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Food security is a key pillar of environmental security yet remains one of the world's greatest challenges. Its obverse, food insecurity, negatively impacts health and well-being, drives mass migration, and undermines national security and global sustainable development. Ensuring food security is a delicate balance of myriad concerns within the atmospheric and Earth sciences, agronomy and agriculture engineering, social sciences, economics, monitoring, and policymaking. A Food Security Presidential Session at the American Meteorological Society's (AMS) 2022 Annual Meeting brought together experts across disciplines to tackle issues at the nexus of weather, climate, and food security. The starkest takeaway was the realization that, despite its importance and clear roles for the atmospheric and climate sciences, food security has not been a focus for the AMS community. The aim of this paper is to build on the perspectives shared by this expert panel and to identify overlapping issues and key points of intersection between the food-security community and AMS. We examine 1) the interactions between weather, climate, and the food system and how they influence food security; 2) the time and spatial scales of food security decision support that match weather and climate phenomena; 3) the role of both providers and users of information as well as decision-makers in improving research to operations for food security; and 4) the opportunities for the AMS community to address food security. We conclude that, moving forward, the AMS community is well-positioned to scale up its engagement across the global food system to address existing scientific needs and technology gaps to improve global food security. SIGNIFICANCE STATEMENT: We examine how members of the AMS community can help ensure global food security, whether they are engaged in the physical and social sciences or the realms of policy and society. Inspired by the messages of panelists at a Presidential Forum on Food Security at the 2022 AMS Annual Meeting, we gather their perspectives and those of experts working in the various relevant fields and find that there are roles for everyone across the AMS—from providing forecasts of the hydrometeorological variables used in food security outlooks to converting data to knowledge and engaging with stakeholders and decision-makers. We make concrete suggestions to ensure the AMS and its members are fully engaged in feeding the world. [ABSTRACT FROM AUTHOR]

Accurate, timely, and accessible meteorological and soil moisture measurements are essential for a number of applications including weather forecasting, agricultural decision-making, and flood and drought prediction. Such data are becoming increasingly available globally, but the large number of networks and various data reporting formats often make utilization of such data difficult. The TexMesonet is a "network of networks" developed within the state of Texas to collect, process, and make public data collected from more than 1700 monitoring stations throughout the state. This paper describes the TexMesonet, with special attention paid to monitoring sites installed and managed by the Texas Water Development Board. It also provides a case study exemplifying how these data may be used and gives recommendations for future data applications. [ABSTRACT FROM AUTHOR]

Providing knowledge inputs to farmers is critical to reduce their vulnerability and enhance resilience against climate change. In developing countries such as India, where small holdings and rain-fed agriculture are predominant, knowledge inputs become even more critical. The India Meteorological Department has provided integrated agrometeorological advisory services (AAS) to farmers since 2008. In this paper, we estimate the scale of access to AAS and its impact on crop yields in 1000 households across 10 villages in two agroclimatic zones in India. We find evidence suggesting that access to AAS can have a significant impact on crop yields in the kharif (June–September) season, whereas other inputs are more important in the case of rabi (winter) crops. Specifically, the yields of pigeon pea, soybean, and pearl millet are higher by 233, 98, and 318 kg ha−1, respectively, for AAS beneficiaries. For the entire study area, this translates to a value addition of $9.66 million for these three crops in one season. Our results show that AAS can be an important contributor to meeting the developmental goals of enhancing food security in dry-land agriculture and building resilience against climate change. Significance Statement: In the era of climate change, with rapidly increasing weather and climatic variability, protecting the incomes of small farmers and ensuring they have the capacity to adapt and build resilience to the growing impacts of climate change is an urgent necessity. We have studied the impact of knowledge services such as the agrometeorological advisory services of the India Meteorological Department on crop yields for major crops in dry agroclimatic zones in India. The study shows that large public programs like the agrometeorological advisory services that bring science to people in meaningful ways can contribute significantly to meeting developmental goals and building resilience against climate change. [ABSTRACT FROM AUTHOR]

Exposure to weather extremes, such as heatwaves, can cause discomfort, harm, or death in grazing cattle in pastures. While the Australian Bureau of Meteorology issues sheep graziers alerts when there is an exposure risk to chill for livestock, there is no equivalent alert for heat stress for Australian cattle. Before any such alert system can be developed, a robust assessment and comparison of relevant cattle thermal stress indices is required. This study evaluates and compares the multiyear climatology of three cattle thermal heat stress indices across Australia in the warm season months (October–March). The same indices are then used to assess historical Australian heat events where cattle died from heat exposure. These events are based off official records and survey responses from northern Australian graziers. In the seven historical heat events studied, high relative humidity combined with low wind speeds, or high solar exposure combined with high surface temperatures, exacerbated the impact of heat stress on cattle. In the two historic events where multiple compounding weather factors combined (e.g., high humidity, low winds, and high solar exposure), the cattle mortality levels were significantly high. These events were characterized by rainy conditions followed by a rapid warming, meaning cattle were likely unable to acclimatize to such dramatic temperature changes. This study highlights the need for using more than one thermal stress index when verifying cattle heat stress events and, importantly, calls for further research on standardizing the risk classifications of these thermal indices for cattle in Australia's variable climate. Significance Statement: Cattle across Australia's northern tropical and semiarid regions often experience extreme hot and humid conditions in the summer months, which increases the risk of heat stress. This is the first study of its kind to evaluate observations of cattle heat stress across Australia using indices that describe the combined effects of solar exposure, wind speed, relative humidity, and surface temperatures. These cattle heat stress indices can be used to evaluate historical cattle mortality events in feedlots and in grazed pastures. This study lays the groundwork for the development of Australian-wide cattle heat stress forecast products on the 7-day to multiweek time scales. [ABSTRACT FROM AUTHOR]

Sustainability of rain-fed agriculture in semiarid regions is being threatened by climate variability and change. Weather and climate information (WCI) can be used to reduce the effects of this threat on agricultural production. WCI may be available, but is it readily accessible and communicated/disseminated efficiently to intended end users? Are stakeholders able to interpret the information to correctly inform decision-making? To answer these questions, in view of intermediate stakeholders (service providers to farmers), a study was carried out in two districts of the Midlands Province of Zimbabwe to identify the type and sources of WCI received by these stakeholders as well as constraints and opportunities to access, interpretation, and use of WCI. The study sample was drawn from the Midlands Provincial Drought Relief Committee, a link between the sources of WCI and the smallholder farmers. A questionnaire pretested for clarity and checked for internal consistency of themes using the standardized Cronbach's alpha was used to collect data. Descriptive statistics were generated using SPSS (version 20.0). Findings were that WCI was sometimes not readily available or was received late. Approximately 36% of the intermediate stakeholders (service providers) passed on WCI to farmers in its original form, from the main source the Meteorological Services Department. It was also unfortunate to discover that 36% of the respondents had challenges interpreting WCI. Impediments to the use of WCI by farmers included scientific information not aligning with indigenous information, which is better understood by farmers, and lack of trust in WCI. It is imperative to improve access to WCI and to train stakeholders on interpretation and dissemination of WCI. Significance Statement: Weather and climate information—if accurate, accessible, provided in a timely manner, and well understood—can be helpful in the farm decision-making process. Its usefulness is becoming more important with increased climatic variability and change. This paper highlights the challenges and opportunities for service providers in communicating and disseminating WCI. We believe that findings from the study will give direction to efficient utilization of the information by the various end users, for which smallholder farmers are the majority in most developing countries. [ABSTRACT FROM AUTHOR]

