California is one of the nation’s top agriculture producers and is vulnerable to extreme events such as droughts and heat waves. Concurrent extreme events may further stress water and energy resources, exerting greater adverse socioeconomic, environmental, and health impacts than individual events. Here we examine the features of compound drought, heat wave, and dust events in California during spring and summer. From 2003 to 2020, 16 compound events are found in warm seasons, with a mean duration of ∼4 days. Compound events are characterized by enhanced surface temperature up to 4.5°C over northern and western California, reduced soil moisture and vegetation density, and an increase in dust optical depth (DOD) by 0.05–0.1 over central and southern California. The enhanced DOD is largely associated with severe vegetation dieback that favors dust emissions and southeasterly wind anomalies that support northward transport of dust from source regions in southern California. Surface fine dust and PM2.5 concentrations also increase by more than 0.5 and 5 μg m−3, respectively, during compound events associated with both enhanced dust emissions and a relatively stable atmosphere that traps pollutants. The development of the compound events is related to an anomalous high over the west coast in the lower to middle troposphere, which is a pattern favoring sinking motion and dry conditions in California. The anomalous high is embedded in a wave train that develops up to 7 days before the events. In comparison with heat wave extremes alone, compound events show significantly higher DOD and lower vegetation density associated with droughts.
Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Most dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of wind erosion threshold (Vthreshold) over dry and sparsely-vegetated surface. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and seasonal cycle of DOD are better captured over the dust belt (i.e. North Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycle as well as dust forecasting.
Most dust forecast models focus on a short, sub‐seasonal lead times, i.e., three to six days, and the skill of seasonal prediction is not clear. In this study we examine the potential of seasonal dust prediction in the U.S. using an observation‐constrained regression model and key variables predicted by a seasonal prediction model developed at NOAA Geophysical Fluid Dynamics Laboratory, the Forecast‐Oriented Low Ocean Resolution (FLOR) Model.
Our method shows skillful predictions of spring dustiness three to six months in advance. It is found that the regression model explains about 71% of the variances of dust event frequency over the Great Plains and 63% over the southwestern U.S. in March‐May from 2004 to 2016 using predictors from FLOR initialized on December 1st. Variations in springtime dustiness are dominated by springtime climatic factors rather than wintertime factors. Findings here will help development of a seasonal dust prediction system and hazard prevention.
Pu, Bing, and Paul Ginoux, March 2018: Climatic factors contributing to long-term variations of fine dust concentration in the United States. Atmospheric Chemistry and Physics, 18(6), DOI:10.5194/acp-18-4201-2018. Abstract
High concentration of dust particles can cause respiratory problems and increase non-accidental mortality. Studies found fine dust (with aerodynamic diameter less than 2.5 microns) is an important component of the total PM2.5 mass in the western and central U.S. in spring and summer and has positive trends. This work examines factors influencing long-term variations of fine dust concentration in the U.S. using station data from the Interagency Monitoring Protected Visual Environments (IMPROVE) network during 1990–2015. The variations of the fine dust concentration can be largely explained by the variations of precipitation, surface bareness, and 10 m wind speed. Moreover, including convective parameters such as convective inhibition (CIN) and convective available potential energy (CAPE) better explains the variations and trends over the Great Plains from spring to fall.
While the positive trend of fine dust concentration in the Southwest in spring is associated with precipitation deficit, the increasing of fine dust over the central Great Plains in summer is largely associated with an enhancing of CIN and a weakening of CAPE, which are related to increased atmospheric stability due to surface drying and lower troposphere warming. The positive trend of the Great Plains low-level jet also contributes to the increasing of fine dust concentration in the central Great Plains in summer via its connections with surface winds and CIN.
Summer dusty days in the central Great Plains are usually associated with a westward extension of the North Atlantic subtropical high that intensifies the Great Plains low-level jet and also results in a stable atmosphere with subsidence and reduced precipitation.
Dust aerosol plays an important role in the climate system by affecting the radiative and energy balances. Biases in dust modeling may result in biases in simulating global energy budget and regional climate. It is thus very important to understand how well dust is simulated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven CMIP5 models using interactive dust emission schemes are examined against satellite derived dust optical depth (DOD) during 2004–2016.
