The CrIMSS EDR Algorithm: Characterization, Optimization, and Validation

Abstract

The Cross‐track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments aboard the Suomi National Polar‐orbiting Partnership satellite provide high‐quality hyperspectral infrared and microwave observations to retrieve atmospheric vertical temperature and moisture profiles (AVTP and AVMP) and many other environmental data records (EDRs). The official CrIS and ATMS EDR algorithm, together called the Cross‐track Infrared and Microwave Sounding Suite (CrIMSS), produces EDR products on an operational basis through the interface data processing segment. The CrIMSS algorithm group is to assess and ensure that operational EDRs meet beta and provisional maturity requirements and are ready for stages 1–3 validations. This paper presents a summary of algorithm optimization efforts, as well as characterization and validation of the AVTP and AVMP products using the European Centre for Medium‐Range Weather Forecasts (ECMWF) analysis, the Atmospheric Infrared Sounder (AIRS) retrievals, and conventional and dedicated radiosonde observations. The global root‐mean‐square (RMS) differences between the CrIMSS products and the ECMWF show that the AVTP is meeting the requirements for layers 30–300 hPa (1.53 K versus 1.5 K) and 300–700 hPa (1.28 K versus 1.5 K). Slightly higher RMS difference for the 700 hPa‐surface layer (1.78 K versus 1.6 K) is attributable to land and polar profiles. The AVMP product is within the requirements for 300–600 hPa (26.8% versus 35%) and is close in meeting the requirements for 600 hPa‐surface (25.3% versus 20%). After just one year of maturity, the CrIMSS EDR products are quite comparable to the AIRS heritage algorithm products and show readiness for stages 1–3 validations.

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

“…AIRS, IASI and CrIS retrievals are described in, for example, Susskind et al (2011), August et al (2014), and Gambacorta et al (2012). Examples of evaluation results for water vapour products from ATOVS and hyperspectral instruments can be found in, for example, Bedka et al (2010), Reale et al (2012) and Divakarla et al (2014).…”

Application of GPS radio occultation to the assessment of temperature profile retrievals from microwave and infrared sounders

“…The NASA AIRS and NOAA IASI products are already defined to be on these levels, so the CrIMSS and GPS RO products are the only profiles that need to be interpolated. After the differences of the sounder minus GPS RO profiles are computed, they are degraded to approximate 1 km layer averages, as is done to the sounder minus reference differences in Susskind et al (2003), Tobin et al (2006), and Divakarla et al (2006Divakarla et al ( , 2014. Next, bias and root-mean-square (rms) profile statistics are calculated for various time and spatial scales.…”

“…Specifically, the 42 temperature layer Atmospheric Vertical Temperature Profile product is used (JPSS Configuration Management Office, 2012). CrIMSS data for the example time period May 2012 that are used in this study are version Mx5.3 and are from the time when the product was still in provisional status prior to major subsequent upgrades (Divakarla et al, 2014). Evaluation of the NOAA products derived from the Crosstrack Infrared Sounder (CrIS)/Advanced Technology Microwave Sounder (ATMS) on the Suomi NPP satellite is ongoing and GPS RO is being used in the product calibration/validation (Nalli et al, 2013).…”

“…Quality control is applied using the overall retrieval quality flag -non-converged retrievals are not included in the analysis. Details of the CrIMSS product algorithm can be found in Divakarla et al (2014).…”

“…Due to the wide range of accuracies among radiosonde systems, it is challenging to use the existing WMO operational radiosonde network as a common reference (Seidel et al, 2009). In current practice, it is popular to use numerical weather prediction (NWP) forecast models that assimilate WMO radiosondes twice a day as a primary way to validate sounder satellite products, because even a single model time step can provide thousands of global matchup cases with the satellite products (Fetzer et al, 2003;Divakarla et al, 2014). However, there is a potential for circular calibration traceability paths for operational satellite product data sets when using this method due to the fact that cloudfree radiances are assimilated into NWP models, while at the same time satellite retrieval algorithms are tuned to agree with global mean NWP forecast assimilation data (McNally et al, 2006;Susskind et al, 2006).…”