Permafrost is undergoing rapid changes due to climate warming, potentially exposing a vast reservoir of carbon to be released to the atmosphere, causing a positive feedback cycle. Despite the importance of this feedback, its specifics remain poorly constrained, because representing permafrost dynamics still poses a significant challenge for Earth System Models (ESMs). This review assesses the current state of permafrost representation in land surface models (LSMs) used in ESMs and offline permafrost models, highlighting both the progress made and the remaining gaps.We identify several key physical processes crucial for permafrost dynamics, including soil thermal regimes, freeze-thaw cycles, and soil hydrology, which are underrepresented in many models. While some LSMs have advanced significantly in incorporating these processes, others lack fundamental elements such as latent heat of freeze-thaw, deep soil columns, and Arctic vegetation dynamics. Offline permafrost models provide valuable insights, offering detailed process testing and aiding the prioritization of improvements in coupled LSMs.Our analysis reveals that while significant progress has been made in incorporating permafrost-related processes into coupled LSMs, many small-scale processes crucial for permafrost dynamics remain underrepresented. This is particularly important for capturing the complex interactions between physical and biogeochemical processes required to model permafrost carbon dynamics. We recommend leveraging advancements from offline permafrost models and progressively integrating them into LSMs, while recognizing the computational and technical challenges that may arise in coupled simulations. We highlight the importance of enhancing the representation of physical processes, including through improvements in model resolution and complexity, as this is a fundamental precursor to accurately incorporate biogeochemical processes and capture the permafrost carbon feedback.

The global cryosphere is retreating under ongoing climate change. The Third Pole (TP) of the Earth, which serves as a critical water source for two billion people, is also experiencing this decline. However, the interplay between rising temperatures and increasing precipitation in the TP results in complex cryospheric responses, introducing uncertainties in the future budget of TP cryospheric water (including glacier and snow water equivalents and frozen soil moisture). Using a calibrated model that integrated multiple cryospheric-hydrological components and processes, we projected the TP cryospheric water budgets under both low and high climatic forcing scenarios for the period 2021-2100 and assessed the relative impact of temperature and precipitation. Results showed (1) that despite both scenarios involving simultaneous warming and wetting, under low climatic forcing, the total cryospheric budget exhibited positive dynamics (0.017 mm yr-1 with an average of 1.77 mm), primarily driven by increased precipitation. Glacier mass loss gradually declined with the rate of retreat slowing, accompanied by negligible declines in the budget of snow water equivalent and frozen soil moisture. (2) By contrast, high climatic forcing led to negative dynamics in the total cryospheric budget (-0.056 mm yr-1 with an average of -1.08 mm) dominated by warming, with accelerated decreases in the budget of all cryospheric components. These variations were most pronounced in higher-altitude regions, indicating elevation-dependent cryospheric budget dynamics. Overall, our findings present alternative futures for the TP cryosphere, and highlight novel evidence that optimistic cryospheric outcomes may be possible under specific climate scenarios.

Recent research on the Himalayan cryosphere has increasingly been focused on climate uncertainty and regional variations, considering features such as glacier recession, lake expansion, outburst floods, and regional hazards. The Bhilangana river basin, located in the central Himalayas, is predominantly characterized by increased elevation-dependent warming and declining seasonal precipitation. Our study shows that high-elevation temperature increased from 2000 to 2022 (0.05(degrees)C/year, p = 20 m/sec). Quantification of the regional hazard reveals potentially severe downstream challenges for low-to-medium-scale hydropower stations, local settlements, and road and railway bridges near Devling and Ghuttu villages.

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

Understanding the origins of Tibetan Plateau (TP) glacier dust is vital for glacier dynamics and regional climate understanding. In May 2016, snow pit samples were collected from glaciers on the TP: Qiyi (QY) in the north, Yuzhufeng (YZF) in the center, and Xiaodongkemadi (XDK) in the south. Rare earth element (REE) concentrations were analyzed using inductively coupled plasma mass spectrometry (ICP-MS), and near-surface PM10 concentrations were extracted from a dataset of Chinese near-surface PM10. Two tracing approaches were used: direct REE tracing and an indirect approach combining potential source contribution function (PSCF) and concentration-weighted trajectory (CWT). Both methods yielded consistent results. Pre-monsoon, TP surface soils, Taklimakan Desert, and Qaidam Basin contributed to glacier dust. Notably, central and southern glaciers showed Thar Desert influence, unlike the northern ones. Taklimakan and Thar Deserts were major contributors due to their substantial contribution and high dust concentration. Taklimakan dust, influenced by terrain and westerly winds, affected central and southern glaciers more than northern ones. Westerlies carried Thar Desert dust to the TP after it was uplifted by updrafts in northwest India, significantly affecting southern glaciers. Furthermore, comparing the two tracer methods, the indirect approach combining PSCF and CWT proved more effective for short-term dust source tracing.

