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Impact of derived global weather data on simulated crop yields.

van Wart J, Grassini P, Cassman KG - Glob Chang Biol (2013)

Bottom Line: In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean).We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain.An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.

View Article: PubMed Central - PubMed

Affiliation: Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583-0915, USA.

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Simulated wheat Yw across four sites in Germany using weather data from NOAA-SR (a), NCEP (b), Climate Research Unit (c), and NASA (d) plotted against simulated Yw based on a control weather database. Insets show deviations of points from the 1:1 line for each site and year for which yield was simulated with GWD or NOAA data. RMSE and mean error (ME) units are in Mg ha−1. NASA Yw simulations were performed from 1997–2007. Symbols represent different locations. Note that site-years affected by frost have points on the x-axis at 0 Mg ha−1 and these Yw values were taken into account in all statistical calculations of RMSE and ME.
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fig04: Simulated wheat Yw across four sites in Germany using weather data from NOAA-SR (a), NCEP (b), Climate Research Unit (c), and NASA (d) plotted against simulated Yw based on a control weather database. Insets show deviations of points from the 1:1 line for each site and year for which yield was simulated with GWD or NOAA data. RMSE and mean error (ME) units are in Mg ha−1. NASA Yw simulations were performed from 1997–2007. Symbols represent different locations. Note that site-years affected by frost have points on the x-axis at 0 Mg ha−1 and these Yw values were taken into account in all statistical calculations of RMSE and ME.

Mentions: On average, simulated yields were overestimated by more than 1.5 t ha−1 in six of nine cases when based on data from gridded GWD compared with the simulated yields using CWD (Figs 2–4). Of particular note was the average upward bias of about 4.0 t ha−1 for Yw of US maize estimated by CRU and NASA, and for Yp of rice in China by NCEP. However, the bias between gridded GWD and CWD based simulations was not consistent. For example, except for NASA based simulations in Germany, simulations in China and Germany made with GWD data overestimated Yp or Yw. But NCEP-based simulations of Yw for maize in the USA had a negative bias of more than 1.0 t ha−1. While CRU based rainfed maize Yw simulations tended to overestimate Yp and Yw at high yield levels, NCEP and NASA tended to overestimate Yp at lower yield levels. In contrast, simulated yields using NOAA-SR weather data were in reasonably close agreement with yields simulated with CWD, although irrigated rice Yp in China had a modest overestimation of Yw (ME = 0.9 Mg ha−1). On average, %RMSE for Yp and Yw simulations based on gridded GWD was 45% and 33%, respectively, compared with 19% and 14% for NOAA-SR-based simulations. Likewise, the degree of correlation between Yp or Yw estimated by NOAA-derived weather data and the CWD was quite high in all cases, ranging from Pearson correlation r values of 0.70 for rice in China to 0.89 for wheat in Germany. Correlations with CWD values for Yp or Yw based on GWD were much poorer and sometimes not statistically significant.


Impact of derived global weather data on simulated crop yields.

van Wart J, Grassini P, Cassman KG - Glob Chang Biol (2013)

Simulated wheat Yw across four sites in Germany using weather data from NOAA-SR (a), NCEP (b), Climate Research Unit (c), and NASA (d) plotted against simulated Yw based on a control weather database. Insets show deviations of points from the 1:1 line for each site and year for which yield was simulated with GWD or NOAA data. RMSE and mean error (ME) units are in Mg ha−1. NASA Yw simulations were performed from 1997–2007. Symbols represent different locations. Note that site-years affected by frost have points on the x-axis at 0 Mg ha−1 and these Yw values were taken into account in all statistical calculations of RMSE and ME.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288967&req=5

fig04: Simulated wheat Yw across four sites in Germany using weather data from NOAA-SR (a), NCEP (b), Climate Research Unit (c), and NASA (d) plotted against simulated Yw based on a control weather database. Insets show deviations of points from the 1:1 line for each site and year for which yield was simulated with GWD or NOAA data. RMSE and mean error (ME) units are in Mg ha−1. NASA Yw simulations were performed from 1997–2007. Symbols represent different locations. Note that site-years affected by frost have points on the x-axis at 0 Mg ha−1 and these Yw values were taken into account in all statistical calculations of RMSE and ME.
Mentions: On average, simulated yields were overestimated by more than 1.5 t ha−1 in six of nine cases when based on data from gridded GWD compared with the simulated yields using CWD (Figs 2–4). Of particular note was the average upward bias of about 4.0 t ha−1 for Yw of US maize estimated by CRU and NASA, and for Yp of rice in China by NCEP. However, the bias between gridded GWD and CWD based simulations was not consistent. For example, except for NASA based simulations in Germany, simulations in China and Germany made with GWD data overestimated Yp or Yw. But NCEP-based simulations of Yw for maize in the USA had a negative bias of more than 1.0 t ha−1. While CRU based rainfed maize Yw simulations tended to overestimate Yp and Yw at high yield levels, NCEP and NASA tended to overestimate Yp at lower yield levels. In contrast, simulated yields using NOAA-SR weather data were in reasonably close agreement with yields simulated with CWD, although irrigated rice Yp in China had a modest overestimation of Yw (ME = 0.9 Mg ha−1). On average, %RMSE for Yp and Yw simulations based on gridded GWD was 45% and 33%, respectively, compared with 19% and 14% for NOAA-SR-based simulations. Likewise, the degree of correlation between Yp or Yw estimated by NOAA-derived weather data and the CWD was quite high in all cases, ranging from Pearson correlation r values of 0.70 for rice in China to 0.89 for wheat in Germany. Correlations with CWD values for Yp or Yw based on GWD were much poorer and sometimes not statistically significant.

Bottom Line: In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean).We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain.An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.

View Article: PubMed Central - PubMed

Affiliation: Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68583-0915, USA.

Show MeSH