Convective Triggering Potential Research Articles

Deducing land–atmosphere coupling regimes from SMAP soil moisture

Abstract. In recent years, there has been a growing recognition of the significance of land–atmosphere (L–A) interactions and feedback mechanisms in understanding and predicting Earth's water and energy cycles. Soil moisture plays a critical role in mediating the strength of L–A interactions and is important for understanding the complex and governing processes across this interface. This study aims to identify the significance of soil moisture in identifying L–A coupling strength within the convective triggering potential (CTP) and humidity index (HI) framework. To address this, a consistent and reliable dataset of atmospheric profiles is created by merging CTP and HI using triple collocation (TC) with three reanalysis datasets. The merged CTP and HI product demonstrates enhanced performance globally compared to the individual datasets when validated with radiosonde and satellite observations. This merged product of CTP and HI is then used to compare the L–A coupling strength based on Soil Moisture Active Passive Level 3 (SMAPL3) and SMAP Level 4 (SMAPL4) over 2 decades (2003–2022) where L–A coupling strength is defined as the persistence probability within the dry and wet coupling regimes. Results indicate that the persistency-based coupling strength is related to the ability of soil moisture to predict future atmospheric humidity and dry vs. wet coupling state. The coupling strength in SMAPL4 is consistently stronger than in SMAPL3 and is likely due to its reliance on a land surface model and reduced susceptibility to random noise. The difference in coupling strength based on the same CTP–HI underscores the importance of soil moisture data in estimating coupling strength within the CTP–HI framework. These findings lay the groundwork for understanding the role of L–A interactions and drought evolution due to soil moisture variations by providing insight into the quantification of coupling strength and its role in drought monitoring and forecast efforts.

Assessing the Convective Environment over Irrigated and Nonirrigated Land Use with Land–Atmosphere Coupling Metrics: Results from GRAINEX

Abstract Land-use land-cover change affects weather and climate. This paper quantifies land–atmosphere interactions over irrigated and nonirrigated land uses during the Great Plains Irrigation Experiment (GRAINEX). Three coupling metrics were used to quantify land–atmosphere interactions as they relate to convection. They include the convective triggering potential (CTP), the low-level humidity index (HIlow), and the lifting condensation level (LCL) deficit. These metrics were calculated from the rawinsonde data obtained from the Integrated Sounding Systems (ISSs) for Rogers Farm and York Airport along with soundings launched from the three Doppler on Wheels (DOW) sites. Each metric was categorized by intensive observation period (IOP), cloud cover, and time of day. Results show that with higher CTP, lower HIlow, and lower LCL deficit, conditions were more favorable for convective development over irrigated land use. When metrics were grouped and analyzed by IOP, compared to nonirrigated land use, HIlow was found to be lower for irrigated land use, suggesting favorable conditions for convective development. Furthermore, when metrics were grouped and analyzed by clear and nonclear days, CTP values were higher over irrigated cropland than nonirrigated land use. In addition, compared to nonirrigated land use, the LCL deficit during the peak growing season was lower over irrigated land use, suggesting a favorable condition for convection. It is found that with the transition from the early summer to the mid/peak summer and increased irrigation, the environment became more favorable for convective development over irrigated land use. Finally, it was found that regardless of background atmospheric conditions, irrigated land use provided a favorable environment for convective development.

Influence of lower-tropospheric moisture on local soil moisture–precipitation feedback over the US Southern Great Plains

