Climate for crops: integrating climate data with information about soils and crop requirements to reduce risks in agricultural decision‐making

Wratt, David; Tait, Andrew; Griffiths, George A.; Espie, P. R.; Jessen, Murray R.; Keys, James E.; Ladd, Matthew; Lew, Daniel; Lowther, W. L.; Mitchell, N. D.; Morton, J. D.; Reid, JB; Reid, Stephen; Richardson, Annette; Sansom, J.; Shankar, Ude

doi:10.1017/s1350482706002416

Cited by 51 publications

(30 citation statements)

References 19 publications

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“…Measurements are not constrained by an upper cutoff in radius. We also evaluated the simulated wind speed and precipitation with 30-year observational climatologies (1980e2010) provided by the National Institute of Water and Atmospheric Research (NIWA) (Wratt et al, 2006) and the South African Weather Service (SWAS) (Rouault et al, 2005) (Table 1). Additionally, NIWA provided climatological maps covering the New Zealand islands at 0.5 Â 0.5 resolution.…”

Section: Methodsmentioning

confidence: 99%

On the evaluation of global sea-salt aerosol models at coastal/orographic sites

Spada

Jorba

García‐Pando

et al. 2015

Atmospheric Environment

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Sea-salt aerosol global models are typically evaluated against concentration observations at coastal stations that are unaffected by local surf conditions and thus considered representative of open ocean conditions. Despite recent improvements in sea-salt source functions, studies still show significant model errors in specific regions. Using a multiscale model, we investigated the effect of high model resolution (0.1 degrees x 0.1 degrees vs. 1 degrees x 1.4 degrees) upon sea-salt patterns in four stations from the University of Miami Network: Baring Head, Chatam Island, and Invercargill in New Zealand, and Marion Island in the sub-antarctic Indian Ocean. Normalized biases improved from +63.7% to +3.3% and correlation increased from 0.52 to 0.84. The representation of sea/land interfaces, mesoscale circulations, and precipitation with the higher resolution model played a major role in the simulation of annual concentration trends. Our results recommend caution when comparing or constraining global models using surface concentration observations from coastal stations. (C) 2014 The Authors. Published by Elsevier Ltd.Postprint (published version

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Section: Methodsmentioning

confidence: 99%

On the evaluation of global sea-salt aerosol models at coastal/orographic sites

Spada

Jorba

García‐Pando

et al. 2015

Atmospheric Environment

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“…Rigorous consideration of the spatial climatic variability prior to plant establishment can therefore lead to greater economic profitability through the lifetime of the horticultural activity. Accurate local-scale climate mapping is an important tool in the planning process (Wratt et al 2006).…”

Section: Introductionmentioning

confidence: 99%

“…The method of using short-term data to predict long-term temperature variables such as frost risk has been performed in the past by Wratt et al (2006), using the previously discussed spline method (in combination with infrared satellite imagery). In that study, minimum temperatures derived from the fitted splines and frost incidence were related to the imagery using least-squares regression.…”

Section: Introductionmentioning

confidence: 99%

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

Webb

Hall

Kidd

et al. 2015

Theor Appl Climatol

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Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination (R 2 ) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31°C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47°C for daily minimum temperature, 1 % and 0.23°C for daily maximum temperature and 3 % and 0.33°C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

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“…(Tait, 2005;Tait et al, 2006;Tait and Zheng, 2007;Tait, 2008). The grids are based on daily data collected from climate stations across New Zealand for the period 1971-2000 (Wratt et al, 2006). As individual weather stations can only record information at their specific sites, the grids were created with a second order derivative trivariate thin plate smoothing spline model using latitude, longitude and elevation to interpolate the temperature data from the irregularly spaced climate stations onto the high resolution (500 m by 500 m) regular grids (Wratt et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…The grids are based on daily data collected from climate stations across New Zealand for the period 1971-2000 (Wratt et al, 2006). As individual weather stations can only record information at their specific sites, the grids were created with a second order derivative trivariate thin plate smoothing spline model using latitude, longitude and elevation to interpolate the temperature data from the irregularly spaced climate stations onto the high resolution (500 m by 500 m) regular grids (Wratt et al, 2006). The annual and seasonal temperature grids have been shown to have root mean square errors of 0.3-0.5°C for individual climate stations, which is in a similar range to gridded data created and used in Australia (Tait and Zheng, 2007;Hall and Jones, 2010).…”

Section: Introductionmentioning

confidence: 99%

Analysis of viticulture region climate structure and suitability in New Zealand

et al. 2012

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Aims: This research analyzes four climate indices derived from gridded, interpolated data to assess New Zealand's climate structure and variation among wine regions. Methods and results:High resolution gridded data based on 1971-2000 climate normals was used to characterize climate indices depicting viticultural suitability in a geographic information system. The statistical properties of each index were assessed over 21 New Zealand viticulture regions. The results show predominately cool to moderately warm climate suitability in New Zealand, comparable to many European and United States regions. While many viticulture regions have one primary class of suitability, variability of climate within regions can be significant, with some regions containing two to four climate classes, making them suitable for a greater range of cultivars. Conclusion:While the indices depict broad patterns expected over New Zealand, both within and between region variations can be substantial among the indices. However, two indices, Growing Season Average Temperature (GST) and Growing Degree-Days (GDD), are functionally identical, but GST is easier to calculate and overcomes many methodological issues in GDD.Significance and impact of the study: This research provides the basis for evaluating general suitability for viticulture in New Zealand, assists comparisons between viticulture regions in New Zealand and worldwide, and offers growers measures of assessing appropriate cultivars and sites. AbstractRésumé

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Climate for crops: integrating climate data with information about soils and crop requirements to reduce risks in agricultural decision‐making

Abstract: Locally applicable information about climate and soil properties can help farmers identify opportunities and reduce risks associated with changing to new land uses. This article describes techniques for preparing high-resolution regional maps and GIS

Cited by 51 publications

References 19 publications

On the evaluation of global sea-salt aerosol models at coastal/orographic sites

On the evaluation of global sea-salt aerosol models at coastal/orographic sites

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

Analysis of viticulture region climate structure and suitability in New Zealand

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