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The representation of groundwater dynamics in land surface models and their roles in global precipitation variations has received attention in recent years. Studies have revealed the overall higher soil moisture but rather diverse precipitation changes after incorporating the groundwater component in climate models. However, groundwater effects on large-scale atmospheric energy transport, the fundamental atmospheric variable regulating Earth’s climate, have not been explored thoroughly. In this study, a pair of idealized experiments corresponding to contrast globally fixed water table depths by AMIP-type simulations in the Community Earth System Model was conducted. In the wet (shallow water table) experiments, an increased meridional surface temperature gradient makes the mean meridional energy transports and Hadley circulation stronger than dry (deep water table) experiments over the tropics. Such energy transport changes are primarily attributed to the dynamic contribution (intensified Hadley circulation). The wet experiments make the simulated world be like an aquaplanet simulation with less land–sea temperature contrast and the enhancement (reduction) of mean meridional circulation (stationary eddies) energy transports. Furthermore, the South Asian monsoon circulation in the wet experiment shows a southward shift in the premonsoon season (April–June) and slight weakening in the mature phase (July and August). This study explores the impacts of the soil conditions caused by various water table depths on global energy transport and has further implications for climate model developments and experiment designs.

Fog plays a vital role in maintaining ecosystems in montane cloud forests. In these forests, a large amount of water on the surface of leaves and canopy (hereafter canopy water) evaporates during the morning. This biophysical process plays a critical factor in regulating afternoon fog formation. Recent studies have found that alterations in precipitation, temperature, humidity, and CO2 concentrations associated with future climate changes may affect terrestrial hydroclimatology, but the responses in cloud forests remain unclear. Utilizing numerical experiments with the Community Land Model, we explored changes in surface evaporative fluxes in Chi-Lan Mountain cloud forests in northeastern Taiwan under the RCP8.5 scenario with changes in the aforementioned various atmospheric variables. The results showed that increased rainfall intensity in climate change runs decreased the accumulation of canopy water, while larger water vapor concentrations led to more nighttime condensation on leaves. Elevated CO2 concentrations did not greatly impact canopy water amounts, but photosynthesis was enhanced, while transpiration was reduced and contributed to decreased latent heat fluxes, implying the importance of forest plant physiology in modulating land evaporative fluxes. Evapotranspiration decreased in Chi-Lan due to multiple combined factors, in contrast to the expected intensification in the global water cycle under global warming. The study, however, is restricted to an offline land surface model without land–atmosphere interactions and the interactions with adjacent grids, which deserves further analyses for the water cycle changes in the montane cloud forest regions.

Deforestation is a major issue affecting both regional and global hydroclimates. This study investigated the effect of deforestation in the Maritime Continent (MC) on tropical intraseasonal climate variability. Using a global climate model with Madden–Julian Oscillation (MJO) simulations, we examined the effect of deforestation over the MC region by replacing the forest canopy with grassland. The results revealed that under constant orographic and land–sea contrast forcing, the modification of the canopy over the MC altered the characteristics of the MJO. We noted the amplification of the MJO and increases in wet–dry fluctuation and the zonal extent. We analyzed more than 100 MJO cases by performing K-means clustering and determined that the continuous propagation of the MJO over the MC increased in 35% and 61% of the total 110 cases in the control and deforestation experiments, respectively. This phenomenon was associated with more substantial vanguard precipitation, increased soil moisture, and a suppressed diurnal cycle in land convection. Furthermore, when the MJO convection was over the Indian Ocean (IO), we observed the enhancement of low-level moisture over the MC region in the deforestation experiment. Grassland surface forcing provides a thermodynamic source for triggering instability in the atmosphere, resulting in low-level moisture convergence. The MJO exhibited a stronger energy recharge–discharge cycle in the deforestation experiment than in the control experiment, and this difference between the experiments enlarged from the IO to MC.

