The Impact of High-Frequency Weather Systems on SST and Surface Mixed Layer in the Central Arabian Sea

The role of high-frequency (sub-daily time scales) weather systems in modulating the sea surface temperature (SST) and the mixed layer (ML) depth in the central Arabian Sea is investigated using one-dimensional mixed-layer models for different monsoon seasons. Simulations forced by sub-hourly sampled meteorological variables, including surface wind, air temperature, humidity and cloud, are compared to simulations forced by daily-averaged meteorological variables. It is found that including high-frequency signals in the meteorological variables lowers the daily-mean SST (by 0.8°C on average) and damps its variability (the standard deviation decreases by 1.0°C), but has little systematic effect on the SST diurnal variability. There is a small but consistent deepening of the ML depth associated with the slightly intensified wind stress and heat loss due to high-frequency weather systems at this site. The cooling effect on the daily-mean SST is found to be closely related to the ML depth on daily-to-seasonal time scales. The impact of high-frequency weather systems is primarily driven by the high-frequency wind via the turbulent heat and momentum fluxes

Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization

Research PaperThe A&P approach, developed by Allen and Pereira (2009), estimates single and basal crop coefficients (Kc and Kcb) from the observed fraction of ground cover (fc) and crop height (h). The practical application of the A&P for several crops was reviewed and tested in a companion paper (Pereira et al., 2020). The current study further addresses the derivation of optimal values for A&P parameter values representing canopy transparency (ML) and stomatal adjustment (Fr), and tests the resulting model performance. Values reported in literature of ML and Fr were analysed. Optimal ML and Fr values were derived by a numerical search that minimized the differences between Kcb A&P with standard Kcb for vegetable, field, and fruit crops as tabulated by Pereira et al. (2021a, 2021b) and Rallo et al. (2021). Sources for fc were literature reviews supplemented by a remote sensing survey. Computed Kcb and Kc for mid- and end-season together with associated parameters values were tabulated. To improve the usability of the ML and Fr parameters a cross validation was performed, which consisted of the linear regression between Kcb computed by A&P and observed Kcb relative to independent data sets obtained from field observations. Results show that both series of Kcb match well, with regression coefficients very close to 1.0, coefficients of determination near 1.0, and root mean square errors (RMSE) of 0.06 for the annual crops and RMSE = 0.07 for the trees and vines. These errors represent less than 10% of most of the computed tabulated Kcb. The tabulated Fr and ML of this paper can be regarded as defaults to support A&P field practice when observations of fc and h are performed. Therefore, the A&P approach shows to be appropriate for use in irrigation scheduling and planning when fc and h are observed using ground and/or remote sensing, hence supporting irrigation water savingsinfo:eu-repo/semantics/publishedVersio

Prediction of crop coefficients from fraction of ground cover and height. Background and validation using ground and remote sensing data

ReviewThe current study aims at reviewing and providing advances on methods for estimating and applying crop coefficients from observations of ground cover and vegetation height. The review first focuses on the relationships between single Kc and basal Kcb and various parameters including the fraction of ground covered by the canopy (fc), the leaf area index (LAI), the fraction of ground shaded by the canopy (fshad), the fraction of intercepted light (flight) and intercepted photosynthetic active radiation (fIPAR). These relationships were first studied in the 1970’s, for annual crops, and later, in the last decennia, for tree and vine perennials. Research has now provided a variety of methods to observe and measure fc and height (h) using both ground and remote sensing tools, which has favored the further development of Kc related functions. In the past, these relationships were not used predictively but to support the understanding of dynamics of Kc and Kcb in relation to the processes of evapotranspiration or transpiration, inclusive of the role of soil evaporation. Later, the approach proposed by Allen and Pereira (2009), the A&P approach, used fc and height (h) or LAI data to define a crop density coefficient that was used to directly estimate Kc and Kcb values for a variety of annual and perennial crops in both research and practice. It is opportune to review the A&P method in the context of a variety of studies that have derived Kc and Kcb values from field measured data with simultaneously observed ground cover fc and height. Applications used to test the approach include various tree and vine crops (olive, pear, and lemon orchards and vineyards), vegetable crops (pea, onion and tomato crops), field crops (barley, wheat, maize, sunflower, canola, cotton and soybean crops), as well as a grassland and a Bermudagrass pasture. Comparisons of Kcb values computed with the A &P method produced regression coefficients close to 1.0 and coefficients of determination≥0.90, except for orchards. Results indicate that the A&P approach can produce estimates of potential Kcb, using vegetation characteristics alone, within reasonable or acceptable error, and are useful for refining Kcb for conditions of plant spacing, size and density that differ from standard values. The comparisons provide parameters appropriate to applications for the tested crops. In addition, the A&P approach was applied with remotely sensed fc data for a variety of crops in California using the Satellite Irrigation Management Support (SIMS) framework. Daily SIMS crop ET (ETc-SIMS) produced Kcb values using the FAO56 and A&P approaches. Combination of satellite derived fc and Kcb values with ETo data from Spatial CIMIS (California Irrigation Management Information System) produced ET estimates that were compared with daily actual crop ET derived from energy balance calculations from micrometeorological instrumentation (ETc EB).Results produced coefficients of regression of 1.05 for field crops and 1.08 for woody crops, and R2 values of 0.81 and 0.91, respectively. These values suggest that daily ETc-SIMS -based ET can be accurately estimated within reasonable error and that the A&P approach is appropriate to support that estimation. It is likely that accuracy can be improved via progress in remote sensing determination of fc. Tabulated Kcb results and calculation parameters are presented in a companion paper in this Special Issueinfo:eu-repo/semantics/publishedVersio