Climate extremes cause significant winter wheat yield loss and can cause much greater impacts than single extremes in isolation when multiple extremes occur simultaneously. Here we show that compound hot-dry-windy events (HDW) significantly increased in the U.S. Great Plains from 1982 to 2020. These HDW events were the most impactful drivers for wheat yield loss, accounting for a 4% yield reduction per 10 h of HDW during heading to maturity. Current HDW trends are associated with yield reduction rates of up to 0.09 t ha⁻¹ per decade and HDW variations are atmospheric-bridged with the Pacific Decadal Oscillation. We quantify the “yield shock”, which is spatially distributed, with the losses in severely HDW-affected areas, presumably the same areas affected by the Dust Bowl of the 1930s. Our findings indicate that compound HDW, which traditional risk assessments overlooked, have significant implications for the U.S. winter wheat production and beyond.

Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management.

Global responses of the hydrological cycle to climate change have been widely studied, but uncertainties still remain regarding water vapor responses to lower-tropospheric temperature. Here, we investigate the trends in global total precipitable water (TPW) and surface temperature from 1958 to 2021 using ERA5 and JRA-55 reanalysis datasets. We further validate these trends using radiosonde from 1979 to 2019 and Atmospheric Infrared Sounder (AIRS) and Special Sensor Microwave Imager/Sounder (SSMIS) observations from 2003 to 2021. Our results indicate a global increase in total precipitable water (TPW) of ∼ 2 % per decade from 1993–2021. These variations in TPW reflect the interactions of global warming feedback mechanisms across different spatial scales. Our results also revealed a significant near-surface temperature (T_2 m) warming trend of ∼ 0.15 K decade⁻¹ over the period 1958–2021. The consistent warming at a rate of ∼ 0.21 K decade⁻¹ after 1993 corresponds to a strong water vapor response to temperature at a rate of 9.5 % K⁻¹ globally, with land areas warming approximately twice as fast as the oceans. The relationship between TPW and T_2 m showed a variation of around 6 % K⁻¹–8 % K⁻¹ in the 15–55° N latitude band, aligning with theoretical estimates from the Clausius–Clapeyron equation.

The bushfires that occurred in Australia in late 2019 and early 2020 were unprecedented in terms of their scale, intensity, and impacts. Using nitrogen dioxide (NO₂) and carbon monoxide (CO) data measured by the Tropospheric Monitoring Instrument (TROPOMI), together with fire counts and fire radiative power (FRP) from MODIS, we analyzed the temporal and spatial variation of NO₂ and CO column densities over three selected areas covering savanna and temperate forest vegetation. The $\mathrm{\Delta }{\mathrm{NO}}_{\mathrm{2}}/\mathrm{\Delta }\mathrm{CO}$ emission ratio and emission factor were also estimated. The $\mathrm{\Delta }{\mathrm{NO}}_{\mathrm{2}}/\mathrm{\Delta }\mathrm{CO}$ emission ratio was found to be 1.57 ± 1.71 for temperate forest fire and ranged from 2.0 ± 2.36 to 2.6 ± 1.92 for savanna fire. For savanna and temperate forest fires, satellite-derived NO_x emission factors were found to be 1.48 and 2.39 g kg⁻¹, respectively, whereas the CO emission factors are 107.39 and 126.32 g kg⁻¹, respectively. This study demonstrates that the large-scale emission ratio from the TROPOMI satellite for different biomass burnings can help identify the relative contribution of smoldering and flaming activities in a large region and their impacts on the regional atmospheric composition and air quality. This method can be applied to study the emissions from other large fires, or even the burning of fossil fuel in megacities, and their impact on air quality.