Texas experienced the most extreme one‐year drought on record in 2011 with precipitation at 40% of long‐term mean and agricultural losses of ~$7.6 billion. We assess the value of Gravity Recovery and Climate Experiment (GRACE) satellite‐derived total water storage (TWS) change as an alternative remote sensing‐based drought indicator, independent of traditional drought indicators based on in situ monitoring. GRACE shows depletion in TWS of 62.3 ± 17.7 km³ during the 2011 drought. Large uncertainties in simulated soil moisture storage depletion (14–83 km³) from six land surface models indicate that GRACE TWS is a more reliable drought indicator than disaggregated soil moisture or groundwater storage. Groundwater use and groundwater level data indicate that depletion is dominated by changes in soil moisture storage, consistent with high correlation between GRACE TWS and the Palmer Drought Severity Index. GRACE provides a valuable tool for monitoring statewide water storage depletion, linking meteorological and hydrological droughts.

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite‐observed solar‐induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME‐2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought‐induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below‐normal precipitation. In contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME‐2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. We conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.

This is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variables across most regions and seasons and higher-resolution models tend to perform better for regional processes. The CMIP5 multimodel ensemble shows a slight improvement relative to CMIP3 models in representing basic climate variables, in terms of the mean and spread, although performance has decreased for some models. Improvements in CMIP5 model performance are noticeable for some regional climate processes analyzed, such as the timing of the North American monsoon. The results of this paper have implications for the robustness of future projections of climate and its associated impacts, which are examined in the third part of the paper.

Previous studies have established that sea surface temperature anomalies (SSTAs) in the tropical Pacific and Atlantic are the main forcing of the interannual variation of the wet season onsets in the Amazon. However, this variation appears to be complex and not uniquely determined by SSTAs. What causes such a complexity and to what extent the interannual variation of the wet season onsets is predictable remain unclear. This study suggests that such a complex relationship is the result of several competing processes, which are nonlinearly related to the SSTAs. In particular, three dry season conditions are crucial for determining interannual variation of the wet season onset. (i) A poleward shift of the Southern Hemisphere subtropical jet (SHSJ) over the South American sector, initiated from a wave train‐like structure possibly forced by south central Pacific SST patterns, can prevent cold frontal systems from moving northward into the Amazon. This delays cold air incursion and results in late wet season onset over the southern Amazon. (ii) An anomalous anticyclonic center, which enhances westerly wind at 850 hPa over the southern Amazon and also the South American low‐level jets, leads to moisture export from the southern Amazon to La Plata basin and reduces convective systems that provide elevated diabatic heating. (iii) Smaller convective available potential energy (CAPE) limits local thermodynamically driven convection. Based on the stepwise and partial least squares regressions, these three selected preseasonal conditions (Niño 4, SHSJ, and CAPE) can explain 57% of the total variance of the wet season onset.