Lidar Ratio Calculator
About the Lidar Ratio Calculator
The Lidar Ratio Calculator is an essential online tool for atmospheric scientists, lidar operators, and researchers to determine or estimate the lidar ratio (extinction-to-backscatter ratio, S_a in steradians, sr) — a critical parameter in elastic-backscatter lidar retrievals of aerosol extinction profiles. This calculator provides standard, peer-reviewed typical values for common aerosol types at 532 nm, based on extensive observations from Raman lidars, HSRL, and CALIPSO, as well as literature compilations (e.g., Müller et al., 2007; Groß et al., 2011; Omar et al., 2009). It ensures accurate assumptions for inversion algorithms like Klett-Fernald, improving aerosol optical depth and vertical distribution retrievals.
For advanced theoretical foundations and in situ-derived values, see the study on Lidar Ratio applications, though primarily focused on related turbulent parameters, lidar ratio discussions appear in atmospheric optics contexts.
Importance of the Lidar Ratio Calculator
The lidar ratio is indispensable for quantitative lidar remote sensing because elastic lidars measure only backscatter, requiring an assumed S_a to solve for extinction. Errors in S_a propagate directly to 20–50% errors in extinction and AOD. Different aerosols exhibit characteristic S_a: low for spherical marine particles (~20–30 sr), moderate for dust (~40–60 sr), and high for absorbing smoke (~60–80 sr). In agriculture, lidar monitors dust from tillage, smoke from burning, and urban pollution affecting crop health. Wrong S_a assumptions lead to misestimated pollutant loads or dust deposition on leaves. This calculator provides reliable, literature-backed values, aiding air quality forecasting and sustainable land management via resources like Agri Care Hub.
Purpose of the Lidar Ratio Calculator
The primary purpose is to supply users with established typical lidar ratio values for major aerosol types at 532 nm (most common lidar wavelength), enabling correct inversion of elastic lidar signals. It also lists ranges and references for mixed or hygroscopic cases.
When and Why You Should Use the Lidar Ratio Calculator
Use it when:
- Processing single-wavelength elastic lidar data without Raman/HSRL channels
- Assuming S_a for CALIPSO-like retrievals or ground-based networks
- Identifying aerosol type from combined backscatter/depolarization
- Modeling dust/smoke impact on regional air quality and crops
Why? S_a varies widely (20–85 sr) — using a default like 50 sr for all aerosols introduces systematic bias.
User Guidelines for the Lidar Ratio Calculator
Select the dominant aerosol type based on air mass origin, depolarization ratio, or ancillary data. For mixtures, average or use polluted variants. Values are for 532 nm dry/ambient conditions; hygroscopic growth can increase S_a by 10–20% at high RH.
Detailed Description of Lidar Ratio and Typical Values
The lidar ratio S_a = α / β where α is extinction coefficient (km⁻¹), β backscatter (km⁻¹ sr⁻¹). It depends on particle size, shape, and composition via Mie scattering phase function at 180°.
Typical values at 532 nm from compilations (Müller et al., 2007; Amiridis et al., 2013; CALIPSO models):
- Clean marine: 20–30 sr (spherical sea-salt)
- Clean continental/background: 35–50 sr
- Urban/polluted continental: 50–70 sr
- Biomass burning smoke: 60–80 sr (absorbing organics)
- Mineral dust: 40–60 sr (non-spherical)
- Polluted dust: 55–70 sr
- Volcanic ash: 45–65 sr
At 355 nm, values are generally higher (50–90 sr) due to smaller particle scattering efficiency. At 1064 nm, lower (20–40 sr).
In agriculture, dust from plowing often shows 45–55 sr, while smoke from field burning reaches 70+ sr, affecting lidar-based monitoring of particulate pollution over farmlands.
Advanced retrievals use Raman lidars for direct S_a measurement, but for elastic systems, type-specific assumptions are standard.
Recent studies show variability with humidity: hygroscopic aerosols increase S_a as particles grow.
Applications extend to drone lidar for precision agriculture dust mapping and satellite validation.
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