MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System

Boukabara, Sid; Garrett, Kevin; Chen, Wanchun; Iturbide-Sanchez, Flavio; Grassotti, Christopher; Kongoli, Cezar; Chen, Ruiyue; Liu, Quanhua; Yan, Banghua; Weng, Fuzhong; Ferraro, Ralph; Kleespies, Thomas J.; Meng, Huan

doi:10.1109/tgrs.2011.2158438

Cited by 205 publications

(146 citation statements)

References 20 publications

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“…The use of microwave data provides an advantage over infrared soundings that need a cloud-free view to sense low-level moisture. Two types of moisture profile retrievals are blended: the NOAA Microwave Integrated Retrieval System (MIRS; Boukabara et al 2011) soundings and AIRS soundings (Dang et al 2012;Olsen 2013). AIRS is used in mostly cloud-free regions and over snow-covered surfaces where MIRS retrievals are not used because of complex surface emissivity.…”

Section: Satellite Moisture Profile Datamentioning

confidence: 99%

“…CIRA also ingests the MIRS sounding product (Boukabara et al 2011), Version 8.0, in near real-time from the NOAA Data Distribution Server (DDS) system for inclusion in the blended LWV products. Currently, MIRS sounding retrievals are available from the NOAA-18, NOAA-19, Metop-A, Metop-B, and DMSP F-18 satellites.…”

Section: B Microwave Integrated Retrieval System (Mirs)mentioning

confidence: 99%

“…The MIRS soundings from DMSP are produced at the resolution of the upper atmospheric sounding channels, which is approximately 75 km. Boukabara et al (2011) give details on the MIRS resolution and footprint matching. Currently, MIRS is being used to perform retrievals at a spatial resolution of 16 km at nadir from the Suomi-NPP and Metop-B satellites.…”

Section: B Microwave Integrated Retrieval System (Mirs)mentioning

confidence: 99%

“…Although an arbitrary number of levels can be selected to be retrieved, only a few pieces of independent information are available from the five channels on MHS. The MIRS system outputs 100 levels of temperature and moisture, but only four independent basis functions are used for moisture (Boukabara et al 2011), so that is the maximum number of independent levels of water vapor. The AIRS retrieval reports a degree-of-freedom field representing the amount of independent information, and it is typically between four and six.…”

Section: Accuracy and Vertical Resolution Of Airs And Mirs Productsmentioning

confidence: 99%

See 3 more Smart Citations

A multisensor, blended, layered water vapor product for weather analysis and forecasting

Forsythe¹,

Kidder²,

Fuell³

et al. 2015

J. Operational Meteor.

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Section: Satellite Moisture Profile Datamentioning

confidence: 99%

Section: B Microwave Integrated Retrieval System (Mirs)mentioning

confidence: 99%

Section: B Microwave Integrated Retrieval System (Mirs)mentioning

confidence: 99%

Section: Accuracy and Vertical Resolution Of Airs And Mirs Productsmentioning

confidence: 99%

See 2 more Smart Citations

A multisensor, blended, layered water vapor product for weather analysis and forecasting

Forsythe¹,

Kidder²,

Fuell³

et al. 2015

J. Operational Meteor.

View full text Add to dashboard Cite

“…Figure 4 is an example of ATMS derived atmospheric temperature and water vapor at 500 hPa. These products are generated from the Microwave Integrated Retrieval System (MiRS) [Boukabara et al, 2011].…”

Section: Atms and Crismentioning

confidence: 99%

Joint Polar Satellite System: The United States next generation civilian polar‐orbiting environmental satellite system

Goldberg¹,

Kilcoyne²,

Cikanek³

et al. 2013

JGR Atmospheres

184

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NOAA's next generation polar‐orbiting environmental satellite system, designated as the Joint Polar Satellite System (JPSS), was proposed in February 2010, as part of the President's Fiscal Year 2011 budget request, to be the Civilian successor to the restructured National Polar‐Orbiting Operational Environmental Satellite System (NPOESS). Beginning 1 October 2013, the JPSS baseline consists of a suite of five instruments: advanced microwave and infrared sounders critical for short‐ and medium‐range weather forecasting; an advanced visible and infrared imager needed for environmental assessments such as snow/ice cover, droughts, volcanic ash, forest fires and surface temperature; ozone sensor primarily used for global monitoring of ozone and input to weather and climate models; and an Earth radiation budget sensor for monitoring the Earth's energy budget. NASA will fund the Earth radiation budget sensor and the ozone limb sensor for the second JPSS operational satellite—JPSS‐2. JPSS is implemented through a partnership between NOAA and the U.S. National Aeronautics and Space Administration (NASA). NOAA is responsible for overall funding; maintaining the high‐level requirements; establishing international and interagency partnerships; developing the science and algorithms, and user engagement; NOAA also provides product data distribution and archiving of JPSS data. NASA's role is to serve as acquisition Center of Excellence, providing acquisition of instruments, spacecraft and the multimission ground system, and early mission implementation through turnover to NOAA for operations.

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The CrIMSS EDR Algorithm: Characterization, Optimization, and Validation

et al. 2014

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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.

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MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System

Cited by 205 publications

References 20 publications

A multisensor, blended, layered water vapor product for weather analysis and forecasting

A multisensor, blended, layered water vapor product for weather analysis and forecasting

Joint Polar Satellite System: The United States next generation civilian polar‐orbiting environmental satellite system

The CrIMSS EDR Algorithm: Characterization, Optimization, and Validation

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