Adaptive Observation Techniques

ENSEMBLE TRANSFORM KALMAN FILTER SINGULAR VECTORS

Sensitive areas for adaptive sampling include both the

hurricane core and environmental

features.

Where should we assimilate extra observations to improve a 2-day forecast of the wind field

associated with Hurricane Katrina?

Techniques to locate adaptive observations have been developed:

Only with global models

Initial results are promising although techniques may disagree

Data Assimilation Research

How do we exploit a wind observation in Katrina’s inner core to produce a realistic analysis?

Ensemble Kalman Filters may produce a realistic mesoscale structure of the hurricane, without a bogus.

Red shading: change in wind speed due to assimilation of one wind observation.

(Courtesy Dr Xuguang Wang,

NOAA/ESRL)

Open Questions for NIS

1. Is there a need for adaptive sampling with NIS?a. Is the adaptive hurricane tracking mode sufficient?b. Any scope for selectively sampling synoptic environment, such as an

approaching precipitating system of mid-latitude origin?c. Is it beneficial to optimize sampling intervals, radius of spiral, over-

sampling, rotational speed, number of arms etc?

2. Adaptive observation strategies have focused on the synoptic environmenta. Are such strategies effective in the TC core? New strategies required?

3. Data assimilation of Z and v within TC core will likely be an asset for NWPa. Important spatial (3-d) and temporal resolution for assimilation?b. Best method to exploit Z fields?

4. Research requireda. Observation System Simulation Experiments (OSSEs) with operational-

quality, core-resolving model and different configurations of synthetic NIS data. Assess impact of data on models.

b. Advances in data assimilation methods (4dVar, EnKFs etc.)

Science Panel II

Develop consensus amongst panel members concerning specific uses and value that NIS would have on TC NWP and data assimilation paradigm. Of particular interest are: a. Given the expectation that operational TC NWP model(s) will be running at cloud-resolving resolutions (~km) and possibly in ensemble mode during the lifetime of the NIS, how will its observations facilitate the initialization of TCs and their precursors via advanced data assimilation? b. What are the most desirable observation parameters (e.g., radial velocity, reflectivity, polarimetric variables, Doppler spectra) and what unique information do they provide for the cloud-resolving TC NWP purpose? c. What unique information will NIS provide to enhance data assimilation for TCs in global and other non-TC specific models that will most likely to be running at non-cloud-resolving resolutions? d. What is the expected duration of NIS impact on both deterministic and probabilistic TC forecasts? e. What are the expected impacts of NIS observations on the overall intensity/structure prediction problem?

Science Panel II

f. What are the expected impacts of NIS observations on TCsurge and hydrological forecasting derived from TC model forecasts? g. Within the proposed technological constraint (~spiral scans of 5000 km diameter area every hour, at 12 km resolution without over-sampling), what might be the preferred scanning configurations for the cloud-resolving TC NWP purpose? Should or can NIS operate in coarse grain (e.g., tracking TC vortex) or fine-grain (e.g., changing scanning configurations for different parts of the TC on the fly and choosing scanning modes based on expected TC development) adaptive scanning mode? What happens when multiple TCs are in view?

(2) Given proposed NIS instrument design (i.e., frequency, Doppler acuity, polarimetric diversity, resolution, scan strategy, orbit) and issues relevant to future TC NWP and data assimilation (i.e., cloud resolving deterministic and probabilistic models), develop consensus on: a. aspects of design that are particularly useful, b. critical weaknesses that must be addressed, c. enhancements to design that should be considered.