022. Anchor table3_5 table3_5
Satellite | Provider | Start | Expected end of life | Orbit | Imaging sensor |
NOAA-20 | NOAA | 2017 | 2024 | 1:30 pm | VIIRS |
JPSS-2 | NOAA | 2022 | 2029 | 1:30 pm | VIIRS |
Metop-SG-A1 | EUMETSAT | 2024 | 2031 | 9:30 am | MetImage |
JPSS-3 | NOAA | 2027 | 2034 | 1:30 pm | VIIRS |
Metop-SG-A2 | EUMETSAT | 2031 | 2038 | 9:30 am | MetImage |
JPSS-4 | NOAA | 2032 | 2039 | 1:30 pm | VIIRS |
Metop-SG-A3 | EUMETSAT | 2038 | 2045 | 9:30 am | MetImage |
Table 3-5 shows that AVHRR-heritage information from one morning and one afternoon orbit will be provided for at least 20 more years from present time (i.e., nominally until 2045. Consequently, it means that CLARA-type CDRs will be possible to compile over a time period exceeding 60 years from the initial launch year of 1978 for the first AVHRR instrument.
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C3S products from Cloud_cci data and the SLSTR ICDR follow the methodology described by Stengel et al. (2018), with four separate uncertainty parameters being included for each mean parameter, x:
Uncertainty parameter | Formula | Description | ||||||
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| where N is the number of L2 pixels included in the L3 average,
is the uncertainty on an individual L2 value and c is the correlation between the L2 pixels. The reader is referred to Stengel et al. (2018) | ||||||
2. The mean uncertainty of the parameter,
, which is simply the mean of the uncertainty values of the data included in the L3 mean: |
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3. The propagated uncertainty (assuming independent measurements),
, which is calculated from the mean of the squared uncertainties of the uncertainty values of the data included in the L3 mean: |
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4. Correlated uncertainty (including correlation between the L2 pixels within the L3 average),
, which is given by the expression: |
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