Numerical simulation and data assimilation of the water-energy cycle over semiarid northeastern China

The default fractional vegetation cover and terrain height were replaced by the estimated fractional vegetation cover, which was calculated by the Normalized Difference Vegetation Index(NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer(EOS-MODIS) and the Digital Elevation Model of the Shuttle Radar Topography Mission(SRTM) system. The near-surface meteorological elements over northeastern China were assimilated into the three-dimensional variational data assimilation system(3DVar) module in the Weather Research and Forecasting(WRF) model. The structure and daily variations of air temperature, humidity, wind and energy fields over northeastern China were simulated using the WRF model. Four groups of numerical experiments were performed, and the simulation results were analyzed of latent heat flux, sensible heat flux, and their relationships with changes in the surface energy flux due to soil moisture and precipitation over different surfaces. The simulations were compared with observations of the stations Tongyu, Naiman, Jinzhou, and Miyun from June to August, 2009. The results showed that the WRF model achieves high-quality simulations of the diurnal characteristics of the surface layer temperature, wind direction, net radiation, sensible heat flux, and latent heat flux over semiarid northeastern China in the summer. The simulated near-surface temperature, relative humidity, and wind speed were improved in the data assimilation case(Case 2) compared with control case(Case 1). The simulated sensible heat fluxes and surface heat fluxes were improved by the land surface parameterization case(Case 3) and the combined case(Case 4). The simulated temporal variations in soil moisture over the northeastern arid areas agree well with observations in Case 4, but the simulated precipitation should be improved in the WRF model. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations. The assimilation datasets generated by this work can be applied to research on climate change and environmental monitoring of arid lands, as well as research on the formation and stability of climate over semiarid areas.     

Vegetation pattern of Istanbul from the Landsat data and the relationship with meteorological parameters

This paper discusses the preliminary results of a study on the vegetation pattern and its relationship with meteorological parameters in and around Istanbul. The study covers an area of over 6800 km² consisting of urban and suburban centers, and uses the visible and near-infrared bands of Landsat. The spatial variation of the Normalized Difference Vegetation Index (NDVI) and meteorological parameters such as sensible heat flux, momentum flux, relative humidity, moist static energy, rainfall rate and temperature have been investigated based on observations in ten stations in the European (Thracian) and Anatolian parts of Istanbul. NDVI values have been evaluated from the Landsat data for a single day, viz. 24 October 1986, using ERDAS in ten different classes. The simultaneous spatial variations of sensible heat and momentum fluxes have been computed from the wind and temperature profiles using the Monin-Obukhov similarity theory. The static energy variations are based on the surface meteorological observations. There is very good correlation between NDVI and rainfall rate. Good correlation also exists between: NDVI and relative humidity; NDVI, sensible heat flux and relative humidity; NDVI, momentum flux and emissivity; and NDVI, sensible heat flux and emissivity. The study suggests that the momentum flux has only marginal impact on NDVI. Due to rapid urbanization, the coastal belt is characterized by reduced NDVI compared to the interior areas, suggesting that thermodynamic discontinuities considerably influence the vegetation pattern. This study is useful for the investigation of small-scale circulation models, especially in urban and suburban areas where differential heating leads to the formation of heat islands. In the long run, such studies on a global scale are vital to gain accurate, timely information on the distribution of vegetation on the earth’s surface. This may lead to an understanding of how changes in land cover affect phenomena as diverse as the atmospheric CO² concentrations, the hydrological cycle and the energy balance at the surface-atmosphere interface.     

我国大陆地区和近海海域能量收支分布及其季节变化的数值模拟研究

应用美国宇航局Goddard地球观测系统四维资料同化系统、计算了我国大陆地区和近海海域1998年各月月平均能量收支各项和10m气温、比湿及风矢量的地理分布特征. 模式计算结果表明,地表短波净辐射最强出现在夏季(7月)新疆和西藏中部地区,高值中心区可达275W/m2,在黄海东海海域春季(4月)最大,其值为250W/m2左右. 地表长波净辐射最强出现在夏季(7月)我国西北地区,中心区值为125W/m2,我国近海海域在冬季(1月)最强,其值为75-100W/m2. 我国近海海面,冬季(1月)潜热通量值高于一般月份,中心区值可达250W/m2,夏季我国大陆西南、华北和东北一带为潜热通量高值区,其值为125W/m2. 月平均能量收支计算结果显示,在黄海、东海海域冬季(1月)净通量为海洋向大气输送,夏季(7月)则反之,新疆和西藏高原中部夏季为净通量正值区. 综合温度、湿度和风矢量场分布发现,夏季从南海向华东地区,孟加拉湾向印度次大陆有明显的水汽平流输送,西藏西南部也有来自西南方向的水汽输送.     