Abstract. ​​​​​​​Land–atmosphere coupling (LAC) has long been studied, focusing on land surface and atmospheric boundary layer processes. However, the influence of humidity in the lower troposphere (LT), especially that above the planetary boundary layer (PBL), on LAC remains largely unexplored. In this study, we use radiosonde observations from the US Southern Great Plains (SGP) site and an entrained parcel buoyancy model to investigate the impact of LT humidity on LAC there during the warm season (May–September). We quantify the effect of LT humidity on convective buoyancy by measuring the difference between the 2–4 km vertically integrated buoyancy with the influence of background LT humidity and that without it. Our results show that, under dry soil conditions, anomalously high LT humidity is necessary to produce the buoyancy profiles required for afternoon precipitation events (APEs). These APEs under dry soil moisture cannot be explained by commonly used local LAC indices such as the convective triggering potential and low-level humidity index (CTP / HILow), which do not account for the influence of the LT humidity. On the other hand, consideration of LT humidity is unnecessary to explain APEs under wet soil moisture conditions, suggesting that the boundary layer moisture alone could be sufficient to generate the required buoyancy profiles. These findings highlight the need to consider the impact of LT humidity, which is often decoupled from the humidity near the surface and is largely controlled by moisture transport, in understanding land–atmospheric feedbacks under dry soil conditions, especially during droughts or dry spells over the SGP.

Rain-fed to irrigation-fed transition of agriculture exacerbates meteorological drought in cropped regions but moderates elsewhere

In recent decades, irrigated agriculture has expanded dramatically over the Southeastern United States (SEUS). The trend is more likely to continue in future given the need to further improve crop productivity and its resilience against droughts, however, the impact of these SEUS land cover changes remains unknown. This study investigates how and to what extent rain-fed to irrigation-fed (RFtoIF) transition in the SEUS region modulates precipitation spatially and temporally under a severe drought meteorological condition. In this study, we perform three Weather Research Forecasting model simulations with varying degrees of irrigated crop areas with meteorological boundary conditions of a record-breaking 2007 drought in the SEUS region. Results show that the SEUS irrigation expansion reduces both the convective triggering potential and low-level humidity index through land-atmospheric interaction. This is accompanied by reduction in the height of atmospheric boundary layer (ABL)-lifting condensation level crossing and increase in the convective available potential energy. These modulations within the ABL provide a favorable condition for strong deep convection during the drought period. However, the impact on precipitation is heterogeneous, with crop areas undergoing RFtoIF transition experiencing an overall reduction in precipitation while other landcovers experiencing an increase. The reduction in precipitation over RFtoIF transitioned croplands is in part due to moisture redistribution aided by generation of an anomalous high-pressure system. The results highlight the complexity of response of precipitation to irrigation expansion in the SEUS, and underscore the need to perform spatially-explicit analysis for mitigating risks to water resources and food security.

Land-atmosphere coupling speeds up flash drought onset

Flash drought is a type of drought with rapid onset and great destructiveness, which poses a serious threat to agriculture, ecosystem, and environment without sufficient early warning. The rapid onset is a unique feature that distinguishes flash drought from conventional dry conditions, but its underlying mechanism remains unclear. With the 42-years reanalysis data, we compared the differences in convective triggering potential and atmospheric humidity indices between flash drought onset and conventional dry conditions over China. We found that the dry land-atmospheric coupling can speed up flash drought onset by suppressing precipitation and increasing evapotranspiration. Results show that the increase of sensible heat transport during flash drought onset can intensify the heating of atmosphere, and enhance the lifting condensation level deficit which efficiently inhibits the convective precipitation. Meanwhile, the atmospheric drying significantly increases the evapotranspiration demand and decreases soil moisture, thus speeds up the drought onset. In this regard, the drier land surface makes the atmosphere drier through land-atmosphere coupling, and the rapid drought onset can be maintained via the positive feedback. Although the contribution of precipitation deficit averaged over China is 92 %, the evapotranspiration excess is also critical for increasing the onset speed especially over South China where the flash drought hotspot exists. With the contribution of evapotranspiration increased by about 26 %, the flash drought onset speed over China almost doubled. This study highlights the importance of dry land-atmospheric coupling for speeding up flash drought onset and provides insights for flash drought diagnosis and prediction.