Anthropogenic land-use change, irrigation, is considered to strongly modulate the hydroclimate at the regional scale by directly triggering evaporative cooling as the preliminary local effect. However, subsequent interactions with the background climate are highly nonlinear, which introduces diverse and unexpected consequences. The North China Plain (NCP) is one of the regions where irrigation has expanded most rapidly since the 20th century. The scarce rainfall in this region makes it necessary for irrigation to supplement the level of soil water for agricultural production. In this study, we quantify the effect of irrigation on the regional climate in China. Two regional climate models, WRF and RegCM, are used to mimic the large-scale practice of irrigation on the NCP. The results of our experiments show consistent cooling and moistening effects centered over the NCP across all experiments. Although the moisture budget and wind field pattern demonstrate that the vertical downdraft and low-level divergence could inhibit rainfall, the humidification dominates the climatic response in the dry April-May-June and increases the amount of precipitation significantly and consistently in the NCP region and the surrounding area in northern China. The enhanced CAPE increase sharply on some ‘calm days’ when the vertical moisture advection is small, especially during afternoon, triggering frequent light rains convectively by destabilizing the atmosphere. The consistent response to irrigation in two different models that employ structurally different land surface schemes could enhance the robustness of the physical mechanism behind the precipitation increase in the heavily irrigated region of NCP.

During the past two decades, the Maritime Continent (MC) has experienced increased deforestation1,2. Using hundred-year long ensemble idealized deforestation experiments conducted with the fully-coupled Community Earth System Model (CESM) V1.2, here we show that the MC deforestation have a potential to alter the complexity (i.e., event-to-event differences) of the El Niño-Southern Oscillation (ENSO) in terms of its spatial pattern and temporal evolution. The deforestation model run increases the occurrences of Central Pacific El Niño and multi-year La Niña events compared to the control experiment. This change in ENSO complexity is caused by the strengthening effect of MC deforestation on subtropical ENSO dynamics. Conventional tropical ENSO dynamics influence ENSO occurrence and evolution through variations in the tropical Pacific thermocline and related tropical ocean-atmosphere interactions. However, subtropical ENSO dynamics govern the ENSO through coupling processes originated from the subtropical North Pacific. The MC deforestation in our idealized experiment accompanies an anomalous local overturning, which further alters the mean strength of the North Pacific subtropical high and strengthens subtropical ENSO dynamics. Therefore, MC deforestation has the potential to make the El Niño more complex and less predictable.

The NCAR Community Earth System Model is used to study aerosol direct effect on Indian summer monsoon (ISM). We perform two sets of 30-year simulations subject to prescribed perpetual SST annual cycle: CTL and AERO. The two differ by anthropogenic emissions over Indian Peninsula that is included in AERO. We examine the differences in the onset and withdrawal between CTL and AERO. The results show that, relative to the ISM evolution in CTL, the transition of ISM from spring to fall in AERO exhibits a similar ensemble-mean onset date with larger spread and more abrupt change, and an earlier but more gradual withdrawal. The difference is related to aerosols-induced circulation changes in the pre-monsoon environment, including upward motion from the Ganges basin to Indian Peninsula, and strengthened anticyclonic circulation over the Arabia Sea and eastern Bay of Bengal. The changes in AERO-CTL for the developed monsoon period feature a northward shift of monsoon flow such that westerly within 10°-20°N is weaker but the tropical ITCZ (0°-10°N) and the local meridional circulation over northern India are stronger. The earlier monsoon withdrawal in AERO relative to CTL is attributed to the aerosol induced anticyclonic flow within 10°-25°N and cyclonic flow within 0°-10°N over eastern India and Bay of Bengal that resemble the transitional changes in the monsoon withdrawal. The anthropogenic aerosols also cause a 16% (32%) increase in concentration (AOD) by natural dust over India that is transported from the Middle East by aerosols-induced westerly wind in the pre-monsoon season.