利用GRACE时变重力场探测2010年中国西南干旱陆地水储量变化

GRACE(Gravity Recovery And Climate Experiment)卫星计划为监测陆地水储量变化提供了有效技术手段.本文采用2003至2010年共计8年的GRACE月重力场模型反演中国西南区域陆地水储量变化,与GLDAS(Global Land Data Assimilation System)全球水文模型进行对比分析,其结果在时空分布上均符合较好,同时在2009年秋至2010年春该区域陆地水储量均呈现明显减少,与该时段云贵川三省的干旱事件相一致;比较分析了2009年秋至2010年春GRACE反演陆地水储量变化与TRMM(Tropical Rainfall Measuring Mission)合成数据计算的月降雨量的时空分布,两组结果均与西南干旱事件对应时段与区域十分吻合;对近8年的陆地水储量变化与月降雨量数据进行相关性分析,其结果表明陆地水储量变化与降雨量强相关,即降雨量是导致陆地水储量变化的主要因素;分析该区域地表温度变化,结果显示2009年9月至2010年3月地表温度均比历史同期高,地表温度的升高加剧了陆地水储量的减少.     

The role of meteorological forcing and snow model complexity in winter glacier mass balance estimation,Columbia River basin,Canada

Glaciers are commonly located in mountainous terrain subject to highly variable meteorological conditions. High resolution meteorological (HRM) data simulated by atmospheric models can complement meteorological station observations in order to assess changes in glacier energy fluxes and mass balance. We examine the performance of two snow models, SnowModel and Alpine3D, forced by different meteorological data for winter mass balance simulations at four glaciers in the Canadian portion of the Columbia Basin. The Weather Research and Forecasting model (WRF) with resolution of 1 km and the North American Land Data Assimilation System with ~12 km resolution, provide HRM data for the two snow models. Evaluation is based on the ability of the snow models to simulate snow depth at both point locations (automated snow weather stations) and over the entire glacier surface (airborne LiDAR [Light Detection and Ranging] surveys) during the 2015/2016 winter accumulation. When forced with HRM data, both models can reproduce snow depth to within ±15% of observed values. Both models underestimate winter mass balance when forced by HRM data. When driven with WRF data, SnowModel underestimates winter mass balance integrated over the glacier area by 1 and 10%, whilst Alpine3D underestimates winter mass balance by 12 and 22% compared with LiDAR and stake measurements, respectively. The overall results show that SnowModel forced by WRF simulated winter mass balance the best.     

降水条件下的典型干旱区陆面特征模拟验证

利用“我国西北干旱区陆－气相互作用观测试验"在敦煌双墩子戈壁站取得的观测资料及最近的一些研究成果对陆面模式中反照率、相似性函数及地表粗糙度(动量粗糙度,标量粗糙度)3个方面的参数化方案进行了改进,然后对一次典型降水过程的陆面特征及近地层的风、温、湿进行了模拟.结果表明：改进的模式能对降水条件下的干旱区陆面特征进行较好的模拟,其中对辐射、地表温度的模拟相当好,而对能量的模拟虽然还有要改进的地方,但总体结果令人满意;另外改进后的模式对近地层的温度和湿度的模拟也有明显的改善.     

Annual heat balance and equilibrium temperature of Lake Aegeri,Switzerland

The mean heat budget of Lake Aegeri, Switzerland, is 950 MJ·m^–2, comparable to that of neighbouring lakes. The annual variation in the net heat flux can be adequately described using a six-term heat balance equation based on 12 years of monthly mean meteorological and surface temperature data. Although the magnitude of the net heat flux is dominated by the radiative terms of the equation, the one-month backward shift of the net flux and total heat content extrema from the solstices and equinoxes respectively is due to the phase shift of the non-radiative with respect to the radiative terms. A linear approximation was used to express the net heat flux in terms of a heat exchange coefficient and an equilibrium temperature. The former varies from 17 to 28 W·m^–2·K^–1 in the course of a year; fluctuations in the latter are found to depend mainly on fluctuations in cloud cover and relative humidity, whilst the effect of fluctuations in air temperature and wind speed is slight.     

