may be due to the lower released amount, and to lower dry deposition
velocities (0.1 cm s1 instead of 0.2 cm s1 in our simulations).
For gaseous 131I, Morino et al. (2011) took 0.5 cm s1
(0.7 cm s1 in our case). Estimates of total iodine dry deposition are
comparable. Wet deposition values are more difficult to compare,
without knowledge of the parameterization used. In our case,
scavenging is the same for all species. In Morino et al. (2011), the
wet deposition scheme seems more efficient for 137Cs, which is in
particulate form, than for 131I, which is mostly gaseous. It probably
explains the higher proportion of 137Cs deposed over land (12% of
their release).
Total deposition values are very close to each other. Compensation
between dry and wet deposition partly explains this agreement.
Based on airborne monitoring data5
, the total quantity of
137Cs within 80 km of the plant over land was estimated to be about
1.49 PBq, with an uncertainty of 0.49 PBq (Gonze, M-A, personal
communication). Both simulations are within this range.
3.2.3. Comparisons to deposition measurements
Fig. 8 shows the comparison between the simulation and
the observations of 137Cs deposition provided by Ministry of
Education, Culture, Sports, Science and Technology (MEXT).6
About 1800 measurements are within our simulation domain.
The overall shape of the northwestern contamination (over
105 Bq m2
) is correct, but the highest values are located too
north compared to the observations. This is probably due to the
use of wind observations at FNPP1 at that time, not representative
of the wind direction at a larger scale. Thus, the model
overestimates deposition north along the coast by more than
a factor five (yellow to red points, Fig. 8(c)). The overestimation
south, after 40 km, is consistent with gamma dose rates at Iwaki.
Fig. 8(d) shows that the agreement is better between 20 and
60 km from the source. Closer to the source, the model tends to
overestimate deposition. Between 60 and 80 km, values are
underestimated, especially in the northern area (gray and purple
points, Fig. 8(c)). In all, 31% of simulated values are within a factor
2 of the observations, 73% within a factor 5, and 90% within
a factor 10. The correlation coefficient is 0.34. The figure of merit
in space (FMS) depends on the chosen threshold. A high
threshold would focus on the model’s ability to forecast extreme
values. For 104 Bq m2 (94% of measurements), the FMS is very
good (0.85). For 105 Bq m2 (30% of measurements, mainly
northwest), it goes down to 0.43, probably because of the misplaced
wet deposition zone.
Very close measurement points may differ by a factor 5e10,
which may be due to running water or changes in terrain type
(school yard, agricultural field.). The simulation gives averaged
values, and does not account for local-scale variability. Thus, further
analyses of the datasets and agg
may be due to the lower released amount, and to lower dry deposition
velocities (0.1 cm s1 instead of 0.2 cm s1 in our simulations).
For gaseous 131I, Morino et al. (2011) took 0.5 cm s1
(0.7 cm s1 in our case). Estimates of total iodine dry deposition are
comparable. Wet deposition values are more difficult to compare,
without knowledge of the parameterization used. In our case,
scavenging is the same for all species. In Morino et al. (2011), the
wet deposition scheme seems more efficient for 137Cs, which is in
particulate form, than for 131I, which is mostly gaseous. It probably
explains the higher proportion of 137Cs deposed over land (12% of
their release).
Total deposition values are very close to each other. Compensation
between dry and wet deposition partly explains this agreement.
Based on airborne monitoring data5
, the total quantity of
137Cs within 80 km of the plant over land was estimated to be about
1.49 PBq, with an uncertainty of 0.49 PBq (Gonze, M-A, personal
communication). Both simulations are within this range.
3.2.3. Comparisons to deposition measurements
Fig. 8 shows the comparison between the simulation and
the observations of 137Cs deposition provided by Ministry of
Education, Culture, Sports, Science and Technology (MEXT).6
About 1800 measurements are within our simulation domain.
The overall shape of the northwestern contamination (over
105 Bq m2
) is correct, but the highest values are located too
north compared to the observations. This is probably due to the
use of wind observations at FNPP1 at that time, not representative
of the wind direction at a larger scale. Thus, the model
overestimates deposition north along the coast by more than
a factor five (yellow to red points, Fig. 8(c)). The overestimation
south, after 40 km, is consistent with gamma dose rates at Iwaki.