The interaction between climate change, agriculture, and financial markets is a topic that has been researched relatively little thus far. This paper intends to extend the literature by empirically testing the relationships between droughts and farms' financing choices (measured in terms of real debt and equity) in New Zealand. Using microeconomic farm-level financial records available from the tax authorities, we quantify how past droughts (measured by the New Zealand pasture growth index) impact farms' financing choices. We show a statistically significant positive impact of droughts on short-term and long-term debts, equity for dairy farms, and short-term debt for sheep and beef farms. [ABSTRACT FROM AUTHOR]

Climate change has negatively affected agricultural productivity in Indonesia. This study conducted a bibliometric analysis of the literature on soil salinity caused by climate change, discussed the impact of soil salinity on Indonesian agriculture, examined various strategies for adaptation to salinity, and delivered some ideas for future research. An analysis of 39 identified Scopus articles related to farmers' vulnerability, adaptation, and practices was carried out. This study was performed in November 2022 and employed Bibliometrix R package and VOSviewer software. Findings show that salinity has left Indonesia's agriculture vulnerable to reduced food production, especially for small-scale farmers losing crop yields and land. Various adaptation measures have been initiated, such as restoring soil fertility and using saline-resistant varieties. Irrigation facilities improvements have also been carried out to reduce the risks of soil salinity expansion. Farmers also try social action measures, such as selling assets, borrowing money for daily needs, and even changing jobs. However, for farmers to survive and sustain their businesses, any such measures need to produce satisfactory results. A review of the existing literature reveals a lack of soil salinity studies in Indonesia, which simultaneously points to research gaps not only on the issue of the impact of salinity on income and the vulnerability of small farmers but also on the development of adaptation strategies to address salinity due to climate change. [ABSTRACT FROM AUTHOR]

Water scarcity threatens agriculture in California. During the last two decades, historically severe droughts have led to severe water shortages. Under projected changes in climate, droughts of greater severity and duration will exacerbate this situation. California produces 80% of the world's almonds, which require consistent water supplies for irrigation. Almonds are the most commonly grown crop in California, covering nearly 1.4 million acres over about 8,000 farms. In response to these challenges, almond growers are considering a myriad of management strategies to save water and mitigate climate change. The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX) aims to identify water and orchard management opportunities to maximize water use efficiency and carbon sequestration in almonds and other woody perennial tree crops. The project combines satellite, uncrewed aerial vehicles, and proximal sensing technologies to retrieve key variables used to model surface fluxes and biophysical properties. We aim to advance our understanding of water management and cultural practices on water-carbon relationships in tree-perennial agroecosystems. Through new methods, such as evapotranspiration-based irrigation scheduling, even a modest 10% decrease in almond orchard irrigation across the state equates to about a third of the water in Lake Oroville, California's second-largest reservoir, at average levels. From a carbon perspective, almond orchards could sequester 8% of the state's current greenhouse gas emissions by transitioning toward climate-smart practices. As such, the almond industry is uniquely positioned to curb water use and contribute to climate change mitigation while maintaining economic viability of almond production. An overview of initial results related to evapotranspiration observational and modeling uncertainty and carbon sequestration potential are presented in this article. [ABSTRACT FROM AUTHOR]

Phenological indicators (PI) are used to study changes to animal and plant behavior in response to seasonal cycles, and they can be useful to quantify the potential impacts of climate change on ecosystems. Here, multiple global climate models and emission scenarios are used to drive dynamically downscaled simulations using the WRF Model over the contiguous United States (CONUS). The wintertime dormancy of plants [chilling units (CU)], timing of spring onset [extended spring indices (SI)], and frequency of proceeding false springs are calculated from regional climate simulations covering historical (1995-2005) and future periods (2025-2100). Southern parts of the CONUS show projected CU decreases (inhibiting some plants from flowering or fruiting), while the northern CONUS experiences an increase (possibly causing plants to break dormancy too early, becoming vulnerable to disease or freezing). Spring advancement (earlier SI dates) is projected, with decadal trends ranging from approximately 1-4 days per decade over the CONUS, comparable to or exceeding those found in observational studies. Projected changes in risk of false spring (hard freezes following spring onset) vary across members of the ensemble and regions of the CONUS, but generally western parts of the CONUS are projected to experience increased risk of false springs. These projected changes to PI connote significant effects on cycles of plants, animals, and ecosystems, highlighting the importance of examining temperature changes during transitional seasons. SIGNIFICANCE STATEMENT: This study examines how phenological indicators, which track the life cycles of plants and animals, could change from 2025 to 2100 as simulated in a regional climate model over the contiguous United States. Chilling units quantify the presence of cooler weather that can benefit plants prior to their growing season. They are projected to decrease in the southern United States, possibly inhibiting agricultural production. Spring onset is projected to occur earlier in the year, advancing by 1-4 days on average over each future decade. Risk of false springs (damaging hard freezes after spring onset) increases in the western United States. Our findings highlight the need to understand effects of climate change during transitional seasons, which can impact agriculture and ecosystems. [ABSTRACT FROM AUTHOR]

Since 2017, the Northern Australia Climate Program (NACP) has assisted the pastoral grazing industry to better manage drought risk and climate variability. The NACP funding is sourced from the beef cattle industry, government, and academia, representing the program's broad range of aims and target beneficiaries. The program funds scientists in the United Kingdom and Australia, in addition to extension advisers called "Climate Mates" across a region that supports 15 million head of cattle. Many Climate Mates are employed in the cattle sector and have existing relationships in their communities and capacity to meaningfully engage with the program's intended beneficiaries—red meat producers. The NACP is a prime example of a successful end-to-end program, integrating climate model improvements (research) with tailored forecast products (development), through to direct stakeholder engagement (extension), on-ground application of technologies (adoption), and improvement in industry and community resilience (impact). The climate information needs of stakeholders also feed back to the research and development components, ensuring the scientific research directly addresses end-user requirements. For any scientific research program, ensuring that research output has measurable real-world impact represents a key challenge. This is more difficult in cases where the scientific research is several steps away from the customer's needs. This paper gives an overview of the NACP and research highlights, discussing how the end-to-end framework could be adapted and applied in other regions and industries. It seeks to provide a roadmap for other groups to follow to produce more targeted research with identifiable real-world benefits. [ABSTRACT FROM AUTHOR]

A simple—yet powerful—indicator for monitoring agricultural drought is the water requirement satisfaction index (WRSI). In data-sparse, food-insecure areas, the WRSI is used to guide billions of dollars of aid every year. The WRSI uses precipitation (PPT) and reference evapotranspiration (RefET) data to estimate water availability relative to water demand experienced over the course of a growing season. If the season is in progress, to-date conditions can be combined with climatological averages to provide insight into potential end-of-season (EOS) crop performance. However, if the average is misrepresented, these forecasts can hinder early warning and delay precious humanitarian aid. While many agencies use arithmetic average climatologies as proxies for "average conditions," little published research evaluates their effectiveness in crop-water balance models. Here, we use WRSI hindcasts of three African regions' growing seasons, from 1981 to 2019, to assess the adequacy of the arithmetic mean climatological forecast—the Extended WRSI. We find that the Extended WRSI is positively biased, overestimating the actual EOS WRSI by 2%–23% in East, West, and southern Africa. The presented alternative combines to-date conditions with data from previous seasons to produce a series of historically realistic conclusions to the current season. The mean of these scenarios is the WRSI Outlook. In comparison with the Extended WRSI, which creates a single forecast scenario using average inputs that are not covarying, the WRSI Outlook employs an ensemble of scenarios, which more adequately capture the historical distribution of distribution of rainfall events along with the covariability between climate variables. More specifically, the impact of dry spells in individual years is included in the WRSI Outlook in a way that is smoothed over in the Extended WRSI. We find that the WRSI Outlook has a near-zero bias score and generally has a lower RMSE. In total, this paper highlights the inadequacies of the arithmetic mean climatological forecast and presents a less biased and more accurate scenario-based approach. To this end, the WRSI Outlook can improve our ability to identify agricultural drought and the concomitant need for humanitarian aid. [ABSTRACT FROM AUTHOR]

