PRISM Climate Group

Orchards and vineyards are particularly sensitive to temperature and are increasingly important to rural economies of the Southwest. However, growers of these high-value perennial fruit and nut crops have limited climate information to support critical decisions about selecting sites and cultivars. This project involves Cooperative Extension in AZ and NM and individual growers to survey a set of orchards and vineyards currently under production to gather information about their siting and cultivars. An assessment will be made of the required temperature conditions for current cultivars, whether these have historically been met, and if they are likely to be met in the coming decades. Crop insurance indemnity records will be used to perform a financial assessment of how site and cultivar selection are functioning in the current regional climate. The suitability of present-day cultivars will be evaluated in the context of anticipated increases in regional temperature.

To help inform the expanding winegrape-growing industry in Arizona, we are compiling and visualizing data of several relevant aspects of climate, soil, and topography specific to the proposed Sonoita, Willcox, and Verde Valley AVAs. This standard information about winegrape-growing regions does not exist for Arizona AVAs. https://cals.arizona.edu/research/climategem/content/arizona-avas.

The Climate Viticulture Newsletter provides a quick look at timely climate topics relevant to winegrape growing in Arizona and New Mexico. Monthly and mid-month special issues are sent via email and posted online. https://cals.arizona.edu/research/climategem/content/climate-viticultur….

Drought is a complex phenomenon that can vary widely over space to due to precipitation patterns and in time due to lagging impacts in slowly varying systems. These factors are magnified in the semiarid Southwest U.S., where extreme interannual climate variability, topography, and highly localized precipitation patterns (e.g., monsoon season thunderstorms) create highly varying hydroclimatic patterns in both space and time and subsequent drought impacts. Current climate monitoring networks across Arizona and New Mexico struggle to capture this variability and accurately portray potential drought conditions.

Complementary datasets, like remote sensing greenness, used in conjunction with existing climate data, offer the potential to monitor drought conditions across large landscapes with sparse monitoring networks. Several efforts, including online geovisualization tools to access raw normalized-difference vegetation index (NDVI or greenness) data and more formalized remote sensing-based drought monitoring tools like VegDRI, have been developed over the past decade. A new effort supported by a recent NOAA-SARP/NIDIS grant spurred the development of tool called DroughtView, which takes a slightly different approach in combining cutting-edge online geovisualization tools with derived remote sensing products targeted at detecting drought conditions. DroughtView builds on the success of its precursor, RangeView, which was developed with guidance from agriculturists and resource managers who need environmental monitoring data. The tools in DroughtView are used to monitor biweekly changes in land surface greenness conditions as a proxy for drought impacts at very fine spatial scales across the Southwest U.S. More information can be found at http://droughtview.arizona.edu

DroughtView combines geovisualization tools with remote sensing products to detect drought conditions. The DroughtView tool served as a key piece of information to help the National Resources Conservation Service, US Bureau of Land Management, and US Forest Service range managers determine drought conditions and Farm Services Agency drought disaster assistance eligibility. DroughtView is a web-based decision-support tool for computers and mobile devices that combines satellite-derived measures of surface greenness with additional geospatial data so that users can visualize and evaluate vegetation dynamics across space and over time.