CLM4-LISSS模型对太湖多时间尺度水热通量模拟性能的评估

湖泊模型为数值天气预报模型提供热量通量、水汽通量和动量通量等下边界条件,但是不同时间尺度上湖泊水热通量变化的控制因子不同,因此有必要对湖泊模型进行多时间尺度上的离线评估.本文利用2012-2016年太湖中尺度通量网避风港站的气象资料和辐射数据驱动CLM4-LISSS模型(Community Land Model version 4-Lake,Ice,Snow and Sediment Simulator),并与涡度相关观测(Eddy Covariance,EC)结果进行对比,以年平均潜热通量模拟结果最佳为目标调整了模式中的消光系数、粗糙度长度方案,研究了该模型从半小时到年尺度上对湖表温度和水热通量的模拟性能.结果表明:模型对湖表温度的模拟在各时间尺度上均比较理想,但是模拟的日较差较小;从半小时到年尺度上潜热通量的变化趋势都能被很好地模拟出来,但在季节尺度上,潜热通量的模拟出现了秋冬季偏高、春夏季偏低的情况,季节变化模拟不准确.湖表温度和潜热通量模拟偏差的原因可能是消光系数的参数化方案.相比之下,感热通量尽管年际变化趋势的模拟值与观测值一致,但是从半小时到年尺度均被高估.特别地,冷锋过境期间,模型能较好地模拟出潜热通量和感热通量的变化趋势,但对于高风速条件下的感热通量模拟效果不佳.本文的研究结果能为湖泊模式的应用与发展提供有用信息.     

积雪在El Niño影响东亚夏季气候异常中的作用

本文利用1948-2010年Global Land Data Assimilation System（GLDAS）NOAH陆面模式资料、GPCC月平均降水资料和NCAR/NCEP全球月平均再分析资料,采用滤波、距平合成和线性相关等方法,分析了El Niño成熟位相冬季欧亚大陆积雪异常的分布特征,研究了关键区积雪融化对后期春、夏季土壤湿度、土壤温度以及大气环流与降水的影响,揭示了El Niño事件通过关键区积雪储存其强迫信号并影响东亚夏季气候异常的机制和过程.主要结论如下：El Niño成熟阶段冬季伊朗高原、巴尔喀什湖东北部和青藏高原南麓区域是雪深异常的三个关键区,这些区域的雪深、雪融和土壤湿度有明显的正相关;这三个关键区雪深异常通过春季融雪将冬季El Niño信号传递给春、夏季局地土壤湿度,通过减少感热通量和增加潜热通量对大气环流产生影响;春末夏初伊朗高原土壤湿度异常对东亚夏季气候异常的影响最大,其引起的降水异常与El Niño次年夏季降水异常分布基本一致,春夏季青藏高原南麓和巴尔喀什湖附近土壤湿度也都明显增加,均会对中国华北降水增加有显著正贡献.总之,在利用El Niño事件研究和预测东亚夏季气候异常时,还应考虑关键区雪深异常对El Niño信号的存储和调制作用.     

Diurnal cycle of surface energy fluxes in high mountain terrain: High-resolution fully coupled atmosphere-hydrology modelling and impact of lateral flow

Water and energy fluxes are inextricably interlinked within the interface of the land surface and the atmosphere. In the regional earth system models, the lower boundary parameterization of land surface neglects lateral hydrological processes, which may inadequately depict the surface water and energy fluxes variations, thus affecting the simulated atmospheric system through land-atmosphere feedbacks. Therefore, the main objective of this study is to evaluate the hydrologically enhanced regional climate modelling in order to represent the diurnal cycle of surface energy fluxes in high spatial and temporal resolution. In this study, the Weather Research and Forecasting model (WRF) and coupled WRF Hydrological modelling system (WRF-Hydro) are applied in a high alpine catchment in Northeastern Tibetan Plateau, the headwater area of the Heihe River. By evaluating and intercomparing model results by both models, the role of lateral flow processes on the surface energy fluxes dynamics is investigated. The model evaluations suggest that both WRF and coupled WRF-Hydro reasonably represent the diurnal variations of the near-surface meteorological fields, surface energy fluxes and hourly partitioning of available energy. By incorporating additional lateral flow processes, the coupled WRF-Hydro simulates higher surface soil moisture over the mountainous area, resulting in increased latent heat flux and decreased sensible heat flux of around 20–50 W/m² in their diurnal peak values during summertime, although the net radiation and ground heat fluxes remain almost unchanged. The simulation results show that the diurnal cycle of surface energy fluxes follows the local terrain and vegetation features. This highlights the importance of consideration of lateral flow processes over areas with heterogeneous terrain and land surfaces.     

