Agronomic benefits and risks associated with the irrigated peanut–maize production system under a changing climate in northern Australia

2015 ◽  
Vol 66 (11) ◽  
pp. 1167 ◽  
Author(s):  
Yashvir S. Chauhan ◽  
Peter Thorburn ◽  
Jody S. Biggs ◽  
Graeme C. Wright
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Ghg Emissions ◽  
Dry Season ◽  
Global Climate Models ◽  
Irrigation Requirement ◽  
Wet Season ◽  
N Losses ◽  
Maize Production ◽  
Increased Temperature

With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.

scholarly journals What Controls Evapotranspiration in the Amazon Basin?

2007 ◽  
Vol 8 (3) ◽  
pp. 380-395 ◽  
Author(s):  
Natalia Hasler ◽  
Roni Avissar
Keyword(s):  
Water Stress ◽  
Large Scale ◽  
Amazon Basin ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Dry Season ◽  
Global Climate Models ◽  
Net Radiation ◽  
Wet Season

Abstract Global climate models (GCMs) and regional climate models (RCMs) generally show a decrease in the dry season evapotranspiration (ET) rate over the entire Amazon basin. Based on anecdotal observations, it has been suggested that they probably overestimate tropical rain forest water stress. In this study, eddy covariance flux measurements from eight different towers of the Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA) were used to provide a first look at the spatial variability and temporal cycle of ET throughout the basin. Results show strong seasonality in ET for stations near the equator (2°–3°S), with ET increasing during the dry season (June–September) and decreasing during the wet season (December–March), both correlated (0.75 to 0.94) and in phase with the net radiation annual cycle. In stations located farther south (9°–11°S) no clear seasonality could be identified in either net radiation or ET. For these more southerly stations, net radiation and ET are still correlated (0.76–0.92) in the wet season, but correlations decrease in the dry season (0–0.71), which is likely associated with water stress. For both pasture sites, located in southern Amazonia, ET decreases during the second half of the dry season, indicating progressively increased water stress. GCMs and RCMs indeed tend to overestimate dry season water stress in the Amazon basin and, therefore, should be revised to better simulate this region, which has a key role in the global hydrometeorology.

scholarly journals A 17 year climatology of the macrophysical properties of convection in Darwin

2018 ◽  
Vol 18 (23) ◽  
pp. 17687-17704 ◽  
Author(s):  
Robert C. Jackson ◽  
Scott M. Collis ◽  
Valentin Louf ◽  
Alain Protat ◽  
Leon Majewski
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Sea Breeze ◽  
Active Phase ◽  
Global Climate Models ◽  
Convective System ◽  
Wet Season ◽  
Australian Monsoon ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract. The validation of convective processes in global climate models (GCMs) could benefit from the use of large datasets that provide long-term climatologies of the spatial statistics of convection. To that regard, echo top heights (ETHs), convective areas, and frequencies of mesoscale convective systems (MCSs) from 17 years of data from a C-band polarization (CPOL) radar are analyzed in varying phases of the Madden–Julian Oscillation (MJO) and northern Australian monsoon in order to provide ample validation statistics for GCM validation. The ETHs calculated using velocity texture and reflectivity provide similar results, showing that the ETHs are insensitive to various techniques that can be used. Retrieved ETHs are correlated with those from cloud top heights retrieved by Multifunctional Transport Satellites (MTSATs), showing that the ETHs capture the relative variability in cloud top heights over seasonal scales. Bimodal distributions of ETH, likely attributable to the cumulus congestus clouds and mature stages of convection, are more commonly observed when the active phase of the MJO is over Australia due to greater mid-level moisture during the active phase of the MJO. The presence of a convectively stable layer at around 5 km altitude over Darwin inhibiting convection past this level can explain the position of the modes at around 2–4 km and 7–9 km. Larger cells were observed during break conditions compared to monsoon conditions, but only during the inactive phase of the MJO. The spatial distributions show that Hector, a deep convective system that occurs almost daily during the wet season over the Tiwi Islands, and sea-breeze convergence lines are likely more common in break conditions. Oceanic MCSs are more common during the night over Darwin. Convective areas were generally smaller and MCSs more frequent during active monsoon conditions. In general, the MJO is a greater control on the ETHs in the deep convective mode observed over Darwin, with higher distributions of ETH when the MJO is active over Darwin.

scholarly journals Net irrigation requirement under different climate scenarios using AquaCrop over Europe

2022 ◽  
Author(s):  
Louise Busschaert ◽  
Shannon de Roos ◽  
Wim Thiery ◽  
Dirk Raes ◽  
Gabriëlle J. M. De Lannoy
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Interannual Variability ◽  
Climate Models ◽  
Global Climate ◽  
Crop Productivity ◽  
Global Climate Models ◽  
Irrigation Requirement ◽  
Aquacrop Model ◽  
Far Future

Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average 70 % of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the FAO crop growth model AquaCrop version 6.1. The model is run at 0.5° lat × 0.5° lon resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the performance of AquaCrop surface soil moisture (SSM) simulations using historical meteorological input from two ISIMIP3 forcing datasets is evaluated with satellite-based SSM estimates. When driven by ISIMIP3a reanalysis meteorology for the years 2011–2016, daily simulated SSM values have an unbiased root-mean-square difference of 0.08 and 0.06 m3m−3 with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively. When forced with ISIMIP3b meteorology from five Global Climate Models (GCM) for the years 2011–2020, the historical simulated SSM climatology closely agrees with the climatology of the reanalysis-driven AquaCrop SSM climatology as well as the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031–2060 and 2071–2100) is compared to the baseline period of 1985–2014, to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 67 mm year–1 (+30 %) under a high emission scenario Shared Socioeconomic Pathway (SSP) 3-7.0. Central and southern Europe are the most impacted with larger Inet increases. The interannual variability of Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1-2.6), the increase in Inet will stabilize around 40 mm year–1 towards the end of the century and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.