Traditional ways of reading nature’s clues to figure out impending weather are widely practiced in many rural societies in the world. They have been, however, often discounted by a western science-based meteorological forecasting system, although they are important sociocultural tools for mitigating climatic risks. This paper concerns two thematic issues: traditional knowledge about reading nature’s clues to figure out impending weather; and the transformation of that knowledge in the changing context of livelihood, the intervention of modern education, and use of modern weather forecasting technology. This study was carried out at Kirtipur of the Kathmandu Valley, Nepal, between 2011 and 2021. Information was collected through key informant interviews, observation, and informal discussion and survey. The findings reveal that the traditional weather forecasting system is closely intertwined with climatic phenomena, traditional agriculture practices, the local landscape, myths, and beliefs. The recognition of farmers’ knowledge on weather forecasting should be a resource of a great potential value. However, rapid expansion of the market economy, access to modern technology, affordability, access to modern education, and anthropogenic climate change have gradually detached people from their farmlands, traditional livelihoods, and occupations. All of this seems to have weakened social interaction between generations as well as their attachment to nature. Last, we conclude that the production and consumption of weather forecasting knowledge need local and scientific communities to work together to reduce knowledge gaps. [ABSTRACT FROM AUTHOR]

The catastrophic derecho that occurred on 10 August 2020 across the midwestern United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth-orbit passive-microwave imager and GOES-16 satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and normalized difference vegetation index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies. [ABSTRACT FROM AUTHOR]

The historical rise of irrigation has profoundly mitigated the effect of drought on agriculture in many parts of the United States. While irrigation directly alters soil moisture, meteorological drought indices ignore the effects of irrigation, since they are often based on simple water balance models that neglect the irrigation input. Reanalyses also largely neglect irrigation. Other approaches estimate the evaporative fraction (EF), which is correlated with soil moisture under water-limited conditions typical of droughts, with lower values corresponding to drier soils. However, those approaches require satellite observations of land surface temperature, meaning they cannot be used to study droughts prior to the satellite era. Here, we use a recent theory of land-atmosphere coupling--surface flux equilibrium (SFE) theory--to estimate EF from readily available observations of near-surface air temperature and specific humidity with long historical records. In contrast to EF estimated from a reanalysis that largely neglects irrigation, the SFE-predicted EF is greater at irrigated sites than at nonirrigated sites during droughts, and its historical trends are typically consistent with the spatial distribution of irrigation growth. Two sites at which SFE-predicted EF unexpectedly rises in the absence of changes in irrigation can be explained by increased flooding due to human interventions unrelated to irrigation (river engineering and the expansion of fish hatcheries). This work introduces a new method for quantifying agricultural drought prior to the satellite era. It can be used to provide insight into the role of irrigation in mitigating drought in the United States over the twentieth century. [ABSTRACT FROM AUTHOR]

Weather index insurance (WII) has long been advertised as a viable alternative to crop yield insurance. WII products were first developed to assist climate-vulnerable farmers from developing countries where establishing a well-structured crop insurance market is expressively difficult due to the poor transport infrastructure and the prevalence of sparsely distributed small-scale farms. In Brazil, the semiarid region stands out as the one that concentrates the ideal conditions for the implementation of a WII product since it houses thousands of climate-vulnerable farmers. With this in mind, we designed and priced a WII product for farmers from the semiarid region of Brazil and posteriorly investigated its risk efficiency. To do so, we first investigated crop yield responses to aridity, enabling the selection of locations for which the WII product was posteriorly assessed. Second, we grouped selected locations into specific contracts according to geographical proximity and evaluated each of these contracts to attest the risk efficiency of the proposed WII product using the method of stochastic efficiency with respect to a function (SERF), which identifies utility efficient alternatives for a range of risk attitudes. Our results show that the WII product may be effective in protecting farmers from adverse variations in production revenue, possibly being attractive for utility-maximizer farmers that are sufficiently risk averse. [ABSTRACT FROM AUTHOR]

Groundwater salinity, caused by overextraction and aggravated by climate change, negatively affects crop productivity and threatens global food security. Poor farmers are vulnerable because of low adaptive capacity. A better understanding of their perceptions and adaptation is important to inform policies for successful adaptation. This paper represents an important study by exploring the same in Mewat, a salinity-affected socioeconomically disadvantaged district of northern India. The study uses a mixed-method approach with both secondary data and a primary survey of 250 farmers. A large number of farmers perceived negative impacts on water, crop, income, and assets, and they adapt in various ways such as water, crop, and land management; livelihood diversification; and a shift toward surface water irrigation. Perceived impacts differed between richer and poorer farmers, whereas adaptation measures varied across the educational, social, and economic backgrounds of farmers. Lack of awareness, education, skill development, and livelihood opportunities are found to be hindrances, whereas institutional and infrastructural support are facilitators of adaptation. In comparing the findings with global experiences, we argued that developed countries intervene more in the policy level and infrastructure, whereas in developing countries, adaptation strategies are local, context specific, and low cost. The insights from our study will be useful for intervention in Mewat and similar areas across the developing world. We further argue that farmers make adaptation decisions on the basis of perceived impacts and cost--benefit analysis. Therefore, future research work on quantifying the negative impacts and cost--benefit analysis of various adaptation measures will be useful to ensure successful adaptation in the region and beyond. [ABSTRACT FROM AUTHOR]

The Maritime Continent (MC), located in the heart of the Indo-Pacific warm pool, plays an important role in the global climate. However, the future MC climate is largely unknown, in particular the ENSO–rainfall teleconnection. ENSO induces a zonal dipole pattern of rainfall variability across the Indo-Pacific Ocean, that is, positive variability in the tropical Pacific and negative variability toward the MC. Here, new CMIP6 models robustly project that, for both land and sea rainfall, the negative ENSO teleconnection over the MC (drier during El Niño and wetter during La Niña) could intensify significantly under the Shared Socioeconomic Pathway 5–8.5 (SSP585) warming scenario. A strengthened teleconnection may cause enhanced droughts and flooding, leading to agricultural impacts and altering rainfall predictability over the region. Models also project that both the Indo-Pacific rainfall center and the zero crossing of dipole-like rainfall variability shift eastward; these adjustments are more notable during boreal summer than during winter. All these projections are robustly supported by the model agreement and scale up with the warming trend. [ABSTRACT FROM AUTHOR]

The impact of climate change on subsistence agriculture is a major concern in the developing world. The vulnerability of the coastal regions to climate change has been highlighted, in particular. The present study assessed the impact of climate change on subsistence rice farming on the eastern Indian coast using an integrated approach of statistical trend analysis by the Mann–Kendall test and Sen's slope estimation of climate data and remote sensing–based land-cover analyses using the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and land surface temperature (LST) complemented by a questionnaire-based perception survey among the farming community. There has been a noticeable change in both ambient temperature and LST in the region. The delayed arrival of the monsoon critically impacts the cropping calendar. The crop harvest season has shifted farther into a time of the year that is prone to weather extremes. Analyses of NDVI and NDWI also indicate a shift in the cropping calendar. Over the years, there was an increasing degree of negative correlation between LST and NDVI in November, which indicates increasing water stress for crops in that time juncture. This may further cause crop sterility and yield loss. The study also reveals large-scale conversion of paddy-growing agricultural land into prawn aquaculture ponds. Farmers attributed such land-use change to cultivation stress caused by the delayed monsoon and consequent crop loss from weather extremes and changes in crop agronomic conditions. Farmers also report increased pest attacks and attribute that to an increasing temperature regime. [ABSTRACT FROM AUTHOR]

