Mark Leidner - Academia.edu (original) (raw)

Papers by Mark Leidner

Quarterly Journal of the Royal Meteorological Society, Apr 1, 2021

Direct remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, o... more Direct remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, or radio occultation bending angle) are often more effective for use in data assimilation (DA) than the corresponding geophysical retrievals (e.g., ocean surface winds, soil moisture, or atmospheric water vapor). In the particular case of Global Navigation Satellite System Reflectometry (GNSS‐R), the lower‐level delay‐Doppler map (DDM) observable shows a complicated relationship with the ocean surface wind field. Prior studies have demonstrated DA using GNSS‐R wind retrievals inferred from DDMs. The complexity of the DDM dependence on winds, however, suggests that the alternative approach of ingesting DDM observables directly into DA systems, without performing a wind retrieval, may be beneficial. We demonstrate assimilation of DDM observables from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission into global ocean surface wind analyses using a two‐dimensional variational analysis method. Bias correction and quality‐control methods are described. Several models for the required observation‐error covariance matrix are developed and evaluated, with the conclusion that a diagonal matrix performs as well as a fully populated matrix empirically tuned to a large ensemble of CYGNSS observation data. The 10‐m surface winds from the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational forecast are used as the background (i.e., prior in the variational analysis). Results are compared with independent scatterometer (the advanced scatterometer (ASCAT), the oceansat‐2 Scatterometer (OSCAT)) winds. For one month (June 2017) of data, the root‐mean‐square difference (RMSD) was reduced from 1.17 to 1.07 m·s−1 and bias from −0.14 to −0.08 m·s−1 for the wind speed at the specular point. Within a 150‐km wide swath along the specular point track, the RMSD was reduced from 1.20 to 1.13 m·s−1. These RMSD and bias statistics are smaller than other CYGNSS wind products available at this time.

Journal of Applied Meteorology, Mar 1, 2000

This paper describes a new methodology developed to provide objective guidance for cost-effective... more This paper describes a new methodology developed to provide objective guidance for cost-effective siting of meteorological observations on the mesoscale for air quality applications. This field-coherence technique (FCT) is based on a statistical analysis of the mesoscale atmospheric structure defined by the spatial and temporal ''coherence'' in the meteorological fields. The coherence, as defined here, is a measure of the distance scale over which there is temporal consistency in the spatial structure within a variable field. It indicates how well a measurement taken at one location can be used to estimate the value of that field at another location at a given analysis time. The FCT postulates that, the larger the field coherence is, the fewer measurement sites are needed to resolve adequately the dominant characteristics of that field. Proof of concept was demonstrated using real data from an extensive field-program database over the San Joaquin Valley in the summer of 1990. The FCT next was applied to numerical model results for the same period, which produced similar guidance. The transferability of the methodology from real data to numerical model results having been demonstrated, the FCT then was applied in a model-based study over California's South Coast Air Basin to contribute in the design of a new field program, the Southern California Ozone Study (SCOS97). Interpretation of the FCT results mostly corroborated a preliminary field-program design produced by the design team and based on past experience, subjective evaluation of historical datasets, and other considerations. However, the FCT results also led the design team to make several changes, which were confirmed by experts familiar with the meteorological behavior of the region and were included in the final SCOS97 fieldprogram plan.

