Land Surface Heat Fluxes Research Articles

Heating pattern and effects of built-up land in response to influencing factors: A statistical estimation of 172 Chinese cities

The increase of the land surface temperature (LST) caused by an urban expansion poses a great threat to the humanity and society. However, the heating characteristics of built-up land and the environmental impacts on these mechanisms remain poorly understood over large areas. Therefore, the change trend (k) and structural distribution of LST during the process of increasing the built-up area in 172 cities in China was quantified. Using correlation analysis and statistical methods to analyze the correlation and possible driving characteristics of influencing factors (climate, topography, land use type, and soil) on k. The results indicated that k varied from −5.955 to 8.240 and showed a spatial characteristic of small in the northwest and large in the southeast. The research emphasized the heating difference of built-up land varied significantly in cities with different natural environmental conditions, with the maximum difference reaching 6 °C. The heating mechanism of built-up land under the interference of influencing factors was explained from the perspective of land surface heat flux, and the mitigation strategies for urban temperature were proposed. Besides, the threshold for the impact of environmental factors on the heating of built-up land was found, which provides a reference for environment-adapted urban design and planning standards tailored by considering the specific characteristics of each city.

Assessing the Correlation Between Spectral Indices and Land Surface Heat Fluxes by Remote Sensing Technology: A Case Study in Thai Binh Province, Red River Delta, Vietnam

Assessing the Correlation Between Spectral Indices and Land Surface Heat Fluxes by Remote Sensing Technology: A Case Study in Thai Binh Province, Red River Delta, Vietnam

Global impacts of vegetation clumping on regulating land surface heat fluxes

The clumping index (CI) quantifies the non-random distribution of vegetation across space, which regulates the canopy radiative transfer processes and land surface carbon, water, and energy cycles. However, its impact on global surface energy budget, particularly sensible heat fluxes and surface temperature, is not well understood. Additionally, while there have been studies showing significant seasonal variations in CI, the impacts of these variations on surface energy fluxes remain unclear. In this study, we incorporated satellite-derived spatially and temporally explicit CI data into the Community Land Model version 5 (CLM5) to evaluate the effects of CI on global land energy fluxes. Our results showed that including CI increased the global mean sensible heat flux dissipated from ground by 3.9 W m−2 (∼18%), while decreasing the global mean vegetation sensible heat flux by 4.9 W m−2 (∼65%), resulting in a total sensible heat decrease of 1.0 W m−2 (∼3%). In contrast, CI increased the global mean latent heat flux by 0.8 W m−2 (∼2%), primarily due to increased evapotranspiration (up to 11 W m−2) in tropical regions. We also found considerable impacts of seasonal variations in CI, particularly on sensible heat fluxes from ground and vegetation in evergreen needleleaf forests and deciduous needleleaf forests. Using constant CI rather than considering seasonal variations resulted in significant overestimation and underestimation of the sensible heat fluxes from vegetation and ground, respectively, in boreal summer. These changes in surface energy fluxes caused by CI and its seasonal variations led to up to 1.7 and 0.5 K differences in simulated mean ground temperature. These findings highlight the importance of including CI and considering its seasonal variations in modeling land surface energy fluxes.

The spatiotemporal variation of land surface heat fluxes in Tibetan Plateau during 2001–2022