Drought monitoring is critical for managing agriculture and water resources and for triggering state emergency response plans and hazard mitigation activities. Fixed thresholds serve as guidelines for the U.S. Drought Monitor (USDM). However, fixed drought thresholds (i.e., using the same threshold in all seasons and climate regions) may not properly reflect local conditions and impacts. Therefore, this study develops impacts-based drought thresholds that are appropriate for drought monitoring in Ohio. We examined four drought indices that are currently used by the state of Ohio: standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer's Z index, and Palmer hydrological drought index (PHDI). Streamflow and corn yield are used as indicators of hydrological and agricultural drought impacts, respectively. Our results show that fixed thresholds tend to indicate milder drought conditions in Ohio, while the proposed impacts-based drought thresholds are more sensitive to exceptional drought (D4) conditions. The area percentage of D4 based on impacts-based drought thresholds is more strongly correlated with corn yield and streamflow. This study provides a methodology for developing local impacts-based drought thresholds that can be applied to other regions where long-term drought impact records exist to provide regionally representative depictions of conditions and improve drought monitoring. [ABSTRACT FROM AUTHOR]

This study describes flash drought (FD) inferred from the evaporative stress index (ESI) over Australia and its relationship to vegetation. During 1975–2020, FD occurrence ranges from less than 1 per decade in the central arid regions to 10 per decade toward the coasts. Although FD can occur in any season, its occurrence is more frequent in summer in the north, winter in the southern interior and southwest, and across a range of months in the far southeast and Tasmania. With a view toward real-time monitoring, FD "declaration" is defined as the date when the ESI declines to at least −1, i.e., drought conditions, after at least 2 weeks of rapid decline. Composite analysis shows that evaporative demand begins to increase about 5–6 weeks before declaration with an increase in solar radiation, while evapotranspiration initially increases with evaporative demand but then decreases in response to the soil moisture depletion. Solar radiation increases simultaneously with precipitation deficit, both reaching their peak around declaration. FD intensity peaks with soil moisture depletion, 2–3 weeks after declaration. The composite wind speed only shows a modest increase around declaration. The composite FD ends 4 weeks after rapid decreases in solar radiation and increases in precipitation. Satellite-derived vegetation health composites show pronounced decline in the nonforested regions, peaking about 4–8 weeks after FD declaration, followed by a recovery period lasting about 12 weeks after flash drought ends. The forest-dominated regions, however, are little impacted. Modeled pasture growth data show reduced values for up to 3 months after the declaration month covering the main agricultural areas of Australia. Significance Statement: Flash drought describes a fast intensification or rapid development of drought conditions with potential severe impacts on agriculture and ecosystems. This study describes the climatology and typical evolution of flash drought over Australia for the period 1975–2020. An objective definition of flash drought, using high-resolution observational-based datasets, is proposed and its spatiotemporal variability is provided, as well as its relationship with vegetation health and pasture growth. This constitutes a guideline for understanding flash drought in Australia and its impacts on vegetation. [ABSTRACT FROM AUTHOR]

Agriculture is a highly weather-dependent activity, and climatic conditions impact both directly crop growth and indirectly diseases and pest developments causing yield losses. Weather forecasts are now a major component of various decision-support systems that assist farmers to optimize the positioning of crop protection treatments. However, properly accounting for weather uncertainty in these systems still remains a challenge. In this paper, three global and regional ensemble prediction systems (EPSs), covering different spatiotemporal scales, are coupled to a temperature-driven developmental model for grapevine moths in order to provide probabilistic forecasts of treatment dates. It is first shown that a parametric postprocessing of the EPSs significantly improves the prediction of treatment dates. Anticipating the need for phytosanitary treatments also requires seamless weather forecasts from the next hour to subseasonal time scales. An approach is presented to design seamless ensemble forecasts from the combination of the three EPSs used. The proposed method is able to leverage the increased performance of high-resolution EPS at short ranges, while ensuring a smooth transition toward larger-scale EPSs for longer ranges. The added value of this seamless integration on agronomic predictions is, however, difficult to assess with the current experimental setup. Additional simulations over a larger number of locations and years may be required. [ABSTRACT FROM AUTHOR]

The southern Great Plains (SGP) is defined by hydrometeorological swings between dry and wet extremes. These swings exacerbate the climatological gradients of moisture (from east to west) and temperature (from south to north), which can impact the agricultural production of the region. Thus, it is key to understand extremes to sustainably maintain agricultural success in the region. This study investigates the wet extremes, or extreme precipitation events, that have become more prominent in the last two decades. Data from 108 U.S. Historical Climatology Network stations were analyzed for the 1950-2020 period to detect changes in the frequency and magnitude of extreme precipitation events. Results show that changes in the magnitude of extreme precipitation are isolated and scattered across the SGP, with only the winter season showing regional shifts in extreme precipitation magnitude. Changes in the frequency of extreme precipitation events were noted across the entire SGP, although the changes in frequency are more notable in the eastern SGP than in the western SGP. Analysis shows that the increased number of events detected is driven more, but not exclusively, by the increasing spatial extent of individual extreme precipitation events than by an increased number of events. Overall, these results depict the changing nature of extreme precipitation within the SGP and differences in extreme precipitation between the eastern and western SGP. [ABSTRACT FROM AUTHOR]

Agricultural stakeholders can effectively manage the risks and opportunities arising from climate change and variability by enhancing climate services in agriculture. Key to understanding and addressing the climate challenge is the provision and the use of climate information to aid decision-makers and policy-makers. Climate services are now integral to the United Nations Framework Convention on Climate Change, the Intergovernmental Panel on Climate Change's Assessment Reports, governments' national adaptation plans, funding bodies, and a growing number of sectors and industries worldwide. The article provides our personal perspective, experience, and views on the important and timely issue of managing better the risks and opportunities to the agriculture sector and community that are arising from changes in climate. We describe a framework to help drive action to tackle the climate challenge comprising enhanced knowledge and information products, efficient information delivery and use, and assured policy and institutional support, in an iterative loop. [ABSTRACT FROM AUTHOR]

The Congo Basin is severely understudied compared to other tropical regions; this is partly due to the lack of meteorological stations and the ubiquitous cloudiness hampering the use of remote sensing products. Clustering of small-scale agricultural deforestation events within the basin may result in deforestation on scales that are atmospherically important. This study uses 500-m MODIS data and the Global Forest Change dataset (GFC) to detect deforestation at a monthly and subkilometer scale and to quantify how deforestation impacts vegetation proxies (VPs) within the basin, the time scales over which these changes persist, and how they are affected by the deforestation driver. Missing MODIS data meant that a new method, based on two-date image differencing, was developed to detect deforestation on a monthly scale. Evaluation against the yearly GFC data shows that the highest detection rate was 79% for clearing sizes larger than 500 m2. Recovery to predeforestation levels occurred faster than expected; analysis of postdeforestation evolution of the VPs found 66% of locations recovered within a year. Separation by land-cover type also showed unexpected regrowth, as over 50% of rural complex and plantation land recovered within a year. The fallow period in the study region was typically short; by the sixth year after the initial deforestation event, ∼88% of the locations underwent a further considerable drop. These results show the importance of fine spatial and temporal information to assess Congo Basin deforestation and highlight the large differences in the impacts of land-use change compared to other rain forests. [ABSTRACT FROM AUTHOR]