MYJ和YSU方案对WRF边界层气象要素模拟的影响

研究新一代中尺度气象模式WRF中两种大气边界层方案(MYJ,YSU)对沈阳冬季大气边界层结构模拟的影响,重点分析温度层结、低层风场、边界层高度等对污染物扩散有重要影响的气象要素.和观测数据的比对表明WRF基本能够模拟出温度风速的日变化特征,但模拟风速偏大.YSU方案由于模拟的边界层顶卷挟和边界层内混合作用较强,夜间接地逆温强度低于MYJ方案,逆温维持时间比MYJ方案短4小时,同时模拟边界层高度也高于MYJ方案,有利于污染物垂直扩散.边界层高度的3种计算方法中,湍流动能方法计算的边界层高度最高,Richardson数方法次之,位温方法得到的高度最低.Richardson数方法对临界值的选取较敏感.     

Analysis of satellite‐based and in situ hydro‐climatic data depicts water storage depletion in North China Region

Water storage depletion is an increasing hydrological threat to agricultural production and social stability across the globe. It is fast approaching threshold levels especially in arid/semiarid regions with low precipitation and excessive evapotranspiration (ET). This study analyses water storage dynamics in the North China Region (NCR) – an important grain‐production base in China. It uses monthly Gravity Recovery and Climate Experiment (GRACE), Global Land Data Assimilation System (GLDAS) and field‐measured precipitation data products for 2002–2009. The datasets are analysed in a basin‐scale water balance equation to determine the state of storage in the NCR study area. Based on the validated satellite‐based data products with field‐measured values, average error/bias in the datasets is <10%. The analysis also shows favourable agreements among the GRACE‐derived and flux‐based storage changes at various temporal scales. Whereas the amplitudes and phases of the precipitation and ET fluxes are largely stable for 2002–2009, those of GLDAS runoff and GRACE total water storage anomaly apparently narrow out. The linear trends in the monthly, seasonal and annual storage changes are negative for the study period, suggesting storage loss. There is an apparent seasonality of storage change in the study area; with summer storage gain, winter storage loss and an overall storage loss that is on the average of 16.8 mm/yr. Storage loss is most severe in the central floodplain region (the main irrigated production zone) of the study area. Storage depletion in this important agro‐based semi‐arid region could have negative implications for the millions of people in the region and beyond in terms of water supply, crop production, food security and social stability. Copyright © 2012 John Wiley & Sons, Ltd.     

Improvement of the Noah land surface model for warm season processes: evaluation of water and energy flux simulation

The Noah model is a land surface model of the National Centers for Environmental Prediction. It has been widely used in regional coupled weather and climate models (i.e. Weather Research and Forecasting Model, Eta Mesoscale Model) and global coupled weather and climate models (i.e. National Centers for Environmental Prediction Global Forecast System, Climate Forecast System). Therefore, its continued improvement and development are keys to enhancing our weather and climate forecast ability and water and energy flux simulation accuracy. North American Land Data Assimilation System phase 1 (NLDAS‐1) experiments indicated that the Noah model exhibited substantial bias in latent heat flux, total runoff and land skin temperature during the warm season, and such bias can significantly affect coupled weather and climate models. This paper presents a study to improve the Noah model by adding model parameterization processes such as including seasonal factor on leaf area index and root distribution and selecting optimal model parameters. We compared simulated latent heat flux, mean annual runoff and land skin temperature from the Noah control and test versions with measured latent heat flux, land surface skin temperature, mean annual runoff and satellite‐retrieved land surface skin temperature. The results show that the test version significantly reduces biases in latent heat, total runoff and land skin temperature simulation. The test version has been used for the NLDAS phase 2 (NLDAS‐2) to produce 30‐year water flux, energy flux and state variable products to support the US drought monitor of National Integrated Drought Information System. Copyright © 2012 John Wiley & Sons, Ltd.     