The surface energy budget is important for understanding of energy and water cycle processes in the Tibetan Plateau (TP). In this study, the daily sensible (SH) and latent (LE) heat fluxes at the horizontal resolution of 1° are first estimated using the maximum entropy production (MEP) model (hereinafter SHMEP and LEMEP) in the entire TP during 2001–2022. The MEP model is built on physical and statistical principles to simulate surface heat fluxes. The surface net radiation, soil moisture (SM), and land surface temperature (LST) are the main driving variables for MEP model. To select the relatively accurate MEP input data, the merged surface net radiation (Rn–merged) under all-sky conditions are generated from CERES, ISCCP-FH, and ERA5 using the Bayesian Model Averaging scheme. Besides, the TP SM and LST from various data sources are evaluated using the in-situ observations at site scale. Based on the daily Rn–merged, ERA5 SM, CERES LST, and the MEP model, the daily SH and LE are estimated in the entire TP. The results show the daily SHMEP and LEMEP perform well at the validation sites, with the regional mean correlation coefficient (R) above 0.7, root-mean-square error (RMSE) of <19 W m−2, absolute value of bias and mean absolute error (MAE) below 11 W m−2. The monthly SHMEP has the regional mean R of 0.96 and RMSE of 6.30 W m−2 at all the measurement stations. For LEMEP, the regional mean R and RMSE values are 0.93 and 10.01 W m−2, respectively. The MEP simulation results are superior to the SH and LE in ERA5, ERA-Interim, MERRA-2, and JRA-55 reanalysis datasets and previous studies, especially for LE. Based on this new dataset, the spatial and temporal varying characteristics of SH and LE in the TP are analyzed. The annual mean SHMEP value are large in the western TP, the Qaidam Basin in the northern TP, and the Himalaya ranges, and small in the southeastern TP. The annual mean LEMEP has the maximum value in southeastern TP, and minimum value in western TP and the Qaidam Basin. The annual mean SHMEP and LEMEP over the entire TP are 34.79 W m−2 and 20.16 W m−2, with the significant declining trends of −0.17 W m−2 year−1 and − 0.052 W m−2 year−1 during the study period, respectively. The spatial distributions of the MEP surface heat fluxes and their trends are mainly influenced by the model inputs of Rn and SM in the TP.

Analyzing the effect of view factors on surface heat flux, surface temperature, and vegetation cover.

With the increase in population in cities, economic, social, and environmental problems continue to increase, and it is thought that the microclimatic conditions created by these problems will cause more environmental problems. One of the factors affecting the urban climate in urban areas is urban geometry. The climate of a region changes due to the shape of the land surface, human activities, atmospheric movements, and latent and sensible heat fluxes. Sky view factor (SVF), building view factor (BVF), and tree view factor (TVF) are actively used in the determination of urban geometry. However, studies on how these factors affect the thermal state of the urban environment are insufficient. Determining the land surface changes and thermal condition characteristics (LST, NDVI, SHF, and LHF) depending on urban growth and examining how these properties affect thermal conditions are very important in the construction of sustainable urban planning. In the study, SVF, BVF, TVF, LST, NDVI, SHF, and LHF values of 55 points determined for three different areas with different urban geometries were calculated. How these values affect each other and their situation on urban outdoor thermal comfort is evaluated. In the study, statistical analysis was performed to evaluate the relationship between surface temperature, surface heat fluxes, different view factors, and vegetation. As a result of ANOVA analysis, it was determined as very significant (p > 0.01) in all regions. Both SHF and LHF values differ with SVF. The SHF value has a direct relationship with the SVF value. LHF is inversely proportional to the SVF value. The situation is reversed for SHF variation concerning vegetation. LHF and NDVI are directly related. SHF and NDVI are inversely proportional. SVF and NDVI values also vary according to the LST value. It has been observed that LST has a direct relationship with SVF and an inverse relationship with NDVI.

Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2

Abstract. All current global climate models (GCMs) utilize only grid-averaged surface heat fluxes to drive the atmosphere, and thus their subgrid horizontal variations and partitioning are absent. This can result in many simulation biases. To address this shortcoming, a novel parameterization scheme considering the subgrid variations of the sensible and latent heat fluxes to the atmosphere and the associated partitioning is developed and implemented into the National Center for Atmospheric Research (NCAR) Climate Earth System Model 1.2 (CESM1.2). Compared to the default model, in addition to the improved boreal summer precipitation simulation over eastern China and the coastal areas of the Bay of Bengal, the long-standing overestimations of precipitation on the southern and eastern margins of the Tibetan Plateau (TP) in most GCMs are alleviated. The improved precipitation simulation on the southern margin of the TP is from suppressed large-scale precipitation, while that on the eastern edge of the TP is due to decreased convective precipitation. Moisture advection is blocked toward the southern edge of the TP, and the anomaly of anticyclonic moisture transport over northern China extends westward, suppressing local convection on the eastern edge of the TP. The altered large-scale circulation in the lower atmosphere resulting from anomalous heating and cooling in the planetary boundary layer is responsible for the change in moisture transport. The performance of other key variables (e.g., surface energy fluxes, clouds and 2 m temperature) is also evaluated thoroughly using the default CESM1.2, the new scheme and the scheme stochastically allocating the subgrid surface heat fluxes to the atmosphere (i.e., without subgrid partitioning included). This study highlights the importance of subgrid surface energy variations and partitioning to the atmosphere in simulating the hydrological and energy cycles in GCMs.

