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https://doi.org/10.1007/s00382-024-07210-5. In this article 17 references, which were wrongly moved to the Supplementary Information, need to be added. The list of added references as given below: The original article has been corrected

Abstract: Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was initiated to study the impact of springtime LST/SUBT anomalies over high mountain areas on summertime precipitation predictions. The present work explores the simulated global scale response of the atmospheric circulation to the springtime TP land surface cooling by 16 current state-of-the-art Earth System Models (ESMs) participating in the LS4P Phase I (LS4P-I) experiment. The LS4P-I results show, for the first time, that springtime TP surface anomalies can modulate a persistent quasi-barotropic Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train from the TP via the northeast Asia and Bering Strait to the western part of the North America, along with the springtime westerly jet from TP across the whole North Pacific basin. The TRC wave train modulated by the TP thermal anomaly play a critical role on the early summer surface air temperature and precipitation anomalies in the regions along the wave train, especially over the northwest North America and the southern Great Plains. The participant models that fail in capturing the TRC wave train greatly under-predict climate anomalies in reference to observations and the successful models. These results suggest that the TP LST/SUBT anomaly via the TRC wave train is the first order source of the S2S variability in the regions mentioned. Furthermore, the TP surface temperature anomaly can influence the Southern Hemispheric circulation by generating cross-equator wave trains. However, the simulated propagation pathways from the TP into the Southern Hemisphere show large inter-model differences. More dynamical understanding of the TRC wave train as well as its cross-equator propagation into the Southern Hemisphere will be explored in the newly launched LS4P phase II experiment.

Abstract: The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented.

Subseasonal-to-seasonal (S2S) precipitation prediction in boreal spring and summer months, which contains a significant number of high-signal events, is scientifically challenging and prediction skill has remained poor for years. Tibetan Plateau (TP) spring observed surface temperatures show a lag correlation with summer precipitation in several remote regions, but current global land-atmosphere coupled models are unable to represent this behavior due to significant errors in producing observed TP surface temperatures. To address these issues, the Global Energy and Water Exchanges (GEWEX) program launched the "Impact of Initialized Land Temperature and Snowpack on Subseasonal-to-Seasonal Prediction"(LS4P) initiative as a community effort to test the impact of land temperature in high-mountain regions on S2S prediction by climate models: more than 40 institutions worldwide are participating in this project. After using an innovative new land state initialization approach based on observed surface 2-m temperature over the TP in the LS4P experiment, results from a multimodel ensemble provide evidence for a causal relationship in the observed association between the Plateau spring land temperature and summer precipitation over several regions across the world through teleconnections. The influence is underscored by an out-of-phase oscillation between the TP and Rocky Mountain surface temperatures. This study reveals for the first time that high-mountain land temperature could be a substantial source of S2S precipitation predictability, and its effect is probably as large as ocean surface temperature over global "hotspot"regions identified here; the ensemble means in some "hotspots"produce more than 40% of the observed anomalies. This LS4P approach should stimulate more follow-on explorations.

Recent observational and modeling studies have demonstrated the substantial influence of the Tibetan Plateau (TP) spring land surface temperature (LST) and subsurface temperature (SUBT) on downstream summer droughts/floods events in East Asia, highlighting the potential application of LST/SUBT on sub-seasonal to seasonal prediction (S2S). In this study, we employ the National Centers for Environment Prediction—Global Forecast System/Simplified Simple Biosphere model version 2 (GFS/SSiB2) to investigate the potential role of the late spring warm LST anomaly over the TP on the extraordinary June 1998 flood in the south of the Yangtze River region. Numerical experiments indicate that the warmer (above normal) May LST over the TP may contribute to the extreme flood of 1998 over the south of the Yangtze River region, with the LST reproducing about 57% and 64% of observed above-normal rainfall anomaly over the south of the Yangtze River region and southeastern China, respectively. Further analyses reveal a possible effect of springtime TP’s LST on summer southern and eastern Asian rainfall and identify some hot spots, suggesting that the TP’s spring LST effect is not only limited to the Yangtze River region, but to a much larger scale. The imposed warm LST/SUBT over the TP triggers a strong wave activities propagating eastward along the upper-level westerly jet, associated with an increase of the atmospheric baroclinic instability as well as a strengthening and southeastward movement of the South Asian high, leading to intensified moisture convergence and convective instability favorable to the excessive rainfall in the downstream region of East Asia. The results of the 1998 case have also been compared with the results from year of 2003, which had a very cold spring LST anomaly over the TP and a severe downstream June 2003 drought (flood) in southern (northern) of the Yangtze River Basin area. Simulation results provide further evidence of the great importance of the TP spring land surface temperature anomaly in regulating summer extreme hydroclimatic events (e.g. droughts and floods) in South and East Asia. The present study suggests that consideration of LST/SUBT anomalies has a strong potential for more skillful S2S prediction of extreme hydroclimatic events such as floods, droughts and heatwaves over both Southern and Eastern Asia.