东太湖水温变化与水-沉积物界面热通量初探

水温对沉水植被的生长和分布具有重要作用,水-沉积物界面热通量对浅水湖泊水温变化的影响值得关注.东太湖是我国东部典型的草型浅水湖区,采用自2013年11月至2015年10月对东太湖湖心进行的不同深度水体及沉积物温度高频观测数据,结合东太湖表层沉积物的热力学性质计算了水-沉积物界面热通量,分析了东太湖水温和水-沉积物界面热通量的变化特征并探讨了其影响因素.结果表明：东太湖各深度水体日升温过程随水深增加后延,升温过程夏季延长,冬季缩短;表层水温日变幅最大,底层水温日变幅次之,沉积物温度日变幅最小,各深度温度日变幅夏季最小、冬季最大;春季和夏季升温过程中各深度日均温变化沿水深存在约1天的延迟,秋季和冬季无此现象;2015年与2014年东太湖温度变化趋势相同,同比月均温差与气温差呈线性相关.沉积物8：00-19：00向水体放热增加或从水体吸热减少,19：00至次日8：00放热减少或吸热增加;3-9月从水体吸热,为热汇,10月至次年2月向水体放热,为热源,沉积物全年为湖泊热源;逐日水-沉积物界面热通量每月6至15日存在相对年变幅较小幅度的正弦式波动.水温和水-沉积物界面热通量的变化主要受太阳辐射和气温的影响,二者对气象参数的响应具有迟滞现象;水-沉积物界面热通量与水温呈负相关,其变化相对水温迟滞,水-沉积物界面热交换的主要作用为缓冲湖泊水体的热量变化;夏季,沉水植物能降低湖泊各层水温和垂向水温差.     

YSU边界层参数化方案中不同地形订正方法对地面风速及温度模拟的影响

为了修正中尺度气象模式WRF(Weather Research and Forecasting model)对低层风速模拟的系统性误差,有学者在新版本WRF模式的YSU(Yonsei University)边界层参数化方案中加入了两个地形订正方法:Jiménez方法和UW(University of Washington method)方法.本文利用这两个地形订正方法,选取了两个时间段,对北京地区的地面气象要素以及气象要素垂直廓线进行了个例模拟研究,模拟结果和观测数据的比对表明在北京地区:是否采用地形订正,对地面温度的模拟几乎没有影响;采用地形订正后,模式对地面风速的模拟有明显的改进,两种方法对风速模拟的差别主要体现在山/丘陵地区;Jiménez方法在山/丘陵地区的模拟风速明显偏大,而采用UW方法进行订正后,模拟的风速减小,更接近观测值;两种方法在山谷地区对风速均有一定的过度订正.通过分析气象要素的垂直廓线发现,不同地形订正方法主要影响的是2000m以下的低层风速.总体而言,UW地形订正方法在北京地区更为适用,采用UW方法后,模拟得到的地面气象要素的各项统计参数基本达到了统计基准值.     

Vertical groundwater flux estimation from borehole temperature profiles by a numerical model,RFLUX

We developed a numerical model, RFLUX, which uses the heat tracer method for vertical groundwater flux estimation, and applied it to the Leizhou Peninsula, South China, to provide information to inform local groundwater resource utilization and management. The temperature–depth (TD) profiles of 24 boreholes, along with the observed ground surface temperature (GST) and surface air temperature (SAT) series in recent decades, were collected in this area. Underground TD data demonstrated the capacity to identify groundwater flow patterns, and local GST and SAT data demonstrated a strong correlation with each other over monthly, seasonal, and annual scales. In the RFLUX model, the average GST and SAT series were applied as an upper boundary condition, and a nonlinear initial condition was set using an analytical solution from the literature. The model results of selected TD profiles demonstrated that the annual vertical groundwater flux was about 0.15 m a^?1, which tended to be overestimated if a linear initial condition was used. This model can be easily applied with minor modifications, considering its clear purpose and simplicity.     

Decadal variability of the Arctic Ocean thermal structure

Long-term variability of heat content (HC) in the upper 1,000 m of the Arctic Ocean is investigated using surface and subsurface temperature and current data during 1958–2005 compiled by Simple Ocean Data Assimilation. Annual cycle of the Arctic Ocean HC is controlled primarily by the negative and positive excursions in net upper ocean heat flux, while the inter-annual variability is mainly associated with meridional thermal advection from the North Atlantic Ocean. Variability in HC is experienced as a basin-wide cooling/warming in association with the Arctic Oscillation on a decadal time scale. In the first three dominant modes of Empirical Orthogonal Function, the maximum amplitude of HC variability occurs in the Greenland–Norwegian Sea and Eurasian Basin. In general, HC showed increasing trend during 1958–2005 indicating continuous warming with regional variations in magnitude.     