Global Impacts of Vegetation Clumping on Regulating Land Surface Heat Fluxes

Global Impacts of Vegetation Clumping on Regulating Land Surface Heat Fluxes

Systematic Evaluation of a High-Resolution CLM5 Simulation over Continental China for 1979–2018

Abstract The land surface model is extensively used to simulate turbulence fluxes and hydrological and momentum variables at the land–atmosphere interface. In this study, the Community Land Model, version 5 (CLM5), driven by the 0.1° × 0.1° Chinese Meteorological Forcing Dataset (CMFD) and the field-surveyed soil parameters, is used to simulate land surface processes during 1979–2018. Various high-quality land surface datasets are adopted to assess the model simulations. In general, the CLM5 well captures the monthly variations of 0–10-cm soil moisture in subregions, particularly in the Tibetan Plateau, with an anomaly correlation coefficient between 0.56 and 0.88. However, the simulated soil moisture shows overall wet biases in the whole country, resulting from several reasons. The model simulation is skillful in replicating both the magnitude and spatial pattern when they are compared with the MODIS snow cover dataset. Compared with in situ measured soil temperature in multiple soil layers within 320-cm soil depth from 1980 to 2018, the simulations accurately capture spatial patterns, vertical profiles, and long-term warming trends. For land surface energy components, the simulations have a highly temporal correlation with the observation of Chinese Flux Observation and Research Network (ChinaFLUX) cropland and grassland sites, except for four forest sites, where biases exist in both atmospheric forcing variables and surface vegetation phenology in the model default input dataset. In summary, this study reveals the overall capability of CLM5 in reproducing land surface energy fluxes and hydrological variables over conterminous China, and the validation results may also provide some references for future model improvement and application. Significance Statement The offline Community Land Model, version 5 (CLM5), driven by a 0.1° × 0.1° (∼10 km) horizontal resolution atmospheric forcing dataset and a set of field-surveyed soil parameters, are used to simulate the land surface hydrological and heat fluxes in continental China for 1980–2018. The simulated hydrological variables and energy fluxes are validated with various sources of high-quality observation-based datasets. From our systematic evaluations, the current CLM5 high–resolution simulation accurately captures the spatial patterns and temporal variations in most of the water and energy balance components, although biases exist in some simulated variables. Overall, this study reveals the capability of the offline CLM5 simulation in conterminous China and provides the reference for future model improvement and application.

Accounting for the Effect of Noise in Satellite Soil Moisture Data on Estimates of Land–Atmosphere Coupling Using Information Theoretical Metrics

Abstract Land states can affect the atmosphere through their control of surface turbulent fluxes and the subsequent impact of those fluxes on boundary layer properties. Information theoretic (IT) metrics are ideal to study the strength and type of coupling between surface soil moisture (SM) and land surface heat fluxes (HFs) because they are nonparametric and thus appropriate for the analysis of highly complex Earth systems containing nonlinear cause-and-effect interactions that may have nonnormal distributions. Specifically, a methodology for the estimation of IT metrics from noisy time series is proposed, accounting for random errors in satellite-based SM data. Performance of the proposed method is demonstrated through synthetic tests. Efficacy of the method is greatest for estimates of entropy and mutual information involving SM; improvements to estimates of transfer entropy are significant but less stark. A global depiction of the information flow between SM and HFs is then constructed from observationally based gridded data. This is used as independent verification for two configurations of the ECMWF modeling system: unconstrained open-loop (retrospective forecasts) and constrained by data assimilation (ERA5). Compared to studies that only investigate the linear SM–HF relationships, extended regions of significant terrestrial coupling are found over the globe, as IT metrics enable detection of nonlinear dependencies. The magnitude and spatial variability of coupling strength and type from models show discrepancies with those from observations, highlighting the potential to improve SM and HF covariability within models. Although ERA5 did not perform better than the unconstrained model in very dry climates, its performance is generally superior to that of the unconstrained model across metrics.