The volume of Earth system observations has grown massively in recent decades. However, multivariate or multisource analyses at the interface of atmosphere and land are still hampered by the sparsity of ground measurements and the abundance of missing values in satellite observations. This can hinder robust multivariate analysis and introduce biases in trends. Nevertheless, gap-filling is often done univariately, which can obscure physical dependencies. Here, we apply the new multivariate gap-filling framework CLIMate data gapFILL (CLIMFILL). CLIMFILL combines state-of-the-art spatial interpolation with an iterative approach accounting for dependencies across multiple incomplete variables. CLIMFILL is applied to a set of remotely sensed and in situ observations over land that are central to observing land-atmosphere interactions and extreme events. The resulting gridded monthly time series covers 1995-2020 globally with gap-free maps of nine variables: surface layer soil moisture from European Space Agency (ESA)-Climate Change Initiative (CCI), land surface temperature and diurnal temperature range from Moderate-resolution Imaging Spectroradiometer, precipitation from GPM, terrestrial water storage from GRACE, ESA-CCI burned area, and snow cover fraction as well as 2-m temperature and precipitation from CRU. Time series of anomalies are reconstructed better compared to state-of-the-art interpolation. The gap-filled data set shows high correlations with ERA5-Land, and soil moisture estimates compare favorably to in situ observations from the International Soil Moisture Network. Soil moisture drying trends in ESA-CCI only agree with the reanalysis product ERA5-Land trends after gap-filling. We furthermore showcase that key features of droughts and heatwaves in major fire seasons are well represented. The data set can serve as a step toward the fusion of multivariate multisource observations.

Polar amplification appears in response to greenhouse gas forcing, which has become a focus of climate change research. However, polar amplification has not been systematically investigated over the Earth's three poles (the Arctic, Antarctica, and the Third Pole). An index of polar amplification is employed, and the annual and seasonal variations of land surface temperature over the Earth's three poles are examined using MODIS (Moderate Resolution Imaging Spectroradiometer) observations for the period 2001-2018. As expected, the warming of the Arctic is most conspicuous, followed by the Third Pole, and is weakest in Antarctica. Compared to the temperature changes for the global land region, positive polar amplification appears in the Arctic and the Third Pole on an annual scale, whereas Antarctic amplification disappears, with a negative amplification index of -0.72. The polar amplification for the Earth's three poles shows seasonal differences. Strong Arctic amplification appears in boreal spring and winter, with a surface warming rate of more than 3.40 times the global mean for land regions. In contrast, the amplification of the Third Pole is most conspicuous in boreal summer. The two poles located in the Northern Hemisphere have the weakest amplification in boreal autumn. Differently from the positive amplification for the Arctic and the Third Pole in all seasons, the faster variations in Antarctic temperature compared to the globe only appear in austral autumn and winter, and the amplification signal is negative in these seasons, with an amplification index of -1.68 and -2.73, respectively. In the austral winter, the strong negative amplification concentrates on West Antarctica and the coast of East Antarctica, with an absolute value of amplification index higher than 5 in general. Generally, the polar amplification is strongest in the Arctic except from June to August, and Antarctic amplification is the weakest among the Earth's three poles. The Earth's three poles are experiencing drastic changes, and the potential influence of climate change should receive attention.

The Granger Causality (GC) statistical test explores the causal relationships between different time series variables. By employing the GC method, the underlying causal links between environmental drivers and global vegetation properties can be untangled, which opens possibilities to forecast the increasing strain on ecosystems by droughts, global warming, and climate change. This study aimed to quantify the spatial distribution of four distinct satellite vegetation products' (VPs) sensitivities to four environmental land variables (ELVs) at the global scale given the GC method. The GC analysis assessed the spatially explicit response of the VPs: (i) the fraction of absorbed photosynthetically active radiation (FAPAR), (ii) the leaf area index (LAI), (iii) solar-induced fluorescence (SIF), and, finally, (iv) the normalized difference vegetation index (NDVI) to the ELVs. These ELVs can be categorized as water availability assessing root zone soil moisture (SM) and accumulated precipitation (P), as well as, energy availability considering the effect of air temperature (T) and solar shortwave (R) radiation. The results indicate SM and P are key drivers, particularly causing changes in the LAI. SM alone accounts for 43%, while P accounts for 41%, of the explicitly caused areas over arid biomes. SM further significantly influences the LAI at northern latitudes, covering 44% of cold and 50% of polar biome areas. These areas exhibit a predominant response to R, which is a possible trigger for snowmelt, showing more than 40% caused by both cold and polar biomes for all VPs. Finally, T's causality is evenly distributed amongst all biomes with fractional covers between similar to 10 and 20%. By using the GC method, the analysis presents a novel way to monitor the planet's ecosystem, based on solely two years as input data, with four VPs acquired by the synergy of Sentinel-3 (S3) and 5P (S5P) satellite data streams. The findings indicated unique, biome-specific responses of vegetation to distinct environmental drivers.

High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas.

The soil freezing and thawing process affects soil physical properties, such as heat conductivity, heat capacity, and hydraulic conductivity in frozen ground regions, and further affects the processes of soil energy, hydrology, and carbon and nitrogen cycles. In this study, the calculation of freezing and thawing front parameterization was implemented into the earth system model of the Chinese Academy of Sciences (CAS-ESM) and its land component, the Common Land Model (CoLM), to investigate the dynamic change of freezing and thawing fronts and their effects. Our results showed that the developed models could reproduce the soil freezing and thawing process and the dynamic change of freezing and thawing fronts. The regionally averaged value of active layer thickness in the permafrost regions was 1.92 m, and the regionally averaged trend value was 0.35 cm yr(-1). The regionally averaged value of maximum freezing depth in the seasonally frozen ground regions was 2.15 m, and the regionally averaged trend value was -0.48 cm yr(-1). The active layer thickness increased while the maximum freezing depth decreased year by year. These results contribute to a better understanding of the freezing and thawing cycle process.