The wildland-urban interface (WUI)—the area where wildland vegetation and urban buildings intermix—is at a greater risk of fire occurrence because of extensive human activity in that area. Although satellite remote sensing has become a major tool for assessing fire damage in wildlands, it is unsuitable for WUI fire monitoring due to the low spatial resolution of the images from satellites that provide frequent information which is relevant for timely fire monitoring in WUI. Here, we take advantage of frequent (i.e., ca. daily), high-spatial-resolution (3 m) imagery acquired from a constellation of nano-satellites operated by Planet Labs (“Planet”) to assess fire damage to urban trees in the WUI of a Mediterranean city in Israel (Haifa). The fire occurred at the end of 2016, consuming ca. 17,000 of the trees (152 trees ha⁻¹) within the near-by wildland and urban parts of the city. Three vegetation indices (GNDVI, NDVI and GCC) from Planet satellite images were used to derive a burn severity map for the WUI area after applying a subpixel discrimination method to distinguish between woody and herbaceous vegetation. The produced burn severity map was successfully validated with information acquired from an extensive field survey in the WUI burnt area (overall accuracy and kappa: 87% and 0.75, respectively). Planet’s vegetation indices were calibrated using in-field tree measurements to obtain high spatial resolution maps of burned trees and consumed woody biomass in the WUI. These were used in conjunction with an ecosystem services valuation model (i-Tree) to estimate spatially-distributed and total economic loss due to damage to urban trees caused by the fire. Results show that nearly half of the urban trees were moderately and severely burned (26% and 22%, respectively). The total damage to the urban forest was estimated at ca. 41 ± 10 M USD. We conclude that using the method developed in this study with high-spatial-resolution Planet images has a great potential for WUI fire economic assessment.

Meteorological and oceanographic data collected at the head of the Gulf of Elat were used to compute the air–sea heat flux components and the heat storage in the water column, which are in turn used to estimate the heat balance of this semienclosed basin. The solar radiation was measured directly, whereas the longwave (LW) cooling and the turbulent heat fluxes (latent, LH; sensible, SH) were computed from commonly used bulk formulas. Nine formulas for LW and four formulas for LH + SH were tested for a total of 36 possible combinations. Independent estimates for the bounds on the advective heat flux through the straits and results from a one-dimensional mixed layer model provided criteria to help identify the best choice of bulk formulas for the gulf. It was concluded that the LW formula of Bignami together with the turbulent flux formulas of Kondo provide the best estimate of the heat balance of the gulf. Based on this, the annual mean evaporation is 1.6–1.8 m yr−1, with a minimum of 1 m yr−1 in (the long) summer and a maximum of 3–4 m yr−1 in (the short) winter. The increase in evaporation rate during the winter results from the instability of the atmosphere at that time when the sea surface temperature exceeds the air temperature; in the summer, when the air temperature is much higher than the sea surface temperature, evaporation nearly stops due to the atmospheric stability. This estimated evaporation rate for the gulf, which is similar for all four of the LH formulas considered, is significantly smaller than values commonly quoted in the literature. Finally, in contrast to previous studies, it is found that the advective heat flux from the Straits of Tiran is large and significant in spring, reaching an estimated value of over 125 W m−2, but its annually averaged value is only about 35–40 W m−2.

As part of the Mediterranean Forecasting System Pilot Project (MFSPP) we have implemented a high-resolution (2 km horizontal grid, 30 sigma levels) version of the Princeton Ocean Model for the southeastern corner of the Mediterranean Sea. The domain extends 200 km offshore and includes the continental shelf and slope, and part of the open sea. The model is nested in an intermediate resolution (5.5 km grid) model that covers the entire Levantine, Ionian, and Aegean Sea. The nesting is one way so that velocity, temperature, and salinity along the boundaries are interpolated from the relevant intermediate model variables. An integral constraint is applied so that the net mass flux across the open boundaries is identical to the net flux in the intermediate model. The model is integrated for three perpetual years with surface forcing specified from monthly mean climatological wind stress and heat fluxes. The model is stable and spins up within the first year to produce a repeating seasonal cycle throughout the three-year integration period. While there is some internal variability evident in the results, it is clear that, due to the relatively small domain, the results are strongly influenced by the imposed lateral boundary conditions. The results closely follow the simulation of the intermediate model. The main improvement is in the simulation over the narrow shelf region, which is not adequately resolved by the coarser grid model. Comparisons with direct current measurements over the shelf and slope show reasonable agreement despite the limitations of the climatological forcing. The model correctly simulates the direction and the typical speeds of the flow over the shelf and slope, but has difficulty properly re-producing the seasonal cycle in the speed.Key words. Oceanography: general (continental shelf processes; numerical modelling; ocean prediction)

Wildfire simulations depend on fuel representation. Present fuel models are mainly based on the density and properties of different vegetation types. This study aims to improve the accuracy of WRF-Fire wildfire simulations, by using synthetic-aperture radar (SAR) data to estimate the fuel load and the trend of vegetation index to estimate the dryness of woody vegetation. We updated the chaparral and timber standard woody fuel classes in the WRF-Fire fuel settings. We used the ESA global above-ground biomass (AGB) based on SAR data to estimate the fuel load, and the Landsat normalized difference vegetation index (NDVI) trends of woody vegetation to estimate the fuel moisture content. These fuel sub-parameters represent the dynamic changes and spatial variability of woody fuel. We simulated two wildfires in Israel while using three different fuel models: the original 13 Anderson Fire Behavior fuel model, and two modified fuel models introducing AGB alone, and AGB and dryness. The updated fuel model (the basic fuel model plus the AGB and dryness) improved the simulation results significantly, i.e., the Jaccard similarity coefficient increased by 283% on average. Our results demonstrate the potential of combining satellite SAR data and Landsat NDVI trends to improve WRF-Fire wildfire simulations.