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There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally and temporally averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative–convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (e.g., 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter W, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).

 

The historical rise of irrigation has profoundly mitigated the effect of drought on agriculture in many parts of the United States. While irrigation directly alters soil moisture, meteorological drought indices ignore the effects of irrigation, since they are often based on simple water balance models that neglect the irrigation input. Reanalyses also largely neglect irrigation. Other approaches estimate the evaporative fraction (EF), which is correlated with soil moisture under water-limited conditions typical of droughts, with lower values corresponding to drier soils. However, those approaches require satellite observations of land surface temperature, meaning they cannot be used to study droughts prior to the satellite era. Here, we use a recent theory of land–atmosphere coupling—surface flux equilibrium (SFE) theory—to estimate EF from readily available observations of near-surface air temperature and specific humidity with long historical records. In contrast to EF estimated from a reanalysis that largely neglects irrigation, the SFE-predicted EF is greater at irrigated sites than at nonirrigated sites during droughts, and its historical trends are typically consistent with the spatial distribution of irrigation growth. Two sites at which SFE-predicted EF unexpectedly rises in the absence of changes in irrigation can be explained by increased flooding due to human interventions unrelated to irrigation (river engineering and the expansion of fish hatcheries). This work introduces a new method for quantifying agricultural drought prior to the satellite era. It can be used to provide insight into the role of irrigation in mitigating drought in the United States over the twentieth century.

Irrigation grew profoundly in the United States over the twentieth century, increasing the resilience of American agriculture to drought. Yet observational records of agricultural drought, and its response to irrigation, are limited to the satellite era. Here, we show that a common measure of agricultural drought (the evaporative fraction, EF) can be estimated using widespread weather data, extending the agricultural drought record decades further back in time. We show that EF estimated using our approach is both sensitive and specific to the occurrence of irrigation, unlike an alternative derived from a reanalysis.

 

Deforestation, urbanization and construction of wind farms can change the land surface roughness, which can further influence surface heat fluxes and thus weather and climate. Land surface roughness anomalies can dynamically trigger convergence through changing mean wind speed. Here, we report a new mechanism, in which roughness anomalies cause thermally direct mesoscale circulations and anomalous precipitation. To study this mechanism, we conduct cloud‐permitting simulations over an idealized land surface with prescribed surface roughness anomalies. Anomalously high roughness increases turbulent mixing near the surface, which decreases land surface temperature and outgoing longwave radiation. The additional surface net radiation partly goes into greater sensible heat flux, which triggers mesoscale circulations driven by differential heating. As a result, precipitation over the high‐roughness anomaly is generally larger than that over the low‐roughness background. This new mechanism, not present in climate models, may be relevant to storm formation over wind farms, cities and forests.

 

“Land radiative management” (LRM)—intentionally increasing land surface albedo to reduce regional temperatures—has been proposed as a form of geoengineering. Its effects on local precipitation and soil moisture over long timescales are not well understood. We use idealized cloud‐permitting simulations and a conceptual model to understand the response of precipitation and soil moisture to a mesoscale albedo anomaly at equilibrium. Initially, differential heating between a high‐albedo anomaly and the lower‐albedo surrounding environment drives mesoscale circulations, increasing precipitation and soil moisture in the surrounding environment. However, over time, increasing soil moisture reduces the differential heating, eliminating the mesoscale circulations. At equilibrium, the fractional increase in simulated soil moisture is up to 1.3 times the fractional increase in co‐albedo (one minus albedo). Thus, LRM may increase precipitation and soil moisture in surrounding regions, enhancing evaporative cooling and spreading the benefits of LRM over a wider region than previously recognized.

 

A frequently expressed viewpoint across the Earth science community is that global soil moisture estimates from satellite L‐band (1.4 GHz) measurements represent moisture only in a shallow surface layer (0–5 cm) and consequently are of limited value for studying global terrestrial ecosystems because plants use water from deeper rootzones. Using this argumentation, many observation‐based land surface studies avoid satellite‐observed soil moisture. Here, based on peer‐reviewed literature across several fields, we argue that such a viewpoint is overly limiting for two reasons. First, microwave soil emission depth considerations and statistical considerations of vertically correlated soil moisture information together indicate that L‐band measurements carry information about soil moisture extending below the commonly referenced 5 cm in many conditions. However, spatial variations of effective depths of representation remain uncertain. Second, in reviewing isotopic tracer field studies of plant water uptake, we find a prevalence of vegetation that primarily draws moisture from these upper soil layers. This is especially true for grasslands and croplands covering more than a third of global vegetated surfaces. Even some deeper‐rooted species (i.e., shrubs and trees) preferentially or seasonally draw water from the upper soil layers. Therefore, L‐band satellite soil moisture estimates are more relevant to global vegetation water uptake than commonly appreciated (i.e., relevant beyond only shallow soil processes like soil evaporation). Our commentary encourages the application of satellite soil moisture across a broader range of terrestrial hydrosphere and biosphere studies while urging more rigorous estimates of its effective depth of representation.

 

Abstract Soil moisture heterogeneity can induce mesoscale circulations due to differential heating between dry and wet surfaces, which can, in turn, trigger precipitation. In this work, we conduct cloud-permitting simulations over a 100 km × 25 km idealized land surface, with the domain split equally between a wet region and a dry region, each with homogeneous soil moisture. In contrast to previous studies that prescribed initial atmospheric profiles, each simulation is run with fixed soil moisture for 100 days to allow the atmosphere to equilibrate to the given land surface rather than prescribing the initial atmospheric profile. It is then run for one additional day, allowing the soil moisture to freely vary. Soil moisture controls the resulting precipitation over the dry region through three different mechanisms: as the dry domain gets drier, (i) the mesoscale circulation strengthens, increasing water vapor convergence over the dry domain, (ii) surface evaporation declines over the dry domain, decreasing water vapor convergence over the dry domain, and (iii) precipitation efficiency declines due to increased reevaporation, meaning proportionally less water vapor over the dry domain becomes surface precipitation. We find that the third mechanism dominates when soil moisture is small in the dry domain: drier soils ultimately lead to less precipitation in the dry domain due to its impact on precipitation efficiency. This work highlights an important new mechanism by which soil moisture controls precipitation, through its impact on precipitation reevaporation and efficiency.