Strategies that demonstrate renewed potential to enhance both social and ecological systems are crucial in today's era of rapid urbanization. However, the approaches used to understand the impacts of such strategies sometimes favor social over environmental theory, or the opposite, but do not always consider both equally. Our study addresses this disconnect by exploring the role of urban agriculture (UA) as an alleviation and land management strategy in Mexico City (MC), Mexico. Our integrated design combined the ecosystem services framework, which was primarily used to assess material and nonmaterial benefits MC residents obtain from UA spaces and its associated vegetation, and the livelihoods framework, which was used to evaluate the relationship between UA and societal impacts. We used a mixed-method approach to quantify the amount of food produced, assess crop diversity, assess six distinct ecological processes linked to UA, identify cultural benefits, and conduct an evaluation of contributions to livelihood capitals. Our study documented the role of UA in supporting ecological processes, connecting humans to nature, and providing a supplemental source of income. However, a multitude of unintended outcomes are identified, such as trade-offs between different ecological processes, constraints in promoting formal education beyond agroecological knowledge, and an inability to fully elevate families out of poverty. Our integrated approach demonstrated how the ecosystem services and livelihoods frameworks can be used simultaneously to provide thorough assessments of socioecological systems, identifying outcomes that could go unnoticed without an interdisciplinary lens. [ABSTRACT FROM AUTHOR]

Climate risk financing programs in agriculture have caught the attention of researchers and policy makers over the last decade. Weather index insurance has emerged as a promising market-based risk financing mechanism. However, to develop a suitable weather index insurance mechanism it is essential to incorporate the distribution of underlying weather and climate risks to a specific event model that can minimize intraseasonal basis risk. In this paper we investigate the erratic nature of rainfall patterns in Kenya using Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) rainfall data from 1983 to 2017. We find that the patterns of rainfall are fractional, both erratic and persistent, which is consistent with the Noah and Joseph effects that are well known in mathematics. The erratic nature of rainfall emerges from the breakdown of the convergence to a normal distribution. Instead we find that the distribution about the average is approximately lognormal, with an almost 50% higher chance of deficit rainfall below the mean than adequate rainfall above the mean. We find that the rainfall patterns obey the Hurst law and that the measured Hurst coefficients for seasonal rainfall pattern across all years range from a low of 0.137 to a high above 0.685. To incorporate the erratic and persistent nature of seasonal rainfall, we develop a new approach to weather index insurance based upon the accumulated rainfall in any 21-day period falling below 60% of the long-term average for that same 21-day period. We argue that this approach is more satisfactory to matching drought conditions within and between various phenological stages of growth. [ABSTRACT FROM AUTHOR]

As impacted by climate change and further global warming, drought turns out to be the most frequent meteorological extreme event worldwide, which severely affects agriculture, ecosystem, water management, and even human survival. In this study, the global pattern and development trends and directions on drought monitoring were presented based on Web of Science database by conducting a bibliometric analysis from 1983 to 2020. The following conclusions were drawn. 1) The United States and China were found as the most productive and influential nations, accounting for 24.63% and 14.30% in publication outputs and taking up 5,023 and 2,040 in local citations, respectively. 2) Chinese Academy of Science was reported as the core institution with 5.73% publication outputs and 829 local citations. 3) Remote Sensing of Environment and Remote Sensing were found as the most influential journals and the most productive journals with 1,045 local citations and 210 publication outputs, respectively. 4) Agricultural drought profoundly affecting food security was found as the most concerning drought type in the world. The drought monitoring research mainly focus on the research and development of drought index, the response of terrestrial ecosystems to drought, and the trends and dynamics of drought in context of climate change. This study explored key findings, contradictions, and limitations of drought monitoring studies were summarized and explored. In addition, the development trend and research direction of drought monitoring research in the future were also explored. [ABSTRACT FROM AUTHOR]

Billed as the creation and provision of timely, tailored information for decision making at all levels of society, climate services have garnered a great deal of attention in recent years. Despite this growing attention, strategies to design, diagnose, and evaluate climate services remain relatively ad hoc -- and while a general sense of what constitutes "good practice" in climate service provision is developing in some areas, and with respect to certain aspects of service provision, a great deal about the effective implementation of such service remains unknown. This paper reviews a sample of more than 100 climate service activities as a means to generate a snapshot of the state of the field in 2012. We find that a "typical climate service" at this time was provided by a national meteorological service operating on a national scale to provide seasonal climate information to agricultural decision makers online. Our analysis shows that the field of climate services was still emerging -- marked by contested definitions, an emphasis on capacity development, uneven progress toward co-production, uncertain funding streams, and a lack of evaluation activities -- and stands as a signpost against which the development of the field can be measured. The paper also reflects on the relative contribution of this sort of sampling activity in informing "good practice" and offers suggestions for how both sampling and case study efforts can be better designed to increase the potential for learning. The paper concludes with some observations on the relative contribution that broad- based analyses can play in informing this emerging field. [ABSTRACT FROM AUTHOR]

The occurrence and properties of hail smaller than severe thresholds (diameter, 25 mm) are poorly understood. Prior climatological hail studies have predominantly focused on large or severe hail (diameter at least 25 mm or 1 in.). Through use of data from the Meteorological Phenomena Identification Near the Ground project, Storm Data, and the Community Collaborative Rain, Hail and Snow Network the occurrence and characteristics of both severe and sub-severe hail are explored. Spatial distributions of days with the different classes of hail are developed on an annual and seasonal basis for the period 2013-20. Annually, there are several hail-day maxima that do not follow the maxima of severe hail: the peak is broadly centered over Oklahoma (about 28 days yr21). A secondary maximum exists over the Colorado Front Range (about 26 days yr21), a third extends across northern Indiana from the southern tip of Lake Michigan (about 24 days yr21 with hail), and a fourth area is centered over the corners of southwest North Carolina, northwest South Carolina, and the northeast tip of Georgia. Each of these maxima in hail days are driven by sub-severe hail. While similar patterns of severe hail have been previously documented, this is the first clear documentation of sub-severe hail patterns since the early 1990s. Analysis of the hail size distribution suggests that to capture the overall hail risk, each of the datasets provide a complimentary data source. [ABSTRACT FROM AUTHOR]

This study used corn insurance data as a proxy for agricultural loss to better inform producers and decision-makers about resilience and mitigation. Building on previous research examining crop losses based on weather and climate perils, updates to the peril climatology, identification of peril hotspots, and the quantification of annual trends using inflation-adjusted indemnities for corn were performed over the period 1989–2020. Normalization techniques in loss cost and acreage loss at county-level spatial resolution were also calculated. Indemnity data showed drought and excess moisture as the two costliest and most frequent perils for corn in the United States, although changes in the socioeconomic landscape and frequency of extreme weather events in the recent decade have led to significant increases in corn indemnities for drought, heat, excess moisture, flood, hail, excess wind, and cold wet weather. Normalized losses also displayed significant trends but were dependent on the cause of loss and amount of spatial aggregation. Perhaps most notable were the documented robust increases in corn losses associated with excess moisture, especially considering future projections for increased mid and end-of-century extreme precipitation. Subtle decreasing trends in drought, hail, freeze/frost, and flood loss cost over the study period indicates hedging taking place to protect against these perils, especially in corn acreage outside the Corn Belt in high-risk production zones. The use of crop insurance as a proxy for agricultural loss highlights the importance for quantifying spatiotemporal trends by informing targeted adaption to certain hazards and operational management decisions. Significance Statement: This study quantified the climatology and trends of weather and climate perils affecting corn in the United States. Robust increases in losses were noted with perils causing excess moisture, which is cause for further concern given projected increases in extreme rainfall under a warming climate. [ABSTRACT FROM AUTHOR]

