Overview
Jiameng's research explores the interactions between the terrestrial biosphere, hydrosphere, climate and anthropogenic drivers at multiple scales.
To achieve that, she integrated state-of-the-art theoretical advances, satellite observations and other innovative multi-source data products,
terrestrial biosphere modeling, data assimilation, and machine learning, to seek knowledge advance and breakthrough solutions for challenges
in sustainable development over diverse ecosystems.
Currently her research programs are focused on the following two themes:
[1] For natural/agricultural ecosystems, how to understand and predict the long-term response/feedbacks of carbon-water cycle to climate change/variability?
(show description)
The exchange of carbon and water between atmosphere and terrestrial biosphere plays a sginificant role in regulating Earth's climate.
Jiameng's researches aim to understand both the long-term trajectory and inter-annual variability of terrestrial photysynthesis,
evapotranspiration, and related processes in response to the climate change, CO2 fertilization, land use/cover change, and environmental stresses.
[2] For urban ecosystems, how to better monitor, understand, and adapt to the human-induced climate modifications? (show description)
Urban Heat Island (UHI) is one of the clearest examples of human-induced climate modifications. Jiameng's researches attempted to address
challenges in UHI monitoring, and to advance understanding of the multi-scale UHI variabilities as well as the underlying mechanisms.
Theme 1: understanding and predicting the long-term response/feedbacks of carbon-water cycle to climate change/variability
Ongoing projects
Effect of explicit consideration of mesophyll diffusion to carbonyl sulfide (OCS) simulation and implication to GPP estimate [show more]
OCS is an atmospheric trace gas which can serve as a photosynthetic tracer, as it shares a similar pathway with CO2 while diffusing from the air to plant cells.
Mesophyll acts as one major barrier to both CO2 and OCS diffusion. However, current terrestrial biosphere models do not take explicit consideration of mesophyll diffusion.
This project shows that an explicit implementation of mesophyll diffusion in models can lead to a better agreement between simulation and site measurement of OCS fluxes,
and the simulated mesophyll-explicit OCS can provide new insight on estimates of global GPP budget.
A paper related to this project (Jiameng is the first author) was in prinple accepted by Nature.
Contribution of mesophyll diffusion to historical increase of C13 discriminations [show more]
Much information of photosynthesis and carbon cycling was embedded in the stable carbon isotope, as plants discriminate against heavier carbon isotope.
The process of isotope discrimination has been implemented in most terrestrial biosphere models (TBMs). However, with NCAR CLM5,
we found the standard equation cannot reproduce the historical long-term increase of isotope discrimination as deduced from atmospheric 13C/12C measurements.
We attributed such a mismatch to the missed representation of photorespiration and, particularly, mesophyll diffusion.
Updating the discrimination equation by leveraging a mechanistic mesophyll diffusion model, we reproduce the trend towards a larger discrimination under higher CO2 levels:
globally the trend is 0.014‰ ppm−1, consistent with atmospheric measurements.
A draft paper related to this project (Jiameng is the first author) has been finished.
Historical trend of water use efficiency (WUE) and its drivers [show more]
Historical increase in WUE (ratio of gross photosynthesis to transpiration) was found responding to the rising CO2.
However, the magnitude and evolution of such an increase over various biomes and scales are poorly understood, and the factors driving such an increase remain debatable.
This ongoing project aims to improve our understanding of the historical WUE trends under changing climate and enviromental stresses.
Assimilating LAI and soil moisture using CLM5-DART for a better carbon monitoring in East Africa [show more]
This ongoing project aims to use CLM5-DART to assimilate MODIS LAI and SMAP soil moisture in East Africa, and analyze how data assimilation affect the carbon cycle modeling.
Previous project
Agriculture and water sustainability in Northwestern China [show more]
This project focused on Northwestern China, which is one of the major global hotspots undergoing massive terrestrial water storage (TWS) depletion.
However, unlike many of other hotspots, drivers underlying the region-wide depletion remain controversial over this dryland ecosystem.
Utilizing diverse observations, we found persistent cropland expansion by >1.2 × 104 km2 since 2003, leading to growth of 59.9% in irrigated area and 19.5% in agricultural water use,
despite a steady enhancement in irrigation efficiency. Correspondingly, a substantially faster evapotranspiration (ET) increase occurred in crop expansion areas, whereas precipitation exhibited no long-term trend.
This enhanced evaporative water loss is the most plausible and ultimate cause underlying the region-wide water depletion.
A paper related to this project (Jiameng is the first author) was published on Environmental Research Letters [link].