97th American Meteorological Society Annual Meeting, Jan 25, 2017

97th American Meteorological Society Annual Meeting, Jan 24, 2017

97th American Meteorological Society Annual Meeting, Jan 26, 2017

98th American Meteorological Society Annual Meeting, Jan 10, 2018

Eos, Transactions American Geophysical Union, 2009

ABSTRACT A new cross-calibrated, multiplatform (CCMP) ocean surface wind product with wide-rangin... more ABSTRACT A new cross-calibrated, multiplatform (CCMP) ocean surface wind product with wide-ranging research applications in meteorology and oceanography became available at the Physical Oceanography Distributed Active Archive Center (PO.DACC) in May 2009. Data sets at three different levels of processing may be downloaded from http://podaac.jpl.nasa.gov/DATA_CATALOG/ccmpinfo.html. The principal data set, denoted as level 3.0, has global ocean coverage (except for the Arctic Ocean) with 25-kilometer resolution every 6 hours for more than 20 years, beginning in July 1987. Applying an enhanced variational analysis method (VAM) to multiple input data sources creates the level 3.0 data set. The VAM performs quality control and optimally combines wind observations from several individual satellite microwave radiometer and scatterometer sensors along with available conventional ship and buoy wind observations and European Centre for Medium-Range Weather Forecasts (ECMWF) analyses.

James Garrison, who is accomplished, open-minded and innovative, for the support and guidance dur... more James Garrison, who is accomplished, open-minded and innovative, for the support and guidance during my PhD studies. I would particularly like to thank Prof. Garrison for giving me opportunities of joining the CYGNSS science team, attending various conferences/workshops and having internships. Those experiences gave me chances to communicate with scientists all over the world and helped me become an independent researcher. I would like to acknowledge my committee members, Prof. Robin Tanamachi, Prof. Arthur Frazho and Prof. Dengfeng Sun for their patient instructions on meteorology and mathematics. Special thanks to Prof. Tanamachi for giving a lot of valuable suggestions on my dissertation.

Proceedings of SPIE, Aug 19, 2010

ABSTRACT Since the 1970s, an extensive series of data impact studies has been performed to evalua... more ABSTRACT Since the 1970s, an extensive series of data impact studies has been performed to evaluate and enhance the impact of satellite surface wind data on ocean surface wind analyses and fluxes, atmospheric and oceanic modeling, and weather prediction. These studies led to the first beneficial impacts of scatterometer winds on numerical weather prediction (NWP), the development of the methodology to assimilate surface wind speeds derived from passive microwave radiometry, and the operational use of satellite surface winds by marine forecasters and NWP models. In recent years, the impact of these data on NWP has decreased as more competing data have become available; however, the results of our recent experiments still show a very significant impact of satellite surface winds on ocean surface wind analyses and on the prediction of selected storms over the oceans.

Monthly Weather Review, Oct 1, 2015

The standard statistical model of data assimilation assumes that the background and observation e... more The standard statistical model of data assimilation assumes that the background and observation errors are normally distributed, and the first-and second-order statistical moments of the two distributions are known or can be accurately estimated. Because these assumptions are never satisfied completely in practice, data assimilation schemes must be robust to errors in the underlying statistical model. This paper tests simple approaches to improving the robustness of data assimilation in tropical cyclone (TC) regions. Analysis-forecast experiments are carried out with three types of data-Tropical Cyclone Vitals (TCVitals), DOTSTAR, and QuikSCAT-that are particularly relevant for TCs and with an ensemble-based data assimilation scheme that prepares a global analysis and a limited-area analysis in a TC basin simultaneously. The results of the experiments demonstrate that significant analysis and forecast improvements can be achieved for TCs that are category 1 and higher by improving the robustness of the data assimilation scheme.