What: Around 270 participants from national agriculture, hydrological, and meteorological services; nongovernmental organizations; the private sector; and research institutions gathered to take stock of progress since the first Climate Services Week; to explore and highlight innovations in climate services that support transformative agri-food systems; to promote knowledge exchange, collaboration, and partnerships; and to develop a collective vision for agriculture climate services in the Asia-Pacific region. When: 30 November-3 December and 7 December 2021 Where: Online. [ABSTRACT FROM AUTHOR]

People’s observations of climate change and its impacts, mediated by cultures and capacities, shape adaptive responses. Adaptation is critical in regions of rainfed smallholder agriculture where changing rainfall patterns have disproportionate impacts on livelihoods, yet scientific climate data to inform responses are often sparse. Despite calls for better integration of local knowledge into adaptation frameworks, there is a lack of empirical evidence linking both smallholder climate observations and scientific data to on-farm outcomes. We combine smallholder observations of past seasonal rainfall timing with satellite-based rainfall estimates in Uganda to explore whether farmers’ ability to track climate patterns is associated with higher crop yields. We show that high-fidelity tracking, or alignment of farmer recall with recent rainfall patterns, predicts higher yields in the present year, suggesting that farmers may translate their cumulative record of environmental knowledge into productive on-farm decisions, such as crop selection and timing of planting. However, tracking of less-recent rainfall (i.e., 1–2 decades in the past) does not predict higher yields in the present, while climate data indicate significant trends over this period toward warmer and wetter seasons. Our findings demonstrate the value of smallholder knowledge systems in filling information gaps in climate science while suggesting ways to improve adaptive capacity to climate change. [ABSTRACT FROM AUTHOR]

Agricultural production in the U.S. Midwest is vulnerable to drought, and specialty crop producers are an underserved audience for monitoring information and decision-support tools. We investigate the decision-making needs of apple, grape, and cranberry growers using a participatory process to develop crop-specific decision calendars. The process highlights growers’ decisions and information needs during the winter dormant, growing, harvest, and postharvest seasons. Apple, grape, and cranberry growers tend to be concerned with the effects of short-term drought on current crop quality and quantity, while also considering the long-term drought effect on the health of perennial plants and future years’ production. We find gaps in drought information particularly for tactical and strategic decision-making. We describe the use of decision calendars to identify points of entry for existing drought monitoring resources and tools, and to highlight where additional research and tool development is needed. SIGNIFICANCE STATEMENT: While drought causes agricultural losses in the U.S. Midwest, more is known about the impacts and decision-support needs of commodity row crop growers in the region than those of perennial specialty crop growers. We find opportunities for climate information providers to tailor drought information delivery to perennial fruit growers according to the season, the parameters that are relevant to their decisions, and the timeframe of information needed for operational, tactical, and strategic decision-making. [ABSTRACT FROM AUTHOR]

Producer organizations representing Canada's farm and livestock sectors are powerful change agents and advocates for their industries, particularly during challenging times such as climate- or weather-related hardships. Such organizations have a complex role: engaging with policy-makers, as well as their memberships and the public, to pursue the interests of their specific communities. This paper includes an examination of how farm producer organizations communicate about climate and weather to these various audiences, and the specific needs and recommendations they advance. Of particular interest are commodities related to pasture-based grazing, which is underrepresented in the climate adaptation literature. A collection of 95 publicly available documents is analyzed, representing a snapshot of climate- and weather-related public and policy engagement of Canadian and Albertan farm and livestock producer organizations from 2010 to 2015. Qualitative coding by scale, commodity, and audience revealed three significant patterns within this exploratory study. First, while national "umbrella" organizations speak climate to government, Alberta-based livestock/forage organizations speak to their members with a focus on weather. Second, while the two national umbrella organizations examined are politically divergent, they appear to be united on the topic of climate change. Third, common ground was also found between climate and weather discourses around on-farm management, specifically rotational grazing. These three patterns reveal a disjointed dialogue within the Canadian farm and livestock sectors on topics of climate adaptation and mitigation, as well as opportunities for future cooperation, and the need for further research on farm organization beliefs and their capacity to create/manage climate knowledge. [ABSTRACT FROM AUTHOR]

Weather derivatives are considered a promising agricultural risk management tool. Station-based meteorological indices typically provide the data underlying these instruments. However, the main shortcoming of these weather derivatives is an imperfect correlation between the weather index and the yield of the insured crop, called basis risk. This paper considers three available remotely sensed vegetation health (VH) indices, namely, the vegetation condition index (VCI), the temperature condition index (TCI), and the vegetation health index (VHI), as indices for weather derivatives in a German case study. We investigated the correlation and period of highest correlation with winter wheat yield. Moreover, we analyzed whether the use of remotely sensed VH indices for weather derivatives can reduce basis risk and thus improve the performance of weather derivatives. The two commonly used meteorological indices, precipitation and temperature sums, were employed as benchmarks. Quantile regression and index value simulation were used for the design and pricing of the weather derivatives. The analysis for the selected farms and corresponding counties in northeastern Germany revealed that, on average, the VHI resulted in the highest correlation with winter wheat yield, and VHI-based weather derivatives were also superior in terms of the hedging effectiveness. The total periods of the highest correlations ranged from the beginning of April to the end of July. VHI- and VCI-based weather derivatives led to statistically significant reductions of basis risk, compared to the benchmarks. Our results indicate that the VHI-based weather derivatives can be useful alternatives to meteorological indices, especially in regions with sparser weather station networks. [ABSTRACT FROM AUTHOR]

This paper explores the link between the anomalous warming hole in the southeastern United States and a major land-use/land-cover (LULC) change in the region. Land surface and satellite observations were analyzed to estimate the net radiative forcing due to LULC change. Albedo and latent energy were specifically addressed for the dominant LULC change of agriculture to forests. It was assumed that in the energy-limited environment of the region, the partition of changes in available energy due to albedo will mostly impact the sensible heat. The results show that in the southeastern United States, for the period of 1920 to 1992, the changes in sensible (as a result of albedo) and latent energies are in direct competition with each other. In the spring and early summer months, the croplands are in peak production and the latent energy associated with their evapotranspiration (ET) is comparable to that of the forests so the decrease in radiation due to albedo dominates the signal. However, during the late summer and fall months, most major crops have matured, thus reducing their transpiration rate while forests (particularly evergreens) maintain their foliage and with their deep roots are able to continue to transpire as long as atmospheric conditions are favorable. This later influence of latent energy appears to more than offset the increased radiative forcing from the spring and early summer. Overall, a mean annual net radiative forcing resulting from a LULC change from cropland to forests was estimated to be −1.06 W m−2 and thus a probable contribution to the 'warming hole' over the Southeast during the majority of the twentieth century. [ABSTRACT FROM AUTHOR]

We analyze a provincial-scale dataset of winter wheat yield, together with finescale daily weather outcomes from 1979 to 2011, to assess the responses of winter wheat yield in China to temperature fluctuations. Contrary to the majority of the previous literature, we find that winter wheat yield in China responded positively to higher nighttime temperature Tmin, with the positive Tmin effects most significant in the northern China winter wheat region. Consistent with the previous studies, winter wheat yield in China exhibited negative responses to higher daytime temperature Tmax. As a result of these opposing temperature effects on yield, the net economic impact of weather variations on China's winter wheat sector is uncertain and is sensitive to specifications and data. Average winter wheat yield is projected to decline by 5.3%–7.0% by 2050 under the global climate model HadGEM2-ES and by 2.0%–3.4% under the NorESM1-M model. [ABSTRACT FROM AUTHOR]