雲霧森林是經常性受到雲霧籠罩所影響的森林生態系。雲霧對於當地有調節水分與能量的作用，是維持該生態系平衡的重要因子。過去研究指出，大量樹冠水在早晨受太陽加熱蒸發，造成潛熱通量的峰值提前而有利於當地雲霧生成。但在氣候變遷下，降水、溫度、濕度及二氧化碳濃度的改變可能影響樹冠水的累積，進而改變地表通量和雲霧生成。本研究利用NCAR地表過程模式，搭配棲蘭雲霧森林及蓮華池森林的大氣觀測資料，以及TCCIP模式的未來氣候推估資料，討論氣候變遷影響雲霧森林樹冠水及地表通量的機制。結果顯示未來增強的降水強度將不利於樹冠水累積，但大氣增溫造成的水氣量增加卻有助於夜間露水凝結，使氣候變遷下平均的樹冠水量增加。二氧化碳濃度的增加對樹冠水量沒有明顯影響，但會提升光合作用效率並造成氣孔縮小而使蒸散量降低。 暖化下增加的樹冠水，提升了雲霧森林在早晨的潛熱通量，但全天平均的潛熱通量則因降水截留的減少而下降，然而其中氣溫提升所造成的潛熱通量增加仍扮演緩解降水強度變強對雲霧森林衝擊的角色。植被透過蒸散作用調節其表面溫度，是暖化下有利夜間露水凝結的重要因素，而在二氧化碳提升下所增加的光合作用速率亦能調節當地二氧化碳濃度的變化，顯示雲霧森林中植被在氣候變遷下的重要性。 雲霧森林中的地表通量在氣候變遷下的改變也會同時透過陸地與大氣間的交互作用而影響到當地的大氣穩定度與邊界層發展等，因此未來將利用大氣與陸地耦合模式並考慮雲霧與山谷風環流在雲霧森林中的關係，進一步討論未來氣候變遷下雲霧森林內的水與能量循環的變化。 Cloud-fog forest is known as a forest ecosystem governed by frequent fog immersion. Fog plays a vital role in maintaining the ecosystem’s equilibrium in montane cloud forests, where a large amount of canopy water evaporates in the morning, being a critical factor for fog formation. Recent studies found that precipitation, temperature, humidity changes, and elevated CO2 concentration under climate change may affect the canopy water amount and surface fluxes in cloud forests, but the mechanisms remain unclear. We explore the changes in surface flux characteristics in the Chi-Lan montane cloud forest under climate change by using the NCAR Community Land Model, in-situ observation from Chi-Lan cloud forest and Lien-Hua-Chih forest, and future climate scenarios from TCCIP modelling outputs. Results show that the future intensified rainfall is unfavorable for canopy water accumulation, while more water vapor under future warming leads to more nighttime condensation on leaves. Elevated CO2 concentration does not greatly impact canopy water amount, but the photosynthesis efficiency is enhanced and the transpiration is suppressed under higher CO2 concentration. The combining results show overall increased canopy water under various climate changes. It promotes strong canopy evaporation when sun rises, but the total daytime evaporation still decreases due to the decreased intercepted rainfall. The response of canopy water and surface fluxes under rising temperature mitigates the impact of higher precipitation intensity on cloud forests. The regulating factor of vegetation temperature plays a critical role in the increasing canopy water under a warming climate. The increased photosynthesis under elevated CO2 weakens the local change of CO2 concentration, implying the importance of vegetation in forests under climate change. The atmosphere can interact with the land surface through the adjusted surface fluxes under climate change. Therefore, future work may require coupled land and atmosphere model simulations and considering changes of fog and local circulations in the future scenario to explore the impact of climate change on cloud forests. &nbsp

