Evaluation and Comparison of the Common Land Model and the Community Land Model by Using In Situ Soil Moisture Observations from the Soil Climate Analysis Network

Soil moisture is a key state variable in land surface processes. Since field measurements of soil moisture are generally sparse and remote sensing is limited in terms of observation depth, land surface model simulations are usually used to continuously obtain soil moisture data in time and space. Therefore, it is crucial to evaluate the performance of models that simulate soil moisture under various land surface conditions. In this work, we evaluated and compared two land surface models, the Common Land Model version 2014 (CoLM2014) and the Community Land Model Version 5 (CLM5), using in situ soil moisture observations from the Soil Climate Analysis Network (SCAN). The meteorological and soil attribute data used to drive the models were obtained from SCAN station observations, as were the soil moisture data used to validate the simulation results. The validation results revealed that the correlation coefficients between the simulations by CLM5 (0.38) and observations are generally higher than those by CoLM2014 (0.11), especially in shallow soil (0–0.1016 m). The simulation results by CoLM2014 have smaller bias than those by CLM5 . Both models could simulate diurnal and seasonal variations of soil moisture at seven sites, but we found a large bias, which may be due to the two models’ representation of infiltration and lateral flow processes. The bias of the simulated infiltration rate can affect the soil moisture simulation, and the lack of a lateral flow scheme can affect the models’ division of saturated and unsaturated areas within the soil column. The parameterization schemes in land surface models still need to be improved, especially for soil simulations at small scales.

Wave Climate and Trends for the Marine Experimental Station of Capo Tirone Based on a 70-Year-Long Hindcast Dataset

Nearshore marine systems provide multiple economic and ecological services to human communities. Several studies addressing the climate change stressors and the inappropriate use of the sea indicate a decline of coastal areas. An extensive monitoring of the most important marine sites and protected areas is crucial to design effective environmental-friendly measures to support the sustainable development of coastal regions. A 70-year-long wave climate analysis is presented to study the climatology of the area belonging to the Marine Experimental Station of Capo Tirone, Italy. The analysis is based on the global atmospheric reanalysis developed by the European Centre for Medium-Range Weather Forecasts, validated through an observed buoy dataset recorded by the Italian Sea Wave Measurement Network. No significant long-term trends have been detected. The need to set up new monitoring stations has been pointed out by means of a hydrodynamic model developed at the regional scale, evaluating the effect of the local morphology on the nearshore wave climate and highlighting the importance of surveying the marine protected area of Capo Tirone located therein.

A Predictive Study of the Redistribution of Some Bread Wheat Genotypes in Response to Climate Change in Egypt

Climate change and global warming have become the most significant challenges to the agricultural production worldwide, especially in arid and semiarid areas. The main purpose of plant breeding programs now is to produce a genetically wide range of genotypes that can withstand the adverse effects of climate change. Moreover, farmers have to reallocate their cultivars due to their ability to tolerate unfavorable conditions. During this study, two field experiments and climate analysis based on 150 years of data are conducted to reallocate some genotypes of bread wheat in respect to climate change based on their performance under drought stress conditions. Climatic data indicate that there is an increase in temperature over all Egyptian sites coupled with some changes in rain amount. Among the tested cultivars, cultivar Giza 160 was the perfect one, while cultivar Masr 03 was the weakest one. Susceptibility indices are a good tool for discovering the superior genotypes under unfavorable conditions and, interestingly, some of the cultivars with high performance were among the superior cultivars in more than one of the tested traits in this study. Finally, combining the climatic data and the experimental data, we can conclude that cultivars Giza 160 and Sakha 94 are suitable for growning in zones with harsh environments, such as the eastern desert and southern Egypt, while cultivars Gemmeza 11, Sahel 01, Sakha 98, Sids 12, and Sakha 93 are suitable for growning in zones with good growing conditions, such as the Nile Delta region and northern Egypt.