The long-term dynamics of TWS in China from 2003–2019.
Theme 2: better monitoring, understanding, and adapting to the human-induced climate modifications
Reconciling debates on the controls on surface urban heat island (SUHI) intensity [show more]
- Variabilities of SUHI intensity (SUHII) were under control of three types of factors (surface property, background climate/weather conditions, and overall urban metric).
We show that the priority of types of controls are dependent closely on the scale and sampling criteria.
- Contributions from climate condition to SUHII gradually decrease with increasing temporal scale.
- No common rank exists in the relative importance of main types of SUHII controls over different spatial scales.
- Sampling style of city cluster by urban area or climate zone contributes to debates on ranks of SUHII controls.
- A paper related to this project (Jiameng is the first author) was published on Geophysical Research Letters [link].
Relative importance of the three types of SUHII control on multiple temporal scales. Each data point denotes one city, and the different locations of dots denote the different priority of the three types of factors on controling the SUHII variability. For more information about the figure, please see the paper[link].
Attribution analysis of the daily variations in the nighttime surface urban heat islands [show more]
- The overall intensity as well as footprint of the SUHI was quantified for 59 Chinese cities, using the Gaussian model.
- Large variaions on the SUHI were demonstrated, not only over the inter-annual/intra-annual scale, but also over the day-to-day scale.
- The day-to-day variations in the SUHI are mainly controlled by meteorological variables.
- Meteorological controls on the SUHI intensity are larger in temperate than in subtropical zones.
- A paper related to this project (Jiameng is the first author) was published on Remote Sensing of Environment [link].
Correlation analysis for mid-term SUHIs and day-to-day SUHIs.The numbers are percentages of megacities where there is a significant correlation (p < 0.05) between the associated SUHI variables and explanatory factors.
Estimation of the next-day nighttime surface urban heat islands [show more]
- A simple yet efficient approach was proposed to statistically estimate the next-day nighttime surface urban heat islands.
- Estimators related to the SUHI day-to-day variations largely contribute to the estimation
- The estimated SUHI intensities have an averaged MAE of 0.67 K.
- A paper related to this project (Jiameng is the first author) was published on ISPRS Journal of Photogrammetry and Remote Sensing [link].
Estimation performance of the next-day SUHIIs in the chosen cities. (a) shows the spatial distribution of the MAE (K). (b) provides the relationship between the estimated next-day SUHIIs and observed SUHIIs, with the dot colors representing the estimated absolute errors. (c) exhibits the boxplot for MAE. (d) displays the MAPE histogram.
Satellite-based investigation on the typical diurnal patterns of surface urban heat islands [show more]
- The satellite-based SUHI variations over a full diurnal cycle were re-constructed, using a four-parameter DTC model.
- Diurnal climatology of the SUHI was estimated for Chinese 354 cities.
- Five typical diurnal patterns of the SUHI intensity were identified.
- Diurnal SUHI patterns are partly controlled by urban-rural NDVI differences.
- A paper related to this project was published on Remote Sensing of Environment (Jiameng is the first author) [link].
The identified five typical diurnal patterns of the surface urban heat island intensity.
Investigation on the impacts from the quality of satellite land surface temperature product on the surface urban heat island estimation [show more]
- The possible biases in the satellite-based SUHI estimation induced by the land surface temperature quality were emphasized.
- Introducing satellite data quality control can modify the SUHI intensity (SUHII) by 24.3% (29.9%) during the day (night).
- Significant north-south contrast in the SUHI variations caused by LST quality was found over Chinese cities.
- A paper related to this project was published on ISPRS Journal of Photogrammetry and Remote Sensing (Jiameng is the first author) [link].
The daytime SUHII variations induced by satellite data quality.
The nighttime SUHII variations induced by satellite data quality.
Reduction in urban heat island during COVID-19 lockdown period [show more]
- Significant decline in both surface and canopy urban heat island was identified over China during COVID-19 lockdown.
- Surface (canopy) UHI intensity is reduced by 0.25 K (0.42 K) and 0.23 K (0.39 K) on average during the day and night, respectively.
- Hourly variations of impact from COVID-19 lockdown on UHI were reported
- A paper related to this project was published on Geophysical Research Letters (Jiameng is the co-first author) [link].
- This work was reported by Inside Climate news [link]
Comparison of the variations in surface UHI intensity (i.e., ΔIs, dark red lines, left y-axis)
and canopy UHII (i.e., ΔIc, dark blue lines, right y-axis) during lockdown periods.