An Eye on the Storm: Integrating a Wealth of Data for Quickly Advancing the Physical Understanding and Forecasting of Tropical Cyclones

Hristova-Veleva, S. M.; Li, P. Peggy; Knosp, B.; Vu, Quoc; Turk, F. Joseph; Poulsen, W. L.; Haddad, Ziad S.; Lambrigtsen, Bjorn; Stiles, B.; Shen, Tsae-Pyng Janice; Niamsuwan, N.; Tanelli, Simone; Sy, Ousmane O.; Seo, Eun‐Kyoung; Su, Hui; Vane, D.; Chao, Yi; Callahan, Philip S.; Dunbar, R. S.; Montgomery, Michael T.; Boothe, Mark A.; Tallapragada, Vijay; Trahan, Samuel; Wimmers, Anthony; Holz, Robert A.; Reid, Jeffrey S.; Marks, Frank D.; Vukićević, Tomislava; Bhalachandran, Saiprasanth; Leighton, Hua; Gopalakrishnan, Sundararaman; Navarro, Andrés; Tapiador, Francisco J.

doi:10.1175/bams-d-19-0020.1

Cited by 10 publications

(8 citation statements)

References 44 publications

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“…16). The RI is a multi-channel index combining brightness temperatures (TB) in the 10-90 GHz range (Hristova-Veleva et al, 2020). The RI from the same GMI overpass (18:52 UTC) shown in Fig.…”

Section: Impact Of the Dawn Data Assimilation On Thementioning

confidence: 99%

“…These quantities are illustrated in the JPL CPEX portal (https://cpexportal.jpl.nasa.gov, last access: 30 April 2021) that combines satellite and airborne observations with model forecasts, specifically tailored for CPEX. The portal options provide interactive visualization and online analysis tools to help users understand tropical convection processes (Hristova-Veleva et al, 2020).…”

Section: Impact Of the Dawn Data Assimilation On Thementioning

confidence: 99%

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Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure

et al. 2021

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Abstract. An improved representation of 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there are few independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective timescales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 µm Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of high-resolution sparsely sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact on the wind field as well as the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to an increase in the near-surface convergence, temperature, and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. The onset of the vertical evolution of the precipitation showed similar radar-derived cloud-top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts.

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Section: Impact Of the Dawn Data Assimilation On Thementioning

confidence: 99%

Section: Impact Of the Dawn Data Assimilation On Thementioning

confidence: 99%

Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure

et al. 2021

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“…This complement of Doppler radar and DWL observations could provide a means to link horizontal wind data outside clouds and inside clouds (away from strong vertical motion, from APR-2), an important transition region. Space-based Doppler radar measurement methods to estimate the horizontal LOS (HLOS) wind in-cloud have been proposed (Illingworth et al, 2018) as one means to complement the HLOS winds from Aeolus. However, further investigation from CPEX and other APR-2 airborne data is needed to assess the quality of the radar wind components before they can be used for science or model data assimilation purposes.…”

Section: Dawn and Apr-2 Horizontal Winds On 11 June 2017mentioning

confidence: 99%

Joint analysis of convective structure from the APR-2 precipitation radar and the DAWN Doppler wind lidar during the 2017 Convective Processes Experiment (CPEX)

et al. 2020

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Abstract. The mechanisms linking convection and cloud dynamical processes are major factors in much of the uncertainty in both weather and climate prediction. Further constraining the uncertainty in convective cloud processes linking 3-D air motion and cloud structure through models and observations is vital for improvements in weather forecasting and understanding limits on atmospheric predictability. To date, there have been relatively few airborne observations specifically targeted for linking the 3-D air motion surrounding developing clouds to the subsequent development (or nondevelopment) of convective precipitation. During the May–June 2017 Convective Processes Experiment (CPEX), NASA DC-8-based airborne observations were collected from the JPL Ku- and Ka-band Airborne Precipitation Radar (APR-2) and the 2 µm Doppler Aerosol Wind (DAWN) lidar during approximately 100 h of flight. For CPEX, the APR-2 provided the vertical air motion and structure of the cloud systems in nearby precipitating regions where DAWN is unable to sense. Conversely, DAWN sampled vertical wind profiles in aerosol-rich regions surrounding the convection but is unable to sense the wind field structure within most clouds. In this paper, the complementary nature of these data are presented from the 10–11 June flight dates, including the APR-2 precipitation structure and Doppler wind fields as well as adjacent wind profiles from the DAWN data.

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“…This evidence comes from combining a number of retrievals of the total precipitable water (TPW) and passive MW rain index (RI) as provided by a variety of NASA, NOAA and EUMETSAT satellite systems. The rain index is a multichannel index combining brightness temperatures (TB) in the 10-90 GHz range (Hristova-Veleva et al, 2020b). These quantities are illustrated in the JPL CPEX portal (https://cpexportal.jpl.nasa.gov) that combines satellite and airborne observations with model forecasts, specifically tailored for CPEX.…”

Section: 2mentioning

confidence: 99%

“…These quantities are illustrated in the JPL CPEX portal (https://cpexportal.jpl.nasa.gov) that combines satellite and airborne observations with model forecasts, specifically tailored for CPEX. The portal options provide interactive visualization and on-line analysis tools to help understand tropical convection processes (Hristova-Veleva et al, 2020b). Figure 16 depicts the RI for the same GPM overpass as in Figure 5, with associated high satellite-derived TPW conditions in this identical area (not shown).…”

Section: 2mentioning

confidence: 99%

Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on the Precipitation and Flow Structure

Hristova-Veleva¹,

Zhang²,

Turk³

et al. 2020

Preprint

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Abstract. An improved representation of the 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there is little independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective times scales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2-um Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of the high resolution, sparsely-sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact to the wind field and the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to increase of the near surface convergence, temperature and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. Onset of the vertical evolution of the precipitation showed similar radar-derived cloud top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts.

show abstract

An Eye on the Storm: Integrating a Wealth of Data for Quickly Advancing the Physical Understanding and Forecasting of Tropical Cyclones

Abstract: Capsule Summary The JPL Tropical Cyclone Information System integrates observations with model forecasts, allowing interrogation of a large number of variables, to help better understand the multi-scale non-linear interactions that lead to storm development, and to evaluate models.

Cited by 10 publications

References 44 publications

Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure

Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure

Joint analysis of convective structure from the APR-2 precipitation radar and the DAWN Doppler wind lidar during the 2017 Convective Processes Experiment (CPEX)

Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on the Precipitation and Flow Structure

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