Journal Of Geophysical Research: Oceans, Oct 1, 2019

The Cross-Calibrated Multiplatform (CCMP) ocean surface wind data set was originally developed by... more The Cross-Calibrated Multiplatform (CCMP) ocean surface wind data set was originally developed by Atlas and coworkers to blend cross-calibrated satellite winds, in situ data, and wind analyses from numerical weather prediction. CCMP uses a variational analysis method to smoothly blend these data sources into a gap-free gridded wind estimate every 6 hr. CCMP version 2.0 is currently produced by Remote Sensing Systems using consistently cross-calibrated satellite winds, in situ data from moored buoys, and background winds from the ERA-Interim reanalysis. The reanalysis fields are only available after a delay of several months, making it impossible to produce CCMP 2.0 in near real time. Measurements from in situ sources such as moored buoys are also often delayed. To overcome these obstacles and produce a near-real-time (NRT) version of CCMP (CCMP-NRT), two changes are made to the input data sets: The background winds are now the operational 0.25-degree NCEP analysis winds, and no in situ data are used. This allows CCMP-NRT to be routinely processed with a latency of less than 48 hr. An intercomparison of the CCMP-NRT results with CCMP 2.0, and independent measurements from moored buoys shows that CCMP-NRT provides a modest improvement over the background wind from NCEP in regions where satellite data are available. Analysis shows that the inclusion of in situ measurement in CCMP improves the agreement with these measurements, artificially reducing estimates of the error. Plain Language Summary Satellites that orbit the Earth estimate winds over the ocean by evaluating the roughness the ocean surface. These satellites make their measurements at different time of the day, and there are spatial gaps between the satellite measurements. These characteristics make the data hard to use. The Cross-Calibrated Multiplatform (CCMP) vector wind analysis uses a mathematical technique that combines satellite measurements, in situ measurements, and a background wind field into complete maps of ocean winds every 6 hr. This paper describes a new version of CCMP that can be constructed only a few days after the satellite measurement are made, opening up near-real-time applications for these data.

Bulletin of the American Meteorological Society, Feb 1, 2011

Global Navigation Satellite System Reflectometry (GNSS-R) is a remote sensing technique that uses... more Global Navigation Satellite System Reflectometry (GNSS-R) is a remote sensing technique that uses satellite navigation (GNSS) transmitters as non-cooperative sources in a bistatic radar configuration (Zavorotny et al., 2014). GNSS-R observations have been collected using receivers on stationary (

Water science and technology library, 2006

... In other data assimilation systems p and w, and perhaps q, are not allowed to vary. ... Befor... more ... In other data assimilation systems p and w, and perhaps q, are not allowed to vary. ... Before the bogus storm is added, the representation of the storm in the original data set is ... description of a tropical cyclone based on all available information, collected either in real-time or later ...

Journal of Applied Meteorology, Jun 1, 1999

The authors report on characteristics of a rain flag derived from collocation of visible and infr... more The authors report on characteristics of a rain flag derived from collocation of visible and infrared image data with rain rates over the North Atlantic Ocean obtained from microwave imagery (SSM/I) during a 3-week period (15 October 1996-2 November 1996). The rain flag has been developed as part of an effort to provide an indication of contamination by heavy rainfall

Monthly Weather Review, Oct 1, 2021

An observing system experiment was conducted to assess the impact of wind products derived from t... more An observing system experiment was conducted to assess the impact of wind products derived from the Cyclone Global Navigation Satellite System (CYGNSS) on tropical cyclone track, maximum 10-m wind speed V max , and minimum sea level pressure forecasts. The experiment used a global data assimilation and forecast system, and the impact of both CYGNSS-derived scalar and vector wind retrievals was investigated. The CYGNSS-derived vector wind products were generated by optimally combining the scalar winds and a gridded a priori vector field. Additional tests investigated the impact of CYGNSS data on a regional model through the impact of lateral boundary and initial conditions from the global model during the developmental phase of Hurricane Michael (2018). In the global model, statistically significant track forecast improvements of 20-40 km were found in the first 60 h. The V max forecasts showed some significant degradations of ;2 kt at a few lead times, especially in the first 24 h. At most lead times, impacts were not statistically significant. Degradations in V max for Hurricane Michael in the global model were largely attributable to a failure of the CYGNSSderived scalar wind test to produce rapid intensification in the forecast initialized at 0000 UTC 7 October. The storm in this test was notably less organized and symmetrical than in the control and CYGNSS-derived vector wind test. The regional model used initial and lateral boundary conditions from the global control and CYGNSS scalar wind tests. The regional forecasts showed large improvements in track, V max , and minimum sea level pressure.