Sensitivity of land–atmosphere coupling strength to changing atmospheric temperature and moisture over Europe

Abstract. The quantification of land–atmosphere coupling strength is still challenging, particularly in the atmospheric segment of the local coupling process chain. This is in part caused by a lack of spatially comprehensive observations of atmospheric temperature and specific humidity which form the verification basis for the common process-based coupling metrics. In this study, we aim at investigating where uncertainty in the atmospheric temperature and moisture affects the land–atmosphere coupling strength over Europe, and how changes in the mean temperature and moisture, as well as their vertical gradients, influence the coupling. For this purpose, we implemented systematic a posteriori modifications to the temperature and moisture fields from a regional climate simulation to create a spread in the atmospheric conditions. Afterwards, the process-based coupling metric convective triggering potential – low-level humidity index framework was applied to each modification case. Comparing all modification cases to the unmodified control case revealed that a strong coupling hotspot region in northeastern Europe was insensitive to temperature and moisture changes, although the number of potential coupling days varied by up to 20 d per summer season. The predominance of positive feedbacks remained unchanged in the northern part of the hotspot, and none of the modifications changed the frequent inhibition of feedbacks due to dry conditions in the atmosphere over the Mediterranean and the Iberian Peninsula. However, in the southern hotspot region in the north of the Black Sea, the dominant coupling class frequently switched between wet soil advantage and transition zone. Thus, both the coupling strength and the predominant sign of feedbacks were sensitive to changes in temperature and moisture in this region. This implies not only uncertainty in the quantification of land–atmosphere coupling strength but also the potential that climate-change-induced temperature and moisture changes considerably impact the climate there, because they also change the predominant atmospheric response to land surface wetness.

Impact of Soil Moisture on Afternoon Convection Triggering Over the Tibetan Plateau Based on 1‐D Boundary Layer Model

AbstractThe impact of soil moisture conditions on the triggering of afternoon convection over the Tibetan Plateau (TP) was investigated by applying the convective triggering potential (CTP) and humidity index framework developed by Findell and Eltahir (2003a, https://doi.org/10.1175/1525-7541(2003)004<0552:acosml>2.0.co;2, 2003b, https://doi.org/10.1175/1525-7541(2003)004<0570:acosml>2.0.co;2) using a slab model. Atmospheric sounding observations from May to September from 2015 to 2019 from 16 sites were used for the diagnosis. The results showed that the thresholds of CTP and humidity index in the lower‐layer atmosphere (HIlow) are distinct from other regions such as the United States and India, suggesting an easier triggering potential for the TP due to its high altitude induced lower air density and higher buoyancy. The convection over the TP is mainly affected by the atmospheric background. The percentages of soil moisture‐controlled cases is close to 50% mainly located in the broadly central TP. In addition, the positive feedback is mainly located in the center of the TP. Negative feedback appears in the southwest of the TP. Soil moisture is the most critical factor for precipitation triggering in soil moisture‐precipitation feedback, while wind speed can also have certain influences. The impact of soil moisture on different outcomes has no significant correlation with land surface elevation differences. Negative feedback in the southwest of the TP appeals to a necessary enhancement requirement for sounding observations in the western TP.

Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.

Evaluation of a land-atmosphere coupling metric computed from a ground-based infrared interferometer