Spatial Pattern and Land Surface Features Associated with Cloud-to-Ground Lightning in Bangladesh: An Exploratory Study

Severe weather events such as lightning appear to be a significant threat to humans and property in South Asia, an area known for intense convective activity directly related to the tropical climate of these areas. The current study was conducted in Bangladesh and examined the association between cloud-to-ground (CG) lightning and ground surface properties, with the aim of improving existing knowledge regarding this phenomenon. GLD360 data from 2015 to 2020 were used to describe the seasonal lightning climatology. Elevation, land use and land cover, vegetation and surface heat flux data were used to examine all land surface features possibly associated with CG lightning occurrence. Hot and cold spot spatial patterning was calculated using local indicators of spatial association. Results indicated a strong CG lightning seasonality. CG stroke density varied considerably across seasons with the pre-monsoon exhibiting the highest density. This was followed by occurrences in the monsoon season. The March–June period experienced 73% of the total observed. Elevation appeared to influence the post-monsoon CG stroke, however, its role in the other seasons was more difficult to define. The land cover/lightning index indicated that waterbodies and herbaceous wetlands had more influence than other land cover types, both during the day and at night, and it appeared that latent heat flux played a major role. The CG stroke hot and cold spot locations varied diurnally. The findings suggest that large-scale irrigation practices, especially during the pre-monsoon months, can influence the observed spatiotemporal pattern. The production of hotspot maps could be an initial step in the development of a reliable lightning monitoring system and play a part in increasing public awareness of this issue.

The root-zone soil moisture spectrum in a mediterranean ecosystem

Storage of water within soil pores of the root zone introduce memory effects in the dynamics of soil moisture that are considerably longer than the integral timescale of many atmospheric processes. Thus, hydro-climatic states can be “sustained” through land-surface heat and water vapor fluxes primarily because they can “feed off” on this long-term soil moisture memory. Root-zone soil moisture memory is only but one feature characterizing the spectrum of soil moisture dynamics, which is analyzed here using a combination of long-term measurements and models. In particular, the spectrum of root-zone soil moisture content in a Mediterranean ecosystem is examined using 14-years of half-hourly measurements. A distinguishing hydro-climatic feature in such ecosystems is that sources (mainly rainfall) and sinks (mainly evapotranspiration) of soil moisture are roughly out of phase with each other. For over 4 decades of time scales and 7 decades of energy, the canonical shape of the measured soil moisture spectrum is shown to be approximately Lorentzian determined by the soil moisture variance and its memory but with two exceptions: the occurrences of a peak at diurnal-to-daily time scales and a weaker peak at near annual time scales. Model calculations and spectral analysis demonstrate that diurnal and seasonal variations in hydroclimate forcing responsible for variability in evapotranspiration had minor impact on the normalized shape of the soil moisture spectrum. However, their impact was captured by adjustments in the temporal variance. These findings indicate that precipitation and not evapotranspiration variability dominates the multi-scaling properties of soil moisture variability consistent with prior climate model simulations. Furthermore, the soil moisture memory inferred by the annual peak of soil moisture (340 d) is consistent with climate model simulations, while the memory evaluated from the loss function of a linearized mass balance approach leads to a smaller value (50 d), highlighting the effect of weak non-stationarity on soil moisture variability.

Mechanical forcing of the North American monsoon by orography.