Abstract. Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

AbstractLand-use and land-cover change (LULCC) is one of the most important forcings affecting climate in the past century. This study evaluates the global and regional LULCC impacts in 1950–2015 by employing an annually updated LULCC map in a coupled land–atmosphere–ocean model. The difference between LULCC and control experiments shows an overall land surface temperature (LST) increase by 0.48 K in the LULCC regions and a widespread LST decrease by 0.18 K outside the LULCC regions. A decomposed temperature metric (DTM) is applied to quantify the relative contribution of surface processes to temperature changes. Furthermore, while precipitation in the LULCC areas is reduced in agreement with declined evaporation, LULCC causes a southward displacement of the intertropical convergence zone (ITCZ) with a narrowing by 0.5°, leading to a tripole anomalous precipitation pattern over the warm pool. The DTM shows that the temperature response in LULCC regions results from the competing effect between increased albedo (cooling) and reduced evaporation (warming). The reduced evaporation indicates less atmospheric latent heat release in convective processes and thus a drier and cooler troposphere, resulting in a reduction in surface cooling outside the LULCC regions. The southward shift of the ITCZ implies a northward cross-equatorial energy transport anomaly in response to reduced latent/sensible heat of the atmosphere in the Northern Hemisphere, where LULCC is more intensive. Tropospheric cooling results in the equatorward shift of the upper-tropospheric westerly jet in both hemispheres, which, in turn, leads to an equatorward narrowing of the Hadley circulation and ITCZ.

Recent studies have shown that spring land surface temperature (LST) and subsurface temperature (SUBT) over the high elevation areas in the western US (WUS) have significant impacts on the downstream summer droughts/floods in North America. In this paper, both the National Centers for Environmental Prediction—Global Forecast System (NCEP-GFS) general circulation model (GCM) and the weather research and forecasting (WRF) regional climate model (RCM) are employed, where RCM scenarios utilized initial and lateral boundary conditions derived from the corresponding NCEP-GFS scenarios. Here we use a late spring flood in the US Southern Great Plains (SGP) case to examine whether simulation of the LST/SUBT downstream effects is sensitive to the domain size choice, change in dynamical cores within the same model, as well as to the representation of surface processes parameterizations. Although all RCM experiments with different settings simulate reasonably geographical patterns of observed LST and precipitation anomalies, we found that the choice of the domain size is crucial for proper downscaling the LST/SUBT downstream effects to accurately produce the observed precipitation/LST anomalies over the SGP/WUS, respectively, along with the associated large-scale features. The southern boundary location has been identified to be crucial in producing the SGP Low Level Jet strength, which in turn brings more moisture from the Gulf of Mexico to the SGP and thereby resulting in a better simulation of the precipitation anomaly in that area. The sensitivity of the simulation of the LST/SUBT downstream effect to dynamical cores is assessed by inter-comparing the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF dynamic cores. We find NMM was better at generating the large-scale eastward wave train, a crucial process associated with the LST/SUBT downstream effect. Meanwhile, this study also shows that the LST/SUBT downstream effects were not significantly dependent on the surface process parameterizations, although the Simplified Simple Biosphere model version 3 (SSiB3) highlighted a better performance over SSiB2.

