Searching the EconLit database for “frost” in article titles returns only four results involving actual frost in agriculture, none dealing with temperature altering. A search in the abstracts of papers published by the American Journal of Agricultural Economics results in two papers, neither mentioning air disturbance technologies. The seeming dis-interest in these technologies is even more peculiar in 2019, when weather information is more accessible than ever: air disturbance systems are now sold with online communication to weather services, with the option for automatic operation in case of frost, and can often be switched on and off remotely. They are probably more efficient and valuable than ever before, given advances in technology and the high value of certain frost-sensitive crops. Technologies such as air disturbance are examples of a concept I call “Micro-Climate Engineering” . These are relatively small interventions in temperature distributions, limited in space and time, which aim to avoid the nonlinear effects of the extremes. The frost examples discussed above deal with left tail effects. There are also technologies available to deal with right tail effects, which is the focus of my last chapter. The final chapter of this dissertation deals with an MCE proposal for California pistachios. Chapter 3 deals with the threat of warm winters on pistachios, estimating the potential losses to this high value crop from climate change. Chapter 4 deals with a proposed solution. The MCE technology proposed for this challenge is spraying the dormant trees with kaolin clay, a non-toxic white substance which reflects the sunlight. Sprayed trees have been shown to experience lower temperatures than control trees, and their yields were higher. This intervention requires precise hourly measures of temperature,large plastic pots for plants so growers can track the buildup of special temperature metrics and decide if and how much treatment is required. Using the pistachio yield-temperature response, estimated in the previous chapter, I build a model that integrates MCE in the pistachio market.
The model can be solved with and without the option to use MCE, under various weather realizations. The value of MCE for California pistachios is calculated as the difference in welfare measures attained in each case. The expected net present value of MCE in pistachios for 2020-2040 is assessed in billions of US dollars. This is yet another example of the potential use of weather information for dealing with climate change challenges in agriculture. Micro-Climate Engineering might remind some readers of Geo-Engineering, a controversial climate change adaptation concept. Geo-engineering proposals involve global scale interventions in the atmosphere and hydrosphere that would revert some of the changes in the total temperature distribution worldwide . In contrast, MCE is a small scale concept, aiming to tweak the temperature tail distributions where necessary rather than shifting the entire distribution year round. Many MCE technologies already exist and are used by growers, making sense both on the technical and economic dimensions. I believe many more examples are out there to be found, and many more will evolve as growers adapt to climate change.The study is based on a survey of CIMIS users. Before running the survey, extensive interviews were held with various users to gather narratives about the roles of CIMIS in different contexts. These interviews provided a first qualitative picture of current CIMIS uses and interactions with other technologies and practices. They suggest that CIMIS has indeed become a mainstay in California agriculture, especially for growers relying on drip irrigation. However, many farmers access CIMIS indirectly through consultants, and might not be aware of the uses and benefits of the system. With the advance of alternative decision making tools , CIMIS is now part of a larger information eco-system. The interviews showed that the public availability of CIMIS data, including historic records, are highly regarded among users. This historical and cross-sectional information store is extremely valuable for decision-making and research. It is essential for calibrating other weather tools, verifying their results, and designing water management schemes that require knowledge of the historical distribution of weather variables. In addition, it may even be used to more accurately value farmland. Interviews were followed by a small survey, carried out by phone and aimed at assessing the initial insights from the interview.
The final step was a full scale online survey, sent to all registered CIMIS users. Results from this survey are the basis for economic value calculations. The electronic survey was designed together with the CIMIS team, considering the results from the initial phone survey. It was decided to try and survey all registered CIMIS users, sending invitations to the email addresses used for enrollment. This might not cover all existing users: some might still be getting information through a third party, such as a consultant or media sources. There are also some electronic services which do not require registration, such as a File Transfer Protocol enabled server run by CIMIS. To survey potential users who are not registered, as well as potential users who are not currently using CIMIS, an invitation to participate was also sent by email to mailing lists provided by the CIMIS team. The survey included some general questions, directed to all audiences, and questions tailored to specific user groups identified in the initial survey: growers, consultants, users in landscape management, regulators, researchers, and others. The CIMIS team decided that the survey will not include direct questions about water use, costs, and willingness to pay for CIMIS services, especially when addressing growers. These questions were deemed too intrusive, jeopardizing both the response rate and general trust of users in the CIMIS system. This meant that a direct WTP approach, like the ones used in the previous study of CIMIS and the one used by Anaman and Lellyett , would not be possible.The analysis of the results uses indirect assessing of CIMIS impacts, using these types of responses and outside information. The online survey was done on a commercial platform, Survey Gizmo. It is worth noting that most registered users are not active. In fact, CIMIS user statistics show that a relative small percent of registered users had logged in and extracted data from the system in the year before the survey. Altogether, we have 3,057 responses, out of which 2,358 are complete.The breakdown of self-reported user types is listed in Table 2.1. About 1/4 of our respondents report their primary activity, as it relates to CIMIS, to be agriculture.
