Vegetation change in the regional surface climate over East Asia due to global warming using BIOME4

This study investigates the possible changes in the regional surface climate due to global warming from a MM5 downscaling simulation for the period of 1971-2100. The main focus of this study is to observe the changes in vegetation types over East Asia. BIOME4, an equilibrium terrestrial biosphere model, is utilized to simulate vegetation patterns. Regional projections of this study show the increase of surface air temperature by 5◦C and precipitation by 6% over East Asia in the end of the 21st century. The present study also noticed that the increasing trend of temperature is associated with the increasing trends of the minimum temperature of the coldest month. Therefore, the region of favorable temperature conditions for vegetation growth in lower latitudes seems to extend toward the higher latitude. It leads to a northward shift of vegetation distribution in the lower latitudes besides the area extension. For instance, the trend in which the warm mixed forest and temperate deciduous forest shift northward may be distinguished. At the same time, the area of temperate deciduous forest pervades the area and replaces temperate grassland regions. Of interest, the tropical evergreen forest is expected to appear over southern China in the end of the 21st century. The possible vegetation changes are mainly affected by a temperature increase rather than a precipitation increase

Retrieving forest soil moisture from SMAP observations considering a microwave polarization difference index (MPDI) to τ-ω model

Estimating soil moisture from microwave brightness temperature is extremely challenging in densely vegetated areas. The soil moisture retrieved from the Soil Moisture Active Passive (SMAP) measurements tends to be consistently overestimated, sometimes exceeding the saturation level of mineral soils. Therefore, the retrieved soil moisture cannot detect or monitor climate extremes, such as floods and droughts for forests, natural resource management, and climate change research. We hypothesize that the main issue is that the scattering albedo (ω) and the optical depth (τ) are parameterized solely with NDVI (Normalized Difference Vegetation Index), neglecting the polarization characteristics from vegetation structure. This study proposes a weighting factor between scattering and optical thickness, a function of MPDI (Microwave Polarization Difference Index), and applies it to both parameters simultaneously to increase the scattering effect and decrease the attenuation effect in high MPDI. The validation results based on the Climate Reference Network revealed that considering MPDI is critical in reducing soil moisture overestimation errors and obtaining more accurate soil moisture over forested regions. This results in correlation improving from 0.36 to 0.44, a decrease in ubRMSE from 0.179 to 0.125 cm³cm-³, and bias lowering from 0.127 to 0.060 cm³cm-³ in comparison with the SMAP measurements over forested regions