A band of intense rainfall extends more than 1,000 km along Mexico's west coast during Northern Hemisphere summer, constituting the core of the North American monsoon1,2. As in other tropical monsoons, this rainfall maximum is commonly thought to be thermally forced by emission of heat from land and elevated terrain into the overlying atmosphere3-5, but a clear understanding of the fundamental mechanism governing this monsoon is lacking. Here we show that the core North American monsoon is generated when Mexico's Sierra Madre mountains deflect the extratropical jet stream towards the Equator, mechanically forcing eastward, upslope flow that lifts warm and moist air to produce convective rainfall. These findings are based on analyses of dynamic and thermodynamic structures in observations, global climate model integrations and adiabatic stationary wave solutions. Land surface heat fluxes do precondition the atmosphere for convection, particularly in summer afternoons, but these heat fluxes alone are insufficient for producing the observed rainfall maximum. Our results indicate that the core North American monsoon should be understood as convectively enhanced orographic rainfall in a mechanically forced stationary wave, not as a classic, thermally forced tropical monsoon. This has implications for the response of the North American monsoon to past and future global climate change, making trends in jet stream interactions with orography of central importance.

Evaluation the WRF Model with Different Land Surface Schemes: Heat Wave Event Simulations and Its Relation to Pacific Variability over Coastal Region, Karachi, Pakistan

This study investigates the relative role of land surface schemes (LSS) in the Weather Research and Forecasting (WRF) model, Version 4, to simulate the heat wave events in Karachi, Pakistan during 16–23 May 2018. The efficiency of the WRF model was evaluated in forecasting heat wave events over Karachi using the three different LSS, namely NOAH, NOAH-MP, and RUC. In addition to this we have used the longwave (RRTM) and shortwave (Dudhia) in all schemes. Three simulating setups were designed with a combination of shortwave, longwave, and LSS: E1 (Dudhia, RRTM, and Noah), E2 (Dudhia, RRTM, and Noah-MP), and E3 (Dudhia, RRTM, and RUC). All setups were carried out with a finer resolution of 1 km × 1 km. Findings of current study depicted that E2 produces a more realistic simulation of daily maximum temperature T(max) at 2 m, sensible heat (SH), and latent heat (LH) because it has higher R2 and lower errors (BIAS, RMSE, MAE) compared to other schemes. Consequently, Noah-MP (LSS) accurately estimates T(max) and land surface heat fluxes (SH&amp;LH) because uses multiple physics options for land atmosphere interaction processes. According to statistical analyses, E2 setup outperforms other setups in term of T(max) and (LH&amp;SH) forecasting with the higher Nash-Sutcliffe efficiency (NSE) agreement is 0.84 (0.89). This research emphasizes that the selection of LSS is of vital importance in the best simulation of T(max) and SH (LH) over Karachi. Further, it is resulted that the SH flux is taking a higher part to trigger the heat wave event intensity during May 2018 due to dense urban canopy and less vegetated area. El Niño-Southern Oscillation (ENSO) event played role to prolong and strengthen the heat wave period by effecting the Indian Ocean Dipole (IOD) through walker circulation extension.

Evaluation of the Skill of a Fully-Coupled Atmospheric–Hydrological Model in Simulating Extreme Hydrometeorological Event: A Case Study Over Cauvery River Catchment

The monsoon-driven river basins are more vulnerable to the flash-floods triggered by intense rainfall activities. Due to the lack of adequate high resolution forecast of real-time hydro-meteorological variables, a reliable forecast of flash floods remains a challenge. One plausible way to generate such a high-resolution forecast of hydro-meteorological variables is to use a coupled atmospheric–hydrologic modelling system. Thus, in this study, a physically-based, fully distributed, multi-scale hydrologic modelling framework, WRF-Hydro with optimized configurations (stand-alone and coupled-mode) is used to simulate the important hydro-meteorological variables like precipitation, runoff, soil moisture, and land surface heat fluxes over Cauvery river basin, India. In stand-alone mode, the model is driven by the high-resolution gridded data from the Global Land Data Assimilation System; while the coupled model is run with the WRF atmospheric model. In this study, the ability of a fully coupled WRF–WRF-Hydro modelling framework , with 3 km grid spacing is used to simulate the hydro-meteorological conditions during an extreme rainfall event (08–09 August 2019). The innermost domain of WRF-Hydro in conjunction with a high resolution hydrological routing grid (300 m) is also utilized, to include the subgrid scale disaggregation–aggregation weighting procedures to generate the land–atmospheric feedbacks on the hydrometeorological variables. The resulting variables have been validated through relevant observations; the overall performance of the coupled WRF-Hydro is shown to be relatively good when compared to the WRF-only simulations.