AbstractLand-atmosphere feedbacks are a critical component of the hydrologic cycle. Vertical profiles of boundary layer temperature and moisture, together with information about the land surface, are used to compute land-atmosphere coupling metrics. Ground based remote sensing platforms, such as the Atmospheric Emitted Radiance Interferometer (AERI), can provide high temporal resolution vertical profiles of temperature and moisture. When co-located with soil moisture, surface flux, and surface meteorological observations, such as at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, it is possible to observe both the terrestrial and atmospheric legs of land-atmosphere feedbacks. In this study, we compare a commonly used coupling metric computed from radiosonde-based data to that obtained from the AERI to characterize the accuracy and uncertainty in the metric derived from the two distinct platforms. This approach demonstrates the AERI’s utility where radiosonde observations are absent in time and/or space. Radiosonde and AERI based observations of the Convective Triggering Potential and Low-Level Humidity Index (CTP-HIlow) were computed during the 1200 UTC observation time and displayed good agreement during both 2017 and 2019 warm seasons. Radiosonde and AERI derived metrics diagnosed the same atmospheric preconditioning based upon the CTP-HIlow framework a majority of the time. When retrieval uncertainty was considered, even greater agreement was found between radiosonde and AERI derived classification. The AERI’s ability to represent this coupling metric well enabled novel exploration of temporal variability within the overnight period in CTP and HIlow. Observations of CTP-HIlow computed within a few hours of 1200 UTC were essentially equivalent, however with greater differences in time arose greater differences in CTP and HIlow.

Seasonal variability of soil moisture-precipitation feedbacks over India

Soil moisture plays a significant role in partitioning surface energy fluxes into latent and sensible heat components and is fundamental for process level understanding of land-atmosphere interactions. Realistic simulations of such interactions by models are constrained due to intrinsic model assumptions. This study examines convective triggering based on soil moisture by employing a framework of coupling diagnostics called Convective triggering potential (CTP) and humidity index (HILow) to classify land regions into various feedback regimes for each season between 2005 and 2015. Results show that atmospherically controlled cases prevail in most of the regions for all seasons. Temporal regime probability values (TRP) suggested a dominant wet regime in southern India and a dominant dry regime in central and western India. Precipitation events triggered in wet advantage conditions were found to have larger accumulations than similar events triggered in dry advantage conditions for all the seasons. This study highlights separate seasonal regime classification and emphasizes on how potential regime hotspots vary for each season.

A Modified Framework for Quantifying Land–Atmosphere Covariability during Hydrometeorological and Soil Wetness Extremes in Oklahoma

AbstractGlobal “hot spots” for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation.

Land–Atmosphere Coupling at the Southern Great Plains Atmospheric Radiation Measurement (ARM) Field Site and Its Role in Anomalous Afternoon Peak Precipitation

Abstract The multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. The area including and surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied in the context of LA coupling. Observation-based studies suggest a coupling signal that is much weaker than modeled, if not elusive. Using North American Regional Reanalysis and North American Land Data Assimilation System data, this study provides a 36-yr (1979–2014) climatology of coupling for ARM-SGP that 1) unifies prior interdisciplinary efforts and 2) isolates the origin of the (weak) coupling signal. Specifically, the climatology of a prominent convective triggering potential–low-level humidity index (CTP–HIlow) coupling classification is linked to corresponding synoptic–mesoscale weather and atmospheric moisture budget analyses. The CTP–HIlow classification defines a dry-advantage regime for which convective triggering is preferentially favored over drier-than-average soils as well as a wet-advantage regime for which convective triggering is preferentially favored over wetter-than-average soils. This study shows that wet-advantage days are a result of horizontal moisture flux convergence over the region, and conversely, dry-advantage days are a result of zonal and vertical moisture flux divergence. In this context, the role of the land is nominal relative to that of atmospheric forcing. Surface flux partitioning, however, can play an important role in modulating diurnal precipitation cycle phase and amplitude and it is shown that soil moisture and sensible heat flux are significantly correlated with both occurrence and intensity of afternoon peak precipitation.

