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Received：01 February 2025，
Published：07 January 2026
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明晰湖泊与邻近陆地之间云量差异的时空格局、影响因素及其物理过程是揭示湖陆辐射差异以及论证使用陆地观测数据驱动湖泊模型适用性的基础。本文基于2019年—2023年Sentinel-5P云量数据，结合ERA5和ERA5-Land再分析数据，分析了中国334个湖泊及其邻近陆地的云量差异（
∆
CF）在夏秋两季的时空格局、影响因素及物理过程。结果表明：（1）5个湖区在夏秋两季均呈现湖泊云量小于邻近陆地的特征（
∆
CF＜0），以青藏高原湖区和蒙新湖区最明显。（2）
∆
CF与湖泊面积呈显著的负相关关系，以东北平原—山地湖区最显著（
R
=-0.95，
P
＜0.01）。除青藏高原湖区外，其他湖区
∆
CF与湖泊平均深度的负相关关系不显著。（3）湖风发生时湖面下沉气流抑制云的形成，进而放大了湖陆云量差异，以色林错最为明显，且在湖面辐散、邻近陆地辐合的流场配置下湖泊较邻近陆地云量更低。以上结果表明，忽略湖陆之间的云量差异，仅使用陆地辐射观测数据驱动湖泊模型将会低估湖面温度和蒸发速率，这一偏差在青藏高原湖区湖风期更为明显。
Investigating the spatial-temporal patterns of lake-land cloud fraction difference (
Δ
CF)
as well as identifying its influencing factors and underlying physical processes
is pivotal for quantifying lake-land radiation discrepancies and evaluating the applicability of land-based observations in driving lake numerical m
odels. This paper analyzed the spatiotemporal patterns of
Δ
CF between 334 lakes and their surrounding lands across five lake zones in summer and autumn using Sentinel-5P cloud fraction products from 2019 to 2023. The influencing factors of
Δ
CF
and underlying physical processes were explored utilizing ERA5 and ERA5-land reanalysis datasets. The results indicate the following: (1) All five lake regions exhibit lower cloud fraction over lakes than over adjacent land areas (
Δ
CF
<
0) during both summer and autumn
with the most pronounced differences in the Tibetan Plateau Lake (TPL) Zone. For example
summer cloud fraction over Qinghai Lake and Nam Co was 8.79% and 7.47% lower respectively
than over adjacent land areas. (2) Lake area is the primary morphological factor influencing lake–land cloud fraction differences
showing significant negative correlations with
Δ
CF across all five lake regions. This correlation was most pronounced in Northeast Plain and Mountain Lake Zone (
R
= -0.95
p
<
0.01). While predominantly controlled by lake area
Δ
CF also shows a significant negative correlation with lake volume. Except in the TPL region
Δ
CF in the other lake regions showed no significant correlation with average lake depth. (3) During lake breeze events
subsidence over the lake surface suppresses cloud formation
thereby amplifying the lake-land cloud fraction difference. During the summer lake breeze period
Δ
CF at Selin Co
Hulun Lake
and Lake Taihu decreased significantly compared with the non-lake-breeze period
with Selin Co showing the most pronounced effect (lake-breeze period
Δ
CF = -6.04%; non-lake-breeze period
Δ
CF = +2.54%). Under favorable large-scale circulation conditions
both flow-field configurations suppress cloud formation over lakes:Configuration 1: low-level divergence over the lake surface and upper-level d
ivergence; Configuration 2: divergence over the lake surface and convergence over adjacent land. The difference in
Δ
CF is more pronounced under Configuration 2 than Configuration 1. Specifically
Δ
CF values for Xingkai Lake (-25.93%) and Selin Co (-14.03%) were 9.09% and 9.76% lower
respectively
than under Configuration 1. These results indicate that neglecting the lake–land cloud fraction difference and directly driving lake models by using land-based radiation observations may underestimate lake surface temperature and evaporation rate. The underestimation would be more pronounced in TPL during lake breeze periods. Future efforts should address this issue by enhancing observations and improving the model.
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