Terrestrial water storage anomaly (TWSA) is a critical component of the global water cycle where improved spatiotemporal dynamics would enhance exploration of weather and climate-linked processes. Thus, correctly simulating TWSA is essential not only for water-resource management but also for assessing feedbacks to climate through land-atmosphere interactions. Here we evaluate simulated TWSA from 25 climate models (from the Climate Model Intercomparison Project 6) through comparison with TWSA from GRACE satellite data (2003 – 2014) in 14 river basins globally and assess causes of discrepancies by examining precipitation (P), evapotranspiration (ET), and runoff (Roff) fluxes during recharge (increasing TWS) and discharge (decreasing TWS) cycles. Most models show consistent biases in seasonal amplitudes of TWS anomalies relative to GRACE output: higher modeled amplitudes in river basins in high northern latitudes, Parana, and Congo, and lower amplitudes in most mid-latitude basins and other tropical basins. This TWSA systematic bias also exists in the previous CMIP5 simulations. Models overestimate P compared to observed P datasets in 7 out of 14 basins, which increases (decreases) seasonal storage amplitude relative to GRACE in the recharge (discharge) cycle. Overestimation (underestimation) of runoff is another common contributing factor in the discharge phase that increases (decreases) TWSA amplitudes relative to GRACE in 5 river basins. The results provide a comprehensive assessment of the reliability of the simulated annual range in TWSA through comparison with GRACE data that can be used to guide future model development.

During the past two decades, the Maritime Continent (MC) has experienced increased deforestation1. Here we show with idealized coupled climate model experiments that deforestation in the MC has the potential to change the complexity (i.e., event-to-event differences) of the El Niño-Southern Oscillation (ENSO) in three key aspects: its spatial pattern, temporal evolution, and amplitude variation. The deforestation alters the relative strengths of the tropical and subtropical types of ENSO dynamics, leading to the changes in ENSO complexity. The strengths of the tropical and subtropical ENSO dynamics are comparable in the control run but the subtropical ENSO dynamics is intensified in the deforestation run. As a result, the deforestation run shows increases in Central Pacific and multi-year La Niñas and re-intensified El Niño events (resembling the 2014-15-16 Super El Niño) compared to the control run. The mechanism for these changes involves an anomalous local overturning circulation over the MC that alters the mean strength of the North Pacific subtropical high resulting in a strengthening of the subtropical ENSO dynamics. The intensified subtropical ENSO dynamics enables a MC-deforested world to produce more complex ENSO events.

One of the critical components in understanding the climate system is the interaction between the land and the atmosphere. Whereas previous studies on land–atmosphere coupling mostly focus on its spatial hotspots, we explore the temporal evolution of land surface coupling strength (LCS) during a large-scale flood event in a semiarid region in northern Australia. The LCS indicates the relationship between soil moisture and latent heat flux, and the spatiotemporal variability in precipitation and soil water strongly affects the variability of LCS. The LCS is usually positive in the semiarid climate, where evapotranspiration (ET) occurs under the soil moisture–limited regime and thus increases with soil moisture. However, our analyses of combined land surface modeling and observational datasets show high temporal variability of LCS in the course of the extreme flood event followed by a drying period. The wet regions transferred the ET regime from the soil moisture–limited to the transition section, weakening the linear growth of ET with soil moisture, which resulted in the decline of LCS. The LCS remained weak until the flood retreated and the soil water approached the prestorm average state. Such temporal variation of the LCS has important implications for realistic parameterization of the land–atmosphere coupling and consequently improving subseasonal to seasonal climate forecast.

Water scarcity (WS) is projected to increase as a result of future climate and population changes, and its impacts will be hazardous to vulnerable groups of people in South Asia (SA). We present the first assessment of WS in SA under the Paris Agreement, using two global hydrological models (GHM) forced by three global climate models (GCM) under the RCP 6.0. Results show that a significant alteration in the hydrological fluxes contributes to the decline in water availability, along with an intense increase in water consumption that augments WS. The seasonal shifting in WS significantly increases the population affected by approximately 16% in June to September (JJAS) to 42% in December to February (DJF) under 1.5 ºC warming. We also highlight spatial hotspots of WS in SA, including North-central, Northwestern, and Southern India, Eastern Pakistan, Northern, and Northwestern Bangladesh. We observe a 1.5 ºC temperature increase as a critical point for WS in SA with a profound impact on 875 million people and suggest the Paris Agreement temperature target of even 1.5 ºC will not ubiquitously alleviate future warming-driven WS. Hence, immediate mitigations and legislations are required to curtail WS in SA.