scholarly journals Variations of future precipitations in Poyang Lake Watershed under the global warming using a spatiotemporally distributed downscaling model

2018 ◽  
Author(s):  
Ling Zhang ◽  
Xiaoling Chen ◽  
Jianzhong Lu ◽  
Dong Liang
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Poyang Lake ◽  
Dry Season ◽  
Global Climate Models ◽  
Wet Season ◽  
Temporal And Spatial Distribution ◽  
Precipitation Frequency ◽  
Change Rate ◽  
Precipitation Changes

Abstract. Traditional statistic downscaling methods are processed on independent stations, which ignores spatial correlations and spatiotemporal heterogeneity. In this study, a spatiotemporally distributed downscaling model (STDDM) was developed. The method interpolated observations and GCMs (Global Climate Models) simulations to continual finer grids; then created relationship, respectively for each grid at each time. We applied the STDDM in precipitation downscaling of Poyang Lake Watershed using MRI-CGCM3 (Meteorological Research Institute Coupled Ocean-Atmosphere General Circulation Model3), with an acceptant uncertainty of ≤ 4.9 %, and created future precipitation changes from 1998 to 2100 (1998–2012 in the historical and 2013–2100 in RCP8.5 scenario). The precipitation changes showed increasing heterogeneities in temporal and spatial distribution under the future climate warming. In the temporal pattern, the wet season precipitation increased with change rate (CR) = 7.33 mm/10a (11.66 mm/K) while the dry season precipitations decreased with CR = −0.92 mm/10a (−4.31 mm/K). The extreme precipitation frequency and intensity were enhanced with CR = 0.49 days/10a and 7.2 mm•day-1/10a respectively. In the spatial pattern, precipitations in wet or dry season showed an uneven change rate over the watershed, and the wet or dry area exhibited a wetter or drier condition in the wet or dry season. Analysis with temperature increases showed precipitation changes appeared significantly (p 

scholarly journals Increased Interannual Precipitation Extremes over California under Climate Change

2015 ◽  
Vol 28 (16) ◽  
pp. 6324-6334 ◽  
Author(s):  
Neil Berg ◽  
Alex Hall
Keyword(s):  
Interannual Variability ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
First Century ◽  
Precipitation Extremes ◽  
Wet Season ◽  
Precipitation Total ◽  
The Mean ◽  
Projected Changes

Abstract Changes to mean and extreme wet season precipitation over California on interannual time scales are analyzed using twenty-first-century precipitation data from 34 global climate models. Models disagree on the sign of projected changes in mean precipitation, although in most models the change is very small compared to historical and simulated levels of interannual variability. For the 2020/21–2059/60 period, there is no projected increase in the frequency of extremely dry wet seasons in the ensemble mean. Wet extremes are found to increase to around 2 times the historical frequency, which is statistically significant at the 95% level. Stronger signals emerge in the 2060/61–2099/2100 period. Across all models, extremely dry wet seasons are roughly 1.5 to 2 times more common, and wet extremes generally triple in their historical frequency (statistically significant). Large increases in precipitation variability in most models account for the modest increases to dry extremes. Increases in the frequency of wet extremes can be ascribed to equal contributions from increased variability and increases to the mean. These increases in the frequency of interannual precipitation extremes will create severe water management problems in a region where coping with large interannual variability in precipitation is already a challenge. Evidence from models and observations is examined to understand the causes of the low precipitation associated with the 2013/14 drought in California. These lines of evidence all strongly indicate that the low 2013/14 wet season precipitation total can be very likely attributed to natural variability, in spite of the projected future changes in extremes.

scholarly journals Comparison of Ensembles Projections of Rainfall from Four Bias Correction Methods over Nigeria

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3044
Author(s):  
Mohammed Sanusi Shiru ◽  
Inhwan Park
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Historical Period ◽  
Linear Scaling ◽  
Wet Season ◽  
Quantile Mapping ◽  
Global Precipitation Climatology Centre

This study compares multi model ensemble (MME) projections of rainfall using general quantile mapping, gamma quantile mapping, Power Transformation and Linear Scaling bias correction (BC) methods for representative concentration pathways (RCPs) 4.5 and 8.5 of the Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models (GCMs). Using the Global Precipitation Climatology Centre historical period (1961–2005) rainfall data as the reference, projection was conducted over 323 grid points of Nigeria for the periods 2010–2039, 2040–2069 and 2070–2099. The performances of the different BC methods in removing biases from the GCMs were assessed using different statistical indices. The computation of the MME of the projected rainfall was conducted by aggregation of 20 GCMs using random forest regression method. The percentage differences in the future rainfall relative to the historical period were estimated for all BC methods. Spatial projection of the percentage changes in rainfall for Linear scaling, which was the best performing BC method, showed increases in rainfall of 5.5–6.9% under RCPs 4.5 and 8.5, respectively, while the decrease range was −3.2–−4.2% respectively during the wet season. The range of annual increases in precipitation was 5.7–7.3% for RCP 4.5 and 8.5, respectively, while the decrease range was −1.0–−4.3%. This study also revealed monthly rainfall within the country will decrease during the wet season between June and September, which is a significant period where most crops need the water for growth. Findings from this study can be of importance to policy makers in the management of changes in hydrological processes due to climate change and management of related disasters such as floods and droughts.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

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