A land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) surface model (LSM) using Local Ensemble Transform Kalman Filter (LETKF). The assimilates microwave from Soil Moisture Active Passive (SMAP) radiometer and Advanced Scatterometer (ASCAT) after bias correction based on cumulative distribution function fitting. estimates are evaluated with ground-based measurements over continental U.S. for five...

Abstract. Land–atmosphere (L–A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, other land-centered anomalies. Local L–A coupling (LoCo) metrics capture relevant highlighting impact soil vegetation states on surface flux partitioning fluxes boundary layer (BL) growth entrainment air above BL. A primary goal Climate Process Team in Coupling Land Atmospheric Subgrid Parameterizations...

Abstract This study investigates the performance of latter NCEP Unified Forecast System (UFS) Coupled Model prototype simulations (P5–P8) during boreal summer 2011–17 in regard to coupled land–atmosphere processes and their effect on model bias. Major land physics updates were implemented course development. Namely, Noah surface was replaced with Noah-MP global vegetation dataset updated starting P7. These changes occurred along many other UFS improvements. UFS’s ability simulate observed...

Rapidly developing droughts, including flash have frequently occurred throughout East Asia in recent years, causing significant damage to agricultural ecosystems. Although many drought monitoring and warning systems been developed decades, the short-term prediction of droughts (within 10 days) is still challenging. This study has models for a short-period time (one pentad) using remote-sensing data climate variability indices over (20°–50°N, 90°–150°E) through random forest machine learning....

Abstract This study investigates the physical mechanisms that contributed to 2016 Eurasian heat wave during boreal summer season (July–August, JA), characterized by much higher than normal temperatures over eastern Europe, East Asia, and Kamchatka Peninsula. It is found JA mean surface air temperature, upper-tropospheric height, soil moisture anomalies are a tri-pole pattern Eurasia continent train-like structure not dissimilar recent (1980–2016) trends in those quantities. A series of...

Abstract The impact of soil moisture initialization on the 2016 Northeast Asian heat wave was explored using Land Information System (LIS) Weather Research and Forecasting (WRF) model. To obtain advanced estimates, various meteorological variables from Global Data Assimilation analysis Integrated Multi‐Satellite Retrievals for Precipitation Measurement observation data were used as atmospheric forcings offline simulation Noah land surface model (Noah‐LSM). Based LIS, Soil Moisture Active...

The representation of snow in land surface models is critical for accurate seasonal forecasting, yet traditional single-layer schemes fail to capture the full insulating properties deep snowpacks. These limitations result pronounced biases, including excessive winter cooling and springtime warming. This study explores impact introducing a multi-layer scheme within Global Seasonal Forecast System (GloSea) address these biases. Using 24 years retrospective forecasts (1993–2016), we...

Abstract Models have historically been the source of global soil moisture (SM) analyses and estimates land-atmosphere coupling, even though they are usually calibrated validated only locally. Satellite-based grown in fidelity duration, offering an independent observationally-based alternative. However, satellite-retrieved SM time series include random periodic errors that degrade including correlations with other variables. This study proposes a mathematical approach to adjust daily European...

Abstract. Land–atmosphere interactions have been investigated at daily or longer timescales due to limited data availability and large errors for measuring high-frequency variations. Yet coupling the subdaily timescale is characterized by diurnal cycle of incoming solar radiation surface fluxes. Based on flux tower observations, this study investigates climatology observed land–atmosphere during warm season. Process-based multivariate metrics are employed quantitatively measure segmented...

Abstract High temperature extremes accompanied by drought have led to serious ramifications for environmental and socio‐economic systems. Thus, improving the predictability of heat‐wave events is a high priority. One key achieving this better understand land‐atmosphere interactions. Recent studies documented hypersensitive regime in soil moisture‐temperature relationship: when dries below critical low threshold, called moisture breakpoint, air temperatures increase at greater rate as...

This study investigates the predictability of 2018 Northern Europe heatwave using GloSea5 forecast model from perspective land-atmosphere interactions. We focus on an inverse relationship wherein soil drying leads to increased temperatures and model's ability simulate this hypersensitivity in moisture-temperature coupling dry side a breakpoint defined as moisture threshold below which land feedbacks nonlinearly amplify extreme heat. When evaluating performance predicting heatwave, we compare...

Abstract The Q10 value represents the soil respiration sensitivity to temperature often used for parameterization of decomposition process has been assumed be a constant in conventional numerical models, whereas it exhibits significant spatial and temporal variation observations. This study develops new method determining by considering dependence on moisture obtained multiple regression each vegetation type. further investigates impacts global terrestrial carbon flux. Our results show that...

This study investigates the predictability of 2018 Northern Europe heatwave using GloSea5 forecast model from perspective land-atmosphere coupling processes. Soil moisture and temperature have an inverse relationship with soil drying leading to increased temperatures. exhibits nonlinearity when hypersensitivity in moisture-temperature arises on dry side a breakpoint, defined as threshold below which land feedbacks strongly amplify extreme heat. When evaluating performance predicting this...

Abstract. Land–atmosphere interactions have been investigated at daily or longer time scales due to limited data availability and large sensor errors for measuring high-frequency signals. Yet coupling the sub-daily scale is characterized by diurnal cycle of incoming solar radiation soil wetness. Based on flux tower observations, this study investigates climatology observed land–atmosphere a during warm season. Process-based multivariate metrics are employed quantitatively measure segmented...

Abstract. Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, other land-centred anomalies. Local L-A coupling (LoCo) metrics capture relevant highlighting impact soil vegetation states on surface flux partitioning, fluxes boundary layer (BL) growth, development, entrainment air above BL. A primary goal Climate Process Team Coupling Land Atmospheric Subgrid...

Abstract. Soil decomposition is one of the critical processes for maintaining a terrestrial ecosystem and global carbon cycle. The sensitivity soil respiration (Rs) to temperature, so-called Q10 value, required parameterizing process assumed be constant in conventional numerical models, while realistically it not cases spatiotemporal heterogeneity. This study develops new parameterization method determining by considering dependence on temperature moisture obtained multiple regression....

The Goddard Earth Observing System version 5 (GEOS‐5) global climate model with a 50‐km horizontal resolution is forced by observed sea surface temperature (SST) to examine the fidelity of seasonal‐mean and inter‐annual variation tropical cyclones (TCs) in western North Pacific (WNP) Atlantic (NATL). standard Relaxed Arakawa Schubert (RAS) deep convection scheme modified improve representation TCs, where implements stochastic limit cumulus entrainment rate. modification drives mid‐...

Abstract. This study explores the influence of implementing a multi-layer snow scheme on climatological bias within seasonal forecast system. A single-layer schemes in land surface models often inadequately represent insulating effect snowpack, resulting warm and cold biases during winter melting seasons, respectively. By contrast, enable enhanced energy transport between atmosphere. To investigate this impact, two versions Global Seasonal Forecast System (GloSea) – GloSea5 with GloSea6 are...