The impact of land–atmosphere anomaly coupling on land variability is investigated using a new two-stage climate model experimental design called the “GLACE-Hydrology” experiment. First, as in the GLACE-CMIP5 experiment, twin sets of coupled land–atmosphere climate model (CAM5-CLM4.5) ensembles are performed, with each simulation using the same prescribed observed sea surface temperatures and radiative forcing for the years 1971–2014. In one set, land–atmosphere anomaly coupling is removed by prescribing soil moisture to follow the control model’s seasonally evolving soil moisture climatology (“land–atmosphere uncoupled”), enabling a contrast with the original control set (“land–atmosphere coupled”). Then, the atmospheric outputs from both sets of simulations are used to force land-only ensemble simulations, allowing investigation of the resulting soil moisture variability and memory under both the coupled and uncoupled scenarios. This study finds that in midlatitudes during boreal summer, land–atmosphere anomaly coupling significantly strengthens the relationship between soil moisture and evapotranspiration anomalies, both in amplitude and phase. This allows for decreased moisture exchange between the land surface and atmosphere, increasing soil moisture memory and often its variability as well. Additionally, land–atmosphere anomaly coupling impacts runoff variability, especially in wet and transition regions, and precipitation variability, although the latter has surprisingly localized impacts on soil moisture variability. As a result of these changes, there is an increase in the signal-to-noise ratio, and thereby the potential seasonal predictability, of SST-forced hydroclimate anomalies in many areas of the globe, especially in the midlatitudes. This predictability increase is greater for soil moisture than precipitation and has important implications for the prediction of drought.

sites_information.csv is the location, codename,land type of study sites. CCH_open_*_2018_2019_daily.csv are the daily Tmax/Tmin/DTR in the open field from 2018to 2019. CCH_forest_*_2018_2019_daily.csv are the daily Tmax/Tmin/DTR in the understory from 2018to 2019. CCH_forest_*_annual_avg.csvare themeandaily Tmax/Tmin/DTRin the understory from2018to 2019. CCH_open_*_annual_avg.csvare themeandaily Tmax/Tmin/DTRin the understory from2018to 2019. CCH_IOP_*.csv is the mean air temperature/visibilityevery 30/10 mins during IOP. 202001_05_CL*norain_temp.csvare themeanair temperature every 30 minsin fog/non-fog days. 2008_2011_CL*_radiation.csvare themean radiationevery 30 minsin fog/non-fog days. &nbsp

Hydro-climate in the montane cloud forest (MCF) regions is unique for its frequent fog occurrence and abundant water interception by tree canopies. Latent heat (LH) flux, the energy flux associated with evapotranspiration (ET), plays an essential role in modulating energy and hydrological cycles. However, how LH flux is partitioned between transpiration (stomatal evaporation) and evaporation (non-stomatal evaporation), and how it impacts local hydro-climate remain unclear. In this study, we investigate how fog modulates the energy and hydrological cycles of MCF by using a combination of in-situ observations and model simulations. We compare LH flux and associated micrometeorological conditions at two eddy-covariance sites—Chi-Lan (CL), a MCF, and Lien-Hua-Chih (LHC), a non-cloud forest in Taiwan. The comparison between the two sites reveals an asymmetric LH flux with an early peak at 9:00 in CL as opposed to LHC, where LH flux peaks at noon. The early peak of LH flux and its evaporative cooling dampen the increase in near-surface temperature during the morning hours in CL. The relatively small diurnal temperature range, abundant moisture brought by the valley wind, and local ET result in frequent afternoon fog formation. Fog water is then intercepted by the canopy, sustaining moist conditions throughout the night. To further illustrate this hydrological feedback, we used a land surface model to simulate how varying canopy water interception can affect surface energy and moisture budgets. Our study highlights the unique hydro-climatological cycle in MCF and, specifically, the inseparable relationship between the canopy and near-surface meteorology during the diurnal cycle.

Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.