On the Canadian Prairies, agricultural practices result in millions of hectares of standing crop stubble that gradually emerges during snowmelt. The importance of stubble in trapping wind-blown snow and retaining winter snowfall has been well demonstrated. However, stubble is not explicitly accounted for in hydrological or energy balance snowmelt models. This paper relates measurable stubble parameters (height, width, areal density, and albedo) to the snowpack energy balance and snowmelt with the new, physically based Stubble–Snow–Atmosphere Model (SSAM). Novel process representations of SSAM quantify the attenuation of shortwave radiation by exposed stubble, the sky and vegetation view factors needed to solve longwave radiation terms, and a resistance scheme for stubble–snow–atmosphere fluxes to solve for surface temperatures and turbulent fluxes. SSAM results were compared to observations of radiometric snow-surface temperature, stubble temperature, snow-surface solar irradiance, areal-average turbulent fluxes, and snow water equivalent from two intensive field campaigns during snowmelt in 2015 and 2016 over wheat and canola stubble in Saskatchewan, Canada. Uncalibrated SSAM simulations compared well with these observations, providing confidence in the model structure and parameterization. A sensitivity analysis conducted using SSAM revealed compensatory relationships in energy balance terms that result in a small increase in net snowpack energy as stubble exposure increases. [ABSTRACT FROM AUTHOR]

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. presented here are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop-specific measurement tool. [ABSTRACT FROM AUTHOR]

Established as a social companion to the Oklahoma Mesonet, the Oklahoma Meso-Scale Integrated Socio-Geographic Network (M-SISNet) is a network of approximately 1500 'social monitoring stations' (geolocated households) across the state of Oklahoma that provide data on household perceptions and responses to signals that are sent from agricultural, hydrological, and meteorological systems. This paper outlines the purpose and nature of the M-SISNet, with specific focus on the sample frame, protocols for recruitment, retention, and survey implementation. It concludes with example survey questions, analyses, and directions for accessing the data. [ABSTRACT FROM AUTHOR]

Farmers stand to be greatly affected by changes in the climate, necessitating adaptive responses, yet little is documented on how U.S. Midwestern farmers understand and perceive climate change adaptation. Eight focus groups with 53 Michigan farmers were conducted in 2011-12 to better understand the following: 1) what do farmers think about the relationship between climate change and agriculture, 2) what differentiates normal weather-related management from climate change adaptation actions, and 3) how do farmers understand the term 'climate change adaptation.' Farmers expressed skepticism at global climate change yet conveyed specific details about the local changes in climate they are experiencing on their farms. They were not able to clearly define the term 'climate change adaptation' but did note specific adaptive actions they have already implemented. The farmers explained that nonclimate factors were of more concern to them when making management decisions, and they showed reactive (not proactive) actions toward adaptation. Farmers noted that any action they take has to address their specific situation, suggesting that generalized adaptation actions and language might not resonate with them. Building on quantitative surveys conducted by others, the findings in this paper contribute to ongoing efforts to more effectively assess farmers' perceptions related to climate change adaptation and to use that understanding to promote education, outreach, research, and public policies to more proactively address the consequences posed by climate change. [ABSTRACT FROM AUTHOR]

Rainfall bursts are relatively short-lived events that typically occur over consecutive days, up to a week. Northern Australian industries like sugar farming and beef are highly sensitive to burst activity, yet little is known about the multiweek prediction of bursts. This study evaluates summer (December–March) bursts over northern Australia in observations and multiweek hindcasts from the Bureau of Meteorology's multiweek to seasonal system, the Australian Community Climate and Earth-System Simulator, Seasonal version 1 (ACCESS-S1). The main objective is to test ACCESS-S1's skill to confidently predict tropical burst activity, defined as rainfall accumulation exceeding a threshold amount over three days, for the purpose of producing a practical, user-friendly burst forecast product. The ensemble hindcasts, made up of 11 members for the period 1990–2012, display good predictive skill out to lead week 2 in the far northern regions, despite overestimating the total number of summer burst days and the proportion of total summer rainfall from bursts. Coinciding with a predicted strong Madden–Julian oscillation (MJO), the skill in burst event prediction can be extended out to four weeks over the far northern coast in December; however, this improvement is not apparent in other months or over the far northeast, which shows generally better forecast skill with a predicted weak MJO. The ability of ACCESS-S1 to skillfully forecast bursts out to 2–3 weeks suggests the bureau's recent prototype development of a burst potential forecast product would be of great interest to northern Australia's livestock and crop producers, who rely on accurate multiweek rainfall forecasts for managing business decisions. [ABSTRACT FROM AUTHOR]

Adaptation of the agricultural sector to climate change is crucial to avoid food insecurity in sub-Saharan Africa. Farmers' perception of climate change is a crucial element in adaptation process. The aim of this study was (i) to compare farmers' perception of climate change with actual weather data recorded in central Mali, (ii) to identify changes in agricultural practices implemented by farmers to adapt to climate change, and (iii) to investigate the link between farmers' perception of climate change and implementation of adaptation practices. Focus group discussions and individual surveys were conducted to identify climate-related changes perceived by farmers and agricultural adaptation strategies they consider relevant to cope with these changes. A majority (.50%) of farmers perceived an increase in temperature, decrease in rainfall, shortening of growing season, early cessation of rainfall, and increase in the frequency of dry spells at the beginning of the growing season. In line with farmers' perception, analysis of climate data indicated (i) an increase in mean annual temperature and minimum growing season temperature and (ii) a decrease in total rainfall. Farmers' perception of early cessation of rainfall and more-frequent drought periods were not detected by climate data analysis. To cope with the decrease in rainfall and late start of the growing season, farmers used drought-tolerant cultivars and implemented water-saving technologies. Despite a perceived warming, no specific adaptation to heat stress was mentioned by farmers. We found evidence of a link between farmers' perception of climate change and the implementation of some adaptation options. Our study highlights the need for a dialogue between farmers and researchers to develop new strategies to compensate for the expected negative impacts of heat stress on agricultural productivity. [ABSTRACT FROM AUTHOR]

The provision of climate services has the potential to generate adaptive capacity and help coffee farmers become or remain profitable by integrating climate information in a risk-management framework. Yet, to achieve this goal, it is necessary to identify the local demand for climate information, the relationships between coffee yield and climate variables, and farmers' perceptions and to examine the potential actions that can be realistically put in place by farmers at the local level. In this study, we assessed the climate information demands from coffee farmers and their perception on the climate impacts to coffee yield in the Samalá watershed in Guatemala. After co-identifying the related candidate climate predictors, we propose an objective, flexible forecast system for coffee yield that is based on precipitation. The system, known as NextGen, analyzes multiple historical climate drivers to identify candidate predictors and provides both deterministic and probabilistic forecasts for the target season. To illustrate the approach, a NextGen implementation is conducted in the Samalá watershed in southwestern Guatemala. The results suggest that accumulated June–August precipitation provides the highest predictive skill associated with coffee yield for this region. In addition to a formal cross-validated skill assessment, retrospective forecasts for the period 1989–2009 were compared with agriculturalists' perception on the climate impacts to coffee yield at the farm level. We conclude with examples of how demand-based climate service provision in this location can inform adaptation strategies like optimum shade, pest control, and fertilization schemes months in advance. These potential adaptation strategies were validated by local agricultural technicians at the study site. Significance Statement: In this study we wanted to provide climate services to coffee farmers in Guatemala who currently face challenges associated with climate variability and change. To do this, we first assessed what climate information they currently have at the farm level, how they use it in decision-making processes, and what improvements would benefit their risk-management framework (e.g., shade management) In addition, we evaluated farmers' perceptions related to the impact of climate to their coffee productivity. We verified the historical impact of several climate variables on coffee yield at the study site location and found that total rainfall for June–August is associated with coffee yield as originally referred by farmers. After identifying rainfall as one of the critical factors associated with coffee yield in this particular watershed of Guatemala, we moved to create a model that could help coffee farmers to forecast precipitation and the associated coffee yield months in advance. We then validated each of the management activities that could be put in place at the farm level with local technical and extension agricultural services in the region, including managing shade, adapting fertilization schemes, and managing weed removal at the farm level. [ABSTRACT FROM AUTHOR]