Neural Network–Based Sensitivity Analysis of Summertime Convection over the Continental United States

Abstract Although land–atmosphere coupling is thought to play a role in shaping the mean climate and its variability, it remains difficult to quantify precisely. The present study aims to isolate relationships between early morning surface turbulent fluxes partitioning [i.e., evaporative fraction (EF)] and subsequent afternoon convective precipitation frequency and intensity. A general approach involving statistical relationships among input and output variables, known as sensitivity analysis (SA), is used to develop a reduced complexity metamodel of the linkage between EF and convective precipitation. Two additional quantities characterizing the early morning convective environment, convective triggering potential (CTP) and low-level humidity (HIlow) deficit, are included. The SA approach is applied to the North American Regional Reanalysis (NARR) for June–August (JJA) conditions over the entire continental United States, Mexico, and Central America domain. Five land–atmosphere coupling regimes are objectively characterized based on CTP, HIlow, and EF. Two western regimes are largely atmospherically controlled, with a positive link to CTP and a negative link to HIlow. The other three regimes occupy Mexico and the eastern half of the domain and show positive links to EF and negative links to HIlow, suggesting that both surface fluxes and atmospheric humidity play a role in the triggering of rainfall in these regions. The regimes associated with high mean EF also tend to have high sensitivity of rainfall frequency to variations in EF. While these results may be sensitive to the choice of dataset, the approach can be applied across observational, reanalysis, and model datasets and thus represents a potentially powerful tool for intercomparison and validation as well as for characterizing land–atmosphere interaction regimes.

Phenomenology of Sahelian convection observed in Niamey during the early monsoon

AbstractThis study aims to achieve a better understanding of the initiation of deep convection in the Sahel by using the African Monsoon Multidisciplinary Analyses (AMMA) dataset. Based on the Massachusetts Institute of Technology (MIT) radar, wind profiler, satellite data, surface flux and meteorological stations, we have characterised the atmospheric convection which occurred over Niamey during the onset period of the monsoon. From 6 to 31 July, radar reflectivity fields combined with brightness temperatures were used to classify the type of convection observed each day within a 50 km radius of the MIT radar location. Four types of convection have been identified: fair weather (FW) with a clear sky throughout the entire day, shallow convection (SH), afternoon locally initiated deep convection (LC), and propagating deep convection (PC). Subsequently, the mechanisms responsible for the initiation of local deep convection were investigated.Neither early morning convective available potential energy nor the convective triggering potential allowed the onset of local deep convection to be predicted correctly. In effect, they were both favourable to deep convection most of the time, while convective inhibition was typically quite large. Our results show that the daytime growth of the atmospheric boundary layer needed to be sufficient for local deep convection to occur during that period. Convergence lines, which grew within the morning clear‐air roll organisation, were found to be precursors of local deep convection. Classes FW, SH and LC ultimately behaved quite similarly, with notable convergence in the lower troposphere, but FW showed smaller boundary‐layer growth, and FW and SH classes revealed a significant divergence above the boundary layer. Most cases of LC generated a circular gust front. These density currents almost always generated new convective cells.

Temporal Variability of Land–Atmosphere Coupling and Its Implications for Drought over the Southeast United States

AbstractDroughts represent a significant source of social and economic damage in the southeast United States. Having sufficient warning of these extreme events enables managers to prepare for and potentially mitigate the severity of their impacts. A seasonal hydrologic forecast system can provide such warning, but current forecast skill is low during the convective season when precipitation is affected by regionally varying land surface heat flux contributions. Previous studies have classified regions into coupling regimes based on the tendency of surface soil moisture anomalies to trigger convective rainfall. Until now, these classifications have been aimed at assessing the long-term dominant feedback signal. Sufficient focus has not been placed on the temporal variability that underlies this signal. To better understand this aspect of coupling, a new classification methodology suitable at daily time scales is developed. The methodology is based on the joint probability space of surface soil moisture, convective triggering potential, and the low-level humidity index. The methodology is demonstrated over the U.S. Southeast using satellite remote sensing, reanalysis, and hydrological model data. The results show strong persistence in coupling events that is linked to the land surface state. A coupling-based drought index shows good agreement with the temporal and spatial variability of drought and highlights the role of coupling in drought recovery. The implications of the findings for drought and forecasting are discussed.