This paper evaluates multi-decadal simulations of the UCLA version of Climate Forecast System version 2, in which the default Noah land surface model has been replaced with the Simplified Simple Biosphere Model version-2. To examine the influence of the atmosphere–ocean (AO) interaction on the variability, two different simulations were conducted: one with interactive ocean component, and the other constrained by the prescribed sea surface temperature. We evaluate the mean seasonal climatology of precipitation and temperature, along with the model’s ability to reproduce atmospheric variability at different scales over the globe, including extratropical modes of atmospheric variability, and long-term trends of global and hemispheric temperature and regional precipitation. Here, we particularly selected two monsoon regions, East Asia and West Africa, where the simulation of multi-decadal variations which has heretofore been a challenging task, to examine decadal variation of monsoon precipitation. In general, temperature anomaly trends were better captured than those of precipitation in both simulations. Results suggest that the AO interaction, represented as latent heat flux, contributes to improve reproducibility of global-wide climatology, extratropical modes of atmospheric variability, and variability in the multi-decadal climate simulation, as well as for inter-decadal variability of the East Asian summer monsoon.

Sea surface temperature (SST) variability has been shown to have predictive value for land precipitation, although SSTs are unable to fully predict intraseasonal to interannual hydrologic extremes. The possible remote effects of large-scale land surface temperature (LST) and subsurface temperature (SUBT) anomalies in geographical areas upstream and closer to the areas of drought/flood have largely been ignored. Here evidence from climate observations and model simulations addresses these effects. Evaluation of observational data using Maximum Covariance Analysis identifies significant correlations between springtime 2-m air temperature (T2 m) cold (warm) anomalies in both the western U.S. and the Tibetan Plateau and downstream drought (flood) events in late spring/summer. To support these observational findings, climate models are used in sensitivity studies, in which initial LST/SUBT anomaly is imposed to produce observed T2 m anomaly, to demonstrate a causal relationship for two important cases: between spring warm T2 m/LST/SUBT anomalies in western U.S. and the extraordinary 2015 flood in Southern Great Plains and adjacent regions and between spring cold T2 m/LST/SUBT anomalies in the Tibetan Plateau and the severe 2003 drought south of the Yangtze River region. The LST/SUBT downstream effects in North America are associated with a large-scale atmospheric stationary wave extending eastward from the LST/SUBT anomaly region. The effects of SST in these cases are also tested and compared with the LST/SUBT effects. These results suggest that consideration of LST/SUBT anomalies has the potential to add value to intraseasonal prediction of dry and wet conditions, especially extreme drought/flood events. The results suggest the importance of developing land data and models capable of preserving observed soil memory.

Climate models' capability of reproducing the present climate at both global and regional scales still needs improvements. The assessment of model performance critically depends on the data sets used as comparators/references. Reanalysis and gridded observational data sets have been frequently used for this purpose. However, none of these can be considered an accurate reference data set because of their associated uncertainties and full representativity. This paper, for the first time, uses in‐situ measurements from National Oceanic and Atmospheric Administration U.S. Climate Reference Network (USCRN) spanning the period 2006–2020 to assess daily temperature and precipitation from a suite of dynamically downscaled regional climate models (RCMs; driven by ERA‐Interim) involved in NA‐CORDEX. The assessment is also extended to the most recent and widely used Earth system reanalyses (ERA5, ERA‐Interim, MERRA2 and NARR) and a few in situ‐based gridded data sets (Daymet, PRISM, Livneh and CPC). Results show that biases for the different data sets are seasonally and subregionally dependent. On average, reanalysis and in situ‐based gridded data sets are warmer (with biases exceeding 0.3°C) than USCRN year‐round, while RCMs are colder (warmer) in winter (summer) with biases ranging from −0.5 (0.9)°C for RCMs at 0.44° to −0.2 (1.4)°C for CRCM5‐UQAM‐11. In situ‐based gridded data sets provide the best performance in most of the Contiguous United States (CONUS) regions compared to reanalyses and RCMs, but still have biases in regions such as the Western mountains and the Pacific Northwest. Furthermore, in most US subregions, reanalysis data sets do not outperform reanalysis‐driven RCMs. Likewise, for both reanalysis data sets and RCMs, temperature and precipitation biases vary considerably depending on the local orography, with larger temperature biases for coarser model resolutions and precipitation biases for reanalysis. [ABSTRACT FROM AUTHOR]