Fig. 8(d) shows that the agreement is better between 20 and
60 km from the source. Closer to the source, the model tends to
overestimate deposition. Between 60 and 80 km, values are
underestimated, especially in the northern area (gray and purple
points, Fig. 8(c)). In all, 31% of simulated values are within a factor
2 of the observations, 73% within a factor 5, and 90% within
a factor 10. The correlation coefficient is 0.34. The figure of merit
in space (FMS) depends on the chosen threshold. A high
threshold would focus on the model’s ability to forecast extreme
values. For 104 Bq m2 (94% of measurements), the FMS is very
good (0.85). For 105 Bq m2 (30% of measurements, mainly
northwest), it goes down to 0.43, probably because of the misplaced
wet deposition zone.
Very close measurement points may differ by a factor 5e10,
which may be due to running water or changes in terrain type
(school yard, agricultural field.). The simulation gives averaged
values, and does not account for local-scale variability. Thus, further
analyses of the datasets and agg
การแปล กรุณารอสักครู่..
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อาจจะเนื่องจากการลดปล่อยเงิน และลดความเร็วในการตกสะสม
บริการ ( 0.1 ซม. เป็น 1 แทน 0.2 ซม. เป็น 1 ใน จำลองของเรา )
ให้ 131I ก๊าซ โมริโนะ et al . ( 2011 ) 0.5 ซม. เป็น 1
( 0.7 ซม. เป็น 1 ในกรณีของเรา ) ประมาณการของไอโอดีนทั้งหมดแห้งทับถมอยู่
เทียบเคียง การตกสะสมเปียกค่ามีมากขึ้นยากที่จะเปรียบเทียบ
โดยปราศจากความรู้ของ parameterization ใช้ . ในกรณีของเรา
scavenging is the same for all species. In Morino et al. (2011), the
wet deposition scheme seems more efficient for 137Cs, which is in
particulate form, than for 131I, which is mostly gaseous. It probably
explains the higher proportion of 137Cs deposed over land (12% of
their release).
Total deposition values are very close to each other. Compensation
ระหว่างแห้งและเปียกสะสมบางส่วนอธิบายข้อตกลงนี้ ขึ้นอยู่กับการตรวจสอบ data5 อากาศ
, ปริมาณรวมของ
137cs ภายใน 80 กิโลเมตรของโรงงานที่ดินประมาณ
1.49 pbq ที่มีความไม่แน่นอนของ 0.49 pbq ( gonze m-a การสื่อสารส่วนบุคคล , ,
) ทั้งแบบภายในช่วงนี้
3.2.3 . การเปรียบเทียบการสะสมวัด
ฟิค 8 shows the comparison between the simulation and
the observations of 137Cs deposition provided by Ministry of
Education, Culture, Sports, Science and Technology (MEXT).6
About 1800 measurements are within our simulation domain.
The overall shape of the northwestern contamination (over
105 Bq m2
) is correct, but the highest values are located too
north compared to the observations.นี้อาจจะเนื่องจาก
ใช้ลมสังเกตที่ fnpp1 ตอนนั้น ไม่ใช่ตัวแทน
ของทิศทางลมในขนาดใหญ่ ดังนั้นรูปแบบ
overestimates สะสมเหนือแนวชายฝั่งมากกว่า
ปัจจัยห้า ( สีเหลืองจุดแดง ภาพที่ 8 ( C ) ส่วนการประเมินมากเกินไป
ใต้ หลังจาก 40 กิโลเมตร สอดคล้องกับอัตราปริมาณรังสีที่ อิวากิ
ฟิค 8(d) shows that the agreement is better between 20 and
60 km from the source. Closer to the source, the model tends to
overestimate deposition. Between 60 and 80 km, values are
underestimated, especially in the northern area (gray and purple
points, Fig. 8(c)). In all, 31% of simulated values are within a factor
2 of the observations, 73% within a factor 5, and 90% within
a factor 10.สัมประสิทธิ์สหสัมพันธ์เท่ากับ 0.34 . รูปทำบุญ
ในอวกาศ ( FMS ) ขึ้นอยู่กับเกณฑ์ที่เลือก เกณฑ์สูง
จะมุ่งเน้นในรูปแบบของความสามารถในการคาดการณ์ค่าสุดขีด
สำหรับ 104 ( M 2 ( 94% ของการวัด ) , FMS มาก
( 0.85 ) 105 ( M 2 ( 30% ของการวัดส่วนใหญ่
ตะวันตกเฉียงเหนือ ) ลงไปถึง 0.43 , อาจเป็นเพราะถูกใส่ผิดที่
แบบเปียก โซนVery close measurement points may differ by a factor 5e10,
which may be due to running water or changes in terrain type
(school yard, agricultural field.). The simulation gives averaged
values, and does not account for local-scale variability. Thus, further
analyses of the datasets and agg
การแปล กรุณารอสักครู่..