As the global atmosphere warms, water vapor concentrations increase with rising temperatures at a rate of 7%/K. Precipitation change is associated with increased moisture convergence, which can be decomposed into thermodynamic and dynamic contributions. Our previous studies involving Coupled Model Intercomparison Project Phase 3 (CMIP3) projections have suggested that seasonal disparity in changes of global precipitation is primarily associated with the thermodynamic contribution. In this study, a vertically integrated atmospheric water budget analysis using multiple reanalysis datasets demonstrated that dynamic changes played a significant role in seasonal precipitation changes during 1979–2008, especially in the global average and ocean average. The thermodynamic component exhibited almost consistent magnitude in the contribution of seasonal precipitation changes during 1979–2008 in both CMIP5_AMIP models and reanalysis datasets, whereas the dynamic component (related to the tendency of ω and water vapor climatology) made a lower or negative contribution in the CMIP5_AMIP models compared with the reanalysis datasets. Strengthened (weakened) ascending and descending motions in the reanalysis datasets (CMIP5_AMIP models), which were indicative of strengthened (weakened) seasonal mean circulation, tended to increase (reduce) precipitation in the wet season and reduce (increase) precipitation in the dry season during the study period. Vertical profiles of the tendency of moist static energy in the mid-to-upper troposphere suggested a trend toward stability in the CMIP5_AMIP models and one toward instability in the reanalysis datasets. Such disagreement in stability might be related to the different warming tendency in the mid-to-upper troposphere over the tropics.

Bangladesh has experienced multiple freshwater issues including salinization from monsoonal floods and groundwater over-pumping that induces severe land subsidence. Therefore, using satellite observations to virtually build a monitoring network becomes an efficient and innovative means. We focus on the Sylhet Mymensingh haor area that has the highest annual precipitation and the largest inundation area in northeastern Bangladesh. The modified normalized difference water index is first used to extract water area from MODIS and Landsat-5/-7/-8 optical imageries. A weekly flood chance model is then created from a sequence of images to recover water extent from the cloud-covered images. Using MODIS images for water identification achieves an overall accuracy of 84% in rainy season and 41% in dry season as validated with Sentinel-1A radar images. This model can be further used to refine the Shuttle Radar Topography Mission digital elevation model (DEM). As compared with ICESat laser altimetry, the root-mean-square of the height difference is improved from 1.65 m to 1.16 m after DEM modification. By combining the recovered water area and the refined DEM, surface water volume (WV) is quantified. A comparison with the Gravity Recovery And Climate Experiment (GRACE) gravimetry retrieved equivalent water heights (EWHs) in 2002 - 2015 is conducted, where the correlation coefficient and root-mean-square of the EWH difference are 91.7% and 0.09 m, respectively.

From the 1980s, Indian summer monsoon rainfall (ISMR) shows a decreasing trend over north and northwest India, and there was a significant observed reduction in July over central and south India in 1982-2003. The key drivers of the changed ISMR, however, remain unclear. It was hypothesized that the large-scale irrigation development that started in the 1950s has resulted in land surface cooling, which slowed large-scale atmospheric circulation, exerting significant influences on ISMR. To test this hypothesis, a fully coupled model, the CESM v1.0.3, was used with a global irrigation dataset. In this study, spatially varying irrigation-induced feedback mechanisms are investigated in detail at different stages of the monsoon. Results show that soil moisture and evapotranspiration increase significantly over India throughout the summertime because of the irrigation. However, 2-m air temperature shows a significant reduction only in a limited region because the temperature change is influenced simultaneously by surface incoming shortwave radiation and evaporative cooling resulting from the irrigation, especially over the heavily irrigated region. Irrigation also induces a 925-hPa northeasterly wind from 30°N toward the equator. This is opposite to the prevailing direction of the Indian summer monsoon (ISM) wind that brings moist air to India. The modeled rainfall in the irrigated case significantly decreases up to 1.5 mm day-1 over central and north India from July to September. This paper reveals that the irrigation can contribute to both increasing and decreasing the surface temperature via multiple feedback mechanisms. The net effect is to weaken the ISM with the high spatial and temporal heterogeneity. © 2018 American Meteorological Society.