Quarterly Journal of the Royal Meteorological Society, Apr 1, 2021

Direct remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, o... more Direct remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, or radio occultation bending angle) are often more effective for use in data assimilation (DA) than the corresponding geophysical retrievals (e.g., ocean surface winds, soil moisture, or atmospheric water vapor). In the particular case of Global Navigation Satellite System Reflectometry (GNSS‐R), the lower‐level delay‐Doppler map (DDM) observable shows a complicated relationship with the ocean surface wind field. Prior studies have demonstrated DA using GNSS‐R wind retrievals inferred from DDMs. The complexity of the DDM dependence on winds, however, suggests that the alternative approach of ingesting DDM observables directly into DA systems, without performing a wind retrieval, may be beneficial. We demonstrate assimilation of DDM observables from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission into global ocean surface wind analyses using a two‐dimensional variational analysis method. Bias correction and quality‐control methods are described. Several models for the required observation‐error covariance matrix are developed and evaluated, with the conclusion that a diagonal matrix performs as well as a fully populated matrix empirically tuned to a large ensemble of CYGNSS observation data. The 10‐m surface winds from the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational forecast are used as the background (i.e., prior in the variational analysis). Results are compared with independent scatterometer (the advanced scatterometer (ASCAT), the oceansat‐2 Scatterometer (OSCAT)) winds. For one month (June 2017) of data, the root‐mean‐square difference (RMSD) was reduced from 1.17 to 1.07 m·s−1 and bias from −0.14 to −0.08 m·s−1 for the wind speed at the specular point. Within a 150‐km wide swath along the specular point track, the RMSD was reduced from 1.20 to 1.13 m·s−1. These RMSD and bias statistics are smaller than other CYGNSS wind products available at this time.

Journal of Applied Meteorology, Mar 1, 2000

This paper describes a new methodology developed to provide objective guidance for cost-effective... more This paper describes a new methodology developed to provide objective guidance for cost-effective siting of meteorological observations on the mesoscale for air quality applications. This field-coherence technique (FCT) is based on a statistical analysis of the mesoscale atmospheric structure defined by the spatial and temporal ''coherence'' in the meteorological fields. The coherence, as defined here, is a measure of the distance scale over which there is temporal consistency in the spatial structure within a variable field. It indicates how well a measurement taken at one location can be used to estimate the value of that field at another location at a given analysis time. The FCT postulates that, the larger the field coherence is, the fewer measurement sites are needed to resolve adequately the dominant characteristics of that field. Proof of concept was demonstrated using real data from an extensive field-program database over the San Joaquin Valley in the summer of 1990. The FCT next was applied to numerical model results for the same period, which produced similar guidance. The transferability of the methodology from real data to numerical model results having been demonstrated, the FCT then was applied in a model-based study over California's South Coast Air Basin to contribute in the design of a new field program, the Southern California Ozone Study (SCOS97). Interpretation of the FCT results mostly corroborated a preliminary field-program design produced by the design team and based on past experience, subjective evaluation of historical datasets, and other considerations. However, the FCT results also led the design team to make several changes, which were confirmed by experts familiar with the meteorological behavior of the region and were included in the final SCOS97 fieldprogram plan.