The second largest category is “other”, encompassing a mix of respondents who, in our opinion,blueberry pot should have picked another definition, and a few others who seem to use the data for personal research. This category has gardeners, nursery workers, water consultants, government workers, and a few retired people working on individual projects. We did not reclassify obvious mis-responses, as that would not change the fact that they ended up answering a different set of questions than their “real” category. The third category is government workers, followed closely by research, environmental consulting and landscape management. About 60% of respondents are aged 45 and above, and only about 17% are aged 25-35. While this might be the result of the age distribution in the major fields of occupation which are potential CIMIS users, it could also be that the current interface of CIMIS caters less to younger potential users who might seek the data elsewhere. About a quarter of respondents are women, and their share decreases at higher age groups. This probably reflects the changing labor force characteristics in CIMIS related professions over the past few decades. In terms of geographic location, most respondents report only one area of activity, with the San Joaquin Valley leading the count. Figure 2.1 below shows the shares of respondents in each region. Note that we allowed more than one response for location. We ask all respondents to rank each type of data, offered by CIMIS, according to the frequency they search for it. Figure 2.2 shows the breakdown of answers for each of the frequency choices. ET and precipitation are large shares of the “often” column. These shares decrease when moving in the “never” direction. On the other hand, one can observe an opposite trend for insolation , soil temperature, and relative humidity, which seem to be of less interest for respondents. Interestingly, air temperature seems less correlated with the frequency response, with response rate for “often” lower than “sometimes”. This could stem from the use of air temperature data: while irrigation requires using ET data often, air temperature data applications might require less frequent data pulls. Respondents seem satisfied with CIMIS services. About 72% of respondents reported using CIMIS at least occasionally. The user types reporting “often” using CIMIS the most were Agriculture, followed by Golf Course Management and Water Districts. These user types are indeed likely to use CIMIS on a day to day basis, at least for some part of the year. In research and planning, on the other hand, one might use CIMIS to draw data only at an initial stage of a given task. In general terms, of the respondents who report using CIMIS to some extent, 77% say it is at least “moderately important” for their operations, with 22% reporting CIMIS as “extremely important”. The frequency of use and importance scores are positively correlated: frequent users also report high importance of CIMIS to their operations, which makes sense.
The correlations between frequency and satisfaction, and between importance and satisfaction, seem less pronounced. There might be users who use CIMIS infrequently, perhaps because only a smaller part of their tasks involve the weather or climate information provided. Nevertheless, they seem satisfied with CIMIS services, as the satisfaction scores are relatively high. We also asked respondents to rank factors which hinder further use of CIMIS. Various answers were provided, given the results of initial surveys, and there was also room to specify other answers. Two main concerns exist, especially for users in agriculture: how reliable is the data and how to integrate it into existing systems and practices. Many growers and consultants in agriculture complement CIMIS with other data sources, such as soil moisture sensors, irrigation logs, and flow meters. Integrating information from multiple sources into decision making is a challenge faced by virtually all growers. 599 respondents, about a quarter of our survey, reported agriculture to be their primary business. Out of these, about half work on one farm, and the rest are consultants of sorts . 89% of respondents in agriculture report using CIMIS to some extent. Growers and consultants were asked to report their total acreage, selecting into pre-determined ranges. Summing these, we have 318,156 acres covered by growers, and almost 3 million acres covered by consultants. Many of the questions for growers and consultants were similar. One notable exception is regarding water use. The team decided not to ask growers how much water they use, fearing that growers would not want to share this information and would not finish the survey. However, consultants were asked how much water their clients use on average. This question was presented in the online survey as a slider bar, with a default at the lower bar , and an option to check a “Not applicable” box. This box was not checked very often. Instead, it seems like many consultants who did not want to answer this questions left the slider bar at the default value of 0.5 AF/acre. This is a very low value for irrigated crops, and we assume that all these responses are basically non-answers. Ignoring them, the average reported water use is 2.96 AF/acre per year . This seems like a very reasonable distribution for water use in irrigated crops. Indeed, the USDA’s most recent Farm and Ranch Irrigation Survey reports a total of 7,543,928 irrigated acres in California, with a total of 23,488,939 AF of water applied, and a resulting average water use of 3.11 AF/acre, only a minor deviation of the reported average. Given the responses from agricultural consultants, we seem to have captured a very large portion of the drip irrigated acres in California. As a baseline for valuation, we will use the total 2013 drip irrigated acreage from the USDA survey, 2.8 million acres. While some growers might use CIMIS with gravitational or sprinkler systems as well, our understanding of the qualitative and quantitative responses is that CIMIS is mostly important for drip.