Effects of Cropland Expansion on the Regional Land Surface Radiative Energy Balance and Heat Fluxes in Northern China

Land use change can impact the land surface radiation budget and energy balance by changing surface biophysical processes. Based on satellite remote sensing data and land use data from 2000 to 2015, we quantitatively estimated radiative forcing induced by cropland expansion during the early 21st century in northern China. The results showed that heat flux from the land surface to the atmosphere due to cropland expansion was quite variable in different climate zones. The heat flux increased in humid North China, whereas it decreased in arid Northwest China, semiarid Inner Mongolia, and humid Northeast China. Cropland expansion from woodland areas led to a general decline in the land surface heat flux to the atmosphere, which led to a cooling effect on the climate. The surface heat flux to the atmosphere due to cropland expansion in grassland areas displayed significant variations in different climate zones. The surface heat flux decreased only in humid Northeast China and arid Northwest China. The net surface radiation and latent heat flux both increased when grasslands were changed into cropland, but to different extents, which produced the differences in the surface heat flux to the atmosphere between different zones.

Parameterizing Subgrid Variations of Land Surface Heat Fluxes to the Atmosphere Improves Boreal Summer Land Precipitation Simulation With the NCAR CESM1.2

AbstractSubgrid horizontal variations of land surface heat fluxes to the atmosphere resulting from subgrid land cover heterogeneity are important in land‐atmosphere interaction in global climate models (GCMs). To incorporate it, a parameterization using stochastic sampling based on truncated normal distributions diagnosed from the land model and internal ensemble mean of multiple calls to the planetary boundary layer and deep convection schemes is developed. After its implementation in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.2 (CESM1.2), large changes of simulated land precipitation are found to occur in regions where large subgrid variations of surface heat fluxes exist. The simulated precipitation is improved in boreal summer, especially over eastern China and the coastal areas of the Bay of Bengal. The improved precipitation is mainly a result of improved large‐scale moisture convergence and advection by altered vertical diffusion and convection.

LIDA: A Land Integrated Data Assimilation Framework for Mapping Land Surface Heat and Evaporative Fluxes by Assimilating Space‐Borne Soil Moisture and Land Surface Temperature

AbstractLand surface heat and evaporative fluxes exchanged between the land and atmosphere play a crucial role in the terrestrial water and energy balance. Regional mapping of these fluxes is hampered by the lack of in situ measurements (with the required coverage and duration) and the high spatial heterogeneity. In this paper, we propose a Land Integrated Data Assimilation framework (LIDA) based on the variational data assimilation technique to estimate the key parameters of surface heat and evaporative fluxes by jointly assimilating Soil Moisture Active Passive (SMAP) data and Geostationary Operational Environmental Satellite (GOES) surface temperature data into a coupled parsimonious land water and energy balance model. The method is implemented over an area of 31,500 km2 in the U.S. Southern Great Plains, and its performance is evaluated through consistency tests, comparison tests, and uncertainty analyses. The maps of retrieved heat and evaporative fluxes are used to analyze a range of feedback mechanisms in land‐atmosphere interaction, such as the dependence of evapotranspiration on vegetation and water availability.