97th American Meteorological Society Annual Meeting, Jan 25, 2017

97th American Meteorological Society Annual Meeting, Jan 24, 2017

97th American Meteorological Society Annual Meeting, Jan 26, 2017

98th American Meteorological Society Annual Meeting, Jan 10, 2018

Eos, Transactions American Geophysical Union, 2009

ABSTRACT A new cross-calibrated, multiplatform (CCMP) ocean surface wind product with wide-rangin... more ABSTRACT A new cross-calibrated, multiplatform (CCMP) ocean surface wind product with wide-ranging research applications in meteorology and oceanography became available at the Physical Oceanography Distributed Active Archive Center (PO.DACC) in May 2009. Data sets at three different levels of processing may be downloaded from http://podaac.jpl.nasa.gov/DATA_CATALOG/ccmpinfo.html. The principal data set, denoted as level 3.0, has global ocean coverage (except for the Arctic Ocean) with 25-kilometer resolution every 6 hours for more than 20 years, beginning in July 1987. Applying an enhanced variational analysis method (VAM) to multiple input data sources creates the level 3.0 data set. The VAM performs quality control and optimally combines wind observations from several individual satellite microwave radiometer and scatterometer sensors along with available conventional ship and buoy wind observations and European Centre for Medium-Range Weather Forecasts (ECMWF) analyses.

James Garrison, who is accomplished, open-minded and innovative, for the support and guidance dur... more James Garrison, who is accomplished, open-minded and innovative, for the support and guidance during my PhD studies. I would particularly like to thank Prof. Garrison for giving me opportunities of joining the CYGNSS science team, attending various conferences/workshops and having internships. Those experiences gave me chances to communicate with scientists all over the world and helped me become an independent researcher. I would like to acknowledge my committee members, Prof. Robin Tanamachi, Prof. Arthur Frazho and Prof. Dengfeng Sun for their patient instructions on meteorology and mathematics. Special thanks to Prof. Tanamachi for giving a lot of valuable suggestions on my dissertation.

Proceedings of SPIE, Aug 19, 2010

ABSTRACT Since the 1970s, an extensive series of data impact studies has been performed to evalua... more ABSTRACT Since the 1970s, an extensive series of data impact studies has been performed to evaluate and enhance the impact of satellite surface wind data on ocean surface wind analyses and fluxes, atmospheric and oceanic modeling, and weather prediction. These studies led to the first beneficial impacts of scatterometer winds on numerical weather prediction (NWP), the development of the methodology to assimilate surface wind speeds derived from passive microwave radiometry, and the operational use of satellite surface winds by marine forecasters and NWP models. In recent years, the impact of these data on NWP has decreased as more competing data have become available; however, the results of our recent experiments still show a very significant impact of satellite surface winds on ocean surface wind analyses and on the prediction of selected storms over the oceans.

Monthly Weather Review, Oct 1, 2015

The standard statistical model of data assimilation assumes that the background and observation e... more The standard statistical model of data assimilation assumes that the background and observation errors are normally distributed, and the first-and second-order statistical moments of the two distributions are known or can be accurately estimated. Because these assumptions are never satisfied completely in practice, data assimilation schemes must be robust to errors in the underlying statistical model. This paper tests simple approaches to improving the robustness of data assimilation in tropical cyclone (TC) regions. Analysis-forecast experiments are carried out with three types of data-Tropical Cyclone Vitals (TCVitals), DOTSTAR, and QuikSCAT-that are particularly relevant for TCs and with an ensemble-based data assimilation scheme that prepares a global analysis and a limited-area analysis in a TC basin simultaneously. The results of the experiments demonstrate that significant analysis and forecast improvements can be achieved for TCs that are category 1 and higher by improving the robustness of the data assimilation scheme.