Observed Land–Atmosphere Coupling from Satellite Remote Sensing and Reanalysis

AbstractThe lack of observational data for use in evaluating the realism of model-based land–atmosphere feedback signal and strength has been deemed a major obstacle to future improvements to seasonal weather prediction by the Global Land–Atmosphere Coupling Experiment (GLACE). To address this need, a 7-yr (2002–09) satellite remote sensing data record is exploited to produce for the first time global maps of predominant coupling signals. Specifically, a previously implemented convective triggering potential (CTP)–humidity index (HI) framework for describing atmospheric controls on soil moisture–rainfall feedbacks is revisited and generalized for global application using CTP and HI from the Atmospheric Infrared Sounder (AIRS), soil moisture from the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E), and the U.S. Climate Prediction Center (CPC) merged satellite rainfall product (CMORPH). Based on observations taken during an AMSR-E-derived convective rainfall season, the global land area is categorized into four convective regimes: 1) those with atmospheric conditions favoring deep convection over wet soils, 2) those with atmospheric conditions favoring deep convection over dry soils, 3) those with atmospheric conditions that suppress convection over any land surface, and 4) those with atmospheric conditions that support convection over any land surface. Classification maps are produced using both the original and modified frameworks, and later contrasted with similarly derived maps using inputs from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications (MERRA). Both AIRS and MERRA datasets of CTP and HI are validated using radiosonde observations. The combinations of methods and data sources employed in this study enable evaluation of not only the sensitivity of the classification schemes themselves to their inputs, but also the uncertainty in the resultant classification maps. The findings are summarized for 20 climatic regions and three GLACE coupling hot spots, as well as zonally and globally. Globally, of the four-class scheme, regions for which convection is favored over wet and dry soils accounted for the greatest and least extent, respectively. Despite vast differences among the maps, many geographically large regions of concurrence exist. Through its ability to compensate for the latitudinally varying CTP–HI–rainfall tendency characteristics observed in this study, the revised classification framework overcomes limitations of the original framework. By identifying regions where coupling persists using satellite remote sensing this study provides the first observationally based guidance for future spatially and temporally focused studies of land–atmosphere interactions. Joint distributions of CTP and HI and soil moisture, rainfall occurrence, and depth demonstrate the relevance of CTP and HI in coupling studies and their potential value in future model evaluation, rainfall forecast, and/or hydrologic consistency applications.

Diagnosis of Local Land–Atmosphere Feedbacks in India

Abstract Following the convective triggering potential (CTP)–humidity index (HIlow) framework by Findell and Eltahir, the sensitivity of atmospheric convection to soil moisture conditions is studied for India. Using the same slab model as Findell and Eltahir, atmospheric conditions in which the land surface state affects convective precipitation are determined. For India, CTP–HIlow thresholds for land surface–atmosphere feedbacks are shown to be slightly different than for the United States. Using atmospheric sounding data from 1975 to 2009, the seasonal and spatial variations in feedback strength have been assessed. The patterns of feedback strengths thus obtained have been analyzed in relation to the monsoon timing. During the monsoon season, atmospheric conditions where soil moisture positively influences precipitation are present about 25% of the time. During onset and retreat of the monsoon, the south and east of India show more potential for feedbacks than the north. These feedbacks suggest that large-scale irrigation in the south and east may increase local precipitation. To test this, precipitation data (from 1960 to 2004) for the period about three weeks just before the monsoon onset date have been studied. A positive trend in the precipitation just before the monsoon onset is found for irrigated stations. It is shown that for irrigated stations, the trend in the precipitation just before the monsoon onset is positive for the period 1960–2004. For nonirrigated stations, there is no such upward trend in this period. The precipitation trend for irrigated areas might be due to a positive trend in the extent of irrigated areas, with land–atmosphere feedbacks inducing increased precipitation.