Effects of Groundwater Pumping on Ground Surface Temperature: A Regional Modeling Study in the North China Plain

AbstractOverexploitation of groundwater (GW) in the North China Plain (NCP) since the 1960s has many environmental consequences. However, mechanistic understanding of this perturbation remains limited, particularly at the regional scale. In this study, the coupled ParFlow.CLM model representing subsurface and land surface processes and their interactions was applied in the NCP at high spatiotemporal resolutions. The model was validated using the water and energy fluxes reported in previous studies and from the JRA‐55 reanalysis. Numerical experiments were designed to examine the impacts of GW pumping and irrigation on the ground surface temperature (GST). Results show significant effects of GW pumping on GST in the NCP. Generally, the subsurface acts as a buffer to temporal variations in heat fluxes at the land surface, but long‐term pumping can gradually weaken this buffer, leading to increases in the spatiotemporal variability of GST, as exemplified by hotter summers and colder winters. Considering that changes of water table depth (WTD) can significantly affect land surface heat fluxes when WTD ranges roughly between 0.01 and 10 m, the 0.5‐m/yr increase of WTD simulated by the model due to pumping can continue to increase the regional averaged WTD and hence, perturb GST for about 20 years after GW pumping began in the NCP, before WTD exceeds 10 m. The variations of GST are expected to increase faster initially and gradually slow down due to the nonlinear behaviors of GST with WTD. The findings from this study in the NCP may also have implications for other regions with GW depletion.

The trends in land surface heat fluxes over global monsoon domains and their responses to monsoon and precipitation

The climatology, trends and leading modes of land surface latent heat flux (LHF) and sensible heat flux (SHF) as well as their responses to monsoon and precipitation in global land monsoon domains are presented. During the past three decades, LHF and SHF have generally undergone a rising and decreasing trend (that is, (LHF+, SHF−)), respectively, in Asian, North African, Austrian, and South American monsoon domains. Moreover, the increasing rate of LHF was higher than the decreasing rate of SHF, which causes a decreased trend in Bowen ratio. Two other dominant trend patterns, (LHF−, SHF−) and (LHF+, SHF+), are observed in South African and South American monsoon domains, respectively. The trends in LHF and SHF are closely linked to increasing global monsoon intensity and precipitation, especially for the monsoon domain that has annual precipitation lower than 1300 mm yr−1. Singular value decomposition (SVD) analyses show that monsoon strength explains 25.2% and 22.2% total covariance of LHF and SHF respectively in the first modes, and that precipitation slightly raises the percentages up to 27.8% and 24% respectively. The increasing monsoon and precipitation on one hand favor more land surface available energy being converted into LHF; on the other hand they enhance the LHF by increasing the land surface net radiation. Moreover, remarkable phase shifts in LHF and SHF are observed for monsoon domains during late-1990s, which are in phase with those of precipitation and monsoon strength. The intensifying LHF and precipitation indicate the acceleration of hydrological cycle in global terrestrial monsoon domains.

Land-surface processes and summer-cloud-precipitation characteristics in the Tibetan Plateau and their effects on downstream weather: a review and perspective.

Correct understanding of the land-surface processes and cloud-precipitation processes in the Tibetan Plateau (TP) is an important prerequisite for the study and forecast of the downstream activities of weather systems and one of the key points for understanding the global atmospheric movement. In order to show the achievements that have been made, this paper reviews the progress on the observations for the atmospheric boundary layer, land-surface heat fluxes, cloud-precipitation distributions and vertical structures by using ground- and space-based multiplatform, multisensor instruments and the effect of the cloud system in the TP on the downstream weather. The results show that the form drag related to the topography, land–atmosphere momentum and scalar fluxes is an important part of the parameterization process. The sensible heat flux decreased especially in the central and northern TP caused by the decrease in wind speeds and the differences in the ground-air temperatures. Observations show that the cloud and precipitation over the TP have a strong diurnal variation. Studies also show the compressed-air column in the troposphere by the higher-altitude terrain of the TP makes particles inside clouds vary at a shorter distance in the vertical direction than those in the non-plateau area so that precipitation intensity over the TP is usually small with short duration, and the vertical structure of the convective precipitation over the TP is obviously different from that in other regions. In addition, the influence of the TP on severe weather downstream is preliminarily understood from the mechanism. It is necessary to use model simulations and observation techniques to reveal the difference between cloud precipitation in the TP and non-plateau areas in order to understand the cloud microphysical parameters over the TP and the processes of the land boundary layer affecting cloud, precipitation and weather in the downstream regions.