Accurate prediction of winter wheat (Triticum aestivum L.) heading date is important for determining the potential incidence of diseases and abiotic stresses such as freeze or heat events. Wheat phenological modeling requires cultivar- and crop-zone-specific vernalization and photoperiod knowledge. Previous models applied in Kansas showed that the uncertainties of predicting heading date were large and could be improved. In this study, a modification to the Scientific Impact Assessment and Modeling Platform for Advanced Crop and Ecosystem Management (SIMPLACE) model was developed and implemented to improve the accuracy of winter wheat heading date estimation. The cultivar- and crop-zone-specific model parameters were calculated using a Markov chain Monte Carlo simulation. The modified models were calibrated by using the longest observation site to cover all cultivars planted in each crop zone. Model performance was then evaluated for seven winter wheat cultivars at eight experiment sites distributed across four crop zones in Kansas. Our modified model (MS) had a root-mean-square error (RMSE) between predicted and observed heading date of 4 days, which reflects an improved accuracy by 5–8 days on average compared to the Agricultural Production Systems Simulator (APSIM) or the original SIMPLACE models. There was a clear correlation between the uncertainty of the modeled heading date and the sowing date in previous models. Our modified model demonstrates that integrating nonlinear temperature response functions, temperature stress factors, and sowing date information improved prediction of the heading date in winter wheat across Kansas. [ABSTRACT FROM AUTHOR]

While climate services have the potential to reduce precipitation- and temperature-related risks to agrarian livelihoods, such outcomes are possible only when they deliver information that is salient, legitimate, and credible to end users. This is particularly true of climate services intended to address the needs of women in agrarian contexts. The design of such gender-sensitive services is hampered by oversimplified framings of women as a group in both the adaptation and climate services literatures. This paper demonstrates that even at the village level, women have different climate and weather information needs, and differing abilities to act on that information. Therefore, starting with preconceived connections between identities and vulnerability is likely to result in overgeneralizations that hinder the ability to address the climate-related development and adaptation needs of the most vulnerable. Instead, as is demonstrated in this paper, the design and implementation of effective gender-sensitive climate services must start with the relevant social differences that shape people's livelihoods decisions and outcomes, including but not limited to gender. [ABSTRACT FROM AUTHOR]

Pesticide applications during surface inversions can lead to spray drift causing severe damage up to several kilometers off-target. Current regulations in Australia prohibit spray application of certain agricultural chemicals when hazardous surface inversions exist. This severely limits spray opportunities. Surface inversions can be classified as weakly or strongly stable. In the weakly stable case, moderate to strong turbulent mixing is not supportive of long-distance concentrated drift. In the very stable case, weak turbulent mixing can support the transport of high concentrations of fine material over long distances. A review of the literature and our analyses indicate that if the turbulence, as measured by the standard deviation of the vertical wind speed σw, is greater than about 0.2 m s−1 then turbulence-driven mixing and dispersion is moderate to strong and conversely if σw is less than about 0.2 m s−1 then turbulence-driven mixing and dispersion is weaker (an order of magnitude). The concept of maximum downward heat flux as a natural division between the regimes is applied within Monin–Obukhov stability theory, and it is shown that the observed mean σw of 0.2 m s−1 aligns with the ridge line of maximum heat flux in stable conditions. The level of turbulence in the weakly stable regime is comparable to the turbulence typically observed in near-neutral conditions that are recommended under current guidelines as suitable for spraying and is therefore seen as an acceptable prerequisite to avoid nondispersive spraying conditions. [ABSTRACT FROM AUTHOR]

This paper examines decision making under climate risks using farmers' decisions in sub-Saharan Africa, where climate risks are very high. Two risk measures are obtained from the Climate Research Unit's high-resolution climatology, diurnal temperature range (DTR) and coefficient of variation in precipitation (CVP), which are both averages of 30-yr climate data. Farm surveys of around 7600 households were matched cell by cell with the climate risk data. This paper finds that climate risks are indeed highest in the lowland arid zones in the Sahel. A spatial logit analysis shows that farmers in sub-Saharan Africa have adapted their agricultural systems to varying degrees of the CVP and the DTR. In the long term, if the CVP were to increase by 30%, an integrated system would increase by 7.0%. On the other hand, the two specialized systems fall: a crops-only system falls by 5.3% and a livestock-only system falls by 1.7%. When the DTR increases, farmers adapt by switching to a specialized livestock system. Under increased climate risks, this paper finds that farmers in the lowland savannahs and arid zones in the Sahel, where climate risks are high at present, will adapt by switching to an integrated system. Studies of climate risks, therefore, must account for behavioral responses of the individuals. These results can be utilized to help African farmers to adapt to increasing climate risks. [ABSTRACT FROM AUTHOR]

Crop water stress monitoring by remote sensing has been the focus of numerous studies. In this paper, specifically red (630-690 nm) and shortwave infrared (SWIR; 1550-1750 nm) wavelength bands are identified to monitor farmland water stress, and a method [modified shortwave infrared perpendicular water stress index (MSPSI)] is developed that is based on the spectral space constructed by SWIR − Red ( Rd) and SWIR + Red ( Rs). The MSPSI stayed at mostly the same water stress level for full vegetation coverage cases with high vegetation water content and saturated bare soil as well as full vegetation coverage with extremely low vegetation water and dry bare soil in the Rs- Rd spectral feature space. This approach makes the water stress conditions between different covers comparable and the MSPSI applicable to farmland water stress monitoring in different vegetation covers throughout the growing season. To validate the proposed index, the MSPSI calculated from Thematic Mapper images and Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance products (from March to October) in the Ningxia Hui Autonomous Region was compared with the ground-measured soil moisture content at different depths. It is evident from the results that the MSPSI derived from satellite imageries is highly correlated with ground-measured soil moisture at different depths (7.6 and 10 cm), with coefficients of determination R2 of 0.666, 0.512, 0.576, 0.361, 0.383, 0.391, 0.357, 0.410, and 0.418. The paper concludes that MSPSI is a promising index for crop water stress monitoring throughout the growing season. [ABSTRACT FROM AUTHOR]

A new, high-resolution (4 km), gridded land surface dataset produced with the Land Information System (LIS) is introduced, and the first set of synthesis of key hydroclimatic variables is reported. The dataset is produced over a 33-yr time period (1980-2012) for the U.S. Midwest with the intent to aid the agricultural community in understanding hydroclimatic impacts on crop production and decision-making in operational practices. While approximately 20 hydroclimatic variables are available through the LIS dataset, the focus here is on soil water content, soil temperature, and evapotranspiration. To assess the performance of the model, the LIS dataset is compared with in situ hydrometeorological observations across the study domain and with coarse-resolution reanalysis products [NARR, MERRA, and NLDAS-2 (phase 2 of the North American Land Data Assimilation System)]. In agricultural regions such as the U.S. Midwest, finescale hydroclimatic mapping that links the regional scale to the field scale is necessary. The new dataset provides this link as an intermediate-scale product that links point observations and coarse gridded datasets. In general, the LIS dataset compares well with in situ observations and coarser gridded products in terms of both temporal and spatial patterns, but cases of strong disagreement exist particularly in areas with sandy soils. The dataset is made available to the broader research community as an effort to fill the gap in spatial hydroclimatic data availability. [ABSTRACT FROM AUTHOR]