Diagnosing Land–Atmosphere Interaction from a Regional Climate Model Simulation over West Africa

Abstract Land–atmosphere interaction at climatological time scales in a large area that includes the West African Sahel has been explicitly explored in a regional climate model (RegCM) simulation using a range of diagnostics. First, areas and seasons of strong land–atmosphere interaction were diagnosed from the requirement of a combined significant correlation between soil moisture, evaporation, and the recycling ratio. The northern edge of the West African monsoon area during June–August (JJA) and an area just north of the equator (Central African Republic) during March–May (MAM) were identified. Further analysis in these regions focused on the seasonal cycle of the lifting condensation level (LCL) and the convective triggering potential (CTP), and the sensitivity of CTP and near-surface dewpoint depressions HIlow to anomalous soil moisture. From these analyses, it is apparent that atmospheric mechanisms impose a strong constraint on the effect of soil moisture on the regional hydrological cycle.

Atmospheric Controls on Soil Moisture–Boundary Layer Interactions. Part II: Feedbacks within the Continental United States

The CTP-HIlow framework for describing atmospheric controls on soil moisture‐boundary layer interactions is described in a companion paper, Part I. In this paper, the framework is applied to the continental United States to investigate how differing atmospheric regimes influence local feedbacks between the land surface and the atmosphere. The framework was developed with a one-dimensional boundary layer model and is based on two measures of atmospheric thermodynamic properties: the convective triggering potential (CTP), a measure of the temperature lapse rate between approximately 1 and 3 km above the ground surface, and a low-level humidity index, HIlow. These two measures are used to distinguish between three types of early-morning atmospheric conditions: those favoring moist convection over dry soils, those favoring moist convection over wet soils, and those that will allow or prevent deep convective activity, independent of the surface flux partitioning. Analyses of multiyear CTP-HIlow scatterplots from radiosonde stations across the contiguous 48 United States reveal that during the summer months (June, July, and August) positive feedbacks between soil moisture and moist convection are likely in much of the eastern half of the country. Over the western half of the country, atmospheric conditions and the likelihood of moist convection are largely determined by oceanic influences, and land surface conditions in the summer are unlikely to impact convective triggering. The only area showing a potential negative feedback is in the dryline and monsoon region of the arid Southwest. This potential arises because of the topography of this and surrounding regions. A relatively narrow band of stations lies in between the eastern and western portions of the country, in some years behaving like the stations to the west and in other years behaving like the stations to the east.

Atmospheric Controls on Soil Moisture–Boundary Layer Interactions. Part I: Framework Development

This paper investigates the influence of soil moisture on the development and triggering of convection in different early-morning atmospheric conditions. A one-dimensional model of the atmospheric boundary layer (BL) is initialized with atmospheric sounding data from Illinois and with the soil moisture set to either extremely wet (saturated) or extremely dry (20% of saturation) conditions. Two measures are developed to assess the lowlevel temperature and humidity structure of the early-morning atmosphere. These two measures are used to distinguish between four types of soundings, based on the likely outcome of the model: 1) those soundings favoring deep convection over dry soils, 2) those favoring deep convection over wet soils, 3) those unlikely to convect over any land surface, and 4) those likely to convect over any land surface. Examples of the first two cases are presented in detail. The early-morning atmosphere is characterized in this work by the newly developed convective triggering potential (CTP) and a low-level humidity index, HIlow. The CTP measures the departure from a moist adiabatic temperature lapse rate in the region between 100 and 300 mb (about 1‐3 km) above the ground surface (AGS). This region is the critical interface between the near-surface region, which is almost always incorporated into the growing BL, and free atmospheric air, which is almost never incorporated into the BL. Together, these two measures form the CTP-HIlow framework for analyzing atmospheric controls on soil moisture‐boundary layer interactions. Results show that in Illinois deep convection is trigged in the model 22% of the time over wet soils and only 13% of the time over dry soils. Additional testing varying the radiative conditions in Illinois and also using the 1D model with soundings from four additional stations confirm that the CTP-HI low framework is valid for regions far removed from Illinois.