It is found that multi-model mean can largely capture the global spatial pattern and zonal mean of DOD over land in present-day climatology in MAM and JJA. Global mean land DOD is underestimated by −25.2 % in MAM to −6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are generally captured by multi-model mean over major dust source regions such as North Africa and the Middle East, these variables are not so well represented by most of the models in South Africa and Australia. Interannual variations of DOD are neither captured by most of the models nor by multi-model mean. Models also do not capture the observed connections between DOD and local controlling factors such as surface wind speed, bareness, and precipitation. The constraints from surface bareness are largely underestimated while the influences of surface wind and precipitation are overestimated.
Projections of DOD change in the late half of the 21st century under the Representative Concentration Pathways 8.5 scenario by multi-model mean is compared with those projected by a regression model. Despite the uncertainties associated with both projections, results show some similarities between the two, e.g., DOD pattern over North Africa in DJF and JJA, an increase of DOD in the Arabian Peninsula in all seasons, and a decrease over northern China from MAM to SON.
Climate models project rising drought risks over the southwestern and central U.S. in the twenty-first century due to increasing greenhouse gases. The projected drier regions largely overlay the major dust sources in the United States. However, whether dust activity in U.S. will increase in the future is not clear, due to the large uncertainty in dust modeling. This study found that changes of dust activity in the U.S. in the recent decade are largely associated with the variations of precipitation, soil bareness, and surface winds speed. Using multi-model output under the Representative Concentration Pathways 8.5 scenario, we project that climate change will increase dust activity in the southern Great Plains from spring to fall in the late half of the twenty-first century – largely due to reduced precipitation, enhanced land surface bareness, and increased surface wind speed. Over the northern Great Plains, less dusty days are expected in spring due to increased precipitation and reduced bareness. Given the large negative economic and societal consequences of severe dust storms, this study complements the multi-model projection on future dust variations and may help improve risk management and resource planning.
Pu, Bing, R Dickinson, and R Fu, April 2016: Dynamical connection between Great Plains low-level winds and variability of central Gulf States precipitation. Journal of Geophysical Research: Atmospheres, 121(7), DOI:10.1002/2015JD024045. Abstract
The Great Plains low-level jet has been related to summer precipitation over the northern Great Plains and Midwest through its moisture transport and convergence at the jet exit area. Much less studied has been its negative relationship with precipitation over the southern Great Plains and the Gulf coastal area. This work shows that the southerly low-level winds at 30°–40°N over the southern Great Plains are significantly correlated with anticyclonic vorticity to its east over the central Gulf States (30°–35°N, 85°–95°W) from May to July. When the low-level jet is strong in June and July, anomalous anticyclonic vorticity over the central Gulf States leads to divergence and consequent subsidence suppressing precipitation over that region. In contrast, an enhanced southerly flow at the entrance region of the jet over the Gulf of Mexico, largely uncorrelated with the meridional wind over the southern Great Plains, is correlated with increased precipitation over the central Gulf States. Precipitation is large over the central Gulf States when the meridional wind over the southern Great Plains is weakest and over the Gulf of Mexico is strongest. This increase is consistent with the increased moisture transport and dynamic balance between loss of vorticity by advection and friction and gain by convergence.
The increasing trend of aerosol optical depth in the Middle East and a recent severe dust storm in Syria have raised questions as whether dust storms will increase and promoted investigations on the dust activities driven by the natural climate variability underlying the ongoing human perturbations such as the Syrian civil war. This study examined the influences of the Pacific decadal oscillation (PDO) on dust activities in Syria using an innovative dust optical depth (DOD) dataset derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products. A significantly negative correlation is found between the Syrian DOD and the PDO in spring from 2003–2015. High DOD in spring is associated with lower geopotential height over the Middle East, Europe, and North Africa, accompanied by near surface anomalous westerly winds over the Mediterranean basin and southerly winds over the eastern Arabian Peninsula. These large-scale patterns promote the formation of the cyclones over the Middle East to trigger dust storms and also facilitate the transport of dust from North Africa, Iraq, and Saudi Arabian to Syria, where the transported dust dominates the seasonal mean DOD in spring. A negative PDO not only creates circulation anomalies favorable to high DOD in Syria but also suppresses precipitation in dust source regions over the eastern and southern Arabian Peninsula and northeastern Africa. On the daily scale, in addition to the favorable large-scale condition associated with a negative PDO, enhanced atmospheric instability in Syria associated with increased precipitation in Turkey and northern Syria is also critical for the development of strong springtime dust storms in Syria.