Journal Of Geophysical Research: Oceans, Oct 1, 2019

The Cross-Calibrated Multiplatform (CCMP) ocean surface wind data set was originally developed by... more The Cross-Calibrated Multiplatform (CCMP) ocean surface wind data set was originally developed by Atlas and coworkers to blend cross-calibrated satellite winds, in situ data, and wind analyses from numerical weather prediction. CCMP uses a variational analysis method to smoothly blend these data sources into a gap-free gridded wind estimate every 6 hr. CCMP version 2.0 is currently produced by Remote Sensing Systems using consistently cross-calibrated satellite winds, in situ data from moored buoys, and background winds from the ERA-Interim reanalysis. The reanalysis fields are only available after a delay of several months, making it impossible to produce CCMP 2.0 in near real time. Measurements from in situ sources such as moored buoys are also often delayed. To overcome these obstacles and produce a near-real-time (NRT) version of CCMP (CCMP-NRT), two changes are made to the input data sets: The background winds are now the operational 0.25-degree NCEP analysis winds, and no in situ data are used. This allows CCMP-NRT to be routinely processed with a latency of less than 48 hr. An intercomparison of the CCMP-NRT results with CCMP 2.0, and independent measurements from moored buoys shows that CCMP-NRT provides a modest improvement over the background wind from NCEP in regions where satellite data are available. Analysis shows that the inclusion of in situ measurement in CCMP improves the agreement with these measurements, artificially reducing estimates of the error. Plain Language Summary Satellites that orbit the Earth estimate winds over the ocean by evaluating the roughness the ocean surface. These satellites make their measurements at different time of the day, and there are spatial gaps between the satellite measurements. These characteristics make the data hard to use. The Cross-Calibrated Multiplatform (CCMP) vector wind analysis uses a mathematical technique that combines satellite measurements, in situ measurements, and a background wind field into complete maps of ocean winds every 6 hr. This paper describes a new version of CCMP that can be constructed only a few days after the satellite measurement are made, opening up near-real-time applications for these data.

Bulletin of the American Meteorological Society, Feb 1, 2011

Global Navigation Satellite System Reflectometry (GNSS-R) is a remote sensing technique that uses... more Global Navigation Satellite System Reflectometry (GNSS-R) is a remote sensing technique that uses satellite navigation (GNSS) transmitters as non-cooperative sources in a bistatic radar configuration (Zavorotny et al., 2014). GNSS-R observations have been collected using receivers on stationary (

Water science and technology library, 2006

... In other data assimilation systems p and w, and perhaps q, are not allowed to vary. ... Befor... more ... In other data assimilation systems p and w, and perhaps q, are not allowed to vary. ... Before the bogus storm is added, the representation of the storm in the original data set is ... description of a tropical cyclone based on all available information, collected either in real-time or later ...

Journal of Applied Meteorology, Jun 1, 1999

The authors report on characteristics of a rain flag derived from collocation of visible and infr... more The authors report on characteristics of a rain flag derived from collocation of visible and infrared image data with rain rates over the North Atlantic Ocean obtained from microwave imagery (SSM/I) during a 3-week period (15 October 1996-2 November 1996). The rain flag has been developed as part of an effort to provide an indication of contamination by heavy rainfall

Monthly Weather Review, Oct 1, 2021

An observing system experiment was conducted to assess the impact of wind products derived from t... more An observing system experiment was conducted to assess the impact of wind products derived from the Cyclone Global Navigation Satellite System (CYGNSS) on tropical cyclone track, maximum 10-m wind speed V max , and minimum sea level pressure forecasts. The experiment used a global data assimilation and forecast system, and the impact of both CYGNSS-derived scalar and vector wind retrievals was investigated. The CYGNSS-derived vector wind products were generated by optimally combining the scalar winds and a gridded a priori vector field. Additional tests investigated the impact of CYGNSS data on a regional model through the impact of lateral boundary and initial conditions from the global model during the developmental phase of Hurricane Michael (2018). In the global model, statistically significant track forecast improvements of 20-40 km were found in the first 60 h. The V max forecasts showed some significant degradations of ;2 kt at a few lead times, especially in the first 24 h. At most lead times, impacts were not statistically significant. Degradations in V max for Hurricane Michael in the global model were largely attributable to a failure of the CYGNSSderived scalar wind test to produce rapid intensification in the forecast initialized at 0000 UTC 7 October. The storm in this test was notably less organized and symmetrical than in the control and CYGNSS-derived vector wind test. The regional model used initial and lateral boundary conditions from the global control and CYGNSS scalar wind tests. The regional forecasts showed large improvements in track, V max , and minimum sea level pressure.