A Study of Fog Characteristics Using a Coupled WRF–COBEL Model Over Thessaloniki Airport, Greece

An attempt is made to couple the one dimensional COBEL-ISBA (Code de Brouillard à l’échelle Locale-Interactions Soil Biosphere Atmosphere) model with the WRF (Weather Research and Forecasting)–ARW (Advanced Research WRF) numerical weather prediction model to study a fog event that formed on 20 January 2008 over Thessaloniki Airport, Greece. It is the first time that the coupling of COBEL and WRF models is achieved and applied to a fog event over an airport. At first, the performance of the integrated WRF–COBEL system is investigated, by validating it against the available surface observations. The temperature and humidity vertical profiles were used for initializing the model. The performance of WRF–COBEL is considered successful, since it realistically simulated the fog onset and dissipation better than the WRF alone. The COBEL’s sensitivity to initial conditions such as temperature and specific humidity perturbations was also tested. It is found that a small increase of temperature (~1°C) counteracts fog development and results in less fog density. On the other hand, a small decrease of temperature results in much denser fog formation. It is concluded that the integrated model approach for aviation applications can be useful to study fog impact on local traffic and aviation.     

Distributed modeling of monthly air temperatures over the rugged terrain of the Yellow River Basin

Our analyses of the monthly mean air temperature of meteorological stations show that altitude, global solar radiation and surface effective radiation have a significant impact on air temperature. We set up a physically-based empirical model for monthly air temperature simulation. Combined the proposed model with the distributed modeling results of global solar radiation and routine meteorological observation data, we also developed a method for the distributed simulation of monthly air temperatures over rugged terrain. Spatial distribution maps are generated at a resolution of 1 km×1 km for the monthly mean, the monthly mean maximum and the monthly mean minimum air temperatures for the Yellow River Basin. Analysis shows that the simulation results reflect to a considerable extent the macro and local distribution characteristics of air temperature. Cross-validation shows that the proposed model displays good stability with mean absolute bias errors of 0.19°C–0.35°C. Tests carried out on local meteorological station data and case year data show that the model has good spatial and temporal simulation capacity. The proposed model solely uses routine meteorological data and can be applied easily to other regions. Supported by China Meteorological Administration key Project on New Technique Diffusion (Grant No. CMATG2006Z10) and Jiangsu Key Laboratory of Meteorological Disasters (Grant No. KLME050102)     

Evaluation of the temporal variations of groundwater storage and its interactions with climatic variables using GRACE data and hydrological models: A study from Turkey

Monitoring of the fluctuations of groundwater storage is particularly important in arid and semi-arid regions where water scarcity brings about various challenges. Remote sensing data and techniques play a preponderant role in developing solutions to environmental problems. The launch of Gravity Recovery and Climate Experiment (GRACE) satellites has eased the remote monitoring and evaluation of groundwater resources with an unprecedented precision over large scales. Within the scope of the current study, the latest release (RL06) of GRACE mass concentrations (Mascons) from Jet Propulsion Laboratory (JPL) dataset as well as Global Land Data Assimilation System (GLDAS) models of Noah and Catchment Land Surface Model (CLSM) were used to provide Groundwater Storage Anomalies (GWSA) over Turkey. The temporal interactions of the estimated GWSA with the climatic variables of precipitation and temperature (derived from the reanalysis datasets of CHELSA [Climatologies at High resolution for the Earth's Land Surface Areas] and FLDAS [the Famine Early Warning Systems Network Land Data Assimilation System], respectively) were investigated statistically. The results suggest that there is a descending trend (from 2003 to 2016) for Terrestrial Water Storage Anomalies (TWSA) and GWSA over Turkey with a total loss of 11 and 6 cm of water, respectively. The statistical analysis results also indicate that the monthly variations of GWSA over Turkey are highly correlated with precipitation and temperature at 2-month lag. The analysis of the climatology (long-term) values of monthly GWSA, precipitation and temperature also revealed high agreement between the variables.