Estimating unprecedented extremes in UK summer daily rainfall

The UNSEEN (UNprecedented Simulated Extremes using ENsembles) method involves using a large ensemble of climate model simulations to increase the sample size of rare events. Here we extend UNSEEN to focus on intense summertime daily rainfall, estimating plausible rainfall extremes in the current climate. To address modelling limitations simulations from two climate models were used; an initialised 25km global model that uses parametrized convection, and a dynamically downscaled 2.2km model that uses explicit convection. In terms of the statistical characteristics that govern very rare return periods, the models are not significantly different from the observations across much of the UK. Our analysis provides more precise estimates of 1000-year return levels for extreme daily rainfall, reducing sampling uncertainty by 70-90% compared to using observations alone. This framework enables observed daily storm profiles to be adjusted to more statistically robust estimates of extreme rainfall. For a damaging storm in July 2007 which led to surface water flooding, we estimate physically plausible increases in the total daily rainfall of 50 – 100%. For much of the UK the annual chance of record-breaking daily summertime rainfall is estimated to be around 1% per year in the present-day climate. Analysis of the dynamical states in our UNSEEN events indicates that heavy daily rainfall is associated with a southward displaced and meandering North Atlantic jet stream, increasing the advection of warm moist air from across Southern Europe and the Mediterranean, and intensifying extratropical storms. This work represents an advancement in the use of climate modelling for estimating present-day climate hazards and outlines a framework for applying UNSEEN at higher spatial and temporal resolutions.

Heavy Lake-Effect Snowfall Changes and Mechanisms for the Laurentian Great Lakes Region

Heavy lake-effect snowfall (HLES) events are snowfall events enhanced by interactions between lakes and overlying cold air. Significant snowfall rates and accumulations caused during such events disrupt socioeconomic activities and sometimes lead to lethal consequences. The aim of this study is to assess projected changes to HLES by the end of the century (2079–2100) using a regional climate model for the first time with 3D representation for the Laurentian Great Lakes. When compared to observations over the 1989–2010 period, the model is able to realistically reproduce key mechanisms and characteristics of HLES events, thus increasing confidence in future projections. Projected changes to the frequency and amount of HLES suggest decreasing patterns, during the onset, active and decline phases of HLES. Despite reduced lake ice cover that will allow enhanced lake–atmosphere interactions favouring HLES, the warmer temperatures and associated increase in liquid to solid precipitation ratio along with reduced cold air outbreaks contribute to reduced HLES in the future climate. Analysis of the correlation patterns for current and future climates further supports the weaker impact of lake ice fraction on HLES in future climates. Albeit the decreases in HLES frequency and intensity and projected increases in extreme snowfall events (resulting from all mechanisms) raise concerns for impacts on the transportation, infrastructure and hydropower sectors in the region.

Global predictions of primary soil salinization under changing climate in the 21st century

Soil salinization has become one of the major environmental and socioeconomic issues globally and this is expected to be exacerbated further with projected climatic change. Determining how climate change influences the dynamics of naturally-occurring soil salinization has scarcely been addressed due to highly complex processes influencing salinization. This paper sets out to address this long-standing challenge by developing data-driven models capable of predicting primary (naturally-occurring) soil salinity and its variations in the world’s drylands up to the year 2100 under changing climate. Analysis of the future predictions made here identifies the dryland areas of South America, southern and western Australia, Mexico, southwest United States, and South Africa as the salinization hotspots. Conversely, we project a decrease in the soil salinity of the drylands in the northwest United States, the Horn of Africa, Eastern Europe, Turkmenistan, and west Kazakhstan in response to climate change over the same period.

Desert Climate Regionalization for Joshua Tree National Park and Surrounding Areas Using New Climate Network Observations

A new amalgamation of weather stations in and around Joshua Tree National Park in southeastern California, USA has allowed for objective climate analysis regionalization at a much finer scale than past studies. First, it sets a baseline for many regions within the park’s boundaries which were not subject to direct observations. Second these new observations are key to understanding shifting microclimate regimes in a desert ecosystem prone to the effects of climate change. Principal component analysis was used to regionalize the climate network based on monthly temperature and precipitation climate observations and standardized anomalies. Both the observation values and standardized climate anomalies identified regional boundaries. In general, these boundaries align with traditional ideas and past studies of the Mojave and Sonoran Deserts based on elevation (specifically the 1000m contour) for the National Park. Standardized anomaly values identified a boundary based on seasonal precipitation, while observation values identified a boundary based on elevation. The boundary line within the park is similar for both data approaches, with the boundary running along the higher western third of the park. Conversely, the two methods differ significantly in the Coachella Valley, where low elevations and low precipitation meets winter dominated seasonal precipitation. This study highlights the importance and opportunity of field observations to create climatological and ecological regionalization, as well as constructs a baseline to monitor and manage shifting desert regions in the future.

Exploring environment as cross-cutting issue among Humanitarian-Development Nexus Actors

Environment mainstreaming across the humanitarian operations and long-term development programs is imperative to the new way of working agreed in the World Humanitarian Summit (2016). Mainstreaming environment in Humanitarian-Development nexus is crucial to minimize the environmental impacts of humanitarian projects and to build long term resilience against environmental and climatic risks and vulnerabilities of communities. This study explores the current environmental mainstreaming strategies of humanitarian and development organizations at the institutional and operational level based on specific attributes. This study conducts the case study of leading humanitarian and development organizations, namely, WFP, IFRC, UNDP, and USAID, based on the conceptual framework on mainstreaming strategies derived from various literature. Multiple case study approach was employed based on information collected through various secondary sources and personal consultation with the organizations. The finding of this study signifies the presence of varying environmental mainstreaming practices within the studied organizations, and comparative analysis among them is also presented. Finally, this study suggests that joint contextual environmental (and climate) analysis by humanitarian and development actors and inclusion of environmental consideration in collaborative multi-year programming to minimize environmental damage in protracted crises.

Future Extreme Climate Analysis of Jeju Using Climate Change Scenario and ETCCDI Index

According to the fifth IPCC report, artificial greenhouse gases are at their highest level since they were first observed, and climate change is expected to have a significant impact on the ecosystem, necessitating a response from Korea. For the purpose of this study, Jeju Island was selected as the target area; the annual average precipitation of the region exhibited a 10% increase from 1,780 mm in 1991 to 1,961 mm in 2019; the annual average temperature increased by 0.3 ℃ over 10 years from 1961 to 2019. There are three weather stations (Jeju, Seogwipo, and Seongsan) on Mt. Halla, which is 1,950 m above sea level; among these stations, Jeju Island's climate patterns are the most atypical. The World Meteorological Organization’s (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) for Jeju Island's extreme climate analysis used 8 of the 27 indexes that are most closely related to climate. For analysis purposes, existing RCP 8.5 climate change scenario data were categorized as: past (data analyzed from 1991 to 2019), and future (data analyzed from 2020 to 2100). According to the extreme climate analysis, Jeju Observatory recorded its highest temperature at 25 ℃ while exhibiting an increasing trend, and at Seongsan, highest temperature of less than 0 ℃ was recorded for more than 40 days in 1996. According to the climate change scenario, the number of hot days in Jeju, Seogwipo, and Seongsan is increasing, but the number of frost days has converged to zero with the progression of the second half of the 21st century. Japan's highest temperature chart shows that 40 ℃ spike in Jeju compared to other regions. Thus, this study highlights the necessity of considering the climate characteristics of each observatory, and the implementation of urban planning and disaster prevention measures.

Variables of influence on thermal performance of buildings under transient conditions

Residential buildings significantly increase electricity demand, especially in developing countries. In this case, the requirements addressed by the standards can ensure the climatic adequacy of the envelope, enhance thermal performance, and promote thermal comfort conditions while reducing energy consumption. However, the criteria for evaluating the thermal performance of a building’s envelope that is commonly adopted in energy performance standards and codes have proved to be inefficient in hot climates. The heat exchanges within buildings are dependent on solar radiation and ventilation. The purpose of this article is to establish the variables with the greatest influence on the thermal performance of naturally ventilated dwellings in hot climates (equatorial, tropical and subtropical). For this investigation, a factorial design was adopted for sensitivity analysis. The structure of the factorial experiment defined the simulations of four patterns of single-family and multifamily residential buildings. We varied the thermophysical properties of the external walls and roofs, the heat gain coefficient of the openings, and natural ventilation. Brazil was adopted as a basis for climate analysis, including equatorial, tropical and subtropical climates. The analyses were based on comfort hours in an adaptive model and statistically evaluated using Analysis of Variance (ANOVA) tests. In general, the absorption of the walls and cover, the thermal transmittance of the cover and the natural ventilation were the variables of greatest influence